{ "cells": [ { "cell_type": "markdown", "id": "b04b1a64", "metadata": {}, "source": [ "# JWST Implementing Detector Effects in Simulations\n", "\n", "Experience and analyses during JWST Cycle 1 showed that various detector systematics were the largest driver of systematic differences between actual measured PSFs and simulations. Physically, the result is that some photo-electron signals are measured in different pixels than the incident photon hit, acting to blur PSFs slightly. STPSF was originally designed as an optics-only simulation, leaving it up to users to optionally use other codes to model detector non-ideal behaviors. \n", "\n", "
\n", "\n", "To make simulated PSFs a closer match to data \"right out of the box\", STPSF as of release 1.2 includes simplified models to add significant detector effects into simulated PSFs for NIRCam, NIRISS, and MIRI. \n", "
\n", "\n", "These effects come in two flavours:\n", " 1. Interpixel capacitance (IPC, for NIRCam, NIRISS, and MIRI) and Post-pixel coupling (PPC, NIRCam only), via convolution kernels measured from flight and ground-testing data.\n", " 2. Charge diffusion, via a simple ad hoc Gaussian convolution, with parameters tuned to match in-flight empirical PSFs for NIRCam, NIRISS, and MIRI. " ] }, { "cell_type": "markdown", "id": "5d801438-5428-40a5-8c2c-906a0865c9e8", "metadata": {}, "source": [ "## Detector physics is complicated. \n", "\n", "Please note that these are *simplified* models of extremely complex detector physics and nonlinearity. \n", "The true physical behavior is more complex, and includes for instance illumination- and time-dependent variations often referred to as the \"brighter-fatter effect\". See for instance [Plazas et al. 2018](https://iopscience.iop.org/article/10.1088/1538-3873/aab820/meta), [Argyriou et al. 2023](https://ui.adsabs.harvard.edu/abs/2023arXiv230313517A/abstract). Detector physics modeling at that level is outside of the scope of STPSF. \n", "The included models of detector effects represent a first pass effort, and we expect will continue to be refined in fidelity over time. \n", "\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "8265f6a8", "metadata": {}, "outputs": [], "source": [ "import stpsf\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "89d7be20", "metadata": {}, "source": [ "## Understanding output PSF products, and where to find the PSFs with detector effects\n", "\n", "Recall that PSF outputs are returned as FITS HDULists with multiple extensions, for instance like: \n", "\n", "```\n", "Filename: (No file associated with this HDUList)\n", "No. Name Ver Type Cards Dimensions Format # Comment\n", " 0 OVERSAMP 1 PrimaryHDU 104 (236, 236) float64 # Ideal PSF, oversampled\n", " 1 DET_SAMP 1 ImageHDU 106 (59, 59) float64 # Ideal PSF, detector-sampled\n", " 2 OVERDIST 1 ImageHDU 153 (236, 236) float64 # With distortions, oversampled\n", " 3 DET_DIST 1 ImageHDU 159 (59, 59) float64 # With distortions, detector-sampled\n", "```\n", "\n", "\n", "The first two extensions give the \"ideal\" diffractive PSF (i.e. \"photons only\"). Geometric distortion effects and detector charge transfer effects are then added to create the last two extensions, named OVERDIST and DET_DIST. The charge diffusion kernel, a continuous effect, is present in both of those; the IPC effect, which is inherently a quantized effect acting on physical detector pixels, is applied after downsampling to detector resolution and is thus only present in the DET_DIST extension by default. \n", "\n", "
\n", "\n", "**To make use of the detector-effects-included PSFs, in general use the DET_DIST (last) FITS extension of the output PSF FITS file.**\n", " \n", "
" ] }, { "cell_type": "markdown", "id": "f06261fc", "metadata": {}, "source": [ "## NIRCam Simulation with detector effects: charge diffusion and IPC+PPC \n", "\n", "These effects are now included in simulated PSFs by default. " ] }, { "cell_type": "code", "execution_count": 5, "id": "1d7cf6f6", "metadata": {}, "outputs": [], "source": [ "nrc = stpsf.NIRCam()\n", "nrc.filter = 'F212N'\n", "fov_pixels = 59\n", "single_stpsf_nircam = nrc.calc_psf(fov_pixels=fov_pixels)" ] }, { "cell_type": "markdown", "id": "3f25972e", "metadata": {}, "source": [ "We use a simple Gaussian convolution as a proxy of charge diffusion. The value of sigma is parameterized as arcseconds for convenience. The current values of sigma are placeholders that can be change in order to better fit observations. You can access the detector charge diffusion default values from stpsf.constants" ] }, { "cell_type": "code", "execution_count": 9, "id": "508e5c34", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'NIRCAM_SW': 0.0062, 'NIRCAM_LW': 0.018, 'NIRISS': 0.0202, 'FGS': 0.07, 'NIRSPEC': 0.036, 'MIRI': 0.001}\n" ] } ], "source": [ "print(stpsf.constants.INSTRUMENT_DETECTOR_CHARGE_DIFFUSION_DEFAULT_PARAMETERS)" ] }, { "cell_type": "markdown", "id": "ce2247b0", "metadata": {}, "source": [ "## NIRCam Simulation without detector effects\n", "\n", "For comparison, let's calculate a PSF with these effects disabled. \n", "\n", "Detector effects can be deactivated via the 'charge_diffusion_sigma' and 'add_ipc' options. Similarly, the 'charge_diffusion_sigma' option can be use to vary sigma to better fit observations. " ] }, { "cell_type": "code", "execution_count": 10, "id": "491ee04c", "metadata": {}, "outputs": [], "source": [ "nrc = stpsf.NIRCam()\n", "nrc.filter = 'F212N'\n", "nrc.options['charge_diffusion_sigma'] = 0\n", "nrc.options['add_ipc'] = False\n", "fov_pixels = 59\n", "single_stpsf_nircam_no_effects = nrc.calc_psf(fov_pixels=fov_pixels)\n" ] }, { "cell_type": "markdown", "id": "830145e2", "metadata": {}, "source": [ "## Comparison between simulations with and without detector effects" ] }, { "cell_type": "code", "execution_count": 11, "id": "82ce3cce", "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, (ax1, ax2, ax3) = plt.subplots(1, 3,figsize=(14,7), sharey=True)\n", "\n", "stpsf.display_psf(single_stpsf_nircam_no_effects, ext = 3, title = 'w/o detector effects', cmap = 'viridis', ax = ax1, colorbar=False )\n", "stpsf.display_psf(single_stpsf_nircam, ext = 3, title = 'detector effects', cmap = 'viridis', ax = ax2, colorbar=False )\n", "stpsf.display_psf_difference(single_stpsf_nircam,single_stpsf_nircam_no_effects, ext1 = 3, ext2 = 3, title = 'Difference', cmap = 'viridis', ax = ax3, colorbar=False )\n" ] }, { "cell_type": "markdown", "id": "d69fd9ec", "metadata": {}, "source": [ "The above shows a comparison between simulations with and without detector effects. From the difference between simulations, it shows that our charge diffusion term is the leading term by broadening the simulated PSF." ] }, { "cell_type": "markdown", "id": "d365e2d2", "metadata": {}, "source": [ "## Comparison with observations of empirical PSFs\n", "We are going to compare NIRISS observations and stpsf simulations with and without detector effects. \n", "For this we are using the set of effective point-spread function (ePSF) presented in [Libralato et al 2023 ApJ 950 101](https://ui.adsabs.harvard.edu/abs/2023ApJ...950..101L/abstract). " ] }, { "cell_type": "markdown", "id": "353646b1", "metadata": {}, "source": [ "Let's define a simple function to meassure FWHM for our set of observed and simulated PSFs. Note that we could also use stpsf.measure_fwhm to acomplish the same result. " ] }, { "cell_type": "code", "execution_count": 160, "id": "075149f5", "metadata": {}, "outputs": [], "source": [ "def measure_fwhm(array):\n", " \"\"\"Fit a Gaussian2D model to a PSF and return the fitted PSF\n", " the FWHM is x and y can be found with fitted_psf.x_fwhm, fitted_psf.y_fwhm\n", "\n", " Parameters\n", " ----------\n", " array : numpy.ndarray\n", " Array containing PSF\n", "\n", " Returns\n", " -------\n", " x_fwhm : float\n", " FWHM in x direction in units of pixels\n", "\n", " y_fwhm : float\n", " FWHM in y direction in units of pixels\n", " \"\"\"\n", " from astropy.modeling import models, fitting\n", " yp, xp = array.shape\n", " y, x, = np.mgrid[:yp, :xp]\n", " p_init = models.Gaussian2D(amplitude = array.max(), x_mean=xp*0.5,y_mean=yp*0.5)\n", " fit_p = fitting.LevMarLSQFitter()\n", " fitted_psf = fit_p(p_init, x, y, array)\n", " return fitted_psf\n" ] }, { "cell_type": "markdown", "id": "3a381fac", "metadata": {}, "source": [ "First, we simulate and calculate the FWHM for the PSFs without detector effects for all NIRISS filters. " ] }, { "cell_type": "code", "execution_count": 147, "id": "efe87ee0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting F090W simulation without detector effects\n", "Starting F115W simulation without detector effects\n", "Starting F140M simulation without detector effects\n", "Starting F150W simulation without detector effects\n", "Starting F158M simulation without detector effects\n", "Starting F200W simulation without detector effects\n", "Starting F277W simulation without detector effects\n", "Starting F356W simulation without detector effects\n", "Starting F380M simulation without detector effects\n", "Starting F430M simulation without detector effects\n", "Starting F444W simulation without detector effects\n", "Starting F480M simulation without detector effects\n" ] } ], "source": [ "wave_arr = np.array([])\n", "fwhm_fun_arr_no_effects = np.array([])\n", "for filters in niriss.filter_list[:-1]:\n", " niriss = stpsf.NIRISS()\n", " niriss.filter = filters\n", " niriss.options['charge_diffusion_sigma'] = 0\n", " niriss.options['add_ipc'] = False\n", " fov_pixels = 25\n", " print('Starting {} simulation without detector effects'.format(filters))\n", " single_stpsf_niriss_no_effects = niriss.calc_psf(fov_pixels=fov_pixels)\n", " wave_arr = np.append(wave_arr, single_stpsf_niriss_no_effects[3].header['WAVELEN'])\n", " fitted_psf = measure_fwhm(single_stpsf_niriss_no_effects[3].data)\n", " fwhm_fun_arr_no_effects = np.append(fwhm_fun_arr_no_effects,np.sqrt(fitted_psf.x_fwhm * fitted_psf.y_fwhm)*niriss.pixelscale)\n" ] }, { "cell_type": "markdown", "id": "821d454e", "metadata": {}, "source": [ "Then, we perform the simulation and FWHM calculation for the PSFs with the inclusion of detector effects" ] }, { "cell_type": "code", "execution_count": 150, "id": "903f7156", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting F090W simulation with detector effects\n", "Starting F115W simulation with detector effects\n", "Starting F140M simulation with detector effects\n", "Starting F150W simulation with detector effects\n", "Starting F158M simulation with detector effects\n", "Starting F200W simulation with detector effects\n", "Starting F277W simulation with detector effects\n", "Starting F356W simulation with detector effects\n", "Starting F380M simulation with detector effects\n", "Starting F430M simulation with detector effects\n", "Starting F444W simulation with detector effects\n", "Starting F480M simulation with detector effects\n" ] } ], "source": [ "wave_arr = np.array([])\n", "fwhm_fun_arr = np.array([])\n", "for filters in niriss.filter_list[:-1]:\n", " niriss = stpsf.NIRISS()\n", " niriss.filter = filters\n", " fov_pixels = 25\n", " print('Starting {} simulation with detector effects'.format(filters))\n", " single_stpsf_niriss = niriss.calc_psf(fov_pixels=fov_pixels)\n", " wave_arr = np.append(wave_arr, single_stpsf_niriss[3].header['WAVELEN'])\n", " fitted_psf = measure_fwhm(single_stpsf_niriss[3].data)\n", " fwhm_fun_arr = np.append(fwhm_fun_arr,np.sqrt(fitted_psf.x_fwhm * fitted_psf.y_fwhm)*niriss.pixelscale)\n" ] }, { "cell_type": "markdown", "id": "dd9f5738", "metadata": {}, "source": [ "Let's take a look at the observed ePSF for NIRISS. For this you will need to download all the NIRISS ePSFs into a local folder. The NIRISS ePSFs from Libralato et al [may be retrieved from this web site](https://www.stsci.edu/~jayander/JWST1PASS/LIB/PSFs/STDPSFs/NIRISS/). " ] }, { "cell_type": "code", "execution_count": 143, "id": "b4368717", "metadata": {}, "outputs": [], "source": [ "from glob import glob\n", "stdpsf = (glob('STDPSF_NIRISS/*fits'))\n", "stdpsf.sort()" ] }, { "cell_type": "markdown", "id": "7c69165e", "metadata": {}, "source": [ "Note the ePSFs are 4x oversample, corresponding to a radial distance of 12.5 real NIRISS pixels. Conveniently this is the same oversampling factor that stpsf uses by default. " ] }, { "cell_type": "code", "execution_count": 144, "id": "02fa2b91", "metadata": {}, "outputs": [], "source": [ "from astropy.io import fits\n", "from scipy import ndimage\n", "fwhm_fun_arr_epsf = np.array([])\n", "\n", "for fn in stdpsf:\n", " hd = fits.open(fn)\n", " eps_data = ndimage.zoom(hd[0].data[12],0.25) # the ePSF is binned down to detector-sampled\n", " fitted_psf_epsf = measure_fwhm(eps_data)\n", " fwhm_fun_arr_epsf = np.append(fwhm_fun_arr_epsf,np.sqrt(fitted_psf_epsf.x_fwhm * fitted_psf_epsf.y_fwhm)*niriss.pixelscale)\n" ] }, { "cell_type": "code", "execution_count": 151, "id": "b679aa9c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 151, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = [8,12])\n", "plt.subplot(2,1,1)\n", "plt.plot(wave_arr*1e6,fwhm_fun_arr_no_effects, 'r^-' , label = 'STPSF: no Detector Effects')\n", "plt.plot(wave_arr*1e6,fwhm_fun_arr, 'ko-', label = 'STPSF: with detector effects' )\n", "plt.plot(wave_arr*1e6,fwhm_fun_arr_epsf, 'm^-', label = 'STDPSF_NIRISS' )\n", "plt.xlabel('Weighted mean wavelength in microns ')\n", "plt.ylabel('PSF FWHM (arcseconds)')\n", "plt.legend(loc = 2)\n", "plt.subplot(2,1,2)\n", "plt.plot(wave_arr*1e6,(fwhm_fun_arr_epsf - fwhm_fun_arr)*100/fwhm_fun_arr_epsf, 'ko-', label = 'measure_fwhm' )\n", "plt.xlabel('Weighted mean wavelength in microns ')\n", "plt.ylabel('ePSF - STPSF (%)')\n", "plt.legend(loc = 0)" ] }, { "cell_type": "markdown", "id": "00ec0425", "metadata": {}, "source": [ "From the comparison above it is clear that stpsf simulations with detector effects are a good match to observations. Note that our basic implementation for charge diffusion is wavelength-independent. However, it is clear that at longer wavelengths we should adjust sigma_charge_difussion to obtain a better fit." ] }, { "cell_type": "markdown", "id": "9a64f49e", "metadata": {}, "source": [ "## Comparison to measured PSFs for other instruments\n", "\n", "Comparisons with preliminary (unpublished, but to be published soon) ePSFs for NIRCam and MIRI shows similarly good matches of stpsf 1.2 outputs to the measured ePSFs. \n", "\n", "This comparison includes NIRCam (all detectors in SW and LW in many filters), and MIRI (all imaging filters). \n", "\n", "These tests do provide evidence for a small dependence of the charge diffusion length scale on wavelength or filter, as expected from theory, and differences in detail between the NIRCam detectors. The adopted parameters currently in stpsf as defaults were selected as to achieve well-balanced average fits over the full focal plane and all filters for each instrument. \n", "\n", "You may find that adjusting the `charge_diffusion_sigma` parameter slightly up or down will allow more precise fits to your particular science data. The STPSF team welcomes feedback about what parameters work well for particular datasets, as input into ongoing work to further refine these models. " ] }, { "cell_type": "markdown", "id": "6671c5a2", "metadata": {}, "source": [ "## What about NIRSpec? Or FGS? \n", "\n", "Implementation of improved PSF models is prioritizing the imaging instruments first. \n", "\n", "Note that IPC effects are yet to be implemented in NIRSpec and FGS simulations, pending available flight calibrations to precisely quantify the IPC effects in those detectors. \n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "575dd903", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "89334f7b", "metadata": {}, "source": [ "## Detector effects in effective PSF grids\n", "\n", "Detector effects are included in effective PSF grids calculated with the `psf_grid` function, too. No special effort or function call parameters are needed for this; it's automatic. \n", "\n", "In particular the `psf_grid` calculation now includes an adjusted implementation of the IPC effect which enables self-consistently including the IPC effect in reconstructed ePSFs on subpixel scales. \n" ] }, { "cell_type": "code", "execution_count": null, "id": "fa9aac98", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "python", "version": "3.11.7" } }, "nbformat": 4, "nbformat_minor": 5 }