The Quantum Geometry of Spin and Statistics

Both, spin and statistics of a quantum system can be seen to arise from underlying (quantum) group symmetries. We show that the spin-statistics theorem is equivalent to a unification of these symmetries. Besides covering the Bose-Fermi case we classify the corresponding possibilities for anyonic spin and statistics. We incorporate the underlying extended concept of symmetry into quantum field theory in a generalised path integral formulation capable of handling general braid statistics. For bosons and fermions the different path integrals and Feynman rules naturally emerge without introducing Grassmann variables. We also consider the anyonic example of quons and obtain the path integral counterpart to the usual canonical approach.Comment: 23 pages, LaTeX with AMS and XY-Pic macros, minor corrections and references adde

A bilinear form relating two Leonard systems

Let $\Phi$, $\Phi'$ be Leonard systems over a field $\mathbb{K}$, and $V$, $V'$ the vector spaces underlying $\Phi$, $\Phi'$, respectively. In this paper, we introduce and discuss a balanced bilinear form on $V\times V'$. Such a form naturally arises in the study of $Q$-polynomial distance-regular graphs. We characterize a balanced bilinear form from several points of view.Comment: 15 page

Signal reconstruction from the magnitude of subspace components

We consider signal reconstruction from the norms of subspace components generalizing standard phase retrieval problems. In the deterministic setting, a closed reconstruction formula is derived when the subspaces satisfy certain cubature conditions, that require at least a quadratic number of subspaces. Moreover, we address reconstruction under the erasure of a subset of the norms; using the concepts of $p$-fusion frames and list decoding, we propose an algorithm that outputs a finite list of candidate signals, one of which is the correct one. In the random setting, we show that a set of subspaces chosen at random and of cardinality scaling linearly in the ambient dimension allows for exact reconstruction with high probability by solving the feasibility problem of a semidefinite program

Quantum Information Approaches to Holographic Dualities

The AdS/CFT correspondence, a remarkable duality between certain gravitational theories in anti-de Sitter (AdS) spacetime and quantum field theories with conformal symmetry (CFT), has had a profound effect on the development of theoretical physics in the past two decades. Recently, many connections of AdS/CFT to quantum information theory have been found, in particular by providing gravitationally dual descriptions of various entanglement measures. Understanding these manifestions of AdS/CFT --- or more generally, the conjectured holographic principle encompassing it --- requires the combination of tools from both high-energy theory and quantum information physics. In this cumulative thesis, the convergence between these two fields is approached from two fronts: First, by calculations within the dual gravitational theory, and second, using a tensor network ansatz to describe the quantum states suspected to possess such a gravitational description. In the first approach, using the gravitational side of AdS/CFT, entanglement entropies of complicated 2+1-dimensional excited CFTs are computed, thus showing how the holographic approach provides access to systems previously out of reach of practical methods, while introducing new numerical methods that this approach necessitates. The second approach is given by tensor networks, a highly successful ansatz for computing properties of one- and two-dimensional quantum systems. Efficiently computable classes of tensor networks are tested in their ability to represent simple holographic systems, successfully reproducing both hyperbolic geometrical features as well as critical boundary states. In addition, the general properties of tensor networks on regular hyperbolic tesselations are considered, leading to new connections to models not previously considered in the context of holography. This interplay of different approaches to quantum information holography showcases the richness of this new field and suggests that a wide range of physical phenomena is accessible via the new tools now at our disposal

Non-Rigid Structure from Motion

This thesis revisits a challenging classical problem in geometric computer vision known as "Non-Rigid Structure-from-Motion" (NRSfM). It is a well-known problem where the task is to recover the 3D shape and motion of a non-rigidly moving object from image data. A reliable solution to this problem is valuable in several industrial applications such as virtual reality, medical surgery, animation movies etc. Nevertheless, to date, there does not exist any algorithm that can solve NRSfM for all kinds of conceivable motion. As a result, additional constraints and assumptions are often employed to solve NRSfM. The task is challenging due to the inherent unconstrained nature of the problem itself as many 3D varying configurations can have similar image projections. The problem becomes even more challenging if the camera is moving along with the object. The thesis takes on a modern view to this challenging problem and proposes a few algorithms that have set a new performance benchmark to solve NRSfM. The thesis not only discusses the classical work in NRSfM but also proposes some powerful elementary modification to it. The foundation of this thesis surpass the traditional single object NRSFM and for the first time provides an effective formulation to realise multi-body NRSfM. Most techniques for NRSfM under factorisation can only handle sparse feature correspondences. These sparse features are then used to construct a scene using the organisation of points, lines, planes or other elementary geometric primitive. Nevertheless, sparse representation of the scene provides an incomplete information about the scene. This thesis goes from sparse NRSfM to dense NRSfM for a single object, and then slowly lifts the intuition to realise dense 3D reconstruction of the entire dynamic scene as a global as rigid as possible deformation problem. The core of this work goes beyond the traditional approach to deal with deformation. It shows that relative scales for multiple deforming objects can be recovered under some mild assumption about the scene. The work proposes a new approach for dense detailed 3D reconstruction of a complex dynamic scene from two perspective frames. Since the method does not need any depth information nor it assumes a template prior, or per-object segmentation, or knowledge about the rigidity of the dynamic scene, it is applicable to a wide range of scenarios including YouTube Videos. Lastly, this thesis provides a new way to perceive the depth of a dynamic scene which essentially trivialises the notion of motion estimation as a compulsory step to solve this problem. Conventional geometric methods to address depth estimation requires a reliable estimate of motion parameters for each moving object, which is difficult to obtain and validate. In contrast, this thesis introduces a new motion-free approach to estimate the dense depth map of a complex dynamic scene for successive/multiple frames. The work show that given per-pixel optical flow correspondences between two consecutive frames and the sparse depth prior for the reference frame, we can recover the dense depth map for the successive frames without solving for motion parameters. By assigning the locally rigid structure to the piece-wise planar approximation of a dynamic scene which transforms as rigid as possible over frames, we can bypass the motion estimation step. Experiments results and MATLAB codes on relevant examples are provided to validate the motion-free idea

Total positivity for cominuscule Grassmannians

In this paper we explore the combinatorics of the non-negative part (G/P)+ of a cominuscule Grassmannian. For each such Grassmannian we define Le-diagrams -- certain fillings of generalized Young diagrams which are in bijection with the cells of (G/P)+. In the classical cases, we describe Le-diagrams explicitly in terms of pattern avoidance. We also define a game on diagrams, by which one can reduce an arbitrary diagram to a Le-diagram. We give enumerative results and relate our Le-diagrams to other combinatorial objects. Surprisingly, the totally non-negative cells in the open Schubert cell of the odd and even orthogonal Grassmannians are (essentially) in bijection with preference functions and atomic preference functions respectively.Comment: 39 page