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Quantum computing promises solutions to classically difficult and new-found problems through controlling the subtleties of quantum computing. The Quantum Approximate Optimisation Algorithm (QAOA) is a recently proposed quantum algorithm…

量子物理 · 物理学 2024-12-24 Nicholas J. Pritchard

The design of fast algorithms for combinatorial optimization greatly contributes to a plethora of domains such as logistics, finance, and chemistry. Quantum approximate optimization algorithms (QAOAs), which utilize the power of quantum…

量子物理 · 物理学 2022-05-25 Zeqiao Zhou , Yuxuan Du , Xinmei Tian , Dacheng Tao

This paper presents a numerical simulation investigation of the Warm-Start Quantum Approximate Optimization Algorithm (QAOA) as proposed by Tate et al. [1], focusing on its application to 3-regular Max-Cut problems. Our study demonstrates…

量子物理 · 物理学 2024-09-16 Sean Feeney , Reuben Tate , Stephan Eidenbenz

The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. Optimal QAOA parameter concentration effects for special…

量子物理 · 物理学 2024-07-10 Jose Falla , Quinn Langfitt , Yuri Alexeev , Ilya Safro

The ability of the Quantum Approximate Optimization Algorithm (QAOA) to deliver a quantum advantage on combinatorial optimization problems is still unclear. Recently, a scaling advantage over a classical solver was postulated to exist for…

量子物理 · 物理学 2024-12-02 Thorge Müller , Ajainderpal Singh , Frank K. Wilhelm , Tim Bode

We introduce a quantum approximate optimization algorithm (QAOA) for continuous optimization. The algorithm is based on the dynamics of a quantum system moving in an energy potential which encodes the objective function. By approximating…

量子物理 · 物理学 2019-02-04 Guillaume Verdon , Juan Miguel Arrazola , Kamil Brádler , Nathan Killoran

Quantum computers are devices, which allow more efficient solutions of problems as compared to their classical counterparts. As the timeline to developing a quantum-error corrected computer is unclear, the quantum computing community has…

量子物理 · 物理学 2023-02-16 Marko J. Rančić

Approximate combinatorial optimisation has emerged as one of the most promising application areas for quantum computers, particularly those in the near term. In this work, we focus on the quantum approximate optimisation algorithm (QAOA)…

量子物理 · 物理学 2022-11-23 Nishant Jain , Brian Coyle , Elham Kashefi , Niraj Kumar

Quantum Approximate Optimization Algorithm (QAOA) is a promising hybrid quantum-classical algorithm for solving combinatorial optimization problems. However, it cannot overcome qubit limitation for large-scale problems. Furthermore, the…

新兴技术 · 计算机科学 2021-03-01 Junde Li , Mahabubul Alam , Swaroop Ghosh

The quantum approximate optimization algorithm (QAOA) transforms a simple many-qubit wavefunction into one which encodes a solution to a difficult classical optimization problem. It does this by optimizing the schedule according to which…

量子物理 · 物理学 2022-06-29 Yunlong Yu , Chenfeng Cao , Carter Dewey , Xiang-Bin Wang , Nic Shannon , Robert Joynt

The quantum approximate optimization algorithm (QAOA) is a near-term quantum algorithm aimed at solving combinatorial optimization problems. Since its introduction, various generalizations have emerged, spanning modifications to the initial…

量子物理 · 物理学 2024-11-18 Truman Yu Ng , Jin Ming Koh , Dax Enshan Koh

The Quantum Approximate Optimization Algorithm (QAOA) is a variational quantum algorithm that can be used to approximately solve combinatorial optimization problems. However, a major limitation of QAOA is that it is a "local" algorithm for…

量子物理 · 物理学 2025-04-10 Quinn Langfitt , Reuben Tate , Stephan Eidenbenz

The quantum approximate optimization algorithm (QAOA) is a promising quantum algorithm that can be used to approximately solve combinatorial optimization problems. The usual QAOA ansatz consists of an alternating application of the cost and…

量子物理 · 物理学 2024-11-01 Anthony Wilkie , Igor Gaidai , James Ostrowski , Rebekah Herrman

The quantum approximate optimization algorithm (QAOA) is a near-term hybrid algorithm intended to solve combinatorial optimization problems, such as MaxCut. QAOA can be made to mimic an adiabatic schedule, and in the $p\to\infty$ limit the…

量子物理 · 物理学 2022-02-02 Jonathan Wurtz , Peter J. Love

The Quantum Approximate Optimization Algorithm can naturally be applied to combinatorial search problems on graphs. The quantum circuit has p applications of a unitary operator that respects the locality of the graph. On a graph with…

量子物理 · 物理学 2020-04-21 Edward Farhi , David Gamarnik , Sam Gutmann

The quantum approximate optimization algorithm (QAOA) is a promising quantum-classical hybrid technique to solve combinatorial optimization problems in near-term gate-based noisy quantum devices. In QAOA, the objective is a function of the…

量子物理 · 物理学 2019-07-24 Mahabubul Alam , Abdullah Ash-Saki , Swaroop Ghosh

As combinatorial optimization is one of the main quantum computing applications, many methods based on parameterized quantum circuits are being developed. In general, a set of parameters are being tweaked to optimize a cost function out of…

量子物理 · 物理学 2022-05-09 Charles Moussa , Hao Wang , Thomas Bäck , Vedran Dunjko

Demonstrating quantum heuristics that outperform strong classical solvers on large-scale optimization remains an open challenge. Here we introduce Regularized Warm-Started QAOA (RWS-QAOA), which initializes qubits by minimizing expected…

The quantum approximate optimization algorithm (QAOA) is one of the canonical algorithms designed to find approximate solutions to combinatorial optimization problems in current noisy intermediate-scale quantum (NISQ) devices. It is an…

量子物理 · 物理学 2023-12-12 Ping Zou

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…

量子物理 · 物理学 2022-09-29 Xinwei Lee , Ningyi Xie , Yoshiyuki Saito , Dongsheng Cai , Nobuyoshi Asai