federica bianco
astro | data science | data for good
Science with Vera C. Rubin Observatory:
Federica Bianco
University of Delaware
Department of Physics and Astronomy
Biden School of Public Policy and Administration
Data Science Institute
Rubin Deputy Project Scientist
Rubin Legacy Survey of Space and Time
Science Collaboration Coordinator
Transients & Variable Stars SC CoChair
Rubin LSST
LSST Science Drivers
Probing Dark Energy and Dark Matter
image credit ESO-Gaia
LSST Science Drivers
Mapping the Milky Way and Local Volume
via resolved stellar population
An unprecedented inventory of the Solar System from threatening NEO to the distant Oort Cloud
LSST Science Drivers
LSST Science Drivers
image credit: ESA-Justyn R. Maund
Exploring the Transients and Variable Universe
8 SCs - 6 continents - 2000 people - 25 countries
Time
Domain
Science
Static
Science
Time
Domain
Science
Static
Science
Time
Domain
Science
Static
Science
AGN
STRONG
LENSING
50M+ AGNs to z~7.5
(AGN+Gal)
variability, microlensing, binaries
(AGN+TVS)
cosmography from Lens Time Delays
(SL+DESC)
calibration of cluster mass function with with S+W Lensing
(SL+DESC)
resolved high z galaxy properties
(SL+Gal)
Time
Domain
Science
Static
Science
Alerts based
Catalog based
Deep stack
based
Deep stack
based
Time
Domain
Science
Static
Science
Alerts based
Catalog based
Deep stack
based
Wide Fast Deep
8oo img over 18,000 sq deg
pairs of observations in <1hour to track asteroid (and get transient colors)
80% of the sky time
Many surveys in one
Minisurveys
Minisurveys
Deep Drilling Fields
Targets of Opportunity
}
20%
Bianco, Jones, Ivezič et al, 2021
150
1200
Nvisits
23
23
24.6
24.6
23
26.8
28
26.9
28.1
5s depth
5s depth
coadd 5s depth
coadd 5s depth
source http://astro-lsst-01.astro.washington.edu:8080/?runId=2
0.576
0.52
intranight gap
hours
15
3
internight gap
days
15
3
internight gap
days
50
5
internight gap
days
source http://astro-lsst-01.astro.washington.edu:8080/?runId=2
0.576
0.52
intranight gap
hours
source http://astro-lsst-01.astro.washington.edu:8080/?runId=2
LSST in the time-domain
Ivezič+ 2019
AGN selection and variability studies (long baseline)
Blazars
Supernovae cosmology
MMA cosmology
Cosmography with SL
QSO
Lensed SNe
Black hole microlensing
Variable stars
Near field cosmology
Variable Star Distance Ladder
Accretion/outflow indicators (X-ray binaries and young stellar objects);
Colors and shapes
GRB, SNe, Eruptions
GW counterparts
Neutrino counterparts
TDA, Blazars
Microlensing
exoplanets
distributions of time gaps in 76 OpSims
Rubin Focus Issue of ApJS on Rubin Survey Strategy Optimization
LSST static science
At this level of precision,everything is variable, everything is blended, everything is moving.
u,g,r,i,z,y | |
---|---|
Photometric precision Photometric accuracy Astrometric precision Astrometric accuracy # visits Single image 5σ depths 10-year stack 5σ depth |
5 mmag 10 mmag 10 mas 50 mas 56, 80, 184, 184, 160, 160 23.9, 25.0, 24.7, 24.0, 23.3, 22.1 26.1, 27.4, 27.5, 26.8, 26.1, 24.9 |
SDSS
LSST
http://faculty.washington.edu/ivezic/talks/NASAseminar.pdf
Filters design for photometric redshift accuracy goals
random errors smaller than 0.02, bias below 0.003, fewer than 10% >3σ outliers
Melissa Graham et al 2017-20
(but also M. Banijer, A. Maiz...)
Low-surface-brightness regime
Evolution history through accurate morphology
Weak Lensing
magnification tomography
shear–shear, galaxy–shear, and gal–gal correlation functions
Discovery
Dark matter through cluster mass function (with WL)
Star Cluster, streams
Galactic structure, ISM
Metallicity studies
Colors and shapes
Projenitors of eruptions and explisions
Environments of eruptions and explosions
Morphology, obscuration,
and their evolution
Multiwavelength
Rubin data and time domain data products
world public
data right holders
public after 2 years
world public
A change of perspective
from rare to statistical samples
Stellar Eruptions: The Giant Eruption of Eta Carinae reached m=1.4, while in an obscured Little Eruption the system reached magnitude 6.2.
TVS Roadmap - in preparation
Historical lightcurve ot Eta Carinae (1800s) and "supernova impostors" Smith & Frew 2011
from rare to statistical samples
Sample of 50M+ out to z~7.5
growth of supermassive black holes with cosmic time
Connect massive black wholes with host Galaxies
Prevalence of outflows, obscurations...
"thinking about the accretion activities of Galaxies vs classifying galaxies as active or not" (M. Banerji)
star formation history vs BH accretion history (Dickinson 2014)
Milky Way structure w 20billion resolved stars + time domain (40x SDSS, 10x farther away)
http://faculty.washington.edu/ivezic/talks/NASAseminar.pdf
Multiwavelength characterization and counterparts
Classification and Characterization
Anomalies and True Novelties
Interacting binaries, Magnetically active stars
Microlensing, Non-degenerate eruptive variables, Transiting exoplanets, Pulsating variables
Fast transients
Supernovae
Tidal Disruption Events
Distance Scales
kynematic history of SS
mass loss in asteroids and comets
Oort cloud and distant SS
10s of interstellar objects for the first time
informatics and statistics
Li et al. almost submitted
AILE: the first AI-based platform for the detection and study of Light Echoes
NSF Award #2108841
Detecting and studying light echoes in the era of Rubin and Artificial Intelligence
P.I. Bianco
Pessimal AI problem:
from rare to statistical samples
from dense time-limited or color-limited to sparse multiband
Magnitude -> Flare energy
Star displacement -> color -> flare temperature
What can we learn from 1 data point?
Because LSST will have exquisite image quality we may be able to measure color from atmospheric diffraction
from dense time-limited or color-limited to sparse multiband high accuracy
Riley Clarke, Davenport, Gizis, Bianco, in prep
What can we learn from 1 data point?
Because LSST will have exquisite image quality we may be able to measure color from atmospheric diffraction
5,000K flare on dM
30,000K flare on dM
Magnitude -> Flare energy
Star displacement -> color -> flare temperature
Stars and Pies in the sky:
what is possible with Rubin LSST?
The unprecedented sensitivity, spatial coverage and observing cadence of LSST will allow for the first time a statistical approach for the discovery and monitoring of "rare" phenomena
Detailed studies of variable star populations; 2% or better accurate multicolor light curves will be available for a sample of at least 50 million variable stars, enabling studies of cataclysmic variables, eclipsing binary systems, and rare types of variables.
some examples
Dark Energy Science Collaboration
(DESC)
+
Transients and Variable
Science Collaboration
(TVS SC)
DDF
WFD
Stellar Accretion Processes: Uniquely, LSSTwill provide both the long-baseline timeseries data necessary to quantify outburst cycles and object occurrence rates but also the rapid alerts necessary to enable outburst phases to be identified while inprogress, triggering more detailed follow-up studies (relies on alerts)
Sara Bonito chair of the Non-Degenerate Eruptive Variables TVS subgroup
TVS Roadmap - in preparation
Studies enabled by statistical samples:
Stellar Eruptions:
TVS Roadmap - in preparation
Historical lightcurve ot Eta Carinae (1800s) and "supernova impostors" Smith & Frew 2011
from rare to statistical samples
YOLO + attention mechanism
precision 80% at 70% recall with a training set of 19 light echo examples!
NSF Award #2108841
Detecting and studying light echoes in the era of Rubin and Artificial Intelligence
P.I. Bianco
Li et al. almost submitted
AILE: the first AI-based platform for the detection and study of Light Echoes
from rare to statistical samples
Micro- and meso-lensing for stellar physics
- detect microlensing events where both the lens and source lie in the Magellanic Clouds, and explore stellar and stellar remnant populations in another galaxy.
- LSST will investigate the mass distribution offaint objects in the local neighborhood, such as low mass dwarfs, stellar remnants, andfree-floating planets.
TVS Roadmap - in preparation
Rachel Street co-chair of TVS
Somayeh Khakpash, chair of microlensingsubgroup
Micro- and meso-lensing for stellar physics
Survey coordination
Rubin + Roman
TVS Roadmap - in preparation
Rachel Street co-chair of TVS
Somayeh Khakpash, chair of microlensingsubgroup
ZZ Cetis: 1-3% r.m.s. pulsation
(~1000 ZZ Cetis detected if pulsation 3% in r)
Pulsation stars
Stellar Envelop Tomography of long-period variables to probe probing layers of different atmospheric depths (Alvarez 2001)... in 6 filters. But these methodologies largely rely on NIR filters, can it be done with z and Y?
with DDF pulsations oh ~hour can be constraieds: Red Giant pulsators
K. Humbleton
TVS Roadmap - in preparation
Pulsation stars
Stellar Envelop Tomography of long-period variables to probe probing layers of different atmospheric depths (Alvarez 2001)... in 6 filters. But these methodologies largely rely on NIR filters, can it be done with z and Y?
with DDF pulsations oh ~hour can be constraieds: Red Giant pulsators
K. Humbleton
Jørgen Christensen-Dalsgaard for the book Asterosesimology (2010) by Conny Aerts
TVS Roadmap - in preparation
What is needed?
To connect sparse photometric LSST lightcurves with excellently characterized stellar properties in the TDA
The result will be a unique dataset of∼1 million regularly spaced stellar lightcurves. The lightcurves will gives a particularly comprehensive collection of late-type stellar flaring, but also short-period binary systems and cataclysmic variables, possibly young stellar objects and ultra-short period exoplanets, and unknown anomalous behaviors.
A single night continuous survey on 1 field during commissioning
A DDF synchronized with Roman
A Carina micro-survey
Astronomy’s Discovery Chain
Discovery Engine
10M alerts/night
Community Brokers
target observation managers
thank you!
University of Delaware
Department of Physics and Astronomy
Biden School of Public Policy and Administration
Data Science Institute
federica bianco
fbianco@udel.edu
Rubin and LEOsats
MMA and LEOsats
Iridium satellite number 35 lit up the predawn sky west of Boston at 5 a.m. EST on February 1, 1998, Sky & Telescope
Satellite flares
can be mitigated:
- orientation of satellite,
- directing flares away from observer
- knowing coordinates to associate them to alerts
if not mitigate there would be bogus alerts and images ruined by saturating flares
Science Collaborations
Science Collaborations
modification to planned schedule carry long lasting consequences on the program
ToO enabled for GW need to scan ~100 sq deg footprint upon trigger - will be compromised
Science Collaborations
Cosmology probes are systematic dominated
mitigation: simulation of the non-linear crosstalk to measure the effect on precision cosmology and effectiveness of removal algorithms
(image credit: Canada-France Hawaii Telescope)
Xiaolong Li et al. almost submitted
AILE: the first AI-based platform for the detection and study of Light Echoes
NSF Award #2108841
Detecting and studying light echoes in the era of Rubin and Artificial Intelligence
P.I. Bianco
Pessimal AI problem:
AILE: the first AI-based platform for the detection and study of Light Echoes
YOLO + attention mechanism
precision 80% at 70% recall with a training set of 19 light echo examples!
NSF Award #2108841
Detecting and studying light echoes in the era of Rubin and Artificial Intelligence
P.I. Bianco
Xiaolong Li et al. almost submitted
Research Inclusion: sonification of LSST lightcurves
Sid Patel, UD undergrad summer research project
Sonification: Data → Sound
New way of understanding data
Gives access to people who cannot
interpret data visually
Sounds cool! Good for public outreach
Research Inclusion: sonification of LSST lightcurves
Presented at 2021 Rubin Project Community Workshop (300 ppl)
Started a new Rubin Working Group
Rubin Rhapsodies
Riley Clarke, UD
By federica bianco