LSST AGN Research Overview
LSST AGN TODO Items
Gordon Richards (Drexel University)
Gordon Richards (Drexel University)
Precursor Observations
•
Lots of photometric quasar/AGN catalogs out
Lots of photometric quasar/AGN catalogs out
there (2 more coming) with ~4x the number of
there (2 more coming) with ~4x the number of
objects as SDSS has spectroscopically
objects as SDSS has spectroscopically
confirmed.
confirmed.
•
Might be good to sparsely target some of these
Might be good to sparsely target some of these
as a function of L, z, color, etc. for guidance for
as a function of L, z, color, etc. for guidance for
classification from LSST photometry
classification from LSST photometry
•
O/IR Spectroscopy in DDFs to enable early
O/IR Spectroscopy in DDFs to enable early
science (e.g. photometric RM)
science (e.g. photometric RM)
•
Pre-plan for future follow-up observations
Pre-plan for future follow-up observations
(TDEs, high-z, etc.)
(TDEs, high-z, etc.)
Synergies with Other Facilities
•
Going the other way – make sure to announce
Going the other way – make sure to announce
our schedule for the benefit of other facilities
our schedule for the benefit of other facilities
•
Build multi-wavelength databases for catalog
Build multi-wavelength databases for catalog
matching
matching
DES/Pan-STARRS
DES/Pan-STARRS
WISE
WISE
VLA
VLA
•
Develop SED band-merging algorithms
Develop SED band-merging algorithms
•
Build databases of existing spectroscopic data
Build databases of existing spectroscopic data
LSST-targeted Simulations
•
Overcome disconnect between DM
Overcome disconnect between DM
and science groups
and science groups
•
More complete simulations (including
More complete simulations (including
u-band) over a wider area
u-band) over a wider area
•
Simulation checking
Simulation checking
Colors
Colors
Variability
Variability
Astrometry (DCR & PM)
Astrometry (DCR & PM)
Morphology
Morphology
Star-galaxy separation
Star-galaxy separation
R&D of Techniques or Algorithms
•
Photo-z Algorithm Development
Photo-z Algorithm Development
Create/test new algorithms that work
Create/test new algorithms that work
across the full luminosity range
across the full luminosity range
sampled
sampled
•
AGN Selection
AGN Selection
Develop new algorithms (e.g.
Develop new algorithms (e.g.
color+var)
color+var)
Test on sims
Test on sims
Test on DES and Pan-STARRS data
Test on DES and Pan-STARRS data
Photo-z’s for AGNs
At high luminosity,
At high luminosity,
empirical methods work
empirical methods work
best (using the emissions
best (using the emissions
line features).
line features).
At low luminosity,
At low luminosity,
template fitting works best
template fitting works best
(using the 4000A break)
(using the 4000A break)
Need to figure out how to
Need to figure out how to
decide which to use and/or
decide which to use and/or
how to transition between
how to transition between
them.
them.
Assef et al. 2010
Multi-parameter Selection
colors
colors
variability
variability
astrometry
astrometry
Software Development
•
Clustering/LF development
Clustering/LF development
Create algorithms appropriate to
Create algorithms appropriate to
data volume/type/format
data volume/type/format
Write papers based on simulations
Write papers based on simulations
that show what errors will be
that show what errors will be
Database and Data Services
•
Liaise with other working groups (e.g.,
Liaise with other working groups (e.g.,
identify objects with high probability
identify objects with high probability
classes from other groups)
classes from other groups)
•
Photo-z as PDFs
Photo-z as PDFs
Other
•
Stripe 82 Work
Stripe 82 Work
Anything that can be done with the sims
Anything that can be done with the sims
•
Deep Drilling Fields
Deep Drilling Fields
How to use as truth tables
How to use as truth tables
•
Variability Characterization
Variability Characterization
A/gamma vs. DRW
A/gamma vs. DRW
Finding vs. physics (observed vs. rest)
Finding vs. physics (observed vs. rest)
How/if to combine ugriz?
How/if to combine ugriz?
Explore various research tasks in the LSST AGN field, including precursor observations, synergies with other facilities, targeted simulations, R&D of techniques/algorithms, photo-z development for AGNs, and software/database services. Tasks involve data analysis, algorithm development, multi-wavelength observations, and coordination with other surveys for enhanced scientific outcomes.
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Presentation Transcript
LSST AGN TODO Items Gordon Richards (Drexel University)
Precursor Observations Lots of photometric quasar/AGN catalogs out there (2 more coming) with ~4x the number of objects as SDSS has spectroscopically confirmed. Might be good to sparsely target some of these as a function of L, z, color, etc. for guidance for classification from LSST photometry O/IR Spectroscopy in DDFs to enable early science (e.g. photometric RM) Pre-plan for future follow-up observations (TDEs, high-z, etc.)
Synergies with Other Facilities Going the other way make sure to announce our schedule for the benefit of other facilities Build multi-wavelength databases for catalog matching DES/Pan-STARRS WISE VLA Develop SED band-merging algorithms Build databases of existing spectroscopic data
LSST-targeted Simulations Overcome disconnect between DM and science groups More complete simulations (including u-band) over a wider area Simulation checking Colors Variability Astrometry (DCR & PM) Morphology Star-galaxy separation
R&D of Techniques or Algorithms Photo-z Algorithm Development Create/test new algorithms that work across the full luminosity range sampled AGN Selection Develop new algorithms (e.g. color+var) Test on sims Test on DES and Pan-STARRS data
Photo-zs for AGNs At high luminosity, empirical methods work best (using the emissions line features). At low luminosity, template fitting works best (using the 4000A break) Need to figure out how to decide which to use and/or how to transition between them. Assef et al. 2010
Multi-parameter Selection colors variability astrometry
Software Development Clustering/LF development Create algorithms appropriate to data volume/type/format Write papers based on simulations that show what errors will be
Database and Data Services Liaise with other working groups (e.g., identify objects with high probability classes from other groups) Photo-z as PDFs
Other Stripe 82 Work Anything that can be done with the sims Deep Drilling Fields How to use as truth tables Variability Characterization A/gamma vs. DRW Finding vs. physics (observed vs. rest) How/if to combine ugriz?
