Compressing the two-particle Green’s function using wavelets: Theory and application to the Hubbard atom
Year: 2024
Type: article
Abstract: Precise algorithms capable of providing controlled solutions in the presence of strong interactions are transforming the landscape of quantum many-body physics. Particularly, exciting breakthroughs are enabling the computation of non-zero temperature correlation functions. However, computational challenges arise due to constraints in resources and memory limitations, especially in scenarios involving complex Green’s functions and lattice effects. Leveraging the principles of signal processing and data compression, this paper explores the wavelet decomposition as a versatile and efficient method for obtaining compact and resource-efficient representations of the many-body theory of interacting systems. The effectiveness of the wavelet decomposition is illustrated through its application to the representation of generalized susceptibilities and self-energies in a prototypical interacting fermionic system, namely the Hubbard model at half-filling in its atomic limit. These results are the first proof-of-principle application of the wavelet compression within the realm of many-body physics and demonstrate the potential of this wavelet-based compression scheme for understanding the physics of correlated electron systems.
Language: English
Topic: Quantum many-body systems
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,790
Awards: aB-IniTio calculations and MAchine learning for suPerconducting collective phenomena in novel materials, G3764568615, G434337789, G4495373907, G4516885165, FOR 5413: Quantenspinsysteme mit langreichweitigen Wechselwirkungen: Experiment, Theorie und Mathematik, G5407046981, Columbia University MRSEC on Precision-Assembled Quantum Materials, Dynamical vertex functions of many-electron systems, G6002429476, G6125720754, G6830791989, Quantum phase transitions and collective modes
OpenAlex ID: W4392019341
