SCIFYsim: a python package for interferometric nulling simulation

It is a python module designed to simulate the behaviour of high-contrast interferometric instruments, with a focus on the Very Large Telescope Interferometer. It can also be easily applied to other ground-based and space facilities.

SCIFYsim aims at replacing GENIEsim [1] for all the simulations in the SCIFY project. It is specifically developped to accompany the development and implementation of future generations of advanced nulling techniques [2] [3].

Principles:

SCIFYsim uses:

• Possibly extended stars and sources of interest using blackbody spectrum or provided spectra.
• The projection of the observing array of pupils
• Absorption and thermal emission of the train of optics and atmosphere
• Random optical path aberrations from fringe tracking error power spectra
• Random injection aberrations based on partially AO-corrected wavefront
• Atmospheric dispersion effects and their correction devices (Work in progress)
• Beam combination in an interchangeable combiner matrix (including chromatic aberrations)
• Spectrograph and detector integration

It produces:

• Direct and differential (kernel) maps of the transmission in the field of view

• Temporal series of simulated observations

• Characterization of noises from

  • Thermal background
  • Photon noise
  • Instrumental aberrations

• Computation of detection sensitivity based on advanced hypothesis testing techniques [4] combining the evolution of the baselines and all the spectral channels.

Documentation:

Find growing API documentation here

Acknowledgement

SCIFYsim is a development carried out in the context of the SCIFY project. SCIFY has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 866070).

Dependencies:

Last tested with python 3.9 . The following packages are required:

• kernuller https://github.com/rlaugier/kernuller
• xaosim <https://github.com/fmartinache/xaosim>

Optional:

• dask To allow the construction of larger sensitivity maps
• jupyterlab To interact with the similator in enriched interactive scripts

Recommandation for installation:

python setup.py install

See the dedicated installation page of the documentation.

Rerences:

[1]	Absil et al. (2006), A&A, 448, 787-800.

[2]	Martinache & Ireland (2018), A&A, 619, A87

[3]	Laugier et al. (2020), A&A, 642, A202

[4]	Ceau et al. (2019), A&A, 630, A120