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We prove that a space whose topological complexity equals 1 is homotopy equivalent to some odd-dimensional sphere. We prove a similar result, although not in complete generality, for spaces X whose higher topological complexity TC_n(X) is…

Algebraic Topology · Mathematics 2012-07-20 Mark Grant , Gregory Lupton , John Oprea

This chapter delves into the realm of computational complexity, exploring the world of challenging combinatorial problems and their ties with statistical physics. Our exploration starts by delving deep into the foundations of combinatorial…

Disordered Systems and Neural Networks · Physics 2023-10-04 Raffaele Marino

In this article we demonstrate how algorithmic probability theory is applied to situations that involve uncertainty. When people are unsure of their model of reality, then the outcome they observe will cause them to update their beliefs. We…

Artificial Intelligence · Computer Science 2014-05-26 Phil Maguire , Philippe Moser , Rebecca Maguire , Mark Keane

In the modern Bayesian view classical probability theory is simply an extension of conventional logic, i.e., a quantitative tool that allows for consistent reasoning in the presence of uncertainty. Classical theory presupposes, however,…

Quantum Physics · Physics 2007-06-20 Jochen Rau

We develop a complexity theory for approximate real computations. We first produce a theory for exact computations but with condition numbers. The input size depends on a condition number, which is not assumed known by the machine. The…

Computational Complexity · Computer Science 2020-05-05 Gregorio Malajovich , Mike Shub

The topological (resp. geodesic) complexity of a topological (resp. metric) space is roughly the smallest number of continuous rules required to choose paths (resp. shortest paths) between any points of the space. We prove that the geodesic…

Metric Geometry · Mathematics 2023-08-09 Donald M. Davis

Composite minimization involves a collection of smooth functions which are aggregated in a nonsmooth manner. In the convex setting, we design an algorithm by linearizing each smooth component in accordance with its main curvature. The…

Optimization and Control · Mathematics 2019-03-26 Jérôme Bolte , Zheng Chen , Edouard Pauwels

In information theory, some optimization problems result in convex optimization problems on strictly convex functionals of probability densities. In this note, we study these problems and show conditions of minimizers and the uniqueness of…

Information Theory · Computer Science 2020-03-17 Tomohiro Nishiyama

As is well known the Complex Langevin (CL) method sometimes fails to converge or converges to the wrong limit. We identified one reason for this long ago: insufficient decay of the probability density either near infinity or near poles of…

High Energy Physics - Lattice · Physics 2019-01-30 Manuel Scherzer , Erhard Seiler , Dénes Sexty , Ion-Olimpiu Stamatescu

We prove Farber's conjecture on the stable topological complexity of configuration spaces of graphs. The conjecture follows from a general lower bound derived from recent insights into the topological complexity of aspherical spaces. Our…

Algebraic Topology · Mathematics 2022-09-20 Ben Knudsen

We consider the problem of packing congruent circles with the maximum radius in a unit square as a mathematical optimization problem. Due to the presence of non-overlapping constraints, this problem is a notoriously difficult nonconvex…

Optimization and Control · Mathematics 2024-04-05 Aida Khajavirad

We show that Kaplansky's unit conjecture is true, under the assumption that the underlying field is complex.

Algebraic Geometry · Mathematics 2022-10-14 Kwok Kwan Wong

We show that a realization of a closed connected PL-manifold of dimension n-1 in n-dimensional Euclidean space (n>2) is the boundary of a convex polyhedron (finite or infinite) if and only if the interior of each (n-3)-face has a point,…

Computational Geometry · Computer Science 2007-05-23 Konstantin Rybnikov

Let $B$ be a point robot moving in the plane, whose path is constrained to forward motions with curvature at most one, and let $P$ be a convex polygon with $n$ vertices. Given a starting configuration (a location and a direction of travel)…

Computational Geometry · Computer Science 2010-08-26 Hee-Kap Ahn , Otfried Cheong , Jirí Matoušek , Antoine Vigneron

We analyse the convergence of the proximal gradient algorithm for convex composite problems in the presence of gradient and proximal computational inaccuracies. We derive new tighter deterministic and probabilistic bounds that we use to…

Optimization and Control · Mathematics 2022-03-07 Anis Hamadouche , Yun Wu , Andrew M. Wallace , Joao F. C. Mota

The complexity of a computational problem is traditionally quantified based on the hardness of its worst case. This approach has many advantages and has led to a deep and beautiful theory. However, from the practical perspective, this…

Computational Complexity · Computer Science 2012-05-23 Yonatan Bilu , Amit Daniely , Nati Linial , Michael Saks

Proving that there are problems in $\mathsf{P}^\mathsf{NP}$ that require boolean circuits of super-linear size is a major frontier in complexity theory. While such lower bounds are known for larger complexity classes, existing results only…

Computational Complexity · Computer Science 2023-06-22 Jan Bydzovsky , Jan Krajicek , Igor C. Oliveira

A previous study analyzed the convergence of probability densities for forward and inverse problems when a sequence of approximate maps between model inputs and outputs converges in $L^\infty$. This work generalizes the analysis to cases…

Probability · Mathematics 2020-01-14 Troy Butler , Tim Wildey , Wenjuan Zhang

We present a generalization of Brouwer's conjectural family of inequalities -- a popular family of inequalities in spectral graph theory bounding the partial sum of the Laplacian eigenvalues of graphs -- for the case of abstract simplicial…

Combinatorics · Mathematics 2019-07-18 Rediet Abebe

Complexity theory as practiced by physicists and computational complexity theory as practiced by computer scientists both characterize how difficult it is to solve complex problems. Here it is shown that the parameters of a specific model…

Disordered Systems and Neural Networks · Physics 2013-05-29 S. N. Coppersmith