11 research outputs found
Quadratic-exponential coherent feedback control of linear quantum stochastic systems
This paper considers a risk-sensitive optimal control problem for a
field-mediated interconnection of a quantum plant with a coherent
(measurement-free) quantum controller. The plant and the controller are
multimode open quantum harmonic oscillators governed by linear quantum
stochastic differential equations, which are coupled to each other and driven
by multichannel quantum Wiener processes modelling the external bosonic fields.
The control objective is to internally stabilize the closed-loop system and
minimize the infinite-horizon asymptotic growth rate of a quadratic-exponential
functional which penalizes the plant variables and the controller output. We
obtain first-order necessary conditions of optimality for this problem by
computing the partial Frechet derivatives of the cost functional with respect
to the energy and coupling matrices of the controller in frequency domain and
state space. An infinitesimal equivalence between the risk-sensitive and
weighted coherent quantum LQG control problems is also established. In addition
to variational methods, we employ spectral factorizations and infinite cascades
of auxiliary classical systems. Their truncations are applicable to numerical
optimization algorithms (such as the gradient descent) for coherent quantum
risk-sensitive feedback synthesis.Comment: 29 pages, 3 figure
Structure-Preserving Model Reduction of Physical Network Systems
This paper considers physical network systems where the energy storage is naturally associated to the nodes of the graph, while the edges of the graph correspond to static couplings. The first sections deal with the linear case, covering examples such as mass-damper and hydraulic systems, which have a structure that is similar to symmetric consensus dynamics. The last section is concerned with a specific class of nonlinear physical network systems; namely detailed-balanced chemical reaction networks governed by mass action kinetics. In both cases, linear and nonlinear, the structure of the dynamics is similar, and is based on a weighted Laplacian matrix, together with an energy function capturing the energy storage at the nodes. We discuss two methods for structure-preserving model reduction. The first one is clustering; aggregating the nodes of the underlying graph to obtain a reduced graph. The second approach is based on neglecting the energy storage at some of the nodes, and subsequently eliminating those nodes (called Kron reduction).</p
Information geometry
This Special Issue of the journal Entropy, titled “Information Geometry I”, contains a collection of 17 papers concerning the foundations and applications of information geometry. Based on a geometrical interpretation of probability, information geometry has become a rich mathematical field employing the methods of differential geometry. It has numerous applications to data science, physics, and neuroscience. Presenting original research, yet written in an accessible, tutorial style, this collection of papers will be useful for scientists who are new to the field, while providing an excellent reference for the more experienced researcher. Several papers are written by authorities in the field, and topics cover the foundations of information geometry, as well as applications to statistics, Bayesian inference, machine learning, complex systems, physics, and neuroscience
MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications
Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described
SIMULATING SEISMIC WAVE PROPAGATION IN TWO-DIMENSIONAL MEDIA USING DISCONTINUOUS SPECTRAL ELEMENT METHODS
We introduce a discontinuous spectral element method for simulating seismic wave in 2- dimensional elastic media. The methods combine the flexibility of a discontinuous finite
element method with the accuracy of a spectral method. The elastodynamic equations are discretized using high-degree of Lagrange interpolants and integration over an element is
accomplished based upon the Gauss-Lobatto-Legendre integration rule. This combination of discretization and integration results in a diagonal mass matrix and the use of discontinuous finite element method makes the calculation can be done locally in each element. Thus, the algorithm is simplified drastically. We validated the results of one-dimensional problem by comparing them with finite-difference time-domain method and exact solution. The comparisons show excellent agreement