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| JLA (Joint Light-curve Analysis) | |
|---|---|
| Name | JLA (Joint Light-curve Analysis) |
| Field | Observational cosmology |
| Related | Supernova cosmology project, High-Z Supernova Search Team, Sloan Digital Sky Survey, Dark Energy Survey |
JLA (Joint Light-curve Analysis) is a compilation and analysis effort combining multiple Type Ia supernova datasets to constrain cosmological parameters. It synthesizes observations from several surveys and collaborations to produce a homogeneous sample for distance measurements, enabling joint constraints on the Hubble diagram, dark energy, and matter density. The analysis integrates photometric calibration, light-curve modeling, and systematic error assessment to produce widely cited cosmological results.
The project integrates datasets from major surveys and institutions including the Supernova Legacy Survey, Sloan Digital Sky Survey, Hubble Space Telescope, Low-z Supernova Survey teams, and collaborations such as the SNfactory, CfA Supernova Program, Pan-STARRS1 pilot studies, and contributors from the European Southern Observatory and Keck Observatory. Key people and teams involved include researchers associated with the Planck (spacecraft), WMAP, Two Micron All Sky Survey, Carnegie Institution for Science, University of California, Berkeley, Harvard University, Stanford University, Lawrence Berkeley National Laboratory, and the Max Planck Institute for Astrophysics. The compilation aims to reconcile photometry and calibration standards used by projects like the Sloan Digital Sky Survey-II Supernova Survey and the SNLS to produce a unified cosmological constraint comparable with results from Planck Collaboration and Baryon Oscillation Spectroscopic Survey measurements.
JLA combines low-redshift spectroscopically confirmed samples from programs such as the Center for Astrophysics (CfA), Carnegie Supernova Project, and the Lick Observatory Supernova Search with intermediate- to high-redshift samples from SNLS, SDSS-II, and targeted Hubble Space Telescope campaigns. Selection criteria reference spectroscopic classification used by teams including ESO Very Large Telescope observers, Gemini Observatory staff, and Subaru Telescope follow-up programs. The sample selection process cross-references host-galaxy identifications from surveys like Two Micron All Sky Survey and Sloan Digital Sky Survey catalogues, and uses redshift information from facilities such as the Anglo-Australian Telescope and Magellan Telescopes. Quality cuts, light-curve coverage requirements, and exclusion lists were informed by analyses from groups at University of Oxford, University of Toronto, Imperial College London, and California Institute of Technology.
The analysis employs light-curve fitters developed in part by teams connected to Guy et al., the SALT2 model, and software with contributions from researchers at IN2P3, CEA Saclay, University of Portsmouth, and University of Southampton. Standardization uses stretch and color corrections following methods refined by groups at Lawrence Berkeley National Laboratory and Harvard-Smithsonian Center for Astrophysics. The color–luminosity relation and host-mass step were calibrated against host properties catalogued by the Sloan Digital Sky Survey and cross-checked with photometric systems used by Pan-STARRS and CFHT (Canada–France–Hawaii Telescope). Photometric transformations and model training involved teams at LPNHE, University of Geneva, and ETH Zurich.
Cosmological parameter estimation combined JLA distances with external probes including cosmic microwave background results from Planck Collaboration and WMAP, baryon acoustic oscillation constraints from BOSS and 6dF Galaxy Survey, and direct Hubble parameter measurements influenced by work at Hubble Space Telescope and SH0ES program teams. The analysis reported constraints on parameters such as the matter density Omega_m and dark energy equation-of-state parameter w, compared with contemporaneous results from the Dark Energy Survey, Euclid preparatory studies, and forecasts from LSST. Statistical pipelines drew on statistical methods used at Stanford University, University of Cambridge, and Princeton University.
JLA places emphasis on calibration uncertainties linking photometric systems of instruments like CFHT MegaCam, SDSS Photometric Telescope, and HST ACS. Systematics treated include zero-point offsets, filter transmission uncertainties characterized by teams at National Institute of Standards and Technology, ESO, and CALTECH/IPAC, and model uncertainties from SALT2 training datasets curated by researchers at INAF and CEA. Host-galaxy correlations, selection biases, and Malmquist effects were quantified using simulations developed by groups at Argonne National Laboratory, Argelander-Institut für Astronomie, and Kavli Institute for Cosmological Physics. Cross-calibration efforts referenced spectrophotometric standards established by CALSPEC and observational programs led by STScI.
JLA was compared to prior and subsequent compilations including the Union2.1 dataset, Pantheon compilation, and localized analyses from the Carnegie Supernova Project II. Differences with results reported by groups at Riess et al. (SH0ES), Scolnic et al., and teams producing the Pantheon+ sample were analyzed, with attention to calibration approaches used by Betoule et al. and methodologies from Conley et al.. Comparative studies referenced cosmological tension discussions involving Planck Collaboration, BOSS, DES Science Collaboration, and independent measurements from H0LiCOW and Megamaser Cosmology Project.
The compilation influenced subsequent work by the Dark Energy Survey, LSST Science Collaboration, Euclid Consortium, and the Roman Space Telescope planning teams by providing a template for cross-survey calibration, light-curve modeling, and systematic treatment. Its methods informed training sets used by SALT3 developers, statistical approaches at Institute for Advanced Study groups, and multi-probe analyses combining supernovae with BAO and CMB data from institutions such as Max Planck Institute for Extraterrestrial Physics and Princeton University. The dataset and methodology remain part of the discourse on parameter estimation, calibration standards, and the Hubble tension debated among researchers at Harvard University, University of Chicago, and Rutgers University.
Category:Supernova cosmology