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Published in 2019 at "Communications in Mathematical Physics"
DOI: 10.1007/s00220-019-03485-6
Abstract: We prove that any one-dimensional (1D) quantum state with small quantum conditional mutual information in all certain tripartite splits of the system, which we call a quantum approximate Markov chain, can be well-approximated by a… read more here.
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Published in 2021 at "Quantum Information Processing"
DOI: 10.1007/s11128-021-03298-4
Abstract: We study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be optimized. Our approach formalizes the connection between quantum symmetry properties of the QAOA dynamics… read more here.
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Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-025-18778-1
Abstract: Finding a Hadamard matrix of a specific order using a quantum computer can lead to a demonstration of practical quantum advantage. Earlier efforts using a quantum annealer were impeded by the limitations of the present… read more here.
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Published in 2024 at "Physical Review A"
DOI: 10.1103/physreva.110.012428
Abstract: Variational quantum algorithms have become the de facto model for current quantum computations. A prominent example of such algorithms -- the quantum approximate optimization algorithm (QAOA) -- was originally designed for combinatorial optimization tasks, but… read more here.
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Published in 2022 at "Physical review letters"
DOI: 10.1103/physrevlett.130.050601
Abstract: In this Letter, we provide analytical and numerical evidence that the single-layer quantum approximate optimization algorithm on universal Ising spin models produces thermal-like states. We find that these pseudo-Boltzmann states can not be efficiently simulated… read more here.
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Published in 2021 at "Mathematical Problems in Engineering"
DOI: 10.1155/2021/6655455
Abstract: A quantum approximate optimization algorithm (QAOA) is a polynomial-time approximate optimization algorithm used to solve combinatorial optimization problems. However, the existing QAOA algorithms have poor generalization performance in finding an optimal solution from a feasible… read more here.
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Published in 2022 at "Algorithms"
DOI: 10.3390/a15060202
Abstract: The quantum approximate optimization algorithm/quantum alternating operator ansatz (QAOA) is a heuristic to find approximate solutions of combinatorial optimization problems. Most of the literature is limited to quadratic problems without constraints. However, many practically relevant… read more here.
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Published in 2022 at "Mathematics"
DOI: 10.3390/math11092176
Abstract: The quantum approximate optimization algorithm (QAOA) is known for its capability and universality in solving combinatorial optimization problems on near-term quantum devices. The results yielded by QAOA depend strongly on its initial variational parameters. Hence,… read more here.