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Quantum computers have the potential to revolutionize diverse fields, including quantum chemistry, materials science, and machine learning. However, contemporary quantum computers experience errors that often cause quantum programs run on…

Quantum Physics · Physics 2025-02-27 Daniel Hothem , Ashe Miller , Timothy Proctor

Quantum computers are designed to outperform standard computers by running quantum algorithms. Areas in which quantum algorithms can be applied include cryptography, search and optimisation, simulation of quantum systems, and solving large…

Quantum Physics · Physics 2016-02-24 Ashley Montanaro

Characterization of noise in current near-term quantum devices is of paramount importance to fully use their computational power. However, direct quantum process tomography becomes unfeasible for systems composed of tens of qubits. A…

The string-net condensate is a new class of materials which exhibits the quantum topological order. In order to answer the important question, "how useful is the string-net condensate in quantum information processing?", we consider the…

Quantum Physics · Physics 2015-05-20 Tomoyuki Morimae

Quantum computers promise to efficiently solve important problems classical computers never will. However, in order to capitalize on these prospects, a fully automated quantum software stack needs to be developed. This involves a multitude…

Quantum Physics · Physics 2023-01-12 Robert Wille , Lukas Burgholzer , Stefan Hillmich , Thomas Grurl , Alexander Ploier , Tom Peham

Recent progress in applying complex network theory to problems in quantum information has resulted in a beneficial crossover. Complex network methods have successfully been applied to transport and entanglement models while information…

Quantum Physics · Physics 2019-05-22 Jacob Biamonte , Mauro Faccin , Manlio De Domenico

Errors are the fundamental barrier to the development of quantum systems. Quantum networks are complex systems formed by the interconnection of multiple components and suffer from error accumulation. Characterizing errors introduced by…

Accurate molecular force fields are of paramount importance for the efficient implementation of molecular dynamics techniques at large scales. In the last decade, machine learning methods have demonstrated impressive performances in…

Quantum Physics · Physics 2022-07-22 Oriel Kiss , Francesco Tacchino , Sofia Vallecorsa , Ivano Tavernelli

Quantum networks of quantum objects promise to be exponentially more powerful than the objects considered independently. To live up to this promise will require the development of error mitigation and correction strategies to preserve…

Neural networks are being used to improve the probing of the state spaces of many particle systems as approximations to wavefunctions and in order to avoid the recurring sign problem of quantum monte-carlo. One may ask whether the usual…

Machine Learning · Computer Science 2022-06-02 Andrei T. Patrascu

Neural networks are a promising tool for characterizing intermediate-scale quantum devices from limited amounts of measurement data. A challenging problem in this area is to learn the action of an unknown quantum process on an ensemble of…

Quantum Physics · Physics 2023-12-06 Yan Zhu , Ya-Dong Wu , Qiushi Liu , Yuexuan Wang , Giulio Chiribella

A tensor network is a type of decomposition used to express and approximate large arrays of data. A given data-set, quantum state or higher dimensional multi-linear map is factored and approximated by a composition of smaller multi-linear…

Quantum Physics · Physics 2022-07-08 Richik Sengupta , Soumik Adhikary , Ivan Oseledets , Jacob Biamonte

This article summarises the current status of classical communication networks and identifies some critical open research challenges that can only be solved by leveraging quantum technologies. By now, the main goal of quantum communication…

Information Theory · Computer Science 2021-06-08 Roberto Ferrara , Riccardo Bassoli , Christian Deppe , Frank H. P. Fitzek , Holger Boche

Tensor networks are a very powerful data structure tool originating from quantum system simulations. In recent years, they have seen increased use in machine learning, mostly in trainings with gradient-based techniques, due to their…

Quantum Physics · Physics 2024-12-24 Sergi Masot-Llima , Artur Garcia-Saez

Quantum networks play a major role in long-distance communication, quantum cryptography, clock synchronization, and distributed quantum computing. Generally, these protocols involve many independent sources sharing entanglement among…

Quantum Physics · Physics 2020-09-16 Johan Åberg , Ranieri Nery , Cristhiano Duarte , Rafael Chaves

A future quantum network will consist of quantum processors that are connected by quantum channels, just like conventional computers are wired up to form the Internet. In contrast to classical devices, however, the entanglement and…

Quantum Physics · Physics 2022-12-28 Andreas Reiserer

This article explores the current state and future prospects of quantum computing in industrial environments. Firstly, it describes three main paradigms in this field of knowledge: gate-based quantum computers, quantum annealers, and tensor…

Quantum computing is a rapidly developing field in the second wave of quantum development, with the potential to revolutionize a wide range of industries and fields of study. As the capabilities of quantum computers continue to advance,…

Physics and Society · Physics 2023-03-10 Astrid Bötticher , Zeki C. Seskir , Johannes Ruhland

The vision of a quantum internet is to fundamentally enhance Internet technology by enabling quantum communication between any two points on Earth. While the first realisations of small scale quantum networks are expected in the near…

Networking and Internet Architecture · Computer Science 2019-09-19 Wojciech Kozlowski , Stephanie Wehner

Tensor networks provide a powerful new framework for classifying and simulating correlated and topological phases of quantum matter. Their central premise is that strongly correlated matter can only be understood by studying the underlying…

Strongly Correlated Electrons · Physics 2026-01-21 Bram Vancraeynest-De Cuiper , Weronika Wiesiolek , Frank Verstraete