P.Woudt : Radio transients and variables with MeerKAT MeerKAT is - precursor for SKA in South Africa - 64 antennas - 3 Ghz receivers inaugurated on 13 july 2018 to be extended by 20 SKA antennae incorporated in SKA1-MID (200 anetnnas - 150 km baseline) Radio Transients and Variables with MeerKAT ThunderKAT scientific goals Cataclysmic variables Short GR Bursts Type Ia supernovae X-ray binaries Image domain (commensal) Targeted observations Cataclysmic variables faint single epoch X-ray bibaries (weekly monitoring) Typical observing sequence 1 ) bandpass calibrator 2 ) gaub (?) calibrator 3 ) target and repeat time resolution 2 or 8 seconds frequency resolution 4000 to 32000 channels black hole X-ray binary MAXI blach hole X-ray binbary GX 339-4 first radio transient discovered by Meerkat (GX 339-4 filed) two years of MeerKat monitoring light curves Processing: Use TraP (developed for LOFAR) Variability statistics cross identification with optical Key Parameters from the observations Key Parameters from the analysis Key Parameters from the light curve Archived data / include the images / how we can make this available Brent : cross-matching with other data , vizer, optical ? Patrick : yes, planned François : Distributing the data ? Vo services maybe ? Patrick : thinking about it ---------------------------------------------------------------------- Dougal Dobie : ASKAP Variable and Slow Transient Survey ASKAP : 36 antennas, 6 km max baseline 30 deg2 fied of view 288 Mhz bandwidth 0.9-1.6 Ghz central feq. 10 hr. sensitivity : 35 microJy VAST survey science Goals orphan GammaRay burst afterglows survey of radio supernovae flaring magnetars, intermittent radio pulsars rotating radio transients cataclysmic variables, flare stars, Xray binaries new class of objects 5 year ASKAP surveys 1 Custom VAST survey 8000 sq deg Multiple epochs/year 2 Commensal surveys VAST has acces to all ASKAP data Transient time scales Timesacle from seconds to years Commensal (shorter) versus Custom VAST (larger) Afterglow Phase space : Number per sq deg versus Flux Worflow diagram display VAST pipeline (ingest images ---> variability metrics) can be queried via web-interface or Python package. stored in postgres database. ingesting VOevents Results: Radio stars : found 75 new radio stars ..; Polarised Transients and variables : several papers GRB afterglows Can you use astropy ? what do you have in the database ? Is that relevant for a TAP interface ? Python package : basic package using astropy in the database : full images, cutouts, light curves, variability metrics. ------------------------------------------------------------------ Vincenzo Galluzzi: ObsCore mapping for INAF pulsar/FRB data 1 ) pulsar/transients observations and data formats 2 ) Data archiving workflow 3 ) Data model 4 ) mapping to Obscore 5 ) summary of current activities 3 single dish / and VLBI . 2.1 TB raw data 2018-2020 Two data formats : a ) PSRFITS (.sf, .cf, .rf) b ) Filterbank (from baseband data .dada) : .fil the archival system : Tango ( based on NADIR) extensible, replication on top of this TAP service1erWeb interface / broadcast results with SAMP Pulsar data model : metadata primary HDU of PSRFITS file / For FILTERBANK only primary header can be mapped on a flat table. 4 ) ObsCore mapping dataproduct_type : dynamic stpetrum or cube in case several polarimetry ? [BC/Nançay] => I suggest to keep dynamic_spectrum here, as it is a search key. calib_level 0 or 1 obs_id : a way to provide TELESCOPE Date Project etc... obs_publisher_did : ivo id based on obs_id access_format : PSRFITS or FILTERBANK s_ra , s_dec and s_fov ...OK s_resolution s_xel1-2 not applicable t_min/t_max/t_resolution/t_exptime OK t_xel not useful Baptiste : dynamic spectrum in all cases AIan and Baptiste: build a team to prepare a Pulsar Obscore mapping Note, with people in Nançay (Louis Bondonneau), Orléans (Jean-Mathias Greissmeier) + Italy (Vincenzo G, Marco M, Alessandra ...) ----------------------------------------------------------------------- Alan Loh : Nenufar : multi-order coverage Phased-array 3 scales: dipole antenna --> Mini Array -> core array sensitivity pattern Nenufar : 1938 LWA-like radiator antennnas 102 Antennae Mini-arrays Core : 19 mini arrays in mini-array mode : alot of lobes due to geometry Global Sky Model to Multi-Ordrer Coverage map and MOC for array patter, MOCs intersection for data validation Time dependancy and also frequency dependancy of these MOCS Time frequency regions contaminated by sources dynamic spectrum -> contamination This is Used eg for all exoplanets .. detection : The database : config file --> json --> elastic search --> visualization : kibana move from that to ObsTAP/EPN-tap (sun and jupiter) Nenufar : adding FOV TMOCS to results Also provide an ObsLOcTAP ... Question: STMOC for contamintion : no overcomplicated ? Baptiste: when spectral domain in MOC, might be easier Baptiste : connection elactic search / TAP has been already presented yesterday in DAL1. Might something to look at more generally at IVOA level Brent ( lost question ad answer?)