Competitive Equilibria in Decentralized Matching with Incomplete Information

This paper shows that all perfect Bayesian equilibria of a decentralized dynamic matching market with two-sided incomplete information of independent private values variety converge to competitive equilibria. Each buyer wants to purchase a bundle of heterogeneous, indivisible goods and each seller owns one unit of a heterogeneous indivisible good (as in Kelso and Crawford (1982) or Gul and Stacchetti (1999)). Buyer preferences and endowments as well as seller costs are private information. Agents engage in costly search and meet randomly. The terms of trade are determined through bilateral bargaining between buyers and sellers. The paper considers a market in steady state. It is shown that as frictions, i.e., discounting and fixed costs of search become small, all equilibria of the market game converge to perfectly competitive equilibria.Bargaining, Search, Matching

Competitive Equilibria in Decentralized Matching with Incomplete Information

This paper shows that all perfect Bayesian equilibria of a dynamic matching game with two-sided incomplete information of independent private values variety are asymptotically Walrasian. Buyers purchase a bundle of heterogeneous, indivisible goods and sellers own one unit of an indivisible good. Buyer preferences and endowments as well as seller costs are private information. Agents engage in costly search and meet randomly. The terms of trade are determined through a Bayesian mechanism proposal game. The paper considers a market in steady state. As discounting and the fixed cost of search become small, all trade takes place at a Walrasian price. However, a robust example is presented where the limit price vector is a Walrasian price for an economy where only a strict subsets of the goods in the original economy are traded, i.e, markets are missing at the limit. Nevertheless, there exists a sequence of equilibria that converge to a Walrasian equilibria for the whole economy where all markets are open.Conditional CAPM

Phonons in Nanocrystalline 57Fe

We measured the phonon density of states (DOS) of nanocrystalline Fe by resonant inelastic nuclear γ-ray scattering. The nanophase material shows large distortions in its phonon DOS. We attribute the high energy distortion to lifetime broadening. A damped harmonic oscillator model for the phonons provides a low quality factor, Qu, averaging about 5, but the longitudinal modes may have been broadened most. The nanocrystalline Fe also shows an enhancement in its phonon DOS at energies below 15 meV. The difference in vibrational entropy of the bulk and nanocrystalline Fe was small, owing to competing changes in the nanocrystalline phonon DOS at low and high energies

Local Chemical Environments and the Phonon Partial Densities of States of 57Fe in 57Fe3Al

Inelastic nuclear resonant scattering spectra were measured on alloys of Fe3Al that were chemically disordered, partially ordered, and D03 ordered. The features in the phonon partial density of states of 57Fe were found to change systematically with chemical short-range order in the alloy. Changes in the phonon partial density of states were modeled successfully by assigning vibrational spectra to 57Fe atoms in different first-nearest-neighbor chemical environments

Designing a road network for hazardous materials shipments

Cataloged from PDF version of article.We consider the problem of designating hazardous materials routes in and through a major population center. Initially, we restrict our attention to a minimally connected network (a tree) where we can predict accurately the flows on the network. We formulate the tree design problem as an integer programming problem with an objective of minimizing the total transport risk. Such design problems of moderate size can be solved using commercial solvers. We then develop a simple construction heuristic to expand the solution of the tree design problem by adding road segments. Such additions provide carriers with routing choices, which usually increase risks but reduce costs. The heuristic adds paths incrementally, which allows local authorities to trade off risk and cost. We use the road network of the city of Ravenna, Italy, to demonstrate the solution of our integer programming model and our path-addition heuristic. © 2005 Elsevier Ltd. All rights reserved

Atom clusters and vibrational excitations in chemically-disordered Pt357Fe

Inelastic nuclear resonant scattering spectra of Fe-57 atoms were measured on crystalline alloys of Pt3Fe-57 that were chemically disordered, partially ordered, and L1(2) ordered. Phonon partial density of states curves for Fe-57 were obtained from these spectra. Upon disordering, about 10% of the spectral intensity underwent a distinct shift from 25 to 19 meV. This change in optical modes accounted for most of the change of the vibrational entropy of disordering contributed by Fe atoms, which was (+0.10 +/- 0.03) k(B) (Fe atom)(-1). Prospects for parametrizing the vibrational entropy with low-order cluster variables were assessed. To calculate the difference in vibrational entropy of the disordered and ordered alloys, the clusters must be large enough to account for the abundances of several of the atom configurations of the first-nearest-neighbor shell about the Fe-57 atoms

Quantum Algorithms for Learning and Testing Juntas

In this article we develop quantum algorithms for learning and testing juntas, i.e. Boolean functions which depend only on an unknown set of k out of n input variables. Our aim is to develop efficient algorithms: - whose sample complexity has no dependence on n, the dimension of the domain the Boolean functions are defined over; - with no access to any classical or quantum membership ("black-box") queries. Instead, our algorithms use only classical examples generated uniformly at random and fixed quantum superpositions of such classical examples; - which require only a few quantum examples but possibly many classical random examples (which are considered quite "cheap" relative to quantum examples). Our quantum algorithms are based on a subroutine FS which enables sampling according to the Fourier spectrum of f; the FS subroutine was used in earlier work of Bshouty and Jackson on quantum learning. Our results are as follows: - We give an algorithm for testing k-juntas to accuracy $\epsilon$ that uses $O(k/\epsilon)$ quantum examples. This improves on the number of examples used by the best known classical algorithm. - We establish the following lower bound: any FS-based k-junta testing algorithm requires $\Omega(\sqrt{k})$ queries. - We give an algorithm for learning $k$-juntas to accuracy $\epsilon$ that uses $O(\epsilon^{-1} k\log k)$ quantum examples and $O(2^k \log(1/\epsilon))$ random examples. We show that this learning algorithms is close to optimal by giving a related lower bound.Comment: 15 pages, 1 figure. Uses synttree package. To appear in Quantum Information Processin