Results 31 to 40 of about 4,386 (222)
Quantum computational phase transition in combinatorial problems
npj Quantum Information, 2022 Quantum Approximate Optimization algorithm (QAOA) aims to search for approximate solutions to discrete optimization problems with near-term quantum computers.
Bingzhi Zhang, Akira Sone, Quntao Zhuang
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Proactively incremental-learning QAOA
, 2023 Solving optimization problems with high performance is the target of existing works of Quantum Approximate Optimization Algorithm (QAOA). With this intention, we propose an advanced QAOA based on incremental learning, where the training trajectory is proactively segmented into incremental phases.
Li, Lingxiao +5 more
openaire +2 more sources
Mean-Field Approximate Optimization Algorithm
PRX Quantum, 2023 The quantum approximate optimization algorithm (QAOA) is suggested as a promising application on early quantum computers. Here a quantum-inspired classical algorithm, the mean-field approximate optimization algorithm (mean-field AOA), is developed by ...
Aditi Misra-Spieldenner +5 more
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Coreset Clustering on Small Quantum Computers
, 2020 Many quantum algorithms for machine learning require access to classical data in superposition. However, for many natural data sets and algorithms, the overhead required to load the data set in superposition can erase any potential quantum speedup over ...
Anschuetz, Eric R. +3 more
core +1 more source
Alignment between initial state and mixer improves QAOA performance for constrained optimization
npj Quantum Information, 2023 Quantum alternating operator ansatz (QAOA) has a strong connection to the adiabatic algorithm, which it can approximate with sufficient depth. However, it is unclear to what extent the lessons from the adiabatic regime apply to QAOA as executed in ...
Zichang He +6 more
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, 2022 We introduce OpenQAOA, a Python open-source multi-backend Software Development Kit to create, customise, and execute the Quantum Approximate Optimisation Algorithm (QAOA) on Noisy Intermediate-Scale Quantum (NISQ) devices and simulators. OpenQAOA facilitates the creation of QAOA workflows, removing the more tedious and repetitive aspects of ...
Sharma, Vishal +6 more
openaire +2 more sources
Digitized-counterdiabatic quantum approximate optimization algorithm
Physical Review Research, 2022 The quantum approximate optimization algorithm (QAOA) has proved to be an effective classical-quantum algorithm serving multiple purposes, from solving combinatorial optimization problems to finding the ground state of many-body quantum systems.
P. Chandarana +6 more
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The QAOA with Few Measurements
, 2022 The Quantum Approximate Optimization Algorithm (QAOA) was originally developed to solve combinatorial optimization problems, but has become a standard for assessing the performance of quantum computers. Fully descriptive benchmarking techniques are often prohibitively expensive for large numbers of qubits ($n \gtrsim 10$), so the QAOA often serves in ...
Polloreno, Anthony M., Smith, Graeme
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Similarity-based parameter transferability in the quantum approximate optimization algorithm
Frontiers in Quantum Science and Technology, 2023 The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization.
Alexey Galda +10 more
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Vanishing performance of the parity-encoded quantum approximate optimization algorithm applied to spin-glass models [PDF]
QuantumThe parity mapping provides a geometrically local encoding of the Quantum Approximate Optimization Algorithm (QAOA), at the expense of having a quadratic qubit overhead for all-to-all connected problems. In this work, we benchmark the parity-encoded QAOA
Elisabeth Wybo, Martin Leib
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