Technical Reports

Observational examples of spectral line calibration at the 30m telescope with MRTCAL and MIRA
Authors: C. Marka (IRAM Granada), J. Pety (IRAM Grenoble, Observatoire de Paris), S. Bardeau (IRAM Grenoble), A. Sievers (IRAM Granada)
Keywords: MRTCAL, MIRA, 30m calibration
Related Documents: MRTCAL documentation, MIRA documentation, CLASS documentation.
Abstract:Since February 2017, MRTCAL has replaced MIRA as the software for spectral line data calibration (except polarimetry and continuum) at the 30m-Telescope. Slight changes in the calibrated spectra are expected, for example in form of an improved calibration accuracy at the edges of the atmospheric windows as result of the narrower calibration bandwidth used by MRTCAL (20MHz by default, compared to up to about 1.35 GHz for MIRA). This report demonstrates the practical performances of MRTCAL by a systematic comparison of observations calibrated with both softwares.
Download: [ PDF file ] .

Gridding spectra with CLASS
Authors: S. Bardeau (IRAM Grenoble) and J. Pety (IRAM Grenoble, LERMA, Observatoire de Paris)
Keywords: Gridding, transposition, memory, large files
Related Documents: CLASS documentation
Abstract: In the sep16a CLASS release, the internal code of the XY MAP command was refurbished to ensure that datasets larger than the available RAM memory can be processed by slicing the data in intervals of channels. The command is now also able to read direct or transposed input XY tables and/or to write direct (LMV) or transposed (VLM) output cubes. The latter feature is useful to easily reimport data when a 2nd step of baselining is desired on the gridded data cube. The online help was upgradeed accordingly (see in particular the output of LAS> HELP XY MAP MEMORY). This memo describes how the gridding is performed in CLASS, from the collection of spectra to the spectral cube. It focuses on the file access effciency, memory consumption, and how the user choices can impact them.
Download: [ PDF file ] .

MAPPING for NOEMA: Concepts and Usage
Authors: S. Guilloteau (LAB Bordeaux)
Keywords: Imaging, data processing
Related Documents: MAPPING documentation
Abstract:With the advent of ALMA and NOEMA, the interferometers deliver much larger data sets than initially anticipated for GILDAS software. This document describes new facilities in MAPPING to handle 1) Mosaics and 2) Wide bandwidth data sets, and a proposed new (simpler) way of using MAPPING.
Download: [ PDF file ] .

Introducing Associated Arrays in CLASS
Authors: S. Bardeau (IRAM Grenoble), J. Pety (IRAM Grenoble and Observatoire de Paris)
Keywords: CLASS Data Format
Related Documents: CLASS documentation, Importing Herschel-FITS into CLASS
Abstract: The concept of Associated Arrays is being added in the CLASS data format. It is an additional section that will store a set of data arrays whose spectral axis matches the brightness spectral axis, i.e., one-to-one channel correspondence. At start, this will be used in two contexts. For Herschel/HIFI, it will store a logical array of blanked channels and a logical array to define the channels where the lines appear (see IRAM Memo 2015-3). At some point, it will be used at the IRAM-30m to store the results of the calibration scans, i.e., the sky counts in the <b>RY</b> array and the hot/cold counts, and the receiver, system, and calibration temperatures in a set of Associated Arrays. This document introduces the detailed specifications of the concept of an Associated Array, its implementation/integration in CLASS, and it gives an example of use, namely how to baseline a spectra using a LINE associated array to define the baseline windows. The specifications of the Associated Arrays is foreseen to evolve following feedback from its use at IRAM and elsewhere. Download: [ PDF file ] .

Importing Herschel-FITS into CLASS
Authors: S. Bardeau (IRAM Grenoble), D.Teyssier (ESAC Madrid), D.Rabois (IRAP Toulouse), J. Pety (IRAM Grenoble and Observatoire de Paris)
Keywords: CLASS Data Format
Related Documents: CLASS documentation, CLASS Associated Arrays
Abstract: Herschel/HIFI data were already readable by CLASS after conversion into specific FITS file by the HiClass task from HIPE. These FITS files are however not the ones served by the Herschel Science Archive as result of the standard data processing. The CLASS community thus requested the possibility to fill Herschel/HIFI archive science products directly into CLASS.
In a nutshell, the new filler automatically recognizes the Herschel/HIFI FITS level 2.0 and 2.5. The standard CLASS sections (General, Position, Spectroscopy, Calibration) are filled from the FITS header parameters. A dedicated Herschel section is added to the CLASS Data Format in order to attach HIFI specific metadata. The data are filled as one or several CLASS spectra depending of the FITS level and/or context (On-The-Fly, spectral survey, etc). The associated FLAG and LINE arrays are filled as associated arrays (new CLASS feature documented in a separate memo) to each spectrum data. This memo describes all these points in details. Download: [ PDF file ] .

NOEMA sensitivity estimator
Authors: J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris), J. Bossier (IRAM Grenoble), E. Reynier (IRAM Grenoble)
Keywords: NOEMA, IRAM instruments, time estimator, GILDAS/ASTRO
Related Documents: Version 1.1 (2015), Version 2.0 (2017), Version 2.1 (2018), Version 2.2 (2018), Version 3.0 (2019), Version 3.1 (2019) Version 3.2 (Jan. 2020)
Abstract: This memo describes the equations used in the NOEMA sensitivity estimator available in the GILDAS/ASTRO program.
Version 3.3  (19^th February 2020) Download: [ PDF file ].

Extended support of sky spherical coordinates in CLASS
Authors: S. Bardeau (IRAM Grenoble), J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris)
Keywords: coordinates, (re)projection, CLASS Data Format
Related Documents: CLASS documentation, CLASSIC Data Container
Abstract: Up to now, CLASS only supported natively the radio projection of the sky spherical coordinates. The main limitation of the radio projection is the absence of support of a projection angle. This could imply some approximation in the handling of On-The-Fly data with rotated scanning directions. CLASS now supports all the projections already supported in the GILDAS kernel, i.e., none (unprojected spherical coordinates), gnomonic, orthographic, azimuthal, stereographic, lambert, aito, radio, and sfl. This required the introduction of the MODIFY PROJECTION command, the modification of the MODIFY POSITION command, and the modication of the position header section in the CLASS Data Format. This memo describes all this in detail. Download: [ PDF file] .

CLASS Data Fillers
Authors: S. Bardeau (IRAM Grenoble), J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris)
Keywords: Data Format, CLASS
Related Documents: Version 1.0 , superseded by Version 1.2 from 02-Dec-2016
Abstract: CLASS is the program of the GILDAS suite dedicated to the data reduction and analysis of heterodyne instruments at cm and (sub-)mm single-dish telescopes. It is used by the IRAM-30m, APEX, SOFIA/GREAT, Herschel/HIFI, YEBES, Effelsberg. Because of tremendous improvement of the heterodyne spectrometer, the CLASS data format is evolving again after years of stability. To help non-IRAM telescope to cope with these changes, the CLASS team is now providing fillers to the Class Data Format writers. Three different possibilities are given: 1) A procedure using the SIC intepreter; 2) A Fortran program linked to the CLASS library; And 3) a Python script using a dedicated Python module. This document describes how those 3 APIs can be used and examples are provided in the appendices. Download: [ PDF file ].

CLASSIC Application Programming Interface
Authors: S. Bardeau (IRAM Grenoble) , V. Pietu (IRAM Grenoble), J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris)
Keywords: Data Format, CLASS, CLIC
Related Documents: The CLASSIC Data Container, IRAM memo 2013-2
Abstract: We describe in details the Application Programming Interface of the CLASSIC Library, provided by GILDAS.
Download: [ PDF file ].

CLASSIC Data Container
Authors: S. Bardeau (IRAM Grenoble) , V. Pietu (IRAM Grenoble), J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris)
Keywords: Data Format, CLASS, CLIC
Related Documents: The CLASSIC Library, IRAM memo 2013-3
Abstract: The CLASS/CLIC Data Format are digital formats used to describe single-dish/interferometric radio-astronomy data. They can be described in two layers: 1) a CLASSIC Data Container, which is generic enough to store many kinds of data, typically several observations which gather observational parameters with actual data, and 2) the CLASS/CLIC Data Format itself, which make a particular use of the CLASSIC Data Container. The size of the datasets produced by the IRAM instruments experience a tremendous increase (because of multi-beam receivers, wide bandwidth receivers, spectrometers with thousands of channels, and/or new observing mode like the interferometric on-the-fly). This implied that the CLASS/CLIC Data Format were reaching common limits in the size of data which could be stored. To solve these issues, the CLASSIC Data Container standard was revised. This documents aims to describe the new standard. A companion document describes the GILDAS library which implements this standard and which is now used by CLASS and CLIC.
Download: [ PDF file ].

Improvement of the IRAM 30m telescope beam pattern
Authors: Carsten Kramer (IRAM Granada), Juan Penalver (IRAM Granada), and Albert Greve (IRAM Grenoble)
Keywords: IRAM 30-M, beam pattern, reflector surface
Related Documents: Numerous revious publications on the subject, see reference section in the report.
Abstract: The beam pattern of the IRAM 30m telescope has been derived from differential total power scans across the limb of the Moon. The 30m beam is described by the main beam and three error beams which are given by residual large-scale deformations of the primary mirror, and its frames and panels. Total power scans across the Moon taken shortly after Full Moon at 86, 145, 210, 280 and 340 GHz in February 2010 under best late-night conditions and at optimum elevation were used to derive the beam pattern of the 30m telescope to a level of less than -30 dB and to a full width of up to 2000 arcsec. The analysis shows the improvement of the IRAM 30m telescope reflector from panel frame adjustments and application of ventilation and temperature control in the telescope yoke and counterweight done between 1998 and 2002. At the present low level of the error beam, transient thermal panel buckling becomes an observational effect. The paper gives an updated table of the error beam parameters and telescope efficiencies which are valid since September 2002. Recipes are given to derive the beam parameters at other frequencies. We also briefly discuss the possible degradation of the beam when observing under non-optimum conditions.
Download: [ PDF file ].

Description of the spectral axis handling in CLASS
Version 1.2, July 6th, 2019
Authors: J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris) , S. Bardeau (IRAM Grenoble)
Keywords: CLASS, spectral information in observations
Related Documents: Version 1.1 (October 10th, 2014), Version 1.0 (October 20th, 2011)
Abstract: An observer is interested by the physical properties (line frequencies, velocity of the gas) of a source in its own reference frame. However, the observations happen in a different frame, namely the topocentric frame for ground-based observations. This implies a change of frame to infer the physical properties in the source frame from the measured frequencies in the measurement frame. This memo tries to explain the different interpretation of the spectral axis, the additional subtleties related to heterodyne receivers in radio-astronomy, the current description of the spectral axis handling in CLASS, and the impact of various short-comings that happen for historical reasons.
Download: [ PDF file ].

CLASS User Section
Authors: S. Bardeau (IRAM Grenoble) , J. Pety (IRAM Grenoble; LERMA, Observatoire de Paris) , S. Guilloteau (LAB, Observatoire de Bordeaux)
Keywords: CLASS, data headers, user-defined information
Related Documents: GILDAS software documentation
Abstract: CLASS is a state-of-the-art GILDAS software for reduction and analysis of (sub)–millimeter spectroscopic data. Up to now, the CLASS data format could only describe a predetermined number of parameters in the observation headers, these parameters being grouped in 17 sections (e.g. the general, spectroscopic or calibration sections). However, the possibility to add telescope-specific information to the CLASS data format was requested several time. Instead of introducing a per-telescope specific and fixed section, we thus decided to introduce a new flexible section, named User Section. This document describes the functionalities available to the end-users as well as the implementation steps which must be developed by the section owner.
Download: [ PDF file ].

WIFISYN: The GILDAS implementation of a new wide-field synthesis algorithm
Authors: J. Pety (IRAM Grenoble and Observatoire de Paris), N. Rodriguez-Fernandez (IRAM Grenoble)
Keywords: Wide-field synthesis, mosaics, interferometric imaging
Related Documents: GILDAS software documentation
Abstract: The usual way to image wide-field interferometric observations is known as mosaicking. Different variants of mosaicking exist (e.g. Cornwell, 1988; Sault et al., 1996), including an interesting recent implementation of mosaicking in the uv plane (Golap et al., priv. comm.). Pety & Rodriguez-Fernandez (2010) revisited the theory of wide-field imaging to propose a different algorithm to image interferometric wide-field observations, based on the well-known Ekers & Rots’ scheme. This algorithm is named wide-field synthesis because it explicitely synthesizes the wide-field spatial frequencies throughout the uv plane. This memo describes the current state of the implementation of this algorithm in a new package, named WIFISYN, of the GILDAS software suite.
Download: [ PDF file ].

Preparing GILDAS for large datasets. I - GREG 2011
Authors: S. Bardeau (IRAM Grenoble), E. Reynier (IRAM Grenoble), J. Pety (IRAM Grenoble and Observatoire de Paris)
Keywords: multi-threading, multi-windowing, the GIMP ToolKit (GTK+), Portable Network Graphics (PNG)
Related Documents: GreG documentation, Programming in GILDAS
Abstract: The size of the datasets produced by the IRAM instruments experience a tremendeous increase (because of multi-beam receivers, wide bandwidth receivers, spectrometers with thousands of channels, and/or new observing mode like the interferometric on-the-fly). Visualizing these datasets in a fluent way is a challenge, which requires the best use of the available hardware and operating systems (multi-cores processors and multi-window environments). This prompted a large rewriting of the part of the GILDAS kernel (known as GTV) in charge of the interface between the plotting facilities and the system. The main guidelines of this rewriting were 1) the backward compatibility when possible, 2) the use of modern standards as the multi-threading or the GTK+ toolkit, 3) the factorization of the source code for different OS (Linux, Mac OSX and MS Windows), 4) the implementation of new facilities like a PNG output or an interactive lens. This document thoroughly describes the improvements for the end-users and the programmers.
Download: [ PDF file ] (Version 1.3, 06-Apr-2011).

Polarimetry with EMIR / XPOL
Authors: H. Wiesemeyer (IRAM Granada, on sabbatical leave at MPIfR) and C. Thum (IRAM Grenoble)
Keywords: IRAM 30-m, heterodyne, polarimetry, EMIR, XPOL
Abstract: Following the installation of the new EMIR receiver in spring 2009, the XPOL observing mode needed to be adapted and the consequences for polarization observations to be investigated. Here we report on test measurements made at 90 and 230 GHz. XPOL now works at these EMIR bands with lower on–axis instrumental polarization than before. Sidelobe levels are however not significantly reduced, with the consequence that observations of extended sources still demand special care. Commissioning of XPOL in the E150 and E330 bands remains to be done.
Download: [ PDF file ].

IRAM-30m MAMBO time / sensitivity estimator
Authors: J. Pety (IRAM Grenoble and Observatoire de Paris), G. Quintana-Lacaci (IRAM Granada), R. Zylka (IRAM Grenoble), S. Bardeau (IRAM Grenoble), E. Reynier (IRAM Grenoble)
Keywords: IRAM 30-m, bolometer, MAMBO
Related Documents: IRAM Call for Proposals
Abstract: This memo describes the equations used in the IRAM-30m MAMBO time/sensitivity estimator available in the GILDAS / ASTRO program.
Download: [ PDF file ].

IRAM-30m HERA time/sensitivity estimator
Authors: J. Pety (IRAM and Observatoire de Paris), M. Gonzalez (IRAM Granada), S. Bardeau (IRAM) and E. Reynier (IRAM)
Keywords: IRAM-30m, Multibeam, HERA
Related Documents: IRAM Call for Proposals
Abstract: This memo describes the equations used in the IRAM-30m HERA time/sensitivity estimator available on the IRAM-30m web page. A large part of the memo aims at describing the peculiarities of time/sensitivity estimation of the On-The-Fly observing mode with a multi-pixel like HERA. It explains how to generalize the equations of the single pixel case, so that the same code can be used in both cases (single and multi-pixel).
Download: [ PDF file ].

Read-write optimization in CLASS
Authors: S. Bardeau (IRAM), J. Pety (IRAM and Observatoire de Paris) and S. Guilloteau (LAB Observatoire de Bordeaux)
Keywords: On-The-Fly, CLASS file format, data rate, user and system times
Related Documents:IRAM memo 2005-1: Improved OTF support
Abstract: CLASS is a GILDAS software for reduction and analysis of (sub){millimeter spectroscopic data. It is daily used to reduce spectra acquired with the IRAM 30m telescope. CLASS is currently used in many other facilities (e.g. CSO, HHT, Effelsberg) and it is considered for use by Herschel/HIFI. CLASS history started in 1983. As a consequence, it was written in FORTRAN 77 and tailored to reduce pointed observations.
When CLASS was re-written in Fortran 90, it was decided to split On-The-Fly spectra into one observation each (see IRAM memo 2005-1). This eases spectra handling from the user side, but, of course, multiplies the number of observations in a single file (typically by a factor ~1000). The increasing number of observations (especially with the OTF acquisition schemes) and number of channels of the back-ends produces larger and larger files. CLASS has thus been revised with new file types and optimized with a faster algorithm in order to ensure a maximal data rate from the software side. We will expose here this new algorithm, and show that the major limitation for writing CLASS large files is currently on the hardware side.
Download: [ PDF file ].

Comparison of ATM versions: Impact on the calibration of IRAM instruments
Authors: J. Pety (IRAM and Observatoire de Paris), S. Bardeau (IRAM) and E. Reynier (IRAM)
Keywords: ATM, atmospherical model, radiative transport
Related Documents: J. Cernicharo, IRAM report ATM 1995
Abstract: Since its first introduction into GILDAS in 1985, the ATM modelling program completely changed. With the advent of large bandwidth receivers and submillimeter receivers, it is time to upgrade the version of ATM used in GILDAS to calibrate IRAM instruments. This memo tries to assess the impact of changing the atmospheric model on the calibration of IRAM instruments. After a short description 1) of the single-dish calibration, 2) of ATM 2009 and 3) the GILDAS interface to ATM 1985 and ATM 2009, an in-depth comparison of the results obtained with ATM 1985 and ATM 2009 is described. From this study, we expect slight variations of the calibration results when swapping from ATM 1985 to ATM 2009.
Download: [ PDF file ].

IRAM-30m EMIR time/sensitivity estimator
Author: J.Pety (IRAM Grenoble and Observatoire de Paris)
Keywords: IRAM 30-m - EMIR - proposal preparation - time estimator
Abstract: This memo describes the equations used in the IRAM-30m EMIR time/sensitivity estimator available in the GILDAS/ASTRO program. A large part of the memo aims at deriving sensitivity estimate for the case of On-The-Fly observations, which is not clearly documented elsewhere (to our knowledge). Numerical values of the different parameters used in the time/sensitivity estimator are grouped in appendix A.
Download: [ PDF file ]. 04-Feb-2009: Version 1.0

Download: [ PDF file ]. 18-Feb-2010: Simplified Version 1.1