Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory
Year: 2025
Type: article
Abstract: Modeling many-body quantum systems is widely regarded as one of the most promising applications for near-term noisy quantum computers. However, in the near term, system size limitation will remain a severe barrier for applications in materials science or strongly correlated systems. A promising avenue of research is to combine many-body physics with machine learning for the classification of distinct phases. We present a workflow that synergizes quantum computing, many-body theory, and quantum machine learning (QML) for studying strongly correlated systems. In particular, it can capture a putative quantum phase transition of the stereotypical strongly correlated system, the Hubbard model. Following the recent proposal of the hybrid quantum-classical algorithm for the two-site dynamical mean-field theory (DMFT), we present a modification that allows the self-consistent solution of the single bath site DMFT. The modified algorithm can be generalized for multiple bath sites. This approach is used to generate a database of zero-temperature wavefunctions of the Hubbard model within the DMFT approximation. We then use a QML algorithm to distinguish between the metallic phase and the Mott insulator phase to capture the metal-to-Mott insulator phase transition. We train a recently proposed quantum convolutional neural network (QCNN) and then utilize the QCNN as a quantum classifier to capture the phase transition region. This work provides a recipe for application to other phase transitions in strongly correlated systems and represents an exciting application of small-scale quantum devices realizable with near-term technology.
Source: Quantum Reports
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,689
Awards: CAREER:Beyond Ideal Quantum Materials: Understanding the Critical Role of Disorder and Electron-Electron Interactions, G1272791968, ExpandQISE: Track 1: Quantum@MTSU: Building QISE Research and Education in Middle Tennessee, Simulations of Competing Phases and Quantum Criticality in Strongly Correlated Materials, G2731530876, LOCALIZATION IN ENERGY MATERIALS, LOCALIZATION IN ENERGY MATERIALS, G3403409181, Taming the Noisy Environment for Photon-Mediated Operations in Quantum Information Processing, G44583232, G5742458454, G855621978
OpenAlex ID: W4409162969