Optimization of trial wave functions for use in quantum Monte Carlo with application to LiH

Methods for both partial and full optimization of wavefunction parameters are explored, and these are applied to the LiH molecule. A partial optimization can be easily performed with little difficulty. But to perform a full optimization we must avoid a wrong minimum, and deal with linear-dependency, time step-dependency and ensemble-dependency problems. Five basis sets are examined. The optimized wavefunction with a 3-function set gives a variational energy of -7.998 + 0.005 a.u., which is comparable to that (-7.990 + 0.003) 1 of Reynold's unoptimized \fin ( a double-~ set of eight functions). The optimized wavefunction with a double~ plus 3dz2 set gives ari energy of -8.052 + 0.003 a.u., which is comparable with the fixed-node energy (-8.059 + 0.004)1 of the \fin. The optimized double-~ function itself gives an energy of -8.049 + 0.002 a.u. Each number above was obtained on a Bourrghs 7900 mainframe computer with 14 -15 hrs CPU time.

Individual differences in risk-taking and associated characteristics : a test of specificity in executive functions /

Multiple measures have been devised by clinicians and theorists from many different backgrounds for the purpose of assessing the influence of the frontal lobes on behaviour. Some utilize self-report measures to investigate behavioural characteristics such as risktaking, sensation seeking, impulsivity, and sensitivity to reward and punishment in an attempt to understand complex human decision making. Others rely more on neuroimaging and electrophysiological investigation involving experimental tasks thought to demonstrate executive functions in action, while other researchers prefer to study clinical populations with selective damage. Neuropsychological models of frontal lobe functioning have led to a greater appreciation of the dissociations among various aspects of prefrontal cortex function. This thesis involves (1) an examination of various psychometric and experimental indices of executive functions for coherence as one would predict on the basis of highly developed neurophysiological models of prefrontal function, particularly those aspects of executive function that involve predominantly cognitive abilities versus processes characterized by affect regulation; and (2) investigation of the relations between risk-taking, attentional abilties and their associated characteristics using a neurophysiological model of prefrontal functions addressed in (1). Late adolescence is a stage in which the prefrontal cortices undergo intensive structural and functional maturational changes; this period also involves increases in levels of risky and sensation driven behaviours, as well as a hypersensitivity to reward and a reduction in inhibition. Consequently, late adolescence spears to represent an ideal developmental period in which to examine these decision-making behaviours due to the maximum variability of behavioural characteristics of interest. Participants were 45 male undergraduate 18- to 19-year olds, who completed a battery of measures that included self-report, experimental and behavioural measures designed to assess particular aspects of prefrontal and executive functioning. As predicted, factor analysis supported the grouping of executive process by type (either primarily cognitive or affective), conforming to the orbitofrontal versus dorsolateral typology; risk-taking and associated characteristics were associated more with the orbitofrontal than the dorsolateral factor, whereas attentional and planning abilities tended to correlate more strongly with the dorsolateral factor. Results are discussed in light of future assessment, investigation and understanding of complex human decision-making and executive functions. Implications, applications and suggestions for future research are also proposed.

An Abstract Algebraic Theory of L-Fuzzy Relations for Relational Databases

Classical relational databases lack proper ways to manage certain real-world situations including imprecise or uncertain data. Fuzzy databases overcome this limitation by allowing each entry in the table to be a fuzzy set where each element of the corresponding domain is assigned a membership degree from the real interval [0…1]. But this fuzzy mechanism becomes inappropriate in modelling scenarios where data might be incomparable. Therefore, we become interested in further generalization of fuzzy database into L-fuzzy database. In such a database, the characteristic function for a fuzzy set maps to an arbitrary complete Brouwerian lattice L. From the query language perspectives, the language of fuzzy database, FSQL extends the regular Structured Query Language (SQL) by adding fuzzy specific constructions. In addition to that, L-fuzzy query language LFSQL introduces appropriate linguistic operations to define and manipulate inexact data in an L-fuzzy database. This research mainly focuses on defining the semantics of LFSQL. However, it requires an abstract algebraic theory which can be used to prove all the properties of, and operations on, L-fuzzy relations. In our study, we show that the theory of arrow categories forms a suitable framework for that. Therefore, we define the semantics of LFSQL in the abstract notion of an arrow category. In addition, we implement the operations of L-fuzzy relations in Haskell and develop a parser that translates algebraic expressions into our implementation.

L-Fuzzy Structured Query Language

Lattice valued fuzziness is more general than crispness or fuzziness based on the unit interval. In this work, we present a query language for a lattice based fuzzy database. We define a Lattice Fuzzy Structured Query Language (LFSQL) taking its membership values from an arbitrary lattice L. LFSQL can handle, manage and represent crisp values, linear ordered membership degrees and also allows membership degrees from lattices with non-comparable values. This gives richer membership degrees, and hence makes LFSQL more flexible than FSQL or SQL. In order to handle vagueness or imprecise information, every entry into an L-fuzzy database is an L-fuzzy set instead of crisp values. All of this makes LFSQL an ideal query language to handle imprecise data where some factors are non-comparable. After defining the syntax of the language formally, we provide its semantics using L-fuzzy sets and relations. The semantics can be used in future work to investigate concepts such as functional dependencies. Last but not least, we present a parser for LFSQL implemented in Haskell.