🔭 astrophysics

The JWST Resolved Stellar Populations Early Release Science Program. IX. The RR Lyrae Population in WLM with HST and JWST

This study utilizes overlapping HST and JWST observations of the WLM galaxy to demonstrate JWST's capability for identifying RR Lyrae stars and to calibrate a new near-infrared Period-Wesenheit-Metallicity relation, ultimately deriving a Gaia-consistent distance modulus of 24.85 mag while highlighting challenges in template fitting for short-baseline data.

Original authors: Catherine M. Slaughter, Evan D. Skillman, Alessandro Savino, Daniel R. Weisz, Meredith Durbin, Jay Anderson, Martha L. Boyer, Roger E. Cohen, Andrew A. Cole, Matteo Correnti, Andrew E. Dolphin, Marla

Published 2026-02-25

📖 6 min read🧠 Deep dive

CC BY 4.0

Original authors: Catherine M. Slaughter, Evan D. Skillman, Alessandro Savino, Daniel R. Weisz, Meredith Durbin, Jay Anderson, Martha L. Boyer, Roger E. Cohen, Andrew A. Cole, Matteo Correnti, Andrew E. Dolphin, Marla C. Geha, Mario Gennaro, Nitya Kallivayalil, Evan N. Kirby, Kristen B. W. McQuinn, Max J. B. Newman, Jack T. Warfield, Benjamin F. Williams

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

The Big Picture: A Cosmic Ruler Check-Up

Imagine you are trying to measure the distance to a lighthouse in the fog. You have a new, incredibly powerful pair of binoculars (the James Webb Space Telescope, or JWST) and an older, trusted pair (the Hubble Space Telescope, or HST).

The goal of this paper is to test out the new binoculars. Specifically, the team is looking at a small, nearby galaxy called WLM (which is like a tiny, isolated island of stars). They want to see if JWST can measure the distance to this galaxy just as well as Hubble, using a specific type of star called an RR Lyrae.

What is an RR Lyrae star?
Think of these stars as "cosmic lighthouses" or "standard candles." They pulse rhythmically, getting brighter and dimmer like a heartbeat. Astronomers know that if they measure how fast the heartbeat is (the period) and how bright it looks, they can calculate exactly how far away it is. It's like knowing a car's speed and how long it takes to pass you; you can figure out how far away it started.

The Challenge: The "Short-Baseline" Problem

The team faced a tricky situation. To measure the heartbeat of these stars perfectly, you usually need to watch them for a long time to see several full cycles.

Hubble's Approach: Hubble watched WLM over several days, taking pictures in short bursts. It was like watching a runner for a whole hour; you saw them run many laps, so you knew their speed perfectly.
JWST's Approach: JWST watched WLM for a much shorter time (about 15 hours total). It was like watching that same runner for only 10 minutes. You might see them run one lap, or maybe just half a lap.

The Problem: Because JWST's "watch time" was so short, it was hard to tell exactly how fast the stars were pulsing. It's like trying to guess the speed of a car by watching it for only 5 seconds; you might think it's going fast, or you might think it's slow, and you won't be very sure.

The Experiment: Comparing the Two

The researchers set up a clever experiment. They pointed both telescopes at the exact same patch of sky in WLM. This allowed them to compare the "old" data (Hubble) with the "new" data (JWST) for the same stars.

Here is what they found, broken down into three main discoveries:

1. Can JWST see the stars? (Yes, but with a catch)

The Analogy: Imagine trying to hear a drumbeat. In the blue light (Hubble), the drum is loud and clear. In the red/infrared light (JWST), the drum is much quieter.
The Result: JWST is incredibly sensitive and can see the stars, but because the "heartbeat" is quieter in infrared light, it's harder to spot the faintest pulses. However, they successfully identified over 100 of these stars with Hubble and found about 125 with JWST. They proved that JWST can find these cosmic lighthouses, even if the signal is a bit whisper-quiet.

2. The "Heartbeat" Measurement Struggle

The Analogy: Because JWST only watched for a short time, the computer software trying to calculate the speed of the heartbeat got confused. It's like trying to solve a puzzle when you only have half the pieces.
The Result: The team found that the standard computer methods used for Hubble didn't work well for JWST's short data. The software kept guessing the wrong speed for the stars.
The Fix: They had to get creative. They used the Hubble data (which had the correct speed) as a "cheat sheet" to help the JWST data. Once they forced the JWST data to use the correct speed, the measurements worked much better. They also discovered that if you just take the "middle" brightness of the star rather than the average, it gives a more accurate distance.

3. The Distance Result: A New, Slightly Closer Map

The Analogy: Imagine you have a map of the galaxy. Everyone agreed the galaxy was about 1 million light-years away. But when you use the new "Gaia" scale (a new, ultra-precise ruler based on our own galaxy's stars), the map changes slightly.
The Result:

Hubble Distance: Using the Hubble data and the new "Gaia" ruler, they calculated WLM is 0.93 million light-years away.
Comparison: This is slightly closer than previous measurements (which were around 0.98 million light-years).
Why the difference? It turns out the old measurements were using a slightly different "ruler" calibration. The new Hubble data, which is consistent with the Gaia scale, suggests the galaxy is a bit closer than we thought.

The "Burn-In" Mystery

While analyzing the JWST data, they noticed a weird glitch. Every time the telescope moved to a new spot to take a picture, the very first image was slightly dimmer than the rest.
The Analogy: It's like a camera sensor that gets "warmed up" by the first few flashes of light. The first few photos are a bit "burned in" before the sensor settles down.
The Conclusion: They found this effect was tiny (like a whisper) and didn't ruin their distance measurements, but it's something future astronomers need to keep in mind.

The Bottom Line

This paper is a "test drive" report for the James Webb Space Telescope.

Good News: JWST is amazing at finding these pulsating stars in distant galaxies. It can do the job Hubble did, but with a new kind of light.
The Catch: Because JWST observations are often shorter (to save money and time), the math to figure out the stars' speeds is harder. We need to develop new ways to analyze this "short-baseline" data.
The Legacy: This study created the first-ever calibration for using JWST to measure distances with these stars. It's like writing the first instruction manual for a new tool. Even though the tool is powerful, we now know exactly how to hold it so we don't drop the measurements.

In short: JWST can measure the universe's distances, but we have to be a little more clever with our math when we don't have a lot of time to watch the stars.

1. Problem Statement

The study addresses the challenges and opportunities of characterizing RR Lyrae variable stars using the James Webb Space Telescope (JWST) compared to the legacy Hubble Space Telescope (HST). While RR Lyrae stars are critical standard candles for measuring distances to nearby galaxies and tracing early star formation, observing them with JWST presents specific difficulties:

Reduced Amplitude: RR Lyrae pulsation amplitudes decrease significantly at longer (near-infrared) wavelengths, making variability harder to detect.
Observational Constraints: JWST's NIRCam instrument requires continuous observation of a single filter to minimize wear on the filter wheel, preventing the interleaved filter switching common in HST programs. This results in short time baselines (approx. 15 hours for WLM) relative to the pulsation periods of RR Lyrae stars (typically 0.2–1.0 days).
Data Processing: Standard JWST pipeline products do not retain individual integration data necessary for time-series analysis of non-time-series observations, requiring custom local pipeline processing.
Calibration Gap: There was no established Period-Wesenheit-Metallicity (PWZ) relation for JWST NIRCam filters, necessitating a calibration against HST data to utilize JWST for precise distance measurements.

2. Methodology

The authors utilized archival data from the WLM (Wolf-Lundmark-Melotte) dwarf irregular galaxy, which features overlapping fields observed by both HST/ACS and JWST/NIRCam.

Data Processing

HST: Used standard DOLPHOT photometry on F475W and F814W filters.
JWST: Developed a custom workflow to extract individual integration data (rateints) from the ERS-1334 program. They processed these through the Stage 2 imaging pipeline to create calibrated calints cubes, which were then split into "pseudo-cal" 2D images compatible with DOLPHOT.
Photometry: Applied strict quality cuts (SNR, sharpness, crowding) to generate catalogs for both instruments.

Variable Star Identification & Fitting

Candidate Selection: Identified variable candidates by comparing epoch-to-epoch photometry, requiring significant RMS scatter, high reduced $\chi^2$ , and periodicity metrics ( $\Theta$ ) derived from the Lafler-Kinman algorithm.
Periodicity Measurement: Employed a hybrid algorithm combining Lafler-Kinman (PDM) and Lomb-Scargle methods.
- Challenge: For JWST, the short baseline meant many sources had less than one full pulsation cycle. The standard PDM algorithm failed for long-period sources because it assigns equal power to periods longer than the observation duration.
- Solution: The authors tested combining light curves from different filters (F090W and F150W) into a single stream. An "aligned" method (matching the magnitude of the final F090W point to the first F150W point) yielded the most robust period estimates for the short-baseline data.
MCMC Template Fitting: Used the emcee sampler to fit light curves to empirical templates (RRab and RRc modes).
- JWST Limitation: Due to the short baseline, the MCMC fitting struggled to converge on periods without fixing them. The authors successfully fitted JWST data by fixing the periods derived from the HST analysis for the overlapping sources.

Distance Determination (PWZ)

HST Analysis: Fitted the Period-Wesenheit-Metallicity (PWZ) relation: $W = \mu + a + b \log(P) + c [Fe/H]$ $W = μ + a + b lo g (P) + c [F e / H]$ .
- Used a Gaussian Mixture Model (GMM) to handle outliers.
- Adopted a top-hat prior for metallicity ( $\langle[Fe/H]\rangle \approx -1.75$ ) based on prior star formation history studies.
JWST Calibration: Used the HST-derived distance modulus as an anchor to calibrate the JWST PWZ relation. Since metallicity was degenerate with the zero-point in the short-baseline JWST fit, they reformulated the equation to solve for a combined zero-point offset ( $\alpha$ ) and slope ( $b$ ).

3. Key Contributions

First JWST RR Lyrae Calibration: Produced the first Period-Wesenheit-Metallicity calibration for JWST NIRCam filters (F090W and F150W).
Methodological Framework for Short Baselines: Developed and tested alternative strategies (filter stitching, period fixing, mid-range magnitude estimation) for analyzing variable stars in JWST data where time baselines are insufficient for standard period-finding.
Instrumental Characterization: Identified and quantified a "burn-in" effect in NIRCam detectors (a temporary signal reduction as detector traps fill) that causes epoch-to-epoch zero-point offsets, though found it negligible compared to template fitting uncertainties.
Cross-Instrument Comparison: Directly compared the efficacy of HST and JWST in identifying RR Lyrae, quantifying recovery rates and completeness in the overlapping WLM field.

4. Key Results

RR Lyrae Population:
- HST: Identified 101 bona fide RR Lyrae stars (85 RRab, 16 RRc).
- JWST: Identified 125 candidates. In the overlapping region, 44 stars were detected in both datasets.
- Recovery Rates: Estimated HST detection probability ( $P_{HST}$ ) at $0.96 \pm 0.03$ and JWST ( $P_{JWST}$ ) at $0.92 \pm 0.04$ for the overlap region.
Distance to WLM:
- The HST-based PWZ fit yielded a distance modulus of $\mu = 24.85 \pm 0.05$ mag ( $0.93 \pm 0.02$ Mpc).
- This is slightly closer than previous measurements (e.g., $\sim 24.97$ mag from Lee et al. 2021). The authors attribute this difference to consistency with the Gaia distance scale, which suggests distances $\sim 3\%$ closer than calibrations based on LMC eclipsing binaries.
JWST PWZ Fit:
- The JWST fit yielded a zero-point offset $\alpha = -1.05^{+0.21}_{-0.26}$ and a slope $b_{JWST} = -1.17^{+0.96}_{-1.26}$ .
- The slope is poorly constrained due to the small sample size and large scatter, but the negative slope is consistent with theoretical expectations.
Alternative Metrics: The study demonstrated that for short-baseline data, mid-range magnitudes (average of max and min) are a more robust estimator of mean magnitude than simple averages, reducing scatter by ~40% compared to simple averages.

5. Significance

Validation of JWST for Variable Stars: The paper confirms that JWST can reliably identify RR Lyrae stars in nearby galaxies despite lower amplitudes and shorter baselines, provided specific analysis techniques are employed.
Future Observing Strategies: The findings suggest that future JWST programs targeting variable stars must prioritize multiple epochs (splitting integration time over several days) rather than single-visit deep imaging to ensure sufficient phase coverage for period determination.
Distance Scale Consistency: The results reinforce the shift toward Gaia-consistent distance scales, highlighting systematic offsets in previous calibrations.
Foundation for Extragalactic Studies: The developed PWZ calibration and analysis pipeline enable the use of JWST to measure distances to galaxies beyond the Local Group where HST resolution is insufficient, significantly expanding the reach of RR Lyrae distance indicators.