🔭 astrophysics

e-CALLISTO FITS Analyzer: A Software Framework for CALLISTO Solar Radio Data

This paper introduces the e-CALLISTO FITS Analyzer, a cross-platform software framework designed to process and analyze e-CALLISTO solar radio burst data by merging fragmented observations, removing noise, and extracting key physical parameters like drift rates and shock speeds to enable more reproducible event-level studies.

Original authors: G. L. S. S. Liyanage, J. Adassuriya, K. P. S. C. Jayaratne, C. Monstein, P. K. Manoharan

Published 2026-03-30

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CC BY 4.0

Original authors: G. L. S. S. Liyanage, J. Adassuriya, K. P. S. C. Jayaratne, C. Monstein, P. K. Manoharan

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the Sun as a massive, chaotic concert hall. Every day, it throws wild parties where particles accelerate and shockwaves crash through the atmosphere. These events create "radio noise" that travels across the solar system. Scientists call these Solar Radio Bursts.

To listen to this cosmic concert, we have a global network of over 150 small, affordable radio telescopes called CALLISTO. They are like a choir of listeners spread all over the Earth, recording the Sun's radio signals 24/7.

However, there's a problem: The data they collect is messy.

It's fragmented: The concert is recorded in 15-minute clips. If a "song" (a solar burst) lasts 30 minutes, it gets chopped into two separate files, making it hard to hear the whole tune.
It's noisy: The recordings are full of static from Earth's own radio signals (like cell phones and Wi-Fi) and background hiss.
It's hard to read: The files are in a complex format (FITS) that requires coding skills to decode, leaving many astronomers unable to analyze the data easily.

The Solution: The "e-CALLISTO FITS Analyzer"

This paper introduces a new software tool, the e-CALLISTO FITS Analyzer, which acts like a "Swiss Army Knife" for solar radio data. It's a user-friendly app that runs on Windows, Mac, and Linux, designed to turn that messy, chopped-up noise into a clear, scientific story.

Here is how it works, using some everyday analogies:

1. The "Puzzle Assembler" (Merging Data)

Imagine you have a jigsaw puzzle, but the pieces are scattered across different boxes, and some pieces are from slightly different puzzles.

The Problem: A solar burst might start in one 15-minute file and end in the next.
The Fix: The Analyzer acts like a smart puzzle assembler. It can take multiple files, stitch the time together (so the 15-minute clips become one long movie), and even combine different frequency bands (like merging different color channels) to create one continuous, seamless spectrum.

2. The "Noise-Canceling Headphones" (Background Subtraction)

Imagine trying to hear a whisper in a crowded, noisy room.

The Problem: The radio data is filled with constant background static and interference.
The Fix: The software calculates the "average noise" of the room and subtracts it. It's like putting on noise-canceling headphones that only let the interesting "whispers" (the solar bursts) through. You can also adjust a "volume knob" (threshold) to make the quiet whispers louder or cut out the loud, annoying static.

3. The "Highlighter Pen" (Interactive Masking)

Imagine a photo of a busy street, and you want to study just one specific car.

The Problem: The data shows the whole sky, but you only care about one specific burst.
The Fix: Instead of writing complex code to tell the computer what to look at, you simply use your mouse to draw a shape (a polygon) around the burst on the screen. The software then "highlights" only that area and ignores everything else. It's like using a highlighter pen on a textbook to focus only on the important sentences.

4. The "Speedometer" (Calculating Physics)

Once the burst is isolated, the software acts like a detective's calculator.

The Goal: Scientists want to know how fast the shockwave is moving and how high up in the Sun's atmosphere it is.
The Method: The software traces the "backbone" (the brightest part) of the burst. It then draws a line through the data points to see how fast the frequency is changing (the "drift").
The Metaphor: Think of a car driving down a hill. As it goes lower, the air gets thicker. If you know how fast the car is changing its altitude based on how the engine pitch changes, you can calculate its speed. The software does this math automatically, using a model of the Sun's atmosphere (the Newkirk model) to tell you: "This shockwave is moving at 449 km/s and is currently 1.7 times the Sun's radius away from the surface."

Why This Matters

Before this tool, analyzing solar radio bursts was like trying to fix a car engine while wearing boxing gloves and reading a manual written in a foreign language. You needed to be a programmer to do it.

The e-CALLISTO FITS Analyzer takes off the boxing gloves and translates the manual. It allows astronomers (and even students) to:

See the whole picture by merging fragmented data.
Clean the signal to see the real event.
Measure the physics with a few clicks.

In short, it democratizes solar research. It turns a mountain of confusing data into a clear, interactive story about the Sun's dynamic behavior, helping us better predict "space weather" that can affect our satellites and power grids here on Earth.

1. Problem Statement

Solar radio bursts (SRBs), particularly Type II and Type III bursts, are critical indicators of particle acceleration and shock propagation associated with solar flares and Coronal Mass Ejections (CMEs). The e-CALLISTO network, comprising over 150 stations worldwide, generates a massive archive of dynamic spectra in FITS format. However, analyzing this data presents significant challenges:

Data Volume & Fragmentation: Observations are segmented into 15-minute FITS files. Long-duration events often span multiple files, and different stations use irregular frequency setups, making it difficult to create continuous spectra for event-level analysis.
Noise & Interference: Raw spectra are heavily contaminated by terrestrial Radio Frequency Interference (RFI) and background noise, requiring robust filtering before physical parameters can be extracted.
Limitations of Existing Tools:
- Statistical/Automated methods (e.g., Area Slope Index, Burst-Finder) often fail to detect weak bursts (low SNR) or produce false positives due to RFI.
- Deep Learning models (e.g., deARCE) act as "black boxes," requiring massive training data and lacking the interactive environment needed for precise kinematic analysis.
- Code libraries (e.g., pyCallisto) require programming proficiency, creating a barrier for observational astronomers.
- Existing GUIs (e.g., Solar Radio Burst Analyzer) are often semi-automated, rely on rigid mathematical models (linear/exponential fits) that may not capture complex non-linear morphologies, and lack seamless workflows for merging fragmented data.

2. Methodology

The authors developed the e-CALLISTO FITS Analyzer, a unified, cross-platform (Windows, macOS, Linux) interactive application written in Python. The software architecture follows a modular design with the following key processing steps:

A. Data Ingestion and Merging

FITS Parsing: The tool parses standard e-CALLISTO FITS files, extracting the intensity matrix ( $I$ ), frequency vector ( $f$ ), and time vector ( $t$ ).
Time & Frequency Combination:
- Frequency Merging: Stacks intensity matrices along the frequency axis to combine sub-bands from different receiver settings.
- Time Merging: Concatenates matrices along the time axis, applying cumulative time offsets to create a continuous, monotonic timeline for events spanning multiple 15-minute files.

B. Pre-processing and Isolation

Background Subtraction: Calculates a per-frequency mean background ( $\mu_i$ ) over time and subtracts it from the intensity matrix to remove quasi-stationary structures.
Threshold Clipping: Applies user-controlled lower and upper thresholds to suppress residual noise and enhance burst contrast.
Interactive Masking: Users define a closed polygon in the time-frequency plane to isolate specific burst regions (e.g., Type II lanes). This creates a Boolean mask to extract a "burst-only" matrix, agnostic to burst class.

C. Quantitative Analysis (Type II Focus)

Backbone Extraction: For the isolated burst, the software extracts the maximum-intensity backbone ( $f_{max}(t)$ ) by finding the frequency index with the highest intensity at each time step.
Interactive Outlier Removal: Users can manually select and remove spurious points (outliers) from the backbone plot to ensure data quality before fitting.
Drift Rate Calculation: The cleaned backbone is fitted using a power-law model ( $f(t) = At^b$ ). The instantaneous drift rate ($df/dt$) is derived from the derivative of this fit, and an average drift rate is calculated over the selected interval.
Shock Parameter Estimation: Using the Newkirk electron density model ( $n_e(R)$ $n_{e} (R)$ ), the tool converts the frequency and drift rate into physical parameters:
- Shock Height ( $R_s$ ): Calculated based on the plasma frequency relation.
- Shock Speed ( $V_s$ ): Derived by differentiating the height with respect to time.
- The model supports $n$ -fold scaling (e.g., fundamental vs. harmonic bands).

D. Visualization and Extensibility

The interface provides real-time visualization of raw, background-subtracted, and isolated spectra with physically meaningful axes (UT time and MHz).
It includes modular extensions for GOES X-ray flux and SOHO/LASCO CME data, allowing correlated analysis within a single ecosystem.

3. Key Contributions

Unified Workflow: First tool to seamlessly merge fragmented FITS files across time and frequency, enabling continuous analysis of long-duration events.
Interactive Flexibility: Replaces rigid, automated classification with an interactive GUI that allows researchers to manually define burst regions, tune background subtraction, and remove outliers, ensuring scientific rigor.
Cross-Platform Accessibility: Provides a standalone application (no coding required) for Windows, macOS, and Linux, democratizing access to rigorous solar radio analysis.
Physical Parameter Derivation: Integrates a complete pipeline from raw data to physical shock parameters (speed, height) using standard coronal density models.

4. Results

The authors validated the tool using a Type II solar radio burst observed by the Arecibo Observatory on March 2, 2022.

Processing: The tool successfully merged data, removed background noise, and isolated the fundamental band of the burst.
Measurements:
- Average Drift Rate: $-0.0400 \pm 0.0003$ MHz/s.
- Shock Speed: $449 \pm 1$ km/s.
- Shock Height: $1.715 \pm 0.002 R_\odot$ (Solar Radii).
Performance: The application demonstrated the ability to handle the specific morphological complexities of the burst, producing publication-ready plots and tabulated data.

5. Significance

The e-CALLISTO FITS Analyzer addresses a critical bottleneck in space weather research by transforming a fragmented, noisy, and technically demanding data archive into a coherent, analyzable resource.

Reproducibility: By standardizing the workflow for merging, cleaning, and fitting, it ensures that different researchers can reproduce event-level analyses.
Event-Focused Analysis: It shifts the focus from simple event logging to detailed physical characterization of shock waves, essential for forecasting geomagnetic storms and Solar Energetic Particle (SEP) events.
Future-Proofing: The modular design allows for the integration of new density models, calibration procedures, and external data sources without disrupting the core radio analysis pipeline.

In summary, this software framework bridges the gap between raw astronomical data and physical insight, enabling a broader community of astronomers to extract meaningful kinematic properties from the vast e-CALLISTO archive.