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Comment on "Test of the Gravitational Force Law on Cosmological Scales Using the Kinematic Sunyaev--Zeldovich Effect''

Published 25 Oct 2026 in astro-ph.CO | (2610.34437v1)

Abstract: Gallardo et al. [Phys. Rev. Lett. \textbf{136}, 151002 (2026)] constrain the index of the force law g∝r−ng\propto r^{-n} with pairwise kinematic Sunyaev--Zeldovich measurements, n=2.1±0.3n=2.1\pm0.3, and exclude the deep-MOND value n=1n=1 at $3.3σ$. The exclusion does not follow from their calculation. Their templates for n≠2n\neq2 [their Eq.~(8)] raise the pair-averaged Newtonian acceleration to the power n/2n/2, whereas the pair average of the pointwise law [their Eq.~(30) for deep MOND] is the average of the transformed field; the step that identifies the two attributes to the three-point function a correction that is of second order and not small. In a Gaussian linear field with linearly biased tracers, Gaussian integration by parts shows that the correctly averaged template is exactly proportional to the Newtonian one, with a constant that the analysis absorbs into the mean optical depth. Gaussian realizations with peak-selected tracers find the same proportionality to within 2\% (0.5\% for the fiducial selection), and refitting the data of the Letter with the resulting template gives χ2=20.1χ^2=20.1--$20.2$, against $20.1$ for the Newtonian template and $33.8$ for Eq.~(8): in every controlled case examined the data do not discriminate between n=1n=1 and n=2n=2, and the $3.3σ$ exclusion, with the $10σ$ forecast that rescales it, rests on the order in which the average and the power were taken. What a self-consistent MOND cosmology predicts for this observable is a separate question, which the Letter does not address.

Authors (1)

Summary

  • The paper challenges the interpretation of Gallardo et al. and claims the exclusion of the deep-MOND value $n=1$ could be due to a methodological error, not the actual physical phenomena.
  • The paper's author, Alberto Melchiorri, argues that the templates used for inference in the pairwise response do not correctly reflect the pointwise force law used in the paper.
  • The original analysis replaced an average of the transformed acceleration with the square root of the averaged acceleration, leading to significant implications for the inferred force law and making the proposed $3.3$ σ exclusion of $n=1$ invalid.

The comment challenges the interpretation of the pairwise kinematic Sunyaev–Zeldovich (kSZ) analysis by Gallardo et al., which reported a constraint on a phenomenological force-law index, n=2.1±0.3n=2.1\pm0.3, and claimed a 3.3σ3.3\sigma exclusion of the deep-MOND value n=1n=1 (Gallardo et al., 15 Apr 2026). Melchiorri does not dispute the kSZ measurement or the numerical fit obtained with the published pipeline. Instead, he argues that the non-Newtonian templates used to infer the force-law exponent do not represent the pairwise response generated by the pointwise force law that they are intended to test (2610.34437).

The central distinction between averaging and nonlinear transformation

The disputed force law is written pointwise as a nonlinear transformation of the Newtonian acceleration,

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.

For a point source, this produces g∝r−ng\propto r^{-n}. In the deep-MOND case, n=1n=1, the transformation becomes

F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.

The observable, however, is not the acceleration at an isolated point. It is a tracer-pair average of the line-of-sight acceleration difference at separation rr,

⟨Xn⟩12(r)=⟨[F(g2)−F(g1)]⋅e12⟩12.\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.

According to the comment, Gallardo et al. instead construct their generalized templates by first computing the pair-averaged Newtonian acceleration and then raising its magnitude to the power n/2n/2:

3.3σ3.3\sigma0

These operations coincide for 3.3σ3.3\sigma1, because the transformation is linear. They do not generally coincide for 3.3σ3.3\sigma2. The distinction is the standard noncommutativity of nonlinear functions with ensemble averages, but it is decisive here because the radial dependence of the published 3.3σ3.3\sigma3 templates is precisely what drives the claimed statistical discrimination.

The comment reproduces the published fit using the public data products: 3.3σ3.3\sigma4 from 15 separation bins, with 3.3σ3.3\sigma5 for the Newtonian template and 3.3σ3.3\sigma6 for the published 3.3σ3.3\sigma7 template. Thus, the criticism is directed at the theoretical identification of the template, not at the numerical implementation or the underlying kSZ measurement.

The invalid treatment of the nonlinear correction

The problematic step appears in the treatment of the MOND square-root relation. The original analysis replaces an average of the transformed acceleration, schematically 3.3σ3.3\sigma8, with the square root of the averaged acceleration, 3.3σ3.3\sigma9, and assigns the neglected term to the three-point correlation function.

Melchiorri shows that this expansion is not controlled in the relevant regime. Expanding around the mean gives a leading correction proportional to the variance,

n=1n=10

not to the three-point function. Consequently, the correction is present even for a Gaussian field, for which the connected three-point function vanishes. The argument used in the Newtonian linear-theory derivation therefore cannot be transferred to a nonlinear square-root mapping.

There is also a scale-separation problem. The acceleration at a tracer is generated by the full surrounding density field, whereas the conditional mean acceleration induced by a partner at separations of n=1n=11–n=1n=12 is only a small shift. In the realizations considered by the comment, the ratio of the tracer acceleration rms to this conditional mean is approximately n=1n=13 at n=1n=14, n=1n=15 at n=1n=16, n=1n=17 at n=1n=18, and n=1n=19 at F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.0. The expansion parameter is therefore not small at any of the relevant separations.

The implication is direct: the radial shape used to exclude F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.1 is not obtained by consistently averaging the pointwise MOND acceleration law. It is generated by applying the nonlinear power to a conditional mean that is much smaller than the underlying local acceleration fluctuations.

Exact result for Gaussian fields with linearly biased tracers

The comment then analyzes a controlled model that closely matches the ingredients entering the published template. The density field is Gaussian and linear, the Newtonian acceleration is a linear functional of that field, and tracers are represented by linear bias weights,

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.2

The pair average is

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.3

For the nonlinear vector function

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.4

Gaussian integration by parts yields an exact relation between correlations involving F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.5 and correlations involving the original acceleration F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.6. Isotropy reduces the tensor derivative to a scalar coefficient,

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.7

with

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.8

The pair-averaged transformed acceleration therefore satisfies

F(g)∝g∣g∣n/2−1.\mathbf{F}(\mathbf{g})\propto \mathbf{g}|\mathbf{g}|^{n/2-1}.9

where g∝r−ng\propto r^{-n}0 is independent of separation. The result is exact within the stated Gaussian, linearly biased model for the considered range of g∝r−ng\propto r^{-n}1.

This is the key analytical finding. The correctly averaged nonlinear force law has the same radial shape as the Newtonian pairwise acceleration. Its dependence on g∝r−ng\propto r^{-n}2 appears only through a constant amplitude. Since the kSZ fit has a free amplitude degenerate with the mean optical depth g∝r−ng\propto r^{-n}3, that constant is not observable in the analysis. Within this model, the pairwise statistic consequently has no shape information with which to distinguish g∝r−ng\propto r^{-n}4 from g∝r−ng\propto r^{-n}5.

The result is stronger than a numerical indication that the published template is inaccurate: under the controlled assumptions, it proves that the entire g∝r−ng\propto r^{-n}6-dependent radial shape in the published construction is an artifact of taking the nonlinear power after the pair average.

Numerical validation beyond linear bias

The analytical result relies on Gaussianity and linear tracer bias, so the comment tests it numerically in more restrictive and more realistic tracer selections. Gaussian realizations of the Planck 2018 linear density field at g∝r−ng\propto r^{-n}7 are generated in periodic boxes of g∝r−ng\propto r^{-n}8 and g∝r−ng\propto r^{-n}9, with smoothing scales of n=1n=10, n=1n=11, and n=1n=12. Tracers are selected either through linear-bias weights or as density peaks above several thresholds. The MOND transformation is applied pointwise to the acceleration before pair differences and pair averaging are computed.

For linearly biased tracers, the ratio

n=1n=13

is constant to n=1n=14 peak-to-peak in the large box and n=1n=15 in the smaller box over n=1n=16–n=1n=17. The measured mean agrees with the analytical proportionality constant to n=1n=18.

Peak selection violates the assumptions of the exact derivation, yet the ratio remains nearly constant. For the fiducial selection, using a n=1n=19 box, F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.0 smoothing, and peaks above F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.1, the mean ratio agrees with the analytical constant evaluated at the tracers to F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.2. Across the tested selections and smoothing scales, deviations remain below approximately F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.3.

Figure 1

Figure 1: The correctly pair-averaged deep-MOND-to-Newtonian ratio remains nearly constant with separation, whereas the published F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.4 template predicts a variation by a factor of approximately F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.5.

This numerical behavior directly contrasts with the published F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.6 template. The latter predicts a radial variation by a factor of F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.7 over the same separation interval. The simulations therefore distinguish the two constructions sharply: the pointwise-transformed and then pair-averaged acceleration is nearly proportional to the Newtonian template, while the power of the pair-averaged Newtonian acceleration produces a strong and unsupported scale dependence.

Consequences for the reported significance

Melchiorri refits the kSZ data using the numerically measured ratio between the correctly averaged MOND and Newtonian accelerations. The resulting goodness of fit is effectively unchanged from the Newtonian case:

Template or selection Minimum F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.8
Newtonian template F(g)=a0g∣g∣.\mathbf{F}(\mathbf{g})=\sqrt{a_0}\frac{\mathbf{g}}{\sqrt{|\mathbf{g}|}}.9
Linear-bias corrected template rr0–rr1
Peak-selected corrected templates rr2–rr3
Published rr4 template rr5

Including the covariance of the simulated ratio changes the minimum rr6 by less than rr70.04rr80.07inthelarge−boxtests.</p><p>Thereported in the large-box tests.</p> <p>The reported r$9 exclusion of $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$0 therefore derives entirely from the radial shape of the published phenomenological template. Once the pair average is performed in the order required by the pointwise force law, the deep-MOND and Newtonian templates fit the data equally well in every controlled case examined. The claimed $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$1 future forecast is consequently not a forecast for a correctly specified MOND template; it is a rescaling of a significance generated by the same disputed template construction.

The comment carefully preserves a narrower interpretation of the published fit. The constraint $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$2 can remain valid as a constraint on the exponent of the phenomenological family

$\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$3

but it cannot be interpreted as a measurement of the exponent in the underlying pointwise force law. This distinction separates an empirical fit to a chosen template family from a physical test of gravity.

Scope and unresolved physical issues

The analytical and numerical results do not constitute a complete cosmological prediction for MOND. They establish the inconsistency of the template prescription under the assumptions examined and show that the published exclusion does not follow from the stated force law. Outside Gaussian fields and the tested tracer selections, exact proportionality is not guaranteed, although the numerical departures found here are small.

More fundamentally, the pointwise relation used in the original analysis is not itself a complete MOND calculation for a generic cosmological density field. The vanishing of the solenoidal component in the relation between Newtonian and MOND fields is guaranteed by special symmetries such as planar, cylindrical, or spherical symmetry, not by considering a finite number of sources or by imposing small primordial non-Gaussianity. A realistic halo acceleration is sourced by the full three-dimensional environment.

In addition, the observed pairwise velocity is a dynamical quantity. It requires solving the modified field equation and integrating the resulting acceleration through the cosmological growth history with specified initial conditions. Applying a modified acceleration relation at one epoch does not supply that velocity prediction. The comment also notes that the alternative prescription considered by Gallardo et al. is explicitly not the prediction of a MOND theory for any $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$4.

The principal open question is therefore specific: what pairwise kSZ signal follows from a fully specified relativistic or nonrelativistic modified-gravity theory, including its cosmological field equation, nonlinear environmental response, and growth history? The paper under discussion does not answer this question, and neither does the analysis it critiques.

Conclusion

Melchiorri’s comment identifies a noncommutativity error at the foundation of the claimed force-law constraint. Gallardo et al. apply the nonlinear transformation to a pair-averaged Newtonian acceleration, whereas the stated force law requires transforming the local acceleration before performing the pair average. In a Gaussian linear field with linearly biased tracers, the correctly ordered calculation is exactly proportional to the Newtonian result; simulations with peak-selected tracers preserve this proportionality to within roughly $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$5. Refitting the data then yields $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$6 for both the Newtonian and deep-MOND constructions, rather than $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$7 for the published $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$8 template. The reported $\langle X_n\rangle_{12}(r) = \left\langle \left[\mathbf{F}(\mathbf{g}_2)-\mathbf{F}(\mathbf{g}_1)\right] \cdot\mathbf{e}_{12} \right\rangle_{12}.$9 exclusion, and its projected $n/2$0 extension, therefore constrain a phenomenological template rather than the index of the underlying force law.

Whiteboard

Explain it Like I'm 14

1. What is this paper about?

This paper is a comment on an earlier study that tried to test the law of gravity on very large, cosmic distances.

The earlier study used the kinematic Sunyaev–Zeldovich (kSZ) effect to study how pairs of galaxies move toward or away from each other. It claimed that the usual Newtonian gravity law fits the data better than the “deep-MOND” alternative.

The usual gravity law can be written roughly as

g∝1r2,g \propto \frac{1}{r^2},

where gg is the strength of gravity and rr is distance. In this notation, the exponent is n=2n=2.

Deep-MOND uses a different behavior, approximately

g∝1r,g \propto \frac{1}{r},

so it corresponds to n=1n=1.

The earlier paper reported:

n=2.1±0.3,n = 2.1 \pm 0.3,

and said that n=1n=1 was ruled out at about 3.3 standard deviations, or “3.3σ3.3\sigma.”

This comment argues that the conclusion is not justified because the earlier study used the mathematical operations in the wrong order.


2. What questions does the paper ask?

The paper mainly asks:

  1. Did the earlier study build the correct prediction for how galaxies should move under a modified force law?
  2. Is the deep-MOND model really ruled out by the kSZ data?
  3. What happens if the force law is applied correctly, before averaging over many galaxy pairs?
  4. Does the data truly distinguish Newtonian gravity from deep-MOND in this test?

The author is not saying that MOND is definitely correct. Instead, the main point is that the earlier analysis did not make a fair or mathematically correct comparison.


3. What research methods were used?

The kSZ measurement

The earlier study used the kSZ effect to estimate the average relative motion of galaxy pairs.

The kSZ effect is a small change in the cosmic microwave background caused when microwave light passes through moving clouds of hot electrons. By studying this change near galaxies, scientists can estimate whether galaxies are moving toward or away from one another.

The galaxies in the study were separated by roughly 30 to 230 million light-years. Their motions can provide information about the forces that influence them.

The mathematical problem: average first or transform first?

The central issue is the difference between these two procedures:

  1. Average the ordinary Newtonian acceleration, then change it using the proposed force law.
  2. Change the acceleration at every location first, then average the results.

These are generally not the same when the transformation is nonlinear.

A simple analogy is averaging numbers before or after squaring them. For example:

  • Average first: the average of 2 and 4 is 3, and 32=93^2=9.
  • Square first: the average of 222^2 and 424^2 is (4+16)/2=10(4+16)/2=10.

So, in general,

⟨x2⟩≠⟨x⟩2.\langle x^2\rangle \neq \langle x\rangle^2.

The earlier study effectively used the second step incorrectly: it took an averaged Newtonian signal and then raised it to a power. But a real force law should act on the acceleration at each point in space, before the averaging is done.

The author’s calculations

The author used several approaches:

  • Analytical calculations: These are calculations done with equations. They considered a simplified universe where the matter distribution is described by a Gaussian random field and galaxies follow the matter distribution in a simple way.
  • Gaussian integration by parts: This is a mathematical rule for calculating averages involving related random quantities. It is similar in spirit to using known relationships between random variables to simplify a complicated average.
  • Computer simulations: The author generated artificial cosmic matter distributions based on the observed large-scale structure of the universe.
  • Different galaxy selections: The simulations used both simply weighted galaxies and galaxies selected as high-density “peaks,” which are more realistic locations for galaxies.
  • Refitting the real data: The author used the original study’s data and analysis pipeline, but replaced the disputed template with the correctly averaged one.

In the simulations, the modified force was applied to the acceleration at each simulated galaxy first. The pairwise averages were calculated only afterward.


4. What did the paper find?

The earlier calculation used the wrong template

The earlier study used a template that was essentially

Tn(r)∝∣⟨XN⟩∣n/2,T_n(r) \propto \left|\langle X_N\rangle\right|^{n/2},

where XNX_N represents the Newtonian acceleration between a pair of galaxies.

For deep-MOND, where n=1n=1, this makes the signal depend on the square root of the averaged Newtonian acceleration.

The comment argues that the correct calculation should instead average the transformed acceleration:

⟨Xn⟩=⟨transformed acceleration at each point⟩.\langle X_n\rangle = \left\langle \text{transformed acceleration at each point} \right\rangle.

These two expressions only automatically agree when the transformation is linear, such as in the ordinary Newtonian case.

The neglected correction was not a three-point effect

The earlier study treated the difference between the two calculations as if it came mainly from a three-point correlation, involving groups of three matter fluctuations.

The comment shows that this is incorrect. For a square-root transformation, the first important correction depends on the variance, which measures ordinary two-point fluctuations.

In simple terms, the earlier study ignored the fact that the acceleration varies greatly from place to place. This variation matters even if the matter field is otherwise statistically simple.

The author also points out that the expansion used by the earlier study was made around a very small average acceleration caused by a distant partner. However, the actual acceleration at a galaxy is affected by its entire surrounding environment. Therefore, the mathematical expansion was not a reliable approximation.

The correctly averaged result has almost the same shape as the Newtonian result

In the simplified Gaussian model, the author finds that the correctly averaged modified-force signal is exactly proportional to the Newtonian signal:

⟨Xn⟩12(r)=Cn⟨XN⟩12(r),\langle X_n\rangle_{12}(r) = C_n \langle X_N\rangle_{12}(r),

where CnC_n is a constant that depends on the force law.

This means that the two theories predict the same dependence on galaxy separation. They differ only by an overall size or amplitude.

However, the amplitude was already allowed to vary freely in the original data analysis because of uncertainty in quantities such as the average optical depth of the gas around galaxies. Therefore, this constant difference cannot be used to distinguish the theories.

The simulations support the analytical result

The simulations found that the ratio between the modified-gravity and Newtonian predictions was nearly constant with distance:

  • For the simplest galaxy model, the variation was less than about 1%.
  • For more complicated, peak-selected galaxies, the variation was usually below about 2%.

This is very different from the disputed template used in the earlier study. For that template, the predicted shape changed by a factor of about 3.3 across the range of separations.

The data no longer reject deep-MOND

When the author refitted the original data using the correctly averaged template, the results were approximately:

  • Correctly averaged modified-gravity template: χ2≈20.1\chi^2 \approx 20.1–$20.2$
  • Newtonian template: χ2≈20.1\chi^2 \approx 20.1
  • Original deep-MOND template: χ2≈33.8\chi^2 \approx 33.8

A lower χ2\chi^2 generally means a better fit. The correctly averaged deep-MOND prediction fits almost exactly as well as the Newtonian prediction.

Therefore, according to this comment, the data do not distinguish between n=1n=1 and n=2n=2 in this analysis.


5. Why are these findings important?

The original paper’s claim that deep-MOND was excluded came almost entirely from the predicted shape of its template—the way the signal changed with galaxy separation.

But the comment argues that this shape was created by taking the power of an average, rather than averaging the force law correctly. In other words, the apparent disagreement with MOND may be caused by a mathematical mistake in constructing the prediction.

This means the reported result

n=2.1±0.3n = 2.1 \pm 0.3

does not necessarily measure the true exponent of a physical force law. It measures the exponent of a particular mathematical template that may not correspond to the force law described in the earlier paper.

The forecast that future surveys could exclude deep-MOND at the level of 10σ10\sigma also becomes unreliable, because it was based on the same incorrect template.


6. What does the paper say about MOND itself?

The author is careful to limit the conclusion.

The paper does not prove that MOND is correct. It only shows that the earlier test did not properly calculate the MOND prediction.

A complete MOND prediction would require:

  • A full physical equation describing the gravitational field, not just a simple point-by-point rule.
  • The effects of the entire matter distribution around each galaxy.
  • The history of how cosmic structures grew over time.
  • The initial conditions of the universe.
  • A calculation of how modified gravity affects galaxy velocities, not just accelerations.

The earlier study did not provide all of these ingredients.

Conclusion

The paper’s main message is:

The earlier study applied the modified force law after averaging the gravitational signal, but it should have applied the force law first and averaged afterward.

Because of this mistake, the earlier study produced a strong difference between Newtonian gravity and deep-MOND that may not be physically real. When the calculation is done in the correct order, both models produce almost the same prediction for the galaxy-pair signal, and both fit the data equally well.

The kSZ effect could still become a useful way to test gravity on very large scales. However, future studies must use predictions that come from a complete and physically consistent theory of gravity.

Practical Applications

Immediate Applications

The paper is primarily a methodological critique rather than a technology-development study. Its most immediate value is therefore in correcting analyses, preventing overinterpretation, and improving the design of cosmological inference workflows.

  • Reanalyze existing kSZ constraints on modified gravity (cosmology, astrophysics; deployable now). Replace templates of the form

Tn(r)∝∣⟨XN⟩12(r)∣n/2T_n(r)\propto |\langle X_N\rangle_{12}(r)|^{n/2}

with templates that first apply the nonlinear force mapping pointwise and then perform the pair average:

⟨Xn⟩12=⟨[F(g2)−F(g1)]⋅e12⟩12.\langle X_n\rangle_{12} = \left\langle [\mathbf F(\mathbf g_2)-\mathbf F(\mathbf g_1)]\cdot\mathbf e_{12} \right\rangle_{12}.

This can be implemented immediately in existing kSZ analysis pipelines using simulated acceleration fields, tracer catalogs, and pairwise estimators.

Dependency: The acceleration field must be modeled consistently with the proposed force law, and the transformation must be applied before pair averaging. The paper’s near-degeneracy result is demonstrated for Gaussian or approximately controlled tracer models, not established universally.

  • Audit published claims about modified-gravity exclusions (academic peer review, reproducibility; deployable now). The paper provides a general diagnostic: whenever a nonlinear physical law is involved, analysts should test whether they have replaced the average of a transformed field with the transformation of an average. This audit can be applied to kSZ, galaxy clustering, weak lensing, peculiar-velocity, and large-scale-structure analyses.

Dependency: The relevant observable and transformation must be written explicitly at the field level. Agreement between a phenomenological template and the data is not sufficient to establish that the template follows from the underlying theory.

  • Update uncertainty assessments and survey forecasts (cosmology and survey planning; deployable now). Forecasts based on the reported 3.3σ3.3\sigma exclusion of the deep-MOND value and its projected 10σ10\sigma extension should be recomputed. Increasing the number of galaxies cannot recover discriminatory power if the competing physical models produce effectively identical pairwise templates after correct averaging.

Dependency: Forecasts must include model-template uncertainty, nonlinear tracer selection, covariance from simulations, and possible degeneracies with the mean optical depth τˉ\bar{\tau}.

  • Use simulation-based template validation as a standard workflow (scientific software and computational astrophysics; deployable now). A practical pipeline could:
    1. generate density and acceleration fields;
    2. apply the candidate force law at every tracer;
    3. construct pair differences;
    4. average over tracer pairs;
    5. compare the resulting radial shape with the proposed analytic template.

The paper’s use of Gaussian realizations, peak-selected tracers, smoothing-scale variations, and multiple box sizes provides a directly reusable validation protocol.

Dependency: Simulations must reproduce the relevant power spectrum, tracer bias, smoothing scale, selection function, survey geometry, and redshift evolution.

  • Treat the fitted amplitude–optical-depth degeneracy explicitly (kSZ data analysis; deployable now). Since the proportionality constant CnC_n can be absorbed into the fitted amplitude or mean optical depth, analyses should avoid interpreting amplitude-independent shape differences as evidence for a force law unless those differences survive a physically correct forward model.

Dependency: Independent calibration of optical depth, baryonic gas physics, and galaxy–halo relations may be required to recover information from the amplitude.

  • Improve graduate training and methodological guidance in statistics and physics (academia; deployable now). The paper offers a concrete example for teaching:

⟨f(X)⟩≠f(⟨X⟩)\langle f(X)\rangle\neq f(\langle X\rangle)

for nonlinear ff. It can be used in courses and research training on perturbation theory, Gaussian random fields, statistical inference, and reproducible computational physics.

Dependency: The example should be presented as a warning about model construction, not as a general proof that modified gravity is indistinguishable from Newtonian gravity.

  • Inform policy and research-funding decisions about evidential strength (science policy; deployable now). Funding agencies, review panels, and survey collaborations can classify the claimed exclusion as requiring reanalysis before it is used to prioritize one gravity model over another. The paper demonstrates that a nominally high-significance result can be driven by an invalid mapping between a theory and its observable template.

Dependency: The critique itself must be independently checked against the original data, covariance, code, and any non-Gaussian or nonlinear effects absent from the controlled tests.

  • Daily-life applications are essentially absent (consumer technology and ordinary daily activity). The findings do not directly produce a consumer product, medical intervention, household technology, or operational service. Their indirect everyday relevance is limited to supporting reliable public scientific conclusions and preventing exaggerated claims about cosmological theories.

Long-Term Applications

The paper identifies several research directions that could eventually enable robust tests of gravity on cosmological scales, but these require theory development, simulations, and new observational analyses.

  • Develop theory-consistent cosmological predictions for MOND-like or other modified-gravity models (theoretical cosmology; long-term). A valid prediction for the pairwise kSZ signal requires a complete field equation, including effects such as the solenoidal or curl component discussed in the paper, rather than a pointwise algebraic mapping between Newtonian and modified accelerations.

A future framework would need to specify: - the gravitational field equation; - boundary conditions and cosmological background; - baryonic and dark-matter components, where applicable; - nonlinear field solutions around halos; - the evolution of perturbations and peculiar velocities.

Dependency: Different modified-gravity theories can share the same static force-law scaling while predicting different cosmological growth histories and kSZ signals.

  • Build end-to-end modified-gravity simulations (high-performance computing, astrophysics; long-term). Large-volume simulations could evolve the density field and velocity field under a theory-specific modified-gravity equation, generate halos and galaxies, model gas pressure and electron optical depth, and produce synthetic microwave maps. These simulations would replace the paper’s controlled Gaussian tests with realistic nonlinear environments.

Dependency: The simulations must resolve halo-scale environments, account for baryonic feedback, and reproduce galaxy selection and redshift distributions. Numerical solvers for nonlinear field equations may be computationally expensive.

  • Construct forward models linking gravity to the full kSZ observable (observational cosmology; long-term). Future analysis tools could jointly model:

gravity→density growth→velocities→electron distribution→kSZ temperature.\text{gravity}\rightarrow\text{density growth}\rightarrow\text{velocities} \rightarrow\text{electron distribution}\rightarrow\text{kSZ temperature}.

Such models would distinguish a genuine force-law effect from changes in galaxy bias, optical depth, feedback, and velocity reconstruction.

Dependency: The kSZ signal depends on ionized gas and electron weighting, not only on gravitational acceleration. Better astrophysical calibration is therefore essential.

  • Combine kSZ with complementary probes of gravity (cosmology; long-term). A robust modified-gravity program could combine pairwise kSZ with weak lensing, galaxy–galaxy lensing, redshift-space distortions, peculiar velocities, cluster dynamics, and cosmic microwave background observations. Joint analyses may separate changes in the velocity field from changes in the matter distribution or optical depth.

Dependency: The probes must be modeled within the same theory and cosmological parameterization. Combining inconsistent phenomenological templates could amplify rather than resolve systematic errors.

  • Develop model-independent tests of nonlinear averaging and tracer selection (statistics and computational science; long-term).
    • non-Gaussian initial conditions;
    • nonlinear density evolution;
    • assembly bias;
    • halo occupation models;
    • redshift-dependent selection;
    • anisotropic environments;
    • different smoothing scales.

The resulting tools could quantify when the pair-averaged transformed field is shape-degenerate with the Newtonian template and when measurable deviations appear.

Dependency: Percent-level conclusions require substantially larger simulation ensembles and carefully propagated cosmic variance, finite-volume, and selection uncertainties.

  • Design future surveys around identifiable shape differences rather than nominal sample size (survey engineering and policy; long-term).
    • broader redshift coverage;
    • multiple tracer populations;
    • independent optical-depth calibration;
    • improved angular resolution;
    • cross-correlation with lensing and velocity data;
    • environments where competing theories predict genuinely different responses.

Dependency: Survey optimization requires a validated theory-specific forecast rather than extrapolation from an incorrect template family.

  • Create reproducibility and template-audit software packages (scientific software; long-term).
    • whether nonlinear transformations are applied before averaging;
    • whether a template follows from a specified field equation;
    • whether nuisance amplitudes absorb theoretically relevant parameters;
    • how tracer selection changes the predicted radial shape;
    • whether forecast significance is robust to template uncertainty.

Dependency: Such a tool would need standardized data formats, access to simulation outputs, transparent covariance estimation, and integration with existing survey pipelines.

  • Establish a general framework for theory-to-observable validation (multiple scientific sectors, especially computational physics; long-term). Beyond modified gravity, the paper’s central lesson can inform any domain where nonlinear physical laws are inferred from averaged data—for example, plasma physics, fluid turbulence, geophysics, and networked dynamical systems. A general workflow would require deriving the observable from the pointwise or microscopic law before applying ensemble, spatial, or pair averaging.

Dependency: The usefulness of this broader application depends on identifying observables where averaging-order errors can produce statistically significant but physically spurious claims.

Glossary

  • AQUAL: A relativistic formulation of Modified Newtonian Dynamics based on a nonlinear gravitational field equation. “u=gN+∇×h\mathbf u=\mathbf g_N+\nabla\times\mathbf h in AQUAL”
  • Atacama Cosmology Telescope (ACT): A ground-based telescope used to observe the cosmic microwave background. “fit a family of velocity templates labelled by the index nn of a force law g∝r−ng\propto r^{-n}, obtain n=2.1±0.3n=2.1\pm0.3, and exclude the deep-MOND value n=1n=1 at 3.3σ3.3\sigma”
  • Baryonic acceleration: The gravitational acceleration produced by ordinary matter, excluding dark matter. “where GbG_b is the dimensionless baryonic (Newtonian) acceleration”
  • Conditional average: An average calculated subject to a specified condition, such as two tracers being separated by a given distance. “the conditional average is taken”
  • Conditional mean shift: The change in the expected value of a field caused by conditioning on another object or event. “No expansion in the conditional mean shift and no assumption about the conditional distribution are involved.”
  • Cosmological growth history: The time-dependent evolution of density perturbations and cosmic structure. “The observed pairwise velocity requires integrating the modified dynamics over the growth history”
  • Deep-MOND: The low-acceleration regime of Modified Newtonian Dynamics in which the gravitational response differs substantially from Newtonian gravity. “which for deep MOND is F(g)=a0 g/∣g∣\mathbf F(\mathbf g)=\sqrt{a_0}\,\mathbf g/\sqrt{|\mathbf g|}”
  • Gaussian field: A random field whose values follow a multivariate Gaussian probability distribution. “it does not vanish for a Gaussian field with ζ≡0\zeta\equiv0”
  • Gaussian integration by parts: An identity for evaluating correlations involving jointly Gaussian variables and derivatives of functions. “For jointly Gaussian variables, Gaussian integration by parts (Stein's identity~\cite{Stein1981}) gives”
  • Gaussian linear density field: A density-contrast field modeled as Gaussian and described by linear perturbation theory. “a Gaussian linear density field δ\delta (smoothed on the tracer scale)”
  • Gravitational acceleration field: A vector field describing the acceleration generated by a gravitational source distribution. “The deep-MOND map is applied pointwise to the Newtonian acceleration of each tracer”
  • Infall: The inward relative motion of matter under gravity. “the sign of the infall (⟨XN⟩12<0\langle X_N\rangle_{12}<0) is carried by the fitted amplitude”
  • Isotropy: Invariance under rotations, meaning that no spatial direction is statistically preferred. “with, by isotropy,”
  • Kinematic Sunyaev–Zeldovich (kSZ) effect: A cosmic microwave background temperature shift caused by CMB photons scattering from moving free electrons. “measure the mean pairwise velocity of SDSS BOSS galaxies through the kSZ effect”
  • Linear bias: An approximation in which tracer-density fluctuations are proportional to underlying matter-density fluctuations. “tracers of linear bias bb”
  • Linear theory: An approximation that treats density and velocity perturbations as small enough that their governing equations can be linearized. “the linear-theory expression in terms of ξgg\xi_{gg}”
  • Mean optical depth: The average Thomson-scattering optical depth associated with the observed tracer population. “The constant CnC_n is therefore unobservable. With the exact proportionality~(\ref{eq:prop}) the deep-MOND and Newtonian templates give the same χ2\chi^2 by construction.”
  • Modified Newtonian Dynamics (MOND): A proposed modification of gravitational dynamics at very low accelerations. “What a self-consistent MOND cosmology predicts for this observable is a separate question”
  • Non-Gaussianity: Statistical dependence among higher-order moments of a field beyond what is captured by a Gaussian distribution. “Constraints on primordial non-Gaussianity, invoked in the Letter at this point, have no bearing on it.”
  • Pairwise kSZ signal: A kSZ observable measuring the average relative motion of pairs of tracers. “The pairwise kSZ effect may yet become a powerful probe of gravity on cosmological scales”
  • Peak-selected tracers: Objects selected because they correspond to high-density peaks in a smoothed density field. “For the peak-selected tracers, to which the derivation does not apply”
  • Phenomenological template: A parametrized model used to fit observations without necessarily being derived from a complete physical theory. “The constraint n=2.1±0.3n=2.1\pm0.3 survives as a statement about the exponent of the phenomenological family~(\ref{eq:wrong})”
  • Primordial non-Gaussianity: Deviations from Gaussian statistics in density fluctuations originating in the early universe. “Constraints on primordial non-Gaussianity”
  • Profile likelihood: A likelihood or equivalent fit statistic evaluated after optimizing nuisance parameters for each value of a parameter of interest. “Δχ2=12.5\Delta\chi^2=12.5 at n=1n=1 along the profile”
  • Solenoidal term: A divergence-free component of a vector field. “planar, cylindrical, or spherical symmetry are sufficient conditions for the solenoidal term to vanish”
  • Stein’s identity: A Gaussian expectation identity relating a variable-function correlation to a derivative expectation. “Gaussian integration by parts (Stein's identity~\cite{Stein1981})”
  • Three-point function: A statistical measure of correlations among three positions or field values. “attributes the correction to the three-point function ζ\zeta”
  • Tracer bias: The difference between the clustering of observed tracers and that of the underlying matter distribution. “Gaussian linear field with linearly biased tracers”
  • Two-point quantity: A statistical quantity determined by correlations between pairs of field values or positions. “its leading correction, −⟨(g−⟨g⟩)2⟩/8⟨g⟩3/2-\langle(g-\langle g\rangle)^2\rangle/8\langle g\rangle^{3/2}, is a two-point quantity”
  • Velocity template: A model prediction for the scale-dependent velocity signal used in fitting observational data. “fit a family of velocity templates labelled by the index nn of a force law g∝r−ng\propto r^{-n}”
  • Weak-field acceleration regime: A regime in which gravitational accelerations are sufficiently small for modified-gravity effects to become important. “The physical acceleration at the tracers has rms $1.7\times10^{-12}\,\mathrm{m\,s^{-2}$, well inside the deep-MOND regime.”
  • Wiener-process-like realization: A numerical sample generated from a specified statistical random field model. “Six realizations of the 1280-Mpc box and two of the 960-Mpc box are used”
  • χ2\chi^2 statistic: A goodness-of-fit measure comparing observed data with model predictions. “refitting the data of the Letter with its pipeline and covariance”
  • ζ\zeta three-point correlation function: A three-point correlation statistic describing non-Gaussian or higher-order clustering. “where ζ\zeta vanishes at linear order”

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