Baryonic feedback and intrinsic alignments in profile: a frequentist view of DES Y3 cosmic shear

Anoma Ganguly; Elisabeth Krause; Tanvi Karwal; Vivian Miranda

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Baryonic feedback and intrinsic alignments in profile: a frequentist view of DES Y3 cosmic shear

Anoma Ganguly, Elisabeth Krause, Tanvi Karwal, Vivian Miranda

Cosmology and Nongalactic Astrophysics · Submitted 2 Nov 2026 · 83 references

Pith's verdict: First profile-likelihood treatment of DES Y3 cosmic shear shows the S8 upper limit tracks the baryonic feedback prior; the qualitative result holds, but the quoted 1σ numbers need calibration.

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CitationAnoma Ganguly, Elisabeth Krause, Tanvi Karwal, Vivian Miranda. "Baryonic feedback and intrinsic alignments in profile: a frequentist view of DES Y3 cosmic shear." arXiv:2611.03537 (2026). https://pith.science/paper/BS47LKG6

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Editor's note

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You should know two things about this paper. First, the central claim holds up: for DES Y3 cosmic shear alone, the S8 profile flattens at high S8, and the flat part extends when the log10(TAGN/K) prior upper bound moves from 8.0 to 8.3. That is a direct demonstration that the cosmic-shear-only upper limit on S8 is set by the assumed feedback range, not by the data. Second, the quoted 1σ intervals in Eqs. (19) and (21) are likelihood-ratio statements, not calibrated frequentist intervals. The authors acknowledge this in App. VIII B and in the conclusion. Treat the first as the real result and the second as provisional.

What is new is the first profile-likelihood treatment of DES Y3 cosmic shear under the Hybrid model, and the pipeline work is solid. CMA-ES with the KiDS-Legacy emulator is validated on noiseless and noisy synthetic data, cross-checked against public Hybrid chains and against PROCOLI; the validation appendix is the strongest part of the paper. The sensitivity checks are the right ones: extending the TAGN prior, freeing the neutrino mass, NLA versus TATT, adding shear ratios, and adding a compressed Planck likelihood on (ωb, ns, h) rather than on S8 itself. There is no circularity here; they compare two inference statistics on fixed data.

The soft spot is the one the stress-test names. Wilks' theorem is least protected exactly where it matters: best fits sit at prior boundaries along the profile (Fig. 1 A2), the likelihood has flat directions, and the high-S8 end is where TAGN is pinned against its upper edge. The ten-realization coverage check is suggestive but is not a Neyman calibration. If the true 68% threshold is 0.7 or 1.4, the numbers in Eqs. (19) and (21) shift; the flatness and the direction of prior dependence do not. The abstract's 'upper 1σ limit' should be read with that caveat until the threshold is calibrated.

Two smaller things. The shear-ratio likelihood is on the full DES Y3 footprint while the cosmic shear data are KiDS-excised; the authors acknowledge the mismatch, and it only affects the robustness section. The Roman forecast is fine but not load-bearing. I agree with the reader's CONDITIONAL verdict, leaning slightly more positive on the qualitative claim than on the numeric intervals.

This paper is for anyone working on the S8 tension or on Stage-IV analysis choices. It deserves a serious referee. Send it out; the revision should sharpen the interval-calibration discussion or explicitly demote the numeric 1σ statements.

What would settle it

Generate a large suite of noisy mock realizations of the DES Y3 cosmic shear data with known input cosmology and known feedback strength, and build Neyman-constructed confidence intervals for $S_8$ from the profile likelihood, repeating the construction as the upper bound on $\log_{10}(T_{AGN}/K)$ is raised from 8.0 to 8.3. If the calibrated upper limit on $S_8$ stops moving when the feedback bound is extended, the claim that the prior boundary drives the limit is refuted; if it keeps tracking the bound, the claim is confirmed. A complementary check: measure the feedback strength of the same source population independently, for example from X-ray gas fractions of the hosting halos, and see whether fixing $T_{AGN}$ collapses the flat high-$S_8$ tail of the profile.

Referee report

Significance

If the central claim holds, it is significant: it implies that stage-III cosmic-shear-only S8 constraints are not fully data-driven, because the upper end of the allowed S8 range is governed by the assumed feedback prior, and it identifies which external information (CMB constraints on omega_b, n_s, h) removes the degeneracy. The qualitative version of this claim is robust and well supported: a flat likelihood plateau cannot locate an upper edge regardless of the threshold used to define intervals, and Fig. 4 shows the flat part of the S8 profile extending as the TAGN bound moves from 8.0 to 8.3. The paper deserves credit for its unusually thorough validation: machine-checkable agreement between the emulator and CAMB, consistency with the independent Procoli code, recovery of five Latin-hypercube input cosmologies with both IA models, ten noisy realizations, and a direct comparison with the public Hybrid chains. The authors are also transparent about approximations: Gaussian calibration terms entered as likelihoods, the shear-ratio footprint mismatch, the fixed neutrino mass with an appendix freeing it, and the uncalibrated coverage of the profile intervals.

Major objections (2)

[Secs. IV B-C, Eqs. (19) and (21), and the abstract] The headline 1-sigma intervals use the Wilks threshold Delta chi^2 <= 1, but their coverage is not calibrated, as the paper itself states in App. VIII B ('More noise realizations are needed to calibrate the true coverage of the profile likelihood intervals') and in the Conclusion ('calibrating 1 sigma profile intervals requires larger sets of noisy realizations, which we leave to future work'). The conditions under which Wilks can fail, named in Sec. II B, are present: Fig. 1(A2) shows profile best fits pinned at prior boundaries, and the high-S8 end of the S8 profile is exactly where log10(TAGN/K) sits at its upper bound. The qualitative finding of Fig. 4 is robust to the threshold choice, but the numeric upper limits in Eqs. (19) and (21), the abstract's 'upper 1 sigma limit,' and the size of the shift between the 8.0 and 8.3 panels are not. As submitted, the abstract and the quoted equations present uncalibrated likelihood-ratio statements as 1-sigma intervals. Please either add a Neyman (or Feldman-Cousins, as cited in Sec. II B) calibration for at least the headline S8 and log10(TAGN/K) intervals, or systematically relabel every quoted interval as a Delta chi^2 <= 1 region with the coverage caveat stated at each point of use, including the abstract. The authors acknowledge this: “More noise realizations are needed to cali- brate the true coverage of the profile likelihood intervals. 14 0.75 0.85 S8 −0.04 0.00 0.04 Δz4 0.00 0.03 Δz3 −0.04 0.00 Δz2 −0.04 0.00 0.04 Δz1 −3 0 3 η1 −4 −2 0 a1 7.4 7.6 7.8 log10 (TAGN/K) 0.2 0.4 mν 0.9 1.0 ns 0.020 0.022 0.024 ωb 70 76 H0 0.6 0.8 1.0 σ8 0.2 0.4 Ωm 0.2 0.4 Ωm 0.7 0.9 σ8 70 78 H0 0.022 ωb 0.9 1.0 ns 0.2 0.4 mν 7.6 7.9 log10 (TAGN/K) −3 0 a1 −2 2 η1 −0.03 0.03 Δz1 −0.01 Δz2 0.00 0.03 Δz3 −0.03 0.03 Δz4 Public DES Y3 hybrid (mν free) CAMB (mν free) Emulator (mν = 0.06 eV) FIG. 13.”
[Sec. IV D, Eq. (21)] The statement that 'including scales down to 2.5 arcmin closes the 1 sigma contour,' and the resulting preference for moderate feedback (log10(TAGN/K) = 7.80+0.23-0.30), depends on the same uncalibrated threshold. If the true 68% threshold for this profile exceeded 1, the Lambda-CDM-optimized-scale-cuts contour could also close, which would change the qualitative message of Sec. IV D that small scales select a feedback value rather than yielding only an upper limit. This is a distinct and more threshold-sensitive claim than the position of the S8 upper limit discussed above: the transition from 'upper limit' to 'closed contour' is a binary outcome of the Delta chi^2 = 1 cut. It needs either a calibration or an explicit statement that 'closing' is defined at Delta chi^2 = 1 without coverage guarantees. The authors acknowledge this: “More noise realizations are needed to cali- brate the true coverage of the profile likelihood intervals. 14 0.75 0.85 S8 −0.04 0.00 0.04 Δz4 0.00 0.03 Δz3 −0.04 0.00 Δz2 −0.04 0.00 0.04 Δz1 −3 0 3 η1 −4 −2 0 a1 7.4 7.6 7.8 log10 (TAGN/K) 0.2 0.4 mν 0.9 1.0 ns 0.020 0.022 0.024 ωb 70 76 H0 0.6 0.8 1.0 σ8 0.2 0.4 Ωm 0.2 0.4 Ωm 0.7 0.9 σ8 70 78 H0 0.022 ωb 0.9 1.0 ns 0.2 0.4 mν 7.6 7.9 log10 (TAGN/K) −3 0 a1 −2 2 η1 −0.03 0.03 Δz1 −0.01 Δz2 0.00 0.03 Δz3 −0.03 0.03 Δz4 Public DES Y3 hybrid (mν free) CAMB (mν free) Emulator (mν = 0.06 eV) FIG. 13.”

Minor objections (5)

[Sec. IV B, paragraph after Eq. (19)] The sentence reading 'After adding the CMB likelihood, the same happens in Fig. 3, where the best-fit parameters along the profile path no longer reach the parameter boundaries' is internally contradictory as written: 'the same happens' refers to the edge-pinning of the noiseless test, but the following clause says the parameters no longer reach the boundaries. Please rewrite to state directly that the CMB likelihood removes the edge-pinning seen in Fig. 1(A2).
[Sec. III F 1] The shear-ratio likelihood is applied on the full DES Y3 footprint while the cosmic shear data are KiDS-excised, and the paper notes that no KiDS-excised version exists. Please add one sentence assessing the expected impact of this footprint mismatch on the parameters the shear ratios most constrain (a1 and the photo-z shifts), since the NLA-versus-TATT agreement claim of Sec. IV E relies on the combined likelihood.
[Sec. IV] The paper never reports the absolute best-fit chi-squared (or chi-squared per degree of freedom) for the DES Y3 cosmic shear fits behind Figs. 2-6. Because all reported constraints are differences Delta chi^2 from the global minimum, the reader cannot assess the absolute quality of the fits; please add the best-fit chi-squared values (and the number of data points) for the main analysis variants.
[App. VIII B, Fig. 12] Please rephrase the Fig. 12 caption so that 'the interval obtained by averaging over the ten noise realizations' is not read as a coverage statement. Averaging intervals across realizations does not estimate the probability that a single Delta chi^2 <= 1 interval contains the true value, and ten realizations cannot constrain a 68% quantile; state explicitly that this is the mean interval over realizations and, if feasible, report the per-realization containment count for S8 and Omega_m.
[Sec. II B] The claim that the Gaussian calibration terms of Eq. (17) 'introduce no prior-volume effect and do not change the number of degrees of freedom of Delta chi^2' is terse; a one-line argument that the same quadratic terms appear in both the numerator and denominator of the likelihood ratio would make the point self-contained and would preempt questions about adding eight auxiliary measurements.

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The paper

The paper claims

For DES Y3 cosmic shear alone, the upper 1σ limit on S8 is set by the baryonic feedback prior range, not the data; CMB information on ωb, ns, and h breaks the degeneracy and reconciles profile likelihood and posterior.

The reading

This paper asks whether the standard error bars on cosmic shear measurements are actually earned by the data or inherited from the prior volume of weakly constrained nuisance parameters. Reanalyzing the DES Y3 + KiDS-1000 'Hybrid' model with a profile likelihood — maximizing over all other parameters at each value of the target parameter rather than marginalizing — the authors find that cosmic shear alone leaves a near-flat degeneracy between $S_8$ and baryonic feedback strength $\log_{10}(T_{AGN}/K)$: the upper $1\sigma$ limit on $S_8$ moves with the assumed feedback range instead of being set by the sky. Adding a compressed Planck likelihood on $\omega_b$, $n_s$, and $h$ — parameters cosmic shear cannot see but that fix the shape of the matter power spectrum — breaks the degeneracy, and the frequentist profiles and Bayesian posteriors come into agreement. The same comparison shows that the extra parameters of the TATT intrinsic-alignment model widen the $S_8$ profile relative to NLA, and that adding DES Y3 shear-ratio data closes the gap between the two statistics. If the paper is right, cosmic-shear-only $S_8$ constraints, including part of the reported $S_8$ tension, should not be billed as fully data-driven.

What carries the argument

The load-bearing object is the profile likelihood, $L_p(\Theta) \equiv \max_n L(d|\Theta,n)$, which replaces Bayesian marginalization over nuisance parameters with a maximization at every value of the parameter of interest, with intervals read off from $\Delta\chi^2 = -2\ln(L_p/L_{\max}) \le 1$. The paper connects the two statistics through $P(\Theta) \propto L_p(\Theta)\,V(\Theta)$, where $V(\Theta)$ is the prior volume of nuisance space consistent with the data at fixed $\Theta$: when the best-fit nuisance parameters sit at the edge of their prior range, that volume shrinks the marginal posterior relative to the profile, which is exactly what happens for cosmic shear alone. Computationally, the profiles are carried by a covariance-adapting evolution strategy optimizer coupled to a fast cosmic shear likelihood that uses an emulator for the HMCode2020 matter power spectrum. The physics doing the real work is the near-degeneracy between $S_8$ and the baryonic feedback parameter $\log_{10}(T_{AGN}/K)$: both push the small-scale lensing signal in the same direction, so a flat likelihood ridge in the high-$S_8$ direction is the natural state of cosmic-shear-only data.

Extended reading notes

Core claim

Under the Hybrid model, the profile likelihood for DES Y3 cosmic shear alone peaks at $S_8 = 0.809^{+0.043}_{-0.022}$, in agreement with the marginal posterior mean $0.813 \pm 0.020$, but the profile is much broader toward high $S_8$: stronger baryonic feedback suppresses the small-scale matter power spectrum and can compensate for a higher $S_8$, so the likelihood is nearly flat in $S_8$ above the peak. The paper makes the prior-dependence explicit by extending the upper bound on $\log_{10}(T_{AGN}/K)$ from 8.0 to 8.3: the global best fit does not move, but the upper $1\sigma$ limit of the profile is pushed to higher $S_8$, and the marginal posterior shifts with it. Adding a compressed Planck 2018 Gaussian likelihood on $\omega_b$, $n_s$, and $h$ removes the degeneracy, so that profile and posterior agree ($S_8 = 0.808 \pm 0.019$ versus $0.805 \pm 0.017$) and the $S_8$ constraint becomes insensitive to the feedback prior. With the CMB included, small-scale data down to 2.5 arcmin close the feedback contour and prefer moderate feedback, $\log_{10}(T_{AGN}/K) = 7.80^{+0.23}_{-0.30}$, consistent with hydrodynamical simulations calibrated to observed gas fractions. In the intrinsic-alignment direction, the TATT model's extra free parameters broaden and shift the $S_8$ profile relative to NLA, and adding the DES Y3 shear-ratio likelihood removes the unphysical $a_1 < 0$ branch and brings profiles and posteriors into close agreement for both models.

Load-bearing premise

The quoted intervals assume that the optimizer finds the true best fit at every value of $S_8$ and that the $\Delta\chi^2 \le 1$ rule delivers 68% coverage, even though the best fits sit at the edge of the parameter range where that rule is least reliable — a limitation the authors themselves acknowledge when they note that more noisy mock realizations are needed to calibrate the true coverage of the profile likelihood intervals.

Editorial extensions

If this is right

Cosmic-shear-only $S_8$ upper limits are prior-controlled: two analyses with identical data but different assumed ranges for $\log_{10}(T_{AGN}/K)$ will report different upper $1\sigma$ limits on $S_8$.
A compressed CMB likelihood on $\omega_b$, $n_s$, and $h$ is sufficient to break the $S_8$–feedback degeneracy; with it, profile likelihoods and marginal posteriors agree and the $S_8$ constraint no longer depends on the feedback prior.
Small-scale cosmic shear combined with CMB shape information constrains baryonic feedback to moderate strengths, $\log_{10}(T_{AGN}/K) = 7.80^{+0.23}_{-0.30}$, consistent with hydrodynamical simulation calibrations based on observed gas fractions.
Adding the DES Y3 shear-ratio likelihood removes the $a_1 < 0$ branch of the NLA profile and brings the NLA and TATT models into agreement with each other and with the Bayesian posteriors.
At Stage-IV precision, the forecast indicates that most parameters become well constrained within their priors, so profile likelihoods and marginal posteriors deliver comparable constraining power.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

If the feedback–$S_8$ degeneracy is as strong as the paper shows, the reported differences in $S_8$ among stage-III surveys — and part of the apparent $S_8$ tension with the CMB — could reflect where each analysis placed its baryon-prior boundary rather than what the sky says; re-running published cosmic-shear-only analyses with one common feedback range would test this directly.
The same prior-volume mechanism should afflict any nuisance parameter with a flat likelihood direction, not just $T_{AGN}$: flexible intrinsic-alignment extensions or a free neutrino mass will tend to drag marginal posteriors relative to the profile, so a profile-versus-posterior audit could be a cheap standard check for every cosmic shear release.
The noiseless Roman-style forecast is optimistic by construction; the claimed convergence of profile and posterior at Stage-IV precision should be re-examined on noisy realizations with realistic covariance, since the interval coverage that the DES Y3 analysis could not calibrate is precisely what would matter for quoted Stage-IV errors.

Original abstract

Current cosmic shear surveys primarily constrain $S_8$ and $\Omega_\mathrm{m}$, while most other model parameters remain dominated by priors. Consequently, marginal posteriors are vulnerable to prior-volume effects, particularly through degeneracies among $S_8$, baryonic feedback, and intrinsic alignment (IA) model parameters. To isolate data-driven constraints from prior volume effects, we compare profile likelihoods with Bayesian posteriors for DES Y3 cosmic shear under the DES Y3+KiDS-1000 Hybrid model. For cosmic shear alone, the profile global best fit and the marginal posterior mean agree in $S_8$, but the profile likelihood reveals a strong degeneracy between feedback strength and $S_8$, leaving the upper $1\sigma$ limit on $S_8$ determined by the assumed feedback range. External CMB information on parameters other than $\Omega_\mathrm{m}$ and $S_8$ breaks this degeneracy, suppressing prior-volume effects and reconciling the profiles with the posteriors. With CMB data included, small-scale cosmic shear data prefers moderate baryonic feedback strengths consistent with hydrodynamical simulations calibrated to observed gas fractions. Furthermore, additional unconstrained parameters in the tidal alignment and tidal torquing (TATT) model result in weaker constraints, shifting and broadening the $S_8$ profile relative to the nonlinear linear alignment (NLA) model. Adding DES Y3 shear ratios mitigates this degeneracy, bringing profile likelihood and marginal posteriors into close agreement.

The compiled record

The paper's own sentences, arranged, kept beside the review and separate from it. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-11-04: 1 request, 6,521 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.69 · human participants 0.01 · controlled comparison 0.25 · randomized assignment 0.01 · states quantitative result 0.29 · compares with prior results 0.90 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; show every role.

Current cosmic shear surveys primarily constrain $S_8$ and $\Omega_\mathrm{m}$, while most other model parameters remain dominated by priors. Consequently, marginal posteriors are vulnerable to prior-volume effects, particularly through degeneracies among $S_8$, baryonic feedback, and intrinsic alignment (IA) model parameters. To isolate data-driven constraints from prior volume effects, we compare profile likelihoods with Bayesian posteriors for DES Y3 cosmic shear under the DES Y3+KiDS-1000 Hybrid model. For cosmic shear alone, the profile global best fit and the marginal posterior mean agree in $S_8$, but the profile likelihood reveals a strong degeneracy between feedback strength and $S_8$, leaving the upper $1\sigma$ limit on $S_8$ determined by the assumed feedback range. External CMB information on parameters other than $\Omega_\mathrm{m}$ and $S_8$ breaks this degeneracy, suppressing prior-volume effects and reconciling the profiles with the posteriors. With CMB data included, small-scale cosmic shear data prefers moderate baryonic feedback strengths consistent with hydrodynamical simulations calibrated to observed gas fractions. Furthermore, additional unconstrained parameters in the tidal alignment and tidal torquing (TATT) model result in weaker constraints, shifting and broadening the $S_8$ profile relative to the nonlinear linear alignment (NLA) model. Adding DES Y3 shear ratios mitigates this degeneracy, bringing profile likelihood and marginal posteriors into close agreement.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Current cosmic shear surveys primarily constrain $S_8$ and $\Omega_\mathrm{m}$, while most other model parameters remain dominated by priors.	background 0.98	0.07	0.04	asserted 1.00
s1	Consequently, marginal posteriors are vulnerable to prior-volume effects, particularly through degeneracies among $S_8$, baryonic feedback, and intrinsic alignment (IA) model parameters.	background 0.80	0.13	0.06	asserted 0.88
s2	To isolate data-driven constraints from prior volume effects, we compare profile likelihoods with Bayesian posteriors for DES Y3 cosmic shear under the DES Y3+KiDS-1000 Hybrid model.	method 0.68	0.93	0.07	asserted 0.94
s3	For cosmic shear alone, the profile global best fit and the marginal posterior mean agree in $S_8$, but the profile likelihood reveals a strong degeneracy between feedback strength and $S_8$, leaving the upper $1\sigma$ limit on $S_8$ determined by the assumed feedback range.	result 0.99	0.92	0.24	asserted 1.00
s4	External CMB information on parameters other than $\Omega_\mathrm{m}$ and $S_8$ breaks this degeneracy, suppressing prior-volume effects and reconciling the profiles with the posteriors.	result 0.83	0.81	0.25	asserted 1.00
s5	With CMB data included, small-scale cosmic shear data prefers moderate baryonic feedback strengths consistent with hydrodynamical simulations calibrated to observed gas fractions.	result 0.96	0.83	0.17	asserted 0.79
s6	Furthermore, additional unconstrained parameters in the tidal alignment and tidal torquing (TATT) model result in weaker constraints, shifting and broadening the $S_8$ profile relative to the nonlinear linear alignment (NLA) model.	result 1.00	0.85	0.06	asserted 1.00
s7	Adding DES Y3 shear ratios mitigates this degeneracy, bringing profile likelihood and marginal posteriors into close agreement.	result 0.98	0.90	0.23	asserted 1.00

What kind of paper the classifier reports this is: empirical study 0.69 · evidence from analysis of existing data 0.99.

What was examined, and what was not

sources read

arXiv listing abstract v1

not examined

full text
figures and tables
references and citing sentences
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P abstract

not run

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

Figures

**Figure 1.** FIG. 1. Comparison of Bayesian and frequentist approaches on one noiseless synthetic DES Y3-like cosmic shear data vector

**Figure 2.** FIG. 2. 2D constraints from Bayesian (dashed contours)

**Figure 3.** FIG. 3. Addition of compressed CMB Planck 2018 TT,TE,EE

**Figure 4.** FIG. 4. Profiles (solid) and posterior (dashed) comparison

**Figure 6.** FIG. 6. Profile comparison between NLA and TATT models

**Figure 7.** FIG. 7. Forecast for a wide Roman survey over the LSST Y10

**Figure 8.** FIG. 8. Effect of prior (parameter) boundaries on marginal

**Figure 9.** FIG. 9. CAMB and emulator profiles run using CMA-ES

**Figure 11.** FIG. 11. Validation on noiseless synthetic cosmic-shear data

**Figure 12.** FIG. 12. Validation on ten synthetic noisy realizations of

**Figure 13.** FIG. 13. Posterior comparison with public DES-KiDS (Σ

Showing 12 of the paper's 14 figures. See all figures in the PDF ↗ Figures reproduced from arXiv:2611.03537 by the authors.

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Discussion

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