Solving Quadratic Equations via PhaseLift when There Are About As Many Equations As Unknowns

This note shows that we can recover a complex vector x in C^n exactly from on the order of n quadratic equations of the form ||^2 = b_i, i = 1, ..., m, by using a semidefinite program known as PhaseLift. This improves upon earlier bounds in [3], which required the number of equations to be at least on the order of n log n. We also demonstrate optimal recovery results from noisy quadratic measurements; these results are much sharper than previously known results.Comment: 6 page

Impact of Ethanol Production on U.S. and Regional Gasoline Prices and On the Profitability of U.S. Oil Refinery Industry

Using pooled regional time-series data and panel data estimation, we quantify the impact of monthly ethanol production on monthly retail regular gasoline prices. This analysis suggests that the growth in ethanol production has caused retail gasoline prices to be $0.29 to$0.40 per gallon lower than would otherwise have been the case. The analysis shows that the negative impact of ethanol on gasoline prices varies considerably across regions. The Midwest region has the biggest impact, at $0.39/gallon, while the Rocky Mountain region had the smallest impact, at$0.17/gallon. The results also indicate that ethanol production has significantly reduced the profit margin of the oil refinery industry. The results are robust with respect to alternative model specifications.crack spread, crude oil prices, ethanol, gasoline prices, Resource /Energy Economics and Policy,

Robust Principal Component Analysis?

This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component individually? We prove that under some suitable assumptions, it is possible to recover both the low-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the L1 norm. This suggests the possibility of a principled approach to robust principal component analysis since our methodology and results assert that one can recover the principal components of a data matrix even though a positive fraction of its entries are arbitrarily corrupted. This extends to the situation where a fraction of the entries are missing as well. We discuss an algorithm for solving this optimization problem, and present applications in the area of video surveillance, where our methodology allows for the detection of objects in a cluttered background, and in the area of face recognition, where it offers a principled way of removing shadows and specularities in images of faces

Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets: A Bayesian Analysis

This paper assesses the roles of various factors influencing the volatility of crude oil prices and the possible linkage between this volatility and agricultural commodity markets. Stochastic volatility models are applied to weekly crude oil, corn and wheat futures prices from November 1998 to January 2009. Model parameters are estimated using Bayesian Markov chain Monte Carlo methods. The main results are as follows. Speculation, scalping, and petroleum inventories are found to be important in explaining oil price variation. Several properties of crude oil price dynamics are established including mean-reversion, a negative correlation between price and volatility, volatility clustering, and infrequent compound Poisson jumps. We find evidence of volatility spillover among crude oil, corn and wheat markets after the fall of 2006. This could be largely explained by tightened interdependence between these markets induced by ethanol production.Gibbs sampling, Merton jump, leverage effect, stochastic volatility, Demand and Price Analysis, Financial Economics, Resource /Energy Economics and Policy, G13, Q4,

Stability vs. optimality in selfish ring routing

We study the asymmetric atomic selfish routing in ring networks, which has diverse practical applications in network design and analysis. We are concerned with minimizing the maximum latency of source-destination node-pairs over links with linear latencies. We obtain the first constant upper bound on the price of anarchy and significantly improve the existing upper bounds on the price of stability. Moreover, we show that any optimal solution is a good approximate Nash equilibrium. Finally, we present better performance analysis and fast implementation of pseudo-polynomial algorithms for computing approximate Nash equilibria

Nanoindentation of the a and c domains in a tetragonal BaTiO3 single crystal

Nanoindentation in conjunction with piezoresponse force microscopy was used to study domain switching and to measure the mechanical properties of individual ferroelectric domains in a tetragonal BaTiO3 single crystal. It was found that nanoindentation has induced local domain switching; the a and c domains of BaTiO3 have different elastic moduli but similar hardness. Nanoindentation modulus mapping on the a and c domains further confirmed such difference in elasticity. Finite element modeling was used to simulate the von Mises stress and plastic strain profiles of the indentations on both a and c domains, which introduces a much higher stress level than the critical value for domain nucleation

Dense Error Correction for Low-Rank Matrices via Principal Component Pursuit

We consider the problem of recovering a low-rank matrix when some of its entries, whose locations are not known a priori, are corrupted by errors of arbitrarily large magnitude. It has recently been shown that this problem can be solved efficiently and effectively by a convex program named Principal Component Pursuit (PCP), provided that the fraction of corrupted entries and the rank of the matrix are both sufficiently small. In this paper, we extend that result to show that the same convex program, with a slightly improved weighting parameter, exactly recovers the low-rank matrix even if "almost all" of its entries are arbitrarily corrupted, provided the signs of the errors are random. We corroborate our result with simulations on randomly generated matrices and errors.Comment: Submitted to ISIT 201

Fast initialization of the spin state of an electron in a quantum dot in the Voigt configuration

We consider the initialization of the spin-state of a single electron trapped in a self-assembled quantum dot via optical pumping of a trion level. We show that with a magnetic field applied perpendicular to the growth direction of the dot, a near-unity fidelity can be obtained in a time equal to a few times the inverse of the spin-conserving trion relaxation rate. This method is several orders-of-magnitude faster than with the field aligned parallel, since this configuration must rely on a slow hole spin-flip mechanism. This increase in speed does result in a limit on the maximum obtainable fidelity, but we show that for InAs dots, the error is very small.Comment: 4 pages, 4 figure

Plasmonic Brownian ratchet

Here we present a Brownian ratchet based on plasmonic interactions. By periodically turning on and off a laser beam that illuminates a periodic array of plasmonic nanostructures with broken spatial symmetry, the random thermal motion of a subwavelength dielectric bead is rectified into one direction. By means of the Molecular Dynamics technique we show a statistical directed drift in particle flow