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A $d$-dimensional matrix is called emph{$1$-polystochastic} if it is non-negative and the sum over each line equals~$1$. Such a matrix that has a single $1$ in each line and zeros elsewhere is called a emph{$1$-permutation} matrix. A emph{diagonal} of a $d$-dimensional matrix of order $n$ is a choice of $n$ elements, no two in the same hyperplane. The emph{permanent} of a $d$-dimensional matrix is the sum over the diagonals of the product of the elements within the diagonal. For a given order $n$ and dimension $d$, the set of $1$-polystochastic matrices forms a convex polytope that includes the $1$-permutation matrices within its set of vertices. For even $n$ and odd $d$, we give a construction for a class of $1$-permutation matrices with zero permanent. Consequently, we show that the set of $1$-polystochastic matrices with zero permanent contains at least $n^{n^{3/2}(1/2-o(1))}$ $1$-permutation matrices and contains a polytope of dimension at least $cn^{3/2}$ for fixed $c,d$ and even $ntoinfty$. We also provide counterexamples to a conjecture by Taranenko about the location of local extrema of the permanent. For odd $d$, we give a construction of $1$-permutation matrices that decompose into a convex linear sum of positive diagonals. These combine with a theorem of Taranenko to provide counterexamples to a conjecture by Dow and Gibson generalising van der Waerdens conjecture to higher dimensions.
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The permanent of a multidimensional matrix is the sum of products of entries over all diagonals. By Mincs conjecture, there exists a reachable upper bound on the permanent of 2-dimensional (0,1)-matrices. In this paper we obtain some generalizations of Mincs conjecture to the multidimensional case. For this purpose we prove and compare several bounds on the permanent of multidimensional (0,1)-matrices. Most estimates can be used for matrices with nonnegative bounded entries.
Let $R$ be a commutative additively idempotent semiring. In this paper, some properties and characterizations for permanents of matrices over $R$ are established, and several inequalities for permanents are given. Also, the adjiont matrices of matriecs over $R$ are considered. Partial results obtained in this paper generalize the corresponding ones on fuzzy matrices, on lattice matrices and on incline matrices.
In this paper we consider the problem of computing the likelihood of the profile of a discrete distribution, i.e., the probability of observing the multiset of element frequencies, and computing a profile maximum likelihood (PML) distribution, i.e., a distribution with the maximum profile likelihood. For each problem we provide polynomial time algorithms that given $n$ i.i.d. samples from a discrete distribution, achieve an approximation factor of $expleft(-O(sqrt{n} log n) right)$, improving upon the previous best-known bound achievable in polynomial time of $exp(-O(n^{2/3} log n))$ (Charikar, Shiragur and Sidford, 2019). Through the work of Acharya, Das, Orlitsky and Suresh (2016), this implies a polynomial time universal estimator for symmetric properties of discrete distributions in a broader range of error parameter. We achieve these results by providing new bounds on the quality of approximation of the Bethe and Sinkhorn permanents (Vontobel, 2012 and 2014). We show that each of these are $exp(O(k log(N/k)))$ approximations to the permanent of $N times N$ matrices with non-negative rank at most $k$, improving upon the previous known bounds of $exp(O(N))$. To obtain our results on PML, we exploit the fact that the PML objective is proportional to the permanent of a certain Vandermonde matrix with $sqrt{n}$ distinct columns, i.e. with non-negative rank at most $sqrt{n}$. As a by-product of our work we establish a surprising connection between the convex relaxation in prior work (CSS19) and the well-studied Bethe and Sinkhorn approximations.
A celebrated result of Morse and Hedlund, stated in 1938, asserts that a sequence $x$ over a finite alphabet is ultimately periodic if and only if, for some $n$, the number of different factors of length $n$ appearing in $x$ is less than $n+1$. Attempts to extend this fundamental result, for example, to higher dimensions, have been considered during the last fifteen years. Let $dge 2$. A legitimate extension to a multidimensional setting of the notion of periodicity is to consider sets of $ZZ^d$ definable by a first order formula in the Presburger arithmetic $<ZZ;<,+>$. With this latter notion and using a powerful criterion due to Muchnik, we exhibit a complete extension of the Morse--Hedlund theorem to an arbitrary dimension $d$ and characterize sets of $ZZ^d$ definable in $<ZZ;<,+>$ in terms of some functions counting recurrent blocks, that is, blocks occurring infinitely often.
In 1960, Hoffman and Singleton cite{HS60} solved a celebrated equation for square matrices of order $n$, which can be written as $$ (kappa - 1) I_n + J_n - A A^{rm T} = A$$ where $I_n$, $J_n$, and $A$ are the identity matrix, the all one matrix, and a $(0,1)$--matrix with all row and column sums equal to $kappa$, respectively. If $A$ is an incidence matrix of some configuration $cal C$ of type $n_kappa$, then the left-hand side $Theta(A):= (kappa - 1)I_n + J_n - A A^{rm T}$ is an adjacency matrix of the non--collinearity graph $Gamma$ of $cal C$. In certain situations, $Theta(A)$ is also an incidence matrix of some $n_kappa$ configuration, namely the neighbourhood geometry of $Gamma$ introduced by Lef`evre-Percsy, Percsy, and Leemans cite{LPPL}. The matrix operator $Theta$ can be reiterated and we pose the problem of solving the generalised Hoffman--Singleton equation $Theta^m(A)=A$. In particular, we classify all $(0,1)$--matrices $M$ with all row and column sums equal to $kappa$, for $kappa = 3,4$, which are solutions of this equation. As a by--product, we obtain characterisations for incidence matrices of the configuration $10_3F$ in Kantors list cite{Kantor} and the $17_4$ configuration $#1971$ in Betten and Bettens list cite{BB99}.
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