A Strategy for Low-Mass Dark Matter Searches with Cryogenic Detectors in the SuperCDMS SNOLAB Facility
SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. W. P. Amaral, T. Aralis, T. Aramaki, I. J. Arnquist, I. Ataee Langroudy, E. Azadbakht, S. Banik, C. Bath… 展开作者
SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. W. P. Amaral, T. Aralis, T. Aramaki, I. J. Arnquist, I. Ataee Langroudy, E. Azadbakht, S. Banik, C. Bathurst, D. A. Bauer, R. Bhattacharyya, P. L. Brink, R. Bunker, B. Cabrera, R. Calkins, R. A. Cameron, C. Cartaro, D. G. Cerdeno, Y. -Y. Chang, M. Chaudhuri, R. Chen, N. Chott, J. Cooley, H. Coombes, J. Corbett, P. Cushman, F. De Brienne, S. Dharani, M. L. di Vacri, M. D. Diamond, E. Fascione, E. Figueroa-Feliciano, C. W. Fink, K. Fouts, M. Fritts, G. Gerbier, R. Germond, M. Ghaith, S. R. Golwala, J. Hall, N. Hassan, B. A. Hines, M. I. Hollister, Z. Hong, E. W. Hoppe, L. Hsu, M. E. Huber, V. Iyer, A. Jastram, V. K. S. Kashyap, M. H. Kelsey, A. Kubik, N. A. Kurinsky, R. E. Lawrence, M. Lee, A. Li, J. Liu, Y. Liu, B. Loer, P. Lukens, D. B. MacFarlane, R. Mahapatra, V. Mandic, N. Mast, A. J. Mayer, H. Meyer zu Theenhausen, E. Michaud, E. Michielin, N. Mirabolfathi, B. Mohanty, S. Nagorny, J. Nelson, H. Neog, V. Novati, J. L. Orrell, M. D. Osborne, S. M. Oser, W. A. Page, R. Partridge, D. S. Pedreros, R. Podviianiuk, F. Ponce, S. Poudel, A. Pradeep, M. Pyle, W. Rau, E. Reid, R. Ren, T. Reynolds, A. Roberts, A. E. Robinson, T. Saab, B. Sadoulet, I. Saikia, J. Sander, A. Sattari, B. Schmidt, R. W. Schnee, S. Scorza, B. Serfass, S. S. Poudel, D. J. Sincavage, C. Stanford, J. Street, H. Sun, F. K. Thasrawala, D. Toback, R. Underwood, S. Verma, A. N. Villano, B. von Krosigk, S. L. Watkins, O. Wen, Z. Williams, M. J. Wilson, J. Winchell, K. Wyko, S. Yellin, B. A. Young, T. C. Yu, B. Zatschler, S. Zatschler, A. Zaytsev, E. Zhang, L. Zheng, S. Zuber
备注：
contribution to Snowmass 2021; v2 updated (assorted corrections and improvements to forecasts) October 2022; v3 updated (corrected SuperCDMS SNOLAB sensitivity curves in upgrade forecast plots in body of text) April 2023
The SuperCDMS Collaboration is currently building SuperCDMS SNOLAB, a dark matter search focused on nucleon-coupled dark matter in the 1-5 GeV/c$^2$ mass range. Looking to the future, the Collaboration has developed a set of experience-based upgrade scenarios, as well as novel directions, to extend the search for dark matter using the SuperCDMS technology in the SNOLAB facility. The experienced-based scenarios are forecasted to probe many square decades of unexplored dark matter parameter space below 5 GeV/c$^2$, covering over 6 decades in mass: 1-100 eV/c$^2$ for dark photons and axion-like particles, 1-100 MeV/c$^2$ for dark-photon-coupled light dark matter, and 0.05-5 GeV/c$^2$ for nucleon-coupled dark matter. They will reach the neutrino fog in the 0.5-5 GeV/c$^2$ mass range and test a variety of benchmark models and sharp targets. The novel directions involve greater departures from current SuperCDMS technology but promise even greater reach in the long run, and their development must begin now for them to be available in a timely fashion.
The experienced-based upgrade scenarios rely mainly on dramatic improvements in detector performance based on demonstrated scaling laws and reasonable extrapolations of current performance. Importantly, these improvements in detector performance obviate significant reductions in background levels beyond current expectations for the SuperCDMS SNOLAB experiment. Given that the dominant limiting backgrounds for SuperCDMS SNOLAB are cosmogenically created radioisotopes in the detectors, likely amenable only to isotopic purification and an underground detector life-cycle from before crystal growth to detector testing, the potential cost and time savings are enormous and the necessary improvements much easier to prototype.
Calibration and Performance of Germanium High Voltage Detectors for SuperCDMS SNOLAB
University of British Columbia（不列颠哥伦比亚大学）；University of Toronto（多伦多大学）；SLAC National Accelerator Laboratory/Kavli Institute for Particle Astrophysics and Cosmology（斯坦福直线加速器实验室/卡弗里粒子天体物理与宇宙学研究所）；Northeastern University（东北大学）；SNOLAB（斯诺拉布）；Laurentian University（劳伦森大学）；Stanford University（斯坦福大学）；Southern Methodist University（南方卫理公会大学）；University of California, Berkeley（加州大学伯克利分校）；National Institute of Science Education and Research, An OCC of Homi Bhabha National Institute（国家科学教育与研究研究所，霍米·巴巴国家研究所附属机构）；Northwestern University（西北大学）；Queen's University（女王大学）；University of Minnesota（明尼苏达大学）；Pacific Northwest National Laboratory（太平洋西北国家实验室）；University of Florida（佛罗里达大学）；University of South Dakota（南达科他大学）；University of Colorado Denver（科罗拉多大学丹佛分校）；Zayed University（扎耶德大学）；California Institute of Technology（加州理工学院）；Fermi National Accelerator Laboratory（费米国家加速器实验室）；Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；South Dakota School of Mines and Technology（南达科他矿业理工学院）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；Santa Clara University（圣克拉拉大学）
In-situ Surface Contamination Removal and Cool-down Process of the DEAP-3600 Experiment
DEAP-3600实验是一个单相探测器，使用3600公斤液态氩在加拿大萨德伯里的SNOLAB寻找暗物质。地下对于100 GeV的WIMP质量，对自旋无关的WIMP-核子截面的投影灵敏度为$10^{-46}$ cm $^{2}$。一个关键的实验要求是减少任何可能模仿暗物质信号的背景源。本文将回顾如何通过使用表面修整机器人从探测器的最内部去除500微米的丙烯酸来原位减少放射性表面背景。此外，它将审查瞬态冷却过程的实验，必要的，以达到低温工作温度。
