Scientific research rests on 3 pillars: experiments/observations, theory and computing. A major part of the knowledge humanity acquired these last decades has been possible only through a smooth interplay between these three different activities.

This site will gather news and fuel discussions on the last comer in this virtuous triangle:”Computing”. Covering not so much the fast number crunching machinery as the new developments, ideas and techniques that are transforming the design, the data acquisition and analysis, the monitoring of experiments as well as the theoretical and simulation tools of physics research. Artificial intelligence, genetic algorithm, multivariate analysis, big data, distributed computing with GRID and clouds, computer algebra, automatic calculations,… are among the central topics.

A workshop series initiated in 1990 in Lyon (France) has been covering these topics. AIHENP (Artificial Intelligence in High Energy and Nuclear Physics) renamed ACAT in 2000 (Advanced Computing and Analysis Techniques for Physics Research). Although independent of the workshop this site will support the scientific discussions on many topics discussed there and most of the expert running the series will contribute. But the site will also welcome opinions and posts from a wide range of invited experts.

Track 1: Computing Technology for Physics Research

  1. Languages, Software quality, IDE and User Interfaces
    • Languages (new C++ standard, Java, …), Code Portability: using templates, toward Compiler
    • Software quality assurance; code reflection; documentation, performance and debugging tools
    • Computer system Benchmarking, beyond LinpackComputer system Benchmarking, beyond Linpack
    • IDE and frameworks
    • User Interfaces, Common Libraries.
  2. Distributed and Parallel Computing
    • Multilevel parallelism
    • Distributed computing
    • GRID and Cloud computing
  3. New architectures, many and multi-cores
    • Many-core
    • accelerator-based computing (GPU, etc)
    • High precision computing (hardware)
  4. Virtualisation
  5. Online computing
    • Advanced Monitoring, Diagnostics and Control
    • Scalable distributed data collectors
    • High Level Triggering (HLT)
    • Stream event processing and High Throughput Computing (HTC)

Track 2: Data Analysis – Algorithms and Tools

  1. Machine Learning
    • Neural Networks and Other Pattern Recognition Techniques
    • Evolutionary and Genetic Algorithms, Multi-variate analysis
    • Package Benchmarking
    • Automation of Science: Data to formula
  2. Advanced Data Analysis Environments
    • Statistical Methods, Multivariate analysis
    • Data mining
  3. Simulation, Reconstruction and Visualisation Techniques
    • Detector and Accelerator Simulations, MC and fast MC
    • Reconstruction Algorithms
    • Visualization Techniques; event displays
  4. Advanced Computing
    • Quantum Computing
    • Bio Computing: life process simulation, brain simulation, Quantum biology

Track 3: Computations in Theoretical Physics: Techniques and Methods

  1. Automatic Systems
    • Automatic Computation Systems: from Processes to Event Generators
    • Multi-dimensional Integration and Event Generators
    • Intensive High Precision Numerical Computations: Algorithms and Systems
  2. Higher orders
    • One-loop event generators
    • Multi-loop Calculations and Higher Order Corrections
  3. Computer Algebra Techniques and Applications
  4. Computational physics, Theoretical and simulation aspects
    • Lattice QCD,
    • Cosmology, Universe Large Scale Structure, Gravitational waves
    • Nuclear physics N-body computation,
    • Plasma physics,
    • Earth Physics, climate, earthquakes