J/AJ/170/222 MK spectral types of MaStar stars using NutMaat (El-Kholy+, 2025)
NutMaat: A Python package for stellar spectral classification on the MK system.
El-Kholy R.I., Hayman Z.M.
<Astron. J., 170, 222 (2025)>
=2025AJ....170..222E 2025AJ....170..222E
ADC_Keywords: MK spectral classification; Models; Photometry, ugriz; Surveys;
Galaxies, spectra; Photometry, SDSS
Keywords: Catalogs ; Chemically peculiar stars ;
Fundamental parameters of stars ; Spectroscopy ;
Stellar classification ; Stellar types ; Open source software
Abstract:
Stellar spectral classification according to the Morgan-Keenan (MK)
system remains fundamental to astrophysical studies, yet modern
surveys require automated, scalable tools. We present NutMaat, an
open-source Python-based package inspired by MKCLASS, designed to
automate MK classification while addressing scalability and usability
limitations. It employs modern computational tools for batch
processing and offers a modular architecture that enables efficient,
platform-independent analysis of large spectral data sets. It also
includes modules for detecting classical chemically peculiar stars,
such as Am, Ap, and λ Boo types, using internal consistency
checks between different line diagnostics. Tested on the CFLIB and
MILES libraries, NutMaat achieved spectral and luminosity
classification accuracies comparable to MKCLASS, with minimal
systematic offsets and a robust performance down to a signal-to-noise
ratio ≤10. NutMaat successfully identified chemically peculiar
stars, tested on LAMOST DR7 ACV variables, and processed the SDSS-IV
MaStar library-which lacks native MK classifications-to produce a
stellar catalog, demonstrating survey readiness. Future development of
NutMaat will focus on extending wavelength coverage beyond the
3800-5600Å range, computational acceleration via Cython, and
refining peculiarity classification. Beyond its technical design,
NutMaat can provide consistent, MK-standard classification across
large-scale spectroscopic surveys, facilitating reliable stellar
population analyses, identification of rare objects, and the
construction of high-quality spectral catalogs essential for galactic
archaeology and stellar evolution studies. As an open-source tool,
NutMaat bridges traditional MK methods with modern data workflows,
offering a scalable solution for current and future spectroscopic
surveys.
Description:
To demonstrate the applicability of NutMaat to modern, large-scale
spectroscopic data sets, we applied the tool to the spectra of the
MaStar library (Yan+2019, J/ApJ/883/175) from SDSS DR17
(Abdurro'uf+2022, III/286). MaStar is a comprehensive empirical
stellar library constructed using the same Baryon Oscillation
Spectroscopic Survey (BOSS) spectrographs as the MaNGA galaxy survey
(DR15; Wake+2017, J/AJ/154/86), with coverage over the 3622-10354Å
wavelength range at R∼1800. We specifically used MaStar visit spectra
flagged as high-quality, those without visual reduction issues, poor
calibration, or low S/N, as documented for MaStar's first release in
Yan+2019. However, in this work, we use the last release of MaStar,
available at http://www.sdss4.org/dr17/mastar/, which will be
described in Yan+, in prep.
SDSS-IV has three major survey components: APOGEE-2 (III/286),
MaNGA (DR15, J/AJ/154/86), and the Extended Baryon Oscillation
Spectroscopic Survey (eBOSS). APOGEE-2 is a medium-resolution infrared
H-band spectroscopy survey of stars in the Milky Way
(Majewski+ 2016AN....337..863M 2016AN....337..863M). It has a northern component executed
with the 2.5m Sloan Foundation Telescope at Apache Point Observatory
(APOGEE-2N), and a southern component executed with the 2.5m du Pont
Telescope at Las Campanas Observatory (APOGEE-2S). MaNGA is an
integral field spectroscopy survey of 10000 nearby galaxies
(Bundy+ 2015ApJ...798....7B 2015ApJ...798....7B ; Law+ 2015AJ....150...19L 2015AJ....150...19L ;
Yan+ 2016AJ....152..197Y 2016AJ....152..197Y and Wake+ 2017, J/AJ/154/86). eBOSS is a
spectroscopic survey of galaxies and quasars in the more distant
universe (Dawson+ 2016AJ....151...44D 2016AJ....151...44D). All these surveys use a
fiber-plug-plate system to conduct observations.
File Summary:
--------------------------------------------------------------------------------
FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
table4.dat 73 59266 MaStar library classification catalog using NutMaat
--------------------------------------------------------------------------------
See also:
B/gcvs : General Catalogue of Variable Stars (Samus+, 2007-2017)
III/183 : Atlas of 837.5-877nm spectral region I. (Andrillat+ 1995)
III/217 : Atlas of 840-880nm spectral region (Andrillat+ 1995-1997)
III/286 : APOGEE-2 DR17 final allStar catalog (Abdurro'uf+, 2022)
V/154 : Sloan Digital Sky Surveys (SDSS) DR16 (Ahumada+, 2020)
V/156 : LAMOST DR7 catalogs (Luo+, 2019)
V/162 : LAMOST DR11 catalogs (Luo+, 2026)
VII/260 : The SDSS-DR7 quasar catalog (Schneider+, 2010)
J/ApJS/107/281 : Atlas of hot, luminous stars at 2 microns (Hanson+ 1996)
J/ApJ/508/397 : H-band Spectral Standards (Meyer+ 1998)
J/ApJ/535/325 : Spectra of normal stars in the J-band (Wallace+ 2000)
J/AJ/121/2148 : Precise spectral types for 372 A, F & G stars (Gray+, 2001)
J/AJ/126/2048 : NStars project: the Northern Sample. I. (Gray+, 2003)
J/ApJS/152/251 : Indo-US library of coude feed stellar spectra (Valdes+, 2004)
J/MNRAS/371/703 : MILES library of empirical spectra (Sanchez-Blazquez+, 2006)
J/AJ/137/3245 : STARMIND MK standard's database (Manteiga+, 2009)
J/ApJS/230/16 : O5 to L3 empirical stellar spectra from SDSS (Kesseli+, 2017)
J/AJ/154/86 : MaNGA catalog, DR15 (Wake+, 2017)
J/ApJ/883/175 : 1st release of MaNGA Stellar Library (MaStar) (Yan+, 2019)
J/A+A/656/A125 : ACV variables in Zwicky Transient Facility (Faltova+, 2021)
J/ApJ/899/62 : Stellar parameters from 1st release of MaSTar (Chen+, 2020)
Byte-by-byte Description of file: table4.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 22 A22 --- MaNGAId ID of spectrum in the MaNGA Survey
24- 32 F9.5 deg RAdeg Right ascension (J2000)
34- 42 F9.5 deg DEdeg Declination (J2000)
44- 47 I4 --- SNR [3/1024] Signal-to-noise ratio
49- 58 A10 --- SpType Spectral type predicted by NutMaat
60- 64 A5 --- Qual Match quality flag estimated by NutMaat (1)
66- 73 E8.2 --- chi2 [7.29e-5/1380]? Chi-squared of match to
standard spectrum (2)
--------------------------------------------------------------------------------
Note (1): The thresholds are empirically calibrated; for example, χ2
values below 1e-4 are always rated "excel," while values above 1e-1
(late types) or 5e-2 (early types) are flagged as "poor." Flag as follows:
excel = 17 occurrences
fair = 957 occurrences
good = 29287 occurrences
poor = 654 occurrences
vgood = 24370 occurrences
Note (2): For interpretive purposes, the degrees of freedom are estimated to be
∼1700. An approximate reduced χ2 can thus be calculated as
χ2/1700.
--------------------------------------------------------------------------------
History:
From electronic version of the journal
License: CC-BY-4.0
(End) Prepared by [AAS], Robin Leichtnam [CDS] 21-Jul-2026