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With the advent and development of quantum computers, various quantum algorithms that can solve linear equations and eigenvalues faster than classical computers have been developed. The Harrow-Hassidim-Lloyd algorithm is an algorithm that…

Quantum Physics · Physics 2025-06-23 Hyunju Lee , Kyungtaek Jun

We study several problems related to properties of non-negative matrices that arise at the boundary between quantum and classical probabilistic computation. Our results are twofold. First, we identify a large class of quantum Hamiltonians…

Quantum Physics · Physics 2010-01-22 Sergey Bravyi , Barbara Terhal

Is there a general theorem that tells us when we can hope for exponential speedups from quantum algorithms, and when we cannot? In this paper, we make two advances toward such a theorem, in the black-box model where most quantum algorithms…

Quantum Physics · Physics 2014-02-07 Scott Aaronson , Andris Ambainis

We consider the problem of learning the Hamiltonian of a quantum system from estimates of Gibbs-state expectation values. Various methods for achieving this task were proposed recently, both from a practical and theoretical point of view.…

Quantum Physics · Physics 2024-10-31 Adam Artymowicz , Hamza Fawzi , Omar Fawzi , Samuel O. Scalet

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 introduce $k$-local quasi-quantum states: a superset of the regular quantum states, defined by relaxing the positivity constraint. We show that a $k$-local quasi-quantum state on $n$ qubits can be 1-1 mapped to a distribution of…

Quantum Physics · Physics 2025-01-27 Itai Arad , Miklos Santha

Hamiltonian Learning (HL) is essential for validating quantum systems in quantum computing. Not all Hamiltonians can be uniquely recovered from a steady state. HL success depends on the Hamiltonian model and steady state. Here, we analyze…

Quantum Physics · Physics 2023-09-19 Jing Zhou , D. L. Zhou

We give a test that can distinguish efficiently between product states of n quantum systems and states which are far from product. If applied to a state psi whose maximum overlap with a product state is 1-epsilon, the test passes with…

Quantum Physics · Physics 2013-10-03 Aram W. Harrow , Ashley Montanaro

Harrow, Hassidim, and Lloyd showed that for a suitably specified $N \times N$ matrix $A$ and $N$-dimensional vector $\vec{b}$, there is a quantum algorithm that outputs a quantum state proportional to the solution of the linear system of…

Quantum Physics · Physics 2017-12-27 Andrew M. Childs , Robin Kothari , Rolando D. Somma

The ground state energy and the free energy of Quantum Local Hamiltonians are fundamental quantities in quantum many-body physics, however, it is QMA-Hard to estimate them in general. In this paper, we develop new techniques to find…

Quantum Physics · Physics 2023-08-08 Thiago Bergamaschi

We quantitatively analyze superradiance (collective emission) in a three-dimensional array of qubits without imposing any restrictions on the size of the sample. We show that even when the spacing between the qubits become arbitrarily…

Quantum Physics · Physics 2015-11-20 D. D. Yavuz , B. Lemberger

A fundamental task in quantum information science is state certification: testing whether a lab-prepared $n$-qubit state is close to a given hypothesis state. In this work, we show that every pure hypothesis state can be certified using…

Quantum Physics · Physics 2025-07-16 Meghal Gupta , William He , Ryan O'Donnell

Quantum chemistry and optimization are two of the most prominent applications of quantum computers. Variational quantum algorithms have been proposed for solving problems in these domains. However, the design of the quantum circuit ansatz…

The local Hamiltonian (LH) problem, the quantum analog of the classical constraint satisfaction problem, is a cornerstone of quantum computation and complexity theory. It is known to be QMA-complete, indicating that it is challenging even…

Quantum Physics · Physics 2024-11-27 Yukun Zhang , Yusen Wu , Xiao Yuan

Recently, feedback-based quantum algorithms have been introduced to calculate the ground states of Hamiltonians, inspired by quantum Lyapunov control theory. This paper aims to generalize these algorithms to the problem of calculating an…

Quantum Physics · Physics 2026-01-21 Salahuddin Abdul Rahman , Özkan Karabacak , Rafal Wisniewski

We discuss classical algorithms for approximating the largest eigenvalue of quantum spin and fermionic Hamiltonians based on semidefinite programming relaxation methods. First, we consider traceless $2$-local Hamiltonians $H$ describing a…

Quantum Physics · Physics 2019-10-08 Sergey Bravyi , David Gosset , Robert Koenig , Kristan Temme

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

The presence of symmetries, be they discrete or continuous, in a physical system typically leads to a reduction in the problem to be solved. Here we report that neither translational invariance nor rotational invariance reduce the…

Quantum Physics · Physics 2008-07-24 Alastair Kay

We solve the generalised quantum Stein's lemma, proving that the Stein exponent associated with entanglement testing, namely, the quantum hypothesis testing task of distinguishing between $n$ copies of an entangled state $\rho_{AB}$ and a…

Quantum Physics · Physics 2025-07-28 Ludovico Lami

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
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