학술논문
A Strategy for Low-Mass Dark Matter Searches with Cryogenic Detectors in the SuperCDMS SNOLAB Facility
Document Type
Working Paper
Author
SuperCDMS Collaboration; Albakry, M. F.; Alkhatib, I.; Amaral, D. W. P.; Aralis, T.; Aramaki, T.; Arnquist, I. J.; Langroudy, I. Ataee; Azadbakht, E.; Banik, S.; Bathurst, C.; Bauer, D. A.; Bhattacharyya, R.; Brink, P. L.; Bunker, R.; Cabrera, B.; Calkins, R.; Cameron, R. A.; Cartaro, C.; Cerdeno, D. G.; Chang, Y. -Y.; Chaudhuri, M.; Chen, R.; Chott, N.; Cooley, J.; Coombes, H.; Corbett, J.; Cushman, P.; De Brienne, F.; Dharani, S.; di Vacri, M. L.; Diamond, M. D.; Fascione, E.; Figueroa-Feliciano, E.; Fink, C. W.; Fouts, K.; Fritts, M.; Gerbier, G.; Germond, R.; Ghaith, M.; Golwala, S. R.; Hall, J.; Hassan, N.; Hines, B. A.; Hollister, M. I.; Hong, Z.; Hoppe, E. W.; Hsu, L.; Huber, M. E.; Iyer, V.; Jastram, A.; Kashyap, V. K. S.; Kelsey, M. H.; Kubik, A.; Kurinsky, N. A.; Lawrence, R. E.; Lee, M.; Li, A.; Liu, J.; Liu, Y.; Loer, B.; Lukens, P.; MacFarlane, D. B.; Mahapatra, R.; Mandic, V.; Mast, N.; Mayer, A. J.; Theenhausen, H. Meyer zu; Michaud, E.; Michielin, E.; Mirabolfathi, N.; Mohanty, B.; Nagorny, S.; Nelson, J.; Neog, H.; Novati, V.; Orrell, J. L.; Osborne, M. D.; Oser, S. M.; Page, W. A.; Partridge, R.; Pedreros, D. S.; Podviianiuk, R.; Ponce, F.; Poudel, S.; Pradeep, A.; Pyle, M.; Rau, W.; Reid, E.; Ren, R.; Reynolds, T.; Roberts, A.; Robinson, A. E.; Saab, T.; Sadoulet, B.; Saikia, I.; Sander, J.; Sattari, A.; Schmidt, B.; Schnee, R. W.; Scorza, S.; Serfass, B.; Poudel, S. S.; Sincavage, D. J.; Stanford, C.; Street, J.; Sun, H.; Thasrawala, F. K.; Toback, D.; Underwood, R.; Verma, S.; Villano, A. N.; von Krosigk, B.; Watkins, S. L.; Wen, O.; Williams, Z.; Wilson, M. J.; Winchell, J.; Wyko, K.; Yellin, S.; Young, B. A.; Yu, T. C.; Zatschler, B.; Zatschler, S.; Zaytsev, A.; Zhang, E.; Zheng, L.; Zuber, S.
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Subject
Language
Abstract
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.
Comment: 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
Comment: 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