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The Quantum Approximate Optimization Algorithm (QAOA) requires considered optimization problems to be translated into a compatible format. A popular transformation step in this pipeline involves the quadratization of higher-order binary…

Quantum Physics · Physics 2025-11-26 Damian Rovara , Lukas Burgholzer , Robert Wille

The Quantum Approximate Optimization Algorithm (QAOA) is a promising approach for programming a near-term gate-based hybrid quantum computer to find good approximate solutions of hard combinatorial problems. However, little is currently…

Quantum Physics · Physics 2018-11-21 Gavin E. Crooks

The quantum approximate optimization algorithm (QAOA) is a hybrid variational quantum-classical algorithm that solves combinatorial optimization problems. While there is evidence suggesting that the fixed form of the standard QAOA ansatz is…

The quantum approximate optimization algorithm (QAOA) is a leading iterative variational quantum algorithm for heuristically solving combinatorial optimization problems. A large portion of the computational effort in QAOA is spent by the…

Quantum Physics · Physics 2022-08-23 Ohad Amosy , Tamuz Danzig , Ely Porat , Gal Chechik , Adi Makmal

The Quantum Approximate Optimization Algorithm (QAOA) is a promising variational quantum algorithm introduced to tackle classically intractable combinatorial optimization problems. This tutorial offers a comprehensive, first-principles…

Quantum Physics · Physics 2025-11-25 Alessandro Giovagnoli

Variational quantum algorithms are believed to be promising for solving computationally hard problems and are often comprised of repeated layers of quantum gates. An example thereof is the quantum approximate optimization algorithm (QAOA),…

The Quantum Approximate Optimization Algorithm (QAOA) is a well-known hybrid quantum-classical algorithm for combinatorial optimization problems. Improving QAOA involves enhancing its approximation ratio while addressing practical…

Quantum Physics · Physics 2025-02-07 Yukun Wang , ZeYang Li , Linchun Wan

Developing quantum algorithms adaptive to specific constraints of near-term devices is an essential step towards practical quantum advantage. In a recent work [Phys. Rev. Lett. 131, 103601(2023)], we show cold atoms in an optical cavity can…

Quantum Physics · Physics 2024-06-12 Yuchen Luo , Xiaopeng Li , Jian Lin

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…

Quantum Physics · Physics 2019-07-24 Mahabubul Alam , Abdullah Ash-Saki , Swaroop Ghosh

The quantum approximate optimization algorithm (QAOA) is an appealing proposal to solve NP problems on noisy intermediate-scale quantum (NISQ) hardware. Making NISQ implementations of the QAOA resilient to noise requires short ansatz…

The Quantum Approximate Optimization Algorithm (QAOA) -- one of the leading algorithms for applications on intermediate-scale quantum processors -- is designed to provide approximate solutions to combinatorial optimization problems with…

Quantum Physics · Physics 2024-09-18 Pontus Vikstål , Laura García-Álvarez , Shruti Puri , Giulia Ferrini

The quantum approximate optimisation ansatz (QAOA) is one of the flagship algorithms used to tackle combinatorial optimisation on graphs problems using a quantum computer, and is considered a strong candidate for early fault-tolerant…

Quantum Physics · Physics 2025-06-24 Yann Beaujeault-Taudière

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…

Quantum Physics · Physics 2021-09-24 Rebekah Herrman , Phillip C. Lotshaw , James Ostrowski , Travis S. Humble , George Siopsis

Designing noisy-resilience quantum algorithms is indispensable for practical applications on Noisy Intermediate-Scale Quantum~(NISQ) devices. Here we propose a quantum approximate optimization algorithm~(QAOA) with a very shallow circuit,…

Quantum Physics · Physics 2021-09-27 Fang-Gang Duan , Dan-Bo Zhang

The quantum approximate optimization algorithm (QAOA) is an approach for near-term quantum computers to potentially demonstrate computational advantage in solving combinatorial optimization problems. However, the viability of the QAOA…

Quantum computers are expected to accelerate solving combinatorial optimization problems, including algorithms such as Grover adaptive search and quantum approximate optimization algorithm (QAOA). However, many combinatorial optimization…

Quantum Physics · Physics 2023-05-05 Takuya Yoshioka , Keita Sasada , Yuichiro Nakano , Keisuke Fujii

The quantum approximate optimization algorithm (QAOA) is a promising method for solving certain classical combinatorial optimization problems on near-term quantum devices. When employing the QAOA to 3-SAT and Max-3-SAT problems, the quantum…

Quantum Physics · Physics 2023-06-07 Yunlong Yu , Chenfeng Cao , Xiang-Bin Wang , Nic Shannon , Robert Joynt

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…

Quantum Physics · Physics 2022-06-29 Yunlong Yu , Chenfeng Cao , Carter Dewey , Xiang-Bin Wang , Nic Shannon , Robert Joynt

The Quantum Approximate Optimization Algorithm (QAOA) is a hybrid quantum-classical variational algorithm designed to tackle combinatorial optimization problems. Despite its promise for near-term quantum applications, not much is currently…

Quantum Physics · Physics 2020-06-26 Leo Zhou , Sheng-Tao Wang , Soonwon Choi , Hannes Pichler , Mikhail D. Lukin

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-24 Seongmin Kim , Vincent R. Pascuzzi , Zhihao Xu , Tengfei Luo , Eungkyu Lee , In-Saeng Suh
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