R. Agnese
Maximum Likelihood Analysis of Low Energy CDMS II Germanium Data
Agnese, R.; Anderson, A.J.; Balakishiyeva, D.; Thakur, R. Basu; Bauer, D.A.; Billard, J.; Borgland, A.; Bowles, M.A.; Brandt, D.; Brink, P.L.; Bunker, R.; Cabrera, B.; Caldwell, D.O.; Cerdeno, D.G.; Chagani, H.; Chen, Y.; Cooley, J.; Cornell, B.; Crewdson, C.H.; Cushman, P.; Daal, M.; Di Stefano, P.C.F.; Doughty, T.; Esteban, L.; Fallows, S.; Figueroa-Feliciano, E.; Fritts, M.; Godfrey, G.L.; Golwala, S.R.; Graham, M.; Hall, J.; Harris, H.R.; Hertel, S.A.; Hofer, T.; Holmgren, D.; Hsu, L.; Huber, M.E.; Jastram, A.; Kamaev, O.; Kara, B.; Kelsey, M.H.; Kennedy, A.; Kiveni, M.; Koch, K.; Leder, A.; Loer, B.; Asamar, E. Lopez; Mahapatra, R.; Mandic, V.; Martinez, C.; McCarthy, K.A.; Mirabolfathi, N.; Moffatt, R.A.; Moore, D.C.; Nelson, R.H.; Oser, S.M.; Page, K.; Page, W.A.; Partridge, R.; Pepin, M.; Phipps, A.; Prasad, K.; Pyle, M.; Qiu, H.; Rau, W.; Redl, P.; Reisetter, A.; Ricci, Y.; Rogers, H.E.; Saab, T.; Sadoulet, B.; Sander, J.; Schneck, K.; Schnee, R.W.; Scorza, S.; Serfass, B.; Sh...
Authors
A.J. Anderson
D. Balakishiyeva
R. Basu Thakur
D.A. Bauer
J. Billard
A. Borgland
M.A. Bowles
D. Brandt
P.L. Brink
R. Bunker
B. Cabrera
D.O. Caldwell
D.G. Cerdeno
H. Chagani
Y. Chen
J. Cooley
B. Cornell
C.H. Crewdson
P. Cushman
M. Daal
P.C.F. Di Stefano
T. Doughty
L. Esteban
S. Fallows
E. Figueroa-Feliciano
M. Fritts
G.L. Godfrey
S.R. Golwala
M. Graham
J. Hall
H.R. Harris
S.A. Hertel
T. Hofer
D. Holmgren
L. Hsu
M.E. Huber
A. Jastram
O. Kamaev
B. Kara
M.H. Kelsey
A. Kennedy
M. Kiveni
K. Koch
A. Leder
B. Loer
E. Lopez Asamar
R. Mahapatra
V. Mandic
C. Martinez
K.A. McCarthy
N. Mirabolfathi
R.A. Moffatt
D.C. Moore
R.H. Nelson
S.M. Oser
K. Page
W.A. Page
R. Partridge
M. Pepin
A. Phipps
K. Prasad
M. Pyle
H. Qiu
W. Rau
P. Redl
A. Reisetter
Y. Ricci
H.E. Rogers
T. Saab
B. Sadoulet
J. Sander
K. Schneck
R.W. Schnee
S. Scorza
B. Serfass
B. Shank
D. Speller
S. Upadhyayula
A.N. Villano
B. Welliver
D.H. Wright
S. Yellin
J.J. Yen
B.A. Young
J. Zhang
Abstract
We report on the results of a search for a Weakly Interacting Massive Particle (WIMP) signal in low-energy data of the Cryogenic Dark Matter Search experiment using a maximum likelihood analysis. A background model is constructed using geant4 to simulate the surface-event background from Pb210 decay-chain events, while using independent calibration data to model the gamma background. Fitting this background model to the data results in no statistically significant WIMP component. In addition, we perform fits using an analytic ad hoc background model proposed by Collar and Fields, who claimed to find a large excess of signal-like events in our data. We confirm the strong preference for a signal hypothesis in their analysis under these assumptions, but excesses are observed in both single- and multiple-scatter events, which implies the signal is not caused by WIMPs, but rather reflects the inadequacy of their background model.
Citation
Agnese, R., Anderson, A., Balakishiyeva, D., Thakur, R. B., Bauer, D., Billard, J., …Zhang, J. (2015). Maximum Likelihood Analysis of Low Energy CDMS II Germanium Data. Physical Review D, 91(5), Article 052021. https://doi.org/10.1103/physrevd.91.052021
Journal Article Type | Article |
---|---|
Publication Date | Mar 30, 2015 |
Deposit Date | Oct 21, 2015 |
Publicly Available Date | Mar 29, 2024 |
Journal | Physical Review D |
Print ISSN | 1550-7998 |
Electronic ISSN | 1550-2368 |
Publisher | American Physical Society |
Peer Reviewed | Peer Reviewed |
Volume | 91 |
Issue | 5 |
Article Number | 052021 |
DOI | https://doi.org/10.1103/physrevd.91.052021 |
Files
Published Journal Article
(7.7 Mb)
PDF
Copyright Statement
Reprinted with permission from the American Physical Society: Physical Review D 92, 052021 © 2015 by the American Physical Society. Readers may view, browse, and/or download material for temporary copying purposes only, provided these uses are for noncommercial personal purposes. Except as provided by law, this material may not be further reproduced, distributed, transmitted, modified, adapted, performed, displayed, published, or sold in whole or part, without prior written permission from the American Physical Society.
You might also like
A direct detection view of the neutrino NSI landscape
(2023)
Journal Article
The dark matter component of the Gaia radially anisotropic substructure
(2020)
Journal Article
Constraints on dark photons and axionlike particles from the SuperCDMS Soudan experiment
(2020)
Journal Article
On the correlation between the local dark matter and stellar velocities
(2019)
Journal Article
B anomalies and dark matter: a complex connection
(2019)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search