Bias in particle tracking acceleration measurement

We investigate sources of error in acceleration statistics from Lagrangian Particle Tracking (LPT) data and demonstrate techniques to eliminate or minimise bias errors introduced during processing. Numerical simulations of particle tracking experiments in isotropic turbulence show that the main sources of bias error arise from noise due to position uncertainty and selection biases introduced during numerical differentiation. We outline the use of independent measurements and filtering schemes to eliminate these biases. Moreover, we test the validity of our approach in estimating the statistical moments and probability densities of the Lagrangian acceleration. Finally, we apply these techniques to experimental particle tracking data and demonstrate their validity in practice with comparisons to available data from literature. The general approach, which is not limited to acceleration statistics, can be applied with as few as two cameras and permits a substantial reduction in the spatial resolution and sampling rate required to adequately measure statistics of Lagrangian acceleration

Producing high fidelity single photons with optimal brightness via waveguided parametric down-conversion

Parametric down-conversion (PDC) offers the possibility to control the fabrication of non-Gaussian states such as Fock states. However, in conventional PDC sources energy and momentum conservation introduce strict frequency and photon number correlations, which impact the fidelity of the prepared state. In our work we optimize the preparation of single-photon Fock states from the emission of waveguided PDC via spectral filtering. We study the effect of correlations via photon number resolving detection and quantum interference. Our measurements show how the reduction of mixedness due to filtering can be evaluated. Interfering the prepared photon with a coherent state we establish an experimentally measured fidelity of the produced target state of 78%.Comment: 15 pages, 10 Figures, published versio

Simple connectome inference from partial correlation statistics in calcium imaging

In this work, we propose a simple yet effective solution to the problem of connectome inference in calcium imaging data. The proposed algorithm consists of two steps. First, processing the raw signals to detect neural peak activities. Second, inferring the degree of association between neurons from partial correlation statistics. This paper summarises the methodology that led us to win the Connectomics Challenge, proposes a simplified version of our method, and finally compares our results with respect to other inference methods

Cosmic Shear Analysis with CFHTLS Deep data

We present the first cosmic shear measurements obtained from the T0001 release of the Canada-France-Hawaii Telescope Legacy Survey. The data set covers three uncorrelated patches (D1, D3 and D4) of one square degree each observed in u*, g', r', i' and z' bands, out to i'=25.5. The depth and the multicolored observations done in deep fields enable several data quality controls. The lensing signal is detected in both r' and i' bands and shows similar amplitude and slope in both filters. B-modes are found to be statistically zero at all scales. Using multi-color information, we derived a photometric redshift for each galaxy and separate the sample into medium and high-z galaxies. A stronger shear signal is detected from the high-z subsample than from the low-z subsample, as expected from weak lensing tomography. While further work is needed to model the effects of errors in the photometric redshifts, this results suggests that it will be possible to obtain constraints on the growth of dark matter fluctuations with lensing wide field surveys. The various quality tests and analysis discussed in this work demonstrate that MegaPrime/Megacam instrument produces excellent quality data. The combined Deep and Wide surveys give sigma_8= 0.89 pm 0.06 assuming the Peacock & Dodds non-linear scheme and sigma_8=0.86 pm 0.05 for the halo fitting model and Omega_m=0.3. We assumed a Cold Dark Matter model with flat geometry. Systematics, Hubble constant and redshift uncertainties have been marginalized over. Using only data from the Deep survey, the 1 sigma upper bound for w_0, the constant equation of state parameter is w_0 < -0.8.Comment: 14 pages, 16 figures, accepted A&

Supernova Simulations and Strategies For the Dark Energy Survey

We present an analysis of supernova light curves simulated for the upcoming Dark Energy Survey (DES) supernova search. The simulations employ a code suite that generates and fits realistic light curves in order to obtain distance modulus/redshift pairs that are passed to a cosmology fitter. We investigated several different survey strategies including field selection, supernova selection biases, and photometric redshift measurements. Using the results of this study, we chose a 30 square degree search area in the griz filter set. We forecast 1) that this survey will provide a homogeneous sample of up to 4000 Type Ia supernovae in the redshift range 0.05<z<1.2, and 2) that the increased red efficiency of the DES camera will significantly improve high-redshift color measurements. The redshift of each supernova with an identified host galaxy will be obtained from spectroscopic observations of the host. A supernova spectrum will be obtained for a subset of the sample, which will be utilized for control studies. In addition, we have investigated the use of combined photometric redshifts taking into account data from both the host and supernova. We have investigated and estimated the likely contamination from core-collapse supernovae based on photometric identification, and have found that a Type Ia supernova sample purity of up to 98% is obtainable given specific assumptions. Furthermore, we present systematic uncertainties due to sample purity, photometric calibration, dust extinction priors, filter-centroid shifts, and inter-calibration. We conclude by estimating the uncertainty on the cosmological parameters that will be measured from the DES supernova data.Comment: 46 pages, 30 figures, resubmitted to ApJ as Revision 2 (final author revision), which has subtle editorial differences compared to the published paper (ApJ, 753, 152). Note that this posting includes PDF only due to a bug in either the latex macros or the arXiv submission system. The source files are available in the DES document database: http://des-docdb.fnal.gov/cgi-bin/ShowDocument?docid=624