This title appears in the Scientific Report :
2023
Please use the identifier:
http://hdl.handle.net/2128/34088 in citations.
Please use the identifier: http://dx.doi.org/10.1103/PhysRevApplied.19.024047 in citations.
Improved Variational Quantum Eigensolver Via Quasidynamical Evolution
Improved Variational Quantum Eigensolver Via Quasidynamical Evolution
The variational quantum eigensolver (VQE) is a hybrid quantum classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There are problems with VQE that forbid a favorable scaling toward...
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Personal Name(s): | Jattana, Manpreet Singh |
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Jin, Fengping / De Raedt, Hans / Michielsen, Kristel (Corresponding author) | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Published in: | Physical review applied, 19 (2023) 2, S. 024047 |
Imprint: |
College Park, Md. [u.a.]
American Physical Society
2023
|
DOI: |
10.1103/PhysRevApplied.19.024047 |
Document Type: |
Journal Article |
Research Program: |
Doktorand ohne besondere Förderung An Open Superconducting Quantum Computer Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups |
Link: |
Get full text OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1103/PhysRevApplied.19.024047 in citations.
The variational quantum eigensolver (VQE) is a hybrid quantum classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There are problems with VQE that forbid a favorable scaling towards quantum advantage. In order to alleviate the problems, we propose and extensively test a quantum annealing inspired heuristic that supplements VQE. The improved VQE enables an efficient initial state-preparation mechanism, in a recursive manner, for a quasidynamical unitary evolution. We conduct an in-depth scaling analysis of finding the ground-state energies with increasing lattice sizes of the Heisenberg model, employing simulations of up to 40 qubits that manipulate the complete state vector. In addition to systematically finding the ground-state energy, we observe that it avoids barren plateaus, escapes local minima, and works with low-depth circuits. For the current devices, we further propose a benchmarking toolkit using a mean-field model and test it on IBM Q devices. Realistic gate execution times estimate a longer computational time to complete the same computation on a fully functional error-free quantum computer than on a quantum computer emulator implemented on a classical computer. However, our proposal can be expected to help accurate estimations of the ground-state energies beyond 50 qubits when the complete state vector can no longer be stored on a classical computer, thus enabling quantum advantage. |