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Merge pull request #120 from lsst/tickets/SP-2937
SP-2937: updating the existing NB 302.3 to incorporate the revised ComCam->SDSS transformation equations from RTN-099 and to address user feedback provided in this Forum post.
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‎DP1/300_Science_Demos/302_Stars_MilkyWay_LocalVolume/302_3_Derived_stellar_properties.ipynb‎

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@@ -22,7 +22,7 @@
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"Data Release: <a href=\"https://dp1.lsst.io\">Data Preview 1</a> <br>\n",
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"Container Size: large <br>\n",
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"LSST Science Pipelines version: r29.2.0 <br>\n",
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"Last verified to run: 2025-10-29 <br>\n",
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"Last verified to run: 2026-02-17 <br>\n",
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"Repository: <a href=\"https://github.com/lsst/tutorial-notebooks\">github.com/lsst/tutorial-notebooks</a> <br>\n",
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"DOI: <a href=\"https://doi.org/10.11578/rubin/dc.20250909.20\">10.11578/rubin/dc.20250909.20</a> <br>"
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]
@@ -74,6 +74,8 @@
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"\n",
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"This notebook converts photometry from the Rubin's ComCam system to SDSS system and applies these calibrated relations to photometric data for F- and G-type main-sequence stars with 0.2 < $g–r$ < 0.6 to infer $T_{eff}$ and [Fe/H]. The expected precision is ∼100 K in temperature and ∼0.2 dex in metallicity, limited mainly by $u$-band photometric errors.\n",
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"\n",
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"**Note:** This tutorial provides a pedagogical framework for illustrating how to handle the DP1 photometry and is not intended to serve as a definitive catalog of stellar parameters. Users should be aware that the derived physical quantities—particularly [Fe/H] and Galactocentric coordinates—are sensitive to systematic uncertainties in distance estimation and interstellar extinction.\n",
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"\n",
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"**References:** See [Ivezić et al. (2008)](https://ui.adsabs.harvard.edu/abs/2008ApJ...684..287I/abstract) for stellar parameter derivation using their colors, and [RTN-099](https://rtn-099.lsst.io/) for photometric transformation from the Rubin's ComCam photometry to SDSS system.\n",
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"\n",
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"**Related tutorials:** See the 300-level DP1 tutorial on the Milky Way foreground dust correction."
@@ -351,24 +353,91 @@
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"source": [
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"### 2.3. Convert photometry to SDSS system\n",
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"\n",
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"Transform the dust-corrected photometry to the SDSS system, following the equations from [RTN-099](https://rtn-099.lsst.io/)."
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"First, calculate various stellar colors using dust-corrected magnitudes and store them as arrays for use in subsequent color-color transformation task."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1341ffdc-c169-454c-9689-c441bf90f669",
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"id": "7b6df3e3-cac8-4ea9-950e-024f53171a14",
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"metadata": {},
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"outputs": [],
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"source": [
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"ug = objtab[\"u_psfMag0\"] - objtab[\"g_psfMag0\"]\n",
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"gr = objtab[\"g_psfMag0\"] - objtab[\"r_psfMag0\"]\n",
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"gi = objtab[\"g_psfMag0\"] - objtab[\"i_psfMag0\"]\n",
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"ri = objtab[\"r_psfMag0\"] - objtab[\"i_psfMag0\"]\n",
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"ri = objtab[\"r_psfMag0\"] - objtab[\"i_psfMag0\"]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0534d9c7-c0dc-4bc8-ac78-4bfacb1899ec",
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"metadata": {},
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"source": [
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"Transform the LSSTComCam photometry in $gri$ to the SDSS system, following the equations in Section 1.3.5 of [RTN-099](https://rtn-099.lsst.io/). The valid color range of these transformations is $0.2 < (g-i)_{ComCam} < 3.0$."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1341ffdc-c169-454c-9689-c441bf90f669",
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"metadata": {},
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"outputs": [],
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"source": [
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"gi_mask = (gi > 0.2) & (gi <= 3.0)\n",
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"\n",
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"gi_sdss = 1.065*gi + 0.005\n",
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"gr_sdss = 1.058*gr + 0.058*ri - 0.002\n",
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"u_sdss = objtab[\"u_psfMag0\"] + 0.063*gi**2 - 0.192*gi + 0.263"
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"g_sdss = np.where(gi_mask, objtab[\"g_psfMag0\"] + 0.066*gi - 0.006, np.nan)\n",
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"r_sdss = np.where(gi_mask, objtab[\"r_psfMag0\"] + 0.007*gi - 0.005, np.nan)\n",
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"i_sdss = np.where(gi_mask, objtab[\"i_psfMag0\"] + 0.012*gi - 0.020, np.nan)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2c60a63e-fe42-4d38-a79e-7b72ae546b9b",
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"metadata": {},
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"source": [
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"Since LSSTComCam DP1 $u$-band exposures do not overlap with SDSS footprints, utilize synthetic photometry based on the Pickles Stellar Spectra Library ([Pickles 1998](https://iopscience.iop.org/article/10.1086/316197)) to derive the $u$-band transformations. Refer to Section 1.2.3 of [RTN-099](https://rtn-099.lsst.io/) for the detailed derivation and validation of these synthetic coefficients."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6c8dcb6b-bc9b-45f3-a220-211329952ca2",
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"metadata": {},
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"outputs": [],
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"source": [
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"u_masks = [\n",
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" (gi > -1.1) & (gi <= -0.4),\n",
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" (gi > -0.4) & (gi <= 0.8),\n",
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" (gi > 0.8) & (gi <= 3.9)\n",
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"]\n",
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"u_outputs = [\n",
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" objtab[\"u_psfMag0\"] + 0.587*gi**2 + 1.424*gi + 0.758,\n",
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" objtab[\"u_psfMag0\"] + 0.063*gi**2 - 0.192*gi + 0.263,\n",
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" objtab[\"u_psfMag0\"] - 0.0003*gi**2 + 0.174*gi + 0.059\n",
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"]\n",
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"u_sdss = np.select(u_masks, u_outputs, default=np.nan)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "46f6a525-cd24-4b97-881f-04d8993a070b",
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"metadata": {},
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"source": [
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"Calculate the required SDSS stellar colors and store them as new arrays for subsequent analysis."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c97d1db9-7c50-409d-b7fc-7a78b7b3dfea",
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"metadata": {},
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"outputs": [],
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"source": [
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"ug_sdss = u_sdss - g_sdss\n",
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"gr_sdss = g_sdss - r_sdss\n",
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"gi_sdss = g_sdss - i_sdss\n",
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"ri_sdss = r_sdss - i_sdss"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"g_cri = (objtab[\"g_psfMag0\"] > 14) & (objtab[\"g_psfMag0\"] < 19.5)\n",
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"gr_cri = (gr > 0.2) & (gr < 0.6)\n",
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"ug_gr_cri = ((ug > 0.7) & (ug < 2.0) &\n",
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" (gr - 0.5 * ug > -0.25) & (gr - 0.5 * ug < 0.05))\n",
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"gr_ri_cri = (0.35*gr - ri > -0.2) & (0.35*gr - ri < 0.1)"
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"g_cri = (g_sdss > 14) & (g_sdss < 19.5)\n",
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"gr_cri = (gr_sdss > 0.2) & (gr_sdss < 0.6)\n",
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"ug_gr_cri = ((ug_sdss > 0.7) & (ug_sdss < 2.0) &\n",
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" (gr_sdss - 0.5*ug_sdss > -0.25) & (gr_sdss - 0.5*ug_sdss < 0.05))\n",
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"gr_ri_cri = (0.35*gr_sdss - ri_sdss > -0.2) & (0.35*gr_sdss - ri_sdss < 0.1)"
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]
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},
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{
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"outputs": [],
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"source": [
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"sel = (A_band[\"r\"] < 0.3) & g_cri & gr_cri & ug_gr_cri & gr_ri_cri\n",
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"print(f\"There are {len(gr[sel])} stars suitable for this analysis.\")"
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"print(f\"There are {len(gr_sdss[sel])} stars suitable for this analysis.\")"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.scatter(np.ma.filled(ug[sel], np.nan), np.ma.filled(gr[sel], np.nan),\n",
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"plt.scatter(np.ma.filled(ug_sdss[sel], np.nan),\n",
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" np.ma.filled(gr_sdss[sel], np.nan),\n",
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" c=10**np.ma.filled(log_teff, np.nan), cmap=plt.cm.jet_r)\n",
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"plt.xlabel('u-g')\n",
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"plt.ylabel('g-r')\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"feh = feh_phot_ivezic2008(ug[sel], gr[sel])"
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"feh = feh_phot_ivezic2008(ug_sdss[sel], gr_sdss[sel])"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.scatter(ug[sel], gr[sel], c=feh, cmap=plt.cm.jet)\n",
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"plt.scatter(ug_sdss[sel], gr_sdss[sel], c=feh, cmap=plt.cm.jet)\n",
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"plt.xlabel('u-g')\n",
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"plt.ylabel('g-r')\n",
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"cb = plt.colorbar()\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"dmod = objtab[\"r_psfMag0\"][sel] - mr_phot_ivezic2008(gi[sel], feh)\n",
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"dmod = r_sdss[sel] - mr_phot_ivezic2008(gi_sdss[sel], feh)\n",
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"dist = 10**(0.2*(dmod+5))/1e3"
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]
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},

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