# Motivation

Astronomical research increasingly rely on realistic simulations to interpret observations, test hypotheses, and develop new analysis techniques. However, generating synthetic astronomical images that accurately reflect real-world data can be challenging due to the complexity of celestial catalogs and instrument effects.

**cabaret** was developed to address these challenges by providing:

- **Easy Access to Gaia Data:**  
  Seamless integration with the [Gaia catalog](https://en.wikipedia.org/wiki/Gaia_catalogues) enables users to simulate star fields based on real astronomical data.

- **Flexible Simulation Tools:**  
  Users can customize observatory parameters, detector properties, and simulation settings to match a wide range of scenarios.

- **Reproducibility and Experimentation:**  
  By generating synthetic data, researchers can test data analysis pipelines, validate algorithms, and train machine learning models in a controlled environment.

- **Educational Value:**  
  Instructors and students can use cabaret to visualize astronomical concepts, experiment with observational setups, and better understand the impact of instrument design on data quality.

## Built on cabaret: alpaca-simulators

[alpaca-simulators](https://github.com/ppp-one/alpaca-simulators) is a comprehensive simulator for ASCOM Alpaca devices, built on top of cabaret. It provides a RESTful API for testing and developing observatory control software. The Alpaca API uses RESTful techniques and TCP/IP to enable ASCOM applications and devices to communicate across modern network environments.

By providing realistic device simulation and image generation, alpaca-simulators enables thorough testing and development of robotic telescope control software and observatory automation systems. Developers can validate control logic, device communication, and data acquisition workflows in a safe, reproducible environment—without requiring access to physical hardware.
