arXiv subjects

Madeleine Ginolin

Publications and source records attributed to Madeleine Ginolin.

7 recordsLinked to original sources

arXiv2026

On the origin of the environmental step: A BayeSN view of the ZTF SN Ia DR2

Astrophysical variabilities of Type Ia supernovae (SNe Ia), such as their link with their birth environment, are now one of the leading sources of systematic uncertainties on the measurement of the dark energy equation-of-state parameter $w$. Population studies of SNe Ia, using large samples, give precious insights into these variabilities. We analyse a volume-limited subsample of the ZTF SN Ia DR2 with BayeSN, a hierarchical Bayesian model for SN Ia SEDs. We investigate the distributions of SN Ia light curve parameters and their link with SN environment. Using a new training of BayeSN released in a companion paper, we find a smaller scatter of Hubble residuals compared to SALT. We then investigate the magnitude step, which accounts for the correlation between SN Ia standardised absolute magnitude and host environments. We find a posteriori steps of $0.103\pm0.010$ mag (a $10.1\sigma$ difference from 0) when using global stellar mass as an environmental proxy, and $0.086\pm0.010$ mag ($8.3\sigma$) when using local colour, in accordance with steps computed using SALT light curve fits. This confirms that the large step seen in the ZTF SN Ia DR2 data was not due to the SALT fit or the associated standardisation process. We then investigate the origin of the step, using a BayeSN model which accounts for both an intrinsic magnitude step and differing dust properties with the SN environment. We find a $0.103\pm0.018$ mag ($5.6\sigma$) step in global mass and a $0.085\pm0.019$ mag ($4.5\sigma$) step in local colour. The means of the $R_V$ distribution are similar between different host environments, with $\Delta\mathbb{E}(R_V)\leq0.2$ across all environment proxies, with significances ranging from $0.6\sigma$ to $1.2\sigma$. This is a strong signal of the existence of an intrinsic dependence of SN Ia absolute magnitude on environment.

astro-ph.CO↗

arXiv2026

Illuminating the Local Universe: Large-Scale Structure from ZTF Type Ia Supernovae

Within the volume-limited subsample at $z<0.06$ of the Zwicky Transient Facility (ZTF) DR2 sample, we confirm a statistically significant excess of Type Ia supernovae (SNe Ia) at $z \simeq 0.02$-$0.04$, previously reported but not explained by survey selection effects. Forward simulations assuming a uniform volumetric SN Ia rate and realistic ZTF detection efficiencies fail to reproduce the feature at the $5$-$7σ$ level. We also detect an excess in the rates compared to our survey simulations at $z \simeq 0.08$ and $0.14$, albeit at smaller significance. To investigate the origin of these inhomogeneities, we compare the observed SN distribution to constrained reconstructions of the local matter density field from the Manticore project, based on Bayesian forward modelling of the 2M++ galaxy catalogue. While SN overdensities are spatially associated with prominent nearby structures such as the Perseus, Coma, and Hercules superclusters, the amplitude of the SN excesses significantly exceeds that expected from matter overdensities alone. By reconstructing a redshift-dependent volumetric SN Ia rate, we find that local enhancements can reach factors of two to five within specific clusters, while the sample-averaged rate remains consistent with previous low-redshift measurements. These results indicate that the SN Ia rate is not a linear tracer of the underlying matter density and suggest a strong environmental dependence in dense structures. We discuss possible physical origins and highlight the implications for low-redshift SN cosmology, including correlated peculiar velocities and additional covariance beyond standard linear corrections.

astro-ph.CO↗

arXiv2026

FlowSN: Neural Simulation-Based Inference under Realistic Selection Effects applied to Supernova Cosmology

We present FlowSN, a statistical framework using simulation-based inference (SBI) with normalising flows to account for selection effects in observational astronomy. Failure to account for selection effects can lead to biased inference on global parameters. An example is Malmquist bias, where detection limits result in a sample skewed towards brighter objects. In Type Ia supernova (SN Ia) cosmology, these selection effects can systematically shift the inferred posterior distributions of cosmological parameters, necessitating the development of robust statistical frameworks to account for the biases. SBI enables us to implicitly learn probability distributions that are analytically intractable to calculate. In this work, we introduce a novel approach that employs a normalising flow to learn the non-analytic selected SN likelihood for a given survey from forward simulations, independent of the assumed cosmological model. The resulting likelihood approximation is incorporated into a hierarchical Bayesian framework and posterior sampling is performed using Hamiltonian Monte Carlo to obtain constraints on cosmological parameters conditioned on the observed data. The modular learnt likelihood approximation can be reused without retraining to evaluate different cosmological models, providing a key advantage over other SBI approaches. We demonstrate the performance of this methodology by training and testing the SBI technique using realistic LSST-like SNANA simulations for the first time. Our FlowSN approach yields accurate posterior estimates on cosmological parameters, including the dark energy equation of state $w_0$, that are an order of magnitude less biased than those obtained with conventional techniques and also exhibit improved frequentist calibration.

astro-ph.CO↗

arXiv2026

Lightcurve Modelling of 2,205 ZTF DR2 Type~Ia Supernovae: Implications for SN Ia Physics and Cosmology

We fit the multi-band light curves of 2,205 Type Ia supernovae (SNe~Ia) from the Zwicky Transient Facility DR2 with a one-zone radioactive decay model with a phenomenological addition to include Fe recombination physics. We find a strong correlation between inferred nickel mass and SALT2 stretch, which within our simplified modelling is linked to larger ejecta masses providing longer diffusion times, providing a physical basis for the brighter-slower relation. SN~Ia in low-mass hosts ($\log_{10}(M_*/M_\odot) < 10$) produce $12\%$ more $^{56}$Ni than those in high-mass hosts ($\Delta M_{\rm Ni} = 0.13~M_\odot$), linking the host-galaxy mass step to ejecta properties and hinting at metallicity or age-dependent burning efficiencies. This suggests that standardisation based on physical parameters may remove the mass-step. SN~1991T-like events show higher ejecta masses (median $1.64~M_\odot$ vs. $1.38~M_\odot$ for normals) and produce $30\%$ more $^{56}$Ni, with $84\%$ having super-Chandrasekhar masses. Through Hierarchical modelling of $902$ SNe ($z \leq 0.06$), we find thermonuclear supernovae can be well described by a Gaussian distribution in ejecta mass and nickel mass with $\mu_{\rm ej} = 1.26 \pm 0.01~M_\odot$ ($\sigma_{\rm ej} = 0.33 \pm 0.01~M_\odot$) and $\mu_{\rm Ni} = 0.64 \pm 0.06~M_\odot$ ($\sigma_{\rm Ni} = 0.42 \pm 0.02~M_\odot$), respectively. This leads to inferred fractions of $43 \pm 2\%$ sub-$M_{\rm Ch}$ ($<1.2~M_\odot$), $34 \pm 1\%$ near-$M_{\rm Ch}$ ($1.2$--$1.5~M_\odot$), and $24 \pm 2\%$ super-$M_{\rm Ch}$ ($>1.5~M_\odot$) events. This work provides a step towards holistic physical characterization of the local SN~Ia population, reinforcing the physical basis of SN~Ia standardization while quantifying diversity and environmental dependencies critical for understanding progenitor physics and mitigating systematics in precision cosmology.

astro-ph.HE↗

arXiv2025

ZTF SN Ia DR2 follow-up: Characterization of subluminous Type Ia supernovae in the ZTF DR2 full sample

The Zwicky Transient Facility Data Release 2 (ZTF DR2) includes a total of 3,628 Type Ia supernovae (SNe~Ia), providing the largest and most complete sample of spectroscopically confirmed SNe~Ia at low redshift to date. In this paper, we present a photometric and spectroscopic analysis of 124 subluminous SNe~Ia, the largest sample of spectroscopically classified subluminous SNe~Ia observed with a single instrument, comprising 87 91bg-like, 12 86G-like, 18 04gs-like, and 7 02es-like events. We complement the published DR2 SALT2 light-curve parameters with new parameters obtained using template-based fits from SNooPy. Expansion velocities and pseudo-equivalent widths pEW of key spectral features are measured using Spextractor, and spectral averages are constructed for each subluminous subtype, binned by phase. We also analyze the host galaxy environments, both global and local, in terms of $g - z$ color, stellar mass, and directional light radius $d_{DLR}$. We find that all subluminous SNe~Ia (except the 02es-like subtype) are intrinsically red. This is evident by separating extrinsic from intrinsic color components. Since SALT2 is not trained on subluminous SNe~Ia, it compensates for their redder colors by inflating the $c$ parameter, thus extending the luminosity-width relation to negative values of x1. As expected, all subluminous SNe~Ia fall within the Cool region of the Branch et al. (2006) diagram, with the exception of 02es-like events, which show lower Si II 5972 pEW values. All subluminous subtypes tend to occur in more massive, redder host galaxies, and in the reddest local environments. Notably, 91bg- and 86G-like SNe~Ia explode at significantly larger normalized galactocentric distances. Finally, we identify the $pEW$ of the blended Ti II+Si II+Mg II absorption feature at 4300~A, along with s_BV, as robust and sufficient indicators for subclassifying subluminous SNe~Ia.

astro-ph.HE↗

arXiv2024

ZTF SN Ia DR2: Overview

We present the first homogeneous release of several thousand Type Ia supernovae (SNe Ia), all having spectroscopic classification, and spectroscopic redshifts for half the sample. This release, named the "DR2", contains 3628 nearby (z < 0.3) SNe Ia discovered, followed and classified by the Zwicky Transient Facility survey between March 2018 and December 2020. Of these, 3000 have good-to-excellent sampling and 2667 pass standard cosmology light-curve quality cuts. This release is thus the largest SN Ia release to date, increasing by an order of magnitude the number of well characterized low-redshift objects. With the "DR2", we also provide a volume-limited (z < 0.06) sample of nearly a thousand SNe Ia. With such a large, homogeneous and well controlled dataset, we are studying key current questions on SN cosmology, such as the linearity SNe Ia standardization, the SN and host dependencies, the diversity of the SN Ia population, and the accuracy of the current light-curve modeling. These, and more, are studied in detail in a series of articles associated with this release. Alongside the SN Ia parameters, we publish our force-photometry gri-band light curves, 5138 spectra, local and global host properties, observing logs, and a python tool to ease use and access of these data. The photometric accuracy of the "DR2" is not yet suited for cosmological parameter inference, which will follow as "DR2.5" release. We nonetheless demonstrate that the multi-thousand SN Ia Hubble Diagram has a typical 0.15 mag scatter.

astro-ph.CO↗

arXiv2023

Growth-rate measurement with type-Ia supernovae using ZTF survey simulations

Measurements of the growth rate of structures at $z < 0.1$ with peculiar velocity surveys have the potential of testing the validity of general relativity on cosmic scales. In this work, we present growth-rate measurements from realistic simulated sets of type-Ia supernovae (SNe Ia) from the Zwicky Transient Facility (ZTF). We describe our simulation methodology, the light-curve fitting and peculiar velocity estimation. Using the maximum likelihood method, we derive constraints on $fσ_8$ using only ZTF SN Ia peculiar velocities. We carefully tested the method and we quantified biases due to selection effects (photometric detection, spectroscopic follow-up for typing) on several independent realizations. We simulated the equivalent of 6 years of ZTF data, and considering an unbiased spectroscopically typed sample at $z < 0.06$, we obtained unbiased estimates of $fσ_8$ with an average uncertainty of 19% precision. We also investigated the information gain in applying bias correction methods. Our results validate our framework which can be used on real ZTF data.

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