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We provide a quantum method for simulating Hamiltonian evolution with complexity polynomial in the logarithm of the inverse error. This is an exponential improvement over existing methods for Hamiltonian simulation. In addition, its scaling…

Quantum Physics · Physics 2013-10-24 Dominic W. Berry , Richard Cleve , Rolando D. Somma

Known as no fast-forwarding theorem in quantum computing, the simulation time for the Hamiltonian evolution needs to be $O(\|H\| t)$ in the worst case, which essentially states that one can not go across the multiple scales as the…

Quantum Physics · Physics 2025-01-30 Yonah Borns-Weil , Di Fang

Quantum optimal control theory is becoming increasingly crucial as quantum devices become more precise, but the need to quickly optimize these systems classically remains a significant bottleneck in their operation. Here we present a new…

Quantum Physics · Physics 2022-05-11 Mogens Dalgaard , Felix Motzoi

Suitable discretizations through tensor product formulas of popular multidimensional operators (diffusion or diffusion--advection, for instance) lead to matrices with $d$-dimensional Kronecker sum structure. For evolutionary Partial…

Numerical Analysis · Mathematics 2024-06-18 Fabio Cassini

The accuracy of quantum dynamics simulation is usually measured by the error of the unitary evolution operator in the operator norm, which in turn depends on certain norm of the Hamiltonian. For unbounded operators, after suitable…

Quantum Physics · Physics 2021-05-26 Dong An , Di Fang , Lin Lin

We introduce an algorithm to improve the error scaling of product formulas by randomly sampling the generator of their exact error unitary. Our approach takes an arbitrary product formula of time $t$, $S_k(t)$ with error $O(t^{k+1})$ and…

Quantum Physics · Physics 2025-08-26 Lana Mineh , Adrian Chapman , Raul A. Santos

Simulation of quantum systems is expected to be one of the most important applications of quantum computing, with much of the theoretical work so far having focused on fermionic and spin-$\frac{1}{2}$ systems. Here, we instead consider…

Quantum computers are believed to have the ability to process huge data sizes which can be seen in machine learning applications. In these applications, the data in general is classical. Therefore, to process them on a quantum computer,…

Quantum Physics · Physics 2023-03-02 Ammar Daskin , Rishabh Gupta , Sabre Kais

Quantum simulation, the simulation of quantum processes on quantum computers, suggests a path forward for the efficient simulation of problems in condensed-matter physics, quantum chemistry, and materials science. While the majority of…

Quantum Physics · Physics 2022-10-03 Paul K. Faehrmann , Mark Steudtner , Richard Kueng , Maria Kieferova , Jens Eisert

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

We present a quantum algorithm for the simulation of molecular systems that is asymptotically more efficient than all previous algorithms in the literature in terms of the main problem parameters. As in previous work [Babbush et al., New…

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

Quantum simulation has shown great potential in many fields due to its powerful computational capabilities. However, the limited fidelity can lead to a severe limitation on the number of gate operations, which requires us to find optimized…

Quantum Physics · Physics 2021-09-20 Yi-Tong Zou , Yu-Jiao Bo , Ji-Chong Yang

Quantum simulation has wide applications in quantum chemistry and physics. Recently, scientists have begun exploring the use of randomized methods for accelerating quantum simulation. Among them, a simple and powerful technique, called…

Quantum Physics · Physics 2026-03-26 Chi-Fang Chen , Hsin-Yuan Huang , Richard Kueng , Joel A. Tropp

Hamiltonian simulation is arguably the most fundamental application of quantum computers. The Magnus operator is a popular method for time-dependent Hamiltonian simulation in computational mathematics, yet its usage requires the…

We study the top Lyapunov exponents of random products of positive $2 \times 2$ matrices and obtain an efficient algorithm for its computation. As in the earlier work of Pollicott, the algorithm is based on the Fredholm theory of…

Dynamical Systems · Mathematics 2020-01-08 Natalia Jurga , Ian Morris

This research introduces an improved framework for constructing matrix product operators (MPOs) and tree tensor network operators (TTNOs), crucial tools in quantum simulations. A given (Hamiltonian) operator typically has a known symbolic…

Quantum Physics · Physics 2025-07-04 Hazar Çakır , Richard M. Milbradt , Christian B. Mendl

We introduce a systematic construction of higher-order matrix product operator (MPO) approximations of the time evolution operator for generic (short and long range) one-dimensional Hamiltonians. We demonstrate the utility of our…

Strongly Correlated Electrons · Physics 2023-03-01 Maarten Van Damme , Jutho Haegeman , Ian McCulloch , Laurens Vanderstraeten

The simulation of time evolution of large quantum systems is a classically challenging and in general intractable task, making it a promising application for quantum computation. A Trotter-Suzuki approximation yields an implementation…

To efficiently implement many-qubit gates for use in quantum simulations on quantum computers we develop and present methods reexpressing exp[-i (H_1 + H_2 + ...) \Delta t] as a product of factors exp[-i H_1 \Delta t], exp[-i H_2 \Delta t],…

Quantum Physics · Physics 2009-10-31 A. T. Sornborger , E. D. Stewart
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