Affiliation:
1. Computer Science Department, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Splaiul Independentei 313, Bucharest 060042, Romania
Abstract
Modern physics is based on both theoretical analysis and experimental validation. Complex scenarios like subatomic dimensions, high energy, and lower absolute temperature are frontiers for many theoretical models. Simulation with stable numerical methods represents an excellent instrument for high accuracy analysis, experimental validation, and visualization. High performance computing support offers possibility to make simulations at large scale, in parallel, but the volume of data generated by these experiments creates a new challenge for Big Data Science. This paper presents existing computational methods for high energy physics (HEP) analyzed from two perspectives: numerical methods and high performance computing. The computational methods presented are Monte Carlo methods and simulations of HEP processes, Markovian Monte Carlo, unfolding methods in particle physics, kernel estimation in HEP, and Random Matrix Theory used in analysis of particles spectrum. All of these methods produce data-intensive applications, which introduce new challenges and requirements for ICT systems architecture, programming paradigms, and storage capabilities.
Funder
SideSTEP—Scheduling Methods for Dynamic Distributed Systems: a self-* approach
Subject
Nuclear and High Energy Physics
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. STREAM: Toward READ-Based In-Memory Computing for Streaming-Based Processing for Data-Intensive Applications;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-11
2. Discovering the in-Memory Kernels of 3D Dot-Product Engines;Proceedings of the 28th Asia and South Pacific Design Automation Conference;2023-01-16
3. Theoretical Background;Search for Higgs Boson Decays to Charm Quarks with the ATLAS Experiment and Development of Novel Silicon Pixel Detectors;2023
4. Review of unfolding methods;Physics-Uspekhi;2022-05
5. Hybrid Analog-Digital In-Memory Computing;2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD);2021-11-01