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Related papers: Improved Time-independent Hamiltonian Simulation

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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

We present the problem of approximating the time-evolution operator $e^{-i\hat{H}t}$ to error $\epsilon$, where the Hamiltonian $\hat{H}=(\langle G|\otimes\hat{\mathcal{I}})\hat{U}(|G\rangle\otimes\hat{\mathcal{I}})$ is the projection of a…

Quantum Physics · Physics 2019-07-17 Guang Hao Low , Isaac L. Chuang

In this paper, time-independent Hamiltonian systems are investigated via a Lie-group/algebra formalism. The (unknown) solution linked with the Hamiltonian is considered to be a Lie-group transformation of the initial data, where the group…

Mathematical Physics · Physics 2020-08-10 Sébastien Bertrand

An exact invariant is derived for $n$-degree-of-freedom Hamiltonian systems with general time-dependent potentials. The invariant is worked out in two equivalent ways. In the first approach, we define a special {\it Ansatz\/} for the…

Classical Physics · Physics 2023-03-23 Jürgen Struckmeier , Claus Riedel

The physics of quantum mechanics is the inspiration for, and underlies, quantum computation. As such, one expects physical intuition to be highly influential in the understanding and design of many quantum algorithms, particularly…

Quantum Physics · Physics 2017-01-06 Guang Hao Low , Isaac L. Chuang

We present a new approach to simulating Hamiltonian dynamics based on implementing linear combinations of unitary operations rather than products of unitary operations. The resulting algorithm has superior performance to existing simulation…

Quantum Physics · Physics 2018-08-02 Andrew M. Childs , Nathan Wiebe

The most widely used approach for simulating the dynamics of time-dependent Hamiltonians via quantum computation depends on the quantum-classical hybrid variational quantum time evolution algorithm, in which ordinary differential equations…

Quantum Physics · Physics 2026-03-19 Minchen Qiao , Zi-Ming Li , Yu-xi Liu

We present an efficient method for estimating the eigenvalues of a Hamiltonian $H$ from the expectation values of the evolution operator for various times. For a given quantum state $\rho$, our method outputs a list of eigenvalue estimates…

Quantum Physics · Physics 2020-09-08 Rolando D. Somma

In this paper, we present a method for the Hamiltonian simulation in the context of eigenvalue estimation problems which improves earlier results dealing with Hamiltonian simulation through the truncated Taylor series. In particular, we…

Quantum Physics · Physics 2018-11-01 Ammar Daskin , Sabre Kais

We propose an iterative algorithm to simulate the dynamics generated by any $n$-qubit Hamiltonian. The simulation entails decomposing the unitary time evolution operator $U$ (unitary) into a product of different time-step unitaries. The…

Quantum Physics · Physics 2012-04-09 Ashok Ajoy , Rama Koteswara Rao , Anil Kumar , Pranaw Rungta

The exponential speedups promised by Hamiltonian simulation on a quantum computer depends crucially on structure in both the Hamiltonian $\hat{H}$, and the quantum circuit $\hat{U}$ that encodes its description. In the quest to better…

Quantum Physics · Physics 2017-07-19 Guang Hao Low , Isaac L. Chuang

We present an efficient algorithm for simulating the time evolution due to a sparse Hamiltonian. In terms of the maximum degree d and dimension N of the space on which the Hamiltonian H acts for time t, this algorithm uses (d^2(d+log*…

Quantum Physics · Physics 2011-01-26 Andrew M. Childs , Robin Kothari

The implementation of time-evolution operators $U(t)$, called Hamiltonian simulation, is one of the most promising usage of quantum computers. For time-independent Hamiltonians, qubitization has recently established efficient realization of…

Quantum Physics · Physics 2023-03-29 Kaoru Mizuta , Keisuke Fujii

Quantum phase estimation combined with Hamiltonian simulation is the most promising algorithmic framework to computing ground state energies on quantum computers. Its main computational overhead derives from the Hamiltonian simulation…

Various Hamiltonian simulation algorithms have been proposed to efficiently study the dynamics of quantum systems on a quantum computer. The existing algorithms generally approximate the time evolution operators, which may need a deep…

Quantum Physics · Physics 2024-03-14 Zi-Jian Zhang , Jinzhao Sun , Xiao Yuan , Man-Hong Yung

Simulating the time evolution of quantum field theories given some Hamiltonian $H$ requires developing algorithms for implementing the unitary operator e^{-iHt}. A variety of techniques exist that accomplish this task, with the most common…

Iterative phase estimation has long been used in quantum computing to estimate Hamiltonian eigenvalues. This is done by applying many repetitions of the same fundamental simulation circuit to an initial state, and using statistical…

Quantum Physics · Physics 2019-07-25 Ian D. Kivlichan , Christopher E. Granade , Nathan Wiebe

We consider the task of simulating time evolution under a Hamiltonian $H$ within its low-energy subspace. Assuming access to a block-encoding of $H'=(H-E)/\lambda$ for some $E \in \mathbb R$, the goal is to implement an…

Quantum Physics · Physics 2024-08-28 Alexander Zlokapa , Rolando D. Somma

We present an algorithm for sparse Hamiltonian simulation whose complexity is optimal (up to log factors) as a function of all parameters of interest. Previous algorithms had optimal or near-optimal scaling in some parameters at the cost of…

Quantum Physics · Physics 2016-01-06 Dominic W. Berry , Andrew M. Childs , Robin Kothari

Recently, there has been growing interest in simulating time-dependent Hamiltonians using quantum algorithms, driven by diverse applications, such as quantum adiabatic computing. While techniques for simulating time-independent Hamiltonian…

Quantum Physics · Physics 2024-11-06 Yu Cao , Shi Jin , Nana Liu