Results 11 to 20 of about 3,302 (256)
Classically Optimal Variational Quantum Algorithms [PDF]
IEEE Transactions on Quantum Engineering, 2021 Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQAs), are suitable for implementation on noisy intermediate-scale quantum computers.
Jonathan Wurtz, Peter Love
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Parameter-parallel distributed variational quantum algorithm
SciPost Physics, 2023 Variational quantum algorithms (VQAs) have emerged as a promising near-term technique to explore practical quantum advantage on noisy intermediate-scale quantum (NISQ) devices.
Yun-Fei Niu, Shuo Zhang, Chen Ding, Wan-Su Bao, He-Liang Huang
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Variational quantum algorithms [PDF]
Nature Reviews Physics, 2021 Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers due to the extremely high computational cost. Quantum computers promise a solution, although fault-tolerant quantum computers will likely not be available in the near future.
M. Cerezo +10 more
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Training Variational Quantum Algorithms Is NP-Hard [PDF]
Physical Review Letters, 2021 Variational quantum algorithms are proposed to solve relevant computational problems on near term quantum devices. Popular versions are variational quantum eigensolvers and quantum ap- proximate optimization algorithms that solve ground state problems from quantum chemistry and binary optimization problems, respectively.
Lennart Bittel, Martin Kliesch
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Quantum variational algorithms are swamped with traps
Nature Communications, 2022 AbstractOne of the most important properties of classical neural networks is how surprisingly trainable they are, though their training algorithms typically rely on optimizing complicated, nonconvex loss functions. Previous results have shown that unlike the case in classical neural networks, variational quantum models are often not trainable. The most
Eric R. Anschuetz, Bobak T. Kiani
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Variational quantum algorithm for estimating the quantum Fisher information [PDF]
Physical Review Research, 2022 v2: significantly revised manuscript according to peer ...
Jacob L. Beckey +3 more
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Optimally stopped variational quantum algorithms [PDF]
Physical Review A, 2018 Quantum processors promise a paradigm shift in high-performance computing which needs to be assessed by accurate benchmarking measures. In this work, we introduce a new benchmark for variational quantum algorithm (VQA), recently proposed as a heuristic algorithm for small-scale quantum processors.
Vinci, Walter, Shabani, Alireza
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Efficient Measure for the Expressivity of Variational Quantum Algorithms [PDF]
Physical Review Letters, 2022 The superiority of variational quantum algorithms (VQAs) such as quantum neural networks (QNNs) and variational quantum eigen-solvers (VQEs) heavily depends on the expressivity of the employed ansatze. Namely, a simple ansatze is insufficient to capture the optimal solution, while an intricate ansatze leads to the hardness of the trainability.
Yuxuan Du +3 more
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Schrödinger-Heisenberg Variational Quantum Algorithms
Physical Review Letters, 2023 5 pages, 4 ...
Zhong-Xia Shang +4 more
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AIP Advances, 2022 The variational quantum eigensolver (VQE), which is a quantum–classical hybrid approach, has latent powers to leverage near-term quantum devices by effectively managing a limited number of qubits with finite coherent lifetimes.
Tsukasa Miki +4 more
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