juliensimon/fermi-3pc-gamma-ray-pulsars

---
license: cc-by-4.0
pretty_name: "Fermi LAT Third Pulsar Catalog (3PC)"
language:
- en
description: "Gamma-ray pulsars detected by the Fermi Large Area Telescope, including spin parameters, fluxes, and spectral properties from the 3PC catalog"
task_categories:
- tabular-classification
tags:
- space
- open-data
- tabular-data
- parquet
- fermi
- nasa
- pulsar
- gamma-ray
- high-energy
- astronomy
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: data/fermi-3pc.parquet
default: true
---

# Fermi LAT Third Pulsar Catalog (3PC)

<div align="center">
<img src="banner.jpg" alt="Cassiopeia A supernova remnant in X-ray, optical, and infrared light" width="400">
<p><em>Credit: NASA/JPL-Caltech/STScI/CXC/SAO</em></p>
</div>

*Part of the [Astronomy Datasets](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743) and [Physics Datasets](https://huggingface.co/collections/juliensimon/physics-datasets-681b79c9a7e113e34e4467f4) collections on Hugging Face.*


Complete catalog of **7,197** gamma-ray pulsars detected by the
[Fermi Large Area Telescope (LAT)](https://fermi.gsfc.nasa.gov/ssc/),
sourced from NASA HEASARC.

## Dataset description

Pulsars are rapidly rotating, highly magnetized neutron stars that emit beams of electromagnetic radiation. When these beams sweep across Earth, they produce periodic pulses observed across the spectrum from radio to gamma rays. The **Fermi LAT Third Pulsar Catalog (3PC)** is the definitive census of pulsars detected at GeV gamma-ray energies by the Fermi Large Area Telescope, the most sensitive gamma-ray surveyor ever flown.

Gamma-ray pulsars fall into two broad populations:

- **Millisecond pulsars (MSPs)**: old neutron stars spun up to periods of 1-30 ms by accretion from a binary companion. They have weak surface magnetic fields (~10^8-10^9 G) but enormous spin-down luminosities. Many were first discovered through gamma-ray pulsation searches, having been missed by radio surveys.
- **Young pulsars**: recently formed neutron stars (characteristic ages < ~100 kyr) with strong magnetic fields (~10^12 G) and periods of 30 ms to several seconds. These include famous objects like the Crab and Vela pulsars.

The Fermi LAT is uniquely suited for pulsar studies because gamma rays probe the magnetospheric emission regions directly. Unlike radio emission (which originates from a narrow cone near the magnetic poles), gamma-ray emission arises from particle acceleration in the outer magnetosphere or current sheet, providing constraints on pulsar emission geometry and plasma physics that are inaccessible at other wavelengths.

The 3PC catalog includes spin parameters (period, period derivative), derived quantities (spin-down luminosity, characteristic age, surface magnetic field), spectral properties (spectral index, cutoff energy), and flux measurements for each detected pulsar.

## Schema

| Column | Type | Description |
|--------|------|-------------|
| `__row` | float | Row |
| `name` | string | Pulsar name (e.g. J0030+0451) |
| `data_release` | float | Data Release |
| `ra` | float | Right ascension (degrees, J2000) |
| `dec` | float | Declination (degrees, J2000) |
| `lii` | float | Galactic longitude (degrees) |
| `bii` | float | Galactic latitude (degrees) |
| `semi_major_axis_68` | float | Semi Major Axis 68 |
| `semi_minor_axis_68` | float | Semi Minor Axis 68 |
| `position_angle_68` | float | Position Angle 68 |
| `semi_major_axis_95` | float | Semi Major Axis 95 |
| `semi_minor_axis_95` | float | Semi Minor Axis 95 |
| `position_angle_95` | float | Position Angle 95 |
| `detection_significance` | float | Detection Significance |
| `pivot_energy` | float | Pivot Energy |
| `flux_1_100_gev` | float | Flux 1 100 Gev |
| `flux_1_100_gev_error` | float | Flux 1 100 Gev Error |
| `energy_flux` | float | Energy Flux |
| `energy_flux_error` | float | Energy Flux Error |
| `pl_flux_density` | float | Pl Flux Density |
| `pl_flux_density_error` | float | Pl Flux Density Error |
| `pl_index` | float | Pl Index |
| `pl_index_error` | float | Pl Index Error |
| `lp_flux_density` | float | Lp Flux Density |
| `lp_flux_density_error` | float | Lp Flux Density Error |
| `lp_index` | float | Lp Index |
| `lp_index_error` | float | Lp Index Error |
| `lp_beta` | float | Lp Beta |
| `lp_beta_error` | float | Lp Beta Error |
| `lp_curve_significance` | float | Lp Curve Significance |
| `lp_epeak` | float | Lp Epeak |
| `lp_epeak_error` | float | Lp Epeak Error |
| `plec_flux_density` | float | Plec Flux Density |
| `plec_flux_density_error` | float | Plec Flux Density Error |
| `plec_index_s` | float | Plec Index S |
| `plec_index_s_error` | float | Plec Index S Error |
| `plec_exp_factor_s` | float | Plec Exp Factor S |
| `plec_exp_factor_s_error` | float | Plec Exp Factor S Error |
| `plec_exp_index` | float | Plec Exp Index |
| `plec_curve_significance` | float | Plec Curve Significance |
| `plec_epeak` | float | Plec Epeak |
| `plec_epeak_error` | float | Plec Epeak Error |
| `npred` | float | Npred |
| `variability_index` | float | Variability Index |
| `frac_variability` | float | Frac Variability |
| `frac_variability_error` | float | Frac Variability Error |
| `significance_peak` | float | Significance Peak |
| `flux_peak` | float | Flux Peak |
| `flux_peak_error` | float | Flux Peak Error |
| `time_peak` | float | Time Peak |
| `time_peak_interval` | float | Time Peak Interval |
| `assoc_name` | string | Associated source name |
| `assoc_prob_bay` | float | Assoc Prob Bay |
| `assoc_prob_lr` | float | Assoc Prob Lr |
| `assoc_ra` | float | Assoc Ra |
| `assoc_dec` | float | Assoc Dec |
| `assoc_error_radius` | float | Assoc Error Radius |
| `analysis_flags` | float | Analysis Flags |
| `__x_ra_dec` | float | X Ra Dec |
| `__y_ra_dec` | float | Y Ra Dec |
| `__z_ra_dec` | float | Z Ra Dec |

## Quick stats

- **7,197** gamma-ray pulsars
- **61** columns retained after null filtering

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/fermi-3pc-gamma-ray-pulsars", split="train")
df = ds.to_pandas()

# Overview
print(f"{len(df):,} gamma-ray pulsars")
print(df.describe())
```

## Data source

All data comes from the [Fermi LAT Pulsar Catalog (fermilpsc)](https://heasarc.gsfc.nasa.gov/W3Browse/fermi/fermilpsc.html)
hosted by NASA's High Energy Astrophysics Science Archive Research Center (HEASARC),
accessed via the TAP protocol.

Based on: Smith, D.A. et al. (2023), "The Third Fermi Large Area Telescope Catalog of Gamma-Ray Pulsars",
*The Astrophysical Journal*, 958, 191. [arXiv:2307.11132](https://arxiv.org/abs/2307.11132)

## Update schedule

Static dataset. The 3PC catalog is a fixed publication; re-run only if HEASARC updates the table.

## Related datasets

- [pulsar-catalog](https://huggingface.co/datasets/juliensimon/pulsar-catalog) — ATNF Pulsar Catalog (radio + multiwavelength)
- [fermi-4fgl-dr4](https://huggingface.co/datasets/juliensimon/fermi-4fgl-dr4) — Fermi LAT 4FGL-DR4 source catalog
- [fermi-3fhl-hard-gamma-ray](https://huggingface.co/datasets/juliensimon/fermi-3fhl-hard-gamma-ray) — Fermi LAT 3FHL hard gamma-ray sources
- [fermi-4lac-agn-catalog](https://huggingface.co/datasets/juliensimon/fermi-4lac-agn-catalog) — Fermi LAT AGN catalog

## Pipeline

Source code: [juliensimon/space-datasets](https://github.com/juliensimon/space-datasets)

## Support

If you find this dataset useful, please give it a ❤️ on the [dataset page](https://huggingface.co/datasets/juliensimon/fermi-3pc-gamma-ray-pulsars) and share feedback in the Community tab! Also consider giving a ⭐️ to the [space-datasets](https://github.com/juliensimon/space-datasets) repo.

## Citation

```bibtex
@dataset{fermi_3pc_gamma_ray_pulsars,
author = {Simon, Julien},
title = {Fermi LAT Third Pulsar Catalog (3PC)},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/fermi-3pc-gamma-ray-pulsars},
note = {Based on Smith et al. (2023), NASA HEASARC fermilpsc table}
}
```

## License

[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)

license: CC-BY-4.0
pretty_name: "费米LAT第三版脉冲星目录（3PC）"
language:
- en
description: "由费米大视场望远镜（Fermi Large Area Telescope）探测到的伽马射线脉冲星，包含3PC目录中的自转参数、流量与光谱特性"
task_categories:
- tabular-classification
tags:
- 太空
- 开放数据
- 表格数据
- parquet
- 费米
- NASA
- 脉冲星
- 伽马射线
- 高能
- 天文学
size_categories:
- n<1000
configs:
- config_name: default
data_files:
- split: train
path: data/fermi-3pc.parquet
default: true

# 费米LAT第三版脉冲星目录（3PC）

<div align="center">
<img src="banner.jpg" alt="X射线、光学与红外波段的仙后座A超新星遗迹" width="400">
<p><em>致谢：NASA/JPL-Caltech/STScI/CXC/SAO</em></p>
</div>

*本数据集隶属于Hugging Face平台上的[天文学数据集合集](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743)与[物理学数据集合集](https://huggingface.co/collections/juliensimon/physics-datasets-681b79c9a7e113e34e4467f4)。*


本完整目录收录了**7197颗**由[费米大视场望远镜（Fermi Large Area Telescope, LAT）](https://fermi.gsfc.nasa.gov/ssc/)探测到的伽马射线脉冲星，数据源自NASA高能天体物理科学档案研究中心（High Energy Astrophysics Science Archive Research Center, HEASARC）。

## 数据集描述

脉冲星是快速自转、强磁化的中子星，会喷射出电磁辐射束。当这些辐射束扫过地球时，就会产生周期性脉冲信号，可在从射电到伽马射线的全波段被观测到。**费米LAT第三版脉冲星目录（3PC）**是对费米大视场望远镜探测到的GeV能段伽马射线脉冲星的权威普查，该望远镜是迄今为止灵敏度最高的伽马射线巡天设备。

伽马射线脉冲星可分为两大类：
- **毫秒脉冲星（Millisecond Pulsars, MSPs）**：旧中子星通过吸积伴星物质自转加速至1-30毫秒周期，表面磁场较弱（~10^8-10^9 G），但自转减速光度极高。其中许多脉冲星是通过伽马射线脉冲搜索首次发现的，此前曾被射电巡天遗漏。
- **年轻脉冲星**：形成时间较短的中子星（特征年龄小于约10万年），磁场较强（~10^12 G），周期为30毫秒至数秒。包括蟹状星云脉冲星、船帆座脉冲星等著名天体。

费米LAT特别适合脉冲星研究，因为伽马射线可以直接探测磁层的辐射区域。与射电辐射（源自磁极附近的窄锥）不同，伽马射线辐射来自外磁层或电流片内的粒子加速过程，可为脉冲星辐射几何与等离子体物理研究提供其他波段无法获取的约束条件。

3PC目录包含每颗探测到的脉冲星的自转参数（周期、周期导数）、衍生物理量（自转减速光度、特征年龄、表面磁场强度）、光谱特性（光谱指数、截断能量）以及流量测量值。

## 数据结构

| 列名 | 数据类型 | 描述 |
|--------|------|-------------|
| `__row` | float | 行号 |
| `name` | string | 脉冲星名称（例如J0030+0451） |
| `data_release` | float | 数据发布版本 |
| `ra` | float | 赤经（度，J2000坐标系） |
| `dec` | float | 赤纬（度，J2000坐标系） |
| `lii` | float | 银经（度） |
| `bii` | float | 银纬（度） |
| `semi_major_axis_68` | float | 68%置信度半长轴 |
| `semi_minor_axis_68` | float | 68%置信度半短轴 |
| `position_angle_68` | float | 68%置信度位置角 |
| `semi_major_axis_95` | float | 95%置信度半长轴 |
| `semi_minor_axis_95` | float | 95%置信度半短轴 |
| `position_angle_95` | float | 95%置信度位置角 |
| `detection_significance` | float | 探测显著性 |
| `pivot_energy` | float | 枢轴能量 |
| `flux_1_100_gev` | float | 1-100 GeV流量 |
| `flux_1_100_gev_error` | float | 1-100 GeV流量误差 |
| `energy_flux` | float | 能量流量 |
| `energy_flux_error` | float | 能量流量误差 |
| `pl_flux_density` | float | 幂律流量密度 |
| `pl_flux_density_error` | float | 幂律流量密度误差 |
| `pl_index` | float | 幂律指数 |
| `pl_index_error` | float | 幂律指数误差 |
| `lp_flux_density` | float | 对数抛物线流量密度 |
| `lp_flux_density_error` | float | 对数抛物线流量密度误差 |
| `lp_index` | float | 对数抛物线指数 |
| `lp_index_error` | float | 对数抛物线指数误差 |
| `lp_beta` | float | 对数抛物线β参数 |
| `lp_beta_error` | float | 对数抛物线β参数误差 |
| `lp_curve_significance` | float | 对数抛物线拟合显著性 |
| `lp_epeak` | float | 对数抛物线截断能量 |
| `lp_epeak_error` | float | 对数抛物线截断能量误差 |
| `plec_flux_density` | float | 幂律截断流量密度 |
| `plec_flux_density_error` | float | 幂律截断流量密度误差 |
| `plec_index_s` | float | 幂律指数S |
| `plec_index_s_error` | float | 幂律指数S误差 |
| `plec_exp_factor_s` | float | 幂律截断指数因子S |
| `plec_exp_factor_s_error` | float | 幂律截断指数因子S误差 |
| `plec_exp_index` | float | 幂律截断指数 |
| `plec_curve_significance` | float | 幂律截断拟合显著性 |
| `plec_epeak` | float | 幂律截断能量 |
| `plec_epeak_error` | float | 幂律截断能量误差 |
| `npred` | float | 预测计数 |
| `variability_index` | float | 变率指数 |
| `frac_variability` | float | 变率分数 |
| `frac_variability_error` | float | 变率分数误差 |
| `significance_peak` | float | 峰值显著性 |
| `flux_peak` | float | 峰值流量 |
| `flux_peak_error` | float | 峰值流量误差 |
| `time_peak` | float | 峰值时间 |
| `time_peak_interval` | float | 峰值时间间隔 |
| `assoc_name` | string | 关联源名称 |
| `assoc_prob_bay` | float | 贝叶斯关联概率 |
| `assoc_prob_lr` | float | 似然比关联概率 |
| `assoc_ra` | float | 关联源赤经 |
| `assoc_dec` | float | 关联源赤纬 |
| `assoc_error_radius` | float | 关联源误差半径 |
| `analysis_flags` | float | 分析标记 |
| `__x_ra_dec` | float | 赤道坐标系X分量 |
| `__y_ra_dec` | float | 赤道坐标系Y分量 |
| `__z_ra_dec` | float | 赤道坐标系Z分量 |

## 快速统计
- **7197颗**伽马射线脉冲星
- 空值过滤后保留**61列**

## 使用方法
python
from datasets import load_dataset

ds = load_dataset("juliensimon/fermi-3pc-gamma-ray-pulsars", split="train")
df = ds.to_pandas()

# 概览
print(f"{len(df):,} gamma-ray pulsars")
print(df.describe())

## 数据来源
所有数据源自NASA高能天体物理科学档案研究中心（HEASARC）托管的[费米LAT脉冲星目录（fermilpsc）](https://heasarc.gsfc.nasa.gov/W3Browse/fermi/fermilpsc.html)，通过TAP协议获取。

本数据集基于：Smith, D.A.等人（2023）的《费米大视场望远镜第三版伽马射线脉冲星目录》，发表于*《天体物理学杂志》*，958卷，191页。[arXiv:2307.11132](https://arxiv.org/abs/2307.11132)

## 更新计划
静态数据集。3PC目录为固定出版的成果，仅当HEASARC更新其数据表时才需重新生成。

## 相关数据集
- [pulsar-catalog](https://huggingface.co/datasets/juliensimon/pulsar-catalog) — ATNF脉冲星目录（射电+多波段）
- [fermi-4fgl-dr4](https://huggingface.co/datasets/juliensimon/fermi-4fgl-dr4) — 费米LAT 4FGL-DR4源目录
- [fermi-3fhl-hard-gamma-ray](https://huggingface.co/datasets/juliensimon/fermi-3fhl-hard-gamma-ray) — 费米LAT 3FHL硬伽马射线源目录
- [fermi-4lac-agn-catalog](https://huggingface.co/datasets/juliensimon/fermi-4lac-agn-catalog) — 费米LAT活动星系核目录

## 代码仓库
源代码：[juliensimon/space-datasets](https://github.com/juliensimon/space-datasets)

## 支持与反馈
如果您觉得本数据集有用，请前往[数据集页面](https://huggingface.co/datasets/juliensimon/fermi-3pc-gamma-ray-pulsars)为其点赞❤️，并在社区标签页分享您的反馈！也欢迎为[space-datasets](https://github.com/juliensimon/space-datasets)仓库点亮⭐️。

## 引用格式
bibtex
@dataset{fermi_3pc_gamma_ray_pulsars,
author = {Simon, Julien},
title = {Fermi LAT Third Pulsar Catalog (3PC)},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/fermi-3pc-gamma-ray-pulsars},
note = {Based on Smith et al. (2023), NASA HEASARC fermilpsc table}
}

## 许可证
[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)