Author(s):  
Samsul Arifin ◽  
Indra Bayu Muktyas

An SPL can be represented as a multiplication of the coefficient matrix and solution vector of the SPL. Determining the solution of an SPL can use the inverse matrix method and Cramer's rule, where both can use the concept of the determinant of a matrix. If the coefficient matrix is a unimodular matrix, then all solutions of an SPL are integers. In this paper we will present a method of generating a unimodular matrix using Python so that it can be utilized on an SPL. Keywords: SPL, Unimodular Matrix, Python


1957 ◽  
Vol 9 ◽  
pp. 47-59
Author(s):  
A. T. Butson

1. Introduction. Let be a Boolean ring of at least two elements containing a unit 1. Form the set of matrices A, B, … of order n having entries aiJ, bij, … (i, j = 1, 2, …, n), which are members of . A matrix U of is called unimodular if there exists a matrix V of such that VU= I, the identity matrix. Two matrices A and B are said to be left-associates if there exists a unimodular matrix U satisfying UA = B.


10.37236/1526 ◽  
2000 ◽  
Vol 7 (1) ◽  
Author(s):  
Benjamin Doerr

We show that the linear discrepancy of a basic totally unimodular matrix $A \in R^{m \times n}$ is at most $1- {1\over {n+1}}$. This extends a result of Peng and Yan.


This paper begins with a heuristic derivation of the explicit and covariant law of multiplica­tion of the Dirac algebra, regarded as a matrix algebra. To achieve this the 'space-time’ R 4 of signature —2 is embedded in a six-dimensional flat space R 6 of signature 0, —2, or — 4, as the case may be. The metric tensor need not be diagonal. The 15 elements of the algebra, excluding the unit element, then transform as a bi-vector in R 6 . Just as two-spinors are associated with four-dimensional Lorentz transformations, so four-spinors, i. e. the vectors and tensors of a four-dimensional complex linear vector space S 4 , naturally associate themselves with Lorentz transformations in six dimensions. After some incidental work the group of proper orthogonal transformations in R 6 is considered, together with the group of spin transformations S it induces in S 4 . One then arrives at once at the known local iso­morphisms SO (5, 1) ≈ SU *(4), SO (4, 2) ≈ SU(2, 2), SO (3, 3) ≈ SL(4, R ); and the generic form of S in each case is explicitly set down. The second part of the work starts with an approach to the law of multiplication from a deductive point of view. It is based upon the observation that transformations of the form SMŚ of any skew-symmetric 4 x 4 matrix by an arbitrary unimodular matrix S leave its skew-symmetry and its determinant ∆ invariant; at the same time ∆ is a perfect square, so that the six linearly independent elements M uv of M can be brought into linear one-one correspondence with six real variables x A in such a way that ∆ is the square of the metric ground form gAB x A x B of an R є . This correspondence between x A and M uv leads to a basis of six skew-symmetric vector spinors u Auv and their duals û A uv . The skew-symmetrized matrix product e AB = u [ A û B ] is deductively shown to obey the law of multiplication of the Dirac algebra. The spinors H, C, T and a vector q A associated with Hermitian conjugation, complex conjugation and transposition of the e AB are examined from a (spin-) tensorial point of view. H -1 , now written as g u̇v is introduced as a metric in S 4. Then T uv and C uv are identical, and further C uv ] is self-dual. The theory is now made fully covariant (in the sense that the restriction det S = 1 is dropped) by attaching suitable spin weights and anti-weights to the various spinors which occur. A new vector-spinor v A is defined which is a kind of six-dimensional analogue of the set of Dirac matrices; and with its help a formal six­-dimensional generalization of Dirac’s equation is written down. The last part of this paper deals with the generalization of the appropriate parts of the preceding theory to the situation in which g AB becomes the metric tensor of a Riemann space V 6 .


2000 ◽  
Vol 9 (3) ◽  
pp. 277-285 ◽  
Author(s):  
JOHN MOUNT

This paper describes methods for counting the number of nonnegative integer solutions of the system Ax = b when A is a nonnegative totally unimodular matrix and b an integral vector of fixed dimension. The complexity (under a unit cost arithmetic model) is strong in the sense that it depends only on the dimensions of A and not on the size of the entries of b. For the special case of ‘contingency tables’ the run-time is 2O(√dlogd) (where d is the dimension of the polytope). The method is complementary to Barvinok's in that our algorithm is effective on problems of high dimension with a fixed number of (non-sign) constraints, whereas Barvinok's algorithms are effective on problems of low dimension and an arbitrary number of constraints.


Sign in / Sign up

Export Citation Format

Share Document