Robust eigensystem assignment for second-order estimators

An approach for the robust eigensystem assignment of flexible structures using full state or output feedback is developed. Using the second-order dynamic equations, the approach can assign the eigenvalues of the system via velocity and displacement feedbacks, or acceleration and velocity feedbacks. The eigenvalues and eigenvectors of the system are assigned, via the second-order eigenvalue problem for the structural system, in two steps. First, an orthonormal basis spanning the attainable closed-loop eigenvector space corresponding to each desired closed-loop eigenvalue is generated using the Singular Value or QR decompositions. Second, a sequential procedure is used to choose a set of closed-loop eigenvectors that are as close as possible to the column space of a well-conditioned target matrix. Among the possible choices of the target matrix, the closest unitary matrix to the open-loop eigenvector matrix appears to be a suitable choice. A numerical example is given to illustrate the proposed algorithm

The Limitations of Optimization from Samples

In this paper we consider the following question: can we optimize objective functions from the training data we use to learn them? We formalize this question through a novel framework we call optimization from samples (OPS). In OPS, we are given sampled values of a function drawn from some distribution and the objective is to optimize the function under some constraint. While there are interesting classes of functions that can be optimized from samples, our main result is an impossibility. We show that there are classes of functions which are statistically learnable and optimizable, but for which no reasonable approximation for optimization from samples is achievable. In particular, our main result shows that there is no constant factor approximation for maximizing coverage functions under a cardinality constraint using polynomially-many samples drawn from any distribution. We also show tight approximation guarantees for maximization under a cardinality constraint of several interesting classes of functions including unit-demand, additive, and general monotone submodular functions, as well as a constant factor approximation for monotone submodular functions with bounded curvature

c-Myc induced changes in higher order rDNA structure accompany growth factor stimulation of quiescent cells

Human c-Myc is believed to be a high level coordinator of protein synthesis capacity and cell growth rate, capable of activating transcription by all three nuclear RNA Polymerases. Direct activation of rDNA transcription by c-Myc is functionally conserved in rat cells, despite high divergence in non-coding rDNA sequences, suggesting that this coordinating role is likely to be a general within mammals. Upon re-feeding of starved cells, c-Myc activity enhances the efficiency of RNA Polymerase I and SL1/TIF-1B recruitment to the rDNA and rapidly induces higher order gene loop structures in rDNA chromatin that juxtapose upstream and downstream rDNA sequences. Furthermore c-Myc induced gene-loop formation in rDNA genes occurs independently of rDNA transcription, implying that it may be an early step in the re-programming of quiescent cells as they enter the growth cycle

Optimal Event-Driven Multi-Agent Persistent Monitoring of a Finite Set of Targets

We consider the problem of controlling the movement of multiple cooperating agents so as to minimize an uncertainty metric associated with a finite number of targets. In a one-dimensional mission space, we adopt an optimal control framework and show that the solution is reduced to a simpler parametric optimization problem: determining a sequence of locations where each agent may dwell for a finite amount of time and then switch direction. This amounts to a hybrid system which we analyze using Infinitesimal Perturbation Analysis (IPA) to obtain a complete on-line solution through an event-driven gradient-based algorithm which is also robust with respect to the uncertainty model used. The resulting controller depends on observing the events required to excite the gradient-based algorithm, which cannot be guaranteed. We solve this problem by proposing a new metric for the objective function which creates a potential field guaranteeing that gradient values are non-zero. This approach is compared to an alternative graph-based task scheduling algorithm for determining an optimal sequence of target visits. Simulation examples are included to demonstrate the proposed methods.Comment: 12 pages full version, IEEE Conference on Decision and Control, 201

System/observer/controller identification toolbox

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data

Cross-Correlation analysis of WMAP and EGRET in Wavelet Space

We cross correlate the Wilkinson Microwave Anisotropy Probe (WMAP) first year data and the diffuse gamma-ray intensity maps from the Energetic Gamma Ray Experiment Telescope (EGRET) using spherical wavelet approaches. Correlations at 99.7% significance level have been detected, at scales around $15^{\circ}$ in the WMAP foreground cleaned W-band and Q-band maps, based on data from regions that are outside the most conservative WMAP foreground mask; no significant correlation is found with the Tegmark cleaned map. The detected correlation is most likely of Galactic origin, and thus can help us probing the origins of possible Galactic foreground residuals and ultimately removing them from measured microwave sky maps.Comment: 4 pages, 7 figures; accepted for publication in ApJ

Breaking and restoration of rotational symmetry for irreducible tensor operators on the lattice

We study the breaking of rotational symmetry on the lattice for irreducible tensor operators and practical methods for suppressing this breaking. We illustrate the features of the general problem using an $\alpha$ cluster model for $^{8}$Be. We focus on the lowest states with non-zero angular momentum and examine the matrix elements of multipole moment operators. We show that the physical reduced matrix element is well reproduced by averaging over all possible orientations of the quantum state, and this is expressed as a sum of matrix elements weighted by the corresponding Clebsch-Gordan coefficients. For our $\alpha$ cluster model we find that the effects of rotational symmetry breaking can be largely eliminated for lattice spacings of $a\leq 1.7$ fm, and we expect similar improvement for actual lattice Monte Carlo calculations.Comment: 8 pages, 4 figure

Precise determination of lattice phase shifts and mixing angles

We introduce a general and accurate method for determining lattice phase shifts and mixing angles, which is applicable to arbitrary, non-cubic lattices. Our method combines angular momentum projection, spherical wall boundaries and an adjustable auxiliary potential. This allows us to construct radial lattice wave functions and to determine phase shifts at arbitrary energies. For coupled partial waves, we use a complex-valued auxiliary potential that breaks time-reversal invariance. We benchmark our method using a system of two spin-1/2 particles interacting through a finite-range potential with a strong tensor component. We are able to extract phase shifts and mixing angles for all angular momenta and energies, with precision greater than that of extant methods. We discuss a wide range of applications from nuclear lattice simulations to optical lattice experiments.Comment: 7 pp, 4 figs, 1 tabl