Gradient estimator in Variational Monte Carlo

I recently tried to derive the formula for the gradient estimator in Variational Monte Carlo and got confused trying to obtain the common covariance formula $\partial_\Theta\braket{E} = 2\text{Re}\text{Cov}[(\partial_\Theta\log\psi)^*, E_l]$ in the case of complex wavefunctions. At first, to me it seemed like the direct derivative of the estimator was missing (which vanishes for real wavefunctions). Indeed most derivations in the literature seem to assume real wavefunctions, however it turns out this direct part gives a similar term included in the score based part which eventually lets us simplify the estimator to the real part of the covariance formula....

February 12, 2025 · 5 min · Tom Magorsch

Bottomonium suppression as an open quantum system

We recently put out a paper on bottomonium suppression in the quark gluon plasma 2403.15545. This is a project I’ve been working on for some time now and I want to show real quick what we have been doing. Quarkonium suppression Heavy ion collisions are experiments where two heavy nuclei are collided. Such experiments are conducted e.g. at CERN. In these collisions a state of matter called the quark gluon plasma is created....

April 11, 2024 · 5 min · Tom Magorsch

GSoC 23 | Quantum Generative Adversarial Networks for HEP event generation the LHC

This is a summary of my 2023 GSoC project with the ML4SCI-organization. In my project I designed and implemented a Quantum Generative Adversarial Network for the generation of HEP experiment data. The full code for all my work can be found on Github. In the following post I will outline my work and describe some parts of the implementation and the results Event generation in HEP experiments In high energy physics experiements like they are conducted at CERN, an integral part of the analysis process is the comparison of measurements with results expected based on predictions from our theory of nature, the Standard Model of particle physics....

October 12, 2023 · 9 min · Tom Magorsch

Quantum GANs

This year I’m participating in the Google Summer of Code again. Just like last year I’m working with the ML4SCI organization. In this years project I am working on Quantum Generative Adversarial Networks. GANs Generative Adversarial Networks (GANs) are a class of unsupervised machine learning models proposed in ( Citation: Goodfellow, Pouget-Abadie & al., 2014 Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A. & Bengio, Y. (2014). Generative Adversarial Networks....

July 29, 2023 · 9 min · Tom Magorsch

NERSC Open Hackathon 2022 | Multi-GPU quantum circuit simulation in Pennylane

The past month I have been participating in the NERSC Open Hackathon hosted together with NVIDIA. Throughout the event we had access to the Perlmutter compute system and worked together with mentors on scaling our scientific software projects on GPUs. During the event I worked on scaling the training of VQCs in Pennylane to multiple GPUs. A word of thanks goes to the organizers and all the mentors who helped us throghout the event....

December 18, 2022 · 5 min · Tom Magorsch