vsgoftest: An R Package for Goodness-of-Fit Testing Based on Kullback-Leibler Divergence

The R package vsgoftest performs goodness-of-fit (GOF) tests, based on Shannon entropy and Kullback-Leibler divergence, developed by Vasicek (1976) and Song (2002), of various classical families of distributions. The so-called Vasicek-Song (VS) tests are intended to be applied to continuous data - typically drawn from a density distribution, even including ties. Their excellent properties - they exhibit high power in a large variety of situations, make them relevant alternatives to classical GOF tests in any domain of application requiring statistical processing. The theoretical framework of VS tests is summarized and followed by a detailed description of the different features of the package. The power and computational time performances of VS tests are studied through their comparison with other GOF tests. Application to real datasets illustrates the easy-to-use functionalities of the vsgoftest package

Matrix Product State description of the Halperin States

Many fractional quantum Hall states can be expressed as a correlator of a given conformal field theory used to describe their edge physics. As a consequence, these states admit an economical representation as an exact Matrix Product States (MPS) that was extensively studied for the systems without any spin or any other internal degrees of freedom. In that case, the correlators are built from a single electronic operator, which is primary with respect to the underlying conformal field theory. We generalize this construction to the archetype of Abelian multicomponent fractional quantum Hall wavefunctions, the Halperin states. These latest can be written as conformal blocks involving multiple electronic operators and we explicitly derive their exact MPS representation. In particular, we deal with the caveat of the full wavefunction symmetry and show that any additional SU(2) symmetry is preserved by the natural MPS truncation scheme provided by the conformal dimension. We use our method to characterize the topological order of the Halperin states by extracting the topological entanglement entropy. We also evaluate their bulk correlation length which are compared to plasma analogy arguments.Comment: 23 pages, 16 figure

Designing an optimal LSST deep drilling program for cosmology with type Ia supernovae

The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) is forecast to collect a large sample of Type Ia supernovae (SNe Ia) expected to be instrumental in unveiling the nature of dark energy. The feat, however, requires accurately measuring the two components of the Hubble diagram, distance modulus and redshift. Distance is estimated from SN Ia parameters extracted from light-curve fits, where the average quality of light curves is primarily driven by survey parameters. An optimal observing strategy is thus critical for measuring cosmological parameters with high accuracy. We present in this paper a three-stage analysis to assess the impact of the deep drilling (DD) strategy parameters on three critical aspects of the survey: redshift completeness, the number of wellmeasured SNe Ia, and cosmological measurements. We demonstrate that the current DD survey plans (internal LSST simulations) are characterized by a low completeness (z ∼ 0.55–0.65), and irregular and low cadences (several days), which dramatically decrease the size of the well-measured SN Ia sample. We propose a method providing the number of visits required to reach higher redshifts. We use the results to design a set of optimized DD surveys for SN Ia cosmology taking full advantage of spectroscopic resources for host galaxy redshift measurements. The most accurate cosmological measurements are achieved with deep rolling surveys characterized by a high cadence (1 day), a rolling strategy (at least two seasons of observation per field), and ultradeep (z 0.8) and deep (z 0.6) fields. A deterministic scheduler including a gap recovery mechanism is critical to achieving a high-quality DD survey

Virulent Shigella flexneri subverts the host innate immune response through manipulation of antimicrobial peptide gene expression

Antimicrobial factors are efficient defense components of the innate immunity, playing a crucial role in the intestinal homeostasis and protection against pathogens. In this study, we report that upon infection of polarized human intestinal cells in vitro, virulent Shigella flexneri suppress transcription of several genes encoding antimicrobial cationic peptides, particularly the human β-defensin hBD-3, which we show to be especially active against S. flexneri. This is an example of targeted survival strategy. We also identify the MxiE bacterial regulator, which controls a regulon encompassing a set of virulence plasmid-encoded effectors injected into host cells and regulating innate signaling, as being responsible for this dedicated regulatory process. In vivo, in a model of human intestinal xenotransplant, we confirm at the transcriptional and translational level, the presence of a dedicated MxiE-dependent system allowing S. flexneri to suppress expression of antimicrobial cationic peptides and promoting its deeper progression toward intestinal crypts. We demonstrate that this system is also able to down-regulate additional innate immunity genes, such as the chemokine CCL20 gene, leading to compromised recruitment of dendritic cells to the lamina propria of infected tissues. Thus, S. flexneri has developed a dedicated strategy to weaken the innate immunity to manage its survival and colonization ability in the intestine