TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhysCodeb.51
TI  - SOLAX: A Python solver for fermionic quantum systems with neural network support
PY  - 2025/02/20
UR  - https://scipost.org/SciPostPhysCodeb.51
JF  - SciPost Physics Codebases
JA  - SciPost Phys. Codebases
SP  - 51
A1  - Thirion, Louis
AU  - Hansmann, Philipp
AU  - Bilous, Pavlo
AB  - Numerical modeling of fermionic many-body quantum systems presents similar challenges across various research domains, necessitating universal tools, including state-of-the-art machine learning techniques. Here, we introduce SOLAX, a Python library designed to compute and analyze fermionic quantum systems using the formalism of second quantization. SOLAX provides a modular framework for constructing and manipulating basis sets, quantum states, and operators, facilitating the simulation of electronic structures and determining many-body quantum states in finite-size Hilbert spaces. The library integrates machine learning capabilities to mitigate the exponential growth of Hilbert space dimensions in large quantum clusters. The core low-level functionalities are implemented using the recently developed Python library JAX. Demonstrated through its application to the Single Impurity Anderson Model, SOLAX offers a flexible and powerful tool for researchers addressing the challenges of many-body quantum systems across a broad spectrum of fields, including atomic physics, quantum chemistry, and condensed matter physics.
ER  -

@Article{10.21468/SciPostPhysCodeb.51,
	title={{SOLAX: A Python solver for fermionic quantum systems with neural network support}},
	author={Louis Thirion and Philipp Hansmann and Pavlo Bilous},
	journal={SciPost Phys. Codebases},
	pages={51},
	year={2025},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCodeb.51},
	url={https://scipost.org/10.21468/SciPostPhysCodeb.51},
}

@Article{10.21468/SciPostPhysCodeb.51-r1.0,
	title={{Codebase release 1.0 for SOLAX}},
	author={Louis Thirion and Philipp Hansmann and Pavlo Bilous},
	journal={SciPost Phys. Codebases},
	pages={51-r1.0},
	year={2025},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCodeb.51-r1.0},
	url={https://scipost.org/10.21468/SciPostPhysCodeb.51-r1.0},
}