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First quantized, grid-based methods for chemistry modelling are a natural and elegant fit for quantum computers. However, it is infeasible to use today's quantum prototypes to explore the power of this approach, because it requires a…

Quantum Physics · Physics 2023-03-09 Hans Hon Sang Chan , Richard Meister , Tyson Jones , David P. Tew , Simon C. Benjamin

The recent advent of commercially available quantum annealing hardware (QAH) has expanded opportunities for research into quantum annealing-based algorithms. In the domain of power systems, this advancement has driven increased interest in…

Optimization and Control · Mathematics 2025-03-26 Rosemary Barrass , Harsha Nagarajan , Carleton Coffrin

Integer factorization has been one of the cornerstone applications of the field of quantum computing since the discovery of an efficient algorithm for factoring by Peter Shor. Unfortunately, factoring via Shor's algorithm is well beyond the…

Quantum Physics · Physics 2018-08-28 Eric R. Anschuetz , Jonathan P. Olson , Alán Aspuru-Guzik , Yudong Cao

Complex quantum simulation workflows are often hindered by incompatible wavefunction representations adopted across different algorithmic frameworks. In particular, the mismatch between the first- and second-quantization formalisms prevents…

Quantum Physics · Physics 2026-05-01 Calvin Ku , Yu-Cheng Chen , Alice Hu , Min-Hsiu Hsieh

Advances in quantum algorithms suggest a tentative scaling advantage on certain combinatorial optimization problems. Recent work, however, has also reinforced the idea that barren plateaus render variational algorithms ineffective on large…

Quantum Physics · Physics 2025-03-14 Tim Bode , Krish Ramesh , Tobias Stollenwerk

This paper explores the use of quantum computing, specifically the use of HHL and VQLS algorithms, to solve optimal power flow problem in electrical grids. We investigate the effectiveness of these quantum algorithms in comparison to…

Quantum Physics · Physics 2024-12-10 Sajad Fathi Hafshejani , Md Mohsin Uddin , David Neufeld , Daya Gaur , Robert Benkoczi

A novel quantum-classical hybrid scheme is proposed to efficiently solve large-scale combinatorial optimization problems. The key concept is to introduce a Hamiltonian dynamics of the classical flux variables associated with the quantum…

Quantum Physics · Physics 2021-04-28 Hirotaka Irie , Haozhao Liang , Takumi Doi , Shinya Gongyo , Tetsuo Hatsuda

Despite the promise that fault-tolerant quantum computers can efficiently solve classically intractable problems, it remains a major challenge to find quantum algorithms that may reach computational advantage in the present era of noisy,…

Quantum Physics · Physics 2024-11-13 Miguel Murça , Duarte Magano , Yasser Omar

Quantum computers leverage the principles of quantum mechanics to do computation with a potential advantage over classical computers. While a single classical computer transforms one particular binary input into an output after applying one…

Emerging Technologies · Computer Science 2025-03-17 Francisco Chicano , Gabiel Luque , Zakaria Abdelmoiz Dahi , Rodrigo Gil-Merino

Many fundamental problems in data mining can be reduced to one or more NP-hard combinatorial optimization problems. Recent advances in novel technologies such as quantum and quantum-inspired hardware promise a substantial speedup for…

Machine Learning · Computer Science 2022-01-10 Osman Asif Malik , Hayato Ushijima-Mwesigwa , Arnab Roy , Avradip Mandal , Indradeep Ghosh

We present a novel multi-scale embedding scheme that links conventional QM/MM embedding and bootstrap embedding (BE) to allow simulations of large chemical systems on limited quantum devices. We also propose a mixed-basis BE scheme that…

We describe a novel analogue algorithm that allows the simultaneous factorization of an exponential number of large integers with a polynomial number of experimental runs. It is the interference-induced periodicity of "factoring"…

Quantum Physics · Physics 2016-03-14 Vincenzo Tamma

Nearest-neighbour clustering is a powerful set of heuristic algorithms that find natural application in the decoding of signals transmitted using the M-Quadrature Amplitude Modulation (M-QAM) protocol. Lloyd et al. proposed a quantum…

Classical machine learning theory and theory of quantum computations are among of the most rapidly developing scientific areas in our days. In recent years, researchers investigated if quantum computing can help to improve classical machine…

Quantum Physics · Physics 2019-06-26 D. V. Fastovets , Yu. I. Bogdanov , B. I. Bantysh , V. F. Lukichev

This paper introduces Quantum Classical Branch-and-Price (QCBP), a hybrid quantum-classical algorithm for the Vertex Coloring problem on neutral-atom Quantum Processing Units (QPUs). QCBP embeds quantum computation within the classical…

Quantum computers show potential for achieving computational advantage over classical computers, with many candidate applications in combinatorial optimisation. We present an application level benchmarking framework for near-term quantum…

We factorize a 48-bit integer using 10 trapped-ion qubits on a Quantinuum's quantum computer. This result outperforms the recent achievement by B. Yan et al., arXiv:2212.12372 (2022), increasing the success probability by a factor of 6 with…

Quantum Physics · Physics 2023-01-27 Narendra N. Hegade , Enrique Solano

Determining the prime factors of a given number N is a problem, which requires super-polynomial time for conventional digital computers. A polynomial-time algorithm was invented by P. Shor for quantum computers. However, the realization of…

Mesoscale and Nanoscale Physics · Physics 2016-10-12 Y. Khivintsev , M. Ranjbar , D. Gutierrez , H. Chiang , A. Kozhevnikov , Y. Filimonov , A. Khitun

Quantum computers promise to revolutionize our ability to simulate molecules, and cloud-based hardware is becoming increasingly accessible to a wide body of researchers. Algorithms such as Quantum Phase Estimation and the Variational…

Quantum Physics · Physics 2021-12-21 Kyle Sherbert , Frank Cerasoli , Marco Buongiorno Nardelli

Quantum machine learning has the potential to provide powerful algorithms for artificial intelligence. The pursuit of quantum advantage in quantum machine learning is an active area of research. For current noisy, intermediate-scale quantum…

Quantum Physics · Physics 2023-05-11 Rui Yang , Samuel Bosch , Bobak Kiani , Seth Lloyd , Adrian Lupascu