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We refine the bit complexity analysis of an algorithm for the computation of at least one point per connected component of a smooth real algebraic set, yielding exponential speedup (with respect to the number of variables) compared to prior…

Symbolic Computation · Computer Science 2025-08-29 Jesse Elliott , Mark Giesbrecht , Edern Gillot , Mohab Safey El Din , Éric Schost

The Numerical Recipes series of books are a useful resource, but all the algorithms they contain cannot be used within open-source projects. In this paper we develop drop-in alternatives to the two algorithms they present for cubic spline…

Mathematical Software · Computer Science 2020-01-28 Haysn Hornbeck

Using region crossing changes, we define a new invariant called the multi-region index of a knot. We prove that the multi-region index of a knot is bounded from above by twice the crossing number of the knot. In addition, we show that the…

Geometric Topology · Mathematics 2020-06-02 Sarah Goodhill , Adam M. Lowrance , Valeria Munoz Gonzales , Jessica Rattray , Amelia Zeh

We investigate the sparse spikes deconvolution problem onto spaces of algebraic polynomials. Our framework encompasses the measure reconstruction problem from a combination of noiseless and noisy moment measurements. We study a TV-norm…

Statistics Theory · Mathematics 2015-05-28 Yohann De Castro , Guillaume Mijoule

We give three algorithms to determine the crosscap number of a knot in the 3-sphere using $0$-efficient triangulations and normal surface theory. Our algorithms are shown to be correct for a larger class of complements of knots in closed…

Geometric Topology · Mathematics 2024-12-25 William Jaco , J. Hyam Rubinstein , Jonathan Spreer , Stephan Tillmann

Recently the author and U. Reif introduced the concept of diversification of uniform tensor product B-splines. Based on this concept, we give a new constructive modification of non-uniform B-splines. The resulting spline spaces are…

Classical Analysis and ODEs · Mathematics 2016-11-17 Nada Sissouno

In this paper, we study a class of approximation problems, appearing in data approximation and signal processing. The approximations are constructed as combinations of polynomial splines (piecewise polynomials), whose parameters are subject…

Optimization and Control · Mathematics 2015-03-05 Zahra Roshan Zamir , Nadezda Sukhorukova

Quantum error correction typically requires repeated syndrome extraction due to measurement noise, which results in substantial time overhead in fault-tolerant computation. Single-shot error correction aims to suppress errors using only one…

Quantum Physics · Physics 2025-11-26 Yingjia Lin , Abhinav Anand , Kenneth R. Brown

New differential-recurrence relations for B-spline basis functions are given. Using these relations, a recursive method for finding the Bernstein-B\'{e}zier coefficients of B-spline basis functions over a single knot span is proposed. The…

Numerical Analysis · Mathematics 2024-07-22 Filip Chudy , Paweł Woźny

We explore the application of automated reasoning techniques to unknot detection, a classical problem of computational topology. We adopt a two-pronged experimental approach, using a theorem prover to try to establish a positive result…

Logic in Computer Science · Computer Science 2014-05-19 Andrew Fish , Alexei Lisitsa

In this paper we investigate the role of local information in the decoding of the repetition and surface error correction codes for the protection of quantum states. Our key result is an improvement in resource efficiency when local…

Quantum Physics · Physics 2020-06-30 Michael Hanks , William J. Munro , Kae Nemoto

We introduce natural language processing into the study of knot theory, as made natural by the braid word representation of knots. We study the UNKNOT problem of determining whether or not a given knot is the unknot. After describing an…

Geometric Topology · Mathematics 2020-11-02 Sergei Gukov , James Halverson , Fabian Ruehle , Piotr Sułkowski

We present a general variational framework for the training of freeform nonlinearities in layered computational architectures subject to some slope constraints. The regularization that we add to the traditional training loss penalizes the…

Machine Learning · Statistics 2025-03-31 Michael Unser , Alexis Goujon , Stanislas Ducotterd

This report studies local asymptotics of P-splines with $p$th degree B-splines and a $m$th order difference penalty. Earlier work with $p$ and $m$ restricted is extended to the general case. Asymptotically, penalized splines are kernel…

Statistics Theory · Mathematics 2012-06-12 Luo Xiao , Yingxing Li , Tatiyana V. Apanasovich , David Ruppert

In this paper, we extend our previous work on the study of local scales of a function to studying local scales on curves and surfaces. In the case of a function f, the local scales of f at x is computed by measuring the deviation of f from…

Functional Analysis · Mathematics 2016-07-22 Triet Minh Le

Location estimation is a central problem in functional data analysis. In this paper, we investigate penalized spline estimators of location for discretely sampled functional data under a broad class of convex loss functions. Our framework…

Methodology · Statistics 2025-08-19 Ioannis Kalogridis

In many classification problems it is desirable to output well-calibrated probabilities on the different classes. We propose a robust, non-parametric method of calibrating probabilities called SplineCalib that utilizes smoothing splines to…

Machine Learning · Statistics 2018-09-21 Brian Lucena

The Slope Conjecture relates a quantum knot invariant, (the degree of the colored Jones polynomial of a knot) with a classical one (boundary slopes of incompressible surfaces in the knot complement). The degree of the colored Jones…

Geometric Topology · Mathematics 2016-08-03 Stavros Garoufalidis , Roland van der Veen

We present new fault jump estimates to guide local refinement in surface approximation schemes with adaptive spline constructions. The proposed approach is based on the idea that, since discontinuities in the data should naturally…

Numerical Analysis · Mathematics 2024-06-27 Cesare Bracco , Carlotta Giannelli , Francesco Patrizi , Alessandra Sestini

Extracting parameter constraints from cosmological observations requires accurate determination of the covariance matrix for use in the likelihood function. We show here that uncertainties in the elements of the covariance matrix propagate…

Cosmology and Nongalactic Astrophysics · Physics 2013-10-30 Scott Dodelson , Michael D. Schneider