[PIPE2D-539] Stellar typing with HSC broad-band data Created: 07/Apr/20  Updated: 05/Jan/21  Resolved: 13/Oct/20

Status: Done
Project: DRP 2-D Pipeline
Component/s: None
Affects Version/s: None
Fix Version/s: None

Type: Story Priority: Normal
Reporter: Takuji Yamashita Assignee: Takuji Yamashita
Resolution: Done Votes: 0
Labels: flux-calibration
Remaining Estimate: Not Specified
Time Spent: Not Specified
Original Estimate: Not Specified

Attachments: PNG File BBPDF_ps7350_g4.0_z-0.25_a-0.1_sn200.png     PNG File gri_rmsRR.png     PNG File Lee11_BBPDF_t6780_g4.021_z-0.479_a-0.003_PMF2053-53446-346_forps.png     PNG File Lee11_BBSpec_t6780_g4.021_z-0.479_a-0.003_PMF2053-53446-346_forps.png     PNG File Lee11_BBSpec_t6780_g4.021_z-0.479_a-0.003_PMF2053-53446-346_forps.png     PNG File Lee11PS1_allspec_woblue.png     PNG File Lee11PS1_allspec_woblue.png     PNG File Lee11PS1BB_gr_chisq_grlt04.png     PNG File Lee11PS1BB_gr_rms_grlt04.png     PNG File sigmaclipRMS_PS1_onlyobs.png     PNG File sigmaclipRMS_PS1.png    
Issue Links:
Blocks
blocks PIPE2D-538 Stellar typing using broad band photo... Done
is blocked by PIPE2D-540 Generate a table of synthetic HSC col... Done
Story Points: 5
Epic Link: flux calibration
Sprint: 2DDRP-2021 A
Reviewers: hassan

 Description   

Classify stellar types of HSC stellar objects with HSC broad band data. Using HSC colors, we try to guess the best values of four parameters (Teff, log(g), Z, alpha element index), which will be used as an initial guess for spectral typing. A code and document will be provided.



 Comments   
Comment by Takuji Yamashita [ 21/Jul/20 ]

A test of broad band typing using HSC synthetic colors of parameter-interpolated AMBRE spectra. The typing is done by chi square probabilities.

This confidence contours are a result of a test spectrum (colors of S/N = 200, Teff = 7350K, Logg = 4.0, Z = 0.25, [alpha/Fe] = 0.1). From this confidence contours, we can find that Teff and Log g are well determined. The metallicity is sometime converged. We cannot determine the [alpha/Fe].

Comment by Takuji Yamashita [ 31/Aug/20 ]

I tried the broad band stellar typing of observed SDSS/SEGUE spectra using PS1 photometries.
This is not a final result because I have not yet corrected the galactic extinction of model spectra.
 
I used 32 F-stars of SDSS/SEGUE in Lee et al. (2011), AJ, 141, 90. The stars have PS1 photometries and g-r color < 0.4 (a color selection for F stars). Using the observed PS1 grizy fluxes and the synthetic PS1 fluxes of interpolated AMBRE models, I found the best fit model spectra.
 
An example of a SDSS spectrum (black), the best fit model (blue), and the best fit model which was convolved by a Gaussian kernel of FWHM=0.3nm (a substitute for LSF) (red).

 

Residuals of all the stars. (Please ignore the colors.) The residuals are distributed around zero. The large residuals at some line features are due to a miss-match of the LSF. 

 
 

Comment by Takuji Yamashita [ 11/Sep/20 ]

The Galactic extinction both for input fluxes and output model spectra was corrected. I used the SFD98 dust map in the `extinctions` Python package and the extinction curve of Fitzpatrick (1999) in the `dust_extinction` Python package. 
 
This is an example of a reproduced model spectrum and the same star as above. There are no big changes. 

 
A confidence contours of estimated parameters. 

 
Residuals of all the spectra. Residual = SDSS - Model 
Black — 0.2 < g-r < 0.4, red — g-r < 0.2.

 
 
R.M.S of the relative residuals on the gri color-color diagram.
Relative residual = (SDSS - Model) / SDSS * 100.
 
The green box is the F star selection window. I plot stars outside of the window for comparison. In the window, the RMS is about 10%.

 
 
 
 

Comment by Takuji Yamashita [ 11/Sep/20 ]

I checked the best model spectra when the flux uncertainties of PS1 become worse, in particularly, when they are comparable to the HSC level (magerr = 0.01), because the PS1 photometries of the stars we use have small magnitude errors, on average, ~0.003. 
 
This is the RMS of the relative residuals as a function of g - r colors. Three cases of the magnitude errors, 0.005, 0.01, 0.1 mag, are shown, as well as the original uncertainties. The means of RMS are 11.0 for the original and 12.8 for '0.01 mag’ (HSC level). Stars in the figure are the mean RMS.
 

Mean RMS: 
Original – 11.0
MagErr=0.005 – 11.9
MagErr=0.01 – 12.8
MagErr=0.1 – 18.5
 
 
Minimum reduced chi squares are distributed around 1, but the worst case (0.1 mag) shows the lowest value.

Mean min red. chisq: 
Original – 6.8
MagErr=0.005 – 6.1
MagErr=0.01 – 1.4
MagErr=0.1 – 0.6
 

Comment by Takuji Yamashita [ 29/Sep/20 ]

Robust RMS of fractional residuals. 
I use sigma clipping (3 sigma, 10 iterations) for the fractional residuals. This is roughly RMS of continuum. 
 
Mean robust RMSs:
Original: 4.0%
MagErr=0.005: 3.9%
MagErr=0.01: 4.2%
MagErr=0.1: 6.8%
 
Robust RMS and g-r color for the original and three cases of mag errors. 

 
This figure is only for the original PS1 data.

 
 
 

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