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The quantum approximate optimization algorithm (QAOA) generates an approximate solution to combinatorial optimization problems using a variational ansatz circuit defined by parameterized layers of quantum evolution. In theory, the…

Motivated by the recent advancement of quantum processors, we investigate quantum approximate optimization algorithm (QAOA) to employ quasi-maximum-likelihood (ML) decoding of classical channel codes. QAOA is a hybrid quantum-classical…

信息论 · 计算机科学 2019-03-07 Toshiki Matsumine , Toshiaki Koike-Akino , Ye Wang

Structured variational quantum algorithms such as the Quantum Approximate Optimisation Algorithm (QAOA) have emerged as leading candidates for exploiting advantages of near-term quantum hardware. They interlace classical computation, in…

量子物理 · 物理学 2026-05-05 Vincent Eichenseher , Maja Franz , Christian Wolff , Wolfgang Mauerer

The Quantum Alternating Operator Ansatz is a generalization of the Quantum Approximate Optimization Algorithm (QAOA) designed for finding approximate solutions to combinatorial optimization problems with hard constraints. In this paper, we…

量子物理 · 物理学 2021-07-02 Jeremy Cook , Stephan Eidenbenz , Andreas Bärtschi

Scaling of variational quantum algorithms to large problem sizes requires efficient optimization of random parameterized quantum circuits. For such circuits with uncorrelated parameters, the presence of exponentially vanishing gradients in…

量子物理 · 物理学 2021-01-28 Tyler Volkoff , Patrick J. Coles

Despite much recent work, the true promise and limitations of the Quantum Alternating Operator Ansatz (QAOA) are unclear. A critical question regarding QAOA is to what extent its performance scales with the input size of the problem…

量子物理 · 物理学 2023-12-07 John Golden , Andreas Bärtschi , Stephan Eidenbenz , Daniel O'Malley

Binary optimization problems are emerging as potential candidates for useful applications of quantum computing. Among quantum algorithms, the quantum approximate optimization algorithm (QAOA) is currently considered the most promising…

量子物理 · 物理学 2025-03-31 Bruno Oziel Fernandez , Rodrigo Bloot , Marcelo Moret

Two-stage stochastic programming often discretizes uncertainty into scenarios, but scenario enumeration makes expected recourse evaluation scale at least linearly in the scenario count. We propose qGAN-QAOA, a unified quantum-circuit…

量子物理 · 物理学 2025-12-30 Taihei Kuroiwa , Daiki Yamazaki , Keita Takahashi , Kodai Shiba , Chih-Chieh Chen , Tomah Sogabe

Proposed hybrid algorithms encode a combinatorial cost function into a problem Hamiltonian and optimize its energy by varying over a set of states with low circuit complexity. Classical processing is typically only used for the choice of…

量子物理 · 物理学 2022-08-25 Libor Caha , Alexander Kliesch , Robert Koenig

The quantum approximate optimization algorithm (QAOA) is considered to be one of the most promising approaches towards using near-term quantum computers for practical application. In its original form, the algorithm applies two different…

量子物理 · 物理学 2021-04-08 Mauro E. S. Morales , Jacob Biamonte , Zoltán Zimborás

We present a quantum alternating operator ansatz (QAOA$^+$) that solves a class of linearly constrained optimization problems by evolving a quantum state within a Hilbert subspace of feasible problem solutions. Our main focus is on a class…

量子物理 · 物理学 2024-09-30 Brayden Goldstein-Gelb , Phillip C. Lotshaw

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) can potentially demonstrate…

We study variational quantum algorithms from the perspective of free fermions. By deriving the explicit structure of the associated Lie algebras, we show that the Quantum Approximate Optimization Algorithm (QAOA) on a one-dimensional…

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

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

An enhanced framework of quantum approximate optimization algorithm (QAOA) is introduced and the parameter setting strategies are analyzed. The enhanced QAOA is as effective as the QAOA but exhibits greater computing power and flexibility,…

量子物理 · 物理学 2020-12-18 Mingyou Wu , Zhihao Liu , Hanwu Chen

The Quantum Approximate Optimization Algorithm (QAOA) has been proposed as a method to obtain approximate solutions for combinatorial optimization tasks. In this work, we study the underlying algebraic properties of three QAOA ans\"atze for…

量子物理 · 物理学 2025-11-27 Sujay Kazi , Martín Larocca , Marco Farinati , Patrick J. Coles , M. Cerezo , Robert Zeier

Quantum computing is a computational paradigm with the potential to outperform classical methods for a variety of problems. Proposed recently, the Quantum Approximate Optimization Algorithm (QAOA) is considered as one of the leading…

机器学习 · 计算机科学 2022-06-16 Sami Khairy , Ruslan Shaydulin , Lukasz Cincio , Yuri Alexeev , Prasanna Balaprakash

In this paper, we aim to expand the understanding of the relationship between the composition of the Hamiltonian in the Quantum Approximate Optimization Algorithm (QAOA) and the corresponding cost landscape characteristics. QAOA is a…

量子物理 · 物理学 2024-05-21 Michał Stęchły , Lanruo Gao , Boniface Yogendran , Enrico Fontana , Manuel Rudolph

The Quantum Approximate Optimization Algorithm (QAOA) has been one of the leading candidates for near-term quantum advantage in gate-model quantum computers. From its inception, this algorithm has sparked the desire for comparison between…

量子物理 · 物理学 2021-12-08 Colin Campbell , Edward Dahl