Xiansheng Cai

Xiansheng Cai is a PH.D. student at the Physics department of University of Massachusetts Amherst. He is actively involved in the development of Julia packages under the Numerical Effective Field Theory (NEFT) framework(https://github.com/numericalEFT) for modeling real-world quantum materials using modern quantum field theory. As the leading designer, his efforts have resulted in the creation of powerful tools CompositeGrids.jl for 1D grid representation, BrillouinZoneMeshes.jl for multi-dimensional Brillouin zone meshgrid representation.

Talks:

14:50 UTC

High-dimensional Monte Carlo Integration with Native Julia

07/27/2023, 2:50 PM — 3:00 PM UTC
32-124

This talk presents a new Julia package for efficient and generic Monte Carlo integration in high-dimensional and complex domains, featuring the Vegas algorithm for self-adaptive important sampling and an improved algorithm for increased robustness. The package demonstrates Julia's superiority over C/C++/Fortran and Python for high-dimensional Monte Carlo integration by enabling the easy creation of user-defined integrand evaluation functions with the speed of C and the flexibility of Python.

18:10 UTC

GreenFunc.jl: A Toolbox for Quantum Many-Body Problems.

07/27/2023, 6:10 PM — 6:20 PM UTC
32-082

GreenFunc.jl is a powerful package that offers a solution to the complex computational challenges of quantum many-body systems. The package is developed using native Julia language which offers both speed and flexibility. GreenFunc.jl implements state-of-the-art algorithms for solving quantum many-body problems using a Green's function approach, making it an invaluable tool for researchers in fields such as material design, high-temperature superconductivity, and quantum information technology.

Platinum sponsors

JuliaHub

Gold sponsors

ASML

Silver sponsors

Pumas AIQuEra Computing Inc.Relational AIJeffrey Sarnoff

Bronze sponsors

Jolin.ioBeacon BiosignalsMIT CSAILBoeing

Academic partners

NAWA

Local partners

Postmates

Fiscal Sponsor

NumFOCUS