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In adiabatic quantum computing the aim is to track an eigenstate as the Hamiltonian changes. In the usual setup this is achieved using the natural time-dependent Hamiltonian evolution of the system and the main technical tool is the…

Quantum Physics · Physics 2026-05-29 Joseph Cunningham , Jérémie Roland

Current approaches to fault-tolerant quantum computation will not enable useful quantum computation on near-term devices of 50 to 100 qubits. Leading proposals, such as the color code and surface code schemes, must devote a large fraction…

Quantum Physics · Physics 2017-11-08 Peter D. Johnson , Jonathan Romero , Jonathan Olson , Yudong Cao , Alán Aspuru-Guzik

We provide practical simulation methods for scalar field theories on a quantum computer that yield improved asymptotics as well as concrete gate estimates for the simulation and physical qubit estimates using the surface code. We achieve…

Combinatorial optimization is a promising application for near-term quantum computers, however, identifying performant algorithms suited to noisy quantum hardware remains as an important goal to potentially realizing quantum computational…

Quantum Physics · Physics 2025-04-01 Titus D. Morris , Ananth Kaushik , Martin Roetteler , Phillip C. Lotshaw

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected Variational Quantum Dynamics (pVQD) algorithm, that performs a global optimization with linear…

Quantum Physics · Physics 2025-02-20 David Linteau , Stefano Barison , Netanel Lindner , Giuseppe Carleo

Quantum simulation is a cornerstone application for quantum computing, yet standard methods face a trade-off between circuit depth and accuracy: Trotterization depth scales with the number of Hamiltonian terms $L$, while sampling-based…

Quantum Physics · Physics 2026-05-01 Sangjin Lee , Sangkook Choi

We discuss two primitive algorithms to evaluate overlaps and transition matrix time series, which are used to construct a variety of quantum-assisted quantum control algorithms implementable on NISQ devices. Unlike previous approaches, our…

Quantum Physics · Physics 2022-06-30 Guru-Vamsi Policharla , Sai Vinjanampathy

As first proposed for the adiabatic quantum information processing by Wu, Byrd and Lidar [ Phys. Rev. Lett. 89, 057904 (2002)], the Trotterization technique is a very useful tool for universal quantum computing, and in particular, the…

Quantum Physics · Physics 2018-06-05 Yin Sun , Jun-Yi Zhang , Mark S. Byrd , Lian-Ao Wu

Compiling time-evolution operators of the form $U(t)=e^{-iHt}$ into hardware-native gate sequences is a central bottleneck for digital quantum simulation on noisy intermediate-scale quantum (NISQ) devices. Generic transpilation treats…

Quantum Physics · Physics 2026-04-30 F. S. Luiz , P. N. Ferreira , M. C. de Oliveira

Near term quantum computers suffer from the presence of different noise sources. In order to mitigate for this effect and acquire results with significantly better accuracy, there is the urge of designing efficient error correction or error…

Hamiltonian simulation is a promising application for quantum computers to achieve a quantum advantage. We present classical algorithms based on tensor network methods to optimize quantum circuits for this task. We show that, compared to…

Quantum Physics · Physics 2023-06-05 Conor Mc Keever , Michael Lubasch

Tensor-network simulations of quantum many-body dynamics are fundamentally limited by entanglement build-up, which leads to exponentially growing computational costs. Furthermore, these classical simulation algorithms are inherently…

Quantum Physics · Physics 2026-04-16 Fredrik Hasselgren , Bálint Koczor

Quantum simulation is a cornerstone application of quantum computing, yet how fundamental quantum resources--entanglement and non-stabilizerness (``magic")--shape simulation fidelity remains an open question. In this work, we establish a…

Quantum Physics · Physics 2026-04-16 Xiangran Zhang , Jue Xu , Qi Zhao , You Zhou

Simulating quantum imaginary-time evolution (QITE) is a major promise of quantum computation. However, the known algorithms are either probabilistic (repeat until success) with impractically small success probabilities or coherent (quantum…

Quantum Physics · Physics 2023-11-02 Thais de Lima Silva , Márcio M. Taddei , Stefano Carrazza , Leandro Aolita

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly…

Path integrals are usually formulated in discrete Euclidean time using the Trotter formula. We propose a new method to study discrete quantum systems, in which we work directly in the Euclidean time continuum. The method is of general…

Condensed Matter · Physics 2014-10-13 B. B. Beard , U. -J. Wiese

The time evolution of a physical system is generally described by a differential equation, which can be solved numerically by adopting a difference scheme with space-time discretization. This discretization, as a numerical artifact, results…

Quantum Physics · Physics 2024-02-01 Shuohang Wu , Zi Cai

Quantum computing gives direct access to the study of real-time dynamics of quantum many-body systems. In principle, it is possible to directly calculate non-equal-time correlation functions, from which one can detect interesting phenomena,…

Noise in quantum devices is generally considered detrimental to computational accuracy. However, the recent proposal of noise-assisted simulation has demonstrated that noise can be an asset in digital quantum simulations of open systems on…

Practical implementation of many quantum algorithms known today is limited by the coherence time of the executing quantum hardware and quantum sampling noise. Here we present a machine learning algorithm, NISQRC, for qubit-based quantum…

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