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Record W2735789488 · doi:10.1103/physrevd.95.082002

Projected sensitivity of the SuperCDMS SNOLAB experiment

2017· article· en· W2735789488 on OpenAlexafffund
R. Agnese, A. J. Anderson, T. Aramaki, I. J. Arnquist, W. Baker, D. Barker, R. Basu Thakur, D. Bauer, A. W. Borgland, M. A. Bowles, P. L. Brink, R. Bunker, Blas Cabrera, D. O. Caldwell, R. Calkins, C. Cartaro, D. G. Cerdeño, H. Chagani, Y. Chen, J. Cooley, Bruce Cornell, P. Cushman, M. Daal, P. C. F. Di Stefano, T. Doughty, Luis Esteban, S. Fallows, E. Figueroa‐Feliciano, M. Fritts, G. Gerbier, M. Ghaith, G. L. Godfrey, S. R. Golwala, J. Hall, H. R. Harris, T. Höfer, D. Holmgren, Z. Hong, E. W. Hoppe, L. Hsu, M. E. Huber, V. Iyer, D. Jardin, A. Jastram, M. H. Kelsey, A. Kennedy, A. Kubik, Noah Kurinsky, A. Leder, B. Loer, E. Lopez Asamar, P. Lukens, R. Mahapatra, V. Mandic, N. Mast, N. Mirabolfathi, R. A. Moffatt, J. D. Morales Mendoza, J. L. Orrell, S. M. Oser, K. Page, W. A. Page, R. Partridge, M. Pepin, A. Phipps, S. S. Poudel, M. Pyle, H. Qiu, W. Rau, P. Redl, A. Reisetter, A. Roberts, Alan Robinson, H. E. Rogers, T. Saab, B. Sadoulet, J. Sander, K. Schneck, R. W. Schnee, B. Serfass, D. Speller, M. Stein, John Street, Hidetaka TANAKA, D. Toback, R. Underwood, A. N. Villano, B. von Krosigk, B. Welliver, Jennifer Wilson, D. H. Wright, S. Yellin, J. J. Yen, B. A. Young, X. Zhang, X. Zhao

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaQueen's University
FundersSLAC National Accelerator LaboratoryPacific Northwest National LaboratoryNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyFermilabBattelleNational Science Foundation
KeywordsPhysicsDark matterDetectorNuclear physicsSemiconductor detectorSensitivity (control systems)RecoilParticle physicsOpticsElectronic engineering

Abstract

fetched live from OpenAlex

SuperCDMS SNOLAB will be a next-generation experiment aimed at directly detecting low-mass particles (with masses $\ensuremath{\le}10\text{ }\text{ }\mathrm{GeV}/{\mathrm{c}}^{2}$) that may constitute dark matter by using cryogenic detectors of two types (HV and iZIP) and two target materials (germanium and silicon). The experiment is being designed with an initial sensitivity to nuclear recoil cross sections $\ensuremath{\sim}1\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}43}\text{ }\text{ }{\mathrm{cm}}^{2}$ for a dark matter particle mass of $1\text{ }\text{ }\mathrm{GeV}/{\mathrm{c}}^{2}$, and with capacity to continue exploration to both smaller masses and better sensitivities. The phonon sensitivity of the HV detectors will be sufficient to detect nuclear recoils from sub-GeV dark matter. A detailed calibration of the detector response to low-energy recoils will be needed to optimize running conditions of the HV detectors and to interpret their data for dark matter searches. Low-activity shielding, and the depth of SNOLAB, will reduce most backgrounds, but cosmogenically produced $^{3}\mathrm{H}$ and naturally occurring $^{32}\mathrm{Si}$ will be present in the detectors at some level. Even if these backgrounds are 10 times higher than expected, the science reach of the HV detectors would be over 3 orders of magnitude beyond current results for a dark matter mass of $1\text{ }\text{ }\mathrm{GeV}/{\mathrm{c}}^{2}$. The iZIP detectors are relatively insensitive to variations in detector response and backgrounds, and will provide better sensitivity for dark matter particles with masses $\ensuremath{\gtrsim}5\text{ }\text{ }\mathrm{GeV}/{\mathrm{c}}^{2}$. The mix of detector types (HV and iZIP), and targets (germanium and silicon), planned for the experiment, as well as flexibility in how the detectors are operated, will allow us to maximize the low-mass reach, and understand the backgrounds that the experiment will encounter. Upgrades to the experiment, perhaps with a variety of ultra-low-background cryogenic detectors, will extend dark matter sensitivity down to the ``neutrino floor,'' where coherent scatters of solar neutrinos become a limiting background.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.402
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations291
Published2017
Admission routes2
Has abstractyes

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