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We describe an algorithm for determining the algebraic subgroup of GL(n,C) that is defined as the closure of the group generated by a finite number of elements of GL(n,C). The algorithm avoids the use of Groebner bases and can be used on…

Group Theory · Mathematics 2026-01-12 Willem A. de Graaf

The Gauss decompositions of the quantum groups, related to classical Lie groups and supergroups are considered by the elementary algebraic and $R$-matrix methods. The commutation relations between new basis generators (which are introduced…

q-alg · Mathematics 2008-02-03 E. V. Damaskinsky , P. P. Kulish , M. A. Sokolov

The Gaussian kernel plays a central role in machine learning, uncertainty quantification and scattered data approximation, but has received relatively little attention from a numerical analysis standpoint. The basic problem of finding an…

Numerical Analysis · Mathematics 2021-04-02 Toni Karvonen , Chris J. Oates , Mark Girolami

The theory of holographic algorithms, which are polynomial time algorithms for certain combinatorial counting problems, yields insight into the hierarchy of complexity classes. In particular, the theory produces algebraic tests for a…

Computational Complexity · Computer Science 2009-04-07 J. M. Landsberg , Jason Morton , Serguei Norine

We give deterministic polynomial-time algorithms that, given an order, compute the primitive idempotents and determine a set of generators for the group of roots of unity in the order. Also, we show that the discrete logarithm problem in…

Commutative Algebra · Mathematics 2016-03-14 H. W. Lenstra , A. Silverberg

Gaussian unitaries, generated by quadratic Hamiltonians, are fundamental in quantum optics and continuous-variable computing. Their structures correspond to symplectic (bosons) and orthogonal (fermions) groups, but physical realizations…

Quantum Physics · Physics 2026-02-10 Jingqi Sun , Joshua Combes , Lucas Hackl

Clustering mixtures of Gaussian distributions is a fundamental and challenging problem that is ubiquitous in various high-dimensional data processing tasks. While state-of-the-art work on learning Gaussian mixture models has focused…

Machine Learning · Computer Science 2018-03-05 Dan Kushnir , Shirin Jalali , Iraj Saniee

In the present paper, we study the finite type invariants of Gauss words. In the Polyak algebra techniques, we reduce the determination of the group structure to transformation of a matrix into its Smith normal form and we give the…

Combinatorics · Mathematics 2014-01-30 Tomonori Fukunaga , Takayuki Yamaguchi , Takaaki Yamanoi

The construction of the general solution sequence of row-finite linear systems is accomplished by implementing -ad infinitum- the Gauss-Jordan algorithm under a rightmost pivot elimination strategy. The algorithm generates a basis (finite…

Functional Analysis · Mathematics 2014-03-12 Alexandros G. Paraskevopoulos

Quantum algorithms for factoring and discrete logarithm have previously been generalized to finding hidden subgroups of finite Abelian groups. This paper explores the possibility of extending this general viewpoint to finding hidden…

Quantum Physics · Physics 2015-06-02 Mark Ettinger , Peter Hoyer

Decompositions of the unitary group U(n) are useful tools in quantum information theory as they allow one to decompose unitary evolutions into local evolutions and evolutions causing entanglement. Several recursive decompositions have been…

Quantum Physics · Physics 2009-11-13 Mehmet Dagli , Domenico D'Alessandro , Jonathan D. H. Smith

We consider a Gaussian process formulation of the multiple kernel learning problem. The goal is to select the convex combination of kernel matrices that best explains the data and by doing so improve the generalisation on unseen data.…

Machine Learning · Statistics 2011-10-25 Cedric Archambeau , Francis Bach

Quantum algorithms are sequences of abstract operations, performed on non-existent computers. They are in obvious need of categorical semantics. We present some steps in this direction, following earlier contributions of Abramsky, Coecke…

Quantum Physics · Physics 2016-11-09 Dusko Pavlovic

We present the view of quantum algorithms as a search-theoretic problem. We show that the Fourier transform, used to solve the Abelian hidden subgroup problem, is an example of an efficient elimination observable which eliminates a constant…

Quantum Physics · Physics 2007-05-23 J. Mark Ettinger , Peter Hoyer

An algorithm is proposed to convert arbitrary unitary matrix to a sequence of $X$ gates and fully controlled $R_y, R_z$ and $R_1$ gates. This algorithm is used to generate Q# implementation for arbitrary unitary matrix. Some optimizations…

Quantum Physics · Physics 2025-01-15 Dmytro Fedoriaka

A modified Gauss's algorithm for solving a system of linear equations in an integral ring is proposed, as well as an appropriate algorithm for calculating the elements of the adjoint matrix.

Symbolic Computation · Computer Science 2017-11-28 Gennadi Malaschonok

Gaussian mixture model is very useful in many practical problems. Nevertheless, it cannot be directly generalized to non Euclidean spaces. To overcome this problem we present a spherical Gaussian-based clustering approach for partitioning…

Machine Learning · Computer Science 2017-05-08 Marek Śmieja , Jacek Tabor

In this paper we consider a generalization of quantum hash functions for arbitrary groups. We show that quantum hash function exists for arbitrary abelian group. We construct a set of "good" automorphisms --- a key component of quantum hash…

Quantum Physics · Physics 2016-05-31 Mansur Ziatdinov

Extraspecial groups form a remarkable subclass of p-groups. They are also present in quantum information theory, in particular in quantum error correction. We give here a polynomial time quantum algorithm for finding hidden subgroups in…

Quantum Physics · Physics 2007-05-23 Gábor Ivanyos , Luc Sanselme , Miklos Santha

Gaussian processes are a powerful framework for uncertainty-aware function approximation and sequential decision-making. Unfortunately, their classical formulation does not scale gracefully to large amounts of data and modern hardware for…

Machine Learning · Computer Science 2025-07-10 Jihao Andreas Lin
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