{"arxiv_id":"2602.02677","incoming":{"papers":2,"sentences":2,"groups":[{"kind":"background","label":"Cites it as background","papers":1,"sentences":1,"quotes":[{"arxiv_id":"2606.23780","title":"Signatures of $^{56}$Ni Mixing and Neutron-rich Ejecta in Supernovae","url":"/paper/2606.23780","section":"Introduction","sentence":"These models have been applied to large samples of core-collapse [ref] , and thermonuclear SNe [ref] , and inferences drawn from such fits are then used to compare explosion mechanisms, nucleosynthetic yields, and the relation between different classes of supernovae.","intent_p":0.83,"contests_p":null}]}],"unlabelled_sentences":1},"outgoing":{"papers":54,"sentences":96,"groups":[{"kind":"method_or_tool","label":"Uses the method or tool of","papers":7,"sentences":11,"quotes":[{"arxiv_id":"1809.02293","title":"An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models","url":"/paper/1809.02293","section":"Hierarchical inference on low-redshift sample","sentence":"The hyper-parameter posterior is given by [ref] , [equation] Here $d_i$ represents the data (light curves) for the $N_obs = 902$ observed events, $π(Λ)$ is the prior on our population parameters, and $ℒ$ is the likelihood for the population hyperparameters.","intent_p":0.95,"contests_p":null},{"arxiv_id":"1809.02063","title":"Extracting distribution parameters from multiple uncertain observations with selection biases","url":"/paper/1809.02063","section":"Hierarchical inference on low-redshift sample","sentence":"The hyper-parameter posterior is given by [ref] , [equation] Here $d_i$ represents the data (light curves) for the $N_obs = 902$ observed events, $π(Λ)$ is the prior on our population parameters, and $ℒ$ is the likelihood for the population hyperparameters.","intent_p":0.95,"contests_p":null},{"arxiv_id":"0809.3437","title":"MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics","url":"/paper/0809.3437","section":"Inference","sentence":"To sample the posterior we use the model and likelihoods implemented in Redback [ref] with the the nested sampler PyMultiNest [ref] via the Bilby [ref] interface.","intent_p":1.0,"contests_p":null},{"arxiv_id":"2308.12806","title":"Redback: A Bayesian inference software package for electromagnetic transients","url":"/paper/2308.12806","section":"Inference","sentence":"To sample the posterior we use the model and likelihoods implemented in Redback [ref] with the the nested sampler PyMultiNest [ref] via the Bilby [ref] interface.","intent_p":1.0,"contests_p":null},{"arxiv_id":"2405.20965","title":"ZTF SN Ia DR2: Environmental dependencies of stretch and luminosity of a volume limited sample of 1,000 Type Ia Supernovae","url":"/paper/2405.20965","section":"Host Galaxy Correlations","sentence":"The Hubble residuals have been corrected for SALT stretch and colour using the package presented in [ref] , leading to $α=0.161$ and $β=3.06$.","intent_p":1.0,"contests_p":null}]},{"kind":"data_used","label":"Uses data or values from","papers":2,"sentences":8,"quotes":[{"arxiv_id":"2409.04346","title":"ZTF SN Ia DR2: Overview","url":"/paper/2409.04346","section":"Sample Selection and Properties","sentence":"Our analysis draws on the Zwicky Transient Facility (ZTF) Data Release 2 (DR2) sample of spectroscopically confirmed Type Ia supernovae [ref] .","intent_p":1.0,"contests_p":null},{"arxiv_id":"1003.5119","title":"The Dependence of Type Ia Supernova Luminosities on their Host Galaxies","url":"/paper/1003.5119","section":"Sample Selection and Properties","sentence":"Host-galaxy stellar masses are available for 2,151 SNe ($97.6%$) of the sample considered in this work [ref] and span $6.0 < log_10(M_*/M_⊙) < 11.5$ with a median of 9.8; the sample is evenly divided across the canonical $log_10(M_*/M_⊙) = 10$ mass step threshold [ref] , providing leverage on environmental trends.","intent_p":1.0,"contests_p":null}]},{"kind":"comparison","label":"Compares with","papers":5,"sentences":6,"quotes":[{"arxiv_id":"astro-ph/0609232","title":"Consistent estimates of (56)Ni yields for type Ia supernovae","url":"/paper/astro-ph/0609232","section":"Physical Parameter Distributions","sentence":"The nickel mass distribution for the selected population has a mean $M_Ni= 1.21 M_⊙$ with a standard deviation of $0.3$ M$_⊙$, higher than the canonical $∼$0.6 M$_⊙$ [ref] .","intent_p":0.97,"contests_p":null},{"arxiv_id":"1507.02501","title":"Measuring nickel masses in Type Ia supernovae using cobalt emission in nebular phase spectra","url":"/paper/1507.02501","section":"Redshift-limited sub-sample","sentence":"This is again more consistent with estimates from smaller, albeit (also biased) samples [ref] , especially given the large uncertainty.","intent_p":0.97,"contests_p":null},{"arxiv_id":"1003.5119","title":"The Dependence of Type Ia Supernova Luminosities on their Host Galaxies","url":"/paper/1003.5119","section":"Host Galaxy Correlations","sentence":"Given that the nickel mass strongly correlates with $x_1$, this plot is directly comparable to the known and expected trends between $x_1$ and host galaxy properties [ref] .","intent_p":0.87,"contests_p":null},{"arxiv_id":"1402.7079","title":"Type Ia Supernova Colors and Ejecta Velocities: Hierarchical Bayesian Regression with Non-Gaussian Distributions","url":"/paper/1402.7079","section":"Physical Parameter Distributions","sentence":"The ejecta velocity distribution has a mean velocity $v_ej = 11,060$ and standard deviation $1,596$ km s$^-1$, consistent with spectroscopic Si II measurements [ref] .","intent_p":0.83,"contests_p":null},{"arxiv_id":"1011.4517","title":"Measuring Ejecta Velocity Improves Type Ia Supernova Distances","url":"/paper/1011.4517","section":"Physical Parameter Distributions","sentence":"The ejecta velocity distribution has a mean velocity $v_ej = 11,060$ and standard deviation $1,596$ km s$^-1$, consistent with spectroscopic Si II measurements [ref] .","intent_p":0.83,"contests_p":null}]},{"kind":"supports_this_paper","label":"Cites as support","papers":1,"sentences":1,"quotes":[{"arxiv_id":"astro-ph/0606449","title":"Secondary Maximum in the Near-Infrared Lightcurves of Type Ia Supernovae","url":"/paper/astro-ph/0606449","section":"Model","sentence":"We stress that these modifications are all phenomenological, and motivated by the real physics seen in radiative-transfer simulations [ref] , which is otherwise too computationally expensive to implement in inference-capable models.","intent_p":0.96,"contests_p":null}]},{"kind":"background","label":"Cites as background","papers":14,"sentences":14,"quotes":[{"arxiv_id":"1003.2917","title":"Detonations in Sub-Chandrasekhar Mass C+O White Dwarfs","url":"/paper/1003.2917","section":"Introduction","sentence":"In sub-$M_Ch$ models, double-detonation is triggered on a less massive WD [ref] .","intent_p":0.95,"contests_p":null},{"arxiv_id":"astro-ph/9602025","title":"Explosion Models for Type Ia Supernovae: A Comparison with Observed Light Curves, distances, H_o and q_o","url":"/paper/astro-ph/9602025","section":"Introduction","sentence":"In Chandrasekhar-mass ($M_Ch ≈1.4$ M$_⊙$) models, the explosion proceeds via delayed detonation or deflagration-to-detonation transition [ref] .","intent_p":0.96,"contests_p":null},{"arxiv_id":"1312.0628","title":"Observational clues to the progenitors of Type-Ia supernovae","url":"/paper/1312.0628","section":"Introduction","sentence":"The most popular model involves the thermonuclear runaway of a carbon-oxygen white dwarf (WD) in a binary system, but the specific progenitor channel—single-degenerate (SD) accretion or double-degenerate (DD) merger—is highly debated [ref] .","intent_p":0.96,"contests_p":null},{"arxiv_id":"astro-ph/9604143","title":"A Precise Distance Indicator: Type Ia Supernova Multicolor Light Curve Shapes","url":"/paper/astro-ph/9604143","section":"Introduction","sentence":"Their utility in cosmology relies on the empirical brighter-slower relation [ref] , which standardizes peak luminosities based on light-curve decline rate, and the brighter-bluer relation [ref] which standardizes based on optical colour.","intent_p":0.96,"contests_p":null},{"arxiv_id":"1011.5910","title":"Type Ia Supernova Light Curve Inference: Hierarchical Models in the Optical and Near Infrared","url":"/paper/1011.5910","section":"Hierarchical inference on low-redshift sample","sentence":"Hierarchical Bayesian inference was first applied to SN Ia samples by [ref] using empirical light curve models.","intent_p":0.9,"contests_p":null}]}],"unlabelled_sentences":56},"claims":[],"thresholds":{"intent_p":0.8,"supports_p":0.95,"contests_p":0.7},"method":"Citing sentences come from each paper's LaTeX source; every \\cite marks the sentence and the works it cites. Pith's classifier typed each sentence. A label is shown at intent probability 0.8 or more (0.95 for support), a contest at 0.7 or more. Measured accuracy against two blind model families is at https://pith.science/accuracy. The quoted sentences are the citing authors' own.","held_up":null,"_links":{"html":"https://pith.science/paper/2602.02677"}}