Lossless Compression for Radio Interferometric Data
Analysis
This paper addresses the critical problem of data volume in radio interferometry, particularly in direction-dependent calibration where model data can explode in size. The authors propose a lossless compression method (Sisco) specifically designed for forward-predicted model data, which is crucial for calibration accuracy. The paper's significance lies in its potential to significantly reduce storage requirements and improve the efficiency of radio interferometric data processing workflows. The open-source implementation and integration with existing formats are also key strengths.
Key Takeaways
- •Proposes a lossless compression method (Sisco) for forward-predicted model data in radio interferometry.
- •Sisco achieves significant compression, reducing data volume to as low as 13% of the original size for smooth data.
- •The method is implemented as an open-source Casacore storage manager, facilitating easy integration.
- •The paper highlights the importance of lossless compression for model data in calibration workflows.
Reference
“Sisco reduces noiseless forward-predicted model data to 24% of its original volume on average.”