Download Concepts discussed Jargon and conventions

Photometry
&
Virtual Observatory
Gijs Verdoes Kleijn
Kapteyn Institute, room 147
[email protected]
050-3638326
Concepts discussed
• The light path
• Photometric calibration
– Standard systems
– Calibration procedures
• Photometric calibration & VO
• In other words: physics of interaction over
light path; calibration: quantifying
interactions; sharing your photometry
Goal: physics via Spectral Energy
Distribution (SED)
Stellar SEDs
•What is required spectral
resolution (?/d?) to get
physics?
•Example: temperature of
blackbody can be obtained
from relative intensity at
two wavelengths
•Spectral resolution ?
? Efficiency?
•broad-band spectroscopy
=photometry
Jargon and conventions
•
•
•
•
•
Flux (e.g., erg/s/cm^2, W/m^2)
Flux density (e.g., erg/s/cm^2/Hz or /Ang)
m(agnitude)=-2.5log10(flux/flux0)
m: Apparent magnitude
M: Absolute Magnitude= apparent
magnitude at 10pc
• Color: e.g., blue-red (B-R)
Example: stellar colors
Hertzsprung Russell Diagram
B star
M star
Hertzsprung -Russell
diagram=life of star
(gal=n_stars )
1
Richards etal AJ, 123, 2945
Higher z
QSOs
QSOs
A stars
stars
• Discovery: 1930s
• Extinction=(Mie) scattering+absorption by
dust particles
• Net effect: reddening
k(?)~1/?
Atmosphere: obscures+shines
counts
• +Continuum+Line Emission
Days
from
new
moon
Sky Brightness
U
B
V
R
I
z
0
22
.0
22
.7
21
.8
20
.9
19
.9
18
.8
3
21
.5
22
.4
21
.7
20
.8
19
.9
18
.8
7
19
.9
21
.6
21
.4
20
.6
19
.7
18
.6
10
18
.5
20
.7
20
.7
20
.3
19
.5
18
.3
14
17
.0
19
.5
20
.0
19
.9
19
.2
18
.1
http://webast.ast.obs-mip.fr/hyperz/hyperz_manual1/node10.html
Galactic ISM: Interstellar extinction
“Maltreatment” of photons
filters
Intergalactic
Medium
• Time/location-variability: Earth
atmosphere, telescopes, filters, detectors.
• How to compare results with this
variability?
http://www.sc.eso.org/~isaviane/photometry/Optical%20
Photometry_files/v3_document.htm
http://www.journals.uchicago.edu/AJ/journal/issues/v123n6/
201557/201557.html
Example Quasar colors
Atmosphere: obscures+shines
• - Extinction by dust, aerosols, molecules
Atmospheric extinction
• Extinction per unit atmosphere is
time/location dependent (haze, clouds,
dust)
• Proportional to airmass~1/cosz
~1/cosz
(nm)
2
Telescope
Filters
Passbands,transmission curves
• Mirrors
• Lenses
• Filter widths ? ?/?
Subaru telescope primary mirror
– Narrow
<0.02
– Intermediate0.02-0.1
– Wide
>0.1
• Filter materials:
– Glass: red (IR) leaks
– gelatin films
– Interference
Commonly used filter sets
Detector effects:
Quantum efficiency
(nm)
Detector effects:
pixel to pixel variation quantum
efficiency: flatfield
Detector effects:
fringing
Fringing= variation in background light
•Origin: Interference of nightsky lines
within CCD
•More pronounced in red part spectrum
•Only affects “background” light
3
•due to internal
scattering of light in
instrument
•Affects both source and
background light
“Maltreatment” of photons
filters
Intergalactic
Medium
• Time/location-variability: Earth
atmosphere, telescopes, filters, detectors.
• How to compare results with this
variability?
Solution: relative measurements
• Measure relative to flux I0 of reference object:
m-m0 = -2.5 log10 ( I/I0)
– i.e., measure (I/I0) instead of I: constants cancel
• Unitless system
• m0 = -2.5 log 10 ( I0/I0) = 0 by definition
• I0 proportional to flux, but can have arbitrary
units:
– m=-2.5log 10 (countrate ) +zeropoint
Photometric standard systems
• Goal: putting mags on
common scale
• Standard system=
http://www.sc.eso.org/~isaviane/photometry/Optical%20
Photometry_files/v3_document.htm
Detector effects:
illumination variation
What one observes
• Effects of ism, atmosphere, telescope, filter and
detector QE and flatfielding are multiplicative gains:
– Iobs = I*g ISM(a,d) * g atm(k,z0) * g tel*gfilt1* g det1(x,y)
– I0,obs = I0*g ISM(a 0,d 0) * g atm(k,z) * gtel1*gfilt1* g det1(x 0,y0)
• Neglected fringing and illumination correction:
discussed in werkcollege
• For telescope2,filter2,detector2:
– Iobs = I*g ISM(a,d)*g atm(k,z)*gtel2*gfilt2*gdet2(x,y)
– I0,obs = I0*g ISM(a 0,d 0)*g atm(k,z0)*gtel2*gfilt2*gdet2(x 0,y0)
Integrating up-link and down-link:
Determining gains translate into
procedurized observations
Atmosphere
– telescope+filter+detector
• Natural system=
– Your telescope+filter+detector
Telescope+filter+QE
• Convert your measurements
as if observed with standard
system
• Example standard systems:
–
–
–
–
Johnson-Cousins
Sloan
Stroemgren
Walraven
Flatfielding
4
from Design-> deliver
•• Scientific
Scientific requirements
requirements -- SRD
SRD
–– Science
Science goals
goals (e.g.,
(e.g., determine
determine temperature
temperature of
of stars
stars out
out to
to
10kpc)
10kpc)
•• User
User requirements
requirements -- URD
URD
–– Shalls:
Shalls: what
what photometric
photometric accuracy
accuracy is
is needed
needed for
for science
science
Reflecting on design->deliver slides from
previous lectures….
•• Architectural
Architectural design
design -- ADD
ADD
–– Designing
Designing aa data
data model
model to
to capture
capture the
the physics
physics of
of
photometric
photometric calibration
calibration
•• Detailed
Detailed design
design –
– DDD
DDD
–– Working
Working out
out the
the details
details and
and writing
writing the
the code
code
••
••
••
New approaches
new balances
Quantify
Quantify
Build
Build
Qualify
Qualify –
– unit
unit tests
tests
1- calibration plan integrated
up-link /down link
Anarchy ç àcoordinated
Freedom ß à fixed system
Standard
Standard data
data products
products ç
ç àuser
àuser tuned
tuned products
products
Data releases ß à user defined hunting
DESIGN
5 Essential STEPS:
2 -Procedurizing
3 Data Model
• Procedurizing
–
– Data
Data taking
taking at
at telescope
telescope for
for both
both science
science and
and
calibration
calibration data
data -- Templates
Templates
•• Observing
Observing Modes:
Modes: —
—Stare
Stare —
—Jitter
Jitter —
—Dither
Dither —
—SSO
SSO
Sanity
Sanity checks
checks
•• Observing
Observing Strategies:
Strategies: —
—Stan
Stan —
—Deep
Deep —
—Freq
Freq —
—Mosaic
Mosaic
–
– Full
Full integration
integration with
with data
data reduction
reduction
–
– DesignDesign- ADD
ADD
–
– Data
Data model
model (classes)
(classes) defined
defined for
for data
data reduction
reduction and
and
calibration
calibration
–
– View
View pipeline
pipeline as
as an
an administrative
administrative problem
problem
Quality
Quality control
control
Image
Image pipeline
pipeline
Calibration
Calibration
procedures
procedures
Source
Source pipeline
pipeline
5
4 Integrated archive
and Large Data Volume
•• Handling
Handling of
of the
the data
data is
is non-trivial
non-trivial
–
– Pipeline
Pipeline data
data reduction
reduction
–
– Calibration
Calibration with
with very
very limited
limited resources
resources
–
– Things
Things change
change in
in time:
time:
–Physical
–Physical changes
changes (atmosphere,
(atmosphere, various
various gains)
gains)
–Code
–Code (new
(new methods,
methods, bugs)
bugs)
–Human
–Human insight
insight in
in changes
changes
–
– Working
Working with
with source
source lists
lists
Photometric calibration and the VO
• Now you have your result and you want to
share it…..=VO
• Describing photometry universally: UCDs
– Properties measurement: aperture…..
– Value and error
Science can only be archive based
Photometric calibration & VO
UCDs for photometry
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•
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E | phot
E | phot.antennaTemp
Q | phot.calib
C | phot.color
Q | phot.color.excess
Q | phot.color.reddFree
E | phot.count
E | phot.fluence
E | phot.flux
Q | phot.flux.bol
E | phot.flux.density
E | phot.flux.density.sb
E | phot.flux.sb
E | phot.limbDark
E | phot.mag
Q | phot.mag.bc
Q | phot.mag.bol
Q | phot.mag.distMod
E | phot.mag.reddFree
E | phot.mag.sb
How to compare magnitudes of
extended sources…
| Photometry
| Antenna temperature
| Photometric calibration
| Color index or magnitude difference
| Color excess
| Dereddened, reddening-free color
| Flux expressed in counts
| Fluence
| Photon flux
| Bolometric flux
| Flux density (per wl/freq/energy interval)
| Flux density surface brightness
| Flux surface brightness
| Limb-darkening coefficients
| Photometric magnitude
| Bolometric correction
| Bolometric magnitude
| Distance modulus
| Dereddened magnitude
| Surface brightness in magnitude units
NED: http://nedwww.ipac.caltech.edu
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