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Blind quantum computation is a secure delegated quantum computing protocol where Alice who does not have sufficient quantum technology at her disposal delegates her computation to Bob who has a fully-fledged quantum computer in such a way…

Quantum Physics · Physics 2015-06-11 Tomoyuki Morimae

With the growing need for online and iterative graph processing, software systems that continuously process large-scale graphs become widely deployed. With optimizations inherent as part of their design, these systems are complex, and have…

Programming Languages · Computer Science 2020-06-15 Philip Dexter , Yu David Liu , Kenneth Chiu

Quantum computers have demonstrated utility in simulating quantum systems beyond brute-force classical approaches. As the community builds on these demonstrations to explore using quantum computing for applied research, algorithms and…

Although quantum computing holds promise to accelerate a wide range of computational tasks, the quantum simulation of quantum dynamics as originally envisaged by Feynman remains the most promising candidate for achieving quantum advantage.…

Quantum Physics · Physics 2024-07-25 Sam Cochran , James Stokes , Paramsothy Jayakumar , Shravan Veerapaneni

Solving finite-temperature properties of quantum many-body systems is generally challenging to classical computers due to their high computational complexities. In this article, we present experiments to demonstrate a hybrid…

Enhanced sampling simulations make the computational study of rare events feasible. A large family of such methods crucially depends on the definition of some collective variables (CVs) that could provide a low-dimensional representation of…

Computational Physics · Physics 2026-03-03 Jintu Zhang , Luigi Bonati , Enrico Trizio , Odin Zhang , Yu Kang , TingJun Hou , Michele Parrinello

This paper shows a novel way of simulating a Markov process by a quantum computer. The main purpose of the paper is to show a particular application of quantum computing in the field of stochastic processes analysis. Using a Quantum…

Quantum Physics · Physics 2020-01-08 Petar Nikolov

Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and…

Quantum Physics · Physics 2022-05-17 Bo Fang , M. Yusuf Özkaya , Ang Li , Ümit V. Çatalyürek , Sriram Krishnamoorthy

Carry Value Transformation (CVT) is a model of discrete dynamical system which is one special case of Integral Value Transformations (IVTs). Earlier in [5] it has been proved that sum of two non-negative integers is equal to the sum of…

Other Computer Science · Computer Science 2016-01-19 Jayanta Kumar Das , Pabitra Pal Choudhury , Sudhakar Sahoo

Accurately modeling quantum dissipative dynamics remains challenging due to environmental complexity and non-Markovian memory effects. Although machine learning provides a promising alternative to conventional simulation techniques, most…

Chemical Physics · Physics 2026-03-18 Muhammad Atif , Arif Ullah , Ming Yang

Variational quantum algorithms dominate contemporary gate-based quantum enhanced optimisation, eigenvalue estimation and machine learning. Here we establish the quantum computational universality of variational quantum computation by…

Quantum Physics · Physics 2021-05-25 Jacob Biamonte

Cardiovascular disease affects millions of people worldwide and its social and economic cost clearly motivates scientific research. Computer simulation can lead to a better understanding of cardiac physiology, and for pathology presents…

Biological Physics · Physics 2023-02-27 Toby Simpson

Quantum computers, besides offering substantial computational speedups, are also expected to provide the possibility of preserving the privacy of a computation. Here we show the first such experimental demonstration of blind quantum…

The rapid development of reliable Quantum Processing Units (QPU) opens up novel computational opportunities for machine learning. Here, we introduce a procedure for measuring the similarity between graph-structured data, based on the…

Quantum Physics · Physics 2021-09-29 Louis-Paul Henry , Slimane Thabet , Constantin Dalyac , Loïc Henriet

Most of the existing quantum neural network models, such as variational quantum circuits (VQCs), are limited in their ability to explore the non-linear relationships in input data. This gradually becomes the main obstacle for it to tackle…

Quantum Physics · Physics 2024-02-14 Jinyang Li , Ang Li , Weiwen Jiang

Quantum algorithms for Noisy Intermediate-Scale Quantum (NISQ) machines have recently emerged as new promising routes towards demonstrating near-term quantum advantage (or supremacy) over classical systems. In these systems samples are…

ZX-calculus is a high-level graphical formalism for qubit computation. In this paper we give the ZX-rules that enable one to derive all equations between 2-qubit Clifford+T quantum circuits. Our rule set is only a small extension of the…

Quantum Physics · Physics 2018-06-13 Bob Coecke , Quanlong Wang

The ZX-calculus is a graphical calculus for reasoning about pure state qubit quantum mechanics. It is complete for pure qubit stabilizer quantum mechanics, meaning any equality involving only stabilizer operations that can be derived using…

Quantum Physics · Physics 2014-12-31 Miriam Backens

We obtain sufficient conditions for the efficient simulation of a continuous variable quantum algorithm or process on a classical computer. The resulting theorem is an extension of the Gottesman-Knill theorem to continuous variable quantum…

Quantum Physics · Physics 2007-05-23 Stephen D. Bartlett , Barry C. Sanders , Samuel L. Braunstein , Kae Nemoto

This paper reviews recent advances in quantum learning theory for continuous-variable (CV) systems. Quantum learning theory investigates how to extract classical information from quantum systems as efficiently as possible. CV systems are…

Quantum Physics · Physics 2026-05-11 Francesco Anna Mele