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We propose a general-purpose, self-adaptive approach to construct variational wavefunction ans\"atze for highly accurate quantum dynamics simulations based on McLachlan's variational principle. The key idea is to dynamically expand the…

Scalable quantum algorithms for the simulation of quantum many-body systems in thermal equilibrium are important for predicting properties of quantum matter at finite temperatures. Here we describe and benchmark a quantum computing version…

Quantum Physics · Physics 2023-09-20 João C. Getelina , Niladri Gomes , Thomas Iadecola , Peter P. Orth , Yong-Xin Yao

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

Adaptive quantum variational algorithms are particularly promising for simulating strongly correlated systems on near-term quantum hardware, but they are not yet viable due, in large part, to the severe coherence time limitations on current…

The advection-diffusion equation is simulated on a superconducting quantum computer via several quantum algorithms. Three formulations are considered: (1) Trotterization, (2) variational quantum time evolution (VarQTE), and (3) adaptive…

Quantum simulation has begun to penetrate the field of quantum chemistry in hopes of efficiently calculating ground state energies and approximating real-time evolution. With modern research highlighting nonadiabatic dynamics, tunably…

Quantum Physics · Physics 2026-05-08 Joshua M. Courtney , P. C. Stancil

Implementing time-evolution operators in shallow quantum circuits is important for quantum simulations. The standard method of Trotterization requires a large number of gates to achieve practical accuracy. Variational Quantum Simulation…

Quantum Physics · Physics 2026-03-09 Satoru Shoji , Kosuke Ito , Yukihiro Shimizu , Keisuke Fujii

In this paper, we present an application of the variational quantum simulation (VQS) framework to capture finite-temperature open-system dynamics on near-term quantum hardware. By embedding the generalized amplitude-damping channel into the…

Adaptive Variational Quantum Dynamics (AVQD) algorithms offer a promising approach to providing quantum-enabled solutions for systems treated within the purview of open quantum dynamical evolution. In this study, we employ the unrestricted…

Quantum Physics · Physics 2024-03-13 Saurabh Shivpuje , Manas Sajjan , Yuchen Wang , Zixuan Hu , Sabre Kais

Classical simulations of quantum circuits are vital for assessing potential quantum advantage and benchmarking devices, yet they require sophisticated methods to avoid the exponential growth of resources. Tensor network approaches, in…

We present an empirical analysis of the scaling of the minimal quantum circuit depth required for a variational quantum simulation (VQS) method to obtain a solution to the time evolution of a quantum system within a predefined error…

Quantum Physics · Physics 2026-04-14 Mario Ponce , Thomas Cope , Inés de Vega , Martin Leib

Variational quantum dynamics simulations (VQDS) provide a promising route to simulate real- and imaginary-time quantum dynamics on noisy intermediate-scale quantum devices using fixed-depth circuits. However, their practical performance is…

Quantum Physics · Physics 2026-05-21 Feng Zhang , Niladri Gomes , Joshua Aftergood , Thomas Iadecola , Yong-Xin Yao , Peter P. Orth

An adaptive variational quantum imaginary time evolution (AVQITE) approach is introduced that yields efficient representations of ground states for interacting Hamiltonians on near-term quantum computers. It is based on McLachlan's…

Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. This approach typically relies on deep circuits and is therefore hampered by the substantial…

Quantum Physics · Physics 2022-01-06 Alexander Miessen , Pauline J. Ollitrault , Ivano Tavernelli

Variational quantum algorithms (VQAs) are promising methods to demonstrate quantum advantage on near-term devices as the required resources are divided between a quantum simulator and a classical optimizer. As such, designing a VQA which is…

Quantum Physics · Physics 2022-05-20 Yuhan Huang , Qingyu Li , Xiaokai Hou , Rebing Wu , Man-Hong Yung , Abolfazl Bayat , Xiaoting Wang

Simulating the dynamics of large quantum systems is a formidable yet vital pursuit for obtaining a deeper understanding of quantum mechanical phenomena. While quantum computers hold great promise for speeding up such simulations, their…

Quantum Physics · Physics 2024-03-27 Gian Gentinetta , Friederike Metz , Giuseppe Carleo

We investigate the potential of near-term quantum algorithms for solving partial differential equations (PDEs), focusing on a linear one-dimensional advection-diffusion equation as a test case. This study benchmarks a ground-state…

Quantum Physics · Physics 2025-04-29 A. Barış Özgüler

Quantum dynamics compilation is an important task for improving quantum simulation efficiency: It aims to synthesize multi-qubit target dynamics into a circuit consisting of as few elementary gates as possible. Compared to deterministic…

Quantum Physics · Physics 2024-09-26 Yuxuan Zhang , Roeland Wiersema , Juan Carrasquilla , Lukasz Cincio , Yong Baek Kim

We present an efficient approach to simulate real-time quantum dynamics using Projected Variational Quantum Dynamics (PVQD), where the computational cost is reduced by strategically optimizing only a subset of the variational parameters at…

Quantum Physics · Physics 2026-01-06 Harshdeep Singh , Sonjoy Majumder , Sabyashachi Mishra

Quantum metrology and sensing seek advantage in estimating an unknown parameter of some quantum state or channel, using entanglement such as spin squeezing produced by one-axis twists or other quantum resources. In particular, qubit phase…

Quantum Physics · Physics 2024-05-29 Tyler G. Thurtell , Akimasa Miyake
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