اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدInternal calibration of Gaia BP/RP low-resolution spectra
82
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The full third Gaia data release will provide the calibrated spectra obtained with the blue and red Gaia slit-less spectrophotometers. The main challenge when facing Gaia spectral calibration is that no lamp spectra or flat fields are available during the mission. Also, the significant size of the line spread function with respect to the dispersion of the prisms produces alien photons contaminating neighbouring positions of the spectra. This makes the calibration special and different from standard approaches. This work gives a detailed description of the internal calibration model to obtain the spectrophotometric data in the Gaia catalogue. The main purpose of the internal calibration is to bring all the epoch spectra onto a common flux and pixel (pseudo-wavelength) scale, taking into account variations over the focal plane and with time, producing a mean spectrum from all the observations of the same source. In order to describe all observations in a common mean flux and pseudo-wavelength scale, we construct a suitable representation of the internally calibrated mean spectra via basis functions and we describe the transformation between non calibrated epoch spectra and calibrated mean spectra via a discrete convolution, parametrising the convolution kernel to recover the relevant coefficients. The model proposed here is able to combine all observations into a mean instrument to allow the comparison of different sources and observations obtained with different instrumental conditions along the mission and the generation of mean spectra from a number of observations of the same source. The output of this model provides the internal mean spectra, not as a sampled function (flux and wavelength), but as a linear combination of basis functions, although sampled spectra can easily be derived from them.
قيم البحث
اقرأ أيضاً
We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R $sim100$) data. The goal of SNIascore is fully automated classification of SNe Ia with a very low
false-positive rate (FPR) so that human intervention can be greatly reduced in large-scale SN classification efforts, such as that undertaken by the public Zwicky Transient Facility (ZTF) Bright Transient Survey (BTS). We utilize a recurrent neural network (RNN) architecture with a combination of bidirectional long short-term memory and gated recurrent unit layers. SNIascore achieves a $<0.6%$ FPR while classifying up to $90%$ of the low-resolution SN Ia spectra obtained by the BTS. SNIascore simultaneously performs binary classification and predicts the redshifts of secure SNe Ia via regression (with a typical uncertainty of $<0.005$ in the range from $z = 0.01$ to $z = 0.12$). For the magnitude-limited ZTF BTS survey ($approx70%$ SNe Ia), deploying SNIascore reduces the amount of spectra in need of human classification or confirmation by $approx60%$. Furthermore, SNIascore allows SN Ia classifications to be automatically announced in real-time to the public immediately following a finished observation during the night.
While the near-infrared wavelength regime is becoming more and more important for astrophysics there is a marked lack of spectrophotometric standard star data that would allow the flux calibration of such data. Furthermore, flux calibrating medium- t
o high-resolution echelle spectroscopy data is challenging even in the optical wavelength range, because the available flux standard data are often too coarsely sampled. We will provide standard star reference data that allow users to derive response curves from 300nm to 2500nm for spectroscopic data of medium to high resolution, including those taken with echelle spectrographs. In addition we describe a method to correct for moderate telluric absorption without the need of observing telluric standard stars. As reference data for the flux standard stars we use theoretical spectra derived from stellar model atmospheres. We verify that they provide an appropriate description of the observed standard star spectra by checking for residuals in line cores and line overlap regions in the ratios of observed (X-shooter) spectra to model spectra. The finally selected model spectra are then corrected for remaining mismatches and photometrically calibrated using independent observations. The correction of telluric absorption is performed with the help of telluric model spectra.We provide new, finely sampled reference spectra without telluric absorption for six southern flux standard stars that allow the users to flux calibrate their data from 300 nm to 2500 nm, and a method to correct for telluric absorption using atmospheric models.
Although a catalogue of synthetic RGB magnitudes, providing photometric data for a sample of 1346 bright stars, has been recently published, its usefulness is still limited due to the small number of reference stars available, considering that they a
re distributed throughout the whole celestial sphere, and the fact that they are restricted to Johnson V < 6.6 mag. This work presents synthetic RGB magnitudes for ~15 million stars brighter than Gaia G = 18 mag, making use of a calibration between the RGB magnitudes of the reference bright star sample and the corresponding high quality photometric G, G_BP and G_RP magnitudes provided by the Gaia EDR3. The calibration has been restricted to stars exhibiting -0.5 < G_BP - G_RP < 2.0 mag, and aims to predict RGB magnitudes within an error interval of $pm 0.1$ mag. Since the reference bright star sample is dominated by nearby stars with slightly undersolar metallicity, systematic variations in the predictions are expected, as modelled with the help of stellar atmosphere models. These deviations are constrained to the $pm 0.1$ mag interval when applying the calibration only to stars scarcely affected by interstellar extinction and with metallicity compatible with the median value for the bright star sample. The large number of Gaia sources available in each region of the sky should guarantee high-quality RGB photometric calibrations.
Given that low-mass stars have intrinsically low luminosities at optical wavelengths and a propensity for stellar activity, it is advantageous for radial velocity (RV) surveys of these objects to use near-infrared (NIR) wavelengths. In this work we d
escribe and test a novel RV extraction pipeline dedicated to retrieving RVs from low mass stars using NIR spectra taken by the CSHELL spectrograph at the NASA Infrared Telescope Facility, where a methane isotopologue gas cell is used for wavelength calibration. The pipeline minimizes the residuals between the observations and a spectral model composed of templates for the target star, the gas cell, and atmospheric telluric absorption; models of the line spread function, continuum curvature, and sinusoidal fringing; and a parameterization of the wavelength solution. The stellar template is derived iteratively from the science observations themselves without a need for separate observations dedicated to retrieving it. Despite limitations from CSHELLs narrow wavelength range and instrumental systematics, we are able to (1) obtain an RV precision of 35 m/s for the RV standard star GJ 15 A over a time baseline of 817 days, reaching the photon noise limit for our attained SNR, (2) achieve ~3 m/s RV precision for the M giant SV Peg over a baseline of several days and confirm its long-term RV trend due to stellar pulsations, as well as obtain nightly noise floors of ~2 - 6 m/s, and (3) show that our data are consistent with the known masses, periods, and orbital eccentricities of the two most massive planets orbiting GJ 876. Future applications of our pipeline to RV surveys using the next generation of NIR spectrographs, such as iSHELL, will enable the potential detection of Super-Earths and Mini-Neptunes in the habitable zones of M dwarfs.
The Mid-Infrared Instrument (MIRI) Medium Resolution Spectrometer (MRS) is the only mid-IR Integral Field Spectrometer on board James Webb Space Telescope. The complexity of the MRS requires a very specialized pipeline, with some specific steps not p
resent in other pipelines of JWST instruments, such as fringe corrections and wavelength offsets, with different algorithms for point source or extended source data. The MRS pipeline has also two different variants: the baseline pipeline, optimized for most foreseen science cases, and the optimal pipeline, where extra steps will be needed for specific science cases. This paper provides a comprehensive description of the MRS Calibration Pipeline from uncalibrated slope images to final scientific products, with brief descriptions of its algorithms, input and output data, and the accessory data and calibration data products necessary to run the pipeline.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
