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
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
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.
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