- The paper introduces a pioneering design of a robotic telescope network that facilitates uninterrupted, high-resolution stellar observations.
- It details the hardware, including 1m alt-az telescopes, high-resolution spectrographs (R=35k–115k), and lucky imaging CCDs for precise imaging.
- The paper outlines an autonomous software architecture utilizing Python, PostgreSQL, and real-time data replication for seamless operation.
Hardware and Software for a Robotic Network of Telescopes - SONG
Introduction
The Stellar Observations Network Group (SONG) project seeks to establish a global network of small robotic telescopes, specifically utilizing 1m telescopes, to facilitate uninterrupted stellar observations over extended periods. This network is designed to consist of four telescopes in each hemisphere, enabling continuous observation of celestial objects for days, weeks, or even months. The project aims to deepen the understanding of stellar structures and evolutionary processes by analyzing stellar oscillations. By employing high-precision radial-velocity measurements via a high-resolution echelle spectrograph, astronomers can perform asteroseismology, which is essential for determining stellar characteristics such as age, mass, and size. The network's capabilities will also support exoplanet exploration through techniques like gravitational microlensing and radial velocity measurements.
Telescope and Instruments
Each SONG site is equipped with critical instruments, including the SONG spectrograph and lucky imaging CCD cameras. The 1m alt-az mounted telescopes, equipped with a sophisticated mirror system, can leverage the guiding system to observe stars with V magnitudes down to 7-8. Notably, the spectrograph operates at resolutions ranging from 35,000 to 115,000, covering wavelengths between 4400 and 6900 Å, ensuring precise spectroscopic data. The lucky imaging cameras, designed for high-resolution imaging, offer unique specifications such as maximum readout speed of 33 Hz for the full frame and less than 1 electron readout noise with electron multiplication gain.
Software Architecture
The SONG observatories are designed to function autonomously, relying on sophisticated control software to manage operations without on-site human intervention. The control system uses Ethernet-based device controls and a suite of Python-written software packages to ensure seamless operation. A central database implemented using PostgreSQL harmonizes data and observing requests across the network. It employs Slony-I for database synchronization and GlusterFS for data replication, enabling continuous and reliable data processing and management. Observational procedures are largely automated, with human interaction limited to scheduling observations through a web interface or Python scripts.
Preliminary Results and Current Status
Initial tests using the SONG spectrograph to observe the Sun demonstrated the system's capability of capturing uninterrupted high-resolution spectroscopic data over multiple days. A power spectrum analysis of a 6-day solar observation campaign revealed notable solar oscillations, demonstrating the potential of the SONG configuration for groundbreaking asteroseismic studies. The current prototype telescope installed at Observatorio del Teide in Tenerife is operational, while a second node is being developed in China.
Conclusion
The SONG network represents a significant advancement in the field of stellar astrophysics and observational astronomy. By developing a networked robotic telescope system, the project addresses the limitations of single-site observations, enabling continuous and comprehensive data collection. The results from initial observations underscore the potential to enhance our understanding of stellar and planetary phenomena. Future efforts aim to expand the network, with additional nodes under development, representing an ongoing enhancement of this global observational infrastructure. The long-term vision of SONG holds promise for innovative and detailed exploration of stellar and planetary dynamics.