Deconfinement from Action Restriction

The effect of restricting the plaquette to be greater than a certain cutoff value is studied. The action considered is the standard Wilson action with the addition of a plaquette restriction, which should not affect the continuum limit of the theory. In this investigation, the strong coupling limit is also taken. It is found that a deconfining phase transition occurs as the cutoff is increased, on all lattices studied (up to $20^4$). The critical cutoff on the infinite lattice appears to be around 0.55. For cutoffs above this, a fixed point behavior is observed in the normalized fourth cumulant of the Polyakov loop, suggesting the existence of a line of critical points corresponding to a massless gluon phase, not unlike the situation in compact U(1). The Polyakov loop susceptibility also appears to be diverging with lattice size at these cutoffs. A strong finite volume behavior is observed in the pseudo-specific heat. It is discussed whether these results could still be consistent with the standard crossover picture which precludes the existence of a deconfining phase transition on an infinite symmetric lattice.Comment: 4 pages latex, 6 ps figures, uses espcrc2.sty (included). Poster presented at LATTICE96(topology

Gauge Invariance and Confinement in Noncompact Simulations of SU(2)

Wilson loops have been measured at strong coupling, $\beta=0.5$, on a $12^4$ lattice in a noncompact simulation of pure SU(2) in which random compact gauge transformations impose a kind of lattice gauge invariance. The Wilson loops suggest a confining potential.Comment: 3 pages, requires PiCTeX, talk presented at Lattice '93, UNM-gicns

Noncompact Lattice Simulations of SU(2) Gauge Theory

Wilson loops have been measured at strong coupling, $\beta=0.5$, on a $12^4$ lattice in noncompact simulations of pure SU(2) without gauge fixing. There is no sign of quark confinement.Comment: 4 pages, UNM-93-nl

Can a Logarithmically Running Coupling Mimic a String Tension?

It is shown that a Coulomb potential using a running coupling slightly modified from the perturbative form can produce an interquark potential that appears nearly linear over a large distance range. Recent high-statistics SU(2) lattice gauge theory data fit well to this potential without the need for a linear string-tension term. This calls into question the accuracy of string tension measurements which are based on the assumption of a constant coefficient for the Coulomb term. It also opens up the possibility of obtaining an effectively confining potential from gluon exchange alone.Comment: 13 pages, LaTeX, two figures not included, available from author. revision - Line lengths fixed so it will tex properl

STI-2062-1

This project investigated solar variability, power conversion and electric power grid response aspects of high penetration solar PV. These are the primary determining factors for acceptable penetration levels. Therefore, the study not only focused on the power system interactions, but also on the design of advanced power conditioners to explore more efficient design options and to look into advanced control impacts to the higher penetration PV deployment systems. Through extensive laboratory and field testing, the team gathered the essential information to better understand grid characteristics, PV systems configuration and power conditioning systems

SU(2) Lattice Gauge Theory with Logarithmic Action: Scaling and Universality

We investigate a version of SU(2) lattice gauge theory with a logarithmic action. The model is found to exhibit confinement, contrary to previous claims in the literature. Comparing ratios of physical quantities, like $\sqrt{\sigma}/T_c$, we find that the model belongs to the same universality class as the standard SU(2) lattice gauge theory with Wilson action. Like the positive plaquette model, the model with logarithmic action has a monotonic $\beta$-function, without the famous dip exhibited by the Wilson action. Short distance dislocations affecting the definition of topology are slightly more suppressed than for the positive plaquette model.Comment: 19 pages. Self-unwrapping compressed postscript fil

Using Basic Science to Design a Clinical Trial: Baseline Characteristics of Women Enrolled in the Kronos Early Estrogen Prevention Study (KEEPS)

Observational and epidemiological studies suggest that menopausal hormone therapy (MHT) reduces cardiovascular disease (CVD) risk. However, results from prospective trials showed neutral or adverse effects most likely due to differences in participant demographics, such as age, timing of initiation of treatment, and preexisting cardiovascular disease, which reflected in part the lack of basic science information on mechanisms of action of hormones on the vasculature at the time clinical trials were designed. The Kronos Early Estrogen Replacement Study (KEEPS) is a prospective, randomized, controlled trial designed, using findings from basic science studies, to test the hypothesis that MHT when initiated early in menopause reduces progression of atherosclerosis. KEEPS participants are younger, healthier, and within 3 years of menopause thus matching more closely demographics of women in prior observational and epidemiological studies than women in the Women’s Health Initiative hormone trials. KEEPS will provide information relevant to the critical timing hypothesis for MHT use in reducing risk for CVD

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed