13 research outputs found
Supersymmetric Gauge Theories with Matters, Toric Geometries and Random Partitions
We derive the relation between the Hilbert space of certain geometries under
the Bohr-Sommerfeld quantization and the perturbative prepotentials for the
supersymmetric five-dimensional SU(N) gauge theories with massive fundamental
matters and with one massive adjoint matter. The gauge theory with one adjoint
matter shows interesting features. A five-dimensional generalization of
Nekrasov's partition function can be written as a correlation function of
two-dimensional chiral bosons and as a partition function of a statistical
model of partitions. From a ground state of the statistical model we reproduce
the polyhedron which characterizes the Hilbert space.Comment: 26 pages, 11 figures; v2 typos correcte
Hyperplane Arrangements and Locality-Sensitive Hashing with Lift
Locality-sensitive hashing converts high-dimensional feature vectors, such as
image and speech, into bit arrays and allows high-speed similarity calculation
with the Hamming distance. There is a hashing scheme that maps feature vectors
to bit arrays depending on the signs of the inner products between feature
vectors and the normal vectors of hyperplanes placed in the feature space. This
hashing can be seen as a discretization of the feature space by hyperplanes. If
labels for data are given, one can determine the hyperplanes by using learning
algorithms. However, many proposed learning methods do not consider the
hyperplanes' offsets. Not doing so decreases the number of partitioned regions,
and the correlation between Hamming distances and Euclidean distances becomes
small. In this paper, we propose a lift map that converts learning algorithms
without the offsets to the ones that take into account the offsets. With this
method, the learning methods without the offsets give the discretizations of
spaces as if it takes into account the offsets. For the proposed method, we
input several high-dimensional feature data sets and studied the relationship
between the statistical characteristics of data, the number of hyperplanes, and
the effect of the proposed method.Comment: 9 pages, 7 figure
Locality-Sensitive Hashing with Margin Based Feature Selection
We propose a learning method with feature selection for Locality-Sensitive
Hashing. Locality-Sensitive Hashing converts feature vectors into bit arrays.
These bit arrays can be used to perform similarity searches and personal
authentication. The proposed method uses bit arrays longer than those used in
the end for similarity and other searches and by learning selects the bits that
will be used. We demonstrated this method can effectively perform optimization
for cases such as fingerprint images with a large number of labels and
extremely few data that share the same labels, as well as verifying that it is
also effective for natural images, handwritten digits, and speech features.Comment: 9 pages, 6 figures, 3 table
Integrable Structure of Supersymmetric Yang-Mills and Melting Crystal
We study loop operators of SYM in background.
For the case of U(1) theory, the generating function of correlation functions
of the loop operators reproduces the partition function of melting crystal
model with external potential. We argue the common integrable structure of
SYM and melting crystal model.Comment: 12 pages, 1 figure, based on an invited talk presented at the
international workshop "Progress of String Theory and Quantum Field Theory"
(Osaka City University, December 7-10, 2007), to be published in the
proceeding
Gravitational Quantum Foam and Supersymmetric Gauge Theories
We study K\"{a}hler gravity on local SU(N) geometry and describe precise
correspondence with certain supersymmetric gauge theories and random plane
partitions. The local geometry is discretized, via the geometric quantization,
to a foam of an infinite number of gravitational quanta. We count these quanta
in a relative manner by measuring a deviation of the local geometry from a
singular Calabi-Yau threefold, that is a A_{N-1} singularity fibred over
\mathbb{P}^1. With such a regularization prescription, the number of the
gravitational quanta becomes finite and turns to be the perturbative
prepotential for five-dimensional \mathcal{N}=1 supersymmetric SU(N)
Yang-Mills. These quanta are labelled by lattice points in a certain convex
polyhedron on \mathbb{R}^3. The polyhedron becomes obtainable from a plane
partition which is the ground state of a statistical model of random plane
partition that describes the exact partition function for the gauge theory.
Each gravitational quantum of the local geometry is shown to consist of N unit
cubes of plane partitions.Comment: 43 pages, 12 figures: V2 typos correcte