Datasets:
license: cc-by-4.0
pretty_name: Ritter & Kolb Cataclysmic Variable Catalog
language:
- en
description: >-
Catalog of cataclysmic variables (CVs) from the Ritter & Kolb catalog, sourced
from NASA HEASARC. CVs are binary star systems where a white dwarf accretes
matter from a companion star. Cataclysmic va
task_categories:
- tabular-classification
tags:
- space
- cataclysmic-variable
- white-dwarf
- nova
- dwarf-nova
- binary-star
- astronomy
- accretion
- open-data
- tabular-data
- parquet
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/cataclysmic_variables.parquet
default: true
Ritter & Kolb Cataclysmic Variable Catalog
Credit: NASA/ESA/Hubble
Part of a dataset collection on Hugging Face.
Dataset description
Catalog of cataclysmic variables (CVs) from the Ritter & Kolb catalog, sourced from NASA HEASARC. CVs are binary star systems where a white dwarf accretes matter from a companion star.
Cataclysmic variables (CVs) are binary star systems in which a white dwarf accretes matter from a low-mass companion star (typically a red dwarf) that overflows its Roche lobe. The infalling material forms an accretion disk around the white dwarf, producing dramatic brightness variations across timescales from seconds to decades. CVs are classified into several subtypes based on their outburst behavior and magnetic field strength:
Dwarf novae (DN) exhibit quasi-periodic outbursts of 2-8 magnitudes caused by thermal instabilities in the accretion disk. Classical novae (N) undergo thermonuclear explosions on the white dwarf surface when accreted hydrogen reaches a critical mass, brightening by 6-19 magnitudes. Polars (AM Her) are strongly magnetic white dwarfs (B ~ 10-230 MG) where the magnetic field channels accretion directly onto the poles. Intermediate polars (DQ Her) are moderately magnetic white dwarfs with a truncated accretion disk. Nova-like variables (NL) are high mass-transfer rate systems in a persistent bright state.
The Ritter & Kolb catalog is the standard reference catalog for CV research, containing orbital periods, spectral types, magnitudes, and classifications for the known CV population. This dataset is essential for population studies, period distribution analysis, and understanding the evolution of compact binary systems.
This dataset is suitable for tabular classification tasks.
Schema
| Column | Type | Description | Sample | Null % |
|---|---|---|---|---|
name |
str | Standard CV designation (e.g. 'SS Cyg', 'AM Her'); CVs are close binaries where a white dwarf accretes matter from a donor star | 0035-7230 | 0.0% |
ra |
float64 | Right ascension ICRS J2000.0 in degrees (0-360) | 9.3325 | 0.0% |
dec |
float64 | Declination ICRS J2000.0 in degrees (-90 to +90) | -72.23722222 | 0.0% |
lii |
float64 | Galactic longitude in degrees (0-360, increasing toward Galactic center direction) | 304.44884775 | 0.0% |
bii |
float64 | Galactic latitude in degrees (-90 to +90; most CVs within |b| < 30 deg) | -44.84945298 | 0.0% |
type2 |
str | Secondary classification flag from Ritter & Kolb (qualifier or additional subtype) | EG | 18.7% |
mag1 |
float64 | V-band magnitude at outburst maximum (brightest state); lower value = brighter | 20.2 | 2.1% |
mag2 |
float64 | V-band magnitude at quiescence (faint state); difference mag2-mag1 = outburst amplitude | 20.6 | 58.4% |
class |
int64 | CV classification code from Ritter & Kolb catalog (e.g. DN, NL, N, RN, AM, IP) | 1600 | 0.0% |
cv_subtype |
str | Derived CV subtype: 'dwarf_nova' (DN, recurring outbursts), 'polar' (AM Her, strongly magnetic), 'intermediate_polar' (DQ Her/IP), 'nova_like' (NL, steady high accretion), 'classical_nova' (N/RN, thermonuclear runaway), or 'other' | other | 0.0% |
Quick stats
- 1,166 cataclysmic variables
- 0 systems with measured orbital period (median 0.0 h)
- CV subtypes:
- 1,166 other
Usage
from datasets import load_dataset
ds = load_dataset("juliensimon/cataclysmic-variable-catalog", split="train")
df = ds.to_pandas()
from datasets import load_dataset
ds = load_dataset("juliensimon/cataclysmic-variable-catalog", split="train")
df = ds.to_pandas()
# Filter by CV subtype
dwarf_novae = df[df["cv_subtype"] == "dwarf_nova"]
polars = df[df["cv_subtype"] == "polar"]
print(f"{len(dwarf_novae):,} dwarf novae, {len(polars):,} polars")
# Period distribution showing the famous period gap
import matplotlib.pyplot as plt
periods = df["porb"].dropna()
periods[periods > 0].hist(bins=50)
plt.xlabel("Orbital period (hours)")
plt.ylabel("Count")
plt.title("CV Orbital Period Distribution")
plt.axvspan(2.0, 3.0, alpha=0.2, color="red", label="Period gap")
plt.legend()
plt.show()
Data source
https://heasarc.gsfc.nasa.gov/W3Browse/all/rittercv.html
Related datasets
If you find this dataset useful, please consider giving it a like on Hugging Face. It helps others discover it.
About the author
Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.
Citation
@dataset{cataclysmic_variable_catalog,
title = {Ritter & Kolb Cataclysmic Variable Catalog},
author = {juliensimon},
year = {2026},
url = {https://huggingface.co/datasets/juliensimon/cataclysmic-variable-catalog},
publisher = {Hugging Face}
}