Coherent states, constraint classes, and area operators in the new spin-foam models

Recently, two new spin-foam models have appeared in the literature, both motivated by a desire to modify the Barrett-Crane model in such a way that the imposition of certain second class constraints, called cross-simplicity constraints, are weakened. We refer to these two models as the FKLS model, and the flipped model. Both of these models are based on a reformulation of the cross-simplicity constraints. This paper has two main parts. First, we clarify the structure of the reformulated cross-simplicity constraints and the nature of their quantum imposition in the new models. In particular we show that in the FKLS model, quantum cross-simplicity implies no restriction on states. The deeper reason for this is that, with the symplectic structure relevant for FKLS, the reformulated cross-simplicity constraints, in a certain relevant sense, are now \emph{first class}, and this causes the coherent state method of imposing the constraints, key in the FKLS model, to fail to give any restriction on states. Nevertheless, the cross-simplicity can still be seen as implemented via suppression of intertwiner degrees of freedom in the dynamical propagation. In the second part of the paper, we investigate area spectra in the models. The results of these two investigations will highlight how, in the flipped model, the Hilbert space of states, as well as the spectra of area operators exactly match those of loop quantum gravity, whereas in the FKLS (and Barrett-Crane) models, the boundary Hilbert spaces and area spectra are different.Comment: 21 pages; statements about gamma limits made more precise, and minor phrasing change

Low-energy electron transport with the method of discrete ordinates

The one-dimensional discrete ordinates code ANISN was adapted to transport low energy (a few MeV) electrons. Calculated results obtained with ANISN were compared with experimental data for transmitted electron energy and angular distribution data for electrons normally incident on aluminum slabs of various thicknesses. The calculated and experimental results are in good agreement for a thin slab (0.2 of the electron range), but not for the thicker slabs (0.6 of the electron range). Calculated results obtained with ANISN were also compared with results obtained using Monte Carlo methods

Revisiting the Simplicity Constraints and Coherent Intertwiners

In the context of loop quantum gravity and spinfoam models, the simplicity constraints are essential in that they allow to write general relativity as a constrained topological BF theory. In this work, we apply the recently developed U(N) framework for SU(2) intertwiners to the issue of imposing the simplicity constraints to spin network states. More particularly, we focus on solving them on individual intertwiners in the 4d Euclidean theory. We review the standard way of solving the simplicity constraints using coherent intertwiners and we explain how these fit within the U(N) framework. Then we show how these constraints can be written as a closed u(N) algebra and we propose a set of U(N) coherent states that solves all the simplicity constraints weakly for an arbitrary Immirzi parameter.Comment: 28 page

High Frequency Multiplicative Component GARCH

This paper proposes a new way of modeling and forecasting intraday returns. We decompose the volatility of high frequency asset returns into components that may be easily interpreted and estimated. The conditional variance is expressed as a product of daily, diurnal and sto-chastic intraday volatility components. This model is applied to a comprehensive sample consisting of 10-minute returns on more than 2500 US equities. We apply a number of dif-ferent specifications. Apart from building a new model, we obtain several interesting fore-casting results. In particular, it turns out that forecasts obtained from the pooled cross section of companies seem to outperform the corresponding forecasts from company-by-company estimation

High Frequency Multiplicative Component GARCH

This paper proposes a new way of modeling and forecasting intraday returns. We decompose the volatility of high frequency asset returns into components that may be easily interpreted and estimated. The conditional variance is expressed as a product of daily, diurnal and stochastic intraday volatility components. This model is applied to a comprehensive sample consisting of 10-minute returns on more than 2500 US equities. We apply a number of different specifications. Apart from building a new model, we obtain several interesting forecasting results. In particular, it turns out that forecasts obtained from the pooled cross section of companies seem to outperform the corresponding forecasts from company-by-company estimation

Use of an Episodic Food Intake Monitoring System to Evaluate Feeding Behavior in Mice

poster abstractThe measurement of food consumption in laboratory animals is critical to studies in metabolism and obesity. Unfortunately, feeding behavior is very sensitive to the environment. Many factors such as the change of cages, diet, and human interactions can introduce undesired experimental variation. Here we describe our experiences with a commercially available episodic food intake monitoring system, the BioDAQ Monitor. This system is designed to quantitatively record feeding behavior in mice. It continuously monitors the weight of the food and uses this information to determine bout length and size. Bouts that occur soon after one another can then be defined as meals. When an animal jostles the food hopper while eating, the weight of the hopper fluctuates and eating is considered to be in progress. Once the hopper weight has been stable for a specified time, that period of feeding is considered to be concluded. The system also has the capability to assess either food or liquid choice paradigms and to directly measure the administration of orally available drugs in either the feed or the water. In addition to these functions, the system uses an environment monitor to record temperature, humidity and lighting of the room every five minutes. Here we present data showing measurements taken in hyperphagic mutant mice, altered feeding paradigms, and under different drug and protein hormone treatments. Future studies using this system will continue to focus on the hyperphagia associated obesity phenotype observed in mice upon conditional disruption of primary cilia

Precise Radial Velocities of Polaris: Detection of Amplitude Growth

We present a first results from a long-term program of a radial velocity study of Cepheid Polaris (F7 Ib) aimed to find amplitude and period of pulsations and nature of secondary periodicities. 264 new precise radial velocity measurements were obtained during 2004-2007 with the fiber-fed echelle spectrograph Bohyunsan Observatory Echelle Spectrograph (BOES) of 1.8m telescope at Bohyunsan Optical Astronomy Observatory (BOAO) in Korea. We find a pulsational radial velocity amplitude and period of Polaris for three seasons of 2005.183, 2006.360, and 2007.349 as 2K = 2.210 +/- 0.048 km/s, 2K = 2.080 +/- 0.042 km/s, and 2K = 2.406 +/- 0.018 km/s respectively, indicating that the pulsational amplitudes of Polaris that had decayed during the last century is now increasing rapidly. The pulsational period was found to be increasing too. This is the first detection of a historical turnaround of pulsational amplitude change in Cepheids. We clearly find the presence of additional radial velocity variations on a time scale of about 119 days and an amplitude of about +/- 138 m/s, that is quasi-periodic rather than strictly periodic. We do not confirm the presence in our data the variation on a time scale 34-45 days found in earlier radial velocity data obtained in 80's and 90's. We assume that both the 119 day quasi-periodic, noncoherent variations found in our data as well as 34-45 day variations found before can be caused by the 119 day rotation periods of Polaris and by surface inhomogeneities such as single or multiple spot configuration varying with the time.Comment: 15 pages, 7 figures, Accepted for publication in The Astronomical Journa

Artificial Intelligence Approach to the Determination of Physical Properties of Eclipsing Binaries. I. The EBAI Project

Achieving maximum scientific results from the overwhelming volume of astronomical data to be acquired over the next few decades will demand novel, fully automatic methods of data analysis. Artificial intelligence approaches hold great promise in contributing to this goal. Here we apply neural network learning technology to the specific domain of eclipsing binary (EB) stars, of which only some hundreds have been rigorously analyzed, but whose numbers will reach millions in a decade. Well-analyzed EBs are a prime source of astrophysical information whose growth rate is at present limited by the need for human interaction with each EB data-set, principally in determining a starting solution for subsequent rigorous analysis. We describe the artificial neural network (ANN) approach which is able to surmount this human bottleneck and permit EB-based astrophysical information to keep pace with future data rates. The ANN, following training on a sample of 33,235 model light curves, outputs a set of approximate model parameters (T2/T1, (R1+R2)/a, e sin(omega), e cos(omega), and sin i) for each input light curve data-set. The whole sample is processed in just a few seconds on a single 2GHz CPU. The obtained parameters can then be readily passed to sophisticated modeling engines. We also describe a novel method polyfit for pre-processing observational light curves before inputting their data to the ANN and present the results and analysis of testing the approach on synthetic data and on real data including fifty binaries from the Catalog and Atlas of Eclipsing Binaries (CALEB) database and 2580 light curves from OGLE survey data. [abridged]Comment: 52 pages, accepted to Ap