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We consider different Linear Combination of Unitaries (LCU) decompositions for molecular electronic structure Hamiltonians. Using these LCU decompositions for Hamiltonian simulation on a quantum computer, the main figure of merit is the…

Quantum Physics · Physics 2023-06-13 Ignacio Loaiza , Alireza Marefat Khah , Nathan Wiebe , Artur F. Izmaylov

We describe a simple, efficient method for simulating Hamiltonian dynamics on a quantum computer by approximating the truncated Taylor series of the evolution operator. Our method can simulate the time evolution of a wide variety of…

Quantum Physics · Physics 2015-03-06 Dominic W. Berry , Andrew M. Childs , Richard Cleve , Robin Kothari , Rolando D. Somma

We describe an improved version of the quantum simulation method based on the implementation of a truncated Taylor series of the evolution operator. The idea is to add an extra step to the previously known algorithm which implements an…

Quantum Physics · Physics 2017-06-05 Leonardo Novo , Dominic W. Berry

Trotter and linear-combination-of-unitary (LCU) are two popular Hamiltonian simulation methods. We propose Hamiltonian simulation algorithms using LCU to compensate Trotter error, which enjoy both of their advantages. By adding few gates…

Quantum Physics · Physics 2025-03-31 Pei Zeng , Jinzhao Sun , Liang Jiang , Qi Zhao

We investigate ancilla-free linear combination of unitaries (LCU) as a framework for approximating complex quantum circuits. This is particularly effective for quantum optimization algorithms, where candidate solutions can be evaluated…

Quantum Physics · Physics 2026-05-20 Almudena Carrera Vazquez , Daniel J. Egger , Stefan Woerner

Linear combination of unitaries (LCU for short) is one of the most important techniques in designing quantum algorithms. In this paper, we propose a new quantum algorithm in three different forms to achieve LCU. Different from previous…

Quantum Physics · Physics 2018-08-17 Changpeng Shao

The simulation of large nonlinear dynamical systems, including systems generated by discretization of hyperbolic partial differential equations, can be computationally demanding. Such systems are important in both fluid and kinetic…

Plasma Physics · Physics 2021-06-14 Alexander Engel , Graeme Smith , Scott E. Parker

We introduce novel algorithms for the quantum simulation of molecular systems which are asymptotically more efficient than those based on the Trotter-Suzuki decomposition. We present the first application of a recently developed technique…

We develop three new methods to implement any Linear Combination of Unitaries (LCU), a powerful quantum algorithmic tool with diverse applications. While the standard LCU procedure requires several ancilla qubits and sophisticated…

Quantum Physics · Physics 2024-10-16 Shantanav Chakraborty

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

One limitation of the variational quantum eigensolver algorithm is the large number of measurement steps required to estimate different terms in the Hamiltonian of interest. Unitary partitioning reduces this overhead by transforming the…

Quantum Physics · Physics 2021-09-01 Alexis Ralli , Peter Love , Andrew Tranter , Peter Coveney

Quantum simulations of lattice gauge theories offer the potential to directly study the non-perturbative dynamics of quantum chromodynamics, but naive analyses suggest that they require large computational resources. Large $N_c$ expansions…

High Energy Physics - Lattice · Physics 2026-02-19 Anthony N. Ciavarella , I. M. Burbano , Christian W. Bauer

Recent work has deployed linear combinations of unitaries techniques to reduce the cost of fault-tolerant quantum simulations of correlated electron models. Here, we show that one can sometimes improve upon those results with optimized…

The unitary coupled cluster (UCC) approximation is one of the more promising wave-function ans\"atze for electronic structure calculations on quantum computers via the variational quantum eigensolver algorithm. However, for large systems…

Quantum Physics · Physics 2021-09-30 Jia Chen , Hai-Ping Cheng , James K. Freericks

Hamiltonian Truncation (a.k.a. Truncated Spectrum Approach) is an efficient numerical technique to solve strongly coupled QFTs in d=2 spacetime dimensions. Further theoretical developments are needed to increase its accuracy and the range…

High Energy Physics - Theory · Physics 2017-12-19 Joan Elias-Miro , Slava Rychkov , Lorenzo G. Vitale

The linear combination of unitaries (LCU) method has proven to scale better than existing product formulas in simulating long time Hamiltonian dynamics. However, given the number of multi-control gate operations in the standard…

Conformal truncation is a powerful numerical method for solving generic strongly-coupled quantum field theories based on purely field-theoretic technics without introducing lattice regularization. We discuss possible speedups for performing…

High Energy Physics - Theory · Physics 2020-12-04 Junyu Liu , Yuan Xin

The encoding of lattice gauge theories onto quantum computers requires a discretization of the gauge field's Hilbert space on each link, which presents errors with respect to the Kogut--Susskind limit. In the electric basis, Hilbert space…

Simulating the dynamics of complex quantum systems is a central application of quantum devices. Here, we propose leveraging the power of measurements to simulate short-time quantum dynamics of physically prepared quantum states in classical…

Quantum Physics · Physics 2025-07-02 Paul K. Faehrmann , Jens Eisert , Maria Kieferova , Richard Kueng

To simulate bosons on a qubit- or qudit-based quantum computer, one has to regularize the theory by truncating infinite-dimensional local Hilbert spaces to finite dimensions. In the search for practical quantum applications, it is important…

Quantum Physics · Physics 2024-04-03 Masanori Hanada , Junyu Liu , Enrico Rinaldi , Masaki Tezuka
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