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Perfect sorting by reversals, a problem originating in computational genomics, is the process of sorting a signed permutation to either the identity or to the reversed identity permutation, by a sequence of reversals that do not break any…

Discrete Mathematics · Computer Science 2012-01-05 Mathilde Bouvel , Cedric Chauve , Marni Mishna , Dominique Rossin

We give a quantum algorithm for evaluating formulas over an extended gate set, including all two- and three-bit binary gates (e.g., NAND, 3-majority). The algorithm is optimal on read-once formulas for which each gate's inputs are balanced…

Quantum Physics · Physics 2012-07-10 Ben W. Reichardt , Robert Spalek

Many combinatorial optimisation problems hide algebraic structures that, once exposed, shrink the search space and improve the chance of finding the global optimal solution. We present a general framework that (i) identifies algebraic…

Artificial Intelligence · Computer Science 2026-04-08 Min Sun , Federica Storti , Valentina Martino , Miguel Gonzalez-Andrades , Tony Kam-Thong

Let K be an algebraic number field of degree d and discriminant D over Q. Let A be an associative algebra over K given by structure constants such that A is isomorphic to the algebra M_n(K) of n by n matrices over K for some positive…

Rings and Algebras · Mathematics 2011-12-22 Gábor Ivanyos , Lajos Rónyai , Josef Schicho

An adiabatic quantum algorithm is essentially given by three elements: An initial Hamiltonian with known ground state, a problem Hamiltonian whose ground state corresponds to the solution of the given problem and an evolution schedule such…

Quantum Physics · Physics 2019-09-17 Davide Pastorello , Enrico Blanzieri

Achieving quantum advantage in efficiently estimating collective properties of quantum many-body systems remains a fundamental goal in quantum computing. While the quantum gradient estimation (QGE) algorithm has been shown to achieve doubly…

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

We consider distributed iterative algorithms for the averaging problem over time-varying topologies. Our focus is on the convergence time of such algorithms when complete (unquantized) information is available, and on the degradation of…

Optimization and Control · Mathematics 2009-01-14 Angelia Nedić , Alex Olshevsky , Asuman Ozdaglar , John Tsitsiklis

The discrete logarithm problem in a finite group is the basis for many protocols in cryptography. The best general algorithms which solve this problem have time complexity of $\mathcal{O}(\sqrt{N}\log N)$, and a space complexity of…

Computational Complexity · Computer Science 2022-03-16 Simran Tinani , Joachim Rosenthal

We study the forrelation problem: given a pair of $n$-bit Boolean functions $f$ and $g$, estimate the correlation between $f$ and the Fourier transform of $g$. This problem is known to provide the largest possible quantum speedup in terms…

Quantum Physics · Physics 2021-11-02 Sergey Bravyi , David Gosset , Daniel Grier , Luke Schaeffer

Let $\C$ be a sequence of multisets of subspaces of a vector space $\F_q^k$. We describe a practical algorithm which computes a canonical form and the stabilizer of $\C$ under the group action of the general semilinear group. It allows us…

Information Theory · Computer Science 2013-05-07 Thomas Feulner

We apply numerical optimization and linear algebra algorithms for classical computers to the problem of automatically synthesizing algorithms for quantum computers. Using our framework, we apply several common techniques from these…

Numerical Analysis · Mathematics 2025-09-16 Yuxin Huang , Benjamin E. Grossman-Ponemon , David A. B. Hyde

Current decision support systems address domains that are heterogeneous in nature and becoming progressively larger. Such systems often require the input of expert judgement about a variety of different fields and an intensive computational…

Other Statistics · Statistics 2017-07-10 Manuele Leonelli , Eva Riccomagno , Jim Q. Smith

Genetic algorithms, which mimic evolutionary processes to solve optimization problems, can be enhanced by using powerful semi-local search algorithms as mutation operators. Here, we introduce reverse quantum annealing, a class of quantum…

We present two quantum algorithms based on evolution randomization, a simple variant of adiabatic quantum computing, to prepare a quantum state $\vert x \rangle$ that is proportional to the solution of the system of linear equations $A…

Quantum Physics · Physics 2019-02-20 Yigit Subasi , Rolando D. Somma , Davide Orsucci

We consider a generic framework of optimization algorithms based on gradient descent. We develop a quantum algorithm that computes the gradient of a multi-variate real-valued function $f:\mathbb{R}^d\rightarrow \mathbb{R}$ by evaluating it…

Quantum Physics · Physics 2019-02-19 András Gilyén , Srinivasan Arunachalam , Nathan Wiebe

We consider a natural generalization of an abelian Hidden Subgroup Problem where the subgroups and their cosets correspond to graphs of linear functions over a finite field F with d elements. The hidden functions of the generalized problem…

Quantum Physics · Physics 2008-09-02 Thomas Decker , Jan Draisma , Pawel Wocjan

Many interesting computational problems can be reformulated in terms of decision trees. A natural classical algorithm is to then run a random walk on the tree, starting at the root, to see if the tree contains a node n levels from the root.…

Quantum Physics · Physics 2009-10-30 Edward Farhi , Sam Gutmann

Exploiting the similarity between adiabatic quantum algorithms and quantum phase transitions, we argue that second-order transitions -- typically associated with broken or restored symmetries -- should be advantageous in comparison to…

Quantum Physics · Physics 2010-01-07 Gernot Schaller , Ralf Schützhold

Quasi-2D Coulomb systems are of fundamental importance and have attracted much attention in many areas nowadays. Their reduced symmetry gives rise to interesting collective behaviors, but also brings great challenges for particle-based…

Numerical Analysis · Mathematics 2025-02-05 Zecheng Gan , Xuanzhao Gao , Jiuyang Liang , Zhenli Xu

Iterative refinement has emerged as an effective paradigm for enhancing the capabilities of large language models (LLMs) on complex tasks. However, existing approaches typically implement iterative refinement at the application or prompting…

Computation and Language · Computer Science 2024-10-15 Yuxi Xie , Anirudh Goyal , Xiaobao Wu , Xunjian Yin , Xiao Xu , Min-Yen Kan , Liangming Pan , William Yang Wang