2,487 research outputs found
Rigorous numerics for nonlinear operators with tridiagonal dominant linear part
We present a method designed for computing solutions of infinite dimensional
non linear operators with a tridiagonal dominant linear part. We
recast the operator equation into an equivalent Newton-like equation , where is an approximate inverse of the derivative
at an approximate solution . We present rigorous
computer-assisted calculations showing that is a contraction near
, thus yielding the existence of a solution. Since does not have an asymptotically diagonal dominant structure, the
computation of is not straightforward. This paper provides ideas for
computing , and proposes a new rigorous method for proving existence of
solutions of nonlinear operators with tridiagonal dominant linear part.Comment: 27 pages, 3 figures, to be published in DCDS-A (Vol. 35, No. 10)
October 2015 issu
On The S-Matrix of Ising Field Theory in Two Dimensions
We explore the analytic structure of the non-perturbative S-matrix in
arguably the simplest family of massive non-integrable quantum field theories:
the Ising field theory (IFT) in two dimensions, which may be viewed as the
Ising CFT deformed by its two relevant operators, or equivalently, the scaling
limit of the Ising model in a magnetic field. Our strategy is that of collider
physics: we employ Hamiltonian truncation method (TFFSA) to extract the
scattering phase of the lightest particles in the elastic regime, and combine
it with S-matrix bootstrap methods based on unitarity and analyticity
assumptions to determine the analytic continuation of the 2 to 2 S-matrix
element to the complex s-plane. Focusing primarily on the "high temperature"
regime in which the IFT interpolates between that of a weakly coupled massive
fermion and the E8 affine Toda theory, we will numerically determine 3-particle
amplitudes, follow the evolution of poles and certain resonances of the
S-matrix, and exclude the possibility of unknown wide resonances up to
reasonably high energies.Comment: typos corrected, references added, additional comparison with
perturbation theory added. 35 pages, 21 figure
Non-Asymptotic Analysis of Tangent Space Perturbation
Constructing an efficient parameterization of a large, noisy data set of
points lying close to a smooth manifold in high dimension remains a fundamental
problem. One approach consists in recovering a local parameterization using the
local tangent plane. Principal component analysis (PCA) is often the tool of
choice, as it returns an optimal basis in the case of noise-free samples from a
linear subspace. To process noisy data samples from a nonlinear manifold, PCA
must be applied locally, at a scale small enough such that the manifold is
approximately linear, but at a scale large enough such that structure may be
discerned from noise. Using eigenspace perturbation theory and non-asymptotic
random matrix theory, we study the stability of the subspace estimated by PCA
as a function of scale, and bound (with high probability) the angle it forms
with the true tangent space. By adaptively selecting the scale that minimizes
this bound, our analysis reveals an appropriate scale for local tangent plane
recovery. We also introduce a geometric uncertainty principle quantifying the
limits of noise-curvature perturbation for stable recovery. With the purpose of
providing perturbation bounds that can be used in practice, we propose plug-in
estimates that make it possible to directly apply the theoretical results to
real data sets.Comment: 53 pages. Revised manuscript with new content addressing application
of results to real data set
Existence and instability of steady states for a triangular cross-diffusion system: a computer-assisted proof
In this paper, we present and apply a computer-assisted method to study
steady states of a triangular cross-diffusion system. Our approach consist in
an a posteriori validation procedure, that is based on using a fxed point
argument around a numerically computed solution, in the spirit of the
Newton-Kantorovich theorem. It allows us to prove the existence of various non
homogeneous steady states for different parameter values. In some situations,
we get as many as 13 coexisting steady states. We also apply the a posteriori
validation procedure to study the linear stability of the obtained steady
states, proving that many of them are in fact unstable
The role of asymptotic functions in network optimization and feasibility studies
Solutions to network optimization problems have greatly benefited from
developments in nonlinear analysis, and, in particular, from developments in
convex optimization. A key concept that has made convex and nonconvex analysis
an important tool in science and engineering is the notion of asymptotic
function, which is often hidden in many influential studies on nonlinear
analysis and related fields. Therefore, we can also expect that asymptotic
functions are deeply connected to many results in the wireless domain, even
though they are rarely mentioned in the wireless literature. In this study, we
show connections of this type. By doing so, we explain many properties of
centralized and distributed solutions to wireless resource allocation problems
within a unified framework, and we also generalize and unify existing
approaches to feasibility analysis of network designs. In particular, we show
sufficient and necessary conditions for mappings widely used in wireless
communication problems (more precisely, the class of standard interference
mappings) to have a fixed point. Furthermore, we derive fundamental bounds on
the utility and the energy efficiency that can be achieved by solving a large
family of max-min utility optimization problems in wireless networks.Comment: GlobalSIP 2017 (to appear
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