A highly optimized vectorized code for Monte Carlo simulations of SU(3) lattice gauge theories

New methods are introduced for improving the performance of the vectorized Monte Carlo SU(3) lattice gauge theory algorithm using the CDC CYBER 205. Structure, algorithm and programming considerations are discussed. The performance achieved for a 16(4) lattice on a 2-pipe system may be phrased in terms of the link update time or overall MFLOPS rates. For 32-bit arithmetic, it is 36.3 microsecond/link for 8 hits per iteration (40.9 microsecond for 10 hits) or 101.5 MFLOPS

Evolutionary Algorithms for Reinforcement Learning

There are two distinct approaches to solving reinforcement learning problems, namely, searching in value function space and searching in policy space. Temporal difference methods and evolutionary algorithms are well-known examples of these approaches. Kaelbling, Littman and Moore recently provided an informative survey of temporal difference methods. This article focuses on the application of evolutionary algorithms to the reinforcement learning problem, emphasizing alternative policy representations, credit assignment methods, and problem-specific genetic operators. Strengths and weaknesses of the evolutionary approach to reinforcement learning are presented, along with a survey of representative applications

Atomic resolved material displacement on graphite surfaces by scanning tunnelling microscopy

Atomic scale modifications and subsequent atomic resolution imaging has been achieved on the highly oriented pyrolytic graphite surface in air. Application of short pulse voltages, above a minimum threshold voltage of 3.5 V, across the tunneling gap results in the displacement of a layer or more of atoms to form a hole and create a neighboring mound or ‘‘nanodot’’ from the displaced atoms. We have found a correlation between the hole and ‘‘nanodot’’ volume at the atomic level and observe an asymmetric displacement of material in all cases of feature creation. Nanofeatures as small as four carbon atoms at beta sites have been created. Our experimental observations are consistent with the modification process depending on the gradient in the electric field induced by the rise time of the bias pulse voltage and not the pulse duration. Interesting faceting behavior has also been observed around some hole edges. Tip bias pulsing sometimes induced a tip, and not a surface modification, resulting in a change in the observed tunneling image

Further development of a charged liquid colloid source for electrostatic propulsion Final report

Performance characteristics of charged liquid droplet electrostatic propulsion syste

The Role of the Family in Immigrants' Labor-Market Activity: Evidence from the United States

We use Census of Population microdata for 1980 and 1990 to examine the labor supply and wages of immigrant husbands and wives in the United States in a family context. Earlier research by Baker and Benjamin (1997) posits a family investment model in which, upon arrival, immigrant husbands invest in their human capital while immigrant wives work to provide the family with liquidity during this period. Consistent with this model, they find for Canada that immigrant wives work longer hours upon arrival than comparable natives, but, with time in Canada, they are eventually overtaken by native wives. In contrast, we find that, among immigrants to the United States, both husbands and wives work and earn less than comparable natives upon arrival, with similar shortfalls for men and women. Further, both immigrant husbands and wives have similar, positive assimilation profiles in wages and labor supply and eventually overtake both the wages and the labor supply of comparable natives.

Using Brain Imaging for Lie Detection: Where Science, Law, and Policy Collide

Progress in the use of functional magnetic resonance imaging (fMRI) of the brain to evaluate deception and differentiate lying from truth-telling has created anticipation of a breakthrough in the search for technology-based methods of lie detection. In the last few years, litigants have attempted to introduce fMRI lie detection evidence in courts. This article weighs in on the interdisciplinary debate about the admissibility of such evidence, identifying the missing pieces of the scientific puzzle that need to be completed if fMRI-based lie detection is to meet the standards of either legal reliability or general acceptance. We believe that the Daubert’s “known error rate” is the key concept linking the legal and scientific standards. We posit that properly-controlled clinical trials are the most convincing means to determine the error rates of fMRI-based lie detection and confirm or disprove the relevance of the promising laboratory research on this topic. This article explains the current state of the science and provides an analysis of the case law in which litigants have sought to introduce fMRI lie detection. Analyzing the myriad issues related to fMRI lie detection, the article identifies the key limitations of the current neuroimaging of deception science as expert evidence and explores the problems that arise from using scientific evidence before it is proven scientifically valid and reliable. We suggest that courts continue excluding fMRI lie detection evidence until this potentially useful form of forensic science meets the scientific standards currently required for adoption of a medical test or device. Given a multitude of stakeholders and, the charged and controversial nature and the potential societal impact of this technology, goodwill and collaboration of several government agencies may be required to sponsor impartial and comprehensive clinical trials that will guide the development of forensic fMRI technology

Transition-metal interactions in aluminum-rich intermetallics

The extension of the first-principles generalized pseudopotential theory (GPT) to transition-metal (TM) aluminides produces pair and many-body interactions that allow efficient calculations of total energies. In aluminum-rich systems treated at the pair-potential level, one practical limitation is a transition-metal over-binding that creates an unrealistic TM-TM attraction at short separations in the absence of balancing many-body contributions. Even with this limitation, the GPT pair potentials have been used effectively in total-energy calculations for Al-TM systems with TM atoms at separations greater than 4 AA. An additional potential term may be added for systems with shorter TM atom separations, formally folding repulsive contributions of the three- and higher-body interactions into the pair potentials, resulting in structure-dependent TM-TM potentials. Towards this end, we have performed numerical ab-initio total-energy calculations using VASP (Vienna Ab Initio Simulation Package) for an Al-Co-Ni compound in a particular quasicrystalline approximant structure. The results allow us to fit a short-ranged, many-body correction of the form a(r_0/r)^{b} to the GPT pair potentials for Co-Co, Co-Ni, and Ni-Ni interactions.Comment: 18 pages, 5 figures, submitted to PR