juliensimon/galactic-novae-schaefer

Galactic Classical Novae (Schaefer 2022)

Credit: NASA/ESA/Hubble

Part of a dataset collection on Hugging Face.

Dataset description

Schaefer's compendium of Galactic classical novae — VizieR J/MNRAS/517/6150 from Schaefer, B.E. (2022), MNRAS 517, 6150, 'The distances to Galactic classical novae'.

Classical novae are thermonuclear runaways on the surface of a white dwarf accreting hydrogen from a close binary companion, producing brightening of 8-15 magnitudes in days and a slow photometric decline lasting weeks to months. They are central to several open questions in astrophysics: as candidate progenitors of Type Ia supernovae, as contributors to the chemical enrichment of the interstellar medium with CNO-cycle isotopes, and as testbeds for binary-star evolution and degenerate-matter physics. Schaefer's paper standardized the literature compilation of two key observables for every recorded Galactic nova: V_peak (peak apparent visual magnitude at outburst) and the interstellar reddening E(B-V) along the line of sight, then combined them with multiple independent distance indicators to derive a homogeneous peak-distance-modulus catalog.

Each row in this dataset records one Galactic nova with its variable-star designation, J2000 sky position from SIMBAD, peak V magnitude and reddening from Schaefer's literature collation, and the corresponding peak distance modulus. Use this dataset alongside juliensimon/cataclysmic-variable-catalog for the broader CV parent population, juliensimon/aavso-vsx-variable-stars for ongoing time-domain photometry, juliensimon/open-supernova-catalog for the closely related thermonuclear-explosion population, and juliensimon/hot-subdwarf-stars for an alternative end state of binary-stripped stellar evolution.

This dataset is suitable for tabular classification tasks.

Schema

Column	Type	Description	Sample	Null %
name	str	Variable-star designation of the nova (Bayer-Argelander convention, e.g. 'OS And', 'CI Aql', 'V603 Aql'); resolves to SIMBAD	OS And	0.0%
vpeak_limit	str	Limit flag for the peak V magnitude: '<' = fainter than this value (upper limit), '>' = brighter than this value (lower limit), blank = direct measurement	<	69.9%
v_peak_magnitude	float64	Peak apparent visual magnitude at outburst (mag); smaller values are brighter; classical novae typically peak between V = 2 and V = 12 depending on distance and reddening	6.5	0.2%
v_peak_magnitude_uncertainty	float64	Uncertainty on V_peak (mag); reflects spread across published photometry compilations	0.1	0.2%
ebv	float64	Interstellar reddening E(B-V) (mag); larger values indicate heavier dust absorption; the V-band extinction is roughly A_V = 3.1 x E(B-V)	0.15	0.0%
ebv_uncertainty	float64	Uncertainty on E(B-V) (mag)	0.05	0.0%
dmpeak_limit	str	Limit flag on the peak distance modulus, same convention as vpeak_limit	<	69.9%
distance_modulus_peak	float64	Apparent distance modulus at peak (mag); equal to V_peak - M_peak - A_V; used to derive heliocentric distance via d = 10^((mu+5)/5) parsecs after reddening correction	13.04	0.2%
distance_modulus_peak_uncertainty	float64	Uncertainty on the peak distance modulus (mag)	1.41	0.2%
simbad_name	str	Canonical SIMBAD identifier for cross-matching (usually identical to name but occasionally a longer alias)	OS And	0.0%
ra	float64	Right ascension (degrees, J2000); transcribed from SIMBAD via VizieR	348.024	0.0%
dec	float64	Declination (degrees, J2000); transcribed from SIMBAD via VizieR	47.47214	0.0%

Quick stats

• 402 Galactic classical novae with literature-compiled photometry and reddening
• Homogeneous peak-magnitude catalog spanning over a century of recorded outbursts
• Peak apparent magnitudes (V_peak) span -0.5 to 17.5 mag
• Interstellar reddening E(B-V) ranges from 0.02 to 4.00 mag — many novae lie behind heavy Galactic dust
• Distance moduli at peak: 5.9 to 20.9 mag (heliocentric distances ~0.3 to ~30 kpc)

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/galactic-novae-schaefer", split="train")
df = ds.to_pandas()

from datasets import load_dataset
import matplotlib.pyplot as plt
import numpy as np

df = load_dataset("juliensimon/galactic-novae-schaefer", split="train").to_pandas()

# Reddening vs distance modulus — heavy dust traces Galactic plane novae
mask = df["ebv"].notna() & df["distance_modulus_peak"].notna()
fig, ax = plt.subplots(figsize=(8, 6))
ax.scatter(df.loc[mask, "distance_modulus_peak"], df.loc[mask, "ebv"],
           s=30, alpha=0.7)
ax.set_xlabel("Distance modulus at peak (mag)")
ax.set_ylabel("E(B-V) reddening (mag)")
ax.set_title("Galactic novae: reddening grows with distance through the disk")
plt.tight_layout()
plt.show()

# Derive heliocentric distance from distance modulus, correcting for extinction
dist_pc = 10 ** ((df["distance_modulus_peak"] - 3.1 * df["ebv"] + 5) / 5)
print(f"Median heliocentric distance: {np.nanmedian(dist_pc) / 1000:.1f} kpc")

Data source

https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/517/6150

Related datasets

• juliensimon/cataclysmic-variable-catalog

• juliensimon/aavso-vsx-variable-stars

• juliensimon/open-supernova-catalog

• juliensimon/hot-subdwarf-stars

• juliensimon/gaia-dr3-white-dwarfs

• juliensimon/pantheon-plus-sne-ia

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About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

@dataset{galactic_novae_schaefer,
  title = {Galactic Classical Novae (Schaefer 2022)},
  author = {juliensimon},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/galactic-novae-schaefer},
  publisher = {Hugging Face}
}

License

CC-BY-4.0