In silico chemical experiments in the Age of AI: From quantum chemistry to machine learning and back

A Aldossary, JA Campos‐Gonzalez‐Angulo… - Advanced …, 2024 - Wiley Online Library
Computational chemistry is an indispensable tool for understanding molecules and
predicting chemical properties. However, traditional computational methods face significant …

Second-order optimization strategies for neural network quantum states

M Drissi, JWT Keeble… - Philosophical …, 2024 - royalsocietypublishing.org
The Variational Monte Carlo (VMC) method has recently seen important advances through
the use of neural network quantum states. While more and more sophisticated ansatze have …

Randomized Kaczmarz with tail averaging

EN Epperly, G Goldshlager, RJ Webber - arxiv preprint arxiv:2411.19877, 2024 - arxiv.org
The randomized Kaczmarz (RK) method is a well-known approach for solving linear least-
squares problems with a large number of rows. RK accesses and processes just one row at …

Neural Pfaffians: Solving Many Many-Electron Schr\" odinger Equations

N Gao, S Günnemann - arxiv preprint arxiv:2405.14762, 2024 - arxiv.org
Neural wave functions accomplished unprecedented accuracies in approximating the
ground state of many-electron systems, though at a high computational cost. Recent works …

Simple Fermionic backflow states via a systematically improvable tensor decomposition

M Bortone, Y Rath, GH Booth - arxiv preprint arxiv:2407.11779, 2024 - arxiv.org
We present an effective ansatz for the wave function of correlated electrons that brings
closer the fields of machine learning parameterizations and tensor rank decompositions. We …

Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing

G Goldshlager, J Hu, L Lin - arxiv preprint arxiv:2502.00882, 2025 - arxiv.org
Due to the ever growing amounts of data leveraged for machine learning and scientific
computing, it is increasingly important to develop algorithms that sample only a small portion …

Ground state phases of the two-dimension electron gas with a unified variational approach

C Smith, Y Chen, R Levy, Y Yang, MA Morales… - arxiv preprint arxiv …, 2024 - arxiv.org
The two-dimensional electron gas (2DEG) is a fundamental model, which is drawing
increasing interest because of recent advances in experimental and theoretical studies of …

Unified Variational Approach Description of Ground-State Phases of the Two-Dimensional Electron Gas

C Smith, Y Chen, R Levy, Y Yang, MA Morales… - Physical Review Letters, 2024 - APS
The two-dimensional electron gas (2DEG) is a fundamental model, which is drawing
increasing interest because of recent advances in experimental and theoretical studies of …

Exact Sampling for Classical and Quantum Many-Body Systems

D Wu - 2024 - infoscience.epfl.ch
Many-body systems at low temperature have revealed non-trivial phases of materials, such
as spin liquids, which have found applications in the evolving fields of superconductivity …

[CITAZIONE][C] Deep learning variational Monte Carlo for solving the electronic Schrödinger equation

L Gerard, P Grohs, M Scherbela - 2024 - Elsevier