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Related papers: Trotterization in Quantum Theory

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Understanding the intricate quantum spin dynamics of radical pair reactions is crucial for unraveling the underlying nature of chemical processes across diverse scientific domains. In this work, we leverage Trotterization to map coherent…

When simulating the time evolution of quantum many-body systems on a digital quantum computer, one faces the challenges of quantum noise and of the Trotter error due to time discretization. The Trotter error in integrable spin chains can be…

We propose a variational alternative to the Trotter-Suzuki decomposition that provides greater control over errors while preserving the unitary structure of time evolution. The variational parameters in our ansatz are derived from a global…

Quantum Physics · Physics 2025-11-20 Ibsal Assi , Michael Vogl , Meenu Kumari , J. P. F. LeBlanc

A typical quantum experiment has a bunch of apparatuses placed so that quantum systems can pass between them. We regard each use of an apparatus, along with some given outcome on the apparatus (a certain detector click or a certain meter…

Quantum Physics · Physics 2015-06-03 Lucien Hardy

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

Trotter decomposition is the basis of the digital quantum simulation. Asymmetric and symmetric decompositions are used in our GPU demonstration of the digital adiabatic quantum simulations of $2+1$ dimensional quantum $\mathbb{Z}_2$ lattice…

Quantum Physics · Physics 2020-09-02 Xiaopeng Cui , Yu Shi

Quantum dynamics can be simulated on a quantum computer by exponentiating elementary terms from the Hamiltonian in a sequential manner. However, such an implementation of Trotter steps has gate complexity depending on the total Hamiltonian…

Quantum Physics · Physics 2023-05-15 Guang Hao Low , Yuan Su , Yu Tong , Minh C. Tran

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

Quantum simulation is a foundational application for quantum computers, projected to offer insights into complex quantum systems beyond the reach of classical computation. However, with the exception of Trotter-based methods, which suffer…

Quantum Physics · Physics 2026-02-10 Amir Kalev , Itay Hen

The Trotter decomposition is a basic approach to Hamiltonian simulation (digital quantum simulation). The first-order Trotter decomposition is the simplest one, whose deviations from target dynamics are of the first order of a small…

Quantum Physics · Physics 2023-08-30 Takuya Hatomura

We discuss the deformation quantization approach for the teaching of quantum mechanics. This approach has certain conceptual advantages which make its consideration worthwhile. In particular, it sheds new light on the relation between…

Quantum Physics · Physics 2015-06-26 Allen C. Hirshfeld , Peter Henselder

Fourier and fractional-Fourier transformations are widely used in theoretical physics. In this paper we make quantum perspectives and generalization for the fractional Fourier transformation (FrFT). By virtue of quantum mechanical…

Mathematical Physics · Physics 2014-08-26 Jun-Hua Chen , Hong-Yi Fan

Quantized tensor trains (QTTs) are a multiscale computational framework that can potentially reduce the computational cost of solving partial differential equations and initial value problems by making low-rank approximations. However, its…

Computational Physics · Physics 2026-05-14 Erika Ye

We provide a recursive method for constructing product formula approximations to exponentials of commutators, giving the first approximations that are accurate to arbitrarily high order. Using these formulas, we show how to approximate…

Quantum Physics · Physics 2013-11-22 Andrew M. Childs , Nathan Wiebe

We derive higher-order error bounds with small prefactors for a general Trotter product formula, generalizing a result of Childs et al. [Phys. Rev. X 11, 011020 (2021)]. We then apply these bounds to the real-time quantum time evolution…

Quantum Physics · Physics 2023-11-06 Ansgar Schubert , Christian B. Mendl

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

This work provides a rigorous and self-contained introduction to numerical methods for Hamiltonian simulation in quantum computing, with a focus on high-order product formulas for efficiently approximating the time evolution of quantum…

Quantum Physics · Physics 2025-07-16 Javier Lopez-Cerezo

Digital quantum simulation of many-body dynamics relies on Trotterization to decompose the target time evolution into elementary quantum gates operating at a fixed equidistant time discretization. Recent advances have outlined protocols…

Quantum Physics · Physics 2024-06-11 Hongzheng Zhao , Ao Chen , Shu-Wei Liu , Marin Bukov , Markus Heyl , Roderich Moessner

Quantum algorithms typically demand prohibitively complicated circuits to solve practical problems. Previous studies have shown that classical randomness can accelerate some specific quantum algorithms. In this work, we introduce the…

Quantum Physics · Physics 2026-01-15 Yue Wang , Qi Zhao

Compilation optimizes quantum algorithms performances on real-world quantum computers. To date, it is performed via classical optimization strategies. We introduce a class of quantum algorithms to perform compilation via quantum computers,…

Quantum Physics · Physics 2025-09-25 Davide Rattacaso , Daniel Jaschke , Marco Ballarin , Ilaria Siloi , Simone Montangero
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