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We present a quantum-classical hybrid random power method that approximates a ground state of a Hamiltonian. The quantum part of our method computes a fixed number of elements of a Hamiltonian-matrix polynomial via quantum polynomial…

Quantum Physics · Physics 2025-04-17 Taehee Ko , Hyowon Park , Sangkook Choi

Effective quantum computation relies upon making good use of the exponential information capacity of a quantum machine. A large barrier to designing quantum algorithms for execution on real quantum machines is that, in general, it is…

Quantum Physics · Physics 2020-05-12 Adam Holmes , A. Y. Matsuura

We present a quantum algorithm for implementing $\phi^4$ lattice scalar field theory on qubit computers. The field is represented in the discretized field amplitude basis. The number of qubits and elementary gates required by the…

Quantum Physics · Physics 2023-03-08 Andy C. Y. Li , Alexandru Macridin , Stephen Mrenna , Panagiotis Spentzouris

Many-body ground state preparation is an important subroutine used in the simulation of physical systems. In this paper, we introduce a flexible and efficient framework for obtaining a state preparation circuit for a large class of…

Quantum Physics · Physics 2024-11-05 Hyun-Soo Kim , Isaac H. Kim , Daniel Ranard

Quantum computing offers potential solutions for finding ground states in condensed-matter physics and chemistry. However, achieving effective ground state preparation is also computationally hard for arbitrary Hamiltonians. It is necessary…

We extend Quantum Computing Quantum Monte Carlo (QCQMC) beyond ground-state energy estimation by systematically constructing the quantum circuits used for state preparation. Replacing the original Variational Quantum Eigensolver (VQE)…

We propose a quantum inverse iteration algorithm which can be used to estimate the ground state properties of a programmable quantum device. The method relies on the inverse power iteration technique, where the sequential application of the…

Quantum Physics · Physics 2020-01-22 Oleksandr Kyriienko

This letter is a proof of concept for quantum power flow (QPF) algorithms which underpin various unprecedentedly efficient power system analytics exploiting quantum computing. Our contributions are three-fold: 1) Establish a…

Quantum Physics · Physics 2021-04-13 Fei Feng , Yifan Zhou , Peng Zhang

In this work we investigate methods to improve the efficiency and scalability of quantum algorithms for quantum chemistry applications. We propose a transformation of the electronic structure Hamiltonian in the second quantization framework…

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

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

Solving for quantum ground states is important for understanding the properties of quantum many-body systems, and quantum computers are potentially well-suited for solving for quantum ground states. Recent work has presented a nearly…

Quantum Physics · Physics 2023-08-23 Matthew Thibodeau , Bryan K. Clark

A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding is that achieving quantum advantage in this area will…

Quantum Physics · Physics 2023-11-08 Guoming Wang , Daniel Stilck França , Ruizhe Zhang , Shuchen Zhu , Peter D. Johnson

We propose a method to manipulate, possibly faster than adiabatically, four-level systems with time-dependent couplings and constant energy shifts (detunings in quantum-optical realizations). We inversely engineer the Hamiltonian, in…

Quantum Physics · Physics 2018-01-24 Y. - C. Li , D. Martínez , S. Martínez-Garaot , X. Chen , J. G. Muga

Many quantum algorithms for ground-state preparation and energy estimation require the implementation of high-degree polynomials of a Hamiltonian to achieve better convergence rates. Their circuit implementation typically relies on quantum…

Quantum Physics · Physics 2025-12-25 Youngjun Park , Minhyeok Kang , Chae-Yeun Park , Joonsuk Huh

We propose new quantum algorithms for thermal and ground state preparation based on system-bath interactions. These algorithms require only forward evolution under a system-bath Hamiltonian in which the bath is a single reusable ancilla…

Quantum Physics · Physics 2025-12-19 Zhiyan Ding , Yongtao Zhan , John Preskill , Lin Lin

Preparing the ground state of a Hamiltonian is a problem of great significance in physics with deep implications in the field of combinatorial optimization. The adiabatic algorithm is known to return the ground state for sufficiently long…

Quantum Physics · Physics 2023-08-02 Benjamin F. Schiffer , Jordi Tura , J. Ignacio Cirac

We present efficient circuits that can be used for the phase space tomography of quantum states. The circuits evaluate individual values or selected averages of the Wigner, Kirkwood and Husimi distributions. These quantum gate arrays can be…

Quantum Physics · Physics 2009-11-10 Juan Pablo Paz , Augusto J. Roncaglia , Marcos Saraceno

Accurate state preparation is a critical bottleneck in many quantum algorithms, particularly those for ground state energy estimation. Even in fault-tolerant quantum computing, preparing a quantum state with sufficient overlap to the…

Quantum Physics · Physics 2025-10-07 Gwonhak Lee , Minhyeok Kang , Jungsoo Hong , Stepan Fomichev , Joonsuk Huh

We present an implementation of an efficient algorithm for the calculation of the spectrum of one-dimensional quantum systems with periodic boundary conditions. This algorithm is based on a matrix product representation for quantum states…

Statistical Mechanics · Physics 2016-12-05 Michael Weyrauch , Mykhailo V. Rakov