Results of a Search for Sub-GeV Dark Matter Using 2013 LUX Data
- Submitting institution
-
The University of Sheffield
- Unit of assessment
- 9 - Physics
- Output identifier
- 7927
- Type
- D - Journal article
- DOI
-
10.1103/physrevlett.122.131301
- Title of journal
- Physical Review Letters
- Article number
- 131301
- First page
- -
- Volume
- 122
- Issue
- 13
- ISSN
- 0031-9007
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
97
- Research group(s)
-
D - Particle Physics and Particle Astrophysics
- Citation count
- 37
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- Kudryavstev contributed to the development of the background model used in the LUX experiment, in particular to the neutron background calculations, where neutron background may come from radioactivity and cosmic-ray muons. His group has also developed an algorithm based on machine learning (Boosted Decision Tree analysis) for studying potential background events caused by multiple scatters of gamma rays that produce two or more overlapping scintillation pulses and only one ionisation pulse. These events can closely mimic the expected signal and were included in the background model.
- Non-English
- No
- English abstract
- -