699 citations · 2.7k across the 97 of their papers we have counts for
17 papers · 1 filter
Progress in End-to-End Optimization of Detectors for Fundamental Physics with Differentiable Programming
Max Aehle, Lorenzo Arsini, R. Belén Barreiro +27
In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models…
Energy reconstruction for large liquid scintillator detectors with machine learning techniques: aggregated features approach
Arsenii Gavrikov, Yury Malyshkin, Fedor Ratnikov
Large-scale detectors consisting of a liquid scintillator target surrounded by an array of photo-multiplier tubes (PMTs) are widely used in the modern neutrino experiments: Borexin…
Generative Adversarial Networks for the fast simulation of the Time Projection Chamber responses at the MPD detector
A. Maevskiy, F. Ratnikov, A. Zinchenko +3
The detailed detector simulation models are vital for the successful operation of modern high-energy physics experiments. In most cases, such detailed models require a significant…
Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper
Tommaso Dorigo, Andrea Giammanco, Pietro Vischia +33
The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, given the large dimensi…
Track reconstruction and matching between emulsion and silicon pixel detectors for the SHiP-charm experiment
SHiP Collaboration
In July 2018 an optimization run for the proposed charm cross section measurement for SHiP was performed at the CERN SPS. A heavy, moving target instrumented with nuclear emulsion…
The SHiP experiment at the proposed CERN SPS Beam Dump Facility
SHIP Collaboration
The Search for Hidden Particles (SHiP) Collaboration has proposed a general-purpose experimental facility operating in beam-dump mode at the CERN SPS accelerator to search for ligh…
The use of Boosted Decision Trees for Energy Reconstruction in JUNO experiment
Arsenii Gavrikov, Fedor Ratnikov
The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino experiment with a broad physical program. The main goals of JUNO are the determination of the neutrino mass order…
A Comparison of CPU and GPU implementations for the LHCb Experiment Run 3 Trigger
R. Aaij, M. Adinolfi, S. Aiola +157
The LHCb experiment at CERN is undergoing an upgrade in preparation for the Run 3 data taking period of the LHC. As part of this upgrade the trigger is moving to a fully software i…
Vertex and Energy Reconstruction in JUNO with Machine Learning Methods
Zhen Qian, Vladislav Belavin, Vasily Bokov +20
The Jiangmen Underground Neutrino Observatory (JUNO) is an experiment designed to study neutrino oscillations. Determination of neutrino mass ordering and precise measurement of ne…
Simulating the Time Projection Chamber responses at the MPD detector using Generative Adversarial Networks
A. Maevskiy, F. Ratnikov, A. Zinchenko +1
High energy physics experiments rely heavily on the detailed detector simulation models in many tasks. Running these detailed models typically requires a notable amount of the comp…
ML-assisted versatile approach to Calorimeter R&D
Alexey Boldyrev, Denis Derkach, Fedor Ratnikov +1
Advanced detector R&D for both new and ongoing experiments in HEP requires performing computationally intensive and detailed simulations as part of the detector-design optimisation…
Using Machine Learning to Speed Up and Improve Calorimeter R&D
Fedor Ratnikov
Design of new experiments, as well as upgrade of ongoing ones, is a continuous process in the experimental high energy physics. Since the best solution is a trade-off between diffe…
Generative Adversarial Networks for LHCb Fast Simulation
Fedor Ratnikov
LHCb is one of the major experiments operating at the Large Hadron Collider at CERN. The richness of the physics program and the increasing precision of the measurements in LHCb le…
Using machine learning to speed up new and upgrade detector studies: a calorimeter case
F. Ratnikov, D. Derkach, A. Boldyrev +3
In this paper, we discuss the way advanced machine learning techniques allow physicists to perform in-depth studies of the realistic operating modes of the detectors during the sta…
SND@LHC
SHiP Collaboration, C. Ahdida, A. Akmete +341
We propose to build and operate a detector that, for the first time, will measure the process at the LHC and search for feebly interacting particles (FIPs) in an unexplor…
Measurement of the muon flux for the SHiP experiment
SHiP Collaboration
The SHiP experiment will search for very weakly interacting particles beyond the Standard Model which are produced in a 400 \GeV/ proton beam dump at the CERN SPS. About $10^{11…
The active muon shield in the SHiP experiment
SHiP collaboration, A. Akmete, A. Alexandrov +229
The SHiP experiment is designed to search for very weakly interacting particles beyond the Standard Model which are produced in a 400 GeV/c proton beam dump at the CERN SPS. An ess…