NATIONAL OPTICAL ASTRONOMY OBSERVATORY

NSF Research Experiences for Undergraduates Site Program in Astronomy at

Kitt Peak National Observatory (KPNO)

Annual Project Report 2011 (AST 0754223)

Submitted to

Robert Scott Fisher, Ph.D.

NSF, Program Director for Education and Special Programs David Silva, Principal Investigator

November 3, 2011

TABLE OF CONTENTS

Annual Report 2011 REU Site Program at KPNO i

NSF RESEARCH EXPERIENCES FOR UNDERGRADUATES (REU) Site Program in Astronomy at the Kitt Peak National Observatory

D. Silva, Principal Investigator K. Mighell, Site Director & Co-Principal Investigator

Annual Report for the 2011 REU Program at KPNO

Project Summary ...................................................................................................................................... 1 Program Activities and Participants ........................................................................................................ 2 Final Research Reports ............................................................................................................................ 6 Publications ……………...................................................................................................................... 75

PROGRAM ACTIVITIES

Annual Report 2011 REU Site Program at KPNO 2

The National Science Foundation Research Experiences for Undergraduates (REU) program is designed to encourage US college and university students to pursue careers in science and engineering. REU site programs make it possible for undergraduates to take part in independent research activities with professional scientists at major research institutions, usually during the summer months. Every year since 1990, NSF has awarded funding to the National Optical Astronomy Observatory (NOAO) to support an REU site program in astronomy at Kitt Peak National Observatory (KPNO).

Six undergraduates were hired as full-time employees at NOAO in Tucson for a period of ten to twelve weeks, beginning May 23, 2011, with $87,848 allocated to the 2011 KPNO REU program. The students spent the major portion of the program working as research assistants with designated members of the NOAO-North scientific staff (REU "mentors") on independent, supervised research projects. In the past, former KPNO REU participants have noted that the chance to attend and participate at a major meeting of the American Astronomical Society (AAS) is one of the most exciting aspects of our REU program. All six of our KPNO REU 2011 participants will be attending the upcoming 219th AAS meeting which will be held at Austin, Texas, Washington on January 8 –12, 2012. While at the AAS meeting, these students will be presenting posters – all as the presenting author. Of our six participants last year, four were women and two were men; one of the men was a Hispanic American. The KPNO REU Site Director for the 2011 program was Kenneth Mighell. In addition to work on their particular research projects, the REU students attended weekly science seminars and lectures by members of the NOAO scientific staff, gave periodic oral reports on the progress of their research to NOAO and visiting scientists, visited and toured nearby observatories and research facilities, and planned and executed observing programs using the world-class optical/infrared telescopes on Kitt Peak. Along with the students of the concurrent REU program at the National Solar Observatory (NSO) in Tucson, the KPNO students also traveled to Sunspot, New Mexico, on a five-day field trip to visit the NSO facilities at Sacramento Peak, the Sloan Digital Sky Survey Telescope at Apache Point, and the National Radio Astronomy Observatory's Very Large Array. At the end of the summer program, the KPNO REU students were required to write up the results of their research work as concise scientific papers. The student papers are presented in this Annual Report under the section Final Research Reports. All six of the KPNO REU 2010 participants presented posters at the 217th AAS meeting which was held at Seattle, Washington on January 9 – 13, 2011; their poster abstracts are reproduced below under the heading Publications and were published in the Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011. Funding Acknowledgement The NOAO/KPNO Research Experiences for Undergraduates (REU) Program is funded by the National Science Foundation (NSF) Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.

PROGRAM ACTIVITIES

Annual Report 2011 REU Site Program at KPNO 3

Recruitment Last year, we had a total of 118 complete and 25 incomplete applicants to our program. From the 118 qualified applicants, six undergraduate students (four women and two men, 1 Hispanic man) were selected to participate in the 2011 REU site program at KPNO. About four months before the application deadline, NOAO began recruitment for the program via on the KPNO REU web site (http://www.noao.edu/kpno/reu/), and by posters and letters sent to colleges and universities across the U.S. and Puerto Rico. In October 2010, approximately 900 posters and letters were mailed to US college and university Science Department chairs and undergraduate advisors (principally in physics, astronomy, math, computer science, and engineering programs); as well as to campus job placement and career counseling offices. Our 118 applicants applied from 33 states and attended 93 schools; 44.9% of applicants were women (53 out of 118) and 55.1% were men. Of the 112 qualified applicants who gave information about their race, we had 1 who classified himself as African-American (0.9%), 8 as Hispanic (7.1%), 3 as Mixed/Other (2.7%), 4 as Asian (3.6%), and 96 as Caucasian (85.7%). Of the 118 qualified applicants aboutt where they heard about the KPNO REU program, 4 said from previous REU students (3.4%), 22 said their advisor (18.6%), 17 said college or department staff member (14.4%), 11 said the REU poster on a bulletin board (9.3%), 55 said the KPNO REU Web site (46.6%), 1 learned of the program from a placement office (0.9%), and 8 said "other" (6.8%). Participants Each of the students selected for the program was matched with an NOAO-North scientific staff member to work on a research project previously proposed by them and evaluated by the REU Site Director. In general, the scientific projects most likely to be approved for the program are those that provide the greatest opportunity for the REU assistant to make substantial progress over the course of the summer, as well as those likely to result in an eventual scientific publication in which the student is a collaborator. Particular research topics are assigned to particular students in consideration of the student's background and avowed scientific interests (as expressed in the student's application).

The six REU students, their college/university affiliations, and the NOAO-North scientists designated as their research advisors for the program are listed as follows:

REU Participant College/University NOAO Research Advisor(s) Vivienne Badassare Hunter College J. Kartaltepe

Alisa Fersch Wesleyan University C. Walker Nicholas Jimenez Alfred University K. Mighell Morgan Rehnberg Beloit College M. Trueblood & K. Mighell Joanna Taylor Indiana University D. Norman Christine Welling Dickinson College S. Pompea

Left to right: Vivienne Baldassare, Alisa Fersch, Nicholas Jimenez, Christine Welling, Morgan Rehnberg, and Joanna Taylor.

PROGRAM ACTIVITIES

Annual Report 2011 REU Site Program at KPNO 4

Research Projects The summer 2010 REU students at NOAO-North spent an average of 11.0 weeks working as full-time research assistants on projects ranging from a study of star formation and AGN activity in ultraluminous infrared galaxies, light pollution around Tucson, and an analysis of known variable stars in the Kepler Field. In addition to work on their individual projects, the students used the KPNO 2.1-m during 14 nights of observing on July 11 – 31, 2011 (an average of 5 observing nights per student; 2 or 3 nights with the FLAMINGOS IR Imaging Spectrogram (FLMN) and 3 or 2 nights with the GoldCam CCD Spectrograph (GCAM). This observational experience is an essential feature of the NOAO/KPNO REU program, allowing each of the students to experience first hand the process of designing and carrying out an original observations at the Kitt Peak National Observatory.

Towards the end of the program, REU students are required to share their research findings with the NOAO astronomical community through oral presentations and written reports. For many of the students, this was their first experience presenting research results in a professional scientific setting. The titles of the students' research topics, presentations, and written reports are listed below. The original written reports are presented in the following section.

• Vivienne Baldassare: Studying Star Formation and AGN Activity in Ultraluminous Infrared Galaxies at z > 1.15

• Alisa Fersch: Light Pollution around Tucson, AZ and its E_ect on the Spatial Distribution of Lesser Long-Nosed Bats

• Nicholas Jimenez: An Analysis of Known Variable Stars in the Kepler Field

• Morgan Rehnberg: PhAst: A Flexible IDL Astronomical Image Viewer

• Joanna Taylor: X-ray Selected AGN in A Merging Cluster

• Christine Welling: Alternative Mounting Systems for the Galileoscope

Scientific Lectures and Field Trips

In addition to the research project, two popular components of the NOAO/KPNO REU program are the weekly science lectures given by NOAO staff and the field trips to nearby observatories and non-NOAO facilities. The lectures and field trips are designed to introduce the REU students to a broad array of current scientific topics -- including instrumentation issues -- in O/IR ground-based, stellar astronomy and solar astronomy. The NOAO/KPNO and NSO REU students visited the National Solar Observatory facilities at Sacramento Peak, New Mexico, during July 3 - 7, 2011; they were given a custom tour of NRAO's Very Large Array by Rick Perley (EVLA Project Scientist) and they also toured the Sloan Digital Sky Survey Telescope at the Apache Point Observatory. On July 12, the KPNO and NSO REU students toured the University of Arizona's Mirror Lab. The NOAO/NSO REU lectures at NOAO-North are informal which allows the students to interact and network with scientists working in many different areas of ground-based astronomy, solar astronomy, and instrumentation. The topics of the 2011 NOAO/NSO REU lecture series (June 2 - July 12, 2010) are listed on the next page.

PROGRAM ACTIVITIES

Annual Report 2011 REU Site Program at KPNO 5

• Dave Silva (NOAO Director): "Welcome to the National Optical Astronomy Observatory"

• Frank Hill (NSO): "Introduction to Helioseismology"

• Simon Schuler (NOAO): "A Primer on Exoplanetary Systems and the Chemical Abundances

of the Host Stars”

• Matt Penn (NSO): Measuring Solar Magnetic Fields and Why the Sunspot Cycle May End”

• Jill Bechtold (University of Arizona): "The Astrophysics Graduate School Admission Process"

• Steve Pompea (NOAO): "Education and Public Outreach Activities at NOAO and the

Galileoscope Project”

• Steve Keil (NSO Director): "The Advanced Technology Solar Telescope"

• Han Uitenbroek (NSO): “Solar Spectral Lines”

• Steve Ridgeway (NOAO): “Introduction to Interferometry”

Left to right: Nick Jimenez (KPNO REU), Jennifer Takaki (NSO Akami), Brittany Johnstone (NSO REU), Morgan Rehnberg (KPNO REU), James Linden (NSO Akami), Philip Adams (NSO REU), Vivenne Baldassare (KPNO REU), Joanna Taylor (KPNO REU), Christine Welling (KPNO REU), Alisa Fersch (KPNO REU), and Catherine Love (NSO RET).

Studying Star Formation and AGN Activity inUltraluminous Infrared Galaxies at z ą 1.15

Vivienne BaldassareKPNO REU 2011 and Hunter College

Advisor: Dr. Jeyhan Kartaltepe (NOAO)

Abstract

We studied active galactic nucleus (AGN) activity and star formation in a sample of52 luminous and ultraluminous infrared galaxies ((U)LIRGs) with 1.17 ă z ă 1.602 andLIR ą 1011.5 L@. Studies done in the local universe have revealed that all local ULIRGsare mergers, and have proposed evolutionary schemes in which early merger stagesare dominated by starbursts, intermediate merger stages are dominated by starburst-AGN composite objects, and late merger stages are dominated by AGN. We utilizethe [NII]/Hα and [OIII]/Hβ line ratios to plot our objects on a BPT diagram whichclassifies them as star forming, composite, or AGN, and then use NIR spectroscopy tostudy whether the trends present in the local universe extend to high redshift. We findthat many of the objects in our sample show evidence of mergers or interaction, andthat all objects with LIR ą 1012.5 L@ are AGN or composite objects.

1 Introduction

Infrared galaxies are objects that emit more energy in the infrared than at all other wave-lengths combined (Sanders & Mirabel 1996). Ultraluminous infrared galaxies (ULIRGs) areinfrared galaxies that have infrared luminosities greater than 1012 L@. ULIRGs are verydusty, and they get their extreme infrared luminosities due to the heating of dust by activegalactic nuclei (AGN) or starbursts. All local ULIRGs are strongly interacting or mergingsystems. In addition, locally, most local ULIRGs with LIR above 1012.4 - 1012.5L@ appearto be AGN (Tran et al. 2001), suggesting it might be necessary to have an AGN to reachthe most extreme luminosities.

An AGN is an energetic central region of a galaxy thought to get its excessive energyfrom an active, supermassive black hole. One piece of evidence for an AGN is the presenceof broad emission lines. These lines are interpreted as being Doppler broadened due to highvelocities of gas surrounding the central black hole.

It is likely that interactions and mergers of gas-rich spirals produce ULIRGs. There is astrong correlation between LIR and merger fractions (Kartaltepe et al 2010). Most luminous

infrared galaxies at LIR ă 1011 L@ appear to be lone galaxies undergoing periods of starformation. At LIR ą 1012 L@, all are undergoing mergers and are gas rich. Because of largeamounts of dust present, it is difficult to ascertain the precise contributions of star formationand AGN activity to the overall infrared luminosity.

One way of distinguishing between star forming galaxies and galaxies with AGN is to usea BPT diagram (Baldwin, Phillips, & Terlevich 1981). A BPT diagram uses line ratios toseparate out objects of different classes. We use the [OIII]/Hβ ratio vs. the [NII]/Hα ratio toseparate our objects into star forming, AGN, or composite following the classification schemeof Kewley et al (2006). (In this paper, [NII] is always taken to mean [NII] 6584). These ratiosare useful because [NII] and [OIII] are very high ionization lines; these transitions requirea lot of energy. The most energetic objects, AGN, will produce the highest [OIII]/Hβ and[NII]/Hα ratios. Another advantage to using these ratios is that [NII] and Hα are very closeto one another, as are [OIII] and Hβ. This makes this diagnostic almost independent of anyreddening.

Recent studies done in the local universe have shown that all local ULIRGs are mergers,and that merger progress correlates with object type. Yuan et al. (2010) found that star-bursts tend to occur in the earliest stages of mergers, with intermediate-stage mergers beingdominated by starburst-AGN composite objects, and late merger stages being dominated bypure AGN. At late merger stages, the fraction of Seyfert objects increases; this correspondsto the highest LIR bin in their sample. Their interpretations include: (1) dust obscuring theAGN is cleared and the AGN can ionize surrounding gas, (2) starburst activity subsides,and (3) AGN activity increases. We decided to explore similar trends between object type,infrared luminosity, and morphology at high redshift to see if they agreed with the corre-lations that exist in the local universe by classifying our objects using a BPT diagram andanalyzing the results.

2 Data, Sample Selection, Methods

2.1 Data

We began with 2,600 objects with spectral data taken by FMOS on the Subaru telescopeon Mauna Kea. These objects are from the COSMOS and CDFS surveys. COSMOS1, orthe Cosmological Evolution Survey (Scoville et al. 2007), covers a 2-square degree field withimaging by space-based telescopes including Hubble, Spitzer, GALEX, XMM, and Chandra,and many large ground based telescopes such as Subaru, VLA, ESO-VLT, UKIRT, NOAO,and CFHT. The survey has detected over 2 million galaxies and spans 75% of the age ofthe universe. CDFS2, or the Chandra Deep Field South Survey, is another survey withmultiwavelength data.. CDFS has the deepest x-ray data of any survey field, and covers0.11-square degrees of sky. The targets observed for these two surveys were x-ray sources

1http://cosmos.astro.caltech.edu/2http://www2.astro.psu.edu/ niel/cdfs/cdfs-chandra.html

Figure 1: Our sample broken down by infrared luminosity

and infrared galaxies, among other selections, making our final sample not representative ofall ULIRGs.

2.2 Sample Selection

After finding redshifts for all objects possible, we made a quality cut in our sample. Wedecided to keep objects with a spectroscopic redshift confidence rating of 3 or 4 (with 4being the most confident and 1 being the least confident) and objects with a confidencerating of 2 that had good agreement with their photometric redshifts.

We next matched these objects with Spitzer 24µm sources, and kept all objects within1.5 arcsec of a 24µm source. This was to ensure that the objects were bright in the infrared.This left us with 158 objects in the sample. Finally, we selected all objects that had redshiftsin such a range that their spectra would contain Hβ, [OIII], Hα, and [NII]. We needed allthese lines in order to plot our objects on a log([OIII]/Hβ) vs. log([NII]/Hα) BPT diagram.After removing any duplicate objects, we were left with a sample of 52 objects with 1.17 ă

z ă 1.602.

2.3 Methods

First, we measured spectroscopic redshifts for all objects from COSMOS and CDFS withFMOS spectroscopy. This was done with a program called SpecPro 3. SpecPro overlays atemplate spectrum on the spectrum of the target so that one can match up emission lines in

3http://specpro.caltech.edu/

Figure 2: Our sample broken down by spectroscopic redshift

order to find the redshift. Finding the spectroscopic redshifts proved to be difficult for manyof the objects, as infrared spectra can be noisy and have many sky lines, and some objectshad very faint signals. Next, we measured the emission line fluxes. We experimented withan IDL program designed to fit emission lines and measure fluxes, but it proved difficultto obtain proper fits for the lines. It was especially difficult for the program to deblendHα and [NII], and there were many cases where it was difficult or impossible to distinguishbetween Hα and [NII]. In the end, we used the splot task in IRAF for the emission line fluxmeasurements. Deblending [NII] and Hα proved to be easier in IRAF, because splot has adeblending task. For some objects, Hβ or [OIII] were too weak to be observed. In thesecases, we estimated the upper limit for the unobserved line. After obtaining all the necessaryemission line flux measurements, we were able to plot the objects on a BPT diagram.

3 Results

3.1 BPT Diagram

The 52 objects in our sample are plotted on a BPT diagram in Figure 3. They are dividedby infrared luminosity bins so that we can better examine trends between object type andinfrared luminosity. The plot also indicates whether an object is a broad line AGN and/oran x-ray detected AGN. We find that all objects with LIR ą 1012.5 L@ are either AGN orcomposite (One object of LIR ą 1013 L@ does fall in the star forming section of the diagram,but its error bars can place it within the composite region. In addition, it has broad lines

Figure 3: Our sample plotted on a BPT diagram. The sample is broken down into four LIR

bins. Arrows indicate that the plot point is an upper or lower limit for an object, and thatthe object could move in the direction of the arrow on the diagram. From this diagram, wecan see that the most luminous objects all contain AGN.

and is x-ray detected, indicating it certainly has an AGN). We also find that the fractionsof broad line and x-ray detected AGN increases with infrared luminosity. Table 1 shows thepercentages of broad line and x-ray detected objects for each luminosity bin.

We also had objects that were classified as AGN that were not X-ray detected. 12 ofthe 24 objects classified by the BPT diagram as AGN were not x-ray detected, as were 3of the 17 composite objects. The fact that these objects were classified as AGN, but arenot detected in the x-ray means they are obscured AGN. For these objects, x-rays are tooheavily extincted to be observed. AGN like these are missed by x-ray surveys, which makesdiagnostic diagrams like the BPT diagram very important.

3.2 Using stellar mass in place of [NII]/Hα

We also examined the effectiveness of a classification scheme that uses stellar mass in placeof the [NII]/Hα ratio (Juneau et al. 2011) for high redshift objects. Such a classificationscheme is useful for cases where [NII] and Hα are not present in a spectrum. We also have

Table 1: Percentages of Broad Line and X-ray Detected Objects

Luminosity Bin: 11.5ă log(LIR/L@)ă12.0 12.0ă log(LIR/L@)ă12.5 12.5ă log(LIR/L@)ă13.0 13.0ă log(LIR/L@

Broad Line AGN: 0 27 54 100

X-ray Detected AGN: 14 54 78 100

a sample of objects at such a high redshift that the Hα and [NII] lines were shifted outof the near-infrared spectrum. We have plotted our objects on the [OIII]/Hβ vs. stellarmass graph in Figure 4. They are color coded by their classification on our BPT diagram,so we can see how well the two classification schemes agree. The stellar mass diagram isvery effective at separating out the AGN objects - all the objects classified as AGN on ourBPT diagram were also classified as AGN on the stellar mass diagram. However, it was lesseffective at separating out star forming and composite objects. None of the objects classifiedas composites on the BPT diagram were classified as composites on the stellar mass diagram.In addition, star forming objects were found in all three areas of the diagram.

3.3 Morphology

Using HST ACS I-band images, we examined the morphologies of our objects and tried toidentify trends between morphology, infrared luminosity, object type, and presence of x-rays.We were not able to identify any clear trend between morphology and infrared luminosity, orbetween morphology and object type. This is not surprising, since our sample size is rathersmall - it is possible that trends would appear with a larger sample.

We were able to identify a trend between the morphologies of objects and the presenceof x-rays. We found that non x-ray detected AGN seemed to be more diffuse than the x-rayAGN, which seemed to be very compact and centrally concentrated. Figure 5 contains twoexamples of non x-ray detected AGN and Figure 6 contains two examples of x-ray detectedAGN.

We also noticed that many of our objects seemed to be merging or interacting in someway, and many appear to be in pairs or multiples. Examples are given in Figure 7.

4 Conclusions

Our three main findings are the following:

1. All objects in our sample with LIR ą 1012.5 L@ have AGN.

2. Many objects in our sample show signatures of interactions or mergers based on theirHST images.

3. Non x-ray detected AGN tend to be more diffuse as opposed to x-ray detected AGN,which are more centrally compacted and well formed.

Figure 4: Our sample plotted on a diagram of log([OIII]/Hβ vs. log(Stellar Mass). Theobjects are color coded according to their classification on the BPT diagram. We can seethat AGN are separated out very well by this diagnostic, but that it falls short at separatingout composite and star forming objects.

Figure 5: Two examples of non x-ray detected AGN

Figure 6: Two examples of x-ray detected AGN

Figure 7: Two examples of objects that appear to be merging or interacting

These findings are in good agreement with what is observed in the local universe. Forexample, all ULIRGs in the local universe are mergers. We observed that many of our highredshift objects in all infrared luminosity bins appeared to be mergers. We also had a goodnumber of objects that appeared as point sources, making it impossible to ascertain thestructure of these objects. The fact that all objects with LIR ą 1012.5 L@ contain AGNsuggests a link between extreme luminosities and the presence of an AGN. Perhaps AGNare necessary for objects to reach these extreme luminosities. In the local universe, the mostobjects with the highest luminosities have AGN.

The trend between morphology and the presence of x-rays in an AGN is an interestingone. The fact that x-ray detected AGN tend to be more compact and well formed suggeststhat these objects are in late merger stages, whereas the diffuse non x-ray detected AGNcould be in the process of merging. In the local universe, it is observed that AGN dominatein the late merger stages, suggesting that dust clearing in later merger stages may allowthe AGN to shine through, or that clearing dust allows the AGN to ionize surrounding gas.Our results support this theory at high redshift. In later merger stages, as dust begins toclear away, x-rays would no longer be completely extincted by the dust and would becomeobservable.

5 Acknowledgements

This project was supported by the NOAO/KPNO Research Experience for Undergraduates(REU) Program which is funded by the National Science Foundation Research Experiencefor Undergraduates Program and the Department of Defense ASSURE program throughScientific Program Order No. 13 (AST-07542223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) andthe NSF. Vivienne also received support for this project through an award from the Avonand Tukman Funds at Hunter College of the City University of New York.

6 References

Baldwin, J.A., Phillips, M.M., & Terlevich, R. 1981, PASP, 93, 5BJuneau, S., Dickinson, M., Alexander, D.M., &Salim, S. 2011, ApJ, 736, 104Kartaltepe, J.S., et al. 2010, ApJ, 709, 572Kartaltepe, J.S., et al. 2010, ApJ, 721, 98Kewley, L.J., Groves, B., Kauffmann, G., &Heckman, T. 2006, MNRAS, 372, 961Sanders, D.B., & Mirabel, I.F. 1996, ARA&A, 34, 749Tran, Q.D., et al. 2001, ApJ, 552, 527Yuan, T.T., Kewley, L.J., & Sanders, D.B. 2010, ApJ, 709, 884

Light Pollution around Tucson, AZ and its Effect on the

Spatial Distribution of Lesser Long-Nosed Bats

Alisa FerschKPNO REU 2011 and Wesleyan University

Advisor: Dr. Constance E. Walker (NOAO)

Abstract

The possible effect of light pollution on the presence of lesser long-nosed bats wasanalyzed for an area around Tucson, Arizona. We used sky quality measurements fromGLOBE at Night and additional data collected during this summer. ArcGIS was thenused to create contour maps of the light pollution. A logistic regression analysis wasrun in order to determine what ecological variables (including light pollution) controlthe spatial distribution of the lesser long-nosed bats. Any relationship between thebats and sky quality is important because this could ultimately be useful in decidingif lighting codes should be stricter in the areas that the bats traverse.

1 Introduction

Ever since the invention of the lightbulb, humans have been adding artificial light into thenighttime sky. According to Cinzano et al. (2001), about 2/3 of the world’s populationlives in areas where the night sky is considered polluted (the artificial sky brightness isgreater than 10% of the natural night sky brightness) and about 80% of the United Statespopulation has skies that are typically brighter than those of the best astronomical sitesduring a full moon. This excess light is well-known as a problem for astronomers; however,it is increasingly being recognized for its environmental problems as well. It has beenshown to alter the behaviors of many species of animals, including birds, insects and seaturtles. This “ecological light pollution” has a wide range of effects on wildlife and cancause important changes in animals’ orienting ability, feeding behaviors, reproduction andcommunication and disturb predator/prey relationships (see Rich and Longcore 2006 formuch more information).

The relationship between artificial light and various species of bats has been exam-ined as well, although much on the subject is still not well studied or understood. Themost recognized effect on bats is the attraction of many insect species to light. While this

abundance of food may at first seem beneficial for the 70% of bat species that are insec-tivorous, it can also increase the bats’ own risk of predation and it puts bat species whichare not willing to fly in the light at a disadvantage, since there will be a lack of insects inthe surrounding environment (Polak et al. 2011). Increased light levels and direct glareon bats’ day roosts can also cause a delayed emergence from their roost which decreasesthe animals’ time to forage and may lead to lower body mass in juveniles (Boldogh et al.2007). Some studies have shown that brighter light can actually impair bat vision as well,and specifically, bats may be more sensitive to UV light (Fure 2006). Artificial light canalso disrupt animals’ circadian rhythms, which are very important for many physiologicprocesses (Patriarca and Debernardi 2010)

The lesser long-nosed bat (Leptonycteris curasoae) is a nectarivorous bat which residesin Mexico and migrates north to Southern Arizona, including the area around Tucson, tospend late April through October. During the days they roost in abandoned mines andcaves and they begin foraging about half an hour to an hour after sunset. The lesser long-nosed bat primarily feeds on the nectar and pollen of saguaro, organ pipe cactus and agavebut are known to visit hummingbird feeders as well. It is a federally endangered species andis considered an important pollinator for many plant species, so it is very important to findout what environmental variables have the largest impact on where these bats choose toinhabit and travel through. This may influence important decisions on habitat protection.(Adams 2003, Arizona Game and Fish Department 2003)

2 Methods

The majority of the data used for this research came from GLOBE at Night.1 GLOBEat Night is a citizen science project that has been gathering sky quality data from peopleworldwide since 2006. Volunteers view the night sky on a moonless night and comparewhat they see with pictures of what the sky would look like at different visible limitingmagnitudes (which corresponds to the magnitude of the dimmest star that one would beable to see with the naked eye). They can also more accurately quantify the brightnessof the sky with a Sky Quality Meter (SQM), which gives the measurement in units ofmagnitudes/arcsec2. The sky brightness, location, date, time and any comments are sub-mitted online. Worldwide over the past six years, over 66,600 observations have beenmade.

The area around Tucson that was included for this study is about 65 x 50 km. Thecoordinates of the northwest corner are 32.4517842777369 N, 111.272317916375 W and thesoutheast corner are 31.9894847605149 N, 110.58604366931 W. In figures in this paper, thisstudy area is outlined in red. The study area was broken up into 742 hexagons (each 5 km2),with the ultimate goal being to have three SQM measurements in each hexagon. There were750 SQM measurements from GLOBE at Night. 15 of these were removed because they

1All of the data is available to the public at www.globeatnight.org/analyze.html

Figure 1: A shows the 735 SQM measurements from GLOBE at Night. B is the 211 data points that werecollected this summer. C shows all 946 SQM points used for this project. The study area is outlined in red.

fell outside the 13-24 mag/arcsec2 SQM range, which are not valid for the night sky. Anadditional 211 SQM measurements were taken in the study area during this summer (Figure1). For all conversions between mag/arcsec2 and visual limiting magnitude, Figure 2 wasused, which came from the formula Nelm = 7.93 − 5 log(104.316−(Bmpas/5) + 1) where Nelm

is the brightness in limiting magnitude and Bmpas is the brightness in magnitudes/arcsec2.2

Figure 2: Conversion used between SQM values and limiting magnitude.

ArcGIS was used to create contour maps of the light pollution around Tucson basedon the SQM data. Several of the GLOBE at Night data points had more than one mea-surement at the exact same location; for these the mean SQM value was taken, so therewere 853 distinct SQM points used for the contour mapping. The data was interpolatedby the geostatistical technique of kriging. This was done with the ‘Geostatistical Analy-sis’ wizard in ArcGIS, which allows the user to change various parameters. Backgroundinformation on the techniques of spatial data analysis in ArcGIS can be found in UsingArcGIS Geostatistical Analyst (Johnston et al. 2003). Similar to many other interpolationtechniques, kriging is based on the assumption that data points spatially close together willhave a similar value (here being SQM). For every location on the map that does not havea measured SQM value, kriging predicts a value. It does this by using a model variogramof the data to determine what the weight of each surrounding ‘known’ point will be. Avariogram is a plot of the variance of each pair of data points versus their distance awayfrom each other. There are several curves which can be fit to the empirical variogram, andthe resulting contour map will appear different based on which of these model variogramsyou choose. The variogram for the data from this research is shown in Figure 3.

The predicted values for each unknown location are also dependent on how many of thesurrounding known locations are being used. The user can choose the number of ‘neighbors’

2http://unihedron.com/projects/darksky/NELM2BCalc.html

Figure 3: Modeling the variogram with ArcGIS’s Geostatistical Wizard.

Figure 4: The Cross Validation for the kriging using an exponential variogram and 75 neighbors. The x-axis isthe actual SQM value at known locations, the y-axis is what the kriging interpolated the SQM value to be at thesepoints. This window also shows the prediction error statistics for this particular kriging.

and then only those closest neighbors will be used in predicting the SQM value. This willkeep points far away (and thus not closely related) from being used in the calculation.

Once a predicted surface is created, kriging allows cross-validation in order to get somesense of ‘how good’ the map is. It does this by predicting SQM values for locations whereyou have actual measurements. The predicted SQM value is then plotted against theactual, measured SQM value (Figure 4). In a perfect world, this graph would be a 1:1 line;however, in our case, there were many low SQM values that were overestimated. There arealso prediction error statistics that can be used to compare different krigings.

ArcGIS was also a very useful tool to manipulate and view the data for each hexagon. Inaddition to the average SQM values per hexagon, each hexagon was categorized by ArizonaGame & Fish based on ecoregion, vegetation cover and landform (Figure 5). “Ecoregions”are large areas of land that share the majority of their plant and animal species. They aredefined by the World Wildlife Fund3. Vegetation cover was broken up into 18 differerent‘classes’ and the hexagons were categorized based on which of these classes covered themost area within the hexagon. Landform is the general shape of the land and includedseveral different categories of hills, canyons and flat land. The presence or absence of thelesser long-nosed bats was also determined for each hexagon (Figure 7), based on radiotelemetry data taken by Arizona Game & Fish in 2007 and 2008 (Lowery et al. 2009), anda hummingbird feeder monitoring study in the Town of Marana4

With this information for each hexagon, a logistic regression analysis was run. Logisticregression is useful when you have several variables which influence a dichotomous outcome(in this case either bat presence or bat absence). The goal is to determine which variable(or combination of variables) can best explain the observed outcome of presence/absence.The models are compared using Akaike Information Criterion (AIC), which is related tothe maximized log-likelihood as well as the number of predictor variables in the model.The best model will be the one with the lowest AIC value; however, AIC does not give anabsolute measure of how far away the model is to reality. The analysis only compares themodels you are testing to each other. You will not know if there is some other combination ofpredictor variables that would explain the observed outcome more correctly. The relatively‘best’ model might, in fact, be a poor model in an absolute sense (Burnham and Anderson2002).

3 Results and Discussion

A histogram for the hexagons’ average SQM values (converted to limiting magnitude) isshown in Figure 6. Figure 8 is the percentage of bat presence hexagons and the percentageof bat absence hexagons at each limiting magnitude (again, converted from the SQM

3Information on each ecoregion can be found athttp://www.worldwildlife.org/wildworld/profiles/terrestrial na.html

4Information on this study can be found at http://marana.com/index.aspx?NID=520

Figure 5: Predictor variables for the study area. Ecoregion, vegetation cover and landform were color-coded basedon information given by Arizona Game & Fish. It is only given for those 5km2 hexagons which we have ‘light’ datafor. Light is the average SQM value (converted to limiting magnitude) from GLOBE at Night and data collectedthis summer.

Figure 6: Average SQM values for the hexagons in the study area (converted to limiting magnitude). The meanof the average hexagons was 19.13481487974 mag/arcsec2 and the median was 19.24875 mag/arcsec2, both of whichcorrespond to a limiting magnitude around 5.

Figure 7: Presence and absence, for each 5km2 hexagon, of lesser long-nosed bats in the study area, as determinedfrom bat telemetry data and the hummingbird feeder study.

Figure 8: Histogram of the percentage of each category of hexagons at each limiting magnitude.

values). 67.57% of the bat presence hexagons were at a limiting magnitude of 5 or above,while 54.65% of the bat absence hexagons were in the same range. This indicates that thelesser long-nosed bats are avoiding brighter locations, at least to some extent.

With ArcGIS, kriging contour maps were created using a variety of model variogramcurves and different numbers of ‘neighbors’. Most of these had a similar overall shapeand only differed in the more local structure. In order to choose the one which was mostaccurate, the statistics for the prediction errors were compared. In general, the kriging mapwith the most accurate predictions will be the one with the mean and mean standardizedclosest to zero, the smallest root-mean-square (RMS), the RMS closest to the averagestandard error and the RMS standardized closest to one. Unfortunately, of the manykrigings that were made, there wasn’t one in particular that met all of these conditions.Two krigings that had good prediction error statistics are shown in Figure 9.

The RMS value shows how far off the predicted values are to the measured values, soultimately, the ‘best’ kriging is the one with the smallest RMS. This kriging was found tobe the one which used the exponential variogram and 75 neighbors, and is seen in Figure 10.This contour map was added to Google Earth in order to compare it to nighttime satellitedata from the Defense Meteorological Satellite Program (DMSP)5. The overall shape ofthe contours matches well, although the kriging does not work as well on the edges, wherethere was much less SQM data.

A visual comparison of this kriging and the bat telemetry data show that the batsappear to avoid the brightest area of Tucson (Figure 11).

5This data can be downloaded at http://www.ngdc.noaa.gov/dmsp/maps.html

Figure 9: Picture A is a kriging using the ‘K-Bessel’ variogram and 75 neighbors. This map had the meanprediction error and the mean standardized error closest to zero (of the different parameters that were tried). PictureB is a kriging using the ‘Stable’ variogram and 25 neighbors. This map had the RMS-standardized closest to 1 andthe smallest difference between RMS and average standard error (of the different parameters that were tried).

Figure 10: Picture A is a kriging using the ‘Exponential‘ variogram and 75 neighbors. This map had the smallestRMS (1.014). Picture B shows the contours of this krigings overlaid onto DMSP satellite data from 2009 (from the.kmz file for DMSP OLS Global Composites Version 4 found on http://www.ngdc.noaa.gov/dmsp/maps.html). Thestudy area is outlined in red.

Figure 11: The kriging using an exponential variogram and 75 neighbors, overlaid in Google Earth with the battelemetry (colorful dots and lines). Interstates 19 and 10 are also shown (yellow lines). The study area is outlinedin red.

Figure 12: Results of the logistic regression analysis. The lower the AIC value, the better the model.

Using the data for each hexagon in the study area, a logistic regression analysis wasrun for several models of the different predictor variables (ecoregion, vegetation cover,landform and light) and their AIC values were compared. One model used a ‘dummy’predictor variable. Because this variable is given random values, it should not explain theobserved outcome of bat presence and absence at all. Thus, anything with a higher AICthan this model (called the “intercept”) will be a poor model. The results of the analysiscan be seen in Figure 12.

The logistic regression analysis shows that, by itself, light is not a good predictor ofwhere lesser long-nosed bats choose to go. Ecoregion and vegetation cover (both separatelyand together) were much better models of the bat presence and absence. However, it isinteresting to see that when light was added to the ecoregion+vegetation model, we do getan even lower AIC value. This indicates that while light is not a primary factor controllingthe spatial distribution of the lesser long-nosed bats, it does play some role.

4 Future Work

One of the most important things for continuing this work is to get more SQM data. Thereare 742 hexagons in the study area and as of right now, only 171 of them have the desiredthree (or more) data points (Figure 13).

Figure 13: Number of SQM data points per 5km2 hexagon

Data is especially lacking in west, south, Saguaro National Park and Coronado National

Forest. Getting better spatial coverage will improve both the contour map and the logisticregression analysis.

It would also be useful to run the logistic regression analysis with other combinationsof predictor variables. Since the logistic regression analysis is a very subjective way to testthe models (the information you get out of it is entirely dependent on the models you putin), it is important to compare all models which would make ecological sense. Additionalpredictor variables that should be considered are elevation, climate and population density.Population density is obviously very closely tied to light pollution, so it will be interestingto see if the model does better with population density, as this may indicate that someother variable associated with humans is causing the bat avoidance, rather than light.

5 Conclusion

The sky quality around Tucson was mapped, using data gathered primarily by residents ofTucson and interpolating the data using the kriging method with ArcGIS. This data, alongwith the average SQM values for the 5km2 hexagons, can be used not only by astronomersbut by ecologists as well. A preliminary analysis to see what variables control the spatialdistribution of lesser long-nosed bats did include the “light” variable in the best model,suggesting that this federally endangered species does take light into consideration whenflying from roost to foraging location.

6 Acknowledgements

I would like to thank my advisor Connie Walker, as well as Shawn Lowery and Joel Dia-mond from the Arizona Game and Fish Department for all their help. This research wassupported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Pro-gram which is funded by the National Science Foundation Research Experiences for Un-dergraduates Program and the Department of Defense ASSURE program through ScientificProgram Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798between the Association of Universities for Research in Astronomy (AURA) and the NSF.

7 References

Adams, Rick A. Bats of the Rocky Mountain West: Natural History, Ecology, andConservation. Boulder: University of Colorado, 2003. 128-30.

Arizona Game and Fish Department. 2003. Leptonycteris curasoae yerbabuenae. Un-published abstract compiled and edited by the Heritage Data Management System, Arizona

Game and Fish Department, Phoenix, AZ.

Boldogh, S., D. Dobrosi, P. Samu. 2007. The effects of the illumination of buildings onhouse-dwelling bats and its conservation consequences. Acta Chiropterologica, 9(2): 527-534

Burnham, Kenneth, and David Anderson. Model Selection and Multimodel Inference.New York: Springer, 2002. 60-64. Print.

Cinzano, P., F. Falchi, C.D. Elvidge. 2001. The first World Atlas of artificial night skybrightness. Mon. Not. R. Astron. Soc. 328, 689-707.

Fure, A. 2006. Bats and lighting. The London Naturalist, No. 85.

Johnston, K., J.M. Ver Hoef, K. Krivoruchko, N. Lucas. Using ArcGIS GeostatisticalAnalyst. Redland, CA: Environmental Systems Research Institute, 2003.URL: dusk.geo.orst.edu/gis/geostat analyst.pdf

Lowery, S. F., S.T. Blackman, D. Abbate. 2009. Urban Movement patterns of LesserLong-nosed bats (Leptonycteris curasoae): Management Implications for the Habitat Con-servation Plan within the City of Tucson and the Town of Marana. Research Branch,Arizona Game and Fish Department, Phoenix, Arizona.

Polak, T., C. Korine, S. Yair, M.W. Holderied. 2011. Differential effects of artificiallighting on flight and foraging behavior of two sympatric bat species in a desert. Journalof Zoology. doi: 10.1111/j.1469-7998.2011.00808.x

Rich, Catherine, and Travis Longcore. Ecological Consequences of Artificial NightLighting. Washington: Island Press, 2006.

An Analysis of Known Variable Stars in the Kepler Field

Nicholas JimenezKPNO REU 2011 and Alfred University

Advisor: Dr. Kenneth Mighell (NOAO)

Abstract

Using the catalog of the All-Sky American Survey (ASAS) variable stars in theKepler Field, we analyzed Kepler light curves from quarters 0, 1, and 2 using theNASA Star and Exoplanet Database (NStED) periodogram service and determinedperiods and amplitudes for the 777 variables that we could access. The ASAS periodsagree very well to the periods determined from the Kepler data except for semiregularvariables. This is due to roughly a week-long interval between ASAS observations.With a higher observing frequency, these stars are much better characterized. Weinvestigated the quality of the NStED service period determinations by comparingperiods of the ASAS eclipsing binaries to the periods determined for them by Slawsonet al. We determined that NStED determines similar periods found by Slawson et al.for well defined eclipsing binaries with sharply peaked periodograms, but when the mainpeak of the periodogram is broad there is greater uncertainty in the measurements. Wealso present an analysis of red giants that exhibit solar-like oscillations from the dataset of Hekker et al. and compare their amplitudes (as measured from the Kepler lightcurves) to the strongly variable red giants in the ASAS data set. We find that variablered giants must be quiet in order to sustain solar-like oscillations.

1 Introduction

The NASA Kepler Space Telescope was launched on March 7, 2009 with the objective ofdetecting exoplanet candidates. It is designed to observe a 105 square degree section of thesky between Cygnus and Lyra. Kepler has a photometer that can precisely detect smallchanges in light given off of stars due to a transiting exoplanet. Kepler can also determineperiods of larger transiting objects, such as eclipsing binaries. Its photometric sensitivityallows Kepler to determine the periods of variable stars to unprecedented precision. Ittakes data in in quarters of 90 days, excluding the first two quarters, Q0 and Q1, whichhad ∼10 and ∼35 days respectively, summed over periods of 30 minutes for long cadenceand over 1 minute for short cadence.

The All-Sky American Survey (ASAS) of variable stars was completed in 2009 (Pigul-ski et al. 2009) to aid in target selection for the Kepler mission. ASAS catalogued 947

variable stars within the Kepler field of view. The ASAS observations were taken withtwo telephoto lenses (Nikkor 200-mm f/2.0) at Haleakala on Maui between July 2006 andDecember 2007 (Pigulski et al. 2009). Kepler has advantages over ground-based observingbecause Kepler has very high precision of photometry combined with very long uninter-rupted sequences of data; aliasing problems inherently associated with the ground-baseddata are avoided. Additionally, since Kepler is a space-based telescope, the atmospheredoes not limit its photometric sensitivity. We analyzed the differences between the Keplerand ASAS periods using the NASA Star and Exoplanet Database (NStED) periodogramservice1 and developed a list of periods of ASAS targets using the Kepler data to furtherquantify the differences between ground-based and space-based variable star observations.

We verified the accuracy of the NStED periodogram by comparing the generated periodsof eclipsing binary stars to those of the Slawson et al. (2011) catalog which includes 2,165eclipsing binary stars in the Kepler Field that were analyzed using a neural network. Wealso looked at the 10,956 red giant stars analyzed by Hekker et al. (2011) that exhibitedsolar-like oscillations. Hekker et al. were able to determine many stellar parameters, likemass, surface gravity, effective temperature, and radius to a higher precision than what isavailable from the Kepler Input Catalog at the Multi-mission Archive at Space Telescope(MAST) website. We compared the peak-to-peak amplitudes of the red giants in ASASto those of Hekker et al. and determined that the amplitudes of the ASAS red giants aremuch larger.

2 Data and NStED

We made a list of the coordinates of all the ASAS stars and downloaded the data fromMAST. Because Q3 data is not yet available for most stars in the ASAS catalog, we reliedpredominantly on Q2 data, and when data for Q2 was unavailable, we used Q1, and usedQ0 when neither Q2 nor Q1 data were available. Data for ASAS stars was unavailable forfour possible reasons: there is no Kepler ID (KID) for the ASAS star, implying that it thestar is not in the Kepler Input Catalog (KIC); the data is still proprietary or unavailableto the public; it was flagged as 0 on the MAST website, signifying that there is no dataavailable; or it was flagged as 1 which means no data is currently available but it is plannedto be observed. If no data was available for the object, we were unable to include it in ouranalysis. This was true for 170 stars, restricting our analysis of the 947 stars in the ASAScatalog to 777. Of the entire ASAS catalog, only one was specified on MAST as dropped.We uploaded the data to the NStED periodogram service and recorded their periods basedon barytime, the barycentric time, and ap raw flux, the simple aperture photometry flux.

We used the simple aperture photometry fluxes and not the corrected flux because thePre-search Data Conditioning (PDC) pipeline is optimized for exoplanet detection, notdetermining periods of variable stars. The simple flux has had basic calibration applied to

1http://nsted.ipac.caltech.edu/periodogram/cgi-bin/Periodogram/nph-simpleupload

it, but lacks the processing of the corrected flux. Using the raw fluxes eliminates addednoise from PDC, and frequently the PDC actually removes the signal entirely.

The periodogram service displays a graph of power as a function of period, and thenoffers links to phased light curves. The power spectrums are created using through threemethods: Lomb-Scargle (the default method) which uses a Discrete Fourier Transform,Box-fitting Least Squares (BLS), and Plavchan which uses a hybrid of both2. We used theLomb-Scargle method, as it frequently provides the least noisy spectrum with little aliasconfusion.

2.1 Analysis of NStED Periodograms

From a broad peak in a periodogram, you can tell that there is a range of periods around thepeak value that would also work, meaning that the program produced the periodogram wasunsure about the reported period. This was the case for nearly all the semiregular, noted bythe ASAS catalog as QPER for quasiperiodic, variables. However, sharp peaks indicate thatthe program is certain about the reported period. The range of acceptable periods is limitedto just the period that occupies the peak in the sharp periodogram. Eclipsing binaries,Cepheids, and RR Lyraes all had sharp peaks. Frequently when analyzing eclipsing binarystars, it was necessary to double the Rank 1 period. Figure 1 shows the Lomb-Scargle firstranked period and Fig. 2 shows double that period.

Figure 1: Lomb-Scargle first ranked period (0.481391 days).

2http://nsted.ipac.caltech.edu/periodogram/applications/Periodogram/docs/About.html

Figure 2: Double the Lomb-Scargle first ranked period (0.962782 days).

By multiplying the Rank 1 period by 2, we get the ×2 alias. The multivalued curveshown in Fig. 1 is not a physically possible. Using the ×2 alias, we see that this is asemi-detached eclipsing binary.

3 NStED Periods of Variable Stars

NStED is particularly good at determining the period of eclipsing binary stars, giving sharpperiodograms. For all of the eclipsing binaries, doubling the Rank 1 period (×2 alias) givesthe correct period, as confirmed by Slawson et al. (2011), except for ASAS 288, 298, and385 which were not included in the Slawson et al. (2011) catalog. For ASAS 98 and ASAS607 the tripled Rank 1 period (×3 alias) gives the correct period.

A lot of information can be interpreted from the periodogram itself. By looking at thenumber of peaks and the orientation of peaks around the maximum peak, the appearance ofthe phased light curve can frequently be predicted. Figures 3, 4, and 5 show, respectively,example phased light curves of a detached eclipsing binary, a semidetached eclipsing binary,and an overcontact eclipsing binary.

Figure 3: A detached eclipsing binary.

Figure 4: A semidetached eclipsing binary.

Figure 5: An overcontact eclipsing binary.

NStED gives broad periodograms for QPERs. There are characterized by multivaluedcurves that are generally in phase. A good example of their varying extrema is exhibitedin ASAS 92 (see Fig. 6).

The phased light curve clearly shows a periodic tendency, but the peak flux varies withtime. This shows evidence of an overtone. This is visible when looking at the light curveover the entire Kepler quarter (see Fig. 7). This is typical for QPERs in the ASAS catalog.

The mechanism that drives this variability is not well-studied. ASAS was not able tophase the majority of these objects, giving periods that were not supported by the Keplerdata. Because of this type of star has a nearly constant period but varying peak flux values,more frequent observations are required for proper characterization.

NStED gives sharp periodograms for objects classified by ASAS as periodic variablestars. They usually have a triangle-wave periodicity. The NStED periods agree well withthe ASAS values.

4 Comparison of ASAS and Hekker data

Figure 8 shows the distribution of ASAS stars superimposed on the Hekker et al. sample.The gray region shows red giants, the lower limit as specified by Ciardi et al. (2011)

and the upper limit used by Hekker et al. (2011). We have 77 stars that fall into thisregion: 27 (empty blue circles) were analyzed by Hekker, and only two (solid red circles)

Figure 6: A typical periodogram of a QPER.

were determined to have solar-like oscillations. The percentage of our red giants thatwere studied by Hekker that have solar oscillations is only 7%. Hekker observed thatapproximately 70% of red giants in her sample had solar oscillations. We determined thatthe major difference between our two red giant sets, excluding sample size, is the amplitude.

4.1 Amplitudes of ASAS and Hekker et al. data

To get the peak-to-peak amplitudes of all the stars in both data sets, we first made a perlscript. This perls cript used a list of the data files to make an IRAF script that utilizedIRAF tstat command which gives the mean, standard deviation, median, minimum, andmaximum values of a column in a FITS table. We did this for all the stars using theap raw flux, finding the minimum and maximum flux. We then took those numbers andinput them into a supermongo script which converted the change in flux to a changein magnitude, using ∆M = −2.5 log(max/min), giving the peak-to-peak amplitude inmagnitudes. Figure 9 is a completeness graph of amplitude for the two samples of redgiants.

Figure 7: A typical light curve of a QPER over a Kepler quarter.

The Hekker et al. sample is the dashed (blue) line and the solid (red) line is the ASASsample. It is apparent that the two sets are very different in respect to peak-to-peakamplitude. All of the Hekker et al. red giants that exhibit solar-like oscillations have peak-to-peak amplitudes of less than or equal to 0.1 magnitudes. Only about 20% of the ASASsample have amplitudes of less than or equal to 0.1 magnitudes. We conclude that inorder for red giants to have solar-like oscillations, they must have small amplitudes. Themajority of ASAS red giants cannot be analyzed using solar-like oscillations to determinetheir stellar parameters.

5 Conclusions

We found that NStED periods for eclipsing variables agree very well with Slawsons periods.This verifies the reliability of NStED. We also determined that the stars in the ASAS cataloggenerally do not exhibit solar-like oscillations because their peak-to-peak amplitude is toolarge to sustain them. ASAS was successful in determining precise periods for all typesof variables except QPER and APER, though for variables that have periods of around aday, like 123, 255, 303, 368, and 615, ASAS was less accurate. This is probably due to thepoor sampling of the ASAS variables. The ASAS variables were observed approximatelyonce every five days. ASAS was able to get accurate periods for long-period variables likeMiras; the periodogram service defaulted to 88.7 days for variables with periods of

Figure 8: The distribution of ASAS stars superimposed on the Hekker et al. sample.

Figure 9: The amplitude distribution of Hekker et al. and ASAS Red Giants.

more than ∼80 days. Combining Kepler data from multiple quarters could possibly enableaccurate determination for periods in excess of ∼80 days but the accurate combination ofraw aperture fluxes could prove to be very problematical. Upcoming sky surveys like LSSTwill likely have difficulty characterizing semiregular variables due to their weekly observingcadence.

References

Ciardi, D. R., von Braun, K., Bryden, G., et al. 2011, AJ, 141, 108

Hekker, S., Gilliland, R. L., Elsworth, Y., et al. 2011, MNRAS, 414, 2594

Pigulski, A., Pojmanski, G., Pilecki, B., & Szczygie l, D. M. 2009, Acta Astronomica, 59,33

Slawson, R. W., Prsa, A., Welsh, W. F., et al. 2011, AJ, 142, 160

PhAst: A Flexible IDL Astronomical Image Viewer

Morgan Rehnberg1,∗, Robert Crawford2, Mark Trueblood3, Ken Mighell3

1 Beloit College, 700 College Street, Beloit, WI 53511

2Rincon Ranch Observatory, 2853 S. Quail Trl, Tucson, AZ 85730

3 National Optical Astronomy Observatory, 950 N. Cherry Ave, Tucson, AZ 85719

∗rehnberm@beloit.edu

Abstract

We present PhAst, a new IDL astronomical image viewer based on the existingapplication ATV. PhAst opens, displays, and analyzes an arbitrary number of FITSimages. Analysis packages include image calibration, photometry, astrometry (pro-vided through an interface with SExtractor, SCAMP, and missFITS). PhAst hasbeen designed to generate reports for the Minor Planet Center reporting. Initialtests indicate PhAst provides an excellent astrometric solution and moderate pho-tometric accuracy. PhAst is cross platform (Linux/Mac OSX/Windows for imageviewing and Linux/Mac OSX for image analysis) and can be obtained from http:

//www.noao.edu/staff/mighell/phast/.

1 Introduction

Flexible Image Transport System (FITS, described in Wells et al. (1981)) compatible imageviewers exist for all major platforms. These exist both as standalone programs (MaxIm DL,Astrometrica) and as part of larger astronomical image packages (e.g., IRAF (Tody, 1986,1993)). These programs are often concerned with more than just image display and process-ing. For example, MaxIm DL (a Windows client), serves primarily as telescope and cameracontrol software for amateur observers. SAOImage DS9, conversely, focuses exclusively ondisplaying images.

IRAF offers a powerful array of analysis tools that covers a wide spectrum of imageprocessing. A new image tool might seem unnecessary. What SAOImage DS9 cannot accessis the vast amount of astronomy analysis code available as open source code in IDL. The IDLlanguage has been used extensively by astronomers for over a decade, and many researchersalready have a mature environment of IDL procedures. An astronomical image viewer whichcould interface with this code would have broad application in the analysis of astronomicalobservations.

An IDL image viewer, ATV (Barth, 2001), exists that reads FITS images. ATV emulatesmany of the features of SAOImage DS9. ATV can either be run stand-alone or be called by

Figure 1: ATV (left) and PhAst (right) as they appear on startup with an image loaded.Note the change in orientation from vertical to horizontal. PhAst exposes more tools on thetoolbar.

another IDL procedure and it possesses similar display and photometry functions to hat ofDS9. PhAst (Photometry-Astrometry), described in this paper, enhances the usefulness ofthe ATV image viewer.

2 Changes to ATV

ATV does not support multiple images. It provides basic support for blinking up to threeimages, but, in general, only one image can be held in memory at a time. For work withNear-Earth Objects (NEOs), frequently more than three images need to be analyzed. Auser should be able to examine as many images as desired and in any order desired. PhAstprovides this functionality by adding an image archive to the existing image viewer. Whileonly one image can be displayed onscreen at any given time, all images are held in memoryand the user may select any of them at any time. The entire image archive may be animatedin various ways, allowing the user to view an entire observation in sequence. When switchingbetween images, all brightness/contrast adjustments are retained.

The interfaces for both DS9 and ATV make poor use of modern displays. These pro-grams are vertically-oriented, while modern displays are becoming increasingly horizontally-oriented. PhAst reorients the interface to take advantage of the additional screen spaceoffered by these displays. The main toolbar is moved from the top to the left side and reor-ganized to fit more cleanly (see Figure 1). When the application is expanded, this allows allof the expanded space to be devoted to displaying a larger portion of the image. Controls forthe blinking/animating process are also placed on the main toolbar to better expose them.

Figure 2: PhAst’s batch processing utility. The user can choose to calibrate an image ordirectory of images with a dark, flat, and bias frame. The calibrated image is then passedto SExtractor and SCAMP to generate an astrometric solution.

These tools are very important in near-Earth asteroid and Kuiper Belt object work, but lessimportant in other fields of observing. To accommodate this, toolbar toolboxes have beenmade collapsable. The state of these boxes can be controlled through a configuration file,allowing users complete control over the toolbar.

Minor changes throughout the ATV code have been made to exploit the flexibility of theimage archive. For example, the photometry tool can now perform photometry on the entiresequence of images, writing each result to file. An option has also been added to import anentire directory, rather than import images one-by-one.

3 New additions

PhAst also includes a number of feature additions that extend its usefulness beyond simplyimage display. Unlike DS9, PhAst does not have an IRAF-style engine operating with it, soadditional functionality has been integrated directly with the application.

Central to these additions is the ability to calibrate raw astronomical CCD images. PhAstallows the user to select a flat, dark, and bias frame which are used to calibrate the raw CCD

science images. The procedure can also make use of an image’s overscan region and thenremove it. Calibration can be applied to either a single image or to an entire directory offiles (see Figure 2).

PhAst integrates a number of powerful tools for determining an astrometric solution fora given astronomical image. The packages SExtractor (Bertin and Arnouts, 1996), SCAMP(Bertin, 2006), and missFITS (Marmo and Bertin, 2008) are maintained separately andPhAst provides a convenient front-end interface to the applications. Once an image hasbeen passed through this pipeline, the astrometric solution is written to the FITS header.SCAMP supports both linear and non linear astrometric solutions, which are both writtento the FITS header for later use.

Once an image has World Coordinate System (WCS) pointing data, PhAst can takeadvantage of it in a number of ways. PhAst retains ATV’s ability to display the rightascension and declination for points on the image as the user mouses over the image. Thesecoordinates can be transformed to a number of different systems. The WCS pointing datacan also be used internally by PhAst in several ways. PhAst can query the online USNO-B1.0 catalog and overlay the names and positions of all field stars (see Figure 3). The usercan also use that catalog data to search for a particular star in the given field, convenientfor those doing photometry on particular stars in an image. If an object was being trackedduring a series of exposures, the WCS pointing data can be used to align the images, freezingthe motion of everything but the object of interest.

PhAst can also take a calibrated and solved image and compute its photometric zero-point. This calculation is performed by matching each star in the image (extracted bySExtractor) with its corresponding catalog star (taken from the USNO-B1.0 catalog). Oncethis value is written to the FITS header, PhAst’s photometry module will automaticallyread and use it to calibrate photometric measurements.

For NEO work, PhAst can prepare an object report for the Minor Planet Center (MPC).MPC reporting requires that an image is calibrated, solved, and has a photometric zero-point. The report is prepared and saved as a plain-text document, as shown in Figure 4.

4 Preliminary results

To help determine whether PhAst meets the requirements for NEO work, a number of imageswere calibrated using its pipeline. These images were taken from an observing run whichoccurred the night of 30 June - 1 August, 2011 at Kitt Peak National Observatory. Thedirect imager on the 2.1-meter telescope was used with a BK-7 clear filter for maximumlight collection. The direct imager’s CCD is a 2046×2048 array which was binned 2×2 todecrease readout time. The night was non-photometric, with occasional cirrus clouds, butrepresented a typical night for NEO observations.

These images processed using PhAst were then compared against the same images asthey were processed by the traditional, multi-application (Maxim DL and Astrometrica),pipeline. The previously-processed images had been submitted and accepted by the MinorPlanet Center (MPC), so they are representative of the analysis quality required for this

Figure 3: PhAst with an image loaded and catalog stars and names overlaid on the image.Note the Overlay Stars toolbox on the bottom of the left pane. The vertical streak is a CCDchip defect and the long, angled streak is likely a satellite.

Figure 4: An example Minor Planet Center report. This text file can be attached to anemail for submission to the MPC.

line of work. PhAst’s astrometry matched very well with the previously processed images,returning results within 0.2 arcseconds of the submitted results. Since the 2.1-meter CCDhas a pixel scale of approximately 0.6”, this is sub-pixel accuracy.

Photometry presents a more difficult situation, as the non-photometric conditions causedincreased error. This error also affected the previously submitted results, which differed fromthe MPC’s best-fit brightness by approximately 0.2 magnitudes. By comparison, PhAst’sphotometry differed from the model by an average of 0.3 magnitude, and from the previouslysubmitted results also by about 0.3 magnitude on average. This is within the computed 1-σ error of 0.48 magnitudes across all the image sequences. Although PhAst seems to haveeliminated a systematic bias present in the multi-application process, further work is requiredto reduce this error.

5 Future work

Although PhAst is functionally complete for basic NEO work, several additions would greatlyexpand its usefulness. Prime among these is the handling of non linear WCS coordinates.When SCAMP determines an astrometric fit for an image, it offers the ability to computea high-order fit. Such a fit is useful for correcting for images taken on optical systemswhich contain significant optical abberations. If PhAst supported this specification, pixelcoordinates on the image could be transformed in realtime to WCS coordinates while stillcorrecting for the nonlinear nature of distortions in the science observation.

Another powerful addition to PhAst would be the implementation of elliptical aperturesfor photometry. When an object (such as a NEO) is tracked non-sidereally, the stars formstreaks as the integration time increases. For photometry, these streaks are much moreaccurately covered by an elliptical aperture than a circular one. If they are too greatlyelongated, these streaks can also interfere with generating an astrometric solution for theimage. A modification of the default commands passed to SCAMP would help account forthis.

Finally, PhAst currently supports only FITS images. This is sufficient for virtuallyall ground-based observations. Some spacecraft planetary science missions, however, use aseparate format for image storage, Video Image Communication And Retrieval (VICAR).VICAR images are similar in structure to FITS images, with a header (or label, in VICARterminology) and an image array. The similarity between the file structures should make itrather straightforward to enable PhAst to handle images from these missions. This wouldmake the program even more flexible for IDL image display and enable direct comparison ofground-based and spacecraft imagery within a single tool.

6 Conclusion

IDL tools will continue to be relevant for years to come. The PhAst project improves uponthe existing ATV image viewer in a number of ways. It conveniently handles the display

and animation of large numbers of images. These images can be calibrated, solved, andoverlaid with catalog information. When suitable photometry and astrometry have beendetermined, PhAst makes it easy to quickly submit reports of near-Earth object sightings tothe Minor Planet Center. Future updates will expand PhAst’s utility for both ground-basedand spacecraft observations.

Acknowledgements

This research was supported by the NOAO/KPNO Research Experiences for Undergraduates(REU) Program which is funded by the National Science Foundation Research Experiencefor Undergraduates Program and the Department of Defense ASSURE program throughScientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) andthe NSF.

References

A. J. Barth. ATV: An Image-Display Tool for IDL. In F. R. Harnden Jr., F. A. Primini, &H. E. Payne, editor, Astronomical Data Analysis Software and Systems X, volume 238 ofAstronomical Society of the Pacific Conference Series, pages 385–387, 2001.

E. Bertin. Automatic Astrometric and Photometric Calibration with SCAMP. In C. Gabriel,C. Arviset, D. Ponz, & S. Enrique, editor, Astronomical Data Analysis Software andSystems XV, volume 351 of Astronomical Society of the Pacific Conference Series, pages112–115, July 2006.

E. Bertin and S. Arnouts. SExtractor: Software for source extraction. Astronomy & Astro-physics Supplement 317, 117:393–404, June 1996.

C. Marmo and E. Bertin. MissFITS and WeightWatcher: Two Optimised Tools for ManagingFITS Data. In R. W. Argyle, P. S. Bunclark, & J. R. Lewis, editor, Astronomical DataAnalysis Software and Systems XVII, volume 394 of Astronomical Society of the PacificConference Series, pages 619–622, August 2008.

D. Tody. The IRAF Data Reduction and Analysis System. In D. L. Crawford, editor,Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, volume627 of Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, page733, January 1986.

D. Tody. IRAF in the Nineties. In R. J. Hanisch, R. J. V. Brissenden, & J. Barnes, editor,Astronomical Data Analysis Software and Systems II, volume 52 of Astronomical Societyof the Pacific Conference Series, pages 173–182, January 1993.

D. C. Wells, E. W. Greisen, and R. H. Harten. FITS - a Flexible Image Transport System.Astronomy and Astrophysics Supplement 44, 44:363–369, June 1981.

X-ray Selected AGN in A Merging Cluster

Joanne TaylorKPNO REU 2011 and Indiana University

Advisor: Dr. Dara Norman (NOAO)

1 Abstract

Almost all active galactic nuclei (AGN) are sources of hard X-rays, while their correspondingoptical features can often be inconspicuous due to color selection bias and obscuration. Weinvestigate the X-ray AGN population and evolution in the merging galaxy cluster DLSCLJ0522.2-4820 discovered via weak gravitational lensing shear from the Deep Lens Survey(DLS). Since weak lensing shear is dependent only on mass, it does not introduce the biasesthat typical cluster selection methods do. This cluster is of particular interest due to bothits extended multiple X-ray emission peaks and its large number of X-ray point sources.We measured the redshifts of X-ray AGN as well as cluster galaxies in order to investigatethe 3-dimensional distribution and possible clustering of AGN in galaxy clusters. Of the125 objects in our sample, 54 are in the cluster; the cluster redshift is determined to bez “ 0.2997 ˘ 0.0096. This agrees well with an earlier value of z “ 0.296 ˘ 0.001. Weidentified several broad line AGN at high redshift, but currently have found no X-ray pointsources to be at the cluster redshift.

2 Introduction

Across the Universe as we know it today, there are on the order of 100 billion galaxies. Ofthese, it is believed 5-10% are active, and 10% of active galaxies have an active galacticnucleus, or AGN. AGN are highly compact central regions of galaxies that emit enormousamounts of energy. The velocity dispersion of gas as well as luminosity variability indicatethat these central regions are up to a few light-weeks across. The mass of these AGN areestimated to be up to 109M@. The only way to account for such a large amount of mass ina very small region is for the central region to actually host a supermassive black hole.

One of the most important features that these black holes create is the accretion disksurrounding AGN. This accretion disk is formed from infalling gas that is heated and emitsvery energetic photons up to UV and X-ray range. X-ray and optically selected AGN mayrepresent a continuum in the evolutionary process of all AGN. One way to fuel an AGN

is through the merger of two galaxies abundant in cold gas (Barnes & Hernquist 1992).Therefore, examining AGN population and distribution in a merging cluster environmentcan provide insight into their evolution.

In many cases these rare AGN show no evidence of activity in optical wavelength bands.Using X-ray measurements is a reliable and efficient method of identifying AGN, as almostall AGN have hard X-ray sources, 2-6 keV (Green et al. 2004). Compact X-ray objectsabove a cutoff luminosity of 1042 ergs s´1 are almost certainly AGN (Martini et al. 2006and Fabbiano 1989). It has been suggested that “optically unremarkable” AGN are simply astage in the evolution that all AGN undergo. As AGN evolve, accretion feedback can fuel theejection of gas from the central regions of galaxies (Hopkins et al. 2005). When this occurs,a seemingly optically unremarkable AGN then becomes observable at optical wavelengths.Building a complete census of AGN type and distribution will help to answer many questionsregarding the evolution of AGN as well as their environments. In particular, examining amerging cluster can allow us to study a specific and unique point in galaxy evolution in anenvironment that is experiencing substantial activity.

This cluster, DLSCL J0522.2-4820, is located at z “ 0.3 and was selected through weakgravitational lensing shear in the Deep Lens survey (DLS, Wittman et al. 2002). Whereasstrong lensing forms completely separate images or arcs, weak gravitational lensing can beobserved through two phenomena: convergence and shear. While convergence magnifies thesource, shear stretches and distorts the source image. Weak lensing shear is a unique selectionmethod in that it depends only on mass. Consequently, it avoids the biases present inoptical, X-ray and Sunyaev-Zeldovich (SZE) surveys, which are dependent on star formationhistory, baryon content, and dynamical state (Wittman et al. 2006). While this cluster wasdiscovered via weak lensing shear, the AGN themselves were found through Chandra X-rayObservatory observations.

This cluster is of specific interest not only because it is one of the first to be selected byweak lensing shear, but also because of the unprecedented number of X-ray sources present.Martini et al. (2006) find that there are between two and ten X-ray sources in a cluster. Inour sample cluster there are 67 individual X-ray sources. Also of note in this cluster are theX-ray subclusters; Chandra observations show that there are four subclusters evidenced byextended X-ray emission. Three of these subclusters are at z “ 0.3, while one is z “ 0.21(see Figure 1). It is tempting to speculate that there may be a connection between the largenumber of AGN and extended X-ray gas in this cluster.

By measuring the redshifts of AGN in this merging cluster, we hope to gain some insightas to where they are located and if they are clustered in any way. In the following sectionswe will detail the data sample and results from redshift measurements.

3 Observations and Reductions

Within the cluster are 67 X-ray point sources from Chandra observations. Of these 67sources, 36 are luminous enough to be AGN and have visible counterparts with Ră23. These36 sources were labeled priority 1. Priority 2 and 3 objects do not have X-ray counterparts,

Figure 1: A map of convergence contours (green) and X-ray contours (white) over an opticalimage of sample cluster DLSCL J1402.0-1019. Subclusters are labeled across the 10’ field ofview. (figure from Wittman et al. 2006)

but have colors putting them near the cluster redshift.This cluster was observed from Gemini South on 2011, January 6 and 7 using Gemini

Multi-Object Spectrograph (GMOS). Spectra were taken of 36 X-ray AGN, as well as 90cluster candidates in order to fill the optical field of view. The R150 low dispersion gratingwas used to cover the wavelength range needed („4500-9000A). 5 masks, consisting of 23-30slits, were strategically positioned over the four subclusters to observe as many AGN aspossible and examine the cluster velocity dispersion. 2-6 900s exposures were taken bothnights for each mask using two wavelength centers (650 and 660nm) in order to cover gapsin the wavelength range due to the physical chip gaps. Spectra were then reduced usingGMOS IRAF tasks, beginning first with bias-subtraction. The CuAr arcs were mosaickedacross all 3 chips and then wavelength calibrated. Flats were then divided from the data andwavelength calibrations applied. Cosmic rays were removed using L.A.Cosmic (van Dokkum2001) and finally spectra were extracted. Extracted Multi-Extension File (MEF) spectrawere separated into their individual extensions and corresponding extensions from both the650 and 660nm wavelength centers were combined to provide higher S/N. See Figures 2-4for examples of cluster spectra.

Figure 2: An example of a high resolution spectrum at cluster redshift (z “ 0.30); absorptionlines are labeled.

Figure 3: A highly-redshifted quasar (z „ 1.8); emission lines are labeled.

Figure 4: A likely Seyfert galaxy at redshift z „ .38; emission lines are labeled.

4 Analysis

In order to measure redshift, we wrote an interactive Fortran program that searches for theCaII H λ3934, CaII K λ3968, G-band λ4304, Mg λ5175 and Na λ5894 absorption lines.Redshifts and their errors were then obtained for galaxies. For emission line targets, aseparate program was written to search for and confirm the Lyα λ1215, CIV λ1549, CIIIλ1909, MgII λ2798, Hγ λ4340, Hβ λ4861, and OIII λ5007 emission lines (reference compositequasar spectrum from Francis et al. 1991). We expect the majority of broad line AGN to bebehind the cluster, at a redshift high enough to shift these emission lines into our wavelengthrange.

In addition, a quality factor was assigned to each spectrum. The Ca H and K absorptionlines can be seen in all spectra for which a significant signal was detected. Therefore, thisfactor signifies the quality of a spectrum in terms of how many of the G-band, Mg, andNa absorption lines can be identified. A quality value of 1 represents a spectrum with thehighest S/N, with all three absorption lines easily identified. All lines are also visible in aquality 2 spectrum, but some noise is introduced. Two out of the three G-band, Mg, and Nafeatures can be seen in a quality 3 spectrum. One out of three lines can be seen in a quality4 while no lines, including the Ca H and K, can be identified in qualities 5 and 6. Quality 5spectra have an identifiable continuum, but are too noisy or faint to identify any lines. In

these cases, additional reduction steps may be required to extract data in the future. Quality6 spectra, though, contain no signal; the slits may be slightly off-target, or the targets aresimply too faint to observe. We plot a histogram of galaxies vs. redshift in Figure 5. Wediscuss the results below after having binned the spectra into redshift ranges.

Figure 5: Histogram of number of galaxies vs. redshift. The majority of galaxies are locatedat z „ 0.3.

5 Results

5.1 Objects In the Cluster

Using the Right Ascension (RA), declination, and redshifts of galaxies, we constructed a3-dimensional map of cluster objects. Objects that were designated as in the cluster were inthe redshift range of 0.25 ă z ă 0.35 (black symbols in Figure 6). 54 galaxies were within

Galaxy Positions

80.45 80.50 80.55 80.60 80.65 80.70 80.75RA [Degrees]

-48.45

-48.40

-48.35

-48.30

-48.25

-48.20

Dec

linat

ion

[Deg

rees

]

Figure 6: Declination vs. RA for all galaxies in the data sample. Triangles represent X-ray point sources while squares and circles are priority 2 and 3 objects (galaxies with noX-ray counterparts), respectively. Yellow Xs are the X-ray extended emission centers. Lightblue objects redshifts were not able to be measured. Dark blue objects are z ă 0.25, black0.25 ă z ă 0.35, green 0.35 ă z ă 0.5, orange 0.5 ă z ă 1.0, and red z ą 1.0. Filled symbolsare broad line AGN.

this range, with a mean redshift value of z “ 0.2997˘ 0.0096. The redshift dispersion of thecluster was found to be `0.0341

´0.0237. Previous measurements of 16 cluster members determineda redshift ofz “ 0.3, which agrees well with our measurement. None of these 54 clustermembers were X-ray selected AGN (triangles in Figure 6).

5.2 Objects Near the Cluster

Two X-ray point sources were found at z„0.45, but seem to have no spatial relationship.(RA “ 80.562˝Dec “ ´48.269˝z “ 0.4522 and RA “ 80.623˝Dec “ ´48.269˝z “ 0.4518).There are five objects at z „ 0.38, one of which is a broad line AGN (green symbola inFigure 6). At redshifts lower than the cluster, there are two galaxies at z „ 0.21 located

near the low-redshift X-ray subcluster D (z “ 0.21), and one broad line AGN galaxy atz „ 0.25 (dark blue symbols in Figure 6)

This large cluster, 12’ across the sky, clearly has substructure along the line of sight.While the cluster redshift is 0.2997, there are galaxies located at z “ 0.38 and 0.21.

5.3 High-Z Objects

At high redshift (z ą 1.0), all eight observed objects are broad line AGN (red symbols inFigure 6). Of particular interest are two AGNs at z „ 1.8. These two AGN are locatedvery near to each other (RA “ 80.559˝Dec “ ´48.239˝z “ 1.7906 and RA “ 80.564˝Dec “´48.234˝z “ 1.7909); it may be that they are one single lensed object. Their angularseparation is 25.456”. There is also an object at RA “ 80.469˝Dec “ ´48.291˝z “ 1.7355,but it is unclear whether this object is related to the z “ 1.8 pair.

5.4 M Stars

Priority 1 objects were selected by having both Chandra X-ray observations and a visiblecounterpart. Three priority 1 objects were found to actually be M stars. These M stars weremost likely incorrectly identified as AGN candidates, or are actually Low-Mass X-ray Binaries(LMXBs). Limits on spatial resolution introduce the possibility of falsely identifying an X-ray sources visible counterpart as a completely separate object. M stars may also appear tobe AGN if they are LMXBs, binary star systems where one component is a compact objectsuch as a white dwarf and the other is a star that has filled its Roche lobe. LMXBs canX-ray luminosities up to 1041 ergs s´1 and can appear to be AGN since they are closer andhave the same X-ray luminosity as an AGN redshifted at z „ 3 (Martini et. al 2006). Mstars can also have the same optical colors as AGN, making it more difficult to distinguishthe two.

6 Discussion and Future Work

We measured the redshifts of 75 objects in the DLS galaxy cluster DLSCL J0522.2-4820,located at a redshift of z “ 0.2997 (see Figure 6 for detail). 36 of these galaxies weredesignated priority 1, or X-ray selected AGN. 54 galaxies were found to be within the cluster(0.25 ă z ă 0.35), but none of these were priority 1 objects. Ultimately, redshifts weremeasured for only 14 of 36 priority 1 objects. Of the 14 actually measured, 10 were actuallybroad line AGN Of the priority 1 objects not measured, three were M stars, seven were fartoo faint to extract any signal, and 12 were too noisy/faint to reliably measure at this point.

While we did not find any AGN in the cluster, other useful information was discovered.Of note is the quasar pair at z “ 1.8 that may be a single lensed object. It is also interestingto see that there are clumps of galaxies located at various redshifts. There are 2 broad lineemission galaxies at z “ 0.45 as well as five galaxies at z “ 0.38.

We hope to continue analysis on the 12 priority 1 objects that were too noisy or faintto measure redshifts for. With more time and reduction, it may be possible to measure theredshifts of these spectra, providing valuable information on AGN distribution.

7 References

Hopkins, P. F., Hernquist, L., Cox, T. J., Di Matteo, T., Roberston, B., & Springel,V., 2005, ApJ, 632, 81

Barnes, J. E., & Hernquist, L., 1992, AR&AA, 30, 705Fabbiano, G., 1989, ARAA, 27, 87Francis, P. J., Hewett, P. C., Foltz, C. B., Chaffee, F. H., Weymann, R. J., & Morris,

S. L., 1991, ApJ, 373, 465Green, 2004, ApJSS, 150, 43Kennicutt, R. C. Jr., 1992, ApJ, 388, 310Martini, P., Kelson, D. D., Kim, E., Mulchaey, J. S., & Athey, A. A., 2006, ApJ,

644, 116van Dokkum, P. G., 2001, PASP, 113, 1420Wittman, D., DellAntonio, I. P., Hughes, J. P., Margoniner, V. E., Tyson, J. A., Cohen, J.G., & Norman, D., 2006, ApJ, 643, 128Wittman, D. et al. 2002, SPIE, 4836, 73

Alternative Mounting Systems for the Galileoscope

Christine WellingKPNO REU 2011 and Dickinson College

Advisor: Dr. Steve Pompea (NOAO)

The Galileoscope is a kit telescope produced for the International Year of Astronomy (IYA)in 2009. As an educational tool, it has been distributed across the world. In order to successfullyobserve with the Galileoscope, it must be steadied in some way. The preferred method for stabilizingthe Galileoscope is to use a tripod. However, this is not always possible, and other stabilizationmethods are needed. In this paper, alternative mounting systems for the Galileoscope are presented.I also document my familiarization with the Galileoscope, and outreach involving the Galileoscope.

I. INTRODUCTION

The Galileoscope is a kit telescope initially producedin 2009 for the International Year of Astronomy (IYA).It is an educational tool to teach children about op-tics and astronomy[1]. The Teaching with Telescopeswebsite[2] and the Galileoscope website[3] contain educa-tional projects and experiments for use in the classroom.For instance, there is a guide for hands-on activities thatallows students to learn how the optics inside the Galileo-scope work.

As part of outreach during the IYA, many Galileo-scopes were distributed worldwide. As of October 2010,over 180,000 Galileoscopes have been distributed in over100 countries[4].

In order to see easily through the Galileoscope, it mustbe steadied in some way. A 1

4 ” - 20 nut was built intothe Galileoscope in order to use a standard size cameratripod to steady it. Many people do not have tripodsfor a variety of reasons, such as availability and cost.These people will not be able to use the Galileoscopeto the fullest possible extent. It should make observersexcited about astronomy. However, continued difficultyusing the Galileoscope can frustrate observers, makingthem less interested in astronomy. This is the oppositeof what we want the Galileoscope to do.

The main goal of my Research Experience for Un-dergraduates (REU) project was to develop inexpensivemounting systems for the Galileoscope. I document myfamiliarization with the Galileoscope by observing withthe Galileoscope, experimenting with digital photogra-phy through the Galileoscope, and attending outreachevents.

II. FAMILIARIZATION WITH THEGALILEOSCOPE

Before designing alternative mounting systems for theGalileoscope, I needed to familiarize myself with theGalileoscope. This gave me some insight into the im-portant aspects of the Galileoscope that needed to re-main available with alternative mounting systems. I alsogained knowledge of the limitations of the Galileoscope.

My familiarization was done in two parts: observing anddigital photography.

A. Observing with the Galileoscope

As part of familiarizing myself with the Galileoscope,I used it to observe both terrestrial and astronomical ob-jects. I looked at trees and antennas to become morecomfortable with aiming and focusing the Galileoscope.This also helped me learn about the eyepieces. The kitcontains three possible eyepiece configurations, Galileanwith 17x magnification, Plossl with 25x magnification,and Barlow with 50x magnification. The Galilean eye-piece shows a small field of view, and is useful for educa-tional purposes, but frustrating for use in observing. ThePlossl eyepiece is useful for beginning observers becauseit has a larger field of view, but still provides magnifica-tion. The Barlow eyepiece can be used for observation ata higher magnification. Because of the high magnifica-tion, the field of view is smaller, making it more difficultto observe an object. Section II B contains more infor-mation about the eyepieces.

The first astronomical object I observed was the moon.I was able to find it and focus the Galileoscope easily us-ing the Plossl eyepiece. Craters and maria were visible,and had nice contrast. However, I had difficulty using theBarlow eyepiece on the moon because the moon driftedquickly through the Galileoscope’s field of view. Specifi-cally, pointing the Galileoscope became an ongoing pro-cess, leaving little time to observe.

Double stars in which at least one was visible to thenaked eye were also easily observed using the Plossl eye-piece. These included Mizar and Alcor, and OmicronCygni. In this case, I was unable to use the higherpower Barlow eyepiece because I was unable to point theGalileoscope with such a small field of view. Addition-ally, Omicron Cygni took up most of the field of viewof the Plossl eyepiece. Using the Barlow eyepiece wouldprohibit seeing both stars.

Planets seemed to be an obvious target. However, theyproved difficult to observe. Saturn was easily visible tothe naked eye. It was possible to observe Saturn throughthe Plossl eyepiece in good weather. A breeze was enough

to throw Saturn out of the field of view of the Plossl.I was unable to point the Galileoscope at Saturn usingthe Barlow eyepiece. I attempted to observe Jupiter andVenus in the early morning. However, neither was locatedat a high enough altitude to be visible before the sunrisemade the sky too bright.

In order to test the limits of the Galileoscope in thesomewhat light polluted city of Tucson, I attempted somedeep sky objects. These objects included the AndromedaGalaxy (M31), the Great Globular Cluster in Hercules(M13), and the Open Cluster in Cygnus (M39). However,I was unable to find any of these.

B. Digital Photography

The second part of Galileoscope familiarization was us-ing it for digital photography. First, I took pictures ofterrestrial objects using a point and shoot digital camerato get a feel for photography through the Galileoscope,and the differences in the eyepieces. The terrestrial pho-tographs were taken by holding the camera up to the fo-cused Galileoscope’s eyepiece. Lining up the optics wasdone by eye using the viewing screen on the camera. Thecamera was partially to completely zoomed in, depend-ing on the eyepiece. This made it easier for the camera’sautofocus to work. The camera was put on a setting fortaking pictures of close-up objects.

FIG. 1: Terrestrial picture of a brick wall taken through theGalilean eyepiece. The camera is completely zoomed in.

Figure 1 shows the best picture taken through theGalilean eyepiece. The camera was completely zoomedin so that the image could be seen. When the camerawas not zoomed in, the pictures showed only glare onthe inside of the Galileoscope. Images taken against thesky were too bright to be able to distinguish any details.This problem partially occurred because of the small im-age in the Galilean eyepiece.

Figure 2 shows an image of a palm tree taken throughthe Plossl eyepiece. For reference, this picture was takenwith the camera zoomed the entire way in, as with theimage in Fig. 1. This demonstrates the small size of the

FIG. 2: Terrestrial picture of a palm tree taken through thePlossl eyepiece. The camera is completely zoomed in.

image in the Galilean eyepiece relative to the size of theimage through the Plossl eyepiece. Due to this small im-age size, the Galilean eyepiece is difficult to use for ob-serving and for photography. It is useful for educationalpurposes only.

FIG. 3: Terrestrial picture of a palm tree taken through thePlossl eyepiece. The camera is partially zoomed in.

Figure 3 shows an image of the same palm tree as inFig. 2, but with a lower zoom setting on the camera.Images taken through the Plossl eyepiece tended to befairly sharp when the Galileoscope was in focus, and thecamera was partially zoomed in. Photographs were ableto easily show any focus issues. It was easiest to line upthe optics with the Plossl eyepiece to take clear pictures.

Figure 4 shows the same palm tree as in Fig. 3. This il-lustrates the magnification difference between the Plossland Barlow eyepieces. The images taken through theBarlow eyepiece were darker, and somewhat grainier.This may be because aligning the camera with theGalileoscope was more difficult through the Barlow eye-piece than through the Plossl eyepiece.

Once I was comfortable with terrestrial photogra-phy, and the limitations of each eyepiece, I attemptedastrophotography with several different digital cam-eras. These included a cell phone camera, a point and

FIG. 4: Terrestrial picture of a palm tree taken through theBarlow eyepiece.

shoot digital camera, a digital single-lens reflex camera(DSLR), and a webcam. The moon was used for all ofthese trials. The Plossl eyepiece was used with the cam-eras because the moon drifted through the Barlow eye-piece too quickly to take a picture.

FIG. 5: Attempted picture of the moon using a cell phonecamera.

The cell phone camera was unable to produce an im-age of the moon. It was unable to collect sufficient light.The images taken of the moon all resembled the imagein Fig. 5. At this point in time, the moon was approach-ing first quarter, and should have been clearly visible.The small bright spot near the center of the image is areflection of light inside the Galileoscope.

Using a point and shoot digital camera works well. Fig-ure 6 shows the moon taken through the Plossl eyepiece.The camera settings was set to ISO, which is a camerasetting used for low light. Even though the moon wasbright, the frame was dark enough to require a low lightsetting. The flash was manually turned off. The cameraagain was zoomed partially in for the camera’s autofocusto properly work.

The DSLR camera did not work quite as well for pho-tography through the Galileoscope because the camera

FIG. 6: Picture of the moon taken through the Plossl eye-piece.

lens was significantly larger than the Galileoscope’s eye-piece. This made it difficult to line up the camera’s opticswith the image in the Galileoscope. When the optics wereproperly lined up, the picture came out well. However,the Galileoscope did not appreciably improve the qualityof the image when compared to a picture directly takenof the moon.

FIG. 7: Picture of the moon taken through the Galileoscopewebcam.

The webcam tested was specifically designed to be usedinstead of the Galileoscope’s eyepiece. It worked fairlywell. Figure 7 shows one image taken using the webcam.Some chromatic aberration is visible. The top part of themoon has a blue tint, while the bottom part of the moonhas a reddish tint. These images showed significantlymore detail than the images taken using the point andshoot digital camera. Additionally, the webcam was ableto take movies. By using this feature and image stackingsoftware, even better images can be achieved.

The webcam had a few problems. In order for thewebcam to work, it had to be plugged into a computer.This meant it required a laptop to run outdoors. It wasdifficult to accurately point the Galileoscope by watchingthe laptop screen. Additionally, the webcam softwarecrashed several times in the course of the evening.

III. OUTREACH WITH THE GALILEOSCOPE

Through the summer, I had several opportunities foroutreach. I was able to attend two Galileoscope builds,where a group of people are led through the process ofbuilding a Galileoscope. Each person builds their ownGalileoscope. I also had several serendipitous interac-tions with people living at my apartment complex.

The first Galileoscope build was for Arizona ScienceTechnology Engineering Mathematics (STEM) teachers.They were given a presentation on how to build theGalileoscope one step at a time. I was one of severalpeople assisting the teachers when they had problems,and checking their work. While there, I noted two issuesthat all of the teachers seemed to have. The first was thatthey were afraid of breaking the Galileoscope. Even whenreassured that the plastic was quite sturdy, they seemeduncomfortable with applying pressure to get pieces tosnap together. The second problem was that none ofthem seemed to know how to use a tripod. There wasalso no presentation available to show them.

The second Galileoscope build was for a science campfor middle school age girls. They were given the samepresentation on how to build the Galileoscope one stepat a time. However, the person presenting and I were theonly people helping who had previous experience buildingGalileoscopes. The other people helping were runningthe science camp. At times, the girls became confusedbecause the people running the camp would move fasterthan the group and give incorrect instructions.

During both Galileoscope builds, there were some com-mon problems. The people building had trouble snappingsome of the plastic parts together. They also had trou-ble getting the eyepiece lenses in the correct order, andclosing the eyepiece assemblies around the lenses.

While observing at my apartment complex, many peo-ple who lived there would ask to look through the Galileo-scope. These included University of Arizona students, agroup of teachers from Mexico attending a workshop atthe University of Arizona, and other REU students. Ingeneral, the non-astronomers asked a lot of questions.The first question was always if they could look throughthe telescope. After that, many wanted to know if I stud-ied astronomy, and if I was a student at the University ofArizona. I was able to use this to talk about the Galileo-scope and my REU project. The specific groups also haddifferent interests when discussing the telescope. TheUniversity of Arizona students tended to share their in-terest in astronomy. The teachers from Mexico expressedmore interest in the educational purposes and value of theGalileoscope. The other REU students were surprised atthe high image quality of the Galileoscope.

IV. MOUNTING SYSTEMS BUILT

As the main goal of my REU, I developed many mount-ing systems for the Galileoscope. These systems needed

to be relatively inexpensive and relatively buildable. Iaimed to design systems that cost less than five dollars.I also tried to use parts that would be easily obtainableat a hardware store, obtainable online, or would alreadybe available in a home.

None of the mounting systems are intended to be theone perfect solution. Instead, each system has strengthsand weaknesses that can be used to assess the bestmounting system for a particular purpose.

Various factors that may influence the choice of mount-ing system are summarized in Table II, at the end of thispaper. Each mounting system was designated as beingeither static or dynamic. Static mounting systems areable to be used by many observers without having to berepointed each time. Dynamic mounting systems mustbe pointed by each person using the Galileoscope. Aqualitative assessment of ease of construction, and easeof use was made. The scale ranged from easy to hard as:Very easy, Easy, Fairly easy, Somewhat easy, Somewhatdifficult, Fairly difficult, Difficult, Very difficult, Impos-sible.

A. C-Clamp Mounting System

The c-clamp mounting system uses a c-clamp thatcomes with a 1

4 ”-20 threaded hole drilled through theback. A 1

4 ” - 20 x 1 14 ” bolt is put through the hole with

the threads pointing out of the c-clamp, as shown in Fig.8. The Galileoscope can be attached to the c-clamp us-ing the bolt. The mounting system can then be clampedsomewhere in order to observe.

FIG. 8: Finished c-clamp mounting system. The Galileoscopeattaches to the bolt on the back of the C.

This system provides a static mount, and the Galileo-scope is unable to move. This can make pointing theGalileoscope difficult, as the clamp itself must adjustedto change the pointing. The c-clamp mounting systemwould not work for objects that quickly drift throughthe field of view, such as the moon. It would be idealfor objects that do not quickly drift through the field ofview. It would also work for terrestrial objects not in the

direction of the sun.

B. C-Clamp with Swivel Mounting System

The c-clamp with swivel mounting system is a mod-ification of the c-clamp mounting system (See sectionIV A). A swivel with 1

4 ” - 20 threads is inserted throughthe threaded hole in the c-clamp instead of the bolt. Theswivel is outside of the c-clamp. Ideally, this swivel willbe straight with a ball joint providing movement.

The swivel was intended to be the third rod end fromsection IV J. This would minimize movement against thec-clamp. However, due to compatibility problems, thatparticular rod end will not work. Another rod end with14 ” - 20 threads can be substituted. In this case, themounting system will be dynamic based on the rod end.Additionally, the range of motion will be the same as thatof the rod end.

C. Cardboard Box Mounting System

The initial directions for the cardboard box mountingsystem were found online[5]. A mark should be made onthe side of the box, near a top corner, where the Galileo-scope will be mounted. A small hole should be startedthere, using scissors. A 1

4 ” - 20 bolt can then be used toenlarge the hole. This way, the hole in the cardboard boxwill just accommodate the 1

4 ” - 20 bolt that will hold theGalileoscope in place. A 1

4 ” washer is put on a 14 ” - 20 x

1” bolt. The bolt should be screwed through the hole inthe box, with the head of the bolt and the washer on theinside of the box. At least one more washer is then puton the bolt. Extra washers may be used for spacers. A14 ” - 20 nut is tightened onto the bolt. The Galileoscopeis then attached to the bolt. Some counterweight shouldbe placed in the box to make the system more stable.Figure 9 shows the Galileoscope attached to the finishedmounting system.

FIG. 9: Finished cardboard box mounting system.

The cardboard box mounting system is dynamic. The

Galileoscope easily turns downwards when not sup-ported. Additionally, it pulls the side of the box out, andgives a torque to the bolt. With time, this wears downthe stability of the cardboard, and another hole must bedrilled. In order to avoid this problem for as long as pos-sible, the Galileoscope must be held up against the box.This system has the advantage that as one hole in thecardboard box wears out, another can be drilled, so thebox can be reused many times. Because this system mustsit on a table, it is difficult to look near zenith. The restof the sky is observable.

D. Caster Wheel Mounting System

The caster wheel mounting system uses an industrialcaster wheel made of hard rubber or plastic. A 1

4 ” holeis drilled through the wheel near the edge. A 1

4 ” - 20bolt is inserted through the hole. The length of the boltdepends on the width of the wheel. There should be ap-proximately 3

4 ” of threads sticking out of the wheel. Anut put on the end of the bolt. The caster wheel shouldbe mounted on the top some object using the directionswith the caster wheel. The Galileoscope attaches to thebolt, and the nut can be tightened against the Galileo-scope to secure it.

FIG. 10: Completed caster wheel mounting system, withoutbeing installed. The caster wheel may also have a brakingsystem.

A permanently installed mounting system will be morestable than a mobile system. If the mounting system willbe permanently outdoors, materials that can withstandthe elements should be used. Mounting the caster wheelto an object that can be brought indoors, such as a broomhandle, will eliminate the need for weatherproof materi-als. In that case, there should be a way to hold themovable object still while observing.

Building this system is somewhat tool intensive. A

handheld electric drill may not be enough to drill a holeinto the caster wheel. Instead, a drill press may beneeded. The caster wheel mounting system is dynamic.It can be static if the caster wheel used has a brakingsystem. This system provides easy movement in both di-rections. It can be used to look almost anywhere on thesky.

E. Coffee Can Mounting System

The coffee can mounting system utilizes an emptymetal coffee can. The paper covering a metal coffee canis removed. A 1

4 ” hole is drilled in the side of the coffeecan, near the top. The hole should be deburred to re-move sharp edges. A 1

4 ” - 20 nut is placed on a 14 ” - 20

x 1” bolt, and then a 14 ” washer is put over that. The

bolt should go through the hole in the coffee can, withthe threads outside of the can. A counterweight to theGalileoscope should be put inside the coffee can. TheGalileoscope is attached to the bolt. The nut should betightened against the coffee can for more pointing stabil-ity. The hardware set-up is shown in Fig. 11.

FIG. 11: Finished coffee can mounting system.

This mounting system is dynamic. It works well forobjects located near the horizon to approximately 45◦

altitude. After the mounting system has been movedwhile observing, the nut loosens. This means that thenut must be tightened often during the course of use.

F. Cut-Out Coffee Can Mounting System

The cut-out coffee can mounting system uses a coffeecan that has been cut apart as the base of the system.The paper is removed from the outside of an empty metalcoffee can. Three marks are made on the outside of thecoffee can to drill 1

4 ” holes. The holes should be approx-imately one quarter of the way around the outside of thecoffee can from each other, and the same distance fromthe end. That is, the two end holes should be across thecenter of the coffee can from each other, and the third

hole should be in the middle of the first two. Three 14 ”

holes are drilled in the can at those points. Two linesshould be drawn from the top and bottom of one endhole to the top and bottom of the middle hole. A hack-saw is used to cut along those lines, forming a 1

4 ” wideslot in the coffee can. The slot will look like Fig. 12. Adeburring tool should be used to remove the sharp edges.

FIG. 12: Slot in the side of the coffee can. This slot shouldgo about a quarter of the way around the can.

The bottom of the coffee can is removed. This canbe done either using a sander, or by rubbing the bottomof the coffee can against concrete. The seal around thebottom of the can will come apart, and the bottom willseparate fairly cleanly from the sides. The edge of thebottom should be deburred. A 1

4 ” hole is drilled throughthe middle of the coffee can bottom, and is deburred.

FIG. 13: Galileoscope attached to the cut-out coffee canmounting system.

A 14 ” washer is placed over a 1

4 ” - 20 thumbscrew.The thumbscrew goes from the inside of the coffee can,through the slot in the side and the hole in the bottom.It is then attached to an object outside, such as a fencepost. A 1

4 ” - 20 nut is put on a 14 ” - 20 x 1” bolt, and

a 14 ” washer is put over that. The bolt is put through

the last hole in the side of the coffee can such that thethreads point out. The Galileoscope is attached to thisbolt such that the body of the Galileoscope is tangent to

the curve of the coffee can, as illustrated in Fig. 13. Thenut is tightened against the washer inside the coffee canto hold the Galileoscope in place. Figure 13 shows thefinished mounting system.

The Galileoscope can move both up and down, andside to side by loosening the thumbscrew. The coffee canis able to turn around the central axis by sliding alongthe slot, allowing altitude movement. The coffee can isalso able to spin from side to side, providing azimuthalmovement.

This mounting system is static and stable. However, itis very difficult to build. It requires the use of many tools,such as the hacksaw and a deburring tool. The sides ofthe coffee can are not very sturdy, making it hard tocut the slot in the side. Removing the bottom is a verytime consuming process. Additionally, even though theedges of all of the cuts have been deburred, they can stillbe very sharp. The cut-out coffee can mounting systemshould only be made by adults, and should only be usedby children when supervised by an adult.

G. Flexible Bicycle Mirror Mounting System

The flexible bicycle mirror mounting system uses theflexible neck of a children’s bicycle mirror to support theGalileoscope. The mirror is removed from the flexibleneck. Wires may be used in the neck to create some sta-bility in the flexible neck. Any wire that may be exposedshould be cut off of the neck. A 1

4 ” - 20 x 1” bolt isinserted into the Galileoscope. A mark is made on thebolt to indicate how much of the bolt fits in the Galileo-scope. This is shown in Fig. 14. Remove the bolt fromthe Galileoscope.

FIG. 14: A black mark on the bolt shows how much of thebolt fits in the Galileoscope. This indicates where to align thebolt with the mirror neck.

The bolt should be aligned next to the mirror necksuch that from the mark on the bolt to the end of thebolt are above the top of the neck. Electrical tape isused to secure the bolt to the side of the mirror neck, asshown in Fig. 15. The Galileoscope is attached to thebolt. The mounting system can then be clamped to an

object similar to the bicycle handlebars for which it wasintended.

FIG. 15: A bolt taped to the side of the mirror neck.

FIG. 16: Finished flexible bicycle mirror mounting system.The neck is unable to support the Galileoscope, so the Galileo-scope falls with the objective lens down.

The flexible bicycle mirror mounting system is dy-namic. However, this is because the mirror neck is unableto support the weight of the Galileoscope. The Galileo-scope falls over, and pulls the neck down, as shown inFig. 16. Because the weight is not supported, the ob-server must support the Galileoscope, making it trickyto observe small objects.

H. PVC Mounting System

The PVC mounting system uses a PVC pipe and a teesteady the Galileoscope. A piece of 3

4 ” PVC pipe shouldbe cut to approximately 5 feet long for standing childrenor for sitting in a chair, or to approximately 6 feet long forstanding adults. A 1

4 ” hole is drilled through the centerof the top of a 3

4 ” PVC slide tee. A 14 ” washer should

be placed on a 14 ” - 20 x 1” bolt. The bolt is inserted

up through the drilled hole in the tee, such that the bolthead and washer are inside of the tee. A 1

4 ” - 20 nut

is attached to the bolt on the outside of the tee. Thisarrangement is shown in Fig. 17. The nut should not betightened yet.

Attach the Galileoscope to the bolt in order to checkthe alignment of the Galileoscope. The body of theGalileoscope should be parallel to the top of the tee.The Galileoscope and bolt are turned until this is thecase, and the nut is tightened to keep this alignment.The Galileoscope should be removed from the tee.

FIG. 17: Arrangement of hardware in the PVC tee for thePVC mounting system. The washer inside the tee providesspacing so that the bolt is not too long.

The tee is attached to one end of the PVC pipe. Thisrequires some pressure and twisting. Once the tee is at-tached to the PVC pipe, it will not come apart. TheGalileoscope is attached to the bolt. The finished mount-ing system is shown in Fig. 18.

FIG. 18: Finished PVC mounting system with Galileoscopeattached. The tee helps stabilize the direction in which theGalileoscope points.

The PVC mounting system is dynamic. The advantageof including the tee in this design is that it allows anotherpipe to be attached to the tee. This could be used to takesteadier pictures through the Galileoscope. Additionally,the Galileoscope is not free to move on the the mountingsystem. The PVC structure must be moved to point indifferent directions. This makes adjusting the eyepiece

height for comfort impossible. However, there are fewerparts that must be held in place by hand.

I. PVC Monopod Mounting System

The PVC monopod is based on monopods designed forcameras. A set 1

4 ” holes are drilled about 2” from the endof a piece of 3

4 ” PVC pipe. The pipe is drilled straightthrough such that there are two hole across from eachother. The pipe should be approximately 5 feet long forstanding children or for sitting in a chair, or approxi-mately 6 feet long for standing adults. Extra holes canbe drilled in the PVC pipe to make the height adjustablefor both children and adults. A 1

4 ” - 20 nut is threadedonto a 1

4 ” - 20 x 2” bolt. The bolt is inserted through aset of holes at an appropriate height. The Galileoscopeis attached to the bolt. The nut on the bolt is tightenedagainst the PVC pipe to hold the Galileoscope in place.Figure 19 shows the Galileoscope attached to the finishedmonopod.

FIG. 19: Galileoscope attached to the finished PVC monopod.

The PVC monopod is a dynamic system. Because ithas only one point to balance on, it is somewhat unstable.The Galileoscope also turns on the bolt, requiring the ob-server to hold both the PVC pipe and the Galileoscope.Together, these instabilities make the Galileoscope wob-bly, and difficult to focus. Pointing the Galileoscope at anobject also becomes tricky. However, the monopod pro-vides sufficient steadying to observe larger objects, suchas the moon.

J. Rod End Mounting Systems

Four pieces of hardware called rod ends were consid-ered in order to create a mounting system containing aball joint. Figure 20 shows the four rod ends used. Forease of reference, they have been numbered I - IV fromleft to right. Table I provides an overview of the fourrod ends selected. All of the rod ends have a small rangeof motion compared to the other mounting systems, so

the table compares their relative ranges of motion. Ingeneral, the rod ends need to be mounted somewhereoutdoors. Objects that could be used for this purposeinclude fence posts and trees.

FIG. 20: The four rod ends. They are numbered I - IV fromleft to right.

Rod end I uses a ball joint that looks a bit like an eye-hook. A 1

4 ” - 20 x 1 14 ” bolt is inserted through the hole

in the rod end. A 14 ” - 20 nut is tightened onto the bolt,

against the rod end. The threaded portion of the rodend is attached to something outdoors such that the rodend is vertical. The Galileoscope is attached to the boltgoing through the rod end. Figure 21 shows the finishedmounting system.

FIG. 21: The first rod end mounting system.

The first rod end has a small range of motion due to thebolt head’s placement against the ball. This placementmeans that the Galileoscope can only be moved from sideto side a small amount. However, the ball in the rod endis able to spin around the center axis of the bolt. In thisway, the the Galileoscope can be pointed from near thehorizon to zenith.

Rod end II employs a rod end that has one threadedend, and a place to clamp a rod into place. A 1

4 ” - 20bolt is inserted through the hole in the rod end, and isclamped in place. This bolt is mounted to something

outside. The Galileoscope is attached to the threadedportion of the rod end. Figure 22 shows the finishedmounting system.

FIG. 22: The second rod end mounting system.

The second rod end has a more even range of motionthan the first rod end. That is, it is able to move approx-imately the same amount side to side as up and down.This range of motion is partially constrained by the posi-tion in which the rod end is mounted. In order to maxi-mize the range of motion, the system should be mountednear a corner. The rod end should be parallel to theground, and on the top of the object to which it is beingattached.

Rod end III uses a rod end that has threads on bothends. The end further from the rubber seal should bemounted outdoors. The end closer to the rubber sealshould attach to the Galileoscope. Figure 23 shows theway in which this piece of hardware should be fastened.However, this particular rod end has metric threads ofsize M6 x 1, which is the closest size to 1

4 ” - 20. Ihave found these sizes to be incompatible. Only a smallamount of the threads on the rod end will attach to a nut.This creates a structurally unstable mounting system. Asimilar mounting system can be used, but this particularpart is not recommended.

Rod end IV utilizes an elbow-shaped rod end. A14 ”-20 bolt or threaded rod should be mounted to some-thing outdoors, with some threads exposed. The locationshould preferably be on the top of the object, near theedge, so that the threaded rod is vertical or nearly ver-tical. The female end of the rod end should be attachedto the threads. The Galileoscope is then attached to thethreaded part of the rod end. Figure 24 shows how thiswill look without setting this system up outdoors.

The fourth rod end has a large range of motion rela-tive to the other rod ends that is equal in all directions.Because of the elbow shape, the threaded rod being usedto hold the rod end will experience some torque, and sothe threaded rod should be securely fastened.

Of the rod ends tested, the second seems to have themost potential. It will have no restrictions to its mo-tion if it is mounted correctly. Additionally, attaching

TABLE I: An overview of the rod ends used for mounting systems. The range of motion shows the relative ranges of motionfor the rod ends.

Rod End I Rod End II Rod End IIIa Rod End IVDistinguishing Feature Eye-swivel In-line swivel with one end In-line swivel with two ends Elbow swivel

Relative Range of Motion Large Largest Smallest LargeMcMaster-Carr Part Number 6072K21 6154K13 8412K11 6058K43

aThis rod end has threads of size M6x1, which is the metric thread size closest to 14 ” - 20. However, this size is incompatible

with the 14 ” - 20 threads in the Galileoscope’s nut.

FIG. 23: The third rod end mounting system. The threadsonly barely fit in the nut.

FIG. 24: The fourth rod end mounting system.

the Galileoscope does not torque the rod end. Ideally,a similar rod end similar to the second could be usedthat provided more support. That is, a rod end that wasable to be moved somewhat easily, but could hold theGalileoscope in place once it was pointed would be thebest solution. The simplest method to solve this problemis finding a ball joint that has more friction.

K. Solid Back Chair Mounting System

The solid back chair mounting system uses the back ofa chair to steady the Galileoscope. One rubber band iswrapped around the two plastic holders that come withthe Galileoscope. It should be close to the flat side of theholders. The holders are placed on the back of a chair,with the V in the holders facing down. The Galileoscopeshould be inserted between the holders and in the rubberband, with the eyepiece end going first. A second rubberband is wrapped around the back end of the Galileoscope,and vertically around the back end of the holders. A sideview of the finished mounting system is shown in Fig. 25.

FIG. 25: Solid back chair mounting system.

This mounting system is static. However, it is difficultto both build and use. The plastic holders slide aroundon chair backs easily. The rubber bands tend to pushthe holders tightly against the Galileoscope. This makespointing difficult because the mounting system moves up-wards with the Galileoscope, and it does not provide aspace for the Galileoscope to move downwards. Addi-tionally, it is difficult to balance.

L. String Mounting System

The string mounting system works by suspending theGalileoscope from a tree, or some overhead structure.One piece of string is attached to the o-ring closer to the

eyepiece. The string is cut to hang from the overheadstructure, and suspend the eyepiece of the Galileoscopeat a comfortable height. The simplest way to do this is tomake the string into a loop that goes over the structureand through the o-ring.

The string system can change direction in both altitudeand azimuth, or just change direction in altitude. Inorder to change both altitude and azimuth, two piecesof strings should be attached to either side of the o-ringfurther from the eyepiece. These strings are suspendedfrom the overhead structure, and have adjustable lengths.If only altitude change is desired, only one string needsto be attached to the o-ring further from the eyepiece. Itstill needs to be adjustable.

Depending on the configuration of the strings, thismounting system can be either static or dynamic. Astatic system ties off the front string or strings once theGalileoscope is pointed. A dynamic system leaves thefront string or strings loose to be adjusted by each ob-server.

It is easiest to make this mounting system static. Try-ing to change the length of the string causes the Galileo-scope to swing back and forth. This only makes it moredifficult, and frustrating, to point the Galileoscope. Ifpossible, it is easiest to suspend the Galileoscope fromone string on each o-ring.

It is a bit difficult to put this mounting system to-gether because the string lengths must be determinedand adjusted. Since the Galileoscope is being suspendedby its o-rings, it may be necessary to have two peoplesetting up the system. One person would support theGalileoscope to minimize the stress to the o-rings whilethe string lengths are being adjusted. The other personwould adjust the length of the strings.

M. Suction Cup Mounting System

The suction cup mounting system uses two suctioncups to support the Galileoscope. The suction cupsshould each be able to support at least two pounds. Eachsuction cup is attached by a piece of string to an o-ring onthe Galileoscope. The head of a 1

4 ” - 20 bolt is wrappedin electrical tape. The bolt is attached to the Galileo-scope. The suction cups are attached to a window andsuspend the Galileoscope. The bolt is used to prop theGalileoscope away from the window. Figures 26 and 27show the finished mounting system.

The suction cup mounting system is static. However,it wobbles a bit when touched because it is balancingon only one point. The Galileoscope’s pointing can bemoved up and down by adjusting the suction cups ap-propriately. Some side to side movement is possible bychanging the position of the bolt against the glass.

FIG. 26: Suction cup mounting system.

FIG. 27: Suction cup mounting system.

N. Zenith Mounting System

The zenith mounting system was designed specificallyto allow observers to comfortably see objects near zenith.It is a hybridization of the PVC monopod mounting sys-tem (See section IV I), and one of the rod end mountingsystems (See section IV J).

A piece of PVC pipe with a 14 ” hole drilled near the

end is used. A bolt is put through the hole, and throughthe hole in rod end II from Section IV J. A nut keepsthe rod end on the bolt. The Galileoscope is attached tothe threaded part of the rod end. Figure 28 shows thecompleted mounting system.

This system is dynamic. It should be used whileseated for more comfort in looking straight up. It maybe difficult to initially focus the Galileoscope while it ismounted. In this case, one person can steady the mount-ing system while a second focuses the Galileoscope.

FIG. 28: Zenith mounting system.

V. GALILEOSCOPE DESIGNS THAT WERENOT BUILT

Additionally, more designs were completed that couldnot be built for several reasons. These included availabil-ity of parts and time constraints. Most of these systemswere meant to use something found in or around a typi-cal western home as the base. Others were meant to useitems that may be widely available in other parts of theworld.

A. Calabash Mounting System

The calabash mounting system was designed partiallyin order to build a ball joint. It could not be built be-cause of the availability of calabashes, which are trop-ical gourds, in the United States. The mounting sys-tem would require the use of two dried, roughly sphericalcalabashes of about the same size. The larger calabashwould be cut in half to form a calabash hemisphere. A 1

4 ”- 20 bolt would be put through the middle of the hemi-sphere, with the threads sticking outwards. The hemi-sphere would be bound to the sphere in some manner,probably with cloth or rope. The Galileoscope would beattached to the bolt going through the hemisphere. Mov-ing the hemisphere on the surface of the sphere could beused for small pointing adjustments. The sphere couldbe turned for larger pointing adjustments. This mount-ing system would probably be dynamic because it wouldrest on a curved surface, and most of the weight wouldbe towards the top of the system.

B. Chain Link Fence Mounting System

The chain link fence mounting system was designedto attach to a chain link fence. A quarter of a plasticcylinder would have three holes drilled through it. Onehole would be near each end, and a 1

4 ” hole would be inthe middle. A 1

4 ” - 20 bolt would be put through the

middle hole, with the threads pointing to the outside ofthe cylinder. Zip ties or string would go through theholes on the ends of the plastic piece, and would be usedto attach the plastic to the pipe on the top of a chain linkfence. The Galileoscope would be attached to the bolt.The plastic piece would be able to slide around the pipe,enabling changes in altitude. The bolt would probably beloose enough to allow some change in azimuthal direction.Due to the movability of the mounting system, it wouldlikely be a dynamic system.

C. Coat Hanger Mounting System

The directions for the coat hanger mounting systemwere found on the internet[6]. It is supposed to mimica popular, and expensive, camera tripod that can bemounted to almost anything. Three pieces of heavy wire,such as coat hangers, have small hooks bent into oneend and are wrapped in electrical tape. Each piece ofwire is then electrical taped to a 1

4 ” - 20 bolt, with thehooked end against the the bolt. The wires should beevenly spaced around the bolt. The mounting systemis positioned by wrapping the loose wire ends aroundsome object. The Galileoscope is then attached to thebolt. This mounting system could be static, if the wireis stiff enough and is wrapped tightly enough. However,it would probably be dynamic.

D. Hinge Mounting System

The hinge mounting system started the idea for thecut-out coffee can mounting system (See section IV F).Figure 29 shows a sketch of what this should look like.One side of a strap hinge is mounted on the top andnear the edge of some outdoor object, such as a fencepost. The connection between the two sides of the hingeshould be next to the edge. The second side of the straphinge should move up, and towards the edge. A boltshould be fastened to the second side of the hinge suchthat the threads point up when the hinge is closed. TheGalileoscope is attached to the hinge using this bolt. Thehinge mounting system would be dynamic, and wouldonly allow changes in altitude.

E. Rail Back Chair Mounting System

The rail back chair mounting system was designed tobe similar to the chain link fence mounting system. Itwould use a plastic cylinder that fits around the top railof the chair. A slit would be cut down the side of thecylinder. A 1

4 ” hole would be drilled the slit. A 14 ” - 20

bolt would be inserted through the hole, with the threadspointing out. A 1

4 ” nut would then be tightened onto thebolt to keep it in place. The cylinder would be wrappedaround the top rail of the chair, using the slit cut in

FIG. 29: Sketch of the hinge mounting system. The Galileo-scope attaches to the bolt.

the cylinder. The slit would then be closed with tape.The Galileoscope would attach to the bolt. Changes inaltitude could be made by turning the cylinder aroundthe top of the chair. Changing the direction the chairpointed would change the azimuthal direction. This sys-tem would be dynamic because the Galileoscope woulddrop when not supported by a person.

F. Sand Bag Mounting System

The sand bag mounting system was designed in or-der to provide the functionality of a ball mount withoutthe expense of trying to find parts to build one. In thismounting system, a 1

4 ” - 20 bolt would be sewn into theseam of a cloth bag. Sand would be used to fill the bag,although other heavy materials could be used to fill it,such as pebbles. The weight of the bag’s filling wouldhold the pointing of the Galileoscope. Provided the bagis heavy enough, this would be a static mounting system.

VI. CONCLUSION AND DISCUSSION

Digital photography through the Galileoscope is pos-sible, provided a steady mounting system is used. Thisshould be a tripod. Most of the alternative mountingsystems described throughout this paper do not have thestability to hold the Galileoscope for photography. Apoint and shoot digital camera was the easiest way totake photographs. Pictures of the moon turned out well,though other astronomical objects did not. The webcamdesigned for the Galileoscope produced the highest qual-ity astronomy images for a reasonable price.

I designed and built seventeen mounting systems forthe Galileoscope. The mounting systems that have been

built are summarized in Table II. It lists some factorsthat may influence which system is built. Each systemis designated as static, meaning the Galileoscope can bepointed and many people can look at the same place,or dynamic, meaning each person using the Galileoscopemust point it. The availability of parts, and an estimateof cost to build the mounting system are provided. Aqualitative ranking system was used to show the ease ofconstruction and ease of use of each mounting system.The ranking system ranges from easy to hard as: Veryeasy, Easy, Fairly easy, Somewhat easy, Somewhat diffi-cult, Fairly difficult, Difficult, Very difficult, Impossible.Ease of construction takes into account the necessity oftool use, the time needed to build the mounting system,and the number and severity of frustrating occurrenceswhile building. Ease of use takes into account how dif-ficult it is to point the Galileoscope, how difficult it isto focus the Galileoscope while it is on the mountingsystem, and how difficult it is to keep the Galileoscopesteady while observing. The areas on the sky that canbe observed and the range of motion of each system aregiven.

After testing the mounting systems, I have determinedrecommendation levels for the systems based on easeof building, quality of observing, ease of use, and cost.Quality of observing and ease of use weighed most heav-ily.

The highly recommended systems are the cut-out cof-fee can mounting system, the PVC mounting system,the cardboard box mounting system, and the coffee canmounting system.

The recommended systems are the caster wheel mount-ing system, the first and second rod end mounting sys-tems, and the PVC monopod.

The suction cup mounting system, the zenith mountingsystem, the fourth rod end mounting system, and the c-clamp with swivel mounting system are recommendedwith reservations.

The solid back chair mounting system, the flexible bi-cycle mirror mounting system, the string mounting sys-tem, the c-clamp mounting system, and the third rod endmounting system are not recommended.

In determining the recommendation levels, inexpensivesystems with a somewhat poorer quality of use may beranked higher than more expensive systems. This is mostnoticeable between the first and second levels of recom-mendation. The caster wheel mounting system is moreexpensive than the cardboard box mounting system orthe coffee can mounting system. There was enough of adifference in price that it adversely affected recommen-dation level of the caster wheel system.

VII. FUTURE WORK

There are two main directions in which these mount-ing systems can continue. The first is to have a systemthat can be distributed along with the Galileoscope. The

second is to have multiple systems that can be built bypeople who have a Galileoscope.

A system that can be distributed with the Galileo-scope is likely to require an industrially manufacturedpart, such as a rod end (see Section IV J). However, thiswill require finding a ball joint that has higher friction.The two or three systems that could be distributed willbe selected for further testing. In order to choose onemounting system from these, focus groups consisting oftarget audiences, probably younger children, older chil-dren, and teachers will be used. The focus groups willtest the chosen mounting systems and provide feedback.

Detailed directions will be made available online formounting systems that can be built at home. The factorsregarding which system is appropriate for a situation willalso be available. Ideally, there will be a way for users toprovide feedback so that improvements can be made tothe designs.

Acknowledgments

This research was supported by the NOAO/KNPO Re-search Experiences for Undergraduates (REU) Programwhich is funded by the National Science Foundation Re-search Experiences for Undergraduates Program and theDepartment of Defense ASSURE program through Sci-entific Program Order No. 13 (AST-0754223) of theCooperative Agreement No. AST-0132798 between theAssociation of Universities for Research in Astronomy(AURA) and the NSF.

I would like to thank Dr. Stephen Pompea and RobertSparks for advising this project, and Ron Harris andRoger Repp for help in designing and building some ofthe mounting systems.

[1] Pompea, S. M., Pfisterer, R. N., Ellis, S., Arion, D. N.,Fienberg, R. T., & Smith, T. C. 2010, Proceedings of theSPIE, 7738, 773803.

[2] “Teaching with Telescopes.”http://teachingwithtelescopes.org/

[3] “The Galileoscope.” https://www.galileoscope.org/gs/[4] Fienberg, R. 15 Oct 2010, “Visualizations: Distribution

of Galileoscopes by Country.” http://www-958.ibm.com/software/data/cognos/manyeyes/visualizations/distribution-of-galileoscopes-by-c

[5] Murphy, S., 4 Jan 2010, “Cardboard Box Mount,” Shan-non’s Weblog. http://aquillam.wordpress.com/2010/01/04/a-cheap-tripod-alternative/

[6] Frerich, H., 4 Dec 2006 “Pocket Tripod,” Instructables.http://www.instructables.com/id/Pocket-Tripod/

TAB

LEII

:An

over

view

ofm

ount

ing

syst

ems

built

for

the

Gal

ileos

cope

.C

olum

n1

lists

each

ofth

em

ount

ing

syst

ems,

and

indi

cate

sa

reco

mm

enda

tion

onus

e.C

olum

n2

give

sth

ede

sign

atio

nof

stat

icor

dyna

mic

.C

olum

n3

give

sth

eav

aila

bilit

yof

part

sus

edin

cons

truc

tion.

Col

umn

4gi

ves

anes

timat

eof

cost

tobu

ildth

em

ount

ing

syst

em.

Col

umn

5gi

ves

the

qual

itativ

eev

alua

tion

for

ease

ofco

nstr

uctio

n.C

olum

n6

give

sth

equ

alita

tive

eval

uatio

nfo

rea

seof

use.

Col

umn

7gi

ves

the

area

son

the

sky

that

can

beob

serv

ed.

Col

umn

8gi

ves

the

rang

eof

mot

ion

ofth

eG

alile

osco

pefo

rea

chm

ount

ing

syst

em.

Mou

n tin

gSy

stem

Stat

ic/D

ynam

icP a

rts

Pric

eC

onst

ruct

ion

Use

Are

aof

Obs

erva

tion

Ran

geof

Mot

ion

C-C

lam

p4St

atic

Onl

ine

$2-3

Very

easy

Very

diffi

cult

Whe

repo

inte

don

lyN

one

C-C

lam

pw

ithSw

ivel

3D

ynam

icO

nlin

e$9

-10

Very

Eas

ySo

mew

hat

diffi

cult

Smal

lar

eaar

ound

whe

repo

inte

dSa

me

assw

ivel

Car

dboa

rdB

ox1

Dyn

amic

Har

dwar

est

ores

$1-2

Fairl

yea

syE

asy

Mos

tof

sky;

not

zeni

thFu

llaz

imut

h∼

70◦

altit

ude

Cas

ter

Whe

el2

Dyn

amic

Onl

ine/

Som

eha

rdw

are

stor

es$5

-7So

mew

hat

diffi

cult

Fairl

yea

syM

ost

ofsk

y;ze

nith

unco

m-

fort

able

Full

azim

uth

Full

altit

ude

Coff

eeC

an1

Dyn

amic

Har

dwar

est

ores

/A

rtic

les

arou

ndho

use

$1-2

Fairl

yea

syE

asy

From

altit

ude

45◦

toho

rizon

Full

azim

uth

∼70

◦al

titud

eC

ut-o

utC

offee

Can

1St

atic

Har

dwar

est

ores

/A

rtic

les

arou

ndho

use

$2Ve

rydi

fficu

ltVe

ryea

syM

ost

ofsk

y;no

tze

nith

Full

azim

uth

∼80

◦al

titud

eFl

exib

leB

icyc

leM

irror

4D

ynam

icO

nlin

e$5

-6So

mew

hat

easy

Som

ewha

tdi

fficu

ltM

ost

ofsk

y;ze

nith

unco

m-

fort

able

Full

azim

uth

Full

altit

ude

PV

C1

Dyn

amic

Har

dwar

est

ores

$2-3

Fairl

yea

syFa

irly

easy

From

altit

ude

45◦

toho

rizon

Full

azim

uth

∼45

◦al

titud

eP

VC

Mon

opod

2D

ynam

icH

ardw

are

stor

es$1

-2E

asy

Som

ewha

tea

syFr

omal

titud

e45

◦to

horiz

onFu

llaz

imut

h∼

45◦

altit

ude

Rod

End

I2D

ynam

icO

nlin

e$6

Very

easy

Fairl

yea

syVe

rtic

ally

from

horiz

onto

alm

ost

zeni

thSm

alls

ide

tosi

deFu

llal

titud

eR

odE

ndII

2D

ynam

icO

nlin

e$4

-5Ve

ryea

sySo

mew

hat

easy

Vert

ical

lyfr

omho

rizon

toal

mos

tze

nith

Smal

lsid

eto

side

Full

altit

ude

Rod

End

III4

Dyn

amic

Onl

ine

$7Im

poss

ible

——

Very

smal

lR

o dE

ndIV

3D

ynam

icO

nlin

e$5

-6E

asy

Som

ewha

tea

syV e

rtic

ally

from

horiz

onto

alm

ost

zeni

th∼

30◦

azim

uth

Full

altit

ude

Solid

Bac

kC

hair4

Stat

icA

rtic

les

arou

ndho

use

$0D

ifficu

ltV e

rydi

fficu

ltN

ear

horiz

onF u

llaz

imut

h∼

45◦

altit

ude

Strin

g4St

atic

orD

ynam

icH

ardw

are

stor

es/

Art

icle

sar

ound

hous

e$0

-2So

mew

hat

diffi

cult

Fairl

ydi

fficu

ltM

ost

ofsk

yif

prop

erly

posi

tione

dSm

alla

zim

uth

Smal

lalti

tude

Suct

ion

cup3

Stat

icH

ardw

are

stor

es$2

-3Ve

ryea

sySo

mew

hat

diffi

cult

From

altit

ude

60◦

toho

rizon

Smal

lazi

mut

h∼

60◦

altit

ude

Zeni

thM

ount

3D

ynam

icH

ardw

are

stor

es/

Onl

ine

$5-6

Eas

yFa

irly

easy

Zeni

than

dsu

rrou

ndin

gar

eas

∼30

◦in

alld

irect

ions

1In

dica

tes

high

lyre

com

men

ded

mou

ntin

gsy

stem

s2In

dica

tes

reco

mm

ende

dm

ount

ing

syst

ems

3In

dica

tes

mou

ntin

gsy

stem

sre

com

men

ded

with

rese

rvat

ions

4In

dica

tes

mou

ntin

gsy

stem

sth

atar

eno

tre

com

men

ded

PUBLICATIONS

Annual Report 2011 REU Site Program at KPNO

75

KPNO REU Students at the 217rd AAS Meeting

January 2011

The opportunity to present the findings of their original research at the most important national meeting of US astronomy is arguably one of the most prized benefits enjoyed by KPNO REU students. All six of the 2010 summer students attended the 215th meeting of the American Astronomical Society (AAS) January 9 – 13, 2011 at Seattle, Washington. All six students were the presenting authors on posters incorporating aspects of their REU summer research projects. Abstracts of the REU papers were published in the Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011. The abstracts of the REU student posters are reproduced below. Effects Of Light Pollution On The Movements Of Leptonycteris Curasoae Yerbabuenae In The Tucson Area Daniel Barringer (Union College), C. Walker (NOAO) Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011 [poster # 349.07] We used data from the GLOBE at Night project and telemetry tracking data of lesser long-nosed bats obtained by the Arizona Game and Fish Department to study the effects of light pollution on the flight paths of the bats between their day roosts and night foraging areas around the city of Tucson, AZ. With the visual limiting magnitude data from GLOBE at Night, we ran a compositional analysis with respect to the bats’ flight paths to determine whether the bats were selecting for or against flight through regions of particular night sky brightness levels. We found that the bats selected for the regions in which the limiting sky magnitudes fell between the ranges of 2.8-3.0 to 3.6-3.8 and 4.4-4.6 to 5.0-5.2, suggesting that the lesser long-nosed bat can tolerate a fair degree of urbanization. We also compared this result to contour maps created with digital Sky Quality Meter data. In this presentation, we present the results from our compositional analysis with respect to the habits of the lesser long-nosed bat. For more information, please visit www.globeatnight.org. Investigating The AGN Population In Cluster Environments Across Different Wavelengths Eleanor Byler (Wellesly College), D. Norman (NOAO) Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011 [poster # 142.27] Currently, there is no complete picture of AGN formation and evolution in galaxy clusters. A general understanding of the AGN population has been impeded by cluster and selection biases and recent studies have shown that there is a large population of obscured or optically unremarkable AGN in galaxy clusters. We used SDSS data to look at the AGN distribution in 12 clusters over a range of redshifts (z = 0.16 - 0.35) and compared the optical and X-ray AGN content with that of six ‘blank’ fields. We found that on average the cluster fields had a small optical AGN excess as compared to blank fields. The AGN population and distribution was also compared by cluster morphology, and non-virialized clusters were found to have a higher X-ray and optical AGN content than virialized clusters. We also compare our optical AGN to Gilmour et al.’s (2009) X-ray survey to compare assumptions made about cluster membership. Byler was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program, which is funded by the

PUBLICATIONS

Annual Report 2011 REU Site Program at KPNO

76

National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF. The CNO Bi-cycle in the Open Cluster NGC 752 Keith Hawkins (Ohio University), S. Schuler (NOAO), J. King (Clemson Univerisity), L. The (Clemson University) Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011 [poster # 242.14] The CNO bi-cycle is the primary energy source for main sequence stars more massive than the sun. To test our understanding of stellar evolution models using the CNO bi-cycle, we have undertaken light-element (CNO) abundance analysis of three main sequence dwarf stars and three red giant stars in the open cluster NGC 752 utilizing high resolution (R ~ 50,000) spectroscopy from the Keck Observatory. Preliminary results indicate, as expected, there is a depletion of carbon in the giants relative to the dwarfs. Additional analysis is needed to determine if the amount of depletion is in line with model predictions, as seen in the Hyades open cluster. Oxygen abundances are derived from the high-excitation O I triplet, and there is a 0.19 dex offset in the [O/H] abundances between the giants and dwarfs which may be explained by non-local thermodynamic equilibrium (NLTE), although further analysis is needed to verify this. The standard procedure for spectroscopically determining stellar parameters used here allows for a measurement of the cluster metallicity, [Fe/H] = 0.04 ± 0.02. In addition to the Fe abundances we have determined Na, Mg, and Al abundances to determine the status of other nucleosynthesis processes. The Na, Mg and Al abundances of the giants are enhanced relative to the dwarfs, which is consistent with similar findings in giants of other open clusters. Support for K. Hawkins was provided by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF. The Extreme Red: Characterizing LSST's Y3 and Y4 Filters Michelle Kislak (U. California – Berkeley), C. Claver (NOAO), V. Krabbendam (NOAO), T. Axelrod (U. Arizona) Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011 [poster # 334.11]

One of the essential science requirements of the Large Synoptic Survey Telescope lies in its high standard for photometric precision for both photometry and photometric redshift calculation. To capture rest-frame optical spectral features in high-redshift sources, the survey will use a variant of the Y band, which encompasses the reddest hundred nanometers before the Silicon response function cut-off. However, a significant data calibration challenge presents itself with this region of wavelength space: a strongly varying water absorption feature is present directly in the midst of it. In light of this, the survey has proposed two versions of the Y filter, a broad Y4 that includes the

PUBLICATIONS

Annual Report 2011 REU Site Program at KPNO

77

water band and a narrower Y3 that excludes it. In an effort to determine whether the wider filter is characterizable, we undertook an observing campaign with a 4k x 4k ccd camera on the 1.2m Calypso telescope on Kitt Peak to directly compare the properties of the two filters. We present preliminary analysis of this data and the conclusions that can be made from it. This research was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.

A Photometric Survey of Ori OB1b Allison T. Merritt (U. California – Berkeley), W. Sherry (NSO) Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011 [poster # 242.10] Several mechanisms have been suggested to describe the formation of sub-stellar mass objects (SSMOs), specifically brown dwarfs. Each proposed mechanism predicts a unique spatial distribution of the brown dwarfs relative to the O and B stars of the association. We have 9 square degrees of optical (VRI) data and 7 square degrees of NIR (JHK) data of Orion OB1b. The purpose of the survey is to obtain the photometric data that will allow us to determine the spatial distribution of brown dwarfs in this region and constrain the various formation theories. We present an overview of the survey, with an emphasis on the NIR data, as well as color-magnitude diagrams. This research was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF. Parameterizing and Modeling Eclipsing Binaries in The Kepler Field Using Kepler Quarter 2 and 3 Data Sean Morrison (Appalachian State University), K. Mighell (NOAO), S. Howell (NOAO), D. Bradstreet (Eastern University) Bulletin of the American Astronomical Society, Vol. 43, No. 2, 2011 [poster # 140.15] We present a preliminary analysis of Quarter 2 and Quarter 3 Kepler light curves for 56 eclipsing binary star systems from the Kepler Cycle 1 program 08-KEPLER08-0014, "A Calibration Study of Variable Stars in the Kepler Field" (PI: Mighell). We developed a C program to phase these long cadence (30 minute) data that determines the period and zero point with a typical precision of 0.0864 seconds for an orbital period of 1.019949 days. We have developed 3D models of the systems using Binary Maker 3 (BM3) by David Bradstreet. Spectra of 32 of the systems were obtained at the Kitt Peak National Observatory 2.1 m telescope using the GoldCam spectrometer. We have determined temperatures for some of the stars from the temperature ratios, based on the BM3 models, and the average temperatures for the spectral classifications of the stars which were derived from the 2.1-m spectra. The high photometric precision of the Kepler light curves allows us to identify significant star spots on a subset of the systems. Morrison was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the

PUBLICATIONS

Annual Report 2011 REU Site Program at KPNO

78

National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF. Barringer, D., Walker, C. E., Pompea, S. M., & Sparks, R. T. 2011, Earth and Space Science: Making Connections in Education and Public Outreach, 443, 373, “Astronomy Meets the Environmental Sciences: Using GLOBE at Night Data”