اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدThe data reduction pipeline for the Hi-GAL survey
584
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We present the data reduction pipeline for the Hi-GAL survey. Hi-GAL is a key project of the Herschel satellite which is mapping the inner part of the Galactic plane (|l| <= 70cdot and |b| <= 1cdot), using 2 PACS and 3 SPIRE frequency bands, from 70{mu}m to 500{mu}m. Our pipeline relies only partially on the Herschel Interactive Standard Environment (HIPE) and features several newly developed routines to perform data reduction, including accurate data culling, noise estimation and minimum variance map-making, the latter performed with the ROMAGAL algorithm, a deep modification of the ROMA code already tested on cosmological surveys. We discuss in depth the properties of the Hi-GAL Science Demonstration Phase (SDP) data.
قيم البحث
اقرأ أيضاً
We present the data reduction procedures being used by the GALAH survey, carried out with the HERMES fibre-fed, multi-object spectrograph on the 3.9~m Anglo-Australian Telescope. GALAH is a unique survey, targeting 1 million stars brighter than magni
tude V=14 at a resolution of 28,000 with a goal to measure the abundances of 29 elements. Such a large number of high resolution spectra necessitates the development of a reduction pipeline optimized for speed, accuracy, and consistency. We outline the design and structure of the Iraf-based reduction pipeline that we developed, specifically for GALAH, to produce fully calibrated spectra aimed for subsequent stellar atmospheric parameter estimation. The pipeline takes advantage of existing Iraf routines and other readily available software so as to be simple to maintain, testable and reliable. A radial velocity and stellar atmospheric parameter estimator code is also presented, which is used for further data analysis and yields a useful verification of the reduction quality. We have used this estimator to quantify the data quality of GALAH for fibre cross-talk level ($lesssim0.5$%) and scattered light ($sim5$ counts in a typical 20 minutes exposure), resolution across the field, sky spectrum properties, wavelength solution reliability (better than $1$ $mathrm{km s^{-1}}$ accuracy) and radial velocity precision.
Since autumn 2008 a new L-band 7-Feed-Array receiver is used for an HI 21-cm line survey performed with the 100-m Effelsberg telescope. The survey will cover the whole northern hemisphere comprising both, the galactic and extragalactic sky in paralle
l. Using state-of-the-art FPGA based digital Fast Fourier Transform spectrometers, superior in dynamic range and temporal resolution, allows to apply sophisticated radio frequency interferences (RFI) mitigation schemes to the survey data. The EBHIS data reduction software includes the RFI mitigation, gain-curve correction, intensity calibration, stray-radiation correction, gridding, and source detection. We discuss the severe degradation of radio astronomical HI data by RFI signals and the gain in scientific yield when applying modern RFI mitigation schemes. For this aim simulations of the galaxy distribution within the local volume (z<0.07) with and without RFI degradation were performed. These simulations, allow us to investigate potential biases and selection effects introduced by the data reduction software and the applied source parametrization methods.
The Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey III, explores the stellar populations of the Milky Way using the Sloan 2.5-m telescope linked to a high resolution (R~22,500), near-infrared (1.
51-1.70 microns) spectrograph with 300 optical fibers. For over 150,000 predominantly red giant branch stars that APOGEE targeted across the Galactic bulge, disks and halo, the collected high S/N (>100 per half-resolution element) spectra provide accurate (~0.1 km/s) radial velocities, stellar atmospheric parameters, and precise (~0.1 dex) chemical abundances for about 15 chemical species. Here we describe the basic APOGEE data reduction software that reduces multiple 3D raw data cubes into calibrated, well-sampled, combined 1D spectra, as implemented for the SDSS-III/APOGEE data releases (DR10, DR11 and DR12). The processing of the near-IR spectral data of APOGEE presents some challenges for reduction, including automated sky subtraction and telluric correction over a 3 degree diameter field and the combination of spectrally dithered spectra. We also discuss areas for future improvement.
Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is an optical fiber-bundle integral-field unit (IFU) spectroscopic survey that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). With a spectral cove
rage of 3622 - 10,354 Angstroms and an average footprint of ~ 500 arcsec^2 per IFU the scientific data products derived from MaNGA will permit exploration of the internal structure of a statistically large sample of 10,000 low redshift galaxies in unprecedented detail. Comprising 174 individually pluggable science and calibration IFUs with a near-constant data stream, MaNGA is expected to obtain ~ 100 million raw-frame spectra and ~ 10 million reduced galaxy spectra over the six-year lifetime of the survey. In this contribution, we describe the MaNGA Data Reduction Pipeline (DRP) algorithms and centralized metadata framework that produces sky-subtracted, spectrophotometrically calibrated spectra and rectified 3-D data cubes that combine individual dithered observations. For the 1390 galaxy data cubes released in Summer 2016 as part of SDSS-IV Data Release 13 (DR13), we demonstrate that the MaNGA data have nearly Poisson-limited sky subtraction shortward of ~ 8500 Angstroms and reach a typical 10-sigma limiting continuum surface brightness mu = 23.5 AB/arcsec^2 in a five arcsec diameter aperture in the g band. The wavelength calibration of the MaNGA data is accurate to 5 km/s rms, with a median spatial resolution of 2.54 arcsec FWHM (1.8 kpc at the median redshift of 0.037) and a median spectral resolution of sigma = 72 km/s.
The SOXS is a dual-arm spectrograph (UV-VIS & NIR) and AC due to mounted on the ESO 3.6m NTT in La Silla. Designed to simultaneously cover the optical and NIR wavelength range from 350-2050 nm, the instrument will be dedicated to the study of transie
nt and variable events with many Target of Opportunity requests expected. The goal of the SOXS Data Reduction pipeline is to use calibration data to remove all instrument signatures from the SOXS scientific data frames for each of the supported instrument modes, convert this data into physical units and deliver them with their associated error bars to the ESO SAF as Phase 3 compliant science data products, all within 30 minutes. The primary reduced product will be a detrended, wavelength and flux calibrated, telluric corrected 1D spectrum with UV-VIS + NIR arms stitched together. The pipeline will also generate QC metrics to monitor telescope, instrument and detector health. The pipeline is written in Python 3 and has been built with an agile development philosophy that includes adaptive planning and evolutionary development. The pipeline is to be used by the SOXS consortium and the general user community that may want to perform tailored processing of SOXS data. Test driven development has been used throughout the build using `extreme mock data. We aim for the pipeline to be easy to install and extensively and clearly documented.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
