A Chen, M Heyl - arXiv preprint arXiv:2302.01941, 2023 - arxiv.org
Neural quantum states (NQSs) have emerged as a novel promising numerical method to solve the quantum many-body problem. However, it has remained a central challenge to …
X Sun, P Zhang, P Zhang, H Shah… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Large Vision-Language Foundation Models (VLFM), such as CLIP, ALIGN and Florence, are trained on large private datasets of image-caption pairs and achieve superior …
A Chen, M Heyl - Nature Physics, 2024 - nature.com
Computing the ground state of interacting quantum matter is a long-standing challenge, especially for complex two-dimensional systems. Recent developments have highlighted the …
The quantum many-body problem is ultimately a curse of dimensionality: the state of a system with many particles is determined by a function with many dimensions, which rapidly …
Predicting the phase diagram of interacting quantum many-body systems is a central problem in condensed matter physics and related fields. A variety of quantum many-body …
With the introduction of x-ray free electron laser sources around the world, new scientific approaches for visualizing matter at fundamental length and time-scales have become …
Describing the ground states of continuous, real-space quantum many-body systems, like atoms and molecules, is a significant computational challenge with applications throughout …
We consider achieving equivariance in machine learning systems via frame averaging. Current frame averaging methods involve a costly sum over large frames or rely on sampling …
Y Rath - arXiv preprint arXiv:2308.07669, 2023 - arxiv.org
Capturing the correlation emerging between constituents of many-body systems accurately is one of the key challenges for the appropriate description of various systems whose …