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exoplanet-detection-period-lomb-scargle-periodogram系外行星探测周期 lomb 斯卡格周期图

Agent Skill

exoplanet-detection-period-lomb-scargle-periodogram 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

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来源可访问

安装方式

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请帮我安装这个 Agent Skill:exoplanet-detection-period-lomb-scargle-periodogram(系外行星探测周期 lomb 斯卡格周期图)
来源仓库:https://github.com/wu-uk/exoplanet-detection-period-lomb-scargle-periodogram
安装命令:
openclaw skills install exoplanet-detection-period-lomb-scargle-periodogram
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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openclaw skills install exoplanet-detection-period-lomb-scargle-periodogram

简介

使用 Lomb-Scargle 方法在不均匀采样数据中查找周期信号。

  • 适合分析径向速度或光变曲线等非均匀时序数据时使用。
  • 需在 OpenClaw 中通过 clawhub 安装,输入时间序列后生成周期图。
  • 建议确认是否涉及傅里叶变换类数学运算权限。exoplanet-detection-period-lomb-scargle-periodogram 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 适用于天文学与信号处理中的周期特征提取场景。

SKILL.md

name
lomb-scargle-periodogram
description
Lomb-Scargle periodogram for finding periodic signals in unevenly sampled time series data. Use when analyzing light curves, radial velocity data, or any astronomical time series to detect periodic variations. Works for stellar rotation, pulsation, eclipsing binaries, and general periodic phenomena. Based on lightkurve library.

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

  1. Single strong peak: Likely the true period
  2. Harmonics: Peaks at period/2, period*2 suggest the fundamental period
  3. 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.

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