Recent Results & Current Status of C RYOGENIC D ARK M ATTER S EARCH Rupak Mahapatra Univ. of California Santa Barbara APS-DPF JPS 2006, Hawaai

     00                     00         What Nature has to Offer Background Rejections ‘R’ Us Action Plan: Reduce and Reject …

Outline Motivation & Candidates: Astro + Particle Detection Principles: Signal & Background CDMS Background Reduction & Rejection Results from 1 and 2 Tower Runs 5-Tower CDMS Run and Current Status

Motivation: Galactic Rotation Curves Is there mass where there is no light? …Dark Matter M m Use light as a guide for mass Expect v 2  1/r bad fit to data

Standard Model? In thermal equilibrium after Big Bang. Non- relativistic. Metals (us)  0.01% Visible Baryons0.5% Dark Baryons 4% Cold Dark Matter (WIMPs?) 23% Cosmological Constant Dark Energy  73% A New Order Has Been Declared….

Clue or Coincidence? Galactic Astrophysics Big Bang Standard Model Weak Scale Supersymmetry 00 Current abundance is related to annihilation cross section to our matter 00 00 q, l,    0  1/  ann  ann ~ weak gives   0 = ¼ observed SUSY restored at Weak Scale gives rise to LSP (  0 ) with weak interaction with matter

Design a Particle and an Experiment Neutral: 1) cool particles neutral – , n,, K 0, Z 0, H 0 … 00 Massive: 1) M  c 2  100 GeV hinted at by accelerator data `Weak Scale’ v/c =   0.7  We use Germanium, A=73, mc 2 =72 GeV; others: Si, S, I, Xe, W E R  ½ m Ge c 2  2  ½ 72 GeV  ½   20 keV  x-ray energy ! Easy! v/c =   0.7  10 -3

Catalog of Recoil Experiments Rick Gaitskell

Traditional Ionization Detector Germanium Electrode Implants E  00 E R  10’s keV 1 cm 7.6 cm Holes e-e- ¼ kg What rate? (in, say, 1kg) Backgrounds? ….…. Gamma rays, neutrons, surface beta-decay

Rate governed by scattering cross section 

What is the weak interaction cross section? Donald H. Perkins, 1987

Experiment CDMS (shallow) DAMA (old!) Theory SUSY, various constraints including Big Bang Gaitskell/Mandic Our Hunting Ground Weakly Interacting Massive Particle

Coherence, density of states enormous bonus! Scattering off a proton…. …. Hopeless! 00 00 Indistinguishable Density of States: Acceptable Rate. But, what about the Background rate….

Rate of Main Background Rate about 10 3 / (kg-day) !!! 10000X bigger than expected signal Strategies: DAMA… huge target mass, look for astrophysical modulation CDMS… small target mass, distinguish electron from nucl. recoil

 0 (calibrate: neutron) v/c  7  Nucleus Recoils dense energy deposition efficiency low distinct energy scale Direct Detection: Signal and Main Background Signal ErEr  v/c  0.3 Electron Recoils Background Sparse Energy Deposition ErEr Differences the Basis of Discrimination

H phonons ionization Q L scintillation CDMS, EDELWEISS CRESST II, ROSEBUD ZEPLIN II, III, MAX, XMAS, XENON NAIAD, ZEPLIN I, DAMA IGEX, DRIFTI, II CRESST I, PICASSO, COUPP Typical Discrimination Technique: Detect More than One Signal

Nuclear Recoil bad at making Ionization Germanium 00 Holes e-e-  more ionization! Both deposit, say, 20 keV Need a second, `fair’ measure of deposited energy… phonons!

CDMS Technique: Phonons v. Ionization Nuclear Recoils (neutron source) Electron Recoils (  source) Yield = Ionization Energy/Phonon Energy. Extremely Powerful Discriminant Phonon Energy: True Energy. No Loss

CDMS Detectors: ZIP `Phonon sensor (4)’ (TES) Ionization Electrodes (2) x-y-z imaging: from timing, sharing Z-coordinate, Ionization, Phonons ZIP Operate at Kelvin

The Phonon Sensor Al quasiparticle trap Al Collector W Transition-Edge Sensor (TES) Ge or Si quasiparticle diffusion phonons Cooper Pair superconducting normal T (mK) T c ~ 80mK R TES (  ) ~ 10mK

Excellent Energy, X-Y Position Reconstruction Am 241 :  14, 18, 20, 26, 60 kev Cd Al foil :  22 kev Cd 109 :  22 kev i.c. electr 63, 84 KeV Detector Calibration at Berkeley

Excellent Rejection of Primary (  ) Background Phonon Neutrons cause nuclear recoils too! Another background… Yield = Ionization/Phonon Most effective Particle ID

Background Neutrons from Cosmic Ray Muons Limited our earlier Stanford results…moved to a deep mine

Why -40 o Depth (meters water equivalent) Log 10 (Muon Flux) (m -2 s -1 ) Kamioka (Japan) Hz muons in 4 m 2 shield Kolar (India) Sudbury (Canada) Mont Blanc (France) Baksan (Russia) Oroville (USA) Boulby (UK) Frejus (France) Soudan (USA) Stanford Underground Site Gran Sasso (Italy) 1 per min

Two 40 mK!! Phonon Sensors Low Activity Lead Polyethylene µ-metal (with copper inside) Ancient lead 41 cm CDMS Outside In To further reduce neutron background and electromagnetic background: Use passive shielding –Lead and Copper for photons –Polyethylene for low- energy neutrons Surround detectors with active muon veto

CDMS Veto System 2” Thick Scintillators ~ 100% Efficient detection for through going muons ~90% Efficient detection external neutrons, due to associated hadronic showers Multiplicity trigger implemented to collect interesting muon events Ray Bunker, Joel Sander  

ZIP 1 (Ge) ZIP 2 (Ge) ZIP 3 (Ge) ZIP 4 (Si) ZIP 5 (Ge) ZIP 6 (Si) 4 K 0.6 K 0.06 K 0.02 K SQUID cards FET cards SQUID cards FET cards 14 C worse  CDMS Tower of Detectors Each tower holds 6 ZIPs Both Ge and Si for neutron background measurement: Si has higher  with N, than Ge Possible WIMP mass meas, if we see a signal Achieved much better sensitivity with Si than Ge for low mass WIMPs

Detectors Veto Scintillator Polyethylen e Lead Cable s Cry o Radioactiv e Source CDMS Geometry Characterize detector response to signal and background using neutron and gamma source, respectively Extensive calibration data throughout run Comparison with MC

 Calibration ( 133 Barium) (e  recoils) Ionization Phonons Energy, KeV Laura Baudis

Energy Calibration Ionization Phonons 275 keV ,  =2.5 keV 384  =8 keV Phonon energy resolution worse than charge at high energy due to incomplete digitization of the full pulse Walter Ogburn

n Calib. ( 252 Californium) (nuclear recoils) Reconstructed recoil energy, KeV Sharmila Kamat

Revisiting the Most Powerful Particle ID Phonon Yield = Ionization/Phonon Most effective Particle ID Rejects 99.9 % background However, still not enough! YIELDYIELD

What does real data look like? Fundamentally different background. Not tail of  distribution. Dangerous . Just like signal Few events in or near signal region. Yield rejects most Bkg ~ 1 M events

Why is  Dangerous? Name of the Game is  Reduction and Rejection  : reduced ionization collection Z Bulk  Recoil Electrons gets absorbed in the first few microns Ionization collection inefficient for surface events Yield = Ionization/Phonon => Yield low for surface events (  ) Doesn’t completely reject . Need some extra handle  background ultimately limits sensitivity of many DM experiments

Calibration: ,  and Neutron 133 Ba  calibration: Used for position and energy calibration  from 133 Ba  : Compton scattered e Cf neutrons : Signal Ionization Yield Recoil Energy (keV) 20x our WIMP-search background Yield not enough to cut all  background Need extra rejection handle to reject these  s Use Pulse Timing to advantage!

(phonon start time) 10-40% Phonon Timing  Pulse Faster Timing quantities used to suppress external electrons Ionization Pulse gives start time   A B D C

Mean has most of the info… Nuclea r Recoil s Surface Event(  ) Rejecting  with Timing Information

Improved  Rejection:  2 Formalism Better combining of discriminators Define  2 hypothesis for signal (neutron) and background (  ) from calibration data Determine how far a particular event is from the signal (rn) and from background (rb) hypothesis Define cut to delineate with desired optimum Rupak Mahapatra & Joel Sander

Surface events from calibration source neutrons from calibration source Resulting Improvement Rupak Mahapatra & Joel Sander

CDMS Blind Analysis Technique Define all cuts from Calibration Data only 252 Cf calibration (N) defines signal region 133 Ba calibration (  ) defines  as well as  Half of 133 Ba calibration is blinded! Once all cuts are defined, Blinded 133 Ba data is used for estimating efficiencies and  leakage Signal region blinded Use data side-bands after full analysis done with calibration data and cuts are frozen Estimate  leakage from side bands and compare with calibration  estimate Understand systematics Calculate expected sensitivity Un-blind. Apply  timing cut Count remaining events. These are candidates Calibration DataWIMP-search Data

WIMP-search Data Blinding

Overall Efficiencies

Improvement in low E regime tremendously improves low mass WIMP sensitivity Rupak Mahapatra & Joel Sander. Jeff Filipini Improved Si Efficiency due to  2 Formalism

15 sig. region Z2/Z3/Z5/Z9/Z11 Ionization Yield Recoil Energy (keV) Surface Electrons 1 candidate (barely) 1 near-miss Unblind: Before/After Timing Cut ESTIMATE: 0.4  0.2 (sys.)  0.2 (stat.) electron recoils 0.06 recoils from neutrons expected

Small Circles: prior to surface rejection Blue circles: passing surface rejection Star: one candidate Expected Background (7-100 keV recoil energy) Beta 0.4±0.2±0.2 for Ge and 1.2±0.6±0.2 for Si Neutron 0.06 for Ge and 0.05 for Si

New Limits (Spin Independent) Silicon: low mass 90% CL About twice more sensitive than 1-tower

00 Neutralino Z0Z0 Axial vector interaction gives spin-dependent scattering… neutron or proton Spin-Dependent Interaction

New Limits (Spin Dependent) 8% 73 Ge 5% 29 Si unpaired neutron Ge (2 nuclear models) Si Super-K Solar Zeplin-I Picasso DAMA CRESST-I NAIAD Majorana neutron proton CDMS Has SD Sensitivity Too !!! World-Best for  0 -neutron coupling Jeff Filipini

Two Papers Published This Year

Improvements –Cryogenics, backgrounds, DAQ –Currently commissioning 30 detectors in 5 towers of 6 –4.75 kg of Ge, 1.1 kg of Si to run through 2006 –Improve sensitivity x10 Installed 3 additional towers in November 04 The Near Future: 5 Towers run for 2 years in Soudan

EGRET EGRET sees Galactic WIMP annihilation? Egret - Data Background(s) (Summed)  0  0  bb

CDMS/Soudan will Confirm/Deny

Sensitivity Expectations: Far Future Harry Nelson

What about the  Background? Source of the  Background? Surface analysis and Screening techniques not sensitive to our background level of 1ppt Many dark matter experiment running deep underground are ultimately limited by the  It is important to try to identify the source and attempt to reduce the background

Search Radioactive decay lines to find Source of Contamination Co-added  Energy Spectrum Phonon Energy in keV Z12  Energy Spectrum Charge Energy in keV Counts No sig. peaks. Very weak upper limit using MC comparison Laura Baudis

Use coincidences to Cut Down Background  multiple scatters & leaves energy in adjacent dets Look for peak in shared energy. Lower combinatorics Peak in Spectrum!! Find radioactive source Rupak Mahapatra Z1 Z2  210 Pb Decay Conversion Electron Peak

Strong correlation of α-  Decay chain also has a 5.3 Mev α from 210Po  206Pb+α Strong correlation of the  rates with the α rates, detector by detector. Further establishes the genuineness of this contamination source Rupak Mahapatra, Jodi Cooley-Sekula

Exclusive 30 keV CE Signature Found 63% BR 30 keV conversion elctrons Rupak Mahapatra Recently also successful in identifying the highest branching fraction (63%) 30 keV conversion electron line. Higher background, due to combinatorics Clearly established 210 Pb as the primary  background source. Must minimize exposure to Radon.

Many Hurdles Along the Way…. 2-Tower Run Shutdown in Aug ’04 Installed Tower 3-5 Sept ’04 - Jan ’05 Many Vac. Leaks Found & Fixed Sum ’05 Excessive Elec. Noise from Cryo-Cooler Vibration Prevented Cooling down to Low Temp Installed Flexible Coupling and Cooled down to Base Temp: Winter 05. But, no Phonon Signals! Thermal Modeling Showed: Thermal Contact between Fridge and Detectors Need Improving Installed Add. Heat Sinks. Finally See Pulses in June ’06 Detectors Tuning: July/Aug. Taking Science Data Now 5-Tower Installation & Commissioning

Improved DAQ, Analysis Factor of 10 Improvement in DAQ Readout Allows for spending only 5% LiveTime on acquiring  /  Calibration Data Calibration Data Sample to be Collected: 50X WIMP-search Data, spending 1 Hr/day Improved Analysis in Pipeline to Better Reject  Significant Effort to Improve Monte Carlo Simulation & Predictions for  /Neutron Bkg.

LHC only ILC only 25 kg SCDMS Phase A Direct Detection only Excluded by Direct Detection Excluded by Accelerators Overlap c CDMS-II Soudan SuperCDMS Hits The Sweet Spot

Elements leading to increased sensitivity Thicker Detectors –Less surface/volume, factor of 2.5 Better Analysis Rejection –Better Monte Carlo, reconstruction, factor of 4 Cleaner Detectors – 210 Pb … Radon Daughter, factor of 5 Move to Deeper Site to suppress neutrons –Deeper is better, less muons, hence neutrons

Future of Dark Matter Searches Direct Detection: Critical & Complimentary to LHC Important Benchmark: Effective Mass, Not Total Mass Effectiveness depends critically on background. Understanding, reducing & rejecting background is a very slow process. Low Bkg. Expt. is typically full of surprises Jump from promise to actual result is large & difficult CDMS: Proven Technology and Demonstrated Background But, Only the Future can tell which Expt. and When the Dark Matter Candidate will be found and What it will be…

The CDMS Collaboration Stanford University P.L. Brink, B. Cabrera, J.P. Castle, C.L. Chang, J. Cooley, A. Tomada, L. Novak, R. W. Ogburn, M. Pyle, University of California, Berkeley M. Daal, J. Filippini, A. Lu, P.Meunier, N. Mirabolfathi, B. Sadoulet, D.N.Seitz, B. Serfass, G. Smith, K. Sundqvist University of California, Santa Barbara R. Bunker, D. Caldwell, D. Callahan, D. Hale, S. Kyre, R. Mahapatra, H. Nelson, J. Sander M. I. T. E. Figuerilo University of Florida T. Saab Aachen University L. Baudis Queens University W. Rau University of Minnesota J. Beaty, P. Cushman, L. Duong, X. Qiu, A. Reisetter Brown University M.J. Attisha, R.J. Gaitskell, J-P. F. Thompson Case Western Reserve University D.S. Akerib, C.N. Bailey, M.R. Dragowsky, D. Grant, R. Hennigs, R.W.Schnee University of Colorado at Denver M. E. Huber Fermi National Accelerator Laboratory D.A. Bauer, R. Choate, M.B. Crisler, R. Dixon, M. Haldeman, D. Holmgren, B. Johnson, W.Johnson, M. Kozlovsky, D. Kubik, L. Kula, B. Lambin, B. Merkel, S. Morrison, S. Orr, E. Ramberg, R.L. Schmitt, J. Williams, J. Yoo Lawrence Berkeley National Laboratory J.H Emes, R. McDonald, A. Smith Santa Clara University B.A. Young

CDMS Collaboration (Mar. 2002)