Performance analysis of a filtering variational quantum algorithm
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| Udgivet i: | New Journal of Physics vol. 27, no. 5 (May 2025), p. 054505 |
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IOP Publishing
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| Online adgang: | Citation/Abstract Full Text - PDF |
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| 001 | 3203894691 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1367-2630 | ||
| 024 | 7 | |a 10.1088/1367-2630/add365 |2 doi | |
| 035 | |a 3203894691 | ||
| 045 | 2 | |b d20250501 |b d20250531 | |
| 100 | 1 | |a Marin-Sanchez, Gabriel |u Quantinuum, Partnership House , Carlisle Place, London SW1P 1BX, United Kingdom | |
| 245 | 1 | |a Performance analysis of a filtering variational quantum algorithm | |
| 260 | |b IOP Publishing |c May 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Even a minor boost in solving combinatorial optimization problems can greatly benefit multiple industries. Quantum computers, with their unique information processing capabilities, hold promise for delivering such enhancements. The filtering variational quantum eigensolver (F-VQE) is a variational hybrid quantum algorithm designed to solve combinatorial optimization problems on existing quantum computers with limited qubit number, connectivity, and fidelity. In this work we employ instantaneous quantum polynomial circuits as our parameterized quantum circuits. We propose a hardware-efficient implementation that respects limited qubit connectivity and show that they halve the number of circuits necessary to evaluate the gradient with the parameter-shift rule. To assess the potential of this protocol in the context of combinatorial optimization, we conduct extensive numerical analysis. We compare the performance against three classical baseline algorithms on weighted MaxCut and the asymmetric traveling salesperson problem (ATSP). We employ noiseless simulators for problems encoded on 13–29 qubits, and up to 37 qubits on the IBMQ real quantum devices. The ATSP encoding employed reduces the number of qubits and avoids the need of constraints compared to the standard quadratic unconstrained binary optimization/Ising model. Despite some observed positive signs, we conclude that significant development is necessary for a practical advantage with F-VQE. | |
| 653 | |a Quantum computing | ||
| 653 | |a Simulators | ||
| 653 | |a Data processing | ||
| 653 | |a Quantum computers | ||
| 653 | |a Combinatorial analysis | ||
| 653 | |a Numerical analysis | ||
| 653 | |a Optimization | ||
| 653 | |a Traveling salesman problem | ||
| 653 | |a Polynomials | ||
| 653 | |a Algorithms | ||
| 653 | |a Ising model | ||
| 653 | |a Circuits | ||
| 653 | |a Filtration | ||
| 653 | |a Qubits (quantum computing) | ||
| 700 | 1 | |a Amaro, David | |
| 773 | 0 | |t New Journal of Physics |g vol. 27, no. 5 (May 2025), p. 054505 | |
| 786 | 0 | |d ProQuest |t Publicly Available Content Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3203894691/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3203894691/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |