Francisco Förster; G. Cabrera-Vives; E. Castillo-Navarrete; P. A. Estévez; P. Sánchez-Sáez; J. Arredondo; F. E. Bauer; R. Carrasco-Davis; M. Catelan; F. Elorrieta; S. Eyheramendy; P. Huijse; G. Pignata; E. Reyes; I. Reyes; D. Rodríguez-Mancini; D. Ruz-Mieres; C. Valenzuela; I. Álvarez-Maldonado; N. Astorga; J. Borissova; A. Clocchiatti; D. De Cicco; C. Donoso-Oliva; M. J. Graham; L. Hernández-García; R. Kurtev; A. Mahabal; J.C. Maureira; R. Molina-Ferreiro; A. Moya; A. Muñoz Arancibia; W. Palma; M. Pérez-Carrasco; A. Papageorgiou; P. Protopapas; M. Romero; L. Sabatini-Gacitua; A. Sánchez; J. San Martı́n; C. Sepúlveda-Cobo; E. Vera; J. R. Vergara
The Universe in a stream: the ALeRCE broker
ALeRCE is a Chilean-led initiative to build a community broker for ZTF, LSST, and other large etendue survey telescopes
Carrasco-Davis et al. 2020 + Förster et al. 2020 + Sánchez-Sáez et al. 2020 (Submitted)
ALeRCE: from HiTS to LSST
~10-100x
~1-10x
Goals
To facilitate the study of variable and transients objects:
The ALeRCE collaboration
Valdivia, Chile, November 2018
Santiago, Chile, June 2019
La Serena, Chile, March 2019
Concepción, Chile, Jan 2020
ALeRCE users
Agile Methodology
Well aligned teams:
Scientific Questions
Transients
Progenitors of stellar explosions (outermost layers) & explosion physics (ejecta structure)
Variable stars
Low mass microlensing events, changing mode stellar pulsators, rapid reaction to eclipsing events, eruptive events
Supermassive black holes
Changing state AGNs, reverberation mapping studies, detection of intermediate mass black holes, tidal disruption events
ALeRCE infrastructure
Distributed Storage
Container orchestrator
Distributed messaging
Distributed database
Services
Feature computation
Model training
Training
Deployment
ALeRCE pipeline
Code your step
Install APF
Configure your step
Run locally
See examples
Build the image
Deploy
Classification
Taxonomy
Complex & growing taxonomy
Stamp classifier
Light curve classifier
+ Forecasting service
+ Outlier detection
Classification models
Light Curve Classifier
Stamp Classifier
Hierarchical Random Forest Classifier
(using light curves with at least 6 observations)
Sánchez-Sáez et al. 2020 (Submitted)
AGN, SN, VS, asteroid, bogus
SN Ia, SN Ibc, SN II, SLSNe,
QSO, AGN, Blazar, YSO, CV/Nova,
LPV, E, DSCT, RRL, CEP, Periodic Other
Stamp Classifier vs Light Curve Classifier
SNe detected by ALeRCE (stamp classifier)
ALeRCE reports more SNe within the first day of detection, using only the public alert stream. We do not report previously reported SNe.
Why single stamp classification?
First detection magnitude vs initial magnitude change rate
1st ZTF detection
+8 hr ALeRCE TNS report
+21 hr spectroscopic confirmation (Ib)
+63 hr 2nd ZTF detection
1st ZTF detection
+4.5 hr ALeRCE TNS report
+42 hr spectroscopic confirmation (Ic)
+96 hr 2nd ZTF detection
One detection reports can be critical to catching very young SNe.
Light curve classifier candidates
Number of candidates per class obtained for 868,371 sources with enough alerts until 2020/06/09
Sánchez-Sáez et al. 2020 (Submitted)
Normalized magnitude distributions in the r band for sources in the labeled set (LS; red) and candidates from the unlabeled ZTF set (blue)
Extragalactic sources
Galactic sources
Web Interfaces
ZTF Explorer
SN Hunter
Web Interfaces
Jupyter Notebooks
TOMs
Output stream
(real-time follow-up)
http://alerce.science
API
API
http://catshtm.alerce.online *
https://findingchart.alerce.online
https://tns.alerce.online/search
* Soumagnac & Ofek (2018), (Ofek 2014; ascl.soft 07005)
New: database, API & client
Database
Detailed description of new schema here
API
Documentation in http://dev.api.alerce.online
Client
Clone new client and pip install -e .
Notebooks
Supernova, AGN and variable stars
Preview available for LSST PCW.
Any feedback is welcome!
New ALeRCE database
Time series, filter dependent
Static
Static, filter dependent
detection: light curves & other relevant time dependent information.
non-detection: limiting magnitudes
data_quality: data quality related time dependent information
object: basic object statistics
xmatch: points to the detailed xmatch tables (allwise, ps1_ztf, gaia_ztf, ss_stf)
magstat: statistics per band per object
feature: object computed features
reference: object statistics for every reference image used
The new ALeRCE explorer
Modular design
Open source
AWS based
New DB connection
New taxonomy
New classifiers
More statistics
Black hole mode!
Try the beta version!
Jupyter Notebooks
New: preview the new DB, API and client (newDB notebooks)
LC and stamp classifiers...
Mobile Phones
Other tools
ALeRCE TOM
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Reporter/Challenger (http://reporter.alerce.online/)
Xmatch service (http://xmatch.alerce.online/)
Summary
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