🔭 astrophysics

Variability and stellar pulsation incidence in Am/Fm stars using TESS and Gaia data

Using TESS and Gaia data to analyze 1,276 Am/Fm stars from the Renson catalogue, this study reveals that 49% of the sample exhibits variability, with pulsating stars (including $\delta$ Scuti, $\gamma$ Doradus, and hybrid types) predominantly located near the red edge of the classical instability strip.

Original authors: Oliver Durfeldt-Pedros, Victoria Antoci, Barry Smalley, Simon Murphy, Natalia Posilek, Ewa Niemczura

Published 2026-06-11

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CC BY 4.0

Original authors: Oliver Durfeldt-Pedros, Victoria Antoci, Barry Smalley, Simon Murphy, Natalia Posilek, Ewa Niemczura

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the universe as a giant, bustling orchestra. Most stars are like steady drummers, keeping a constant beat. But some stars, specifically a group called Am and Fm stars, are the soloists who sometimes hum, sometimes wobble, and sometimes stop singing altogether. These stars are "chemically peculiar," meaning their atmospheres are like a soup where some ingredients (like calcium) have settled to the bottom, while others (like zinc and strontium) have floated to the top. This happens because they spin very slowly, allowing gravity and light to sort their atoms like a cosmic sifter.

This paper is a massive census of these specific stars, using two powerful "eyes" in the sky: the TESS satellite (which takes bright, fast photos of stars to catch them wiggling) and the Gaia mission (which acts like a cosmic GPS to tell us exactly how far away and how bright these stars are).

Here is what the researchers found, broken down simply:

1. The Great Star Census

The team looked at 1,276 of these peculiar stars from a famous list called the Renson catalogue. They wanted to answer a simple question: How many of these stars actually sing (pulsate), and how many just sit there quietly?

The Quiet Majority (51%): Just over half of the stars (649 of them) were completely silent. They didn't show any signs of pulsing. They are the "constant" stars of the group.
The Singers (25%): About a quarter of the stars (318 of them) were found to be pulsating. These are the ones vibrating like a plucked guitar string.
The Troublemakers (24%): The rest were either part of a binary system (two stars dancing around each other, sometimes blocking light like an eclipse) or had their light dimming and brightening because they were spinning and had "starspots" (like sunspots) on their surface.

2. The Types of "Songs"

Among the stars that were singing, the researchers figured out what kind of song they were singing:

The High-Pitched Singers (δ Scuti): 54% of the pulsating stars were vibrating in high-frequency modes. Think of these as the high notes.
The Low-Pitched Singers (γ Doradus): 10% were vibrating in low-frequency modes. These are the deep bass notes.
The Mixed Singers (Hybrids): 36% were doing both! They were singing high and low notes at the same time. This is special because it lets astronomers listen to the star's core and its outer skin simultaneously.

3. Where Do They Sing?

The researchers plotted these stars on a giant map called the Hertzsprung-Russell (HR) diagram, which is basically a "stellar family tree" showing how hot and bright stars are.

The Red Edge Rule: They found that the singing stars mostly hang out near the "red edge" of a specific zone called the Instability Strip. Imagine this strip as a "danger zone" where stars naturally want to wobble. The Am/Fm stars seem to prefer the cooler, redder side of this zone.
The Mystery Gap: The researchers noticed something strange. There seemed to be two "ridges" where stars loved to vibrate, but a "gap" in between where very few stars were singing. It's like finding that people love to dance in two specific corners of a room, but no one dances in the middle. The paper suggests this might mean there are two different physical mechanisms (one involving heat, one involving turbulence) pushing the stars to sing, but they need more data to be sure.

4. The "Chemical" Connection

The paper also looked at how "peculiar" the chemistry of these stars was. They found a funny trend: The less chemically weird a star was, the more likely it was to sing.

Stars with very strong chemical differences (very "metal-rich" or "metal-poor" in specific ways) were often silent.
Stars that were only slightly peculiar were the ones most likely to be pulsating.
It's as if the chemical sorting process (atomic diffusion) acts like a mute button for the star's vibration. The more the atoms sort themselves out, the quieter the star becomes.

5. Why This Matters

For a long time, scientists thought that because these Am/Fm stars had their helium atoms sorted out and moved away from the surface, they shouldn't be able to vibrate at all. It was like expecting a drum with no skin to make a sound.

But this paper proves they do make sound. This challenges our understanding of how stars work. The researchers suggest that maybe "turbulent pressure" (like the churning of boiling water) is helping to keep these stars vibrating, even when the usual "heat engine" (the κ-mechanism) is turned down by the chemical sorting.

The Bottom Line

This paper is a massive "roll call" of 1,276 weird stars. It tells us that while most of them are quiet, a significant chunk (about 1 in 5) are actually pulsating stars. By mapping out exactly where they sing and how they sing, the authors have provided a new roadmap for understanding how stars mix their ingredients and how they vibrate. They have also released a public catalog (like a phonebook) so other astronomers can pick out the most interesting "singers" to study in even greater detail.

Technical Summary: Variability and Stellar Pulsation Incidence in Am/Fm Stars Using TESS and Gaia Data

Problem Statement
Am and Fm stars are chemically peculiar intermediate-mass stars (1.4–2.6 $M_{\odot}$ ) characterized by over-abundances of metals (e.g., Zn, Sr, Y, Zr, Ba) and under-abundances of Ca and Sc. These peculiarities arise from atomic diffusion in radiative envelopes, a process facilitated by slow rotation rates ( $<120$ km s $^{-1}$ ). The depletion of Helium from the outer envelope was historically expected to impede the $\kappa$ -mechanism in the He II ionisation layer, which drives $\delta$ Scuti pulsations. Consequently, stellar oscillations were not anticipated in these stars. However, recent detections have challenged this view, suggesting alternative excitation mechanisms, such as turbulent pressure or the "edge-bump" mechanism. Despite these detections, the incidence of pulsation, the specific pulsation modes (p-modes, g-modes, or hybrids), and the distribution of these stars within the instability strip remain poorly constrained due to a lack of large, homogeneous datasets.

Methodology
The authors conducted an ensemble analysis of 1,276 Am/Fm and $\rho$ Puppis stars selected from the Renson catalogue of chemically peculiar stars. The study integrates data from two primary sources:

TESS Photometry: 2-minute cadence Single Aperture Photometry (SAP) light curves were retrieved from the Mikulski Archive for Space Telescopes (MAST) across 58 sectors. The data were processed using the Lightkurve Python package.
Gaia Astrometry and Spectroscopy: Stellar parameters (effective temperature $T_{\text{eff}}$ , surface gravity $\log g$ , luminosity) were derived from Gaia Data Release 3 (DR3). The authors specifically utilized the GSP-Phot (photometric) and FLAME modules, validating their reliability against probabilistic distance estimates from Bailer-Jones et al. (2021) and external catalogues (APOGEE, GALAH, etc.).

Variability Classification and Frequency Analysis

Variability Determination: Amplitude spectra were generated using Lomb-Scargle periodograms. A two-stage filtering process was employed: an initial signal-to-noise (S/N) threshold of 4 was applied, followed by a stricter S/N $\ge$ 10 threshold to distinguish true pulsations from noise and data gaps. Visual inspection of light curves and spectra was performed to classify stars into: (1) Pulsating stars, (2) Eclipsing binaries, (3) Modulated light curves (rotational modulation/ellipsoidal variation), and (4) Constant stars.
Contamination Control: Potential flux contamination from neighboring stars was assessed using the TESS Asteroseismic Science Operations Centre (TASOC) database. 18 contaminated cases were identified and removed.
Frequency Extraction: The ECHO (Extraction of CoHerent Oscillations) pipeline was used for iterative pre-whitening. A strict false-positive rate ( $p=0.0027$ ) was applied, and linear combination frequencies were identified and removed to avoid overestimating excited modes.
Mode Identification: Due to the short time baselines for many targets (1–2 sectors), the analysis focused primarily on p-modes ( $\delta$ Scuti) rather than low-frequency g-modes ( $\gamma$ Doradus). Radial mode excitation was estimated using the pulsation constant $Q$ (Fitch 1981), calculated via stellar parameters from Gaia. The number of excited radial orders was mapped onto the Hertzsprung-Russell (HR) diagram.

Key Results

Sample Statistics: Of the 1,276 analyzed stars:
- 51% (649 stars) are constant (non-variable).
- 25% (318 stars) are pulsating (including Am/Fm and $\rho$ Puppis stars). Specifically, 20% (261 stars) are exclusively Am/Fm pulsators.
- 17% (210 stars) exhibit variability indicative of binarity or rotational modulation.
- 7% (93 stars) are confirmed eclipsing binaries.
Pulsation Types: Among the pulsating subset:
- 54% (172 stars) are $\delta$ Scuti type (p-modes).
- 10% (32 stars) are $\gamma$ Doradus type (g-modes).
- 36% (114 stars) are hybrids (p- and g-modes).
HR Diagram Distribution: Pulsating Am/Fm stars are predominantly located near the Zero-Age Main Sequence (ZAMS) and cluster near the red edge of the classical instability strip. This distribution contrasts with the general population of A-type pulsators, which are more evenly distributed or found near the blue edge.
Radial Order Excitation: The study identified a non-uniform distribution of excited radial orders. High numbers of excited orders are found near the ZAMS and along two distinct ridges in the HR diagram, separated by a "gap" where fewer orders are excited.
Metallicism Correlation: An analysis of the metallicism index ( $\Delta = m - k$ ) suggests a downward trend in pulsation incidence as chemical peculiarity increases (higher $\Delta$ ). Pulsation incidence appears higher in stars with lower metallicism (less pronounced peculiarities).

Significance and Claims
The paper claims to provide the first large-scale, homogeneous census of variability in Am/Fm stars using TESS and Gaia data. The primary significance lies in:

Establishing Incidence: Quantifying that approximately 20% of Am/Fm stars are pulsators, challenging the notion that atomic diffusion completely suppresses pulsation.
Refining the Instability Strip: Demonstrating that Am/Fm pulsators occupy a specific region near the red edge of the instability strip, consistent with theoretical models where Helium depletion narrows the strip and shifts the blue edge to cooler temperatures.
Data Resource: The authors have released catalogues and summary tables (available on GitHub and CDS) containing light curves, amplitude spectra, and derived parameters for 1,276 stars, serving as a foundational resource for future asteroseismic studies.
Mechanism Constraints: The observed distribution and the presence of high-order radial excitations suggest that current models (e.g., turbulent pressure vs. $\kappa$ -mechanism) require further refinement, particularly regarding the role of Helium depletion and the depth of chemical peculiarities.

The authors maintain a modest tone regarding the "gap" in radial order excitation and the specific driving mechanisms, noting that the limited time series for g-mode resolution and the uncertainties in Gaia DR3 surface gravities necessitate future detailed modeling and spectroscopic follow-up to fully resolve the excitation physics.