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Light dark matter in LUX

A. Manalaysay, May 30, 2015 8

Bob Jacobsen PI, Professor

Murdock Gilchriese Senior Scientist

Kevin Lesko Senior Scientist

Peter Sorensen Scientist

Victor Gehman Scientist

Attila Dobi Postdoc

Daniel Hogan Graduate Student

Mia Ihm Graduate Student

Kate Kamdin Graduate StudentKelsey Oliver-Mallory Graduate Student

The LUX CollaborationRichard Gaitskell PI, Professor

Simon Fiorucci Research Associate

Samuel Chung Chan Graduate Student

Dongqing Huang Graduate Student

Will Taylor Graduate Student

Casey Rhyne Graduate Student

James Verbus Graduate Student

Brown

Thomas Shutt PI, Professor

Dan Akerib PI, Professor

Kim Palladino Project Scientist

Tomasz Biesiadzinski Research Associate

Christina Ignarra Research Associate

Wing To Research Associate

Rosie Bramante Graduate Student

Wei Ji Graduate Student

T.J. Whitis Graduate Student

SLAC Nation Accelerator Laboratory

Lawrence Berkeley + UC Berkeley

Adam Bernstein PI, Leader of Adv. Detectors Grp.

Kareem Kazkaz Staff Physicist

Brian Lenardo Graduate Student

Lawrence Livermore

Xinhua Bai PI, Professor

Doug Tiedt Graduate Student

SD School of Mines

James White † PI, Professor

Robert Webb PI, Professor

Rachel Mannino Graduate Student

Paul Terman Graduate Student

Texas A&M

Mani Tripathi PI, Professor

Britt Hollbrook Senior Engineer

John Thmpson Development EngineerDave Herner Senior Machinist

Ray Gerhard Electronics Engineer

Aaron Manalasay Postdoc

Scott Stephenson Postdoc

James Moard Graduate Student

Sergey Uvarov Graduate Student

Jacob Cutter Graduate Student

University of Maryland

Carter Hall PI, Professor

Richard Knoche Graduate Student

Jon Balajthy Graduate Student

Frank Wolfs PI, Professor

Wojtek Skutski Senior Scientist

Eryk Druszkiewicz Graduate Student

Dev Ashish Khaitan Graduate Student

Mongkol Moongweluwan Graduate Student

University of Rochester

Dongming Mei PI, Professor

Chao Zhang Postdoc

Angela Chiller Graduate Student

Chris Chiller Graduate Student

University of South Dakota

Daniel McKinsey PI, Professor

Ethan Bernard Research Scientist

Markus Horn Research Scientist

Blair Edwards Postdoc

Scott Hertel Postdoc

Kevin O’Sullivan Postdoc

Elizabeth Boulton Graduate Student

Nicole Larsen Graduate Student

Evan Pease Graduate Student

Brian Tennyson Graduate Student

Lucie Tvrznikova Graduate Student

Yale

LIP Coimbra

Isabel Lopes PI, Professor

Jose Pinto da Cunha Assistant Professor

Vladimir Solovov Senior Researcher

Francisco Neves Auxiliary Researcher

Alexander Lindote Postdoc

Claudio Silva Postdoc

UC Santa Barbara

Harry Nelson PI, Professor

Mike Witherell Professor

Susanne Kyre Engineer

Dean White Engineer

Carmen Carmona Postdoc

Scott Haselschwardt Graduate Student

Curt Nehrkorn Graduate Student

Melih Solmaz Graduate Student

Henrique Araujo PI, Reader

Tim Sumner Professor

Alastair Currie Postdoc

Adam Bailey Graduate Student

Khadeeja Yazdani Graduate Student

Imperial College London

Chamkaur Ghag PI, Lecturer

Lea Reichhart Postdoc

Sally Shaw Graduate Student

University College London

Alex Murphy PI, Reader

Paolo Beltrame Research Fellow

James Dobson Postdoc

Maria Francesca Marzioni Graduate Student

Tom Davison Graduate Student

University of Edinburgh

David Taylor Project Engineer

Mark Hanhardt Support Scientist

SDSTA

1

Matthew Szydagis PI, Professor

Jeremy Mock Postdoc

Steven Young Graduate Student

SUNY at Albany

UC Davis

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OSOS

Decreasing this response cutoff from 3 keV to < 1 keV Decreasing this response cutoff from 3 keV to < 1 keV provides access to a factor of 8000 more signal at Decreasing this response cutoff from 3 keV to < 1 keV provides access to a factor of 8000 more signal at provides access to a factor of 8000 more signal at MDecreasing this response cutoff from 3 keV to < 1 keV Decreasing this response cutoff from 3 keV to < 1 keV Decreasing this response cutoff from 3 keV to < 1 keV

MMMM = 6 GeV

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2

duced via Bremsstrahlung, Compton scattering, axio-recombination and axio-deexcitation [10] (referred to assolar axions). Additionally, searches can be conducted forALPs that may have been generated via a non-thermalproduction mechanism in the early universe and whichnow constitute the dark matter in our galaxy (referredto as galactic ALPs).

Axions and ALPs may give rise to observable signa-tures in detectors through their coupling to photons(g

A�

), electrons (gAe

) and nuclei (gAN

). The couplinggAe

may be tested via scattering o↵ the electron ofa target, such as liquid xenon (LXe), through theaxio-electric e↵ect [11–15]. This process is the analogueof the photo-electric e↵ect with the absorption of anaxion instead of a photon.

We report on the first axion searches performed withthe XENON100 detector. The expected interaction rateis obtained by the convolution of the flux and the axio-electric cross section. The latter is given, both for QCDaxions and ALPs, by

�Ae

= �pe

(EA

)gAe

2

�A

3EA

2

16⇡ ↵em

me

2

1� �2/3

A

3

!, (1)

as described in [12–16]. In Eq. 1, �pe

is the photoelectriccross section for LXe [17], E

A

is the axion energy, ↵em

isthe fine structure constant, m

e

is the electron mass, and�A

is the axion velocity over the speed of light, c.

The solar axion flux has recently been recalculatedin [10]. This incorporates four production mechanismsthat depend upon g

Ae

: Bremsstrahlung, Compton scat-tering, atomic recombination, and atomic deexcitation.The corresponding flux is 30% larger than previous es-timates due to atomic recombination and deexcitation,which were not previously taken into account. However,[10] does not include corrections for axions with a masslarger than 1 keV/c2, which constitutes an upper masslimit for our analysis. For solar axions, both flux andcross-section depend upon g2

Ae

, thus the interaction ratescales with the fourth power of the axion-electron cou-pling.

For non-relativistic ALPs in the galaxy, assumingthat they constitute the whole dark matter halo density(⇢

DM

⇠ 0.3 GeV/cm3 [18]), the total flux is given by�ALP = c�

A

⇥ ⇢DM

/mA

, where mA

is the ALP mass.The interaction rate for these ALPs depends on g2

Ae

,as the flux is independent from the axion coupling. As�A

⇡ 10�3 in the non-relativistic regime, the velocitiescancel out in the convolution between �

Ae

and the flux.Thus the expected electron recoil spectrum is indepen-dent from the particle speed. As the kinetic energy ofthe ALPs is negligible with respect to their rest mass en-ergy, a monoenergetic peak at the axion mass is expectedin the spectrum.

II. ANALYSIS

A. XENON100

The XENON100 detector is a double-phase time pro-jection chamber with a LXe target operating at the Lab-oratori Nazionali del Gran Sasso (LNGS) in Italy. Atotal of 178 low radioactivity, UV-sensitive photomulti-plier tubes (PMTs) measure signals induced by particlesinteracting in the sensitive volume, which contains 62 kgof ultra-pure LXe. An energy deposition in the detectorproduces both scintillation photons and ionization elec-trons. The electrons, moved from the interaction pointby a drift field of 530 V/cm, are extracted from the liquidand accelerated in the gas by a 12 kV/cm field, producingproportional scintillation light. The direct scintillationsignal (S1) and the amplified charge signal (S2) are de-tected by the PMTs. The time di↵erence between the S1and the S2 signals is used to estimate the z-coordinate ofthe interaction, while the S2-hit-pattern on the PMTs isemployed to estimate the (x , y) - coordinate. A detaileddescription of the instrument and its operational princi-ple is given in [19].

The XENON100 detector is installed at LNGS, at anaverage depth of 3600m water equivalent, where themuon flux is suppressed by six orders of magnitude withrespect to sea level. Due to a careful selection of materi-als, the total background in the inner 34 kg fiducial vol-ume is 5.3⇥ 10�3 events/(keV ⇥ kg ⇥ day) [20, 21]. Thisultra low background makes XENON100 sensitive to rareevent searches in general, and in particular for those pro-ducing electronic recoils (ER), as is the case for axions.

B. Data sample and analysis

In this work, we analyse the same data set used for thespin-independent [20] and spin-dependent [22] WIMP-searches, with an exposure of 224.6 live days and 34 kgfiducial mass. Detailed information on the analysis pro-cedure is available in [23]. The same quality and selectioncuts are applied, with the exception of a consistency cuton the S2 width, which was found to be not useful forthis ER analysis.

Fig.1 (top) shows the distribution in the log10(S2b/S1)vs.S1 for calibration data (grey dots), and the sciencedata passing all the selection cuts (black dots), whereonly the S2 signal detected by the bottom PMTs, S2

b

, isused since it requires smaller corrections [19]. The cali-bration data is obtained by exposing the detector to 60Coand 232Th sources. The mean of the log10(S2b/S1) bandfrom the calibration is subtracted in order to remove theenergy-dependence of this parameter. The lower energythreshold was set to 3 photoelectrons (PE) in S1 in orderto limit the presence of random coincidences from darkcounts in the PMTs. In addition, a lower threshold of150 PE in S2 has been imposed to be una↵ected by thetrigger threshold [23]. In order to reject ER events with

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The data are compatible with the background model,and no excess is observed for the background onlyhypothesis.Figure 5 shows the new XENON100 exclusion limit on

gAe at 90% C.L. The sensitivity is shown by the green/yellow band (1σ=2σ). As we used the most recent andaccurate calculation for solar axion flux from [10], which isvalid only for light axions, we restrict the search tomA < 1 keV=c2. For comparison, we also present otherrecent experimental constraints [31–33]. Astrophysical

bounds [34–36] and theoretical benchmark models [4–7]are also shown. For solar axions with masses below1 keV=c2, XENON100 is able to set the strongest con-straint on the coupling to electrons, excluding values of gAelarger than 7.7 × 10−12 (90% C.L.).For a specific axion model, the limit on the dimension-

less coupling gAe can be translated to a limit on the axionmass. Within the DFSZ and KSVZ models [4–7],XENON100 excludes axion masses above 0.3 eV=c2

and 80 eV=c2, respectively. For comparison, the CASTexperiment, testing the coupling to photons, gAγ , hasexcluded axions within the KSVZ model in the mass rangebetween 0.64 and 1.17 eV=c2 [37,38].

B. Galactic ALPs

Figure 6 shows the XENON100 data after the selectioncuts in the larger energy region of interest used for thesearch for nonrelativistic galactic ALPs (1422 survivingevents), along with their statistical errors. Also shown is theexpected signal for different ALP masses, assuming acoupling of gAe ¼ 4 × 10−12 and that ALPs constitute allof the galactic dark matter. The width of the monoenergeticsignal is given by the energy resolution of the detector at therelevant S1 signal size [19]. As for the solar axion search,the data are compatible with the background hypothesis,and no excess is observed for the background-only hypoth-esis for the various ALP masses.The XENON100 90% C.L. exclusion limit for galactic

ALPs is shown in Fig. 7, together with other experimentalconstraints [31,39,40]. Astrophysical bounds [34–36] andthe KSVZ benchmark model [6,7] are also presented.The expected sensitivity is shown by the green/yellowbands (1σ=2σ). The steps in the sensitivity around 5 and35 keV=c2 reflect the photoelectric cross section due to

S1 [PE]0 5 10 15 20 25 30

Eve

nts/

PE

1

10

210

1 2.5 5 7.5 10Expected Mean Recoil Energy [keV]

FIG. 4 (color online). Event distribution of the data (black dots)and background model (grey) of the solar axion search. Theexpected signal for solar axions withmA < 1 keV=c2 is shown bythe dashed blue line, assuming gAe ¼ 2 × 10−11, the current bestlimit, from EDELWEISS-II [31]. The vertical dashed red lineindicates the low S1 threshold, set at three PE. The top axisindicates the expected mean energy for ERs as derived from theobserved S1 signal.

]2 [keV/cAm

-510 -410 -310 -210 -110 1

Ae

g

-1310

-1210

-1110

-1010

-910

νSolar

Red giant

Si(Li)

XMASS

EDELWEISS

DFSZ

KSVZXENON100

FIG. 5 (color online). The XENON100 limits (90% C.L.) onsolar axions are indicated by the blue line. The expectedsensitivity, based on the background hypothesis, is shown bythe green/yellow bands ð1σ=2σÞ around the XENON100 limits.Results by EDELWEISS-II [31] and XMASS [32] are shown,together with the ones from a Si(Li) detector by Derbin et al. [33].Indirect astrophysical bounds from solar neutrinos [34] and redgiants [35] are represented by light grey horizontal lines. Thebenchmark DFSZ and KSVZ models are represented by darkgrey lines [4–7].

S1 [PE]0 10 20 30 40 50 60 70 80 90 100

Eve

nts/

PE

1

10

210

1 5 10 15 20 25 30 35Expected Mean Recoil Energy [keV]

21 keV/c

25 keV/c28 keV/c 210 keV/c

215 keV/c220 keV/c

230 keV/c

FIG. 6 (color online). Event distribution in the galactic ALPssearch region between 3 and 100 PE (black dots with error bars).The grey line shows the background model used for the profilelikelihood function. The vertical dashed red line indicates the S1threshold. The expected signal in XENON100 for various ALPmasses, assuming gAe ¼ 4 × 10−12, is shown as blue dashedpeaks. The top axis indicates the expected mean energy for ERsas derived from the observed S1 signal.

FIRST AXION RESULTS FROM THE XENON100 EXPERIMENT PHYSICAL REVIEW D 90, 062009 (2014)

062009-5

!70/U%I'.U%>%eP%DSPO`E%PaSPPe

the atomic energy levels. Below 5 keV=c2 the obtained90% C.L. is higher than expected, deviating by as much as2σ from the mean predicted sensitivity. This is due to aslight excess of events between 3 and 5 PE. A similar effectis responsible for the limit oscillating around the predictedsensitivity above 5 keV=c2. The ALP limit is very sensitiveto fluctuations in individual bins because of the expectedmonoenergetic signal. In the 5–10 keV=c2 mass range,XENON100 sets the best upper limit, excluding an axion-electron coupling gAe > 1 × 10−12 at the 90% C.L., assum-ing that ALPs constitute all of the galactic dark matter.The impact of systematic uncertainties has been evalu-

ated for both analyses presented here. In particular, we haveconsidered the parametrization of the cross section ofthe axioelectric effect, the data selection based on a band

in the log10ðS2b=S1Þ vs S1 space, the choice of the fiducialvolume, as well as the conversion of the S1 signal into anER energy and the energy resolution.Previous works (e.g., [15,32]) have used a different

parametrization of the axion velocity term in σA, while wechose to employ ð1 − β2=3A =3Þ [Eq. (1)], as suggested by[31]. However, we also tested the other assumptions andfound the impact on the final limit to be negligible.Varying the width of the band chosen to select the data

entering the analysis [shown in Fig. 1 (top) as horizontaldashed red lines] from #1σ up to #4σ changes the finalresult on gAe by 5%, i.e., well within the #2σ of thesensitivity band.Similarly, a variation of the fiducial volume has a

negligible impact on the sensitivity: the inner ellipsoidwas changed in size to accomodate between 28 and 40 kg,but maintaining the same 224.6 days of live time. Thereduced background for smaller fiducial masses is com-pensated by the smaller total exposure, resulting in avariation of the limit well below 10%.The uncertainty on the energy scale used for the

conversion from the observed S1 signal in PE into keV[Fig. 2 and Eq. (2)] is taken into account in the profilelikelihood function and is profiled out via the nuisanceparameter t [Eq. (5)]. The detector’s energy resolution isconsidered by smearing the predicted energy spectrumdR=dE by Poisson and Gaussian processes, as described inEq. (7). We note that the final results on gAe are also robustagainst further changes in the energy scale: even if LYðEÞ,as defined in Eq. (2), is varied by 25%, the limits change byless than 5% and about 10% for the solar and for thegalactic axion searches, respectively.

ACKNOWLEDGMENTS

We gratefully acknowledge support from NSF, DOE,SNF, Volkswagen Foundation, FCT, Region des Pays de laLoire, STCSM, NSFC, DFG, MPG, Stichting voorFundamenteel Onderzoek der Materie (FOM), theWeizmann Institute of Science, the EMG research center,and INFN. We are grateful to LNGS for hosting andsupporting XENON100.

[1] R. D. Peccei and H. R. Quinn, Phys. Rev. Lett. 1440, 38(1977).

[2] S. Weinberg, Phys. Rev. Lett. 40, 223 (1978).[3] F. Wilczeck, Phys. Rev. Lett. 40, 279 (1978).[4] M. Dine, W. Fischler, and M. Srednicki, Phys. Lett. 104B,

199 (1981).[5] A. R. Zhitnitsky, Sov. J. Nucl. Phys. 31, 260 (1980).[6] J. E. Kim, Phys. Rev. Lett. 43, 103 (1979).

[7] M. A. Shifman, A. I. Vainshtein, and V. I. Zakharov, Nucl.Phys. B166, 493 (1980).

[8] L. Abbott and P. Sikivie, Phys. Lett. 120B, 133(1983).

[9] P. Sikivie, Phys. Rev. Lett. 51, 1415 (1983).[10] J. Redondo, J. Cosmol. Astropart. Phys. 12 (2013) 008.[11] S. Dimopoulos, G. D. Starkman, and B.W. Lynn, Phys. Rev.

B 168, 145 (1986).

]2 [keV/cAm1 2 3 4 5 6 7 8 910 20 30

Ae

g

-1310

-1210

-1110

-1010

-910

KSVZ

νSolar

CDMSCoGeNT EDELWEISS

XENON100

FIG. 7 (color online). The XENON100 limits (90% C.L.) onALP coupling to electrons as a function of the mass, under theassumption that ALPs constitute all of the dark matter in ourgalaxy (blue line). The expected sensitivity is shown by the green/yellow bands 1σ=2σ. The other curves are constraints set byCoGeNT [39] (light brown dashed line), CDMS [40] (bluedashed line, more dotted), and EDELWEISS-II [31] (ochredashed line, extending up to 40 keV=c2). Indirect astrophysicalbound from solar neutrinos [34] is represented as a continuouslight grey line. The benchmark KSVZ model is represented by adark grey line [6,7].

E. APRILE et al. PHYSICAL REVIEW D 90, 062009 (2014)

062009-6

1 keVee , allowing ER band (Fig. 3) and detection effi-ciency calibrations (Fig. 1) with unprecedented accuracy;the tritiated methane is subsequently fully removed bycirculating the xenon through the getter.A 83mKr injection was performed weekly to determine

the free electron lifetime and the three-dimensional cor-rection functions for photon detection efficiency, whichcombine the effects of geometric light collection and PMTquantum efficiency (corrected S1 and S2). The 9.4 and32.1 keV depositions [22] demonstrated the stability ofthe S1 and S2 signals in time, the latter confirmed withmeasurements of the single extracted electron response.131mXe and 129mXe (164 and 236 keV deexcitations)afforded another internal calibration, providing a cross-check of the photon detection and electron extractionefficiencies. To model these efficiencies, we employedfield- and energy-dependent absolute scintillation andionization yields from NEST [23–25], which provides anunderlying physics model, not extrapolations, where onlydetector parameters such as photon detection efficiency,electron extraction efficiency and single electron responseare inputs to the simulation. Using a Gaussian fit to thesingle phe area [26], together with the S1 spectrum oftritium events, the mean S1 photon detection efficiencywas determined to be 0.14! 0.01, varying between 0.11and 0.17 from the top to the bottom of the active region.This is estimated to correspond to 8.8 phe=keVee (electron-

equivalent energy) for 122 keV γ rays at zero field [23].This high photon detection efficiency (unprecedented in axenon WIMP-search TPC) is responsible for the lowthreshold and good discrimination observed [27].Detector response to ER and NR calibration sources is

presented in Fig. 3. Comparison of AmBe data withsimulation permits extraction of NR detection efficiency(Fig. 1), which is in excellent agreement with that obtainedusing other data sets (252Cf and tritium). We describe thepopulations as a function of S1 (Figs. 3 and 4), as thisprovides the dominant component of detector efficiency.We also show contours of approximated constant-energy[28], calculated from a linear combination of S1 and S2[24,27,29] generated by converting the measured pulse areasinto original photons and electrons (given their efficiencies).A parameterization (for S2 at a given S1) of the ER band

from the high-statistics tritiumcalibration is used to character-ize the background. In turn, the NR calibration is morechallenging, partly due to the excellent self-shielding of thedetector. Neutron calibrations therefore include systematiceffects not applicable to the WIMP signal model, such asmultiple-scattering events (including those where scattersoccur in regions of differing field) or coincident Comptonscatters fromAmBeand 252Cf γ raysand(n,γ) reactions.Theseeffects produce the dispersion observed in data, which is wellmodeled in our simulations (in both band mean and width,verifying the simulatedenergy resolution), and larger than thatexpected from WIMP scattering. Consequently, these datacannot be used directly to model a signal distribution. FordifferentWIMPmasses, simulatedS1 andS2 distributions areobtained, accounting for their unique energy spectra.The ratio of keVee to nuclear recoil energy (keVnr) relies

on both S1 and S2, using the conservative techniquepresented in [29] (Lindhard with k ¼ 0.110, compared tothe default Lindhard value of 0.166 and the implied best-fit

0 10 20 30 40 501

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

log 10

(S2 b/S

1) x

,y,z

cor

rect

ed

S1 x,y,z corrected (phe)

3 6 9 12 15 18 21 24 27 30 keVnr

1.3

1.8

3.5

4.65.9

7.1

keVee

FIG. 4 (color online). The LUX WIMP signal region. Events inthe 118 kg fiducial volume during the 85.3 live-day exposure areshown. Lines as shown in Fig. 3, with vertical dashed cyan linesshowing the 2–30 phe range used for the signal estimation analysis.

1

1.5

2

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1) x

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0 10 20 30 40 50

1

1.5

2

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S1 x,y,z corrected (phe)

36 9 12 15 18 21 24 27keV

nr

(b) AmBe and Cf 252 NR Calibration

FIG. 3 (color online). Calibrations of detector response in the118 kg fiducial volume. The ER (tritium, panel (a) and NR(AmBe and 252Cf, panel (b)) calibrations are depicted, with themeans (solid line) and !1.28σ contours (dashed line). Thischoice of band width (indicating 10% band tails) is for presen-tation only. Panel (a) shows fits to the high statistics tritium data,with fits to simulated NR data shown in panel (b), representingthe parameterizations taken forward to the profile likelihoodanalysis. The ER plot also shows the NR band mean and viceversa. Gray contours indicate constant energies using an S1-S2combined energy scale (same contours on each plot). The dot-dashed magenta line delineates the approximate location of theminimum S2 cut.

PRL 112, 091303 (2014) P HY S I CA L R EV I EW LE T T ER Sweek ending

7 MARCH 2014

091303-4


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