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$ agentstack add skill-xushuwenn-redact-lomb-scargle-periodogram ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
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✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
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Reliability & compatibility
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Lomb-Scargle Periodogram
The Lomb-Scargle periodogram is the standard tool for finding periods in unevenly sampled astronomical time series data. It's particularly useful for detecting periodic signals in light curves from space missions like Kepler, K2, and TESS.
Overview
The Lomb-Scargle periodogram extends the classical periodogram to handle unevenly sampled data, which is common in astronomy due to observing constraints, data gaps, and variable cadences.
Basic Usage with Lightkurve
import lightkurve as lk
import numpy as np
# Create a light curve object
lc = lk.LightCurve(time=time, flux=flux, flux_err=error)
# Create periodogram (specify maximum period to search)
pg = lc.to_periodogram(maximum_period=15) # Search up to 15 days
# Find strongest period
strongest_period = pg.period_at_max_power
max_power = pg.max_power
print(f"Strongest period: {strongest_period:.5f} days")
print(f"Power: {max_power:.5f}")
Plotting Periodograms
import matplotlib.pyplot as plt
pg.plot(view='period') # View vs period (not frequency)
plt.xlabel('Period [days]')
plt.ylabel('Power')
plt.show()
Important: Use view='period' to see periods directly, not frequencies. The default view='frequency' shows frequency (1/period).
Period Range Selection
Choose appropriate period ranges based on your science case:
- Stellar rotation: 0.1 - 100 days
- Exoplanet transits: 0.5 - 50 days (most common)
- Eclipsing binaries: 0.1 - 100 days
- Stellar pulsations: 0.001 - 1 day
# Search specific period range
pg = lc.to_periodogram(minimum_period=2.0, maximum_period=7.0)
Interpreting Results
Power Significance
Higher power indicates stronger periodic signal, but be cautious:
- High power: Likely real periodic signal
- Multiple peaks: Could indicate harmonics (period/2, period*2)
- Aliasing: Very short periods may be aliases of longer periods
Common Patterns
- Single strong peak: Likely the true period
- Harmonics: Peaks at period/2, period*2 suggest the fundamental period
- Aliases: Check if period*2 or period/2 also show signals
Model Fitting
Once you find a period, you can fit a model:
# Get the frequency at maximum power
frequency = pg.frequency_at_max_power
# Create a model light curve
model = pg.model(time=lc.time, frequency=frequency)
# Plot data and model
import matplotlib.pyplot as plt
lc.plot(label='Data')
model.plot(label='Model')
plt.legend()
plt.show()
Dependencies
pip install lightkurve numpy matplotlib
References
When to Use This vs. Other Methods
- Lomb-Scargle: General periodic signals (rotation, pulsation, eclipsing binaries)
- Transit Least Squares (TLS): Specifically for exoplanet transits (more sensitive)
- Box Least Squares (BLS): Alternative transit detection method
For exoplanet detection, consider using TLS after Lomb-Scargle for initial period search.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: XuShuwenn
- Source: XuShuwenn/RedAct
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.