Atmospheric aNd Instrumental models in the Measurement Equation - Anime - is an instrument modelling framework for radio interferometry written in Julia, an open source, high performance language for scientific computing. Anime aims to support efficient handling of various data formats commonly used in VLBI, provide seamless conversion between these formats and a variety of data products as output by a Very Long Baseline Interferometry (VLBI) array, and integrate with other Julia-based software packages for VLBI data analysis.

Signals from astronomical sources are affected by various effects (e.g. atmospheric, mechanical, electronic) along the propagation path before they are recorded. Some of these effects can be modelled from first principles while for others a phenomenological approach that captures the statistical properties of the effect is more useful. Modelling these effects is an important step towards understanding both the astronomical source of interest and the capabilities and limitations of existing and planned instruments.

Within the EHT, MeqSilhouette v2 (MEQSv2)[IN2022][TB2017] is used to generate uncalibrated synthetic data using a physics-based a priori approach to simulate certain propagation path effects. The end-to-end synthetic data generation pipeline SYMBA[RJ2020] passes the synthetic data generated by MEQSv2 to rPICARD[MJ2019], a CASA-based calibration pipeline, to simulate realistic residual calibration errors. While SYMBA/MEQSv2 can introduce some complex propagation path effects this comes at a high computational cost due to its being a full-fledged pipeline with many moving parts implemented in bash and python that stitch together data products from different "monolothic" stages.

Anime is designed to provide a complete framework in Julia to compute instrument models from first principles wherever possible and to generate synthetic VLBI data sets with support for and convert b/w multiple VLBI data storage formats. It can construct instrument models for multi-scan VLBI observations with irregulary-spaced and missing data without having to construct a regular grid of complex visibilities in baseline and time (like SYMBA/MEQSv2), thereby speeding up the generation of synthetic data. It also constructs more realistic models, re-implementing existing models from SYMBA/MEQSv2 in Julia for more efficient computation and introducing new ones. The ultimate aim is to be able to read/write commonly used on-disk data formats in VLBI and provide a set of instrument modelling functions that other software written in Julia (e.g. Comrade[PT2022]) can import and use for synthetic data generation, calibration and imaging. Inference methods for emulating the statistical properties of actual data are also in development.


  • RJ2020Roelofs F., Janssen M., Natarajan I. et al. SYMBA: An end-to-end VLBI synthetic data generation pipeline (2020) A&A
  • AC2018Chael A. et al., Interferometric Imaging Directly with Closure Phases and Closure Amplitudes (2018) ApJ
  • IN2022Natarajan I. et al. MeqSilhouette v2: spectrally resolved polarimetric synthetic data generation for EHT (2022) MNRAS
  • TB2017Blecher T. et al. MEQSILHOUETTE: a mm-VLBI observation and signal corruption simulator (2017) MNRAS
  • MJ2019Janssen M. et al. rPICARD: A CASA-based calibration pipeline for VLBI data (2019) A&A
  • PT2022Tiede P. Comrade: Composable Modeling of Radio Emission (2022) JOSS