output
20022024
most citedGW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral

9.8k citations

Showing 2024Show all

11 papers · 1 filter

hep-ex2024

Measurements of Pion and Muon Nuclear Capture at Rest on Argon in the LArIAT Experiment

M. A. Hernandez-Morquecho, R. Acciarri, J. Asaadi +22

We report the measurement of the final-state products of negative pion and muon nuclear capture at rest on argon by the LArIAT experiment at the Fermilab Test Beam Facility. We mea…

cs.SE202413 cited

Making sense of AI systems development

Mateusz Dolata, Kevin Crowston

We identify and describe episodes of sensemaking around challenges in modern AI-based systems development that emerged in projects carried out by IBM and client companies. All proj…

hep-ex20246 cited

Search for the rare decay of charmed baryon into final state

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1066

A search for the nonresonant decay is performed using proton-proton collision data recorded at a centre-of-mass energy of 13 TeV by the LHCb experiment, corre…

cs.MA20242 cited

Multi-agent Cooperative Games Using Belief Map Assisted Training

Qinwei Huang, Chen Luo, Alex B. Wu +3

In a multi-agent system, agents share their local observations to gain global situational awareness for decision making and collaboration using a message passing system. When to se…

astro-ph.HE2024

A Potential Second Shutoff from AT2018fyk: An updated Orbital Ephemeris of the Surviving Star under the Repeating Partial Tidal Disruption Event Paradigm

Dheeraj Pasham, Eric Coughlin, Muryel Guolo +4

The tidal disruption event (TDE) AT2018dyk/ASASSN-18UL showed a rapid dimming event 500 days after discovery, followed by a re-brightening roughly 700 days later. It has been hypot…

hep-ex2024

Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

MicroBooNE collaboration, P. Abratenko, O. Alterkait +186

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture f…