3,117 research outputs found
Coherent State Quantization of Constraint Systems
A careful reexamination of the quantization of systems with first- and
second-class constraints from the point of view of coherent-state phase-space
path integration reveals several significant distinctions from more
conventional treatments. Most significantly, we emphasize the importance of
using path-integral measures for Lagrange multipliers which ensure that the
quantum system satisfies the quantum constraint conditions. Our procedures
involve no delta-functionals of the classical constraints, no need for gauge
fixing of first-class constraints, no need to eliminate second-class
constraints, no potentially ambiguous determinants, and have the virtue of
resolving differences between canonical and path-integral approaches. Several
examples are considered in detail.Comment: Latex, 38 pages, no figure
Noncanonical quantization of gravity. II. Constraints and the physical Hilbert space
The program of quantizing the gravitational field with the help of affine
field variables is continued. For completeness, a review of the selection
criteria that singles out the affine fields, the alternative treatment of
constraints, and the choice of the initial (before imposition of the
constraints) ultralocal representation of the field operators is initially
presented. As analogous examples demonstrate, the introduction and enforcement
of the gravitational constraints will cause sufficient changes in the operator
representations so that all vestiges of the initial ultralocal field operator
representation disappear. To achieve this introduction and enforcement of the
constraints, a well characterized phase space functional integral
representation for the reproducing kernel of a suitably regularized physical
Hilbert space is developed and extensively analyzed.Comment: LaTeX, 42 pages, no figure
Noncanonical Quantization of Gravity. I. Foundations of Affine Quantum Gravity
The nature of the classical canonical phase-space variables for gravity
suggests that the associated quantum field operators should obey affine
commutation relations rather than canonical commutation relations. Prior to the
introduction of constraints, a primary kinematical representation is derived in
the form of a reproducing kernel and its associated reproducing kernel Hilbert
space. Constraints are introduced following the projection operator method
which involves no gauge fixing, no complicated moduli space, nor any auxiliary
fields. The result, which is only qualitatively sketched in the present paper,
involves another reproducing kernel with which inner products are defined for
the physical Hilbert space and which is obtained through a reduction of the
original reproducing kernel. Several of the steps involved in this general
analysis are illustrated by means of analogous steps applied to one-dimensional
quantum mechanical models. These toy models help in motivating and
understanding the analysis in the case of gravity.Comment: minor changes, LaTeX, 37 pages, no figure
A multi-level algorithm for the solution of moment problems
We study numerical methods for the solution of general linear moment
problems, where the solution belongs to a family of nested subspaces of a
Hilbert space. Multi-level algorithms, based on the conjugate gradient method
and the Landweber--Richardson method are proposed that determine the "optimal"
reconstruction level a posteriori from quantities that arise during the
numerical calculations. As an important example we discuss the reconstruction
of band-limited signals from irregularly spaced noisy samples, when the actual
bandwidth of the signal is not available. Numerical examples show the
usefulness of the proposed algorithms
Indirect Image Registration with Large Diffeomorphic Deformations
The paper adapts the large deformation diffeomorphic metric mapping framework
for image registration to the indirect setting where a template is registered
against a target that is given through indirect noisy observations. The
registration uses diffeomorphisms that transform the template through a (group)
action. These diffeomorphisms are generated by solving a flow equation that is
defined by a velocity field with certain regularity. The theoretical analysis
includes a proof that indirect image registration has solutions (existence)
that are stable and that converge as the data error tends so zero, so it
becomes a well-defined regularization method. The paper concludes with examples
of indirect image registration in 2D tomography with very sparse and/or highly
noisy data.Comment: 43 pages, 4 figures, 1 table; revise
Consistent Multitask Learning with Nonlinear Output Relations
Key to multitask learning is exploiting relationships between different tasks
to improve prediction performance. If the relations are linear, regularization
approaches can be used successfully. However, in practice assuming the tasks to
be linearly related might be restrictive, and allowing for nonlinear structures
is a challenge. In this paper, we tackle this issue by casting the problem
within the framework of structured prediction. Our main contribution is a novel
algorithm for learning multiple tasks which are related by a system of
nonlinear equations that their joint outputs need to satisfy. We show that the
algorithm is consistent and can be efficiently implemented. Experimental
results show the potential of the proposed method.Comment: 25 pages, 1 figure, 2 table
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