icon Instrument Features


MEGARA (Multi-Espectrógrafo en GTC de Alta Resolución para Astronomía) is an optical integral-field Unit (IFU) and multi-object spectrograph (MOS) designed for the GTC. The MEGARA IFU mode will offer a fibre bundle covering 12.5 arcsec x 11.3 arcsec with a spaxel size of 0.62 arcsec, which makes use of 100 μm-core optical fibres. The MEGARA MOS will allow observing up to 100 objects in a region of 3.5 arcmin x 3.5 arcmin around the IFU bundle. Eight of these bundles will be devoted to the determination of the sky during the observation with the IFU, so only 92 of these positioners will be available for MOS observations. Both the IFU and MOS capabilities of MEGARA will provide intermediate-to-high spectral resolutions (R~5,500, 12,000 and 20,000 respectively for the LR, MR and HR modes).


A infographic view of the PseudoSlit, Collimator, dispersion elements (VPHs) on the wheel and the set Cryostat+Camera.


MEGARA focal plane component attached to the Folded-Cass F focal station of GTC (left) and MEGARA spectrograph at the Nasmyth-A focal station (right).

icon Observing modes


MEGARA has two different bundles of fibres distribution: the Large Compact Bundle IFU and the Multi-Object Spectrograph (MOS) mode.

With MEGARA, spatially spread individual targets could be observed in MOS mode, as well as compact or extended targets with fibre-limited spatial resolution in the centre of the instrument (IFU mode).

In the table below we provide a summary of the main characteristics of the two MEGARA modes (IFU and MOS) and the corresponding spectral resolutions yield for each set of VPHs. Also, the current VPHs available in MEGARA can be found here.

Field of View 12.5 x 11.3 arcsec2 3.5 x 3.5 arcmin2
Spaxel size 0.62 arcsec
Sampling (1D FWHM) 3.6 pix
LR VPHs R(λ/Δλ) ~ 5 500
MR VPHs R(λ/Δλ) ~ 12 000
HR VPHs R(λ/Δλ) ~ 20 000

icon Volume Phase Holographic


Figure below shows the distribution of the VPHs in the resolving power versus wavelength coverage plane for all MEGARA VPHs in the case of the 100 μm-core fibres (LCB IFU and MOS modes) when theoretically projected at designing stage (in different colours) and black/grey after empirical estimates at lab. Average resolutions at midpoint of range are above expectations.


Coverage of the MEGARA VPHs in resolving power (RFWHM) and wavelength for the LCB IFU mode (for MOS mode is very similar) (100 μm-core fibres).

The scientific empirical performance (from commissioning measures) of the complete MEGARA gratings is given in the following table:

VPH ID Setup RFWHM λ12 λC Δλ(@λC) lin res
(Å) (Å) (Å) (Å/pix)
VPH405-LR LR-U 5750 3654.32-4391.88 4025.90 0.700 0.176
VPH480-LR LR-B 5000 4332.05-5199.96 4785.32 0.957 0.207
VPH570-LR LR-V 5850 5143.74-6168.19 5687.63 0.971 0.244
VPH675-LR LR-R 5900 6096.54-7303.21 6729.61 1.141 0.287
VPH799-LR LR-I 5750 7224.11-8640.37 7976.31 1.387 0.337
VPH890-LR LR-Z 5800 8042.74-9634.92 8873.16 1.530 0.379
VPH410-MR MR-U 13100 3919.81-4282.17 4102.87 0.313 0.086
VPH443-MR MR-UB 13050 4226.38-4625.79 4429.44 0.339 0.095
VPH481-MR MR-B 13200 4585.66-5025.07 4809.46 0.364 0.105
VPH521-MR MR-G 12000 4963.22-5445.00 5208.79 0.434 0.115
VPH567-MR MR-V 12600 5413.11-5923.90 5664.96 0.450 0.122
VPH617-MR MR-VR 12100 5894.23-6448.26 6165.79 0.510 0.132
VPH656-MR MR-R 12150 6243.10-6865.26 6560.33 0.540 0.148
VPH712-MR MR-RI 12200 6764.58-7440.85 7109.81 0.583 0.161
VPH777-MR MR-I 8600 7386.53-8127.95 7766.14 0.903 0.177
VPH926-MR MR-Z 11600 8810.52-9698.97 9274.84 0.800 0.212
VPH665-HR HR-R 20050 6405.61-6797.14 6602.59 0.329 0.093
VPH863-HR HR-I 20500 8380.20-8882.38 8626.01 0.421 0.120

icon Efficiency


Based on designs parameters and some features estimates at the lab, compared expected efficiency of MEGARA lead us to think that it is a very insteresting instrument for resolving lines even in faint targets case.

Compared efficiency

MEGARA detection efficiency for the different sets of VPHs.

Also, the following plots show the exposure times needed to achive S/N=5 per Angstrom as a function of the magnitude of the target (continuum level) for the most demanded MEGARA VPHs, based on MEGARA ETC predictions. These estimates correspond to the flux integrated in C+R1 fibers, that is 7 spaxels, for a 0.9" seeing in dark/photometric conditions for a point source of uniform spectrum (R mag used).

Individual efficiency

Exposure times needed to achieve S/N=5 with the most demanded MEGARA VPHs as a function of the magnitude of the targets. Dashed yellow line corresponds to 1 hour of integration on source.

Plots for all the VPHs available in MEGARA can be retrieved in the next Table:


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icon Details about CCD


The MEGARA spectrograph is equipped with a 4k x 4k CCD. Given the wide wavelength coverage of the instrument the detector chosen will be a deep-depleted E2V CCD231-84 (see left panel above). This detector provides very low fringing and relatively good efficiency in the blue end of the optical window, specially when combined with the astro-2 coating provided by E2V. The main characteristics of the MEGARA CCD are summarized in the table below.

CCD provider E2V
CCD model CCD 231-84 (Deep Depleted)
Coating astro-2
Number of pixels 4k x 4k (15 micron per pixel)
N of amplifiers 2 used (of 4 available) in operation mode
Readout time ~ 50s
Readout noise 3.4 electrons
Efficiency 90% (between 400-800nm)

No binning will be offered so operations would only produce frames 1x1. Bias level is quite stable around 2 thousend ADU. There is a little difference (less than 50 ADU) between channels.

As it is a Deep-Depletion (DD) CCD this detector would be more sensible to cosmic rays (CRs) than those with non-depletion characteristics (i.e. OSIRIS' CCD). But after some studies in lab we found that even among DD devices, the MEGARA's CCD shows a greater sensitivity to CR events than others. It will be studied in depth after normal operation would start. Nevertheless it is strongly recomended to split every exposure into, at least, 3 different exposures no longer than 20 minutes (i.e. 1200s) to minimize the impact of CRs in observations.

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icon IFU Overview


The IFU, also called as Large Compact Bundle (LCB), is, in fact, a bundle containing 567 fibres (0.62 arcsec diameter), completed with the 8 minibundles (with 7 fibres every one) that sample the sky background emission. All those 623 fibres are organised in a total of 81 sub-units of 7 fibres distributed in 17 boxes on the pseudo-slit. These boxes are grouping and parceling out the fibres toward left and right of the center of the pseudo-slit in order to take advantage of the "covering".


MEGARA central bundle of fibres distribution: the Large Compact Bundle or IFU.

The IFU capability of MEGARA samples the 12.5 x 11.3 arcsec2 of the pointed sky area. The fibres distribution is the one that minimizes the cross-talk and/or the contamination between adjacent fibres. Two spaxels adjacent in the detector are physically separated (placed in different locations of the bundle). This is thought like this in order to prevent the concentration of brightly illuminated fibres at the detector.

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icon MOS Overview


The MOS is composed of 92 robotic arms holding 7 fibres each of them in a minibundle. Every Robotic positioner (RP) can patrol an hexagonal area which is the result of dividing the whole MOS 3.5 x 3.5 arcmin2 FOV (on sky) around the central IFU.

The positioning of the fiber minibundle is performed by combining the interpolation of two rotations, which allows covering a circle with a radius of 11.605 mm from the center of the positioner (this circle reaches the corners of the hexagon).

This sums up a total of 644 fibres devoted to science and sky (upon user decission).


There are one hundred minibundles but 8 are devoted to sky/background emission for IFU mode and they are fixed. The rest, 92, are able to patrol their cells and invade slitghly contiguous cell (non-zero risk of colliding).

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icon Use of Cover


There is available the capability of using a Cover which will interrupt the pass of light all over the half of field of view selected (it could be LEFT or RIGHT)


Note the gain in the paths separation by using the cover.

Since the MEGARA design is thought to separate every two neighbor fibres onto different part of the detector, if used you will need a specific set of calibrations (Traces, Arcs, Flats), but as compensation the recovered signal is almost free of pollution from adjacent fibres. Cover will not obstruct the fibres in the centre of the Field Of View (FOV), hence for a number of fibres of the IFU and depending on the MOS setup somes of the non-used robots might be vignetted by the cover edge.

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icon Preparing an observation with MEGARA


In order to prepare the observations with MEGARA, first of all an intensive use of Exposure Time Calculator should be considered. This link takes us to the ETC webpage to pre-compute our expected SNR or needed integration time. This is the most important thing to take into account when observing with the IFU. After this, on Phase-II you will be asked for coordinates, orientation of the field, grating or gratings to be used, exposure times and number of exposures and other relevants aspect of a MEGARA observation. Acquisition is always requested. You may find not relevant this step for your science case; if so please contact with your support astronomer of with Daniel Reverte to find an alternative way of acquiring your target.

Working with low surface brightness objects (IFU mode) the blind offset strategy is the most suitable. It is also recommended to every target with repeated pointings that has no relevant figures to aligned and different blocks should be overlapped (different VPHs separated in different blocks or targets with long total integration time splitted into few or several blocks).

In the case of performing a blind offset, please:

  • locate the brightest (< 15 mag) and closest (< 60 arcsec) star to the target of your interest;
  • write down the coordinates of that star in the "target definition" section; and then
  • in the blind-offset complete the (RA, Dec) offset needed to move from the star to the target (Remind that: + North / - South, + East / - West -> and also remind to apply a declination correction to the shift in RA).

For the Multi-Object Spectroscopy (MOS) mode: when preparing observations for MOS mode we would have to use the MOS preparation tool. A stand-alone java tool (java 1.8 or above is required) to configure and select the sources. It is important to note that, this (java) tool should be (more than very convenient) executed with internet connection in order to allow update of the config file from GTC web pages. To feed the tool you need to follow a particular ascii format. Please, contact with us if you find any problem.

Please consider care about the following recommendations:

  • Include at least 3 (and no more than 5) fiduciary stars as REFERENCE in the input megara-fmat file (.maf);
  • Needed SNR to get an appropriate offset in the acquisition (non-skippable) is almost 20, so select the brightest stars (preferable above 14 mag) or devote the required exp-time to obtain a centering;
  • SKY should be sampled with bundles among the 92* available. Hence using the megara-etc compute the number of needed robots to reach the relation S/N desired. To dedicate a bundle to sample the background identify as BLANK in the Source Type (meg).

* Check availability at the auto-updated megara-fmat start.

WARNING: With new version of the software previous issues declared here have been debbuged. Please, remind to use BLANK code instead of SKY for the positioners devoted to the background subtraction.


View of the Fiber MOS Positioning Tool for MEGARA.

The tool comes with an user manual very descriptive and complete.

Then, a file containing needed figures (Robots positions, Field centre, Position Angle and others), would be produced onto your system. By uploading that file to your Phase-II the Fiber MOS assigning file (extension .meg) needs to be checked against our system. For this reason an automatic process would start and you will have on the spot feedback about the upload validity. When passed that check most of details requested for this mode would be recovered from the .meg file. And the only thing that user would have to define is which is the grism (or are the grisms) and integration time(s) for the block.

Further questions, please contact Daniel Reverte.

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icon Data Reduction Pipeline

MEGARA instrument has its own data reduction pipeline, designed and developed as a pipeline (by Sergio Pascual and Nicolas Cardiel --and team-, UCM) that allows a complete cycle of work on the science images to produce flux and wavelength calibrated spectra. This data reduction pipeline is based on python and performs automatically the reduction, wavelength and flux-calibration (with just one input file of definitions -- image types and reduction desired) optimizing and recovering the best instrument capabilities as it was designed for.

There are some different ways to install this. The last MEGARA Data Reduction Pipeline version can be downloaded here (this corresponds to the latest release). Note that this requires some packages to be also installed in order to work properly.

We strongly recommend to install a platform to generate soft-isolated environments in order not to overlap functions or versions [and to prevent interaction with the OS (for python and others)]. In fact, among the eligible ones you could find some devoted to astronomy as astroconda (on github).

The most common and safe way is to install the appropriate version of anaconda and once you got it you will be able to install the megara-drp just by activating the base environment in your machine and by typing

(base) yourprompt> conda create -n megaradrp
(base) yourprompt> conda activate megaradrp
(megaradrp) yourprompt> conda install -c conda-forge megaradrp

Last installing method ensures a clean dependecies resolution and the last stable version.

The MEGARA Data Reduction Pipeline could be installed in another few simple ways. All of them well explained at the document installation instructions.

For an extensive introduction to the Data reduction process please consult the MEGARA Reduction cookbook.

icon Dependence on temperature

During tests carried out in the Lab review stage (on 2017, at the UCM), some dependence of the trace map on temperature was found. It was stated that there was a small shift in spatial-direction of the track that defines the path to recover every single fibre spectrum. That shift was found to be proportional to the shift in temperature respect to a work standard.

In any case, the effect is not neglectable when changes in temperature are above 2℃, in which case a proper trace map should be provided.

icon NOW AVAILABLE OFFICIAL Brand new Tool (for megara data handling)

Thanks to the UCM team, an official brand new tool to handle the output/reductions of the megaradrp from LCB data has been released. Although it is on its first stages, programmers wanted to share their advances to the whole community in the area of images/spectrum extraction, reconstruction and management.

Up to date one output from a LCB observation reduced through the megaradrp packages (final_rss.fits) could be represented graphically via one instruction within the same reduction package and conda env:

python -m megaradrp.visualization final_rss.fits [optional --wcs-grid --stretch (linear,sqrt,..) ...]

By obtaining a python output like:

The package megara-tools version 0.1.1 included in the new release, allows the PI having MEGARA data to reconstruct the cube, extract and/or analize single spectrum, among other functionalities well described in the section 6 of MEGARA Reduction cookbook.

This package is now available and can be installed through pip [pip install megara-tools] megara-tools, a package for handling with MEGARA Data Reduction Package outputs, by allowing, for instance, the cube reconstruction.

Please, for more details read about on chapter 6 here.

icon External Tool (for RSS to Cube reconstruction)

Thanks to Javier Zaragoza (INAOE) we have available this external tool to build up a cube from the output of the pipeline, the Raw Stacked Spectra.

Megararss2cube is a tool to convert MEGARA LCB reduced dataproducts from the RSS format obtained with megaradrp to a more user-friendly 3d datacube. Megararss2cube is based on the E3D format converter.

icon Random uncertainties estimate in emission line analysis

Python routines employed to automatically reduce and analyze the data from the MEGARA IFU instrument at GTC, including the method developed to estimate the random uncertainties associated to the emission line properties developed by C. Cabello as part of her thesis work can be retrieved here.

The program is first mentioned in Cabello, C. - PhD Thesis 2023, and Cabello et al. 2023 in prep.

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icon Data inspection / Ghosts


When you download your data (FTP direction:, the first you should identify in the package (tar.gz) is structured in subdirs. Science Data would be uncompressed under object directory, flats and traceMaps in flat, bias frames in bias, arcLamps frames in arcs, and spectrophotometric standard star/s in stds.

If you open directly (without processing) a fit frame of your IFU (MegaraLcbIMage) bright object or of the standard star, knowing that the centre of the Bundle is around the central fibres (those just up and down the overscan in the centre of the CCD), a ghost coming from the zero-order dispersion should appear vertically and coincident with the signal.


That signal is rather less than a 3rd of the peak signal emission for the object in the trace, and due to the precise way of extraction (via traceMap recovery) it is not expected that affects mainly on the final spectrum. It is located toward the 2200 pix in X direction.

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icon Scientific Cases


MEGARA Science Team is keen on a wide range of scientific interests. Some of them can be grouped in two categories:

  • 1. the study of Galactic and extragalactic nebulae.
  • 2. the study of (or close to) point-sources with intermediate-to-high surface densities.

Among the former their interests include the study of nearby galaxies, Planetary Nebulae and the emission of the resonant UV lines from the high-redshift IGM and among the latter the study of Galactic open stellar clusters, stellar populations in Local Group galaxies, GC systems in nearby galaxies, intermediate-redshift dwarf and starburst galaxies, and high-redshift galaxy clusters are the main subject of their research activities.

For further details, please visit the MEGARA team collection of web pages:

- Nearby Galaxies
- Intermediate Redshift
- High Redshift
- Planetary Nebulae
- Stellar Clusters

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icon MEGARA contact persons at GTC


contact email @
Daniel Reverte - main contact daniel.reverte
Nieves Castro nieves.castro

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icon Useful Documents

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icon More Information

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Last modified: 05 March 2024

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