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Balmer break grows from cosmic dawn to noon, JWST survey finds

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2026-07-09 01:50 UTC pith:PMJ3EQKY

load-bearing objection Systematic photometric Balmer break survey across z=3.5–10: solid primary result, circular secondary analysis the 2 major comments →

arxiv 2607.07698 v1 pith:PMJ3EQKY submitted 2026-07-08 astro-ph.GA

Tracing the Evolution of the Balmer Break from Cosmic Dawn to Cosmic Noon with JWST

Adarsh Kuruvanthodi , Daniel Schaerer , Rui Marques-Chaves , Andrea Weibel , Damien Korber , Corinne Charbonnel This is my paper
classification astro-ph.GA
keywords cosmicpopulationstellarstrengthredshiftacrossbalmerbreak
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper uses JWST near-infrared photometry from four major survey programs to measure the Balmer break strength of galaxies across a wide redshift range (z = 3.5 to 10), corresponding to roughly the first 1.5 billion years of cosmic history. The Balmer break is a step-like discontinuity in a galaxy's spectrum at around 4000 angstroms, caused by absorption in the atmospheres of stars cooler than about 10,000 kelvin. Its strength traces how old the dominant stellar population is: young, actively star-forming galaxies show little to no break (or even an inverted feature called a Balmer jump from nebular gas), while older or quenched galaxies show a strong break. The authors designed five redshift windows where pairs of adjacent JWST broadband filters straddle the break without being contaminated by strong emission lines, allowing them to measure break strength from photometry alone across a sample of nearly 17,000 galaxies. They find that the median break strength, expressed as a flux ratio of light redward to blueward of the break, increases from about 1.1 at z ~ 10 (cosmic dawn) to about 1.5 at z ~ 3.5 (cosmic noon). This trend is driven primarily by stellar population age: galaxies at later cosmic times have had more time for their massive, short-lived stars to die, leaving cooler A-type and later stars that produce a stronger break. The authors convert break strengths to ages using two limiting star formation history models, finding that the typical stellar age decreases from roughly 350 million years at z ~ 3.5 (under a constant star formation assumption) to about 20 million years at z ~ 10, or from about 50 to 10 million years under an instantaneous burst assumption. They also identify a population of galaxies with extremely strong breaks (flux ratio above 3.0) at both low and high redshifts. At z = 3.5 to 4, these are dusty quiescent or post-starburst galaxies plus some Little Red Dots, a newly recognized class of compact red objects. At z = 7 to 10, the strongest breaks are almost exclusively from Little Red Dots, whose break strengths sometimes exceed what standard stellar population models can produce, pointing to exotic explanations such as supermassive stars or dense gas around a black hole.

Core claim

The central finding is that the median Balmer break strength in the galaxy population evolves systematically from 1.1 to 1.5 in flux ratio between z ~ 10 and z ~ 3.5, and that this evolution is primarily an age effect. The paper establishes that photometric measurements of the break using carefully chosen JWST filter pairs are consistent with spectroscopic measurements from the literature, validating a method that can be applied to far larger samples than spectroscopy alone permits. The authors also show that break strength correlates positively with stellar mass, age, dust extinction, and UV redness, and negatively with hydrogen emission line equivalent widths, across most redshift bins. A子

What carries the argument

The Balmer break itself is the central object. Defined as the flux ratio F_nu(redward)/F_nu(blueward) of the spectral discontinuity near 4000 angstroms rest frame, it serves as a direct thermometer of stellar population age. The paper uses two bracketing star formation histories, instantaneous burst and constant star formation, as limiting cases to translate break strength into age. The Little Red Dots, compact red sources with extremely strong breaks, emerge as a distinct population whose break strengths defy standard stellar population models.

Load-bearing premise

The highest-redshift bin (z = 9.2 to 10) contains only 12 photometric objects, and the authors acknowledge that some may be interlopers, such as emission-line galaxies at z ~ 8.5 or dusty galaxies at z = 3 to 4 misidentified as high-redshift sources. Contamination in this bin could bias the median break strength and the correlations derived there.

What would settle it

If future spectroscopic follow-up of the z = 9.2 to 10 candidates reveals that a significant fraction are lower-redshift interlopers rather than genuine Balmer break sources at z > 9, the claimed median break strength at cosmic dawn and any correlations involving that bin would need revision.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • If photometric Balmer break measurements are reliable across z = 3.5 to 10, then future wide-field JWST imaging surveys can characterize stellar population ages for tens of thousands of galaxies without needing spectroscopy, dramatically expanding the sample size for studies of early galaxy formation.
  • The identification of two distinct populations of strong-break galaxies (dusty quiescent galaxies at z < 5, Little Red Dots at z > 7) suggests that the mechanisms producing strong breaks change with cosmic epoch, from classical quenching to something potentially involving exotic stellar populations or AGN.
  • The correlation between break strength and emission line equivalent widths (H-alpha, H-beta) provides a cross-check that can be exploited by upcoming spectroscopic surveys to calibrate photometric break measurements at redshifts where filter coverage is sparse.
  • The existence of galaxies at z > 7 whose break strengths exceed the maximum predicted by standard stellar population models constrains the formation timescale of these objects and may point to star formation beginning at z > 10 or to non-standard stellar populations.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the highest-redshift bin (z = 9.2 to 10) is contaminated by interlopers as the authors acknowledge, the true median break strength at cosmic dawn may be even lower than 1.1, which would strengthen the claimed evolutionary trend and imply even younger stellar populations at the earliest epochs.
  • The transition from Balmer break to Balmer jump in the median population above z ~ 6, noted in spectroscopic literature, if confirmed by larger unbiased samples, would mark a cosmic epoch where the average galaxy transitions from quiescence-dominated to star-formation-dominated, offering a observational anchor for models of when sustained star formation becomes the norm.
  • The fact that supermassive star models can reproduce the strongest observed breaks (up to flux ratios of 5.5 to 6) suggests a testable prediction: if such stars exist in Little Red Dots, their spectra should show specific signatures of very cool, very massive stars that differ from the spectral signatures of AGN-dominated scenarios.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 7 minor

Summary. This paper presents a systematic photometric study of Balmer break (BB) strengths in galaxies from z=3.5 to z=10 using JWST NIRCam data from CEERS, JADES, FRESCO, and PRIMER. The authors measure BB strengths using adjacent broadband filters in five redshift windows designed to avoid strong emission-line contamination. They find that the median BB strength decreases from ~1.5 to ~1.1 (flux ratio) from z~3.5 to z~10, consistent with spectroscopic estimates from Roberts-Borsani et al. (2024) and Langeroodi & Hjorth (2024). They convert BB strengths to stellar population ages using polynomial fits to mock simulations for two limiting SFHs (instantaneous burst and constant star formation), and examine correlations between BB strength and various physical parameters (mass, age, E(B-V), beta, sSFR, EW(Halpha), etc.). They also identify objects with extremely large BB strengths and discuss their nature, including quiescent galaxies, dusty sources, and Little Red Dots.

Significance. The paper provides a timely and valuable systematic characterization of BB strengths across a wide redshift range using JWST photometry. The filter-selection strategy to avoid strong line contamination is well-motivated, and the validation against independent spectroscopic measurements (Fig. 6) and convolved stacked spectra lends credibility to the photometric approach. The mock simulation framework (§3) provides a self-consistent basis for interpreting the observations. The identification of strong BB sources across redshifts and the discussion of their physical nature (quiescent galaxies vs. LRDs) adds useful observational context. The comparison with literature data in Fig. 8 is comprehensive. The paper ships falsifiable predictions (BB-age relations in Table C.1) and reproducible methodology (CIGALE parameter spaces in Tables A.1–A.2).

major comments (2)
  1. §4.3, Figure 7 (second row), and §3.6/Table C.1: The BB–age correlation reported in §4.3 is partially circular. The ages plotted on the y-axis of the BB-vs-age correlation are derived directly from the BB strength itself via the polynomial relations in Table C.1 (Age = 10^(m×BB+c)). This makes the correlation mathematically guaranteed by construction for individual objects, not an independent empirical test. The paper does have independent CIGALE SED-fitting ages from the delayed-τ model (§2.2, Table A.1), but these are not used in the correlation analysis of §4.3. The claim that 'age is a primary driver for the BB strength' (§4.3) would be substantially strengthened if the correlation were computed using the independent CIGALE SED-fitting ages rather than the BB-derived ages. As currently presented, the BB–age correlation is tautological and should either be replaced with the SED-fiting
  2. §4.1, §5.3.1, Table 1 (z=9.2–10 row): The highest-redshift photometric bin contains only 12 objects, and the authors acknowledge (§5.3.1) that 'some candidates in the highest redshift bin (z=9.2–10) may not be genuine BB sources; they could instead be emission-line galaxies at z~8.5... or dusty galaxies at z=3–4 misclassified as Lyman-break galaxies at z=9.2–10.' This interloper contamination directly affects the median BB value and all correlation coefficients reported for this bin. Given that the central claim includes the median BB evolution from z=3.5 to z=10, the authors should quantify the potential bias from interlopers on the median BB in this bin (e.g., through a contamination fraction estimate or by excluding likely interlopers and recomputing the median). The spectroscopic sample has 27 objects in this bin; a comparison of the photometric and spectroscopic medians specifically
minor comments (7)
  1. §3.6: The polynomial fit formula 'Age=10^(m×BB+c)' is ambiguous about whether the exponent is base-10 or natural. Please clarify explicitly (it appears to be base-10 from context, but this should be stated).
  2. §5.3.3: The statement that 'neglecting individual uncertainties is unlikely to affect the results' would be stronger if the median photometric uncertainty were quantified and compared to the observed scatter in BB distributions (σ≈0.25 mag, §4.1).
  3. Figure 8: The y-axis is labeled in flux ratio units but uses square-root scaling, which may be visually misleading for the reader. A note in the caption or a secondary linear-scale axis would help.
  4. §2.2: The SMC metallicity (Z=0.004) is adopted as a single value for all objects. Given the redshift range z=3.5–10 and the likely diversity of metallicities, a brief discussion of how this assumption affects the age estimates (especially given the metallicity dependence shown in Fig. 4) would strengthen this section.
  5. Table C.1: The BB range column for the CSF scenario in the z=3.5–4.0 bin lists '0.61≤BB≤0.74', which seems narrow; please verify this is correct and consistent with the range of observed BB values in that bin.
  6. §4.1: The KS test results are described qualitatively ('D exceeds 0.2 for all pairwise comparisons'). Providing the actual D and p-values in a table or supplementary material would allow readers to assess significance more precisely.
  7. §5.2, Figure 9: The delayed-τ model with quenching after 500 Myr is introduced but the specific parameters (τ value, quenching timescale) are not fully specified. Please provide these for reproducibility.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for a careful and constructive report. Both major comments identify genuine issues that we will address in the revised manuscript. Below we respond point by point.

read point-by-point responses

  1. Referee: §4.3, Figure 7 (second row), and §3.6/Table C.1: The BB–age correlation reported in §4.3 is partially circular. The ages plotted on the y-axis are derived directly from the BB strength itself via the polynomial relations in Table C.1 (Age = 10^(m×BB+c)). This makes the correlation mathematically guaranteed by construction. The paper does have independent CIGALE SED-fitting ages from the delayed-τ model (§2.2, Table A.1), but these are not used in the correlation analysis of §4.3. The claim that 'age is a primary driver for the BB strength' would be substantially strengthened if the correlation were computed using the independent CIGALE SED-fitting ages rather than the BB-derived ages. As currently presented, the BB–age correlation is tautological and should either be replaced with the SED-fitting ages or supplemented with them.

    Authors: The referee is correct, and we thank them for identifying this issue. The ages shown in the second row of Figure 7 are indeed derived from the BB strength via the polynomial relations in Table C.1, which makes the BB–age correlation tautological by construction. This was an oversight on our part. We will revise the manuscript to use the independent CIGALE SED-fitting ages (delayed-τ model, §2.2, Table A.1) for the correlation analysis in §4.3 and Figure 7. The BB-derived ages from §4.2 will be retained only for the age distribution analysis (Figures D.2, D.3), where they serve as illustrative estimates under the two limiting SFH assumptions, not as independent variables for correlation testing. We will also add an explicit note in §4.3 clarifying that the SED-fitting ages are independent of the BB measurement and are therefore the appropriate variable for testing whether age drives BB strength. We will update the correlation coefficients and the associated discussion accordingly. If the correlation persists with the independent SED-fitting ages, the claim that age is a primary driver of BB strength will be substantially strengthened; if it weakens, we will report that honestly and revise our conclusions. revision: yes

  2. Referee: §4.1, §5.3.1, Table 1 (z=9.2–10 row): The highest-redshift photometric bin contains only 12 objects, and the authors acknowledge that some candidates may not be genuine BB sources. This interloper contamination directly affects the median BB value and all correlation coefficients reported for this bin. The authors should quantify the potential bias from interlopers on the median BB in this bin (e.g., through a contamination fraction estimate or by excluding likely interlopers and recomputing the median). The spectroscopic sample has 27 objects in this bin; a comparison of the photometric and spectroscopic medians specifically for this bin would be valuable.

    Authors: We agree that the interloper contamination in the z=9.2–10 bin needs to be quantified rather than only acknowledged qualitatively. We will address this in the revised manuscript through the following steps: (1) We will provide a direct comparison of the median BB strength between the photometric (12 objects) and spectroscopic (27 objects) samples in this bin. The spectroscopic sample, by construction, is not subject to photometric redshift interloper contamination, so this comparison directly constrains the bias. (2) We will identify likely interlopers in the photometric sample by examining objects whose CIGALE and EAZY redshifts diverge most strongly, or whose SEDs show alternative low-redshift solutions with comparable χ², and recompute the median BB excluding these candidates. (3) We will estimate a contamination fraction based on the fraction of photometric sources in this bin that have plausible alternative redshift solutions (e.g., z~8.5 emission-line galaxies or z~3–4 dusty galaxies). We will report the median BB with and without likely interlopers, and we will add an explicit error bar or systematic uncertainty on the z=9.2–10 median that accounts for this contamination. We note that the spectroscopic median in this bin (BB~1.09 in flux ratio) is already shown in Figure 6 and is lower than the photometric median (BB~1.11), which provides a preliminary indication that the contamination bias is modest but present. We will make this comparison explicit in the text and in a small table. We will also add a caveat that all correlation coefficients reported for this bin (§4.3) are particularly uncertain given the small sample size and potential contamination, and we will flag these accordingly in Figure 7. revision: yes

Circularity Check

3 steps flagged

BB–age correlation is tautological: ages are computed from BB strength via polynomial fits, making the 'age is primary driver' claim circular by construction

specific steps
  1. fitted input called prediction [§3.6 (Age estimation from BB strength), §4.3 (correlation analysis), Table C.1]
    "To first order, it is possible to estimate the age of dominant stellar populations from the BB strength. We fitted the BB color versus age plots created using mock galaxy simulations for SMC metallicity with a first-order polynomial. With that, a slope and an intercept have been estimated for each redshift interval to measure the age of the dominant stellar populations. The age in Myr can be calculated as: Age=10^(m×BB+c), where m and c are slope and intercept, respectively, and given in Table C.1 for IB and CSF SFH."

    The paper's §4.3 reports a 'moderate to strong correlation between BB strength and age' and uses this as evidence that 'age is a primary driver for the BB strength.' However, the ages used in this correlation analysis are not independently measured — they are computed directly from the BB strength itself using the polynomial relation Age = 10^(m×BB+c) from §3.6 and Table C.1. This makes the BB–age correlation mathematically guaranteed by construction: if Age = f(BB) is a monotonic function, then corr(BB, Age) is guaranteed to be high. The correlation is not an empirical test of whether age drives BB; it is a tautological restatement of the calibration. The paper does have independent CIGALE SED-fitting ages from the delayed-τ model (§2.2, Table A.1), but these are not used in the §4.3 age–

  2. fitted input called prediction [§4.3 (correlation analysis with E(B−V), β, EW(Hα)), §2.2 (CIGALE SED fitting)]
    "In this section, we investigate how the observed BB color index correlates with various physical parameters estimated from the SED fits. The following physical parameters are considered: stellar mass, age of the object (dominant stellar population), UV slope (β), specific star formation rate (sSFR), EW(Hα), EW(Hβ), extinction (E(B−V))..."

    The correlations reported in §4.3 between BB strength and E(B−V), β, EW(Hα), EW(Hβ), sSFR, and stellar mass use physical parameters derived from CIGALE SED fitting (§2.2). The SED fits use the same NIRCam photometry — including the BB-probing filters — that are used to measure the BB strength itself. The BB-probing filters (e.g., F150W and F200W at z~3.7) directly enter both the BB measurement and the SED fit, so the fitted parameters (E(B−V), β, etc.) are not fully independent of the BB measurement. The correlations between BB and these SED-derived quantities are therefore partially constructed by the fitting procedure rather than being fully independent observational tests. This is a partial circularity: the correlations are not guaranteed by construction (unlike the age case), but they

  3. self citation load bearing [§2.4 (BB measurement reliability), §3.1 (D4000 Kuruvanthodi definition)]
    "The reliability of this method is already discussed in Kuruvanthodi et al. (2024) for redshifts ≥7. They applied the above strategy to the convolved stacked spectra of Roberts-Borsani et al. (2024) and showed that the BB measurements from photometry are similar to spectroscopic ones... D4000 Kuruvanthodi... Kuruvanthodi et al. (2023)"

    The paper introduces a custom BB measurement definition ('D4000 Kuruvanthodi' from Kuruvanthodi et al. 2023) and validates its reliability by citing Kuruvanthodi et al. (2024), which shares the same first author. The validation of the photometric BB method — a load-bearing methodological choice — rests on a self-citation whose independent verification is not reproduced in the present paper. However, this is a minor issue: the method is also validated against external spectroscopic studies (Roberts-Borsani et al. 2024; Langeroodi & Hjorth 2024) in §4.1 and Figure 6, providing independent support. The self-citation is supplementary rather than the sole basis for the method's validity.

full rationale

The paper's central observational claim — that median BB strength evolves from 1.1 to 1.5 from z~10 to z~3.5 — is independently grounded: BB is measured directly from filter colors (a direct observable), and the trend is validated against independent spectroscopic studies (Roberts-Borsani et al. 2024; Langeroodi & Hjorth 2024) in Figure 6. However, the secondary claim that 'age is the primary driver of BB strength' is circular by construction: the ages used in the §4.3 correlation analysis are computed directly from BB strength via the polynomial fits of §3.6 (Age = 10^(m×BB+c), Table C.1), making the BB–age correlation tautological. The paper does have independent CIGALE SED-fitting ages from the delayed-τ model (§2.2, Table A.1), but these are not used in the correlation analysis. The correlations with other SED-derived parameters (E(B−V), β, EW(Hα)) are partially circular because the SED fits use the same photometry that measures the BB. The theoretical model predictions (§3.2) showing BB increases with age are sound but are model-based, not observational tests. The self-citation to Kuruvanthodi et al. (2024) for method reliability is minor and supplemented by external validation. Score 6 reflects that one 'prediction' (the age–BB correlation) reduces by construction to its input, while the paper's primary result (median BB evolution) remains independently grounded.

Axiom & Free-Parameter Ledger

4 free parameters · 5 axioms · 0 invented entities

No new physical entities are postulated. The paper discusses SMS, BH*, and AGN as possible explanations for extreme BB sources but does not introduce them; they are drawn from prior literature.

free parameters (4)
  • SMC metallicity Z=0.004 = 0.004
    Fixed metallicity assumption used throughout for age estimation from BB; chosen as representative but not fitted to individual galaxies.
  • Polynomial fit slopes/intercepts for age calibration = See Table C.1
    First-order polynomial coefficients fitted to mock CIGALE simulations to convert BB color to age, for each redshift bin and SFH type, with piecewise BB ranges.
  • Redshift bin boundaries = z=3.5-4.0, 5.4-5.8, 7.1-8.0, 8.0-9.2, 9.2-10
    Chosen to align filter combinations with rest-frame BB wavelength range and avoid strong emission lines; not fitted but designed around filter properties.
  • 3σ detection threshold = 3
    Required detection significance in BB-probing filters; chosen to ensure measurement reliability but affects sample completeness.
axioms (5)
  • domain assumption Bruzual & Charlot (2003) stellar population models accurately predict galaxy SEDs at z=3.5-10
    Used throughout for both SED fitting and mock simulations; all age and BB predictions depend on this model being correct at low metallicities and young ages.
  • domain assumption SMC attenuation law is appropriate for high-redshift galaxies
    Applied uniformly (power-law slope -0.5) for all objects; the choice of attenuation law affects E(B-V) estimates and BB interpretation (§3.4).
  • domain assumption Two limiting SFHs (instantaneous burst and constant star formation) bracket the true SFHs
    Used to convert BB measurements to age estimates; the authors acknowledge 'real SFHs are complex' (§3.5) but the entire age analysis relies on these two extremes.
  • domain assumption Photometric redshifts from CIGALE+EAZY agreement within 0.2 are reliable
    The cross-matching criterion (§2.3) is the primary redshift quality filter; its reliability at z>8 is questioned by the authors themselves (§5.3.1).
  • domain assumption Salpeter IMF
    Fixed IMF assumption affecting stellar mass estimates and model predictions; not varied or tested.

pith-pipeline@v1.1.0-glm · 29198 in / 4701 out tokens · 336313 ms · 2026-07-09T01:50:43.149797+00:00 · methodology

0 comments
read the original abstract

The Balmer break (BB) is a key spectral feature for constraining stellar population ages, star formation histories, and redshifts of high-redshift sources. The redshift evolution and distribution of BB strength, together with the properties of BB galaxies, constrain stellar population characteristics and the nature of star formation across cosmic epochs. However, a systematic and unbiased characterization of BB strengths across the full galaxy population remains limited with the James Webb Space Telescope (JWST). We aim to characterize the redshift evolution of BB strength over $z=3.5$-10 and its distribution across different epochs using photometry. We also examine correlations between BB strength and key physical parameters within these redshift intervals. We further assess the implications of BB galaxies for the nature of star formation and stellar populations at $z>3.5$. We used the JWST NIRCam photometric observations taken as part of various programs, including CEERS, JADES, FRESCO, and PRIMER. We estimated the BB strength of the objects with two adjacent broadband filters in various redshift windows between redshifts 3 and 10, which exclude strong line contamination. We employ the SED-fitting code CIGALE for both SED fitting and the generation of mock galaxy simulations. We find that the median Balmer break strength (expressed as a flux ratio) increases from cosmic dawn to cosmic noon, from 1.1 to 1.5, primarily driven by the age of the stellar population. These estimations are in agreement with the latest spectroscopic estimations in the literature. We identify objects with extremely large BB strengths (BB$>3.0$) at $z=3.5$-4 and $z=7$-10, indicating strong extinction combined with an old stellar population and the presence of Little Red Dots (LRDs) in the former, and predominantly LRDs in the latter.[abridged]

Figures

Figures reproduced from arXiv: 2607.07698 by Adarsh Kuruvanthodi, Andrea Weibel, Corinne Charbonnel, Damien Korber, Daniel Schaerer, Rui Marques-Chaves.

Figure 1
Figure 1. Figure 1: Redshift distribution of the various samples studied in [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Model spectra for the instantaneous burst scenario for [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 4
Figure 4. Figure 4: BB-probing color (F150W [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Except for a few galaxies, which we discuss below, all [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 5
Figure 5. Figure 5: BB distribution of objects in different redshift bins up to z ∼ 9.2. A Gaussian fit performed for the distribution is shown in the red and yellow lines for photometric and spectroscopic samples, respectively. The median value of the distribution is shown in green and brown dashed lines for photometric and spectroscopic samples, respectively. The maximum BB expected from the CSF and IB (without extinction, … view at source ↗
Figure 6
Figure 6. Figure 6: Median evolution of BB with redshift for photo [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Correlation of Balmer break strength with various physical parameters for the photometric and spectroscopic sample. The [PITH_FULL_IMAGE:figures/full_fig_p009_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Comparison of the Balmer break sources in this work with the literature. Small green solid circles (photometric sample) and [PITH_FULL_IMAGE:figures/full_fig_p011_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Evolution of Balmer break strength with formation redshift. The solid line indicates IB SFH, the dashed line indicates CSF [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗

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