TY - GEN
T1 - Prepare Ground States of Highly Frustrated Magnetic Clusters on Quantum Computers
AU - Wang, Yan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Solving challenging problems in physical, chemical, and materials sciences is one of the most promising applications of quantum utility that can be realized on current noisy hardware, considering (i) the direct map (encoding) from the quantum particles and their interactions to the qubits and their entangling gates and (ii) the rapidly improved quantum hardware and advanced error-mitigation techniques. Understanding quantum spin liquid in frustrated magnetic materials is a longstanding challenge in condensed matter physics and the nature of the ground-state phases is highly debated among researchers. Using IBM quantum computers with superconducting qubits, we implemented a variational quantum eigensolver (VQE) algorithm to prepare the ground states of two 12-site cluster approximations of these highly frustrated magnetic materials. The interaction graphs of the two corresponding Hamiltonians are (a) the six-pointed star graph (a unit cell of the kagome lattice) and (b) the cuboctahedral graph (the kagome on a sphere). These are also two instances of Quantum Max Cut problem. With the VQE based on the Hamiltonian variational ansatz acting on a valence bond solid initial trial state, we prepared the ground states and obtained the exact ground energy on simulator and high accuracy on noisy hardware. The deep ansatz necessary to reach the ground state of the cuboctahedral graph indicates that it is a hard instance of Quantum Max Cut.
AB - Solving challenging problems in physical, chemical, and materials sciences is one of the most promising applications of quantum utility that can be realized on current noisy hardware, considering (i) the direct map (encoding) from the quantum particles and their interactions to the qubits and their entangling gates and (ii) the rapidly improved quantum hardware and advanced error-mitigation techniques. Understanding quantum spin liquid in frustrated magnetic materials is a longstanding challenge in condensed matter physics and the nature of the ground-state phases is highly debated among researchers. Using IBM quantum computers with superconducting qubits, we implemented a variational quantum eigensolver (VQE) algorithm to prepare the ground states of two 12-site cluster approximations of these highly frustrated magnetic materials. The interaction graphs of the two corresponding Hamiltonians are (a) the six-pointed star graph (a unit cell of the kagome lattice) and (b) the cuboctahedral graph (the kagome on a sphere). These are also two instances of Quantum Max Cut problem. With the VQE based on the Hamiltonian variational ansatz acting on a valence bond solid initial trial state, we prepared the ground states and obtained the exact ground energy on simulator and high accuracy on noisy hardware. The deep ansatz necessary to reach the ground state of the cuboctahedral graph indicates that it is a hard instance of Quantum Max Cut.
KW - NISQ Applications
KW - Quantum Computing
KW - Quantum Max Cut
KW - Variational Quantum Algorithms
UR - http://www.scopus.com/inward/record.url?scp=85180011227&partnerID=8YFLogxK
U2 - 10.1109/QCE57702.2023.10300
DO - 10.1109/QCE57702.2023.10300
M3 - Conference contribution
AN - SCOPUS:85180011227
T3 - Proceedings - 2023 IEEE International Conference on Quantum Computing and Engineering, QCE 2023
SP - 397
EP - 398
BT - Proceedings - 2023 IEEE International Conference on Quantum Computing and Engineering, QCE 2023
A2 - Muller, Hausi
A2 - Alexev, Yuri
A2 - Delgado, Andrea
A2 - Byrd, Greg
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Quantum Computing and Engineering, QCE 2023
Y2 - 17 September 2023 through 22 September 2023
ER -