activity
19962026
most citedDemonstrating sub-3 ps temporal resolution in a superconducting nanowire single-photon detector

565 citations · 5.6k across the 116 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

hep-ex2019★ 24 cited

Particle Generative Adversarial Networks for full-event simulation at the LHC and their application to pileup description

Jesus Arjona Martinez, Thong Q Nguyen, Maurizio Pierini +2

We investigate how a Generative Adversarial Network could be used to generate a list of particle four-momenta from LHC proton collisions, allowing one to define a generative model…

quant-ph2019★ 307 cited

Perspectives on quantum transduction

Nikolai Lauk, Neil Sinclair, Shabir Barzanjeh +4

Quantum transduction, the process of converting quantum signals from one form of energy to another, is an important area of quantum science and technology. The present perspective…

hep-ex2019★ 70 cited

Interaction networks for the identification of boosted decays

Eric A. Moreno, Thong Q. Nguyen, Jean-Roch Vlimant +6

We develop an algorithm based on an interaction network to identify high-transverse-momentum Higgs bosons decaying to bottom quark-antiquark pairs and distinguish them from ordinar…

quant-ph2019★ 31 cited

Charged particle tracking with quantum annealing-inspired optimization

Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant +4

At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for analysis are expected to face challenges due to scaling wit…

hep-ex2019★ 124 cited

JEDI-net: a jet identification algorithm based on interaction networks

Eric A. Moreno, Olmo Cerri, Javier M. Duarte +7

We investigate the performance of a jet identification algorithm based on interaction networks (JEDI-net) to identify all-hadronic decays of high-momentum heavy particles produced…

quant-ph2019★ 22 cited

Quantum adiabatic machine learning with zooming

Alexander Zlokapa, Alex Mott, Joshua Job +3

Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific applicat…

physics.data-an2019★ 1 cited

Processing Columnar Collider Data with GPU-Accelerated Kernels

Joosep Pata, Maria Spiropulu

At high energy physics experiments, processing billions of records of structured numerical data from collider events to a few statistical summaries is a common task. The data proce…