Quantum Brain
← Back to papers

Utilizing Quantum Processor for the Analysis of Strongly Correlated Materials

Hengyue Li, Yusheng Yang, Pin Lv, Jinglong Qu, Zhe-Hui Wang, Jian Sun, Shenggang Ying·April 3, 2024·DOI: 10.1088/1402-4896/ad770b
Quantum Physicscond-mat.str-el

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

This study introduces a systematic approach for analyzing strongly correlated systems by adapting the conventional quantum cluster method to a quantum circuit model. We have developed a more concise formula for calculating the cluster's Green's function, requiring only real-number computations on the quantum circuit instead of complex ones. This approach is inherently more suited to quantum circuits, which primarily yield statistical probabilities. As an illustrative example, we explored the Hubbard model on a 2D lattice. The ground state is determined utilizing Xiaohong, a superconducting quantum processor equipped with 66 qubits, supplied by QuantumCTek Co., Ltd. Subsequently, we employed the circuit model to compute the real-time retarded Green's function for the cluster, which is then used to determine the lattice Green's function. We conducted an examination of the band structure in the insulator phase of the lattice system. This preliminary investigation lays the groundwork for exploring a wealth of innovative physics within the field of condensed matter physics.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.