fink-science 3.13.3

User-defined science module for the Fink broker.

Fink Science

This repository contains science modules used to generate added values to alert collected by the Fink broker.

ZTF alert stream

It currently contains:

Source	Field in Fink alerts	Type	Contents
fink_science/xmatch	cdsxmatch++	string	Counterpart (cross-match) from any CDS catalog or database using the CDS xmatch service. Contains also crossmatch to the General Catalog of Variable Stars and the International Variable Star Index, 3HSP, 4LAC DR3, Mangrove
fink_science/random_forest_snia	rf_snia_vs_nonia	float	Probability to be a rising SNe Ia based on Random Forest classifier (1 is SN Ia). Based on https://arxiv.org/abs/2111.11438
fink_science/snn	snn_snia_vs_nonia	float	Probability to be a SNe Ia based on SuperNNova classifier (1 is SN Ia). Based on https://arxiv.org/abs/1901.06384
fink_science/snn	snn_sn_vs_all	float	Probability to be a SNe based on SuperNNova classifier (1 is SNe). Based on https://arxiv.org/abs/1901.06384
fink_science/microlensing	mulens	float	Probability score to be a microlensing event by LIA
fink_science/asteroids	roid	int	Determine if the alert is a Solar System object
fink_science/kilonova	rf_kn_vs_nonkn	float	probability of an alert to be a kilonova using a Random Forest Classifier (binary classification).
fink_science/nalerthist	nalerthist	int	Number of detections contained in each alert (current+history). Upper limits are not taken into account.
fink_science/ad_features	lc_*	dict[int, array]	Numerous light curve features used in astrophysics.
fink_science/agn	rf_agn_vs_nonagn	float	Probability to be an AGN based on Random Forest classifier (1 is AGN).
fink_science/anomaly_detection	anomaly_score	float	Anomaly score (lower values mean more anomalous observations)
fink_science/t2	t2	dic[str, float]	Classifier based on Transformers. Based on https://arxiv.org/abs/2105.06178

You will find README in each subfolder describing the module.

ELASTiCC stream (Rubin-like simulated data)

These modules are being tested for Rubin era on the LSST-DESC ELASTiCC data challenge:

Source	Field in Fink alerts	Type	Contents
fink_science/agn_elasticc	rf_agn_vs_nonagn	float	Probability to be an AGN based on Random Forest classifier (1 is AGN).
fink_science/random_forest_snia	rf_snia_vs_nonia	float	Probability to be a rising SNe Ia based on Random Forest classifier (1 is SN Ia). Based on https://arxiv.org/abs/2111.11438
fink_science/snn	snn_snia_vs_nonia	float	Probability to be a SNe Ia based on SuperNNova classifier (1 is SN Ia). Based on https://arxiv.org/abs/1901.06384
fink_science/snn	broad	array[float]	Broad classifier based on SNN. Returns [class, max(prob)].
fink_science/cats	fine	array[float]	Fine classifier based on the CBPF Algorithm for Transient Search. Returns [class, max(prob)].

How to contribute

Learn how to design your science module, and integrate it inside the Fink broker.

Installation

If you want to install the package (broker deployment), you can just pip it:

pip install fink_science