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This paper proposes a variant of the normalized cut algorithm for spectral clustering. Although the normalized cut algorithm applies the K-means algorithm to the eigenvectors of a normalized graph Laplacian for finding clusters, our…

Computer Vision and Pattern Recognition · Computer Science 2015-03-06 Tomohiko Mizutani

The solution of many physical evolution equations can be expressed as an exponential of two or more operators acting on initial data. Accurate solutions can be systematically derived by decomposing the exponential in a product form. For…

Computational Physics · Physics 2007-05-23 Siu A. Chin

Recent work by Dhulipala et al. \cite{DLRSSY22} initiated the study of the $k$-core decomposition problem under differential privacy via a connection between low round/depth distributed/parallel graph algorithms and private algorithms with…

Data Structures and Algorithms · Computer Science 2024-03-01 Laxman Dhulipala , George Z. Li , Quanquan C. Liu

For the integer $ D=pq$ of the product of two distinct odd primes, we construct an elliptic curve $E_{2rD}:y^2=x^3-2rDx$ over $\mathbb Q$, where $r$ is a parameter dependent on the classes of $p$ and $q$ modulo 8, and show, under the parity…

Number Theory · Mathematics 2015-03-13 Xiumei Li , Jinxiang Zeng

Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of ``components.'' Typically, these components are linear combinations of the rows and columns of the matrix, and are thus…

Data Structures and Algorithms · Computer Science 2007-08-29 Petros Drineas , Michael W. Mahoney , S. Muthukrishnan

Quantum algorithms are at the heart of the ongoing efforts to use quantum mechanics to solve computational problems unsolvable on ordinary classical computers. Their common feature is the use of genuine quantum properties such as…

Quantum Physics · Physics 2023-09-20 Giuseppe Mussardo , Andrea Trombettoni

The polynomial method from circuit complexity has been applied to several fundamental problems and obtains the state-of-the-art running times. As observed in [Alman and Williams, STOC 2017], almost all applications of the polynomial method…

Computational Complexity · Computer Science 2018-11-20 Lijie Chen , Ruosong Wang

This paper describes efficient algorithms for computing rank-revealing factorizations of matrices that are too large to fit in RAM, and must instead be stored on slow external memory devices such as solid-state or spinning disk hard drives…

Mathematical Software · Computer Science 2020-03-05 Nathan Heavner , Per-Gunnar Martinsson , Gregorio Quintana-Ortí

We present computational algorithms to work with points on the modular curve associated to the normaliser of a non-split Cartan group of prime level $p$. Rather than working with explicit equations, we represent these points using the…

Number Theory · Mathematics 2026-05-29 Marusia Rebolledo , Christian Wuthrich

For an elliptic curve E/Q without complex multiplication we study the distribution of Atkin and Elkies primes l, on average, over all good reductions of E modulo primes p. We show that, under the Generalised Riemann Hypothesis, for almost…

Number Theory · Mathematics 2019-02-20 Igor E. Shparlinski , Andrew V. Sutherland

We consider a version of Shor's quantum factoring algorithm such that the quantum Fourier transform is replaced by an extremely simple one where decomposition coefficients take only the values of $1,i,-1,-i$. In numerous calculations which…

Quantum Physics · Physics 2007-05-23 Felix M Lev

High-performance techniques to simulate quantum programs on classical hardware rely on exponentially large vectors to represent quantum states. When simulating quantum algorithms, the quantum states that occur are often sparse due to…

Quantum Physics · Physics 2021-05-05 Samuel Jaques , Thomas Häner

Shor's algorithm is one of the most significant quantum algorithms. Shor's algorithm can factor large integers with a certain success probability in polynomial time. However, Shor's algorithm requires an unbearable amount of qubits in the…

Quantum Physics · Physics 2024-12-16 Ligang Xiao , Daowen Qiu , Le Luo , Paulo Mateus

Given a prime q and a negative discriminant D, the CM method constructs an elliptic curve E/\Fq by obtaining a root of the Hilbert class polynomial H_D(X) modulo q. We consider an approach based on a decomposition of the ring class field…

Number Theory · Mathematics 2019-02-20 Andrew V. Sutherland

In this work we propose a high-quality decomposition approach for qubit routing by swap insertion. This optimization problem arises in the context of compiling quantum algorithms onto specific quantum hardware. Our approach decomposes the…

Quantum Physics · Physics 2023-05-15 Friedrich Wagner , Andreas Bärmann , Frauke Liers , Markus Weissenbäck

Recht, Fazel, and Parrilo provided an analogy between rank minimization and $\ell_0$-norm minimization. Subject to the rank-restricted isometry property, nuclear norm minimization is a guaranteed algorithm for rank minimization. The…

Numerical Analysis · Mathematics 2009-05-01 Kiryung Lee , Yoram Bresler

Let g >= 1 and let Q be a monic, squarefree polynomial of degree 2g + 1 in Z[x]. For an odd prime p not dividing the discriminant of Q, let Z_p(T) denote the zeta function of the hyperelliptic curve of genus g over the finite field F_p…

Number Theory · Mathematics 2013-09-27 David Harvey

Assuming the Generalized Riemann Hypothesis, we design a deterministic algorithm that, given a prime p and positive integer m=o(sqrt(p)/(log p)^4), outputs an elliptic curve E over the finite field F_p for which the cardinality of E(F_p) is…

Number Theory · Mathematics 2017-01-03 Igor E. Shparlinski , Andrew V. Sutherland

In RSA cryptography numbers of the form $pq$, with $p$ and $q$ two distinct proportional primes play an important role. For a fixed real number $r>1$ we formalize this by saying that an integer $pq$ is an RSA-integer if $p$ and $q$ are…

Number Theory · Mathematics 2020-08-27 Pieter Moree , Sumaia Saad Eddin

Robust principal component analysis (RPCA) has been widely used for recovering low-rank matrices in many data mining and machine learning problems. It separates a data matrix into a low-rank part and a sparse part. The convex approach has…

Computer Vision and Pattern Recognition · Computer Science 2016-09-29 Chong Peng , Zhao Kang , Qiang Chen
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