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Estimating transition rates in open quantum systems is hampered by computing-resource demands that grow rapidly with system size. We present a quantum-simulation framework that enables efficient estimation by recasting the transition rate,…

Quantum Physics · Physics 2025-12-16 Robson Christie , Kyunghyun Baek , Jeongho Bang , Jaewoo Joo

Quantum mechanical problems are among the hardest to simulate and, in some cases, remain intractable even for the most powerful computers. Quantum computing has emerged as a new technological platform to address such challenges, with rapid…

Quantum Physics · Physics 2025-09-01 Alexander Miessen

Imaginary-time evolution plays an important role in algorithms for computing ground-state and thermal equilibrium properties of quantum systems, but can be challenging to simulate on classical computers. Many quantum algorithms for…

Quantum Physics · Physics 2025-07-22 Annie Ray , Esha Swaroop , Ningping Cao , Michael Vasmer , Anirban Chowdhury

In this work, we developed an efficient quantum algorithm for the simulation of non-Markovian quantum dynamics, based on the Feynman path integral formulation. The algorithm scales polynomially with the number of native gates and the number…

Quantum Physics · Physics 2024-11-28 Avin Seneviratne , Peter L. Walters , Fei Wang

We develop an analog classical simulation algorithm of noiseless quantum dynamics. By formulating the Schr\"{o}dinger equation into a linear system of real-valued ordinary differential equations (ODEs), the probability amplitudes of a…

Quantum Physics · Physics 2025-02-11 Ka-Wa Yip

Important nonlinear dynamics, such as those found in plasma and fluid systems, are typically hard to simulate on classical computers. Thus, if fault-tolerant quantum computers could efficiently solve such nonlinear problems, it would be a…

We present a variational algorithm for fault tolerant quantum computing to solve a system of linear equations which directly maximises the parameters of the target fidelity. This so-called measurement test algorithm can be applied to any…

Quantum Physics · Physics 2026-04-30 Alain Giresse Tene , Thomas Konrad

Identifying and calibrating quantitative dynamical models for physical quantum systems is important for a variety of applications. Here we present a closed-loop Bayesian learning algorithm for estimating multiple unknown parameters in a…

Assessment of practical quantum information processing (QIP) remains partial without understanding limits imposed by noise. Unfortunately, mere description of noise grows exponentially with system size, becoming cumbersome even for modest…

Quantum Physics · Physics 2024-08-14 Vikesh Siddhu , John Smolin

We present an efficient algorithm for simulating open quantum systems dynamics described by the Lindblad master equation on quantum computers, addressing key challenges in the field. In contrast to existing approaches, our method achieves…

Quantum Physics · Physics 2024-12-31 Giovanni Di Bartolomeo , Michele Vischi , Tommaso Feri , Angelo Bassi , Sandro Donadi

The efficient simulation of quantum dynamics and ground states is a central challenge in physics and a key frontier for quantum advantage. While short-time evolution in one-dimensional systems can often be simulated classically, extending…

Quantum Physics · Physics 2025-09-22 Yusen Wu , Yukun Zhang , Chuan Wang , Xiao Yuan

Designing quantum algorithms for simulating quantum systems has seen enormous progress, yet few studies have been done to develop quantum algorithms for open quantum dynamics despite its importance in modeling the system-environment…

Quantum Physics · Physics 2022-02-11 Zixuan Hu , Rongxin Xia , Sabre Kais

In this Letter, we strengthen and extend the connection between simulation and estimation to exploit simulation routines that do not exactly compute the probability of experimental data, known as the likelihood function. Rather, we provide…

Quantum Physics · Physics 2014-04-14 Christopher Ferrie , Christopher E. Granade

We obtain exact analytic expressions for a class of functions expressed as integrals over the Haar measure of the unitary group in d dimensions. Based on these general mathematical results, we investigate generic dynamical properties of…

Quantum Physics · Physics 2013-04-30 Manuel Gessner , Heinz-Peter Breuer

We present two quantum algorithms based on evolution randomization, a simple variant of adiabatic quantum computing, to prepare a quantum state $\vert x \rangle$ that is proportional to the solution of the system of linear equations $A…

Quantum Physics · Physics 2019-02-20 Yigit Subasi , Rolando D. Somma , Davide Orsucci

The logarithm-determinant is an widely-present operation in many areas of physics and computer science. Derivatives of the logarithm-determinant compute physically relevant quantities in statistical physics models, quantum field theories,…

Quantum Physics · Physics 2025-09-23 Thomas E. Baker , Jaimie A. Greasley

Simulating the dynamics of open quantum systems is a crucial task in quantum computing, offering wide-ranging applications but remaining computationally challenging. In this paper, we propose two quantum algorithms for simulating the…

Quantum Physics · Physics 2025-10-29 Sirui Peng , Xiaoming Sun , Qi Zhao , Hongyi Zhou

Due to the exponential growth of the state space of coupled quantum systems it is not possible, in general, to numerically store the state of a very large number of quantum systems within a classical computer. We demonstrate a method for…

Quantum Physics · Physics 2017-02-07 J. J. Bowen , V. M. Dwyer , I. W. Phillips , M. J. Everitt

The physics of Markovian open quantum systems can be described by quantum master equations. These are dynamical equations, that incorporate the Hamiltonian and jump operators, and generate the system's time evolution. Reconstructing the…

Quantum Physics · Physics 2020-07-01 Eitan Ben Av , Yotam Shapira , Nitzan Akerman , Roee Ozeri

We propose a quantum algorithm to solve systems of nonlinear algebraic equations. In the ideal case the complexity of the algorithm is linear in the number of variables $n$, which means our algorithm's complexity is less than $O(n^{3})$ of…

Quantum Physics · Physics 2019-03-15 Peng Qian , Wei-Cong Huang , Gui-Lu Long