English
Related papers

Related papers: Quantum optimization using variational algorithms …

200 papers

A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding is that achieving quantum advantage in this area will…

Quantum Physics · Physics 2023-11-08 Guoming Wang , Daniel Stilck França , Ruizhe Zhang , Shuchen Zhu , Peter D. Johnson

Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum…

Quantum Physics · Physics 2019-12-17 Hsin-Yuan Huang , Kishor Bharti , Patrick Rebentrost

With rapid advances in quantum hardware, a central question is whether quantum devices with or without full error correction can outperform classical computers on practically relevant problems. Variational Quantum Algorithms (VQAs) have…

Quantum Physics · Physics 2025-09-09 Adelina Bärligea , Benedikt Poggel , Jeanette Miriam Lorenz

Implementing variational quantum algorithms with noisy intermediate-scale quantum machines of up to a hundred qubits is nowadays considered as one of the most promising routes towards achieving a quantum practical advantage. In multiqubit…

Quantum Physics · Physics 2021-08-18 Andrey Kardashin , Anastasiia Pervishko , Jacob Biamonte , Dmitry Yudin

We explore the preparation of specific nuclear states on gate-based quantum hardware using variational algorithms. Large scale classical diagonalization of the nuclear shell model have reached sizes of $10^9 - 10^{10}$ basis states, but are…

Nuclear Theory · Physics 2022-07-11 I. Stetcu , A. Baroni , J. Carlson

The last decade has witnessed remarkable progress in the development of quantum technologies. Although fault-tolerant devices likely remain years away, the noisy intermediate-scale quantum devices of today may be leveraged for other…

Solving optimisation problems is a promising near-term application of quantum computers. Quantum variational algorithms leverage quantum superposition and entanglement to optimise over exponentially large solution spaces using an…

Quantum Physics · Physics 2022-10-13 Edric Matwiejew , Jason Pye , Jingbo B. Wang

Variational Quantum Algorithms have emerged as a leading paradigm for near-term quantum computation. In such algorithms, a parameterized quantum circuit is controlled via a classical optimization method that seeks to minimize a…

Quantum Physics · Physics 2021-10-19 Javier Rivera-Dean , Patrick Huembeli , Antonio Acín , Joseph Bowles

Variational quantum algorithms have been advocated as promising candidates to solve combinatorial optimization problems on near-term quantum computers. Their methodology involves transforming the optimization problem into a quadratic…

Quantum Physics · Physics 2023-08-01 Zoé Verchère , Sourour Elloumi , Andrea Simonetto

Variational quantum algorithms are proposed to solve relevant computational problems on near term quantum devices. Popular versions are variational quantum eigensolvers and quantum ap- proximate optimization algorithms that solve ground…

Quantum Physics · Physics 2022-04-15 Lennart Bittel , Martin Kliesch

To arrive at some viable product design, product development processes frequently use numerical simulations and mathematical programming techniques. Topology optimization, in particular, is one of the most promising techniques for…

Quantum Physics · Physics 2025-05-06 Yuki Sato , Ruho Kondo , Satoshi Koide , Seiji Kajita

Despite extensive research efforts, few quantum algorithms for classical optimization demonstrate realizable quantum advantage. The utility of many quantum algorithms is limited by high requisite circuit depth and nonconvex optimization…

Quantum Physics · Physics 2022-01-27 Taylor L. Patti , Jean Kossaifi , Anima Anandkumar , Susanne F. Yelin

Variational hybrid quantum-classical algorithms are some of the most promising workloads for near-term quantum computers without error correction. The aim of these variational algorithms is to guide the quantum system to a target state that…

Quantum Physics · Physics 2021-03-18 Shavindra P. Premaratne , A. Y. Matsuura

One of the challenging scientific computing problems is topology optimization, where searching through the combinatorially complex configurations and solving the constraints of partial differential equations need to be done simultaneously.…

Quantum Physics · Physics 2025-03-05 Jungin E. Kim , Yan Wang

Variational Quantum Algorithms (VQAs) are relatively robust to noise, but errors are still a significant detriment to VQAs on near-term quantum machines. It is imperative to employ error mitigation techniques to improve VQA fidelity. While…

An essential component of many sophisticated metaheuristics for solving combinatorial optimization problems is some variation of a local search routine that iteratively searches for a better solution within a chosen set of immediate…

Quantum Physics · Physics 2025-02-05 M. Podobrii , V. Kuzmin , V. Voloshinov , M. Veshchezerova , M. R. Perelshtein

Combinatorial optimization is considered a promising class of problems in which quantum computers can show significant advantages. However, problems of practical relevance typically have more variables than current or foreseeable quantum…

Quantum Physics · Physics 2025-12-23 Mathias Schmid , Naeimeh Mohseni , Michael J. Hartmann

Quantum computing brings a promise of new approaches into computational quantum chemistry. While universal, fault-tolerant quantum computers are still not available, we want to utilize today's noisy quantum processors. One of their flagship…

With an ever-expanding ecosystem of noisy and intermediate-scale quantum devices, exploring their possible applications is a rapidly growing field of quantum information science. In this work, we demonstrate that variational quantum…

Quantum Physics · Physics 2021-07-16 Johannes Jakob Meyer , Johannes Borregaard , Jens Eisert

Variational quantum metrology represents a powerful tool for optimizing generic estimation strategies, combining the principles of variational optimization with the techniques of quantum metrology. Such optimization procedures result…