297 citations · 1.6k across the 23 of their papers we have counts for
9 papers · 1 filter
Expected Sensitivity of the Light Dark Matter eXperiment to Long-Lived Dark Photons and Axion-Like Particles
Torsten Akesson, Clay Barton, Charles Bell +53
The Light Dark Matter eXperiment (LDMX) is an electron-beam fixed-target experiment primarily designed to achieve world-leading, model-independent sensitivity to sub-GeV dark matte…
Measurement of the LCLS-II dark current using the LDMX Trigger Scintillator Prototype
Elizabeth Berzin, Lene Kristian Bryngemark, Robert Craig Group +9
The Light Dark Matter eXperiment (LDMX) is a proposed fixed-target missing momentum search for sub-GeV thermal relic dark matter. LDMX aims to probe thermal dark matter targets wit…
LDMX -- The Light Dark Matter eXperiment
Torsten Akesson, Layan Alsaraya, Stephen Appert +116
The Light Dark Matter eXperiment (LDMX) is an electron fixed-target experiment optimized to search for sub-GeV dark matter production through the missing momentum signature. LDMX i…
Sensitivity of an Early Dark Matter Search using the Electromagnetic Calorimeter as a Target for the Light Dark Matter eXperiment
LDMX Collaboration, Torsten Åkesson, Elizabeth Berzin +53
The Light Dark Matter eXperiment (LDMX) is proposed to employ a thin tungsten target and a multi-GeV electron beam to carry out a missing momentum search for the production of dark…
Photon-rejection Power of the Light Dark Matter eXperiment in an 8 GeV Beam
Torsten Åkesson, Cameron Bravo, Liam Brennan +44
The Light Dark Matter eXperiment (LDMX) is an electron-beam fixed-target experiment designed to achieve comprehensive model independent sensitivity to dark matter particles in the…
Deep learning applications for quality control in particle detector construction
N. Akchurin, J. Damgov, S. Dugad +7
The growing complexity of particle detectors makes their construction and quality control a new challenge. We present studies that explore the use of deep learning-based computer v…