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Recently [Bhattacharya et al., STOC 2015] provide the first non-trivial algorithm for the densest subgraph problem in the streaming model with additions and deletions to its edges, i.e., for dynamic graph streams. They present a…

Data Structures and Algorithms · Computer Science 2015-07-30 Hossein Esfandiari , MohammadTaghi Hajiaghayi , David P. Woodruff

Most quantum algorithms that give an exponential speedup over classical algorithms exploit the Fourier transform in some way. In Shor's algorithm, sampling from the quantum Fourier spectrum is used to discover periodicity of the modular…

Quantum Physics · Physics 2015-05-14 Martin Roetteler

We construct a hybrid quantum-classical approach for the $K$-Nearest Neighbour algorithm, where the information is embedded in a phase-distributed multimode coherent state with the assistance of a single photon. The task of finding the…

Quantum Physics · Physics 2024-04-19 Vivek Mehta , Francesco Petruccione , Utpal Roy

We show a $2^{n+o(n)}$-time (and space) algorithm for the Shortest Vector Problem on lattices (SVP) that works by repeatedly running an embarrassingly simple "pair and average" sieving-like procedure on a list of lattice vectors. This…

Data Structures and Algorithms · Computer Science 2019-01-28 Divesh Aggarwal , Noah Stephens-Davidowitz

We describe a quantum algorithm for finding the smallest eigenvalue of a Hermitian matrix. This algorithm combines Quantum Phase Estimation and Quantum Amplitude Estimation to achieve a quadratic speedup with respect to the best classical…

Variational quantum algorithms hold great promise for unlocking the power of near-term quantum processors, yet high measurement costs, barren plateaus, and challenging optimization landscapes frequently hinder them. Here, we introduce…

Quantum Physics · Physics 2026-03-10 Mengzhen Ren , Yu-Cheng Chen , Yangsen Ye , Min-Hsiu Hsieh , Alice Hu , Chang-Yu Hsieh

In this paper, we propose a general framework for tensor singular value decomposition (tensor SVD), which focuses on the methodology and theory for extracting the hidden low-rank structure from high-dimensional tensor data. Comprehensive…

Statistics Theory · Mathematics 2020-01-09 Anru Zhang , Dong Xia

Evaluating the entanglement spectrum is essential for characterizing exotic quantum phases such as quantum criticality and topological order. However, for large quantum many-body systems, this task is hindered by the exponential measurement…

Quantum Physics · Physics 2026-05-12 Shohei Miyakoshi , Takanori Sugimoto , Tomonori Shirakawa , Seiji Yunoki , Hiroshi Ueda

The state hidden subgroup problem (StateHSP) is a recent generalization of the hidden subgroup problem. We present an algorithm that solves the non-abelian StateHSP over $N$ copies of the dihedral group of order $8$ (the symmetries of a…

Quantum Physics · Physics 2026-03-16 Gideon Lee , Jonathan A. Gross , Masaya Fukami , Zhang Jiang

Given a graph and an integer $k$, Densest $k$-Subgraph is the algorithmic task of finding the subgraph on $k$ vertices with the maximum number of edges. This is a fundamental problem that has been subject to intense study for decades, with…

Computational Complexity · Computer Science 2023-03-31 Chris Jones , Aaron Potechin , Goutham Rajendran , Jeff Xu

We present the variational separability verifier (VSV), which is a novel variational quantum algorithm (VQA) that determines the closest separable state (CSS) of an arbitrary quantum state with respect to the Hilbert-Schmidt distance (HSD).…

Quantum Physics · Physics 2022-12-20 Mirko Consiglio , Tony John George Apollaro , Marcin Wieśniak

Characterization of quantum processes is a preliminary step necessary in the development of quantum technology. The conventional method uses standard quantum process tomography, which requires $d^2$ input states and $d^4$ quantum…

Quantum Physics · Physics 2020-02-26 Zhibo Hou , Jun-Feng Tang , Christopher Ferrie , Guo-Yong Xiang , Chuan-Feng Li , Guang-Can Guo

Understanding quantum phase transitions in physical systems is fundamental to characterize their behavior at low temperatures. Achieving this requires both accessing good approximations to the ground state and identifying order parameters…

Quantum Physics · Physics 2025-06-06 Chenfeng Cao , Filippo Maria Gambetta , Ashley Montanaro , Raul A. Santos

One of the most promising and versatile approaches to creating new quantum algorithms is based on the quantum hidden subgroup (QHS) paradigm, originally suggested by Alexei Kitaev. This class of quantum algorithms encompasses the…

Quantum Physics · Physics 2007-05-23 Samuel J. Lomonaco , Louis H. Kauffman

Unit group computations are a cryptographic primitive for which one has a fast quantum algorithm, but the required number of qubits is $\tilde O(m^5)$. In this work we propose a modification of the algorithm for which the number of qubits…

Cryptography and Security · Computer Science 2023-03-08 Razvan Barbulescu , Adrien Poulalion

This paper details a new algorithm to solve the shortest path problem in valued graphs. Its complexity is $O(D \log v)$ where $D$ is the graph diameter and $v$ its number of vertices. This complexity has to be compared to the one of the…

Data Structures and Algorithms · Computer Science 2007-05-23 Michel Koskas

We describe an efficient quantum algorithm for computing discrete logarithms in semigroups using Shor's algorithms for period finding and discrete log as subroutines. Thus proposed cryptosystems based on the presumed hardness of discrete…

Quantum Physics · Physics 2015-01-23 Andrew M. Childs , Gábor Ivanyos

We present a quantum algorithm which identifies with certainty a hidden subgroup of an arbitrary finite group G in only a polynomial (in log |G|) number of calls to the oracle. This is exponentially better than the best classical algorithm.…

Quantum Physics · Physics 2016-12-30 Mark Ettinger , Peter Hoyer , Emanuel Knill

The VQE algorithm has turned out to be quite expensive to run given the way we currently access quantum processors (i.e. over the cloud). In order to alleviate this issue, we introduce Quantum Sampling Regression (QSR), an alternative…

Quantum Physics · Physics 2020-12-07 Pedro Rivero , Ian C. Cloët , Zack Sullivan

We present two stochastic descent algorithms that apply to unconstrained optimization and are particularly efficient when the objective function is slow to evaluate and gradients are not easily obtained, as in some PDE-constrained…

Optimization and Control · Mathematics 2019-04-30 David Kozak , Stephen Becker , Alireza Doostan , Luis Tenorio
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