https://doi.org/10.1140/epjp/s13360-024-05403-9
Regular Article
Compressing the two-particle Green’s function using wavelets: Theory and application to the Hubbard atom
1
Institute for Solid State Physics, TU Wien, 1040, Vienna, Austria
2
Institute for Solid State Physics and Institute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria
3
Department of Physics, Columbia University, 538 W 120th Street, 10027, New York, NY, USA
4
Center for Computational Quantum Physics, Flatiron Institute, 162 5th Avenue, 10010, New York, NY, USA
5
Center for Computational Mathematics, Flatiron Institute, 162 5th Avenue, 10010, New York, NY, USA
6
Department of Physics and Astronomy, Rutgers University, 08854, Piscataway, NJ, USA
7
Department of Physics and Astronomy, University of Bologna, 40127, Bologna, Italy
Received:
20
February
2024
Accepted:
27
June
2024
Published online:
7
August
2024
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.
E. Moghadas and N. Dräger have contributed equally to this work.
© The Author(s) 2024
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