Determinantal Sieving

We introduce determinantal sieving, a new, remarkably powerful tool in the toolbox of algebraic FPT algorithms. Given a polynomial $P(X)$ on a set of variables $X=\{x_1,\ldots,x_n\}$ and a linear matroid $M=(X,\mathcal{I})$ of rank $k$, both over a field $\mathbb{F}$ of characteristic 2, in $2^k$ evaluations we can sieve for those terms in the monomial expansion of $P$ which are multilinear and whose support is a basis for $M$. Alternatively, using $2^k$ evaluations of $P$ we can sieve for those monomials whose odd support spans $M$. Applying this framework, we improve on a range of algebraic FPT algorithms, such as: 1. Solving $q$-Matroid Intersection in time $O^*(2^{(q-2)k})$ and $q$-Matroid Parity in time $O^*(2^{qk})$, improving on $O^*(4^{qk})$ (Brand and Pratt, ICALP 2021) 2. $T$-Cycle, Colourful $(s,t)$-Path, Colourful $(S,T)$-Linkage in undirected graphs, and the more general Rank $k$ $(S,T)$-Linkage problem, all in $O^*(2^k)$ time, improving on $O^*(2^{k+|S|})$ respectively $O^*(2^{|S|+O(k^2 \log(k+|\mathbb{F}|))})$ (Fomin et al., SODA 2023) 3. Many instances of the Diverse X paradigm, finding a collection of $r$ solutions to a problem with a minimum mutual distance of $d$ in time $O^*(2^{r(r-1)d/2})$, improving solutions for $k$-Distinct Branchings from time $2^{O(k \log k)}$ to $O^*(2^k)$ (Bang-Jensen et al., ESA 2021), and for Diverse Perfect Matchings from $O^*(2^{2^{O(rd)}})$ to $O^*(2^{r^2d/2})$ (Fomin et al., STACS 2021) All matroids are assumed to be represented over a field of characteristic 2. Over general fields, we achieve similar results at the cost of using exponential space by working over the exterior algebra. For a class of arithmetic circuits we call strongly monotone, this is even achieved without any loss of running time. However, the odd support sieving result appears to be specific to working over characteristic 2

Traversing combinatorial 0/1-polytopes via optimization

In this paper, we present a new framework that exploits combinatorial optimization for efficiently generating a large variety of combinatorial objects based on graphs, matroids, posets and polytopes. Our method relies on a simple and versatile algorithm for computing a Hamilton path on the skeleton of any 0/1-polytope \conv(X), where X\seq \{0,1\}^n. The algorithm uses as a black box any algorithm that solves a variant of the classical linear optimization problem~$\min\{w\cdot x\mid x\in X\}$, and the resulting delay, i.e., the running time per visited vertex on the Hamilton path, is only by a factor of $\log n$ larger than the running time of the optimization algorithm. When $X$ encodes a particular class of combinatorial objects, then traversing the skeleton of the polytope~\conv(X) along a Hamilton path corresponds to listing the combinatorial objects by local change operations, i.e., we obtain Gray code listings. As concrete results of our general framework, we obtain efficient algorithms for generating all ($c$-optimal) bases and independent sets in a matroid; ($c$-optimal) spanning trees, forests, matchings, maximum matchings, and $c$-optimal matchings in a general graph; vertex covers, minimum vertex covers, $c$-optimal vertex covers, stable sets, maximum stable sets and $c$-optimal stable sets in a bipartite graph; as well as antichains, maximum antichains, $c$-optimal antichains, and $c$-optimal ideals of a poset. Specifically, the delay and space required by these algorithms are polynomial in the size of the matroid ground set, graph, or poset, respectively. Furthermore, all of these listings correspond to Hamilton paths on the corresponding combinatorial polytopes, namely the base polytope, matching polytope, vertex cover polytope, stable set polytope, chain polytope and order polytope, respectively. As another corollary from our framework, we obtain an \cO(t_{\upright{LP}} \log n) delay algorithm for the vertex enumeration problem on 0/1-polytopes $\{x\in\mathbb{R}^n\mid Ax\leq b\}$, where $A\in \mathbb{R}^{m\times n}$ and~$b\in\mathbb{R}^m$, and t_{\upright{LP}} is the time needed to solve the linear program $\min\{w\cdot x\mid Ax\leq b\}$. This improves upon the 25-year old \cO(t_{\upright{LP}}\,n) delay algorithm due to Bussieck and L\"ubbecke

Análise de mecanismos com restrições redundantes através da aplicação da teoria de matroides

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2015.O estudo de mecanismo é uma das áreas mais importantes no projeto de máquinas e os seus problemas podem ser divididos em dois grupos: análise de mecanismos e síntese de mecanismos. O foco desta tese é a análise da topologia de mecanismos, em termos de graus de liberdade e restrições, através da teoria de helicoides e da teoria de matroides. Na tese é elaborada uma modelagem geral dos graus de liberdade e das restrições de um mecanismo, utilizando a representação por helicoides e a adaptação das leis de Kirchhoff proposta por Davies para cadeias cinemáticas. Baseada nesta modelagem, é desenvolvida uma nova metodologia de análise de mecanismos para a eliminação automática das restrições redundantes. Ao mesmo tempo, a teoria de matroides é utilizada na análise dos mecanismos. A tese introduz novos resultados na teoria de mecanismos. Primeiramente, é analisada a escolha dos conjuntos de atuadores válidos para um mecanismo. Dois novos algoritmos são propostos para a enumeração de todos os possíveis conjuntos válidos de atuadores e a para a escolha ótima de um conjunto válido de atuadores com base nas especificações do mecanismo. Posteriormente, são analisados os possíveis mecanismos auto alinhantes derivados de um mecanismo com restrições redundantes. Dois novos algoritmos são propostos para enumeração de todos os possíveis mecanismos auto alinhantes obtidos retirando as restrições redundantes de um dado mecanismo e para escolha ótima de um mecanismo auto alinhante, com base nas suas especificações. Os algoritmos foram implementados no software Sage e apresentam complexidade polinomial. Exemplos de aplicação são apresentados e os resultados validados frente à literatura. Duas contribuições adicionais são também introduzidas: a definição de um invariante cinemático que relaciona a mobilidade com o número de restrições redundantes de um mecanismos e um contraexemplo para a metodologia de análise das restrições redundantes proposta por Reshetov.Abstract : The study of mechanisms is one of the most important areas on which machine design relies. Research in mechanism can be roughly divided into two main problems: mechanism analysis and mechanism synthesis. This thesis focuses on topology analysis of mechanism, by means of screw theory representation of mechanisms. Freedoms and constraints in mechanisms are thus described applying the Kirchhoff's laws adaptation to multibody systems proposed by Davies. Based on this modelling, overconstraint in mechanisms is analysed in terms of free motions and constraints. Two main contributions are proposed along this work, based on matroid theory and linear algebra modelling. First, the actuation schemes of a mechanism are investigated. Two algorithms are proposed for enumerating all valid actuation schemes of an overconstrained mechanism and for selecting an optimal actuation scheme, based on a set of criteria. Second, the self-aligning mechanisms kinematically equivalent to an overconstraint mechanism are investigated. Two new algorithms for enumerating all self-aligning kinematically equivalent mechanisms to an overconstrained one and for selecting an optimal self-aligning topology, based on a set of criteria, are proposed. All algorithms have been implemented in Sage software and run in polynomial time. Examples of applications are presented, and the results obtained validated with literature cases. Moreover, two further contributions are proposed: the definition of an invariant kinematic chain relating mobility and degree of constraint and a counterexample for the methodology proposed by Reshetov

All your bases are belong to us : listing all bases of a matroid by greedy exchanges

You provide us with a matroid and an initial base. We say that a subset of the bases "belongs to us" if we can visit each one via a sequence of base exchanges starting from the initial base. It is well-known that "All your base are belong to us". We refine this classic result by showing that it can be done by a simple greedy algorithm. For example, the spanning trees of a graph can be generated by edge exchanges using the following greedy rule: Minimize the larger label of an edge that enters or exits the current spanning tree and which creates a spanning tree that is new (i.e., hasn't been visited already). Amazingly, this works for any graph, for any labeling of its edges, for any initial spanning tree, and regardless of how you choose the edge with the smaller label in each exchange. Furthermore, by maintaining a small amount of information, we can generate each successive spanning tree without storing the previous trees. In general, for any matroid, we can greedily compute a listing of all its bases matroid such that consecutive bases differ by a base exchange. Our base exchange Gray codes apply a prefix-exchange on a prefix-minor of the matroid, and we can generate these orders using "history-free" iterative algorithms. More specifically, we store O(m) bits of data, and use O(m) time per base assuming O(1) time independence and coindependence oracles. Our work generalizes and extends a number of previous results. For example, the bases of the uniform matroid are combinations, and they belong to us using homogeneous transpositions via an Eades-McKay style order. Similarly, the spanning trees of fan graphs belong to us via face pivot Gray codes, which extends recent results of Cameron, Grubb, and Sawada [Pivot Gray Codes for the Spanning Trees of a Graph ft. the Fan, COCOON 2021]

Approximate Sampling and Counting of Graphs with Near-Regular Degree Intervals

The approximate uniform sampling of graphs with a given degree sequence is a well-known, extensively studied problem in theoretical computer science and has significant applications, e.g., in the analysis of social networks. In this work we study an extension of the problem, where degree intervals are specified rather than a single degree sequence. We are interested in sampling and counting graphs whose degree sequences satisfy the degree interval constraints. A natural scenario where this problem arises is in hypothesis testing on social networks that are only partially observed. In this work, we provide the first fully polynomial almost uniform sampler (FPAUS) as well as the first fully polynomial randomized approximation scheme (FPRAS) for sampling and counting, respectively, graphs with near-regular degree intervals, in which every node $i$ has a degree from an interval not too far away from a given $d \in \N$. In order to design our FPAUS, we rely on various state-of-the-art tools from Markov chain theory and combinatorics. In particular, we provide the first non-trivial algorithmic application of a breakthrough result of Liebenau and Wormald (2017) regarding an asymptotic formula for the number of graphs with a given near-regular degree sequence. Furthermore, we also make use of the recent breakthrough of Anari et al. (2019) on sampling a base of a matroid under a strongly log-concave probability distribution. As a more direct approach, we also study a natural Markov chain recently introduced by Rechner, Strowick and M\"uller-Hannemann (2018), based on three simple local operations: Switches, hinge flips, and additions/deletions of a single edge. We obtain the first theoretical results for this Markov chain by showing it is rapidly mixing for the case of near-regular degree intervals of size at most one