Julian Arnold

I am PhD Student in the Quantum Theory Group of Prof. Christoph Bruder at the University of Basel (Switzerland) working at the interface between machine learning and quantum physics.

https://arnoldjulian.github.io/

Talks:

15:30 UTC

Differentiable isospectral flows for matrix diagonalization

07/28/2023, 3:30 PM — 3:40 PM UTC
32-D463 (Star)

In this talk, we present a differentiable Julia implementation of eigenvalue algorithms based on isospectral flows, i.e., matrix systems of ordinary differential equations (ODEs) that continuously drive Hermitian matrices toward a diagonal steady state. We discuss different options for suitable ODE solvers as well as methods for computing sensitivities, and showcase applications in quantum many-body physics.

16:10 UTC

Machine learning phase transitions: A probabilistic framework

07/28/2023, 4:10 PM — 4:20 PM UTC
32-D463 (Star)

In recent years, it has been extensively demonstrated that phase transitions can be detected from data by analyzing the output of neural networks (NNs) trained to solve specific classification problems. In this talk, we present a framework for the autonomous detection of phase transitions based on analytical solutions to these problems. We discuss the conditions that enable such approaches and showcase their computational advantage compared to NNs based on our Julia implementation.

Platinum sponsors

JuliaHub

Gold sponsors

ASML

Silver sponsors

Pumas AIQuEra Computing Inc.Relational AIJeffrey Sarnoff

Bronze sponsors

Jolin.ioBeacon Biosignals

Academic partners

NAWA

Local partners

Postmates

Fiscal Sponsor

NumFOCUS