Bayesian inference of petrophysical properties with generative spectral induced polarization models

Mechanistic induced polarization (IP) models describe the relationships between the intrinsic properties of geomaterials and their frequency-dependent complex conductivity spectra. However, the uncertainties associated with estimating petrophysical properties from IP data are still poorly understood. Therefore, practitioners rarely use mechanistic models to interpret actual IP data. We propose a framework for critically assessing any IP model's sensitivity and parameter estimation limitations. The framework consists of a conditional variational autoencoder (CVAE), an unsupervised Bayesian neural network specializing in data dimension reduction and generative modeling. We train the CVAE on the IP signatures of synthetic mixtures of metallic mineral inclusions in electrolyte-filled host geomaterials and describe the effect of data transformations on the model. First, the CVAE's Jacobian reveals the relative importance of each petrophysical property for generating spectral IP data. The most critical parameters are the conductivity of the host, the volumetric content of the inclusions, the characteristic length of the inclusions, and the permittivity of the host. The inclusions' diffusion coefficient, permittivity, and conductivity, as well as the host's diffusion coefficient, only have marginal importance for generative IP modeling. A parameter estimation experiment yields the standardized accuracy of petrophysical properties using various model constraints scenarios and corroborates the sensitivity analysis results. Finally, we visualize the effects of data transformations and model constraints on the petrophysical parameter space. We conclude that a common logarithm data transformation yields optimal parameter estimation results and that constraining the electrochemical properties of the geomaterial improves estimates of the characteristic length of its metallic inclusions and vice versa.Comment: 31 pages, 12 figures, 1 table. Original manuscript submitted to SEG Geophysics for review. For associated code, see https://doi.org/10.5281/zenodo.694865

Recherche et caractérisation de systèmes binaires dont l'une des composantes est de faible masse

Nous présentons la découverte de quatorze nouveaux systèmes binaires ayant une séparation supérieure à 250 UA et dont au moins l'une des composantes est une naine M ou une naine L. Ces systèmes ont d'abord été identifiés en cherchant des objets ayant un mouvement propre commun autour d'étoiles connues possédant un mouvement propre élevé, grâce à une corrélation croisée de grands relevés du ciel dans l'infrarouge proche (2MASS, SDSS et SIMP). Un suivi astrométrique, afin de confirmer le mouvement propre commun, a été réalisé sur toutes les cibles avec la caméra SIMON et/ou la caméra CPAPIR à l'Observatoire du Mont-Mégatic (OMM) ou à l'Observatoire interaméricain du Cerro Tololo (CTIO). Un suivi spectroscopique a aussi été effectué sur la plupart des compagnons avec GMOS ou GNIRS à Gemini afin de déterminer leurs types spectraux. La probabilité que deux objets forment un système binaire par hasard a été évaluée afin de s'assurer que les couples candidats que nous présentons soient réellement liés.Un de nos nouveaux systèmes a un compagnon de masse sous-stellaire : 2M1259+1001 (L4.5). L'étude des systèmes que nous avons découverts pourra, entre autre, nous aider à mieux comprendre les mécanismes de formation des étoiles de très faible masse et des naines brunes.We report the discovery of 14 new low-mass binary systems containing mid-M to mid-L dwarf companions with a separation larger than 250 AU. These systems were first identified by searching for common proper motion sources in the vicinity of known high proper motion stars, based on a cross-correlation of wide area near-infrared surveys (2MASS, SDSS, and SIMP). An astrometric follow-up, for common proper motion confirmation, was made with SIMON and/or CPAPIR at the Observatoire du Mont-Mégantic (OMM) and Cerro Tololo Inter-American Observatory (CTIO) telescopes for most of the candidates identified. A spectroscopic follow-up was also made with GMOS or GNIRS at Gemini to determine their spectral types. Statistical arguments are provided to show that all of the systems we report here are very likely to be truly bound. One of the new systems we discovered has a brown dwarf companion: 2M1259+1001 (L4.5). The study of the new systems we have discovered will be useful to help us better understand how very low mass stars and brown dwarfs form

MADGene: retrieval and processing of gene identifier lists for the analysis of heterogeneous microarray datasets

Summary: MADGene is a software environment comprising a web-based database and a java application. This platform aims at unifying gene identifiers (ids) and performing gene set analysis. MADGene allows the user to perform inter-conversion of clone and gene ids over a large range of nomenclatures relative to 17 species. We propose a set of 23 functions to facilitate the analysis of gene sets and we give two microarray applications to show how MADGene can be used to conduct meta-analyses

WEIRD: Wide-orbit Exoplanet search with InfraRed Direct imaging

We report results from the Wide-orbit Exoplanet search with InfraRed Direct imaging (WEIRD), a survey designed to search for Jupiter-like companions on very wide orbits (1000 to 5000 AU) around young stars ($<$120 Myr) that are known members of moving groups in the solar neighborhood ($<$70 pc). Sharing the same age, distance, and metallicity as their host while being on large enough orbits to be studied as "isolated" objects make such companions prime targets for spectroscopic observations and valuable benchmark objects for exoplanet atmosphere models. The search strategy is based on deep imaging in multiple bands across the near-infrared domain. For all 177 objects of our sample, $z_{ab}^\prime$, $J$, [3.6] and [4.5] images were obtained with CFHT/MegaCam, GEMINI/GMOS, CFHT/WIRCam, GEMINI/Flamingos-2, and $Spitzer$/IRAC. Using this set of 4 images per target, we searched for sources with red $z_{ab}^\prime$ and $[3.6]-[4.5]$ colors, typically reaching good completeness down to 2Mjup companions, while going down to 1Mjup for some targets, at separations of $1000-5000$ AU. The search yielded 4 candidate companions with the expected colors, but they were all rejected through follow-up proper motion observations. Our results constrain the occurrence of 1-13 Mjup planetary-mass companions on orbits with a semi-major axis between 1000 and 5000 AU at less than 0.03, with a 95\% confidence level.Comment: 55 pages, 16 figures, accepted to A

Constraints on the occurrence and distribution of 1--20 \mj\ companions to stars at separations of 5--5000\,au from a compilation of direct imaging surveys

We present the first statistical analysis of exoplanet direct imaging surveys combining adaptive optics imaging at small separations with deep seeing-limited observations at large separations allowing us to study the entire orbital separation domain from 5 to 5000~au simultaneously. Our sample of 344 stars includes only confirmed members of nearby young associations and is based on all AO direct-imaging detection limits readily available online, with addition of our own previous seeing limited surveys. Assuming that the companion distribution in mass and semi-major axis follows a power law distribution and adding a dependence on the mass of the host star, such as $d^2n\propto fM^{\alpha}a^{\beta} (M_\star/M_{\odot})^{\gamma}$d$M$d$a$, we constrain the parameters to obtained $\alpha=-0.18^{+0.77}_{-0.65}$, $\beta=-1.43^{+0.23}_{-0.24}$, and $\gamma=0.62^{+0.56}_{-0.50}$,at a 68\% confidence level, and we obtain $f=0.11^{+0.11}_{-0.05}$, for the overall planet occurrence rate for companions with masses between 1 to 20~\mj\ in the range 5--5000~au. Thus, we find that occurrence of companions is negatively correlated with semi-major axis and companion mass (marginally) but is positively correlated with the stellar host mass. Our inferred mass distribution is in good agreement with other distributions found previously from direct imaging surveys for planets and brown dwarfs, but is shallower as a function of mass than the distributions inferred by radial velocity surveys of gas giants in the 1--3\,au range. This may suggest that planets at these wide and very-wide separations represent the low-mass tail of the brown dwarfs and stellar companion distribution rather than an extension of the distribution of the inner planets.Comment: 26 pages, 8 figures Accepted to Astronomical Journal Updated Table

Bayesian analysis to identify new star candidates in nearby young stellar kinematic groups

We present a new method based on a Bayesian analysis to identify new members of nearby young kinematic groups. The analysis minimally takes into account the position, proper motion, magnitude and color of a star, but other observables can be readily added (e.g. radial velocity, distance). We use this method to find new young low-mass stars in the \beta Pictoris (\beta PMG) and AB Doradus (ABDMG) moving groups and in the TW Hydrae (TWA), Tucana-Horologium (THA), Columba, Carina and Argus associations. Starting from a sample of 758 mid-KM (K5V-M5V) stars showing youth indicators such as H\alpha\ and X-ray emission, our analysis yields 215 new highly probable low-mass members of the kinematic groups analyzed. One is in TWA, 37 in \beta PMG, 17 in THA, 20 in Columba, 6 in Carina, 50 in Argus, 33 in ABDMG, and the remaining 51 candidates are likely young but have an ambiguous membership to more than one association. The false alarm rate for new candidates is estimated to be 5% for \beta PMG and TWA, 10% for THA, Columba, Carina and Argus, and 14% for ABDMG. Our analysis confirms the membership of 58 stars proposed in the literature. Firm membership confirmation of our new candidates will require measurement of their radial velocity (predicted by our analysis), parallax and lithium 6708 {\AA} equivalent width. We have initiated these follow-up observations for a number of candidates and we have identified two stars (2MASSJ0111+1526, 2MASSJ0524-1601) as very strong candidate members of the \beta PMG and one strong candidate member (2MASSJ0533-5117) of the THA; these three stars have radial velocity measurements confirming their membership and lithium detections consistent with young age. Finally, we proposed that six stars should be considered as new bona fide members of \beta PMG and ABDMG, one of which being first identified in this work, the others being known candidates from the literature.Comment: Accepted for publication in Ap

WEIRD: Wide-orbit Exoplanet Search with InfraRed Direct Imaging

We report results from the Wide-orbit Exoplanet search with InfraRed Direct imaging, or WEIRD, a survey designed to search for Jupiter-like companions on very wide orbits (1000–5000 au) around young stars (<120 Myr) that are known members of moving groups in the solar neighborhood (<70 pc). Companions that share the same age, distance, and metallicity as their host while being on large enough orbits to be studied as "isolated" objects make prime targets for spectroscopic observations, and they are valuable benchmark objects for exoplanet atmosphere models. The search strategy is based on deep imaging in multiple bands across the near-infrared domain. For all 177 objects of our sample, z_(ab)', J, [3.6], and [4.5] images were obtained with CFHT/MegaCam, GEMINI/GMOS, CFHT/WIRCam, GEMINI/Flamingos-2, and Spitzer/IRAC. Using this set of four images per target, we searched for sources with red z_(ab)' and [3.6]–[4.5] colors, typically reaching good completeness down to 2 M_(Jup) companions, while going down to 1 M_(Jup) for some targets, at separations of 1000–5000 au. The search yielded four candidate companions with the expected colors, but they were all rejected through follow-up proper motion observations. Our results constrain the occurrence of 1–13 M_(Jup) planetary-mass companions on orbits with a semimajor axis between 1000 and 5000 au at less than 0.03, with a 95% confidence level

Meta-analysis of muscle transcriptome data using the MADMuscle database reveals biologically relevant gene patterns

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc.</p> <p>Description</p> <p>We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (<it>Drosophila melanogaster, Caenorhabditis elegans</it>) and vertebrates (<it>Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus</it>). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies.</p> <p>Conclusions</p> <p>Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.</p