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Performing large-scale, accurate quantum simulations of many-fermion systems is a central challenge in quantum science, with applications in chemistry, materials, and high-energy physics. Despite significant progress, realizing generic…

Quantum Physics · Physics 2025-09-12 Nishad Maskara , Marcin Kalinowski , Daniel Gonzalez-Cuadra , Mikhail D. Lukin

In this paper, an algorithm for Quantum Inverse Fast Fourier Transform (QIFFT) is developed to work for quantum data. Analogous to a classical discrete signal, a quantum signal can be represented in Dirac notation, application of QIFFT is a…

Quantum Physics · Physics 2024-09-13 Mayank Roy , Devi Maheswaran

We present a quantum algorithm for the dynamical simulation of time-dependent Hamiltonians. Our method involves expanding the interaction-picture Hamiltonian as a sum of generalized permutations, which leads to an integral-free Dyson series…

Quantum Physics · Physics 2021-09-15 Yi-Hsiang Chen , Amir Kalev , Itay Hen

Quantum sensing exploits fundamental features of quantum system to achieve highly efficient measurement of physical quantities. Here, we propose a strategy to realize a single-qubit pseudo-Hermitian sensor from a dilated two-qubit Hermitian…

Quantum Physics · Physics 2020-01-22 Yaoming Chu , Yu Liu , Haibin Liu , Jianming Cai

Recent technological developments have focused the interest of the quantum computing community on investigating how near-term devices could outperform classical computers for practical applications. A central question that remains open is…

Quantum Physics · Physics 2021-11-24 Daniel Stilck Franca , Raul Garcia-Patron

We study the efficiency of algorithms simulating a system evolving with Hamiltonian $H=\sum_{j=1}^m H_j$. We consider high order splitting methods that play a key role in quantum Hamiltonian simulation. We obtain upper bounds on the number…

Quantum Physics · Physics 2010-10-12 Anargyros Papageorgiou , Chi Zhang

Gaussian processes (GPs) are important models in supervised machine learning. Training in Gaussian processes refers to selecting the covariance functions and the associated parameters in order to improve the outcome of predictions, the core…

To overcome the fast oscillatory behavior of correlation functions for extracting scattering phase shift in real-time quantum simulations encountered in Ref.\cite{Guo:2026qkx}, we propose and test two solutions in the present work. One is…

Quantum Physics · Physics 2026-04-02 Peng Guo , Paul LeVan , Frank X. Lee , Yong Zhao

The phase estimation algorithm is a powerful quantum algorithm with applications in cryptography, number theory, and simulation of quantum systems. We use this algorithm to simulate the time evolution of a system of two spin-1/2 particles…

Quantum Physics · Physics 2021-05-12 Scott Johnstun , Jean-François Van Huele

We consider a particular discretization of the harmonic oscillator which admits an orthogonal basis of eigenfunctions called Kravchuk functions possessing appealing properties from the numerical point of view. We analytically prove the…

Analysis of PDEs · Mathematics 2022-12-07 Quentin Chauleur , Erwan Faou

In this work, we develop a highly efficient representation of functions and differential operators based on Fourier analysis. Using this representation, we create a variational hybrid quantum algorithm to solve static, Schr\"odinger-type,…

Simulating quantum states on a classical computer is hard, typically requiring prohibitive resources in terms of memory and computational power. Efficient simulation, however, can be achieved for certain classes of quantum states, in…

Quantum Physics · Physics 2022-12-19 Igor Brandão , Daniel Tandeitnik , Thiago Guerreiro

The quantum Fourier transform (QFT) is a fundamental primitive in quantum computation and quantum information. In this work, we generalize the QFT for finite groups to a QFT for finite-dimensional semisimple algebras, and give efficient…

Quantum Physics · Physics 2026-05-08 Ben Foxman , Barak Nehoran , Yongshan Ding

In the accompanying paper of arXiv:2505.00697, we have presented a generalized scheme of adaptive quantum gradient estimation (QGE) algorithm, and further proposed two practical variants which not only achieve doubly quantum enhancement in…

Quantum Physics · Physics 2025-05-05 Yuki Koizumi , Kaito Wada , Wataru Mizukami , Nobuyuki Yoshioka

Variational hybrid quantum-classical optimization represents one of the most promising avenue to show the advantage of nowadays noisy intermediate-scale quantum computers in solving hard problems, such as finding the minimum-energy state of…

Quantum Physics · Physics 2020-11-18 Laura Gentini , Alessandro Cuccoli , Stefano Pirandola , Paola Verrucchi , Leonardo Banchi

Discrete Gaussian Sampling on lattices is a fundamental problem in lattice-based cryptography. It appears both in basic cryptographic primitives such as digital signatures and as an important cryptanalysis building block for solving hard…

Quantum Physics · Physics 2026-05-20 Clémence Chevignard , Yixin Shen , André Schrottenloher

A quantum computer directly manipulates information stored in the state of quantum mechanical systems. The available operations have many attractive features but also underly severe restrictions, which complicate the design of quantum…

Quantum Physics · Physics 2015-06-26 Sos S. Agaian , Andreas Klappenecker

Simulating the real-time dynamics of lattice gauge theories, underlying the Standard Model of particle physics, is a notoriously difficult problem where quantum simulators can provide a practical advantage over classical approaches. In this…

Quantum Physics · Physics 2023-10-18 Torsten V. Zache , Daniel González-Cuadra , Peter Zoller

Quantum computers will allow calculations beyond existing classical computers. However, current technology is still too noisy and imperfect to construct a universal digital quantum computer with quantum error correction. Inspired by the…

Quantum Physics · Physics 2020-10-27 Ana Martin , Lucas Lamata , Enrique Solano , Mikel Sanz

We present a quantum algorithm for efficiently sampling transformed Gaussian random fields on $d$-dimensional domains, based on an enhanced version of the classical moving average method. Pointwise transformations enforcing boundedness are…

Quantum Physics · Physics 2025-08-20 Matthias Deiml , Daniel Peterseim