Results 11 to 20 of about 3,092 (256)
Variational Quantum Algorithms for Semidefinite Programming [PDF]
QuantumA semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond.
Dhrumil Patel +2 more
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Iteration Complexity of Variational Quantum Algorithms [PDF]
QuantumThere has been much recent interest in near-term applications of quantum computers, i.e., using quantum circuits that have short decoherence times due to hardware limitations.
Vyacheslav Kungurtsev +3 more
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Variational quantum algorithm for the Poisson equation [PDF]
Physical Review A, 2021 The Poisson equation has wide applications in many areas of science and engineering. Although there are some quantum algorithms that can efficiently solve the Poisson equation, they generally require a fault-tolerant quantum computer which is beyond the current technology.
Hai-Ling Liu +6 more
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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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A Variational Algorithm for Quantum Neural Networks [PDF]
, 2020 Quantum Computing leverages the laws of quantum mechanics to build computers endowed with tremendous computing power. The field is attracting ever-increasing attention from both academic and private sectors, as testified by the recent demonstration of quantum supremacy in practice.
Macaluso, Antonio +3 more
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Accelerating variational quantum algorithms with multiple quantum processors
CoRR, 2021 Variational quantum algorithms (VQAs) have the potential of utilizing near-term quantum machines to gain certain computational advantages over classical methods. Nevertheless, modern VQAs suffer from cumbersome computational overhead, hampered by the tradition of employing a solitary quantum processor to handle large-volume data.
Yuxuan Du, Yang Qian, Dacheng Tao
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