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A package to gnerate a catalog of NIR guide stars for the TMT AO observations.

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TMT-IRGSC

Introduction

This is a python repository dedicated to the development of the Near-Infrared Guide Star Catalog (IRGSC) for the Adaptive Optics (AO) observations of the Thirty Meter Telescope (TMT) project. This package generates the catalog by computing the NIR magnitudes of the optical stellar sources in the PANSTARSS DR2 data.

Packages

irgsctool:

This is a python package aimed to compute the NIR magnitudes of the optical sources in the PANSTARRS stack-photometric data by modelling them with the Kurucz, Castelli-Kurucz and Phoenix stellar atmospheric models. This package also validates the computed NIR magnitudes with the observed NIR data from UKIDSS (if it is available). The methodology implemented in this python package is implemented on twenty test-fields across the TMT's observable sky and the generated as well as validated IRGSC is available on the GitHub homepage. Most of the sources have the computed NIR magnitudes similar to the observed. The generated catalog contains astrometric information from GAIA DR3 also. Read the section below to see the nature of IRGSC.

Nature of the generated catalog

The IRGSC generated has various information about the sources shown in the following Table. This table describes the columns in the IRGSC generated for a particular test field. The details of the flags, e.g., infoflags, filterflags, and qualityflags can be found here. These flags indicate various values assigned to the source by the PANSTARRS team, which gives further information about the nature of the source and the quality of its detection, which can help understand more about a particular object of interest. It is to be noted that although this package relies on the PANSTARRS StackObjectView table, the Right Ascension and Declination of the source is obtained from the mean photometric information as they are well calibrated using Gaia DR2.

Column Name Description Data Type
PS1_ObjID Source identifier in the PANSTARRS data float
PS1_ra Right Ascencion of the source in the PANSTARRS DR2 weighted mean photometry float
PS1_ra_error Uncertainty in PS1_ra float
PS1_dec Declination of the source in the PANSTARRS DR2 weighted mean photometry float
PS1_dec_error Uncertainty in the PS1_dec float
PS1_gpsf psf magnitude of the source in the g-band stacked photometry float
PS1_gpsf Uncertainty in PS1_gpsf
PS1_rpsf psf magnitude of the source in the r-band stacked photometry float
PS1_rpsf Uncertainty in PS1_rpsf float
PS1_ipsf psf magnitude of the source in the i-band stacked photometry float
PS1_ipsf Uncertainty in PS1_ipsf float
PS1_zpsf psf magnitude of the source in the z-band stacked photometry float
PS1_zpsf Uncertainty in PS1_zpsf float
PS1_ypsf psf magnitude of the source in the y-band stacked photometry float
PS1_ypsf Uncertainty in PS1_ypsf float
SAM_Name Name of the best-fitted Stellar Atmospheric Model (SAM) string
Teff Best-fitted model parameter: Teff float
logg Best-fitted model parameter: log(g) float
[Fe/H] Best-fitted model parameter: [Fe/H] float
sam_g Best-fitted model magnitudes in PANSTARRS g-filter float
sam_r Best-fitted model magnitudes in PANSTARRS r-filter float
sam_i Best-fitted model magnitudes in PANSTARRS i-filter float
sam_z Best-fitted model magnitudes in PANSTARRS z-filter float
sam_y Best-fitted model magnitudes in PANSTARRS y-filter float
sam_j Best-fitted model magnitudes in PANSTARRS j-filter float
sam_h Best-fitted model magnitudes in PANSTARRS h-filter float
sam_k Best-fitted model magnitudes in PANSTARRS k-filter float
scale factor The scale factor computed after fitting the SAM float
scale factor error Error in the computed scale factor float
d_dev The parameter denoting the goodness-of-fit float
Computed J The computed J magnitude in the Vega system float
Computed J error Error in computed J magnitude float
Computed H The computed H magnitude in the Vega system float
Computed H error Error in computed H magnitude float
Computed K The computed K magnitude in the Vega system float
Computed K error Error in computed K magnitude float
gaia source id Source identifier in Gaia DR3 float
gaia ra Right Ascension of the source in Gaia DR3 catalog float
gaia ra error Uncertainty in gaia ra float
gaia dec Declination of the source in Gaia DR3 catalog float
gaia dec error Uncertainty in gaia dec float
gaia parallax Parallax (mas) of the source in the Gaia DR3 catalog float
gaia parallax error Uncertainty in gaia parallax float
gaia pm pm of the source (mas/yr) in Gaia DR3 catalog float
gaia pm ra pm of the source along R.A. axis in the Gaia DR3 catalog float
gaia pm ra error Uncertainty gaia pm ra float
gaia pm dec pm of the source along Dec. axis in the Gaia DR3 catalog float
gaia pm dec error Uncertainty gaia pm dec float
gaia ruwe Renormalised Unit Weight Error flag of the source in Gaia DR3 float
objinfoflag These flag values of the source in PANSTARRS data specify whether the object is a QSO, transient, asteroid, extended, a known solar system object, etc. in nature float
objqualityflag These flag values denote if an object is real or a possible false positive float
ndetections The number of times something is detected from the individual exposures float
nstackdetections The number of stack detections after which the stack photometric measurements are done float
ginfoflag These flags indicate the details of the g filter stack photometry float
ginfoflag2 These flags indicate the details of the g filter stack photometry float
ginfoflag3 These flags indicate the details of the g filter stack photometry float
rinfoflag These flags indicate the details of the r filter stack photometry float
rinfoflag2 These flags indicate the details of the r filter stack photometry float
rinfoflag3 These flags indicate the details of the r filter stack photometry float
iinfoflag These flags indicate the details of the i filter stack photometry float
iinfoflag2 These flags indicate the details of the i filter stack photometry float
iinfoflag3 These flags indicate the details of the i filter stack photometry float
zinfoflag These flags indicate the details of the z filter stack photometry float
zinfoflag2 These flags indicate the details of the z filter stack photometry float
zinfoflag3 These flags indicate the details of the z filter stack photometry float
yinfoflag These flags indicate the details of the y filter stack photometry float
yinfoflag2 These flags indicate the details of the y filter stack photometry float
yinfoflag3 These flags indicate the details of the y filter stack photometry float
SAM The name of the best-fitted Stellar Atmospheric Model (SAM) string

Application of irgsctool on fields

The method developed for the generation of IRGSC has applied on twenty test fields across the sky. The generaed IRGSC is also valiated using the UKIDSS data available for those fields and the generated as well as validated catalog for these fields can be found in the 'generated_irgsc' directory. In addition to the twenty test fields, additional ten catalogs are provided for the PANSTARRS Medium Deep Survey (MDS) Fields more information available here. Since the MDS data is not publically released by the PANSTARRS, the optical data to generate the IRGSC for these fields is been taken from the PANSTARRS $3\pi$ survey.

R.A. Decl. l b E(B-V)
227.26 0.0 359.27 47.24 0.04
335.00 -1.25 61.96 -45.43 0.07
60.00 1.25 188.72 -36.53 0.26
30.00 0.50 156.53 -57.82 0.02
11.16 7.83 120.00 -55.00 0.04
225.53 2.19 0.00 50.00 0.04
269.93 -13.48 15.00 5.00 0.98
334.80 50.96 100.00 -5.00 0.28
324.09 51.47 95.00 -0.50 2.48
298.02 34.02 70.00 3.00 1.01
0.00 0.00 96.33 -60.18 0.02
34.50 -5.16 169.97 -59.87 0.01
36.25 -4.50 171.65 -58.22 0.02
164.25 57.66 148.39 53.43 0.04
66.75 15.86 180.08 -22.32 0.58
82.25 -2.60 205.62 -19.48 0.62
189.83 0.00 296.33 62.71 0.01
150.25 10.00 227.71 46.40 0.03
15.0 0.90 127.47 -61.89 0.02
35.0 -3.50 168.62 -58.28 0.01

Requirements

This package is developed for Python versions above 3.6. It uses various other packages like: astroquery, astropy, matplotlib, astropy, dustmaps, numpy, datetime, requests, and pyvo.

Note: It is recommended to install irgsctool in a fresh environment and requires a stable internet connection to fetch the data.

Installation

1. Using pip:

pip install irgsctool

2. Using .zip file from GitHub:

Download the .zip file from here and unzip it. Then open the directory in terminal and type:

pip install .

3 Using the Development version from GitHub:

pip install git+https://github.com/sshah1502/irgsc@main

Usage

 class GenerateIRGSC

This class is defined by importing irgsctool module and passing the R.A. and Decl. arguments. In this package, the catalog is generated using the optimal method described in the work report (link). After initializing, this module alerts the user if there is no observed NIR UKIDSS data for the given field.

from irgsctool import GenerateIRGSC as GC
gc = GC(ra(float),dec(float))
gc.generate_irgsc()

The module Generate_IRGSC is the module that generates the catalog in .csv format. Irrespective of whether UKIDSS data is available or not, this module (the command gc.generate_irgsc()) generates the catalog using the optical PANSTARRS data from 3pi steradian survey for given ra (float) and decl.(float). The name of the generated catalog has IRGSC prefix followed by RA, Dec., and the data of generation. eg. IRGSC_RA_0_0_DEC_0_0.csv for (ra,dec) = (0.0, 0.0)

class Validate

from irgssctool import Validate vd = Validate(ra,dec) vd.validate()

The module Validate(ra,dec) is the module that validates the computed NIR magnitudes after importing the IRGSC library. If initialized without generating the catalog, this module independantly checks whether the UKIDSS observed NIR data can be obtained for the given field.

# Conclusion/Disclaimer

Please add the following acknowledgment if you use our package in your work.

"This work has made use of "tmt-irgsc" developed as part of the Thirty Meter Telescope (TMT) project."

If you have any questions or suggestions for improvements to this repo,
please contact the owners of the repository.

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A package to gnerate a catalog of NIR guide stars for the TMT AO observations.

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