In this work, we show that when supernova Ia (SN Ia) data sets are used to put constraints on the free parameters of inhomogeneous models, certain extra information regarding the light-curve fitter used in the supernovae Ia luminosity fluxes processing should be taken into account. We found that the size of the void as well as other parameters of these models might be suffering extra degenerations or additional systematic errors due to the fitter. A recent proposal to relieve the tension between the results from Planck satellite and SNe Ia is re-analyzed in the framework of these subjects.
There is substantial and growing observational evidence from the normalized luminosity density in the near-infrared that the local universe is under-dense on scales of several hundred Megaparsecs. We test whether our parameterization of the observational data of such a "void" is compatible with the latest supernovae type Ia data and with constraints from line-of-sight peculiar velocity motions of galaxy clusters with respect to the cosmic microwave background rest frame, known as the linear kinematic Sunyaev-Zel'dovich (kSZ) effect. Our study is based on the large local void (LLV) radial profi…
In this work we utilise the most recent publicly available type Ia supernova (SN Ia) compilations and implement a well formulated cosmological model based on Lemaître-Tolman-Bondi metric in presence of cosmological constant $Λ$ ($Λ$LTB) to test for signatures of large local inhomogeneities at $z\leq0.15$. Local underdensities in this redshift range have been previously found based on luminosity density (LD) data and galaxy number counts. Our main constraints on the possible local void using the Pantheon SN Ia dataset are: redshift size of $z_{\rm size}=0.068^{+0.021}_{-0.030}$; density contras…
We examine the cosmological implications of measurements of the void-galaxy cross-correlation at redshift $z=0.57$ combined with baryon acoustic oscillation (BAO) data at $0.1<z<2.4$. We find direct evidence of the late-time acceleration due to dark energy at $>10σ$ significance from these data alone, independent of the cosmic microwave background and supernovae. Using a nucleosynthesis prior on $Ω_bh^2$, we measure the Hubble constant to be $H_0=72.3\pm1.9\;{\rm km\,s}^{-1}{\rm Mpc}^{-1}$ from BAO+voids at $z<2$, and $H_0=69.0\pm1.2\;{\rm km\,s}^{-1}{\rm Mpc}^{-1}$ when adding Lyman-$α$ BAO a…
We test the cosmological implications of a varying absolute magnitude of Type Ia supernovae using the Pantheon compilation, by reconstructing different phenomenological approaches that could justify a varying absolute magnitude, but also approaches based on cosmic voids, modified gravity models and a binning scheme. In all the cases considered in this work, we find good agreement with the expected values of the standard $Λ$CDM model and no evidence of new physics.
Few statements in cosmology can be made without assuming a cosmological model within which to interpret data. Statements about cosmic acceleration are no exception to this rule, and the inferred positive volume acceleration of our Universe often quoted in the literature is valid in the context of the standard Friedmann-Lemaitre-Robertson-Walker (FLRW) class of space-times. Using the Joint Light-curve Analysis (JLA) catalogue of type Ia supernovae (SNIa), we examine the fit of a class of exact scaling solutions with dynamical spatial curvature formulated in the framework of a scalar averaging s…
We review the needs of the supernova community for improvements in survey coordination and data sharing that would significantly boost the constraints on dark energy using samples of Type Ia supernovae from the Vera C. Rubin Observatories, the \textit{Nancy Grace Roman Space Telescope}, and the \textit{Euclid} Mission. We discuss improvements to both statistical and systematic precision that the combination of observations from these experiments will enable. For example, coordination will result in improved photometric calibration, redshift measurements, as well as supernova distances. We also…
A potential solution to the Hubble tension is the hypothesis that the Milky Way is located near the center of a matter underdensity. We model this scenario through the Lemaître-Tolman-Bondi formalism with the inclusion of a cosmological constant ($Λ$LTB) and consider a generalized Gaussian parametrization for the matter density profile. We constrain the underdensity and the background cosmology with a combination of data sets: the Pantheon Sample of type Ia supernovae (both the full catalogue and a redshift-binned version of it), a collection of baryon acoustic oscillations data points and the…
Redshift measurement has always been a constant need in modern astronomy and cosmology. And as new surveys have been providing an immense amount of data on astronomical objects, the need to process such data automatically proves to be increasingly necessary. In this article, we use simulated data from the Dark Energy Survey, and from a pipeline originally created to classify supernovae, we developed a linear regression algorithm optimized through novel automated machine learning (AutoML) frameworks achieving an error score better than ordinary data pre-processing methods when compared with oth…
Using the Pantheon data set of Type Ia supernovae, a recent publication (R20 in this work) reports a $~2σ$ detection of oscillations in the expansion history of the universe. Applying the R20 methodology to simulated Pantheon data, we determine that these oscillations likely arise from analysis artifacts. The uneven spacing of Type Ia supernovae in redshift space and the complicated analysis method of R20 impose a structured throughput function. When analyzed with the R20 prescription, about $11\%$ of artificial $Λ$CDM data sets produce a stronger oscillatory signal than the actual Pantheon da…
Both multi-messenger astronomy and new high-throughput wide-field surveys require flexible tools for the selection and analysis of astrophysical transients. We here introduce the Alert Management, Photometry and Evaluation of Lightcurves (AMPEL) system, an analysis framework designed for high-throughput surveys and suited for streamed data. AMPEL combines the functionality of an alert broker with a generic framework capable of hosting user-contributed code, that encourages provenance and keeps track of the varying information states that a transient displays. The latter concept includes inform…
We present a novel method of classifying Type Ia supernovae using convolutional neural networks, a neural network framework typically used for image recognition. Our model is trained on photometric information only, eliminating the need for accurate redshift data. Photometric data is pre-processed via 2D Gaussian process regression into two-dimensional images created from flux values at each location in wavelength-time space. These "flux heatmaps" of each supernova detection, along with "uncertainty heatmaps" of the Gaussian process uncertainty, constitute the dataset for our model. This prepr…
We present BVRI and unfiltered light curves of 93 Type Ia supernovae (SNe Ia) from the Lick Observatory Supernova Search (LOSS) follow-up program conducted between 2005 and 2018. Our sample consists of 78 spectroscopically normal SNe Ia, with the remainder divided between distinct subclasses (three SN 1991bg-like, three SN 1991T-like, four SNe Iax, two peculiar, and three super-Chandrasekhar events), and has a median redshift of 0.0192. The SNe in our sample have a median coverage of 16 photometric epochs at a cadence of 5.4 days, and the median first observed epoch is ~4.6 days before maximum…
