A Convolutional Neural Network Approach to Supernova Time-Series Classification

One of the brightest objects in the universe, supernovae (SNe) are powerful explosions marking the end of a star's lifetime. Supernova (SN) type is defined by spectroscopic emission lines, but obtaining spectroscopy is often logistically unfeasible. Thus, the ability to identify SNe by type using time-series image data alone is crucial, especially in light of the increasing breadth and depth of upcoming telescopes. We present a convolutional neural network method for fast supernova time-series classification, with observed brightness data smoothed in both the wavelength and time directions with Gaussian process regression. We apply this method to full duration and truncated SN time-series, to simulate retrospective as well as real-time classification performance. Retrospective classification is used to differentiate cosmologically useful Type Ia SNe from other SN types, and this method achieves >99% accuracy on this task. We are also able to differentiate between 6 SN types with 60% accuracy given only two nights of data and 98% accuracy retrospectively.Comment: Accepted at the ICML 2022 Workshop on Machine Learning for Astrophysic

First Detection of Cosmic Microwave Background Lensing and Lyman-{\alpha} Forest Bispectrum

We present the first detection of a correlation between the Lyman-$\alpha$ forest and cosmic microwave background (CMB) lensing. For each Lyman-$\alpha$ forest in SDSS-III/BOSS DR12, we correlate the one-dimensional power spectrum with the CMB lensing convergence on the same line of sight from Planck. This measurement constitutes a position-dependent power spectrum, or a squeezed bispectrum, and quantifies the non-linear response of the Lyman-$\alpha$ forest power spectrum to a large-scale overdensity. The signal is measured at 5~$\sigma$ and is consistent with the $\Lambda$CDM expectation. We measure the linear bias of the Lyman-$\alpha$ forest with respect to the dark matter distribution, and constrain a combination of non-linear terms including the non-linear bias. This new observable provides a consistency check for the Lyman-$\alpha$ forest as a large-scale structure probe and tests our understanding of the relation between intergalactic gas and dark matter. In the future, it could be used to test hydrodynamical simulations and calibrate the relation between the Lyman-$\alpha$ forest and dark matter.Comment: 8 pages, 7 figures; accepted for publication in Phys. Rev.

Cosmology with the Roman Space Telescope -- Synergies with CMB lensing

We explore synergies between the Nancy Grace Roman Space Telescope and CMB lensing data to constrain dark energy and modified gravity scenarios. A simulated likelihood analysis of the galaxy clustering and weak lensing data from the Roman Space Telescope High Latitude Survey combined with CMB lensing data from the Simons Observatory is undertaken, marginalizing over important astrophysical effects and calibration uncertainties. Included in the modeling are the effects of baryons on small-scale clustering, scale-dependent growth suppression by neutrinos, as well as uncertainties in the galaxy clustering biases, in the intrinsic alignment contributions to the lensing signal, in the redshift distributions, and in the galaxy shape calibration. The addition of CMB lensing roughly doubles the dark energy figure-of-merit from Roman photometric survey data alone, varying from a factor of 1.7 to 2.4 improvement depending on the particular Roman survey configuration. Alternatively, the inclusion of CMB lensing information can compensate for uncertainties in the Roman galaxy shape calibration if it falls below the design goals. Furthermore, we report the first forecast of Roman constraints on a model-independent structure growth, parameterized by $\sigma_8 (z)$, and on the Hu-Sawicki f(R) gravity as well as an improved forecast of the phenomenological $(\Sigma_0,\mu_0)$ model. We find that CMB lensing plays a crucial role in constraining $\sigma_8(z)$ at z>2, with percent-level constraints forecasted out to z=4. CMB lensing information does not improve constraints on the f(R) models substantially. It does, however, increase the $(\Sigma_0,\mu_0)$ figure-of-merit by a factor of about 1.5.Comment: 19 pages, 12 figures, replaced with accepted version in MNRA

Widespread infection with homologues of human parvoviruses B19, PARV4, and human bocavirus of chimpanzees and gorillas in the wild

Infections with human parvoviruses B19 and recently discovered human bocaviruses (HBoVs) are widespread, while PARV4 infections are transmitted parenterally and prevalent specifically in injecting drug users and hemophiliacs. To investigate the exposure and circulation of parvoviruses related to B19 virus, PARV4, and HBoV in nonhuman primates, plasma samples collected from 73 Cameroonian wild-caught chimpanzees and gorillas and 91 Old World monkey (OWM) species were screened for antibodies to recombinant B19 virus, PARV4, and HBoV VP2 antigens by enzyme-linked immunosorbent assay (ELISA). Moderate to high frequencies of seroreactivity to PARV4 (63% and 18% in chimpanzees and gorillas, respectively), HBoV (73% and 36%), and B19 virus (8% and 27%) were recorded for apes, while OWMs were uniformly negative (for PARV4 and B19 virus) or infrequently reactive (3% for HBoV). For genetic characterization, plasma samples and 54 fecal samples from chimpanzees and gorillas collected from Cameroonian forest floors were screened by PCR with primers conserved within Erythrovirus, Bocavirus, and PARV4 genera. Two plasma samples (chimpanzee and baboon) were positive for PARV4, while four fecal samples were positive for HBoV-like viruses. The chimpanzee PARV4 variant showed 18% and 15% nucleotide sequence divergence in NS and VP1/2, respectively, from human variants (9% and 7% amino acid, respectively), while the baboon variant was substantially more divergent, mirroring host phylogeny. Ape HBoV variants showed complex sequence relationships with human viruses, comprising separate divergent homologues of HBoV1 and the recombinant HBoV3 species in chimpanzees and a novel recombinant species in gorillas. This study provides the first evidence for widespread circulation of parvoviruses in primates and enables future investigations of their epidemiology, host specificity, and (co)evolutionary histories

Combinations of cosmic microwave background and large-scale structure cosmological probes

Cette thèse s’intéresse aux combinaisons d’observables cosmologiques provenant des mesures du fond diffus cosmologique et des relevés de galaxies, et est basée sur l’exploitation des données du satellite Planck et du Baryon Oscillation Spectroscopic Survey (BOSS) du Sloan Digital Sky Survey. On explore l’utilisation de corrélations croisées entre les jeux de données afin de mettre en évidence de nouveaux effets et d’améliorer les contraintes statistiques sur les paramètres cosmologiques. Dans un premier temps, on mesure pour la première fois une corrélation entre le lentillage gravitationnel du fond diffus cosmologique et le spectre de puissance des fluctuations de la forêt Lyman-α des quasars. Cet effet, d’origine purement non-linéaire, est interprété comme la réponse du spectre de puissance à des grandes échelles. Il montre comment les fluctuations dans la densité en hydrogène neutre dans le milieu intergalactique sont influencées par des fluctuations à grande échelle dans la densité de matière noire. Le signal mesuré est compatible avec l’approche théorique et des simulations menées par d’autres groupes. Dans un deuxième temps, on développe un formalisme permettant une analyse conjointe de la densité de galaxies et de quasars de BOSS avec le lentillage gravitationnel du fond diffus cosmologique. La prise en compte des corrélations croisées entre ces sondes permet de diminuer les barres d’erreurs de certains paramètres cosmologiques de 20%, ce qui équivaut à augmenter la surface couverte par les relevés de presque 50%. Cette analyse est complétée par la mesure des anisotropies de température du fond diffus cosmologique afin de contraindre tous les paramètres du modèle standard ΛCDM, ainsi que les biais des galaxies. Puis on étend le modèle afin d’explorer les contraintes sur l’équation d’état de l’énergie noire et la somme des masses des neutrinosThis thesis addresses the combinations of cosmological probes from the measurements of the cosmic microwave background (CMB) and galaxy redshift surveys, and exploits data from the Planck satellite and the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey. It explores how cross-correlations between different data sets can be used to detect new signals and improve contraints on cosmological parameters. First, we measure, for the first time, the cross-correlation between gravitational lensing of the CMB and the power spectrum of the Lyman-α forest in the spectra of quasars. This effect, which emerges from purely non-linear evolution, is interpreted as the response of the power spectrum to large-scale modes. It shows how fluctuations in the density of neutral hydrogen in the intergalactic medium are affected by large-scale fluctuations in the density of dark matter. The measured signal is compatible with the theoretical approach and simulations run by another group. In a second time, we develop a formalism enabling the joint analysis of the galaxy/quasar density contrast and CMB lensing. Taking cross-correlations between these probes into account reduces error bars on some cosmological parameters by up to 20%, equivalent to an increase in the size of the survey of about 50%. This analysis is completed by CMB temperature anisotropies information in order to constrain all the parameters of the ΛCDM standard model and galaxy biases at once. Finally, it is extended to obtain contraints on the dark energy equation of state as well as the sum of the masses of neutrino

A new statistical method to analyze Morris Water Maze data using Dirichlet distribution

International audienceThe Morris Water Maze (MWM) is a behavioral test widely used in the field of neuroscience to evaluate spatial learning memory of rodents. However, the interpretation of results is often impaired by the common use of statistical tests based on independence and normal distributions that do not reflect basic properties of the test data, such as the constant-sum constraint. In this work, we propose to analyze MWM data with the Dirichlet distribution, which describes constant-sum data with minimal hypotheses, and we introduce a statistical test based on uniformity (equal amount of time spent in each quadrant of the maze) that evaluates memory impairments. We demonstrate that this test better represents MWM data and show its efficiency on simulated as well as in vivo data. Based on Dirichlet distribution, we also propose a new way to plot MWM data, showing mean values and inter-individual variability at the same time, on an easily interpretable chart. Finally, we conclude with a perspective on using Bayesian analysis for MWM data

Impact of blending on weak lensing measurements with the Vera C. Rubin Observatory

International audienceUpcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will scan the sky to unprecedented depths and detect billions of galaxies. This amount of detections will however cause the apparent superposition of galaxies on the images, called blending, and generate a new systematic error due to the confusion of sources. As consequences, the measurements of individual galaxies properties such as their redshifts or shapes will be impacted, and some galaxies will not be detected. However, galaxy shapes are key quantities, used to estimate masses of large scale structures, such as galaxy clusters, through weak gravitational lensing. This work presents a new catalog matching algorithm, called friendly, for the detection and characterization of blends in simulated LSST data for the DESC Data Challenge 2. By identifying a specific type of blends, we show that removing them from the data may partially correct the amplitude of the $\Delta\Sigma$ weak lensing profile that could be biased low by around 20% due to blending. This would result in impacting clusters weak lensing mass estimate and cosmology

Impact of blending on weak lensing measurements with the Vera C. Rubin Observatory

International audienceUpcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will scan the sky to unprecedented depths and detect billions of galaxies. This amount of detections will however cause the apparent superposition of galaxies on the images, called blending, and generate a new systematic error due to the confusion of sources. As consequences, the measurements of individual galaxies properties such as their redshifts or shapes will be impacted, and some galaxies will not be detected. However, galaxy shapes are key quantities, used to estimate masses of large scale structures, such as galaxy clusters, through weak gravitational lensing. This work presents a new catalog matching algorithm, called friendly, for the detection and characterization of blends in simulated LSST data for the DESC Data Challenge 2. By identifying a specific type of blends, we show that removing them from the data may partially correct the amplitude of the $\Delta\Sigma$ weak lensing profile that could be biased low by around 20% due to blending. This would result in impacting clusters weak lensing mass estimate and cosmology