Introduction

ORCS (Outils de Réduction de Cubes Spectraux) is an analysis engine for SITELLE spectral cubes. With ORCS you can:

• extract integrated spectra

• fit the sinc emission lines

• recalibrate your data in wavelength, astrometry and flux

• choose between a Bayesian or a classical fitting algorithm

• and much more ...

warning ORCS is always in fast development. You might see bugs or strange behaviours ! You might also want desperatly to have new features. In all cases please send an email: thomas.martin.1@ulaval.ca

Documentation

You can find the up-to-date documentation here: https://orcs.readthedocs.io/

Examples

Examples in Jupyter notebook format can be found in the documentation:

https://github.com/thomasorb/orcs/tree/master/docs/examples

First basic examples

These examples show the basic usage of ORCS

• Example of a single spectrum fit
• How precise must be the input velocity parameter ?
• Extract the deep frame and use the WCS
• Make a fit over an entire region of the field
• Differences between fitting a sincgauss model and two sinc lines

Bayesian fitting vs. classical fitting

Here are more advanced examples that show step-by-step the differences between a classical fit and a Bayesian fit on a model spectrum. You will thus first learn how to model a spectrum and then fit a model spectrum with one line, two resolved lines and two unresolved lines: this is when the bayesian fitting algorithm becomes intersting ;)

• Modelling and fitting a single line spectrum
• Modelling and fitting a spectrum with two resolved lines
• Modelling and fitting two unresolved emission lines with a bayesian approach

Calibrating your data

A data cube can be recalibrated using mode specific algorithm which depends on the type of data you have observed. You might want to give a try to these examples to see if you can get a better calibration for your data.

• Wavelength recalibration with the sky lines (Mendel OH bands)
• Image registration
• Flux Calibration Example Using HST image

Advanced fitting

These examples show advanced fitting procedures.

• Constraining line ratios
• Use mapped inputs (e.g. for the velocity)

Other Tools

• Automatic source detection
• Radial Velocity Correction

Related Publications

• Martin, Drissen, Melchior (2017). A SITELLE view of M31's central region - I: Calibrations and radial velocity catalogue of nearly 800 emission-line point-like sources. MNRAS (accepted) http://adsabs.harvard.edu/abs/2017arXiv170701366M

• Martin, Drissen (2017). SITELLE's level-1 calibration. MNRAS (submitted) http://adsabs.harvard.edu/abs/2017arXiv170603230M

• Martin, Prunet, Drissen (2016). Optimal fitting of Gaussian-apodized or under-resolved emission lines in Fourier transform spectra providing new insights on the velocity structure of NGC 6720. MNRAS http://adsabs.harvard.edu/abs/2016MNRAS.463.4223M

• Martin, Drissen, Joncas (2015). ORBS, ORCS, OACS, a Software Suite for Data Reduction and Analysis of the Hyperspectral Imagers SITELLE and SpIOMM. PASP http://adsabs.harvard.edu/abs/2015ASPC..495..327M

Installation

1. install ORB

Follow the installation instructions here

2. add orcs module

clone ORCS

mkdir orcs-stable # do it where you want to put orcs files
cd orcs-stable
git clone https://github.com/thomasorb/orcs.git

in the downloaded folder

conda activate orb # you don't need to do it if you are already in the orb environment
cd path/to/orcs-stable/orcs
python setup.py install

Test it:

conda activate orb # you don't need to do it if you are already in the orb environment
python -c 'import orcs.process'