Ground-State Dynamical Correlation Functions: An Approach from Density Matrix Renormalization Group Method

A numerical approach to ground-state dynamical correlation functions from Density Matrix Renormalization Group (DMRG) is developed. Using sum rules, moments of a dynamic correlation function can be calculated with DMRG, and with the moments the dynamic correlation function can be obtained by the maximum entropy method. We apply this method to one-dimensional spinless fermion system, which can be converted to the spin 1/2 Heisenberg model in a special case. The dynamical density-density correlation function is obtained.Comment: 11 pages, latex, 4 figure

Reconstruction of Objects by Direct Demodulation

High resolution reconstruction of complicated objects from incomplete and noisy data can be achieved by solving modulation equations iteratively under physical constraints. This direct demodulation method is a powerful technique for dealing with inverse problem in general case. Spectral and image restorations and computerized tomography are only particular cases of general demodulation. It is possible to reconstruct an object in higher dimensional space from observations by a simple lower dimensional instrument through direct demodulation. Our simulations show that wide field and high resolution images of space hard X-rays and soft gamma rays can be obtained by a collimated non-position-sensitive detector without coded aperture masks.Comment: 11 pages, 6 figure

Self-consistent stability analysis of spherical shocks.

In this paper, we study self-similar solutions, and their linear stability as well, describing the flow within a spherical shell with finite thickness, expanding according to a power law of time, t q , where q>0. The shell propagates in a medium with initially uniform density and it is bounded by a strong shock wave at its outer border while the inner face is submitted to a time-dependent uniform pressure. For q=2/5, the well-known Sedov–Taylor solution is recovered. In addition, although both accelerated and decelerated shells can be unstable against dynamic perturbations, they exhibit highly different behaviors. Finally, the dispersion relation derived earlier by Vishniac (Vishniac, E.T. in Astrophys. J. 274:152, 1983) for an infinitely thin shell is obtained in the limit of an isothermal shock wave

The Cholecystectomy As A Day Case (CAAD) Score: A Validated Score of Preoperative Predictors of Successful Day-Case Cholecystectomy Using the CholeS Data Set

Background Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

Maximum entropy reconstructions of krill distribution and estimates of krill density from acoustic surveys at South Georgia, 1996-2000

This paper presents Maximum Entropy (MaxEnt) reconstructions of krill distribution and estimates of mean krill density within two survey boxes (dimensions 80 km x 100 km) north of South Georgia. The reconstructions were generated from line-transect acoustic survey data gathered in the boxes during austral summers from 1996 to 2000. Krill densities had previously been determined at approximately 0.5 km intervals along each of the ten 80 km transects in each box, providing about 1600 density estimates per box. The MaxEnt technique uses an iterative Bayesian approach to infer the most probable krill density for each of the 32 000 0.5 x 0.5 km cells in each box, taking explicit account of the spatial relationship between densities in the observed data. Despite some very large interannual and regional differences in mean krill density, the MaxEnt approach works well, providing plausible maps of krill distribution. The maps reveal some consistent 'hot spots' of krill distribution, knowledge of which could aid the understanding of mechanisms influencing krill distribution, and hence krill/predator interactions. The MaxEnt technique also yields mean krill densities for each survey, for which the confidence limits are often narrower than those determined from conventional statistical analyses

Atmospheric PSF Interpolation for Weak Lensing in Short Exposure Imaging Data

A main science goal for the Large Synoptic Survey Telescope (LSST) is to measure the cosmic shear signal from weak lensing to extreme accuracy. One difficulty, however, is that with the short exposure time ({approx_equal}15 seconds) proposed, the spatial variation of the Point Spread Function (PSF) shapes may be dominated by the atmosphere, in addition to optics errors. While optics errors mainly cause the PSF to vary on angular scales similar or larger than a single CCD sensor, the atmosphere generates stochastic structures on a wide range of angular scales. It thus becomes a challenge to infer the multi-scale, complex atmospheric PSF patterns by interpolating the sparsely sampled stars in the field. In this paper we present a new method, psfent, for interpolating the PSF shape parameters, based on reconstructing underlying shape parameter maps with a multi-scale maximum entropy algorithm. We demonstrate, using images from the LSST Photon Simulator, the performance of our approach relative to a 5th-order polynomial fit (representing the current standard) and a simple boxcar smoothing technique. Quantitatively, psfent predicts more accurate PSF models in all scenarios and the residual PSF errors are spatially less correlated. This improvement in PSF interpolation leads to a factor of 3.5 lower systematic errors in the shear power spectrum on scales smaller than {approx} 13, compared to polynomial fitting. We estimate that with psfent and for stellar densities greater than {approx_equal}1/arcmin{sup 2}, the spurious shear correlation from PSF interpolation, after combining a complete 10-year dataset from LSST, is lower than the corresponding statistical uncertainties on the cosmic shear power spectrum, even under a conservative scenario