Toward the end-to-end optimization of particle physics instruments with differentiable programming-Reference-Cited by-同舟云学术

Toward the end-to-end optimization of particle physics instruments with differentiable programming

Published:2023-06 Issue: Volume:10 Page:100085
ISSN:2405-4283
Container-title:Reviews in Physics
language:en
Short-container-title:Reviews in Physics

Author:

Dorigo Tommaso^ORCID,Giammanco Andrea,Vischia Pietro,Aehle Max,Bawaj Mateusz,Boldyrev Alexey,de Castro Manzano Pablo,Derkach Denis,Donini Julien,Edelen Auralee,Fanzago Federica,Gauger Nicolas R.,Glaser Christian,Baydin Atılım G.,Heinrich Lukas,Keidel Ralf,Kieseler Jan,Krause Claudius,Lagrange Maxime,Lamparth Max,Layer Lukas,Maier Gernot,Nardi Federico,Pettersen Helge E.S.,Ramos Alberto,Ratnikov Fedor,Röhrich Dieter,de Austri Roberto Ruiz,del Árbol Pablo Martínez Ruiz,Savchenko Oleg,Simpson Nathan,Strong Giles C.,Taliercio Angela,Tosi Mia,Ustyuzhanin Andrey,Zaraket Haitham

Publisher

Elsevier BV

Subject

General Physics and Astronomy

Reference347 articles.

1. Topology optimization approaches;Sigmund;Struct. Multidiscip. Optim.,2013

2. Reporting results in high energy physics publications: A manifesto;Vischia;Rev. Phys.,2020

3. CMS Physics: Technical Design Report Volume 1: Detector Performance and Software,2006

4. The frontier of simulation-based inference;Cranmer;Proc. Natl. Acad. Sci.,2020

5. Toward machine learning optimization of experimental design;Baydin;Nucl. Phys. News,2021

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