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Related papers: Hybrid Quantum Classical Simulations

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The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There…

Quantum Physics · Physics 2023-03-22 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

Variational Quantum optimization algorithms, such as the Variational Quantum Eigensolver (VQE) or the Quantum Approximate Optimization Algorithm (QAOA), are among the most studied quantum algorithms. In our work, we evaluate and improve an…

Quantum Physics · Physics 2022-10-24 David Winderl , Nicola Franco , Jeanette Miriam Lorenz

Quantum enhanced optimization of classical cost functions is a central theme of quantum computing due to its high potential value in science and technology. The variational quantum eigensolver (VQE) and the quantum approximate optimization…

Quantum Physics · Physics 2024-11-27 Giuseppe Scriva , Nikita Astrakhantsev , Sebastiano Pilati , Guglielmo Mazzola

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

In the present Noisy Intermediate-Scale Quantum (NISQ), hybrid algorithms that leverage classical resources to reduce quantum costs are particularly appealing. We formulate and apply such a hybrid quantum-classical algorithm to a power…

Combinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical hybrid algorithms, is designed to solve…

Quantum Physics · Physics 2024-03-12 Lixue Cheng , Yu-Qin Chen , Shi-Xin Zhang , Shengyu Zhang

The major advances in quantum computing over the last few decades have sparked great interest in applying it to solve the most challenging computational problems in a wide variety of areas. One of the most pronounced domains here are…

Quantum Physics · Physics 2024-04-11 Andreas Sturm , Bharadwaj Mummaneni , Leon Rullkötter

A key open question in quantum computing is whether quantum algorithms can potentially offer a significant advantage over classical algorithms for tasks of practical interest. Understanding the limits of classical computing in simulating…

Quantum Physics · Physics 2021-06-23 Matija Medvidovic , Giuseppe Carleo

Quantum computing is an emerging field on the multidisciplinary interface between physics, engineering, and computer science with the potential to make a large impact on computational intelligence (CI). The aim of this paper is to introduce…

Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQA), are suitable for implementation on NISQ computers. In this Letter we expand an implicit step of VQAs: the classical pre-computation subroutine which can…

Quantum Physics · Physics 2021-04-01 Jonathan Wurtz , Peter Love

Quantum computing is an important developing technology with the potential to revolutionise the landscape of scientific and business problems that can be practically addressed. The widespread excitement derives from the potential for a…

Quantum Physics · Physics 2022-11-24 R. Cumming , T. Thomas

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…

Analytical and practical evidence indicates the advantage of quantum computing solutions over classical alternatives. Quantum-based heuristics relying on the variational quantum eigensolver (VQE) and the quantum approximate optimization…

Quantum Physics · Physics 2023-01-05 Sarthak Gupta , Vassilis Kekatos

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

Quantum optimization allows for up to exponential quantum speedups for specific, possibly industrially relevant problems. As the key algorithm in this field, we motivate and discuss the Quantum Approximate Optimization Algorithm (QAOA),…

Quantum Physics · Physics 2025-11-18 Jonas Stein , Maximilian Zorn , Leo Sünkel , Thomas Gabor

Hybrid algorithms that combine quantum and classical resources have become commonplace in quantum computing. The variational quantum eigensolver (VQE) is routinely used to solve prototype problems. Currently, hybrid algorithms use no more…

Quantum Physics · Physics 2024-08-27 Manpreet Singh Jattana

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

Hybrid quantum-classical variational algorithms such as the variational quantum eigensolver (VQE) and the quantum approximate optimization algorithm (QAOA) are promising applications for noisy, intermediate-scale quantum (NISQ) computers.…

Quantum Physics · Physics 2021-09-13 William M. Kirby , Peter J. Love

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…

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…

Machine Learning · Computer Science 2022-06-16 Sami Khairy , Ruslan Shaydulin , Lukasz Cincio , Yuri Alexeev , Prasanna Balaprakash
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