A short review of the present status of computer packages for the high order analytical perturbative calculations is presented. The mathematical algorithm and the quantum field theory methods used are briefly discussed. The most recent computer package HEPLoops for analytical computations in high energy physics up to four-loops is also discussed.
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.
The BaBar experiment uses data since 1999 in examining the violation of charge and parity (CP) symmetry in the field of high energy physics. This event simulation experiment is a compute intensive task due to the complexity of the Monte-Carlo simulation implemented on the GEANT engine. Data needed as input for the simulation (stored in the ROOT format), are classified into two categories: conditions data for describing the detector status when data are recorded, and background triggers data for noise signal necessary to obtain a realistic simulation. In this chapter, the grid approach is applied to the BaBar production framework using the INFN-GRID network.
Specialized documentation envisioned from a pedagogical bases to train scientifically and technologically teachers and researchers, who initiate themselves in the analysis of high energy physics (HEP) experiments, is scarce. The lack of this material makes that young scientists' learning process be prolonged in time, raising costs in experimental research. In this paper we present the Monte Carlo technique applied to simulate the threshold energy for producing final-state particles of a specific two-body process (A + B → C + D), as pedagogical environment to face both computationally and conceptually an experimental analysis. The active/interactive learning-teaching formative process presented here is expected to be an educational resource for reducing young scientists' learning curve and saving time and costs in HEP scientific research.
EXASCALE ALGORITHMS AND SOFTWARE FOR LATTICE FIELD THEORY IN HIGH ENERGY PHYSICS: SEARCHING BEYOND THE STANDARD MODEL