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A variational quantum algorithm for numerically solving partial differential equations (PDEs) on a quantum computer was proposed by Lubasch et al. In this paper, we generalize the method introduced by Lubasch et al. to cover a broader class…

Quantum Physics · Physics 2024-06-26 Abhijat Sarma , Thomas W. Watts , Mudassir Moosa , Yilian Liu , Peter L. McMahon

The Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. This model provides insight into a range of phenomena in correlated electron systems. We wish to examine the paradigm of quantum…

Quantum Physics · Physics 2026-05-12 Kunal Vyas , Fengping Jin , Hans De Raedt , Kristel Michielsen

We propose machine learning methods for solving fully nonlinear partial differential equations (PDEs) with convex Hamiltonian. Our algorithms are conducted in two steps. First the PDE is rewritten in its dual stochastic control…

Computational Finance · Quantitative Finance 2022-05-23 William Lefebvre , Grégoire Loeper , Huyên Pham

Density Matrix Exponentiation is a technique for simulating Hamiltonian dynamics when the Hamiltonian to be simulated is available as a quantum state. In this paper, we present a natural analogue to this technique, for simulating Markovian…

Quantum Physics · Physics 2023-09-06 Dhrumil Patel , Mark M. Wilde

We develop a Lindblad framework for quantum stochastic thermodynamics to study the nonequilibrium thermodynamics of open quantum systems. Our approach adopts the local quantum detailed balance condition, ensuring thermodynamic consistency…

Quantum Physics · Physics 2025-02-28 Jin-Fu Chen

A Koopman decomposition of a complex system leads to a representation in which nonlinear dynamics appear to be linear. The existence of a linear framework with which to analyse nonlinear dynamical systems brings new strategies for…

Fluid Dynamics · Physics 2019-03-12 Jeremy Parker , Jacob Page

Quantum computing promises to speed up some of the most challenging problems in science and engineering. Quantum algorithms have been proposed showing theoretical advantages in applications ranging from chemistry to logistics optimization.…

Quantum Physics · Physics 2021-11-12 Niklas Heim , Atiyo Ghosh , Oleksandr Kyriienko , Vincent E. Elfving

Eigenvalue transformations, which include solving time-dependent differential equations as a special case, have a wide range of applications in scientific and engineering computation. While quantum algorithms for singular value…

Quantum Physics · Physics 2024-11-07 Dong An , Andrew M. Childs , Lin Lin , Lexing Ying

Particle breakage due to collisional interactions plays a vital role in the development of several phenomena in science and engineering. The nonlinear collisional breakage equations (NCBEs) are a significant set of equations in this…

Numerical Analysis · Mathematics 2026-04-14 Arushi Arushi , Naresh Kumar

We study a new method - called Schrodingerisation introduced in [Jin, Liu, Yu, arXiv: 2212.13969] - for solving general linear partial differential equations with quantum simulation. This method converts linear partial differential…

Quantum Physics · Physics 2025-04-22 Shi Jin , Nana Liu , Yue Yu

The Lindblad approach to continuous quantum measurements is applied to a system composed of a two-level atom interacting with a stationary quantized electromagnetic field through a dispersive coupling fulfilling quantum nondemolition…

Quantum Physics · Physics 2009-10-31 Roberto Onofrio , Lorenza Viola

The Lindblad equation is an evolution equation for the density matrix in quantum theory. It is the general linear, Markovian, form which ensures that the density matrix is hermitian, trace 1, positive and completely positive. Some…

Mathematical Physics · Physics 2015-06-04 Philip Pearle

A diffusion probabilistic model (DPM) is a generative model renowned for its ability to produce high-quality outputs in tasks such as image and audio generation. However, training DPMs on large, high-dimensional datasets such as…

Quantum Physics · Physics 2025-11-05 Yunfei Wang , Ruoxi Jiang , Yingda Fan , Xiaowei Jia , Jens Eisert , Junyu Liu , Jin-Peng Liu

The Lattice Boltzmann method (LBM) is a well-established mesoscopic approach for simulating fluid dynamics by evolving particle distribution functions on discrete lattices. While the LBM is highly parallelizable on classical hardware, its…

Quantum Physics · Physics 2026-04-14 Trong Duong , Matthias Möller , Norbert Hosters

We apply Lie symmetry analysis of partial differential equations (PDEs) to the Euler-Lagrange equations of the two-Higgs-doublet model (2HDM), to determine its scalar Lie point symmetries. A Lie point symmetry is a structure-preserving…

High Energy Physics - Phenomenology · Physics 2026-01-26 M. Aa. Solberg

The quantum dynamics of a damped and forced harmonic oscillator described by a Lindblad master equation is analyzed. The master equation is converted into a matrix-vector representation and the resulting non-Hermitian Schr\"odinger equation…

Quantum Physics · Physics 2019-09-10 H. J. Korsch

An efficient, reliable, and interpretable global solution method, the Deep learning-based algorithm for Heterogeneous Agent Models (DeepHAM), is proposed for solving high dimensional heterogeneous agent models with aggregate shocks. The…

General Economics · Economics 2022-02-22 Jiequn Han , Yucheng Yang , Weinan E

In the paper we suggest the homotopy method for solving of the non linear evolution equation. This method consists of two steps. First is the analytical solution for the linearized version of the non-linear evolution deep in the saturation…

High Energy Physics - Phenomenology · Physics 2023-06-07 Carlos Contreras , Eugene Levin , Rodrigo Meneses

Quantum algorithms for solving linear systems of equations have generated excitement because of the potential speed-ups involved and the importance of solving linear equations in many applications. However, applying these algorithms can be…

The present work proposes a well-balanced finite volume-type numerical method for the solution of non-conservative hyperbolic partial differential equations (PDEs) with source terms. The method is characterized, first, by the use of a…

Numerical Analysis · Mathematics 2026-05-06 Chiara Colombo , Caterina Dalmaso , Lucas O. Müller , Annunziato Siviglia
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