In this paper we apply ideas from information theory to create a method for the design of optimal filters for photometric redshift estimation. We show the method applied to a series of simple example filters in order to motivate an intuition for how photometric redshift estimators respond to the properties of photometric passbands. We then design a realistic set of six filters covering optical wavelengths that optimize photometric redshifts for $z <= 2.3$ and $i < 25.3$. We create a simulated catalog for these optimal filters and use our filters with a photometric redshift estimation code to show that we can improve the standard deviation of the photometric redshift error by 7.1% overall and improve outliers 9.9% over the standard filters proposed for the Large Synoptic Survey Telescope (LSST). We compare features of our optimal filters to LSST and find that the LSST filters incorporate key features for optimal photometric redshift estimation. Finally, we describe how information theory can be applied to a range of optimization problems in astronomy.
To investigate in more details of Stellar Abundance and Galactic Evolution (SAGE) and in a huge sample, we are performing a northern sky photometric survey named SAGES with the SAGE photometric system, which consists of 8 filters: Strömgren-$u$, SAGE-$v$, SDSS $g$, $r$, $i$, DDO-$51$, $Hα_{wide}$, and $Hα_{narrow}$, including three Sloan broadband filters, three intermediate-band filters and two narrow-band filters, and one newly-designed narrow-band filter. SAGES covers $\sim$12,000 square degrees of the northern sky with $δ> -5 ^{\circ}$, excluding the Galactic disk ($|b|<10^{\circ}$) and th…
The Chinese Space Station Optical Survey (CSS-OS) is a major science project of the Space Application System of the China Manned Space Program. This survey is planned to perform both photometric imaging and slitless spectroscopic observations, and it will focus on different cosmological and astronomical goals. Most of these goals are tightly dependent on the accuracy of photometric redshift (photo-z) measurement, especially for the weak gravitational lensing survey as a main science driver. In this work, we assess if the current filter definition can provide accurate photo-z measurement to mee…
This paper describes the characterization of the GALANTE photometric system, a seven intermediate- and narrow-band filter system with a wavelength coverage from 3000 $Å$ to 9000 $Å$ . We describe the photometric system presenting the full sensitivity curve as a product of the filter sensitivity, CCD, telescope mirror, and atmospheric transmission curves, as well as some first- and second-order moments of this sensitivity function. The GALANTE photometric system is composed of four filters from the J-PLUS photometric system, a twelve broad-to-narrow filter system, and three exclusive filters, s…
We present a new photometric calibration of the WFC3-UVIS and WFC3-IR detectors based on observations collected from 2009 to 2020 for four white dwarfs, namely GRW+70~5824, GD~153, GD~71, G191B2B, and a G-type star, P330E. These calibrations include recent updates to the Hubble Space Telescope primary standard white dwarf models and a new reference flux for Vega. Time-dependent inverse sensitivities for the two WFC3-UVIS chips, UVIS1 and UVIS2, were calculated for all 42 full-frame filters, after accounting for temporal changes in the observed count rates with respect to a reference epoch in 2…
The China Space Station Telescope (CSST) photometric survey aims to perform a high spatial resolution (~0.15'') photometric imaging for the targets that cover a large sky area (~17,500 deg^2) and wide wavelength range (from NUV to NIR). It expects to explore the properties of dark matter, dark energy, and other important cosmological and astronomical areas. In this work, we evaluate whether the filter design of the Multi-channel Imager (MCI), one of the five instruments of the CSST, can provide accurate photometric redshift (photo-z) measurements with its nine medium-band filters to meet the r…
We present the photometric calibration of the twelve optical passbands observed by the Javalambre Photometric Local Universe Survey (J-PLUS). The proposed calibration method has four steps: (i) definition of a high-quality set of calibration stars using Gaia information and available 3D dust maps; (ii) anchoring of the J-PLUS gri passbands to the Pan-STARRS photometric solution, accounting for the variation of the calibration with the position of the sources on the CCD; (iii) homogenization of the photometry in the other nine J-PLUS filters using the dust de-reddened instrumental stellar locus…
We present a flexible template-based photometric redshift estimation framework, implemented in C#, that can be seamlessly integrated into a SQL database (or DB) server and executed on-demand in SQL. The DB integration eliminates the need to move large photometric datasets outside a database for redshift estimation, and utilizes the computational capabilities of DB hardware. The code is able to perform both maximum likelihood and Bayesian estimation, and can handle inputs of variable photometric filter sets and corresponding broad-band magnitudes. It is possible to take into account the full co…
As one of the best ground-based photometric dataset, Pan-STARRS1 (PS1) has been widely used as the reference to calibrate other surveys. In this work, we present an independent validation and re-calibration of the PS1 photometry using spectroscopic data from the LAMOST DR7 and photometric data from the corrected Gaia EDR3 with the Stellar Color Regression (SCR) method. Using per band typically a total of 1.5 million LAMOST-PS1-Gaia stars as standards, we show that the PS1 photometric calibration precisions in the $grizy$ filters are around $4\sim 5$ mmag when averaged over $20'$ regions. Howev…
We present optimal survey strategies for the upcoming NIX imager, part of the ERIS instrument to be installed on the Very Large Telescope (VLT). We will use a custom 2.2 micron K-peak filter to optimise the efficiency of a future large-scale direct imaging survey, aiming to detect brown dwarfs and giant planets around nearby stars. We use the results of previous large scale imaging surveys (primarily SPHERE SHINE and Gemini GPIES) to inform our choice of targets, as well as improved planet population distributions. We present four possible approaches to optimise survey target lists for the hig…
The 85-cm telescope at the Xinglong station is a well-operated prime focus system with high science outputs. The telescope has been upgraded since 2014 with new corrector, filters and camera, which are provided by Beijing Normal University (BNU). The filter set is Johnson-Cousins UBVRI system. We report the test results of the new system including the bias, dark current, linearity, gain and readout noise of the CCD camera . Then we derive accurate instrumental calibration coefficients in UBVRI bands with Landolt standard stars in the photometric nights. Finally, we give the limiting magnitudes…
The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning model…
The Southern Photometric Local Universe Survey (S-PLUS) is an ongoing survey of $\sim$9300 deg$^2$ in the southern sky in a 12-band photometric system. This paper presents the second data release (DR2) of S-PLUS, consisting of 514 tiles covering an area of 950 deg$^2$. The data has been fully calibrated using a new photometric calibration technique suitable for the new generation of wide-field multi-filter surveys. This technique consists of a $χ^2$ minimisation to fit synthetic stellar templates to already calibrated data from other surveys, eliminating the need for standard stars and reducin…
We present criteria for separately classifying stars and unresolved background galaxies in photometric catalogs generated with the point spread function (PSF) fitting photometry software DOLPHOT from images taken of Draco II, WLM, and M92 with the Near Infrared Camera (NIRCam) on JWST. Photometric quality metrics from DOLPHOT in one or two filters can recover a pure sample of stars. Conversely, colors formed between short-wavelength (SW) and long-wavelength (LW) filters can be used to effectively identify pure samples of galaxies. Our results highlight that the existing DOLPHOT output paramete…
We study the characteristics of a narrow band type Ia supernova survey through simulations based on the upcoming Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS). This unique survey has the capabilities of obtaining distances, redshifts, and the SN type from a single experiment thereby circumventing the challenges faced by the resource-intensive spectroscopic follow-up observations. We analyse the flux measurements signal-to-noise ratio and bias, the supernova typing performance, the ability to recover light curve parameters given by the SALT2 model, the photometric…
There are several networks of precision quantum sensors in existence, including networks of atomic clocks, magnetometers, and gravitational wave detectors. These networks can be re-purposed for searches of exotic physics, such as direct dark matter searches. Here we explore a detection strategy for macroscopic dark matter objects with such networks using the matched-filter technique. Such "clumpy" dark matter objects would register as transients sweeping through the network at galactic velocities. As a specific example, we consider a network of atomic clocks aboard the Global Positioning Syste…
Large photometric surveys of transient phenomena, such as Pan-STARRS and LSST, will locate thousands to millions of type Ia supernova candidates per year, a rate prohibitive for acquiring spectroscopy to determine each candidate's type and redshift. In response, we have developed an economical approach to identifying SNe Ia and their redshifts using an uncommon type of optical filter which has multiple, discontinuous passbands on a single substrate. Observation of a supernova through a specially designed pair of these `cross-correlation filters' measures the approximate amplitude and phase of …
Measuring the physical properties of galaxies such as redshift frequently requires the use of Spectral Energy Distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space. Here we present a new method to estimate SEDs as a function of color from a small training set of template SEDs. We first cover the mathematical background behind the technique before demonstrating our ability to reconstruct spectra based upon colors and then compare to other common interpolation and extrapolation methods. When the photometric filters and s…
The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. We develop a new photometric redshift estimation workflow TOPz to provide reliable and efficient redshift estimations for the upcoming large-scale survey J-PAS which will observe 8500 deg2 of the northern sky through 54 narrow-band filters. TOPz relies on template-based photo-z estimation with some added J-PAS specific features and possibilities. We present TOPz performance on data from the miniJPAS survey, a precursor to the J-PAS survey with an…
In this white paper, we present the scientific cases for adding narrowband optical filters to the Large Synoptic Survey Telescope (LSST). LSST is currently planning to observe the southern sky in 6 broadband optical filters. Three of the four LSST science themes would benefit from adding narrowband filter observations. We discuss the technical considerations of using narrowband filters with the LSST and lay out the scientific impact that would result on the study of AGB stars, emission line nebula (e.g., supernova remnants and planetary nebulae), photometric redshifts of galaxies, and the dete…
Optical-NIR Multi-band Photometric Analysis and Characterization of Giant Exoplanets with CPI-C
Nanjing Institute of Astronomical Optics \& Technology, Chinese Academy of Sciences, \ 210042, China；CAS Key Laboratory of Astronomical Optics \& Technology, Nanjing Institute of Astronomical Optics \& Technology, \ 210042, China
Relevant information about physical properties of the surface of airless bodies such as porosity, particle size, or roughness can be inferred knowing the dependence of the brightness with illumination and observing geometry. Additionally, this knowledge is necessary to standardize or photometrically correct data acquired under different illumination conditions. In this work we develop a robust, automatic, and efficient photometric modeling methodology which is tested and validated using Bennu images acquired by the camera MapCam from the OSIRIS-REx spacecraft. It consists of a supervised machi…
We present MUFFIT, a new generic code optimized to retrieve the main stellar population parameters of galaxies in photometric multi-filter surveys, and we check its reliability and feasibility with real galaxy data from the ALHAMBRA survey. Making use of an error-weighted $χ^2$-test, we compare the multi-filter fluxes of galaxies with the synthetic photometry of mixtures of two single stellar populations at different redshifts and extinctions, to provide through a Monte Carlo method the most likely range of stellar population parameters (mainly ages and metallicities), extinctions, redshifts, …
Expanding upon the work of Way and Srivastava 2006 we demonstrate how the use of training sets of comparable size continue to make Gaussian process regression (GPR) a competitive approach to that of neural networks and other least-squares fitting methods. This is possible via new large size matrix inversion techniques developed for Gaussian processes (GPs) that do not require that the kernel matrix be sparse. This development, combined with a neural-network kernel function appears to give superior results for this problem. Our best fit results for the Sloan Digital Sky Survey (SDSS) Main Galax…
In this study, we propose a three-stage training approach of neural networks for both photometric redshift estimation of galaxies and detection of out-of-distribution (OOD) objects. Our approach comprises supervised and unsupervised learning, which enables using unlabeled (UL) data for OOD detection in training the networks. Employing the UL data, which is the dataset most similar to the real-world data, ensures a reliable usage of the trained model in practice. We quantitatively assess the model performance of photometric redshift estimation and OOD detection using in-distribution (ID) galaxi…
