The Centro-Invertible Matrix: a New Type of Matrix Arising in Pseudo-Random Number Generation ∗ Roy S
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CONSTRUCTING INTEGER MATRICES with INTEGER EIGENVALUES CHRISTOPHER TOWSE,∗ Scripps College
Applied Probability Trust (25 March 2016) CONSTRUCTING INTEGER MATRICES WITH INTEGER EIGENVALUES CHRISTOPHER TOWSE,∗ Scripps College ERIC CAMPBELL,∗∗ Pomona College Abstract In spite of the proveable rarity of integer matrices with integer eigenvalues, they are commonly used as examples in introductory courses. We present a quick method for constructing such matrices starting with a given set of eigenvectors. The main feature of the method is an added level of flexibility in the choice of allowable eigenvalues. The method is also applicable to non-diagonalizable matrices, when given a basis of generalized eigenvectors. We have produced an online web tool that implements these constructions. Keywords: Integer matrices, Integer eigenvalues 2010 Mathematics Subject Classification: Primary 15A36; 15A18 Secondary 11C20 In this paper we will look at the problem of constructing a good problem. Most linear algebra and introductory ordinary differential equations classes include the topic of diagonalizing matrices: given a square matrix, finding its eigenvalues and constructing a basis of eigenvectors. In the instructional setting of such classes, concrete “toy" examples are helpful and perhaps even necessary (at least for most students). The examples that are typically given to students are, of course, integer-entry matrices with integer eigenvalues. Sometimes the eigenvalues are repeated with multipicity, sometimes they are all distinct. Oftentimes, the number 0 is avoided as an eigenvalue due to the degenerate cases it produces, particularly when the matrix in question comes from a linear system of differential equations. Yet in [10], Martin and Wong show that “Almost all integer matrices have no integer eigenvalues," let alone all integer eigenvalues. -
Fast Computation of the Rank Profile Matrix and the Generalized Bruhat Decomposition Jean-Guillaume Dumas, Clement Pernet, Ziad Sultan
Fast Computation of the Rank Profile Matrix and the Generalized Bruhat Decomposition Jean-Guillaume Dumas, Clement Pernet, Ziad Sultan To cite this version: Jean-Guillaume Dumas, Clement Pernet, Ziad Sultan. Fast Computation of the Rank Profile Matrix and the Generalized Bruhat Decomposition. Journal of Symbolic Computation, Elsevier, 2017, Special issue on ISSAC’15, 83, pp.187-210. 10.1016/j.jsc.2016.11.011. hal-01251223v1 HAL Id: hal-01251223 https://hal.archives-ouvertes.fr/hal-01251223v1 Submitted on 5 Jan 2016 (v1), last revised 14 May 2018 (v2) HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Fast Computation of the Rank Profile Matrix and the Generalized Bruhat Decomposition Jean-Guillaume Dumas Universit´eGrenoble Alpes, Laboratoire LJK, umr CNRS, BP53X, 51, av. des Math´ematiques, F38041 Grenoble, France Cl´ement Pernet Universit´eGrenoble Alpes, Laboratoire de l’Informatique du Parall´elisme, Universit´ede Lyon, France. Ziad Sultan Universit´eGrenoble Alpes, Laboratoire LJK and LIG, Inria, CNRS, Inovall´ee, 655, av. de l’Europe, F38334 St Ismier Cedex, France Abstract The row (resp. column) rank profile of a matrix describes the stair-case shape of its row (resp. -
Chapter 0 Preliminaries
Chapter 0 Preliminaries Objective of the course Introduce basic matrix results and techniques that are useful in theory and applications. It is important to know many results, but there is no way I can tell you all of them. I would like to introduce techniques so that you can obtain the results you want. This is the standard teaching philosophy of \It is better to teach students how to fish instead of just giving them fishes.” Assumption You are familiar with • Linear equations, solution sets, elementary row operations. • Matrices, column space, row space, null space, ranks, • Determinant, eigenvalues, eigenvectors, diagonal form. • Vector spaces, basis, change of bases. • Linear transformations, range space, kernel. • Inner product, Gram Schmidt process for real matrices. • Basic operations of complex numbers. • Block matrices. Notation • Mn(F), Mm;n(F) are the set of n × n and m × n matrices over F = R or C (or a more general field). n • F is the set of column vectors of length n with entries in F. • Sometimes we write Mn;Mm;n if F = C. A1 0 • If A = 2 Mm+n(F) with A1 2 Mm(F) and A2 2 Mn(F), we write A = A1 ⊕ A2. 0 A2 • xt;At denote the transpose of a vector x and a matrix A. • For a complex matrix A, A denotes the matrix obtained from A by replacing each entry by its complex conjugate. Furthermore, A∗ = (A)t. More results and examples on block matrix multiplications. 1 1 Similarity, Jordan form, and applications 1.1 Similarity Definition 1.1.1 Two matrices A; B 2 Mn are similar if there is an invertible S 2 Mn such that S−1AS = B, equivalently, A = T −1BT with T = S−1. -
Ratner's Work on Unipotent Flows and Impact
Ratner’s Work on Unipotent Flows and Its Impact Elon Lindenstrauss, Peter Sarnak, and Amie Wilkinson Dani above. As the name suggests, these theorems assert that the closures, as well as related features, of the orbits of such flows are very restricted (rigid). As such they provide a fundamental and powerful tool for problems connected with these flows. The brilliant techniques that Ratner in- troduced and developed in establishing this rigidity have been the blueprint for similar rigidity theorems that have been proved more recently in other contexts. We begin by describing the setup for the group of 푑×푑 matrices with real entries and determinant equal to 1 — that is, SL(푑, ℝ). An element 푔 ∈ SL(푑, ℝ) is unipotent if 푔−1 is a nilpotent matrix (we use 1 to denote the identity element in 퐺), and we will say a group 푈 < 퐺 is unipotent if every element of 푈 is unipotent. Connected unipotent subgroups of SL(푑, ℝ), in particular one-parameter unipo- Ratner presenting her rigidity theorems in a plenary tent subgroups, are basic objects in Ratner’s work. A unipo- address to the 1994 ICM, Zurich. tent group is said to be a one-parameter unipotent group if there is a surjective homomorphism defined by polyno- In this note we delve a bit more into Ratner’s rigidity theo- mials from the additive group of real numbers onto the rems for unipotent flows and highlight some of their strik- group; for instance ing applications, expanding on the outline presented by Elon Lindenstrauss is Alice Kusiel and Kurt Vorreuter professor of mathemat- 1 푡 푡2/2 1 푡 ics at The Hebrew University of Jerusalem. -
Integer Matrix Approximation and Data Mining
Noname manuscript No. (will be inserted by the editor) Integer Matrix Approximation and Data Mining Bo Dong · Matthew M. Lin · Haesun Park Received: date / Accepted: date Abstract Integer datasets frequently appear in many applications in science and en- gineering. To analyze these datasets, we consider an integer matrix approximation technique that can preserve the original dataset characteristics. Because integers are discrete in nature, to the best of our knowledge, no previously proposed technique de- veloped for real numbers can be successfully applied. In this study, we first conduct a thorough review of current algorithms that can solve integer least squares problems, and then we develop an alternative least square method based on an integer least squares estimation to obtain the integer approximation of the integer matrices. We discuss numerical applications for the approximation of randomly generated integer matrices as well as studies of association rule mining, cluster analysis, and pattern extraction. Our computed results suggest that our proposed method can calculate a more accurate solution for discrete datasets than other existing methods. Keywords Data mining · Matrix factorization · Integer least squares problem · Clustering · Association rule · Pattern extraction The first author's research was supported in part by the National Natural Science Foundation of China under grant 11101067 and the Fundamental Research Funds for the Central Universities. The second author's research was supported in part by the National Center for Theoretical Sciences of Taiwan and by the Ministry of Science and Technology of Taiwan under grants 104-2115-M-006-017-MY3 and 105-2634-E-002-001. The third author's research was supported in part by the Defense Advanced Research Projects Agency (DARPA) XDATA program grant FA8750-12-2-0309 and NSF grants CCF-0808863, IIS-1242304, and IIS-1231742. -
Matrices That Are Similar to Their Inverses
116 THE MATHEMATICAL GAZETTE Matrices that are similar to their inverses GRIGORE CÃLUGÃREANU 1. Introduction In a group G, an element which is conjugate with its inverse is called real, i.e. the element and its inverse belong to the same conjugacy class. An element is called an involution if it is of order 2. With these notions it is easy to formulate the following questions. 1) Which are the (finite) groups all of whose elements are real ? 2) Which are the (finite) groups such that the identity and involutions are the only real elements ? 3) Which are the (finite) groups in which the real elements form a subgroup closed under multiplication? According to specialists, these (general) questions cannot be solved in any reasonable way. For example, there are numerous families of groups all of whose elements are real, like the symmetric groups Sn. There are many solvable groups whose elements are all real, and one can prove that any finite solvable group occurs as a subgroup of a solvable group whose elements are all real. As for question 2, note that in any Abelian group (conjugations are all the identity function), the only real elements are the identity and the involutions, and they form a subgroup. There are non-abelian examples as well, like a Suzuki 2-group. Question 3 is similar to questions 1 and 2. Therefore the abstract study of reality questions in finite groups is unlikely to have a good outcome. This may explain why in the existing bibliography there are only specific studies (see [1, 2, 3, 4]). -
Alternating Sign Matrices, Extensions and Related Cones
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/311671190 Alternating sign matrices, extensions and related cones Article in Advances in Applied Mathematics · May 2017 DOI: 10.1016/j.aam.2016.12.001 CITATIONS READS 0 29 2 authors: Richard A. Brualdi Geir Dahl University of Wisconsin–Madison University of Oslo 252 PUBLICATIONS 3,815 CITATIONS 102 PUBLICATIONS 1,032 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: Combinatorial matrix theory; alternating sign matrices View project All content following this page was uploaded by Geir Dahl on 16 December 2016. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original document and are linked to publications on ResearchGate, letting you access and read them immediately. Alternating sign matrices, extensions and related cones Richard A. Brualdi∗ Geir Dahly December 1, 2016 Abstract An alternating sign matrix, or ASM, is a (0; ±1)-matrix where the nonzero entries in each row and column alternate in sign, and where each row and column sum is 1. We study the convex cone generated by ASMs of order n, called the ASM cone, as well as several related cones and polytopes. Some decomposition results are shown, and we find a minimal Hilbert basis of the ASM cone. The notion of (±1)-doubly stochastic matrices and a generalization of ASMs are introduced and various properties are shown. For instance, we give a new short proof of the linear characterization of the ASM polytope, in fact for a more general polytope. -
Centro-Invertible Matrices Linear Algebra and Its Applications, 434 (2011) Pp144-151
References • R.S. Wikramaratna, The centro-invertible matrix:a new type of matrix arising in pseudo-random number generation, Centro-invertible Matrices Linear Algebra and its Applications, 434 (2011) pp144-151. [doi:10.1016/j.laa.2010.08.011]. Roy S Wikramaratna, RPS Energy [email protected] • R.S. Wikramaratna, Theoretical and empirical convergence results for additive congruential random number generators, Reading University (Conference in honour of J. Comput. Appl. Math., 233 (2010) 2302-2311. Nancy Nichols' 70th birthday ) [doi: 10.1016/j.cam.2009.10.015]. 2-3 July 2012 Career Background Some definitions … • Worked at Institute of Hydrology, 1977-1984 • I is the k by k identity matrix – Groundwater modelling research and consultancy • J is the k by k matrix with ones on anti-diagonal and zeroes – P/t MSc at Reading 1980-82 (Numerical Solution of PDEs) elsewhere • Worked at Winfrith, Dorset since 1984 – Pre-multiplication by J turns a matrix ‘upside down’, reversing order of terms in each column – UKAEA (1984 – 1995), AEA Technology (1995 – 2002), ECL Technology (2002 – 2005) and RPS Energy (2005 onwards) – Post-multiplication by J reverses order of terms in each row – Oil reservoir engineering, porous medium flow simulation and 0 0 0 1 simulator development 0 0 1 0 – Consultancy to Oil Industry and to Government J = = ()j 0 1 0 0 pq • Personal research interests in development and application of numerical methods to solve engineering 1 0 0 0 j =1 if p + q = k +1 problems, and in mathematical and numerical analysis -
On the Construction of Lightweight Circulant Involutory MDS Matrices⋆
On the Construction of Lightweight Circulant Involutory MDS Matrices? Yongqiang Lia;b, Mingsheng Wanga a. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China b. Science and Technology on Communication Security Laboratory, Chengdu, China [email protected] [email protected] Abstract. In the present paper, we investigate the problem of con- structing MDS matrices with as few bit XOR operations as possible. The key contribution of the present paper is constructing MDS matrices with entries in the set of m × m non-singular matrices over F2 directly, and the linear transformations we used to construct MDS matrices are not assumed pairwise commutative. With this method, it is shown that circulant involutory MDS matrices, which have been proved do not exist over the finite field F2m , can be constructed by using non-commutative entries. Some constructions of 4 × 4 and 5 × 5 circulant involutory MDS matrices are given when m = 4; 8. To the best of our knowledge, it is the first time that circulant involutory MDS matrices have been constructed. Furthermore, some lower bounds on XORs that required to evaluate one row of circulant and Hadamard MDS matrices of order 4 are given when m = 4; 8. Some constructions achieving the bound are also given, which have fewer XORs than previous constructions. Keywords: MDS matrix, circulant involutory matrix, Hadamard ma- trix, lightweight 1 Introduction Linear diffusion layer is an important component of symmetric cryptography which provides internal dependency for symmetric cryptography algorithms. The performance of a diffusion layer is measured by branch number. -
Publications of Roger Horn
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Linear Algebra and its Applications 424 (2007) 3–7 www.elsevier.com/locate/laa Publications of Roger Horn 1. A heuristic asymptotic formula concerning the distribution of prime numbers (with P.T. Bateman), Math. Comp. 16 (1962), 363–367 (MR26#6139). 2. Primes represented by irreducible polynomials in one variable, Theory of Numbers (with P.T. Bateman), In: Proceedings of Symposia in Pure Mathematics, vol. VIII, American Mathematical Society, Providence, Rhode Island, 1965, pp. 119–132 (MR31#1234). 3. On boundary values of a Schlicht mapping, Proc. Amer. Math. Soc. 18 (1967) 782–787 (MR36#2792). 4. On infinitely divisible matrices, kernels, and functions, Z. Wahrscheinlichkeitstheorie verw. Gebiete 8 (1967) 219–230 (MR36#925). 5. The theory of infinitely divisible matrices and kernels, Trans. Amer. Math. Soc. 136 (1969) 269–286 (MR41#9327). 6. Infinitely divisible positive definite sequences, Trans. Amer. Math. Soc. 136 (1969) 287–303 (MR58#17681). 7. On a functional equation arising in probability (with R.D. Meredith), Amer. Math. Monthly 76 (1969) 802–804 (MR40#4622). 8. On the Wronskian test for independence, Amer. Math. Monthly 77 (1970) 65–66. 9. On certain power series and sequences, J. London Math. Soc. 2 (2) (1970) 160–162 (MR41#5629). 10. On moment sequences and renewal sequences, J. Math. Anal. Appl. 31 (1970) 130–135 (MR42#6541). 11. On Fenchel’s theorem, Amer. Math. Monthly 78 (1971) 380–381 (MR44#2142). 12. Schlicht mappings and infinitely divisible kernels, Pacific J. -
K-Theory of Furstenberg Transformation Group C ∗-Algebras
Canad. J. Math. Vol. 65 (6), 2013 pp. 1287–1319 http://dx.doi.org/10.4153/CJM-2013-022-x c Canadian Mathematical Society 2013 K-theory of Furstenberg Transformation Group C∗-algebras Kamran Reihani Abstract. This paper studies the K-theoretic invariants of the crossed product C∗-algebras associated n with an important family of homeomorphisms of the tori T called Furstenberg transformations. Using the Pimsner–Voiculescu theorem, we prove that given n, the K-groups of those crossed products whose corresponding n × n integer matrices are unipotent of maximal degree always have the same rank an. We show using the theory developed here that a claim made in the literature about the torsion subgroups of these K-groups is false. Using the representation theory of the simple Lie algebra sl(2; C), we show that, remarkably, an has a combinatorial significance. For example, every a2n+1 is just the number of ways that 0 can be represented as a sum of integers between −n and n (with no repetitions). By adapting an argument of van Lint (in which he answered a question of Erdos),˝ a simple explicit formula for the asymptotic behavior of the sequence fang is given. Finally, we describe the order structure of the K0-groups of an important class of Furstenberg crossed products, obtaining their complete Elliott invariant using classification results of H. Lin and N. C. Phillips. 1 Introduction Furstenberg transformations were introduced in [9] as the first examples of homeo- morphisms of the tori that under some necessary and sufficient conditions are mini- mal and uniquely ergodic. -
Equivalent Conditions for Singular and Nonsingular Matrices Let a Be an N × N Matrix
Equivalent Conditions for Singular and Nonsingular Matrices Let A be an n × n matrix. Any pair of statements in the same column are equivalent. A is singular (A−1 does not exist). A is nonsingular (A−1 exists). Rank(A) = n. Rank(A) = n. |A| = 0. |A| = 0. A is not row equivalent to In. A is row equivalent to In. AX = O has a nontrivial solution for X. AX = O has only the trivial solution for X. AX = B does not have a unique AX = B has a unique solution solution (no solutions or for X (namely, X = A−1B). infinitely many solutions). The rows of A do not form a The rows of A form a basis for Rn. basis for Rn. The columns of A do not form The columns of A form abasisforRn. abasisforRn. The linear operator L: Rn → Rn The linear operator L: Rn → Rn given by L(X) = AX is given by L(X) = AX not an isomorphism. is an isomorphism. Diagonalization Method To diagonalize (if possible) an n × n matrix A: Step 1: Calculate pA(x) = |xIn − A|. Step 2: Find all real roots of pA(x) (that is, all real solutions to pA(x) = 0). These are the eigenvalues λ1, λ2, λ3, ..., λk for A. Step 3: For each eigenvalue λm in turn: Row reduce the augmented matrix [λmIn − A | 0] . Use the result to obtain a set of particular solutions of the homogeneous system (λmIn − A)X = 0 by setting each independent variable in turn equal to 1 and all other independent variables equal to 0.