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LSST Calibration Simulation. WP1 - Simulation Main Program - Bogdan Popescu, Margaret Hanson, Brian Meadows, Mike Sokoloff (U. of Cincinnati), and David Cinabro (Wayne State University). WP2 - Standards and Targets - Lynne Jones and Zeljko Ivezic (U. of Washington, Seattle).

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slide1

LSST Calibration Simulation

WP1 - Simulation Main Program - Bogdan Popescu, Margaret Hanson, Brian Meadows, Mike Sokoloff (U. of Cincinnati), and David Cinabro (Wayne State University)

WP2 - Standards and Targets - Lynne Jones and ZeljkoIvezic (U. of Washington, Seattle)

WP3 - Instrument and Hardware Calibration - Raul Armendariz, Jim Frank and John Haggerty(Brookhaven and Harvard University)

WP4 - Auxiliary Instrumentation and Atmosphere - Jim Bartlett (APC Paris 7) and David Burke (SLAC)

WP 5 - Pipelines - Tim Axelrod (LSSTC) and representatives from WP1-WP4

August 2007 Bogdan Popescu

slide2

LSST Calibration Simulation

LSST Calibration Simulation Main Program (WP1)

LSST Operations Simulator

LSSTFOV(i)

Generate

References & Standards (WP2)

Standard SEDs

Simulate

Precursor Campaign

and Priors (WP2)

Standard s Catalog

Generate

Test Targets (WP2)

Target SEDs

Generate Instrument Response (WP3)

Ir(x,y,n,i)

Simulate

Calibration Pipeline (WP3)

Im(x,y,n,i)

Generate Instrument Calibration (WP3)

Flats and Bias

Generate

Aux Telescope Ops (WP4)

AUXFOV(j)

Simulate Aux Observing(WP4)

Aux Object Catalog

Zr(az,el,n,i/j)

Generate

Atmosphere(WP4)

Compute Model Source Catalog (WP1)

Simulate

Image Processing Pipeline (WP5)

Model Source Catalog

Simulation Analysis

and Reporting (WP1)

Object Catalog and Zm(az,el,n,i/j)

August 2007 Bogdan Popescu

slide3

LSST Calibration Simulation - WP1.part1+2

LSST Calibration Simulation Main Program (WP1)

i (obsHistID, fieldID), RA and Dec (fieldRA,fieldDec), elevation and azimuth (computed from RA, Dec,etc), camera rotation (rotSkyPos, rotTelPos), filter, date and time (expDate, expMJD, expTime), cloud conditions(xparency), sky brightness (skyBright)

LSST Operations Simulator

LSSTFOV(i)

Generate

References & Standards (WP2)

Standard SEDs

RA and Dec (standard stars), SED's (mean stellar spectra)

Simulate

Precursor Campaign

and Priors (WP2)

Standard s Catalog

Generate

Test Targets (WP2)

Target SEDs

RA and Dec (targets), SED's (mean stellar spectra)

Generate Instrument Response (WP3)

Ir(x,y,n,i)

ADUs (n,x,y,i)

Simulate

Calibration Pipeline (WP3)

Im(x,y,n,i)

Generate Instrument Calibration (WP3)

Flats and Bias

unknown (at this time)

Generate

Aux Telescope Ops (WP4)

j , RA and Dec , elevation and azimuth(computed from RA, Dec), date and time

AUXFOV(j)

Simulate Aux Observing(WP4)

Aux Object Catalog

Zr(az,el,n,i/j)

Atmospheric transmission(n)

Generate

Atmosphere(WP4)

Compute Model Source Catalog (WP1)ADUs, i,j, RA and Dec (azimuth, elevation), SEDs

Simulate

Image Processing Pipeline (WP5)

Model Source Catalog

Object Catalog and Zm(az,el,n,i/j)

Simulation Analysis

and Reporting (WP1)

August 2007 Bogdan Popescu

slide4

LSST Calibration Simulation

WP1 - LSSTFOV(i). Elevation, azimuth, camera rotation, filter, date and time, etc from LSST Operations Simulator output file. Indexed sequentially from i=1 to the total number of LSST visits in the observing period.

WP2 - Standard and Target SEDs. Top-of-the-atmosphere SEDs for reference (e.g. main sequence), standard (e.g. DA WD) stars, and test science targets (stars, and perhaps galaxies).

WP3 - Instrumental Response Ir(x,y,n,i). Response of the telescope and camera to photons (with frequency n) in the telescope pupil from sources on the sky that are imaged with centroid at (x,y) in the focal plane. Output is ADUs in the computer.

WP3 - Flats and Biases. Data used in the Calibration Pipeline - dome flats, bias frames, etc.

WP4 - AUXFOV(j). Operating parameters for the Auxiliary Telescope (AT); elevation, azimuth, instrument, exposure duration, date and time, etc. Indexed sequentially from j=1 to total number of AT visits in the observing period (not constrained to number of LSST visits).

WP4 - Atmospheric Extinction Zr(az,el,n,i/j). Extinction in the atmosphere for both LSST and AUX FOVs. Includes spatial (az,el) and temporal correlations for FOVs i and j.

WP1 - Model Image Catalog. Object-indexed catalog of photometric quantities (and others as appropriate) computed from modeled parameters for each LSST visit (two images). Output is in raw ADUs in the computer.

August 2007 Bogdan Popescu

slide5

LSST Calibration Simulation - UBERCAL

UBERCAL - "CMB-like" method (replace CMB temperature fluctuations with the magnitude of stars)

Relative calibration achieved using repeated observations. Absolute calibration obtained by

comparing with standard stars. That is not a new idea. New : large angular scale and accuracy.

The flux :

K=K(exposure time, detector efficiency, filter response, telescope optical system, atmosphere, SED)

(K gives the absolute calibration)

Conversion of flux to magnitude :

a(t) = optical response of the telescope and detectors

f(i,j;t) = detector flat fields (in magnitudes) (i,j= CCD coordinates)

k(t) x = atmospheric extinction (x = airmass = sec(z) in astronomy)

ADU - Analog -to-Digital Unit is the digitization of the analog detector output

August 2007 Bogdan Popescu

slide6

LSST Calibration Simulation - UBERCAL

Here t is for one night only;

tref = reference time, midnight usually.

(a, b, g indexing the appropriate a-term, k-term (and tref) and f-term)

j = counts multiple observations; i = ith star.

August 2007 Bogdan Popescu

slide7

LSST Calibration Simulation - UBERCAL

Using a large number of star (table example from SDSS*) and priors for k-terms and flat fields

(mean values), the accuracy can be < 1%.

Finaly :

Relative calibration + Zero Points (for each filter) = Absolute Calibration

* Padmanabhan et al, astro-ph/0703454v1

August 2007 Bogdan Popescu

slide8

LSST Calibration Simulation - UBERCAL

UBERCAL References :

Padmanabhan et al, astro-ph/0703454v1

Ivezic et al, astro-ph/0703157v1

August 2007 Bogdan Popescu

slide10

Package Description

The original plan for creating this package was to allow us to look at the various search

methods being applied to find massive clusters in the inner galaxy, and to figure out how

these are biased by distance, age, extinction, and compactness of the clusters.

We intended to create a simulation of our view of the MW with a variety of assumptions

about the distribution of clusters in the MW and to see if current search methods would 

find any differences.

We would base these MW simulations on what is seen in fully face-on galaxies that have

a similar star formation rate as the MW. Thus, this would be a reasonable first step

towards understanding the distribution and the characteristics of such clusters, since  

present searches have no way of determining their real 'limit' and sampling biases.  

August 2007 Bogdan Popescu

slide11

Package Description

MASSive CLuster - Mcluster = 103 - 104 - 105 - 106 solar masses

Evolution - log(Tyears) = 3.00 .. 10.20

ANalysis - HR diagrams, color-magnitude diagrams, FITS images *.

MASSCLEAN uses as input a small number of parameters :

mass , distance, age, King Model parameters (rt , rc), extinction (AV , RV), metalicity.

Using theoretical models - mass distribution (Salpeter IMF), stellar evolution (Geneva

Database), spatial distribution (King Model) and extinction (CCM Model) - MASSCLEAN

computes actual mass, absolute and apparent magnitude (UBVRIJHK), color indexes,

temperature, luminosity and position for all the stars (over 40 000 stars for 105 solar

masses cluster) and all the ages included in the Geneva Database.

* using SkyMaker (Bertin 2001, Bertin & Fouque 2001-2007)

August 2007 Bogdan Popescu

slide12

Package Description

Mass

Geneva Database

Mass Distribution

Stellar Evolution

Salpeter IMF

rt , rc

Spatial Distribution

King Model

Cluster Model

AV , RV

Extinction

CCM Model

Age

August 2007 Bogdan Popescu

slide13

RESULTS : Images & Extinction

August 2007 Bogdan Popescu

slide14

GENEVA DATABASE

Advantages :

Upper mass limit is 120 solar masses.

Fine grid.

Age range log(Tyears) = 3.00 .. 10.20

*. UBVRIJHKLM file example :

##

## Isochrone for log(age)= 6.250

# Tracks used: Models with overshooting and OPAL opacities, Z=0.020, 1 X Mdot, Schaller et al. (paper I)

# 555

# n M_initM_actlogTefflogglogL M( V) U-B B-V V-R V-I V-K R-I I-K J-H H-K K-L J-K J-L J-L2 K-M

# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

1 0.8000 0.8000 3.687 4.656 -0.612 6.628 0.847 0.960 0.527 0.949 2.274 0.423 1.319 0.513 0.085 0.076 0.598 0.674 0.676 0.552

2 0.8100 0.8100 3.691 4.654 -0.589 6.549 0.802 0.939 0.515 0.932 2.225 0.417 1.288 0.504 0.083 0.074 0.587 0.661 0.662 0.541

3 0.8200 0.8200 3.695 4.652 -0.566 6.470 0.757 0.917 0.504 0.914 2.175 0.410 1.256 0.494 0.081 0.071 0.575 0.647 0.648 0.530

4 0.8300 0.8300 3.699 4.650 -0.544 6.392 0.711 0.895 0.492 0.896 2.124 0.404 1.224 0.485 0.079 0.069 0.564 0.633 0.634 0.519

..............................................................

# iso_c020_0625. UBVRIJHKLM

c = basic grid

log(t) range : [3.00,10.20]

0.020 = metalicity Z

0625- log(t)=6.25

August 2007 Bogdan Popescu

slide15

RESULTS : Images - Westerlund1

August 2007 Bogdan Popescu

slide16

RESULTS : Images - H and CHI PERSEI

August 2007 Bogdan Popescu

slide17

MASSCLEAN References

Alvez, J. et al 2007, A&A,462,L17

Bertin, E. 2001, SkyMaker,

http://terapix.iap.fr/cplt/oldSite/soft/skymaker/

Charbonnel, C. et al 1993, A&A, 101, 415

Charbonnel, C. et al 1996, A&A, 115, 339

Charbonnel, C. et al 1999, A&A, 135, 405

Clark, J.S. & Negueruela, I 2002, A&A, 396, L25

Clark, J.S. et al 2005, A&A, 434, 949

Figer,D.F. et al 2006, ApJ, 643, 1166

Gutermuth, R.A. et al 2005, ApJ, 632, 397

Hanson, M. M, Near Infrared tehniques for the study

of Massive Star Populations in the Milky Way,

in Astronomical Society of the Pacific

Conference Series, volume 322, The Formation

and Evolution of Massive Young Star Clusters,

proceedings of a meeting held in Cancun,

Mexico, 2003, 17-21 November

Johnstone,D & Bally,J. 2006, ApJ, 653, 383

King, I. 1962, AJ, 67, 471

Lejeune, T. & Schaerer, D. 2001, A&A, 366, 538

Maeder, A. & Meynet, G. 2000, ARA&A, 38, 143

Martins,F. & Plez,B. 2006, A&A, 457, 637

Massey, P. et al 2002, ApJ, 565, 982

Meynet, G. et al 1994, A&AS, 103, 97

Mowlavi, N. et al 1998, A&AS, 128, 471

Muno, M.P. et al. 2006, ApJ, 636, L41

Negueruela, I. & Clark, J.S. 2005, A&A, 436, 541

Oey, M.S. & Clarke,C.J. 2005, ApJ, 620, L43

Piatti, A.E. et al. 1998, A&AS, 127, 423

Salpeter, E.E. 1955, ApJ, 121, 161S

Schaerer, D. et al 1993, A&AS, 102, 339

Schaerer, D. et al 1993, A&AS, 98, 523

Schaller, G. et al 1992, A&AS, 96, 269

Westerlund, B. 1961, PASP, 73, 51

August 2007 Bogdan Popescu