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Many astrophysical simulations involve extreme dynamic range of timescales around 'special points' in the domain (e.g. black holes, stars, planets, disks, galaxies, shocks, mixing interfaces), where processes on small scales couple strongly…

Instrumentation and Methods for Astrophysics · Physics 2026-05-11 Philip F. Hopkins , Elias R. Most

Analog quantum simulations---simulations of one Hamiltonian by another---is one of the major goals in the noisy intermediate-scale quantum computation (NISQ) era, and has many applications in quantum complexity. We initiate the rigorous…

Quantum Physics · Physics 2019-10-03 Dorit Aharonov , Leo Zhou

Simulations of quantum systems with Hamiltonian classical stochastic noise can be challenging when the noise exhibits temporal correlations over a multitude of time scales, such as for $1/f$ noise in solid-state quantum information…

Quantum Physics · Physics 2025-02-19 Tameem Albash , Steve Young , N. Tobias Jacobson

While non-Hermitian Hamiltonians enable exotic dynamical phenomena, implementing their nonunitary time evolution on near-term quantum devices remains challenging. We propose a hardware-friendly protocol that simulates non-Hermitian dynamics…

Quantum Physics · Physics 2026-02-26 Hiroki Kuji , Suguru Endo , Tetsuro Nikuni , Ryusuke Hamazaki , Yuichiro Matsuzaki

In this paper, we present a spherical Fast Multipole Method (sFMM) for ray tracing simulation of gravitational lensing (GL) on a curved sky. The sFMM is a non-trivial extension of the Fast Multiple Method (FMM) to sphere $\mathbb S^2$, and…

Instrumentation and Methods for Astrophysics · Physics 2023-05-17 Xingpao Suo , Xi Kang , Chengliang Wei , Guoliang Li

We present a generic partition refinement algorithm that quotients coalgebraic systems by behavioural equivalence, an important task in system analysis and verification. Coalgebraic generality allows us to cover not only classical…

Data Structures and Algorithms · Computer Science 2023-06-22 Thorsten Wißmann , Ulrich Dorsch , Stefan Milius , Lutz Schröder

The difficulty of simulating quantum dynamics depends on the norm of the Hamiltonian. When the Hamiltonian varies with time, the simulation complexity should only depend on this quantity instantaneously. We develop quantum simulation…

Quantum Physics · Physics 2020-04-21 Dominic W. Berry , Andrew M. Childs , Yuan Su , Xin Wang , Nathan Wiebe

Simulation of quantum chemistry is expected to be a principal application of quantum computing. In quantum simulation, a complicated Hamiltonian describing the dynamics of a quantum system is decomposed into its constituent terms, where the…

Quantum Physics · Physics 2020-03-04 Yingkai Ouyang , David R. White , Earl T. Campbell

In this work we study the convergence of a classical algorithm called Simulated Quantum Annealing (SQA) on the Spike Hamiltonian, a specific toy model Hamiltonian for quantum-mechanical tunneling introduced by [FGG02]. This toy model…

Quantum Physics · Physics 2020-12-01 Thiago Bergamaschi

We present an extension of many-body downfolding methods to reduce the resources required in the quantum phase estimation (QPE) algorithm. In this paper, we focus on the Schrieffer--Wolff (SW) transformation of the electronic Hamiltonians…

Quantum Physics · Physics 2022-11-22 Karol Kowalski , Nicholas P. Bauman

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

In this contribution, we present a numerical analysis of the continuous stochastic gradient (CSG) method, including applications from topology optimization and convergence rates. In contrast to standard stochastic gradient optimization…

Optimization and Control · Mathematics 2023-03-23 Max Grieshammer , Lukas Pflug , Michael Stingl , Andrian Uihlein

Computation of the Green's function is crucial to study the properties of quantum many-body systems such as strongly correlated systems. Although the high-precision calculation of the Green's function is a notoriously challenging task on…

The "folding algorithm"\cite{fold1} is a matrix product state algorithm for simulating quantum systems that involves a spatial evolution of a matrix product state. Hence, the computational effort of this algorithm is controlled by the…

Quantum Physics · Physics 2015-03-18 M. B. Hastings , R. Mahajan

Gaussian processes (GPs) are important probabilistic tools for inference and learning in spatio-temporal modelling problems such as those in climate science and epidemiology. However, existing GP approximations do not simultaneously support…

Machine Learning · Computer Science 2021-06-21 Will Tebbutt , Arno Solin , Richard E. Turner

Gaussian boson sampling (GBS) is not only a feasible protocol for demonstrating quantum computational advantage, but also mathematically associated with certain graph-related and quantum chemistry problems. In particular, it is proposed…

We present an efficient quantum algorithm for simulating the evolution of a sparse Hamiltonian H for a given time t in terms of a procedure for computing the matrix entries of H. In particular, when H acts on n qubits, has at most a…

Quantum Physics · Physics 2007-05-23 Dominic W. Berry , Graeme Ahokas , Richard Cleve , Barry C. Sanders

We present a universal quantum Monte Carlo algorithm for simulating arbitrary high-spin (spin greater than 1/2) Hamiltonians, based on the recently developed permutation matrix representation (PMR) framework. Our approach extends a…

Computational Physics · Physics 2026-01-27 Arman Babakhani , Lev Barash , Itay Hen

Communication-efficient SGD algorithms, which allow nodes to perform local updates and periodically synchronize local models, are highly effective in improving the speed and scalability of distributed SGD. However, a rigorous convergence…

Machine Learning · Computer Science 2019-01-28 Jianyu Wang , Gauri Joshi

We present an exact spin-elimination technique that reduces the dimensionality of both quadratic and k-local Ising Hamiltonians while preserving their original ground-state configurations. By systematically replacing each removed spin with…

Quantum Physics · Physics 2025-05-13 Natalia G. Berloff