Combinatorics, Symmetric Functions, and Hilbert Schemes
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Isospectralization, Or How to Hear Shape, Style, and Correspondence
Isospectralization, or how to hear shape, style, and correspondence Luca Cosmo Mikhail Panine Arianna Rampini University of Venice Ecole´ Polytechnique Sapienza University of Rome [email protected] [email protected] [email protected] Maks Ovsjanikov Michael M. Bronstein Emanuele Rodola` Ecole´ Polytechnique Imperial College London / USI Sapienza University of Rome [email protected] [email protected] [email protected] Initialization Reconstruction Abstract opt. target The question whether one can recover the shape of a init. geometric object from its Laplacian spectrum (‘hear the shape of the drum’) is a classical problem in spectral ge- ometry with a broad range of implications and applica- tions. While theoretically the answer to this question is neg- ative (there exist examples of iso-spectral but non-isometric manifolds), little is known about the practical possibility of using the spectrum for shape reconstruction and opti- mization. In this paper, we introduce a numerical proce- dure called isospectralization, consisting of deforming one shape to make its Laplacian spectrum match that of an- other. We implement the isospectralization procedure using modern differentiable programming techniques and exem- plify its applications in some of the classical and notori- Without isospectralization With isospectralization ously hard problems in geometry processing, computer vi- sion, and graphics such as shape reconstruction, pose and Figure 1. Top row: Mickey-from-spectrum: we recover the shape of Mickey Mouse from its first 20 Laplacian eigenvalues (shown style transfer, and dense deformable correspondence. in red in the leftmost plot) by deforming an initial ellipsoid shape; the ground-truth target embedding is shown as a red outline on top of our reconstruction. -
Covariances of Symmetric Statistics
CORE Metadata, citation and similar papers at core.ac.uk Provided by Elsevier - Publisher Connector JOURNAL OF MULTIVARIATE ANALYSIS 41, 14-26 (1992) Covariances of Symmetric Statistics RICHARD A. VITALE Universily of Connecticut Communicared by C. R. Rao We examine the second-order structure arising when a symmetric function is evaluated over intersecting subsets of random variables. The original work of Hoeffding is updated with reference to later results. New representations and inequalities are presented for covariances and applied to U-statistics. 0 1992 Academic Press. Inc. 1. INTRODUCTION The importance of the symmetric use of sample observations was apparently first observed by Halmos [6] and, following the pioneering work of Hoeffding [7], has been reflected in the active study of U-statistics (e.g., Hoeffding [8], Rubin and Vitale [ 111, Dynkin and Mandelbaum [2], Mandelbaum and Taqqu [lo] and, for a lucid survey of the classical theory Serfling [12]). An important feature is the ANOVA-type expansion introduced by Hoeffding and its application to finite-sample inequalities, Efron and Stein [3], Karlin and Rinnott [9], Bhargava Cl], Takemura [ 143, Vitale [16], Steele [ 131). The purpose here is to survey work on this latter topic and to present new results. After some preliminaries, Section 3 organizes for comparison three approaches to the ANOVA-type expansion. The next section takes up characterizations and representations of covariances. These are then used to tighten an important inequality of Hoeffding and, in the last section, to study the structure of U-statistics. 2. NOTATION AND PRELIMINARIES The general setup is a supply X,, X,, . -
The Minimal Model Program for the Hilbert Scheme of Points on P2 and Bridgeland Stability
THE MINIMAL MODEL PROGRAM FOR THE HILBERT SCHEME OF POINTS ON P2 AND BRIDGELAND STABILITY DANIELE ARCARA, AARON BERTRAM, IZZET COSKUN, AND JACK HUIZENGA 2[n] 2 Abstract. In this paper, we study the birational geometry of the Hilbert scheme P of n-points on P . We discuss the stable base locus decomposition of the effective cone and the corresponding birational models. We give modular interpretations to the models in terms of moduli spaces of Bridgeland semi-stable objects. We construct these moduli spaces as moduli spaces of quiver representations using G.I.T. and thus show that they are projective. There is a precise correspondence between wall-crossings in the Bridgeland stability manifold and wall-crossings between Mori cones. For n ≤ 9, we explicitly determine the walls in both interpretations and describe the corresponding flips and divisorial contractions. Contents 1. Introduction 2 2. Preliminaries on the Hilbert scheme of points 4 2[n] 3. Effective divisors on P 5 2[n] 4. The stable base locus decomposition of the effective cone of P 8 5. Preliminaries on Bridgeland stability conditions 15 6. Potential walls 18 7. The quiver region 23 8. Moduli of stable objects are GIT quotients 26 9. Walls for the Hilbert scheme 27 10. Explicit Examples 30 2[2] 10.1. The walls for P 30 2[3] 10.2. The walls for P 31 2[4] 10.3. The walls for P 32 2[5] 10.4. The walls for P 33 2[6] 10.5. The walls for P 34 2[7] 10.6. -
Representation Theory
Representation Theory Andrew Kobin Fall 2014 Contents Contents Contents 1 Introduction 1 1.1 Group Theory Review . .1 1.2 Partitions . .2 2 Group Representations 4 2.1 Representations . .4 2.2 G-homomorphisms . .9 2.3 Schur's Lemma . 12 2.4 The Commutant and Endomorphism Algebras . 13 2.5 Characters . 17 2.6 Tensor Products . 24 2.7 Restricted and Induced Characters . 25 3 Representations of Sn 28 3.1 Young Subgroups of Sn .............................. 28 3.2 Specht Modules . 33 3.3 The Decomposition of M µ ............................ 44 3.4 The Hook Length Formula . 48 3.5 Application: The RSK Algorithm . 49 4 Symmetric Functions 52 4.1 Generating Functions . 52 4.2 Symmetric Functions . 53 4.3 Schur Functions . 57 4.4 Symmetric Functions and Character Representations . 60 i 1 Introduction 1 Introduction The following are notes from a course in representation theory taught by Dr. Frank Moore at Wake Forest University in the fall of 2014. The main topics covered are: group repre- sentations, characters, the representation theory of Sn, Young tableaux and tabloids, Specht modules, the RSK algorithm and some further applications to combinatorics. 1.1 Group Theory Review Definition. A group is a nonempty set G with a binary operation \·00 : G×G ! G satisfying (1) (Associativity) a(bc) = (ab)c for all a; b; c 2 G. (2) (Identity) There exists an identity element e 2 G such that for every a 2 G, ae = ea = a. (3) (Inverses) For every a 2 G there is some b 2 G such that ab = ba = e. -
The Lci Locus of the Hilbert Scheme of Points & the Cotangent Complex
The lci locus of the Hilbert scheme of points & the cotangent complex Peter J. Haine September 21, 2019 Abstract Weintroduce the basic algebraic geometry background necessary to understand the main results of the work of Elmanto, Hoyois, Khan, Sosnilo, and Yakerson on motivic infinite loop spaces [5]. After recalling some facts about the Hilbert func- tor of points, we introduce local complete intersection (lci) and syntomic morphisms. We then give an overview of the cotangent complex and discuss the relationship be- tween lci morphisms and the cotangent complex (in particular, Avramov’s charac- terization of lci morphisms). We then introduce the lci locus of the Hilbert scheme of points and the Hilbert scheme of framed points, and prove that the lci locus of the Hilbert scheme of points is formally smooth. Contents 1 Hilbert schemes 2 2 Local complete intersections via equations 3 Relative global complete intersections ...................... 3 Local complete intersections ........................... 4 3 Background on the cotangent complex 6 Motivation .................................... 6 Properties of the cotangent complex ....................... 7 4 Local complete intersections and the cotangent complex 9 Avramov’s characterization of local complete intersections ........... 11 5 The lci locus of the Hilbert scheme of points 13 6 The Hilbert scheme of framed points 14 1 1 Hilbert schemes In this section we recall the Hilbert functor of points from last time as well as state the basic representability properties of the Hilbert functor of points. 1.1 Recollection ([STK, Tag 02K9]). A morphism of schemes 푓∶ 푌 → 푋 is finite lo- cally free if 푓 is affine and 푓⋆풪푌 is a finite locally free 풪푋-module. -
Generating Functions from Symmetric Functions Anthony Mendes And
Generating functions from symmetric functions Anthony Mendes and Jeffrey Remmel Abstract. This monograph introduces a method of finding and refining gen- erating functions. By manipulating combinatorial objects known as brick tabloids, we will show how many well known generating functions may be found and subsequently generalized. New results are given as well. The techniques described in this monograph originate from a thorough understanding of a connection between symmetric functions and the permu- tation enumeration of the symmetric group. Define a homomorphism ξ on the ring of symmetric functions by defining it on the elementary symmetric n−1 function en such that ξ(en) = (1 − x) /n!. Brenti showed that applying ξ to the homogeneous symmetric function gave a generating function for the Eulerian polynomials [14, 13]. Beck and Remmel reproved the results of Brenti combinatorially [6]. A handful of authors have tinkered with their proof to discover results about the permutation enumeration for signed permutations and multiples of permuta- tions [4, 5, 51, 52, 53, 58, 70, 71]. However, this monograph records the true power and adaptability of this relationship between symmetric functions and permutation enumeration. We will give versatile methods unifying a large number of results in the theory of permutation enumeration for the symmet- ric group, subsets of the symmetric group, and assorted Coxeter groups, and many other objects. Contents Chapter 1. Brick tabloids in permutation enumeration 1 1.1. The ring of formal power series 1 1.2. The ring of symmetric functions 7 1.3. Brenti’s homomorphism 21 1.4. Published uses of brick tabloids in permutation enumeration 30 1.5. -
Math 263A Notes: Algebraic Combinatorics and Symmetric Functions
MATH 263A NOTES: ALGEBRAIC COMBINATORICS AND SYMMETRIC FUNCTIONS AARON LANDESMAN CONTENTS 1. Introduction 4 2. 10/26/16 5 2.1. Logistics 5 2.2. Overview 5 2.3. Down to Math 5 2.4. Partitions 6 2.5. Partial Orders 7 2.6. Monomial Symmetric Functions 7 2.7. Elementary symmetric functions 8 2.8. Course Outline 8 3. 9/28/16 9 3.1. Elementary symmetric functions eλ 9 3.2. Homogeneous symmetric functions, hλ 10 3.3. Power sums pλ 12 4. 9/30/16 14 5. 10/3/16 20 5.1. Expected Number of Fixed Points 20 5.2. Random Matrix Groups 22 5.3. Schur Functions 23 6. 10/5/16 24 6.1. Review 24 6.2. Schur Basis 24 6.3. Hall Inner product 27 7. 10/7/16 29 7.1. Basic properties of the Cauchy product 29 7.2. Discussion of the Cauchy product and related formulas 30 8. 10/10/16 32 8.1. Finishing up last class 32 8.2. Skew-Schur Functions 33 8.3. Jacobi-Trudi 36 9. 10/12/16 37 1 2 AARON LANDESMAN 9.1. Eigenvalues of unitary matrices 37 9.2. Application 39 9.3. Strong Szego limit theorem 40 10. 10/14/16 41 10.1. Background on Tableau 43 10.2. KOSKA Numbers 44 11. 10/17/16 45 11.1. Relations of skew-Schur functions to other fields 45 11.2. Characters of the symmetric group 46 12. 10/19/16 49 13. 10/21/16 55 13.1. -
Isospectral Towers of Riemannian Manifolds
New York Journal of Mathematics New York J. Math. 18 (2012) 451{461. Isospectral towers of Riemannian manifolds Benjamin Linowitz Abstract. In this paper we construct, for n ≥ 2, arbitrarily large fam- ilies of infinite towers of compact, orientable Riemannian n-manifolds which are isospectral but not isometric at each stage. In dimensions two and three, the towers produced consist of hyperbolic 2-manifolds and hyperbolic 3-manifolds, and in these cases we show that the isospectral towers do not arise from Sunada's method. Contents 1. Introduction 451 2. Genera of quaternion orders 453 3. Arithmetic groups derived from quaternion algebras 454 4. Isospectral towers and chains of quaternion orders 454 5. Proof of Theorem 4.1 456 5.1. Orders in split quaternion algebras over local fields 456 5.2. Proof of Theorem 4.1 457 6. The Sunada construction 458 References 461 1. Introduction Let M be a closed Riemannian n-manifold. The eigenvalues of the La- place{Beltrami operator acting on the space L2(M) form a discrete sequence of nonnegative real numbers in which each value occurs with a finite mul- tiplicity. This collection of eigenvalues is called the spectrum of M, and two Riemannian n-manifolds are said to be isospectral if their spectra coin- cide. Inverse spectral geometry asks the extent to which the geometry and topology of M is determined by its spectrum. Whereas volume and scalar curvature are spectral invariants, the isometry class is not. Although there is a long history of constructing Riemannian manifolds which are isospectral but not isometric, we restrict our discussion to those constructions most Received February 4, 2012. -
Further Pathologies in Algebraic Geometry Author(S): David Mumford Source: American Journal of Mathematics , Oct., 1962, Vol
Further Pathologies in Algebraic Geometry Author(s): David Mumford Source: American Journal of Mathematics , Oct., 1962, Vol. 84, No. 4 (Oct., 1962), pp. 642-648 Published by: The Johns Hopkins University Press Stable URL: http://www.jstor.com/stable/2372870 JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at https://about.jstor.org/terms The Johns Hopkins University Press is collaborating with JSTOR to digitize, preserve and extend access to American Journal of Mathematics This content downloaded from 132.174.252.179 on Sat, 01 Aug 2020 11:36:26 UTC All use subject to https://about.jstor.org/terms FURTHER PATHOLOGIES IN ALGEBRAIC GEOMETRY.*1 By DAVID MUMFORD. The following note is not strictly a continuation of our previous note [1]. However, we wish to present two more examples of algebro-geometric phe- nomnena which seem to us rather startling. The first relates to characteristic ]) behaviour, and the second relates to the hypothesis of the completeness of the characteristic linear system of a maximal algebraic family. We will use the same notations as in [1]. The first example is an illustration of a general principle that might be said to be indicated by many of the pathologies of characteristic p: A non-singular characteristic p variety is analogous to a general non- K:ahler complex manifold; in particular, a projective embedding of such a variety is not as "strong" as a Kiihler metric on a complex manifold; and the Hodge-Lefschetz-Dolbeault theorems on sheaf cohomology break down in every possible way. -
Some New Symmetric Function Tools and Their Applications
Some New Symmetric Function Tools and their Applications A. Garsia ∗Department of Mathematics University of California, La Jolla, CA 92093 [email protected] J. Haglund †Department of Mathematics University of Pennsylvania, Philadelphia, PA 19104-6395 [email protected] M. Romero ‡Department of Mathematics University of California, La Jolla, CA 92093 [email protected] June 30, 2018 MR Subject Classifications: Primary: 05A15; Secondary: 05E05, 05A19 Keywords: Symmetric functions, modified Macdonald polynomials, Nabla operator, Delta operators, Frobenius characteristics, Sn modules, Narayana numbers Abstract Symmetric Function Theory is a powerful computational device with applications to several branches of mathematics. The Frobenius map and its extensions provides a bridge translating Representation Theory problems to Symmetric Function problems and ultimately to combinatorial problems. Our main contributions here are certain new symmetric func- tion tools for proving a variety of identities, some of which have already had significant applications. One of the areas which has been nearly untouched by present research is the construction of bigraded Sn modules whose Frobenius characteristics has been conjectured from both sides. The flagrant example being the Delta Conjecture whose symmetric function side was conjectured to be Schur positive since the early 90’s and there are various unproved recent ways to construct the combinatorial side. One of the most surprising applications of our tools reveals that the only conjectured bigraded Sn modules are remarkably nested by Sn the restriction ↓Sn−1 . 1 Introduction Frobenius constructed a map Fn from class functions of Sn to degree n homogeneous symmetric poly- λ nomials and proved the identity Fnχ = sλ[X], for all λ ⊢ n. -
Geometry of Matrix Decompositions Seen Through Optimal Transport and Information Geometry
Published in: Journal of Geometric Mechanics doi:10.3934/jgm.2017014 Volume 9, Number 3, September 2017 pp. 335{390 GEOMETRY OF MATRIX DECOMPOSITIONS SEEN THROUGH OPTIMAL TRANSPORT AND INFORMATION GEOMETRY Klas Modin∗ Department of Mathematical Sciences Chalmers University of Technology and University of Gothenburg SE-412 96 Gothenburg, Sweden Abstract. The space of probability densities is an infinite-dimensional Rie- mannian manifold, with Riemannian metrics in two flavors: Wasserstein and Fisher{Rao. The former is pivotal in optimal mass transport (OMT), whereas the latter occurs in information geometry|the differential geometric approach to statistics. The Riemannian structures restrict to the submanifold of multi- variate Gaussian distributions, where they induce Riemannian metrics on the space of covariance matrices. Here we give a systematic description of classical matrix decompositions (or factorizations) in terms of Riemannian geometry and compatible principal bundle structures. Both Wasserstein and Fisher{Rao geometries are discussed. The link to matrices is obtained by considering OMT and information ge- ometry in the category of linear transformations and multivariate Gaussian distributions. This way, OMT is directly related to the polar decomposition of matrices, whereas information geometry is directly related to the QR, Cholesky, spectral, and singular value decompositions. We also give a coherent descrip- tion of gradient flow equations for the various decompositions; most flows are illustrated in numerical examples. The paper is a combination of previously known and original results. As a survey it covers the Riemannian geometry of OMT and polar decomposi- tions (smooth and linear category), entropy gradient flows, and the Fisher{Rao metric and its geodesics on the statistical manifold of multivariate Gaussian distributions. -
Class Notes, Functional Analysis 7212
Class notes, Functional Analysis 7212 Ovidiu Costin Contents 1 Banach Algebras 2 1.1 The exponential map.....................................5 1.2 The index group of B = C(X) ...............................6 1.2.1 p1(X) .........................................7 1.3 Multiplicative functionals..................................7 1.3.1 Multiplicative functionals on C(X) .........................8 1.4 Spectrum of an element relative to a Banach algebra.................. 10 1.5 Examples............................................ 19 1.5.1 Trigonometric polynomials............................. 19 1.6 The Shilov boundary theorem................................ 21 1.7 Further examples....................................... 21 1.7.1 The convolution algebra `1(Z) ........................... 21 1.7.2 The return of Real Analysis: the case of L¥ ................... 23 2 Bounded operators on Hilbert spaces 24 2.1 Adjoints............................................ 24 2.2 Example: a space of “diagonal” operators......................... 30 2.3 The shift operator on `2(Z) ................................. 32 2.3.1 Example: the shift operators on H = `2(N) ................... 38 3 W∗-algebras and measurable functional calculus 41 3.1 The strong and weak topologies of operators....................... 42 4 Spectral theorems 46 4.1 Integration of normal operators............................... 51 4.2 Spectral projections...................................... 51 5 Bounded and unbounded operators 54 5.1 Operations..........................................