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Universal fault-tolerant quantum computers will require error-free execution of long sequences of quantum gate operations, which is expected to involve millions of physical qubits. Before the full power of such machines will be available,…

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most promising Noisy Intermediate Quantum Algorithms (NISQ) in solving combinatorial optimizations and displays potential over classical heuristic techniques.…

Quantum Physics · Physics 2024-01-18 Arul Rhik Mazumder , Anuvab Sen , Udayon Sen

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

A new methodology is proposed to solve classical Boolean problems as Hamiltonians, using the quantum approximate optimization algorithm (QAOA). Our methodology successfully finds all optimized approximated solutions for Boolean problems,…

Quantum Physics · Physics 2024-07-11 Ali Al-Bayaty , Marek Perkowski

Photonic quantum computers, programmed within the framework of the measurement-based quantum computing (MBQC), currently concur with gate-based platforms in the race towards useful quantum advantage, and some algorithms emerged as main…

Quantum Physics · Physics 2023-04-10 Massimiliano Proietti , Filippo Cerocchi , Massimiliano Dispenza

Quantum approximate optimization algorithm (QAOA) is a promising hybrid quantum-classical algorithm to solve combinatorial optimization problems in the era of noisy intermediate-scale quantum computers. Recently warm-start approaches have…

Quantum Physics · Physics 2024-01-19 Ken N. Okada , Hirofumi Nishi , Taichi Kosugi , Yu-ichiro Matsushita

Optimization is often cited as a promising application of quantum computers. However, the low degree of provable quantum speedups has led prior rigorous end-to-end resource analyses to conclude that a quantum computer is unlikely to surpass…

Noisy intermediate-scale quantum computers (NISQ computers) are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms (VQAs). Among them, the Quantum Approximate Optimization Algorithm (QAOA)…

Optimization and Control · Mathematics 2024-08-13 Camille Grange , Michael Poss , Eric Bourreau

Quantum algorithms for binary optimization problems have been the subject of extensive study. However, the application of quantum algorithms to integer optimization problems remains comparatively unexplored. In this paper, we study the…

The efficient management of energy communities relies on the solution of the "prosumer problem", i.e., the problem of scheduling the household loads on the basis of the user needs, the electricity prices, and the availability of local…

Quantum Physics · Physics 2023-11-20 Carlo Mastroianni , Francesco Plastina , Luigi Scarcello , Jacopo Settino , Andrea Vinci

Until high-fidelity quantum computers with a large number of qubits become widely available, classical simulation remains a vital tool for algorithm design, tuning, and validation. We present a simulator for the Quantum Approximate…

Quantum Physics · Physics 2023-11-14 Danylo Lykov , Ruslan Shaydulin , Yue Sun , Yuri Alexeev , Marco Pistoia

Quantum annealing is a heuristic optimization algorithm that exploits quantum evolution to approximately find lowest energy states. Quantum annealers have scaled up in recent years to tackle increasingly larger and more highly connected…

Quantum Physics · Physics 2025-07-04 Humberto Munoz Bauza , Daniel A. Lidar

Methods to find the solution state for optimization problems encoded into Ising Hamiltonians are a very active area of current research. In this work we compare the quantum approximate optimization algorithm (QAOA) with multi-stage quantum…

The quantum approximate optimisation algorithm (QAOA) is a hybrid quantum-classical algorithm used to approximately solve combinatorial optimisation problems. It involves multiple iterations of a parameterised ansatz comprising a problem…

Quantum Physics · Physics 2024-02-16 V. Vijendran , Aritra Das , Dax Enshan Koh , Syed M. Assad , Ping Koy Lam

Quantum computers and simulators may offer significant advantages over their classical counterparts, providing insights into quantum many-body systems and possibly improving performance for solving exponentially hard problems, such as…

Heterogeneous HPC workflow scheduling under multiple hard constraints poses a challenging combinatorial optimization problem. Classical exact solvers guarantee optimality but face scalability limits, motivating interest in quantum-inspired…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-26 Aasish Kumar Sharma , Christian Boehme , Julian Kunkel

Regression testing is key in verifying that software works correctly after changes. However, running the entire regression test suite can be impractical and expensive, especially for large-scale systems. Test suite optimization methods are…

Quantum Physics · Physics 2025-05-01 Antonio Trovato , Martin Beseda , Dario Di Nucci

The quantum-classical hybrid algorithm is an algorithm that holds promise in demonstrating the quantum advantage in NISQ devices. When running such algorithms, effects from quantum noise are inevitable. In our work, we consider a well-known…

Quantum Physics · Physics 2019-12-10 Cheng Xue , Zhao-Yun Chen , Yu-Chun Wu , Guo-Ping Guo

Quantum optimal control plays a crucial role in quantum computing by providing the interface between compiler and hardware. Solving the optimal control problem is particularly challenging for multi-qubit gates, due to the exponential growth…

Quantum Physics · Physics 2024-07-25 N. Anders Petersson , Stefanie Günther , Seung Whan Chung

We introduce a novel approach to translate arbitrary 3-SAT instances to Quadratic Unconstrained Binary Optimization (QUBO) as they are used by quantum annealing (QA) or the quantum approximate optimization algorithm (QAOA). Our approach…

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