ACAT2027

Scientific Programme

ACAT 2027 will feature a dynamic scientific program centered around plenary sessions, parallel tracks & poster sessions. It is designed to encourage exchange across disciplines and foster in-person interaction between communities working at the intersection of physics, computing, and artificial intelligence.

Parallel Track 1: Computing Technology for Physics Research

This track covers enabling technologies that shape how physics research and data analysis are performed, from software ecosystems to large-scale computing infrastructures.

1. Software: language interoperability; software design, sustainability, and quality; analysis libraries, frameworks, and tools

2. Computing Architectures & Models: distributed and parallel computing; programming models; heterogeneous architectures (GPUs, ASICs, FPGAs, HPC systems); floating-point and numerical models; hardware abstraction layers; online and trigger-level computing; emerging paradigms such as quantum computing

3. Data Technologies: high-throughput data transfer; networking; storage systems; data formats, compression, and I/O optimization

4. Simulation & Visualization: detector and accelerator simulations (full and fast); visualization methods; event displays; interactive and immersive analysis environments

Parallel Track 2: Data Analysis — Algorithms and Tools

This track focuses on innovative algorithms, analysis strategies, and software tools that enable extracting physics results from increasingly complex datasets.

1. Machine Learning: neural network architectures; training strategies; hyperparameter optimization; efficient deployment and inference

2. Differentiable Programming: end-to-end optimization, differentiable simulations, and analysis pipelines

3. Statistical Methods & Inference Tools: statistical modeling, uncertainty estimation, hypothesis testing, and global analysis frameworks

4. Novel Reconstruction & Pattern-Recognition Algorithms: advanced tracking, clustering, and object reconstruction methods

Parallel Track 3: Computational Techniques and Methods in Theoretical Particle Physics, Astrophysics, and Cosmology

This track addresses computational techniques and algorithmic advances in theoretical particle physics, astrophysics, and cosmology, ranging from precision calculations and symbolic methods to gravitational-wave techniques and large-scale numerical simulations of astrophysical and cosmological systems.

1. Automated Computational Systems: symbolic and numerical frameworks from amplitudes to event generators; multidimensional integration techniques; automated computational pipelines; high-precision numerical algorithms

2. Higher-Order and Precision Calculations: multi-loop computations; higher-order corrections; resummation; matching fixed-order calculations to parton showers; precision phenomenology

3. Computer Algebra and Symbolic Methods: symbolic computation techniques; algebraic reduction; automated manipulation of theoretical models and complex mathematical expressions

4. Computational Particle and Nuclear Theory: numerical simulations; lattice and continuum methods; many-body calculations; phenomenological simulations; algorithmic developments for theoretical studies

5. Computational Astrophysics, Cosmology, and Gravitational-Wave Techniques: numerical relativity; gravitational-wave modeling and computational techniques; cosmological and large-scale structure simulations; compact-object modeling; gravitational and plasma dynamics; multi-messenger astrophysics

6. Large-Scale Simulation and Numerical Methods: scalable numerical solvers; adaptive and multiscale methods; particle- and grid-based simulations; surrogate and reduced-order models; GPU and HPC acceleration