16,825 research outputs found
Central limit theorem for fluctuations of linear eigenvalue statistics of large random graphs
We consider the adjacency matrix of a large random graph and study
fluctuations of the function
with .
We prove that the moments of fluctuations normalized by in the limit
satisfy the Wick relations for the Gaussian random variables. This
allows us to prove central limit theorem for and then extend
the result on the linear eigenvalue statistics of any
function which increases, together with its
first two derivatives, at infinity not faster than an exponential.Comment: 22 page
Eigenvalue Spacing Distribution for the Ensemble of Real Symmetric Toeplitz Matrices
Consider the ensemble of Real Symmetric Toeplitz Matrices, each entry iidrv
from a fixed probability distribution p of mean 0, variance 1, and finite
higher moments. The limiting spectral measure (the density of normalized
eigenvalues) converges weakly to a new universal distribution with unbounded
support, independent of p. This distribution's moments are almost those of the
Gaussian's; the deficit may be interpreted in terms of Diophantine
obstructions. With a little more work, we obtain almost sure convergence. An
investigation of spacings between adjacent normalized eigenvalues looks
Poissonian, and not GOE.Comment: 24 pages, 3 figure
Eigenvalue variance bounds for Wigner and covariance random matrices
This work is concerned with finite range bounds on the variance of individual
eigenvalues of Wigner random matrices, in the bulk and at the edge of the
spectrum, as well as for some intermediate eigenvalues. Relying on the GUE
example, which needs to be investigated first, the main bounds are extended to
families of Hermitian Wigner matrices by means of the Tao and Vu Four Moment
Theorem and recent localization results by Erd\"os, Yau and Yin. The case of
real Wigner matrices is obtained from interlacing formulas. As an application,
bounds on the expected 2-Wasserstein distance between the empirical spectral
measure and the semicircle law are derived. Similar results are available for
random covariance matrices
Spectrum of the Product of Independent Random Gaussian Matrices
We show that the eigenvalue density of a product X=X_1 X_2 ... X_M of M
independent NxN Gaussian random matrices in the large-N limit is rotationally
symmetric in the complex plane and is given by a simple expression
rho(z,\bar{z}) = 1/(M\pi\sigma^2} |z|^{-2+2/M} for |z|<\sigma, and is zero for
|z|> \sigma. The parameter \sigma corresponds to the radius of the circular
support and is related to the amplitude of the Gaussian fluctuations. This form
of the eigenvalue density is highly universal. It is identical for products of
Gaussian Hermitian, non-Hermitian, real or complex random matrices. It does not
change even if the matrices in the product are taken from different Gaussian
ensembles. We present a self-contained derivation of this result using a planar
diagrammatic technique for Gaussian matrices. We also give a numerical evidence
suggesting that this result applies also to matrices whose elements are
independent, centered random variables with a finite variance.Comment: 16 pages, 6 figures, minor changes, some references adde
Arbitrary Rotation Invariant Random Matrix Ensembles and Supersymmetry
We generalize the supersymmetry method in Random Matrix Theory to arbitrary
rotation invariant ensembles. Our exact approach further extends a previous
contribution in which we constructed a supersymmetric representation for the
class of norm-dependent Random Matrix Ensembles. Here, we derive a
supersymmetric formulation under very general circumstances. A projector is
identified that provides the mapping of the probability density from ordinary
to superspace. Furthermore, it is demonstrated that setting up the theory in
Fourier superspace has considerable advantages. General and exact expressions
for the correlation functions are given. We also show how the use of hyperbolic
symmetry can be circumvented in the present context in which the non-linear
sigma model is not used. We construct exact supersymmetric integral
representations of the correlation functions for arbitrary positions of the
imaginary increments in the Green functions.Comment: 36 page
Lax Operator for the Quantised Orthosymplectic Superalgebra U_q[osp(2|n)]
Each quantum superalgebra is a quasi-triangular Hopf superalgebra, so
contains a \textit{universal -matrix} in the tensor product algebra which
satisfies the Yang-Baxter equation. Applying the vector representation ,
which acts on the vector module , to one side of a universal -matrix
gives a Lax operator. In this paper a Lax operator is constructed for the
-type quantum superalgebras . This can in turn be used to
find a solution to the Yang-Baxter equation acting on
where is an arbitrary module. The case is included
here as an example.Comment: 15 page
Level Repulsion in Constrained Gaussian Random-Matrix Ensembles
Introducing sets of constraints, we define new classes of random-matrix
ensembles, the constrained Gaussian unitary (CGUE) and the deformed Gaussian
unitary (DGUE) ensembles. The latter interpolate between the GUE and the CGUE.
We derive a sufficient condition for GUE-type level repulsion to persist in the
presence of constraints. For special classes of constraints, we extend this
approach to the orthogonal and to the symplectic ensembles. A generalized
Fourier theorem relates the spectral properties of the constraining ensembles
with those of the constrained ones. We find that in the DGUEs, level repulsion
always prevails at a sufficiently short distance and may be lifted only in the
limit of strictly enforced constraints.Comment: 20 pages, no figures. New section adde
FLEET: Butterfly Estimation from a Bipartite Graph Stream
We consider space-efficient single-pass estimation of the number of
butterflies, a fundamental bipartite graph motif, from a massive bipartite
graph stream where each edge represents a connection between entities in two
different partitions. We present a space lower bound for any streaming
algorithm that can estimate the number of butterflies accurately, as well as
FLEET, a suite of algorithms for accurately estimating the number of
butterflies in the graph stream. Estimates returned by the algorithms come with
provable guarantees on the approximation error, and experiments show good
tradeoffs between the space used and the accuracy of approximation. We also
present space-efficient algorithms for estimating the number of butterflies
within a sliding window of the most recent elements in the stream. While there
is a significant body of work on counting subgraphs such as triangles in a
unipartite graph stream, our work seems to be one of the few to tackle the case
of bipartite graph streams.Comment: This is the author's version of the work. It is posted here by
permission of ACM for your personal use. Not for redistribution. The
definitive version was published in Seyed-Vahid Sanei-Mehri, Yu Zhang, Ahmet
Erdem Sariyuce and Srikanta Tirthapura. "FLEET: Butterfly Estimation from a
Bipartite Graph Stream". The 28th ACM International Conference on Information
and Knowledge Managemen
Instabilities in complex mixtures with a large number of components
Inside living cells are complex mixtures of thousands of components. It is
hopeless to try to characterise all the individual interactions in these
mixtures. Thus, we develop a statistical approach to approximating them, and
examine the conditions under which the mixtures phase separate. The approach
approximates the matrix of second virial coefficients of the mixture by a
random matrix, and determines the stability of the mixture from the spectrum of
such random matrices.Comment: 4 pages, uses RevTeX 4.
Role of the Tracy-Widom distribution in the finite-size fluctuations of the critical temperature of the Sherrington-Kirkpatrick spin glass
We investigate the finite-size fluctuations due to quenched disorder of the
critical temperature of the Sherrington-Kirkpatrick spin glass. In order to
accomplish this task, we perform a finite-size analysis of the spectrum of the
susceptibility matrix obtained via the Plefka expansion. By exploiting results
from random matrix theory, we obtain that the fluctuations of the critical
temperature are described by the Tracy-Widom distribution with a non-trivial
scaling exponent 2/3
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