25,894 research outputs found
Matrices coupled in a chain. I. Eigenvalue correlations
The general correlation function for the eigenvalues of complex hermitian
matrices coupled in a chain is given as a single determinant. For this we use a
slight generalization of a theorem of Dyson.Comment: ftex eynmeh.tex, 2 files, 8 pages Submitted to: J. Phys.
Calculation of some determinants using the s-shifted factorial
Several determinants with gamma functions as elements are evaluated. This
kind of determinants are encountered in the computation of the probability
density of the determinant of random matrices. The s-shifted factorial is
defined as a generalization for non-negative integers of the power function,
the rising factorial (or Pochammer's symbol) and the falling factorial. It is a
special case of polynomial sequence of the binomial type studied in
combinatorics theory. In terms of the gamma function, an extension is defined
for negative integers and even complex values. Properties, mainly composition
laws and binomial formulae, are given. They are used to evaluate families of
generalized Vandermonde determinants with s-shifted factorials as elements,
instead of power functions.Comment: 25 pages; added section 5 for some examples of application
Finite-difference distributions for the Ginibre ensemble
The Ginibre ensemble of complex random matrices is studied. The complex
valued random variable of second difference of complex energy levels is
defined. For the N=3 dimensional ensemble are calculated distributions of
second difference, of real and imaginary parts of second difference, as well as
of its radius and of its argument (angle). For the generic N-dimensional
Ginibre ensemble an exact analytical formula for second difference's
distribution is derived. The comparison with real valued random variable of
second difference of adjacent real valued energy levels for Gaussian
orthogonal, unitary, and symplectic, ensemble of random matrices as well as for
Poisson ensemble is provided.Comment: 8 pages, a number of small changes in the tex
Random matrix ensembles associated with Lax matrices
A method to generate new classes of random matrix ensembles is proposed.
Random matrices from these ensembles are Lax matrices of classically integrable
systems with a certain distribution of momenta and coordinates. The existence
of an integrable structure permits to calculate the joint distribution of
eigenvalues for these matrices analytically. Spectral statistics of these
ensembles are quite unusual and in many cases give rigorously new examples of
intermediate statistics
Competition and cooperation:aspects of dynamics in sandpiles
In this article, we review some of our approaches to granular dynamics, now
well known to consist of both fast and slow relaxational processes. In the
first case, grains typically compete with each other, while in the second, they
cooperate. A typical result of {\it cooperation} is the formation of stable
bridges, signatures of spatiotemporal inhomogeneities; we review their
geometrical characteristics and compare theoretical results with those of
independent simulations. {\it Cooperative} excitations due to local density
fluctuations are also responsible for relaxation at the angle of repose; the
{\it competition} between these fluctuations and external driving forces, can,
on the other hand, result in a (rare) collapse of the sandpile to the
horizontal. Both these features are present in a theory reviewed here. An arena
where the effects of cooperation versus competition are felt most keenly is
granular compaction; we review here a random graph model, where three-spin
interactions are used to model compaction under tapping. The compaction curve
shows distinct regions where 'fast' and 'slow' dynamics apply, separated by
what we have called the {\it single-particle relaxation threshold}. In the
final section of this paper, we explore the effect of shape -- jagged vs.
regular -- on the compaction of packings near their jamming limit. One of our
major results is an entropic landscape that, while microscopically rough,
manifests {\it Edwards' flatness} at a macroscopic level. Another major result
is that of surface intermittency under low-intensity shaking.Comment: 36 pages, 23 figures, minor correction
Generalization of the Poisson kernel to the superconducting random-matrix ensembles
We calculate the distribution of the scattering matrix at the Fermi level for
chaotic normal-superconducting systems for the case of arbitrary coupling of
the scattering region to the scattering channels. The derivation is based on
the assumption of uniformly distributed scattering matrices at ideal coupling,
which holds in the absence of a gap in the quasiparticle excitation spectrum.
The resulting distribution generalizes the Poisson kernel to the nonstandard
symmetry classes introduced by Altland and Zirnbauer. We show that unlike the
Poisson kernel, our result cannot be obtained by combining the maximum entropy
principle with the analyticity-ergodicity constraint. As a simple application,
we calculate the distribution of the conductance for a single-channel chaotic
Andreev quantum dot in a magnetic field.Comment: 7 pages, 2 figure
Minimizing Higgs Potentials via Numerical Polynomial Homotopy Continuation
The study of models with extended Higgs sectors requires to minimize the
corresponding Higgs potentials, which is in general very difficult. Here, we
apply a recently developed method, called numerical polynomial homotopy
continuation (NPHC), which guarantees to find all the stationary points of the
Higgs potentials with polynomial-like nonlinearity. The detection of all
stationary points reveals the structure of the potential with maxima,
metastable minima, saddle points besides the global minimum. We apply the NPHC
method to the most general Higgs potential having two complex Higgs-boson
doublets and up to five real Higgs-boson singlets. Moreover the method is
applicable to even more involved potentials. Hence the NPHC method allows to go
far beyond the limits of the Gr\"obner basis approach.Comment: 9 pages, 4 figure
Generalized Mixability via Entropic Duality
Mixability is a property of a loss which characterizes when fast convergence
is possible in the game of prediction with expert advice. We show that a key
property of mixability generalizes, and the exp and log operations present in
the usual theory are not as special as one might have thought. In doing this we
introduce a more general notion of -mixability where is a general
entropy (\ie, any convex function on probabilities). We show how a property
shared by the convex dual of any such entropy yields a natural algorithm (the
minimizer of a regret bound) which, analogous to the classical aggregating
algorithm, is guaranteed a constant regret when used with -mixable
losses. We characterize precisely which have -mixable losses and
put forward a number of conjectures about the optimality and relationships
between different choices of entropy.Comment: 20 pages, 1 figure. Supersedes the work in arXiv:1403.2433 [cs.LG
Two photon annihilation operators and squeezed vacuum
Inverses of the harmonic oscillator creation and annihilation operators by their actions on the number states are introduced. Three of the two photon annihilation operators, viz., a(sup +/-1)a, aa(sup +/-1), and a(sup 2), have normalizable right eigenstates with nonvanishing eigenvalues. The eigenvalue equation of these operators are discussed and their normalized eigenstates are obtained. The Fock state representation in each case separates into two sets of states, one involving only the even number states while the other involving only the odd number states. It is shown that the even set of eigenstates of the operator a(sup +/-1)a is the customary squeezed vacuum S(sigma) O greater than
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