Line-of-sight acceleration as a test of the Galactic Yukawa potential

Davi C. Rodrigues; Felipe A. da Silva Barbosa; Luca Amendola; Roberto Capuzzo-Dolcetta

REVIEW 3 major objections 4 minor 32 references

Line-of-sight acceleration as a test of the Galactic Yukawa potential

T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read A forecast finds that 136,000 RR Lyrae stars measured at 10 cm/s/decade can recover the Milky Way's Yukawa parameters as tightly as rotation-curve data, while globular clusters need sub-cm/s precision.

desk verdict Conditional forecast that RR Lyrae LOS accelerations at 10 cm/s/decade can match rotation-curve Yukawa constraints; worth a referee, but the fixed-baryon assumption is the main caveat. read the letter →

arxiv 2506.24002 v1 pith:FLPDVB7V submitted 2025-06-30 astro-ph.GA

Felipe A. da Silva Barbosa , Luca Amendola , Davi C. Rodrigues , Roberto Capuzzo-Dolcetta This is my paper

classification astro-ph.GA

keywords line-of-sightaccelerationYukawapotentialmodifiedgravityRRLyraestarsglobularclustersMilkyWayrotationcurveparameterforecastMCMC

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper forecasts whether direct line-of-sight acceleration measurements — made by comparing two high-precision radial-velocity readings of the same star taken a decade apart — can pin down a Yukawa-type (fifth-force) correction to the Newtonian gravitational potential in the Milky Way. Using a Galactic model of a bulge, two disks, and an NFW dark-matter halo, the paper fits the rotation curve to fix fiducial parameters, then simulates acceleration measurements for 165 globular clusters and 136,000 RR Lyrae stars. The central result is that RR Lyrae stars at about 10 cm/s per decade of precision — the level expected from next-generation spectrographs — recover the Yukawa strength and range, $\beta = -3.98^{+0.33}_{-0.37}$ and $\log_{10}\lambda = -0.10^{+0.03}_{-0.03}$, plus the halo parameters, as tightly as rotation-curve analysis; the same precision fails for globular clusters, which need better than 0.6 cm/s per decade to compete. If the forecast holds, a decade-long spectroscopic campaign on RR Lyrae stars would give an independent, equilibrium-free test of modified gravity in the dark matter-baryon interaction.

What carries the argument

The load-bearing object is the Yukawa-corrected dark-matter potential for a spherical NFW halo, $\Psi_{\rm dm}(r) = \Psi_{\rm dm,N}(r) + \Psi_{\rm dm,Y}(r)$, where $\Psi_{\rm dm,Y}$ is built from exponential-integral functions and carries the two free parameters $\beta$ (fifth-force coupling strength) and $\lambda$ (interaction range). Added to a Plummer bulge and two exponential disks, this gives the total potential $\Psi_T$; the observable is the line-of-sight acceleration $a_{\rm los} = -\hat{u}\cdot\nabla\Psi_T(r)$, the projection of the Galactic-frame acceleration onto the solar-system line of sight. The forecast then contrasts MCMC posteriors from a Gaussian acceleration likelihood against the posterior from rotation-curve data, with fiducial parameters taken from the rotation-curve fit. The main lever is target number: 165 globular clusters cannot beat a 10 cm/s/decade noise floor, while binning $1.36\times10^5$ RR Lyrae stars in $(r, \cos\alpha)$ makes the same noise level competitive.

What would settle it

Re-run the forecast while marginalizing over the baryonic model parameters with their published uncertainties; if the recovered $1\sigma$ intervals on $\beta$ and $\log_{10}\lambda$ widen by more than a factor of about two relative to Eq. (4.6), the claimed competitiveness of 10 cm/s/decade RR Lyrae data does not survive baryonic uncertainty.

Watch

Extended reading notes

Core claim

The paper claims that a population of roughly $1.3\times10^5$ RR Lyrae stars, each measured twice a decade apart at 10 cm/s/decade radial-velocity precision, yields line-of-sight acceleration posteriors on the Yukawa parameters ($\beta$, $\lambda$) that are as tight as — and for the Yukawa parameters tighter than — those from the Milky Way rotation curve, with the specific forecast $\beta = -3.98^{+0.33}_{-0.37}$ and $\log_{10}\lambda = -0.10^{+0.03}_{-0.03}$ (Eq. 4.6). For the 165 globular clusters the same precision produces prior-dominated posteriors; a precision better than 0.6 cm/s/decade is needed to match the rotation-curve constraints on the modified-gravity parameters. Because the Yukawa correction decays exponentially, the discriminating power concentrates near the Galactic center, where about 100 RR Lyrae stars show Newtonian-versus-Yukawa acceleration differences above 10 cm/s/decade; these are the natural targets for a direct search.

Load-bearing premise

The forecast assumes the baryonic mass distribution — the bulge and disk masses and scale lengths, taken from a single published model — is exactly known and not marginalized over, even though the Yukawa parameters are degenerate with the total mass.

Editorial extensions

If this is right

Combining rotation-curve and line-of-sight acceleration data would break degeneracies between the Yukawa and halo parameters, because the two data sets have different degeneracy directions.
A dedicated RR Lyrae program at next-generation spectrograph precision would determine $\beta$ to about 10% and $\log_{10}\lambda$ to about 30% from line-of-sight accelerations alone, independent of rotation-curve assumptions.
Globular clusters are not viable targets for this test at 10 cm/s/decade; the sub-cm/s precision required makes them a lower priority than the abundant RR Lyrae population.
The strongest discriminating signal comes from the innermost targets ($r \lesssim 1$ kpc), so future surveys should concentrate on the high-acceleration RR Lyrae stars near the Galactic center.
Because line-of-sight accelerations are measured directly from redshifts, they probe the potential without assuming dynamical equilibrium, complementing rotation-curve and Jeans analyses.

Reading between the lines

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

The quoted 10% and 30% uncertainties likely understate the real measurement error: marginalizing over the baryonic model would show how much constraining power survives, in line with the paper's own stated limitations.
Measuring only the roughly 100 RR Lyrae stars with the largest Newtonian-versus-Yukawa differences might capture most of the signal, since the difference decays exponentially with radius; the paper does not quantify this reduced-sample trade-off.
If an actual measurement found $\beta$ consistent with zero, the same dataset would set a tight direct constraint on the baryon-dark-matter fifth-force coupling on Galactic scales; if it found $\beta \approx -4$, it would motivate cross-checks with laboratory and cosmological fifth-force bounds.
The same target-selection logic — choosing stars with the largest predicted acceleration differences between theories — transfers directly to other modified-gravity models, such as MOND-like alternatives, turning this forecast into a general framework for acceleration-based gravity tests.

Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

Short take: this is a legitimate, carefully done conditional forecast, not a measurement. If you accept the model, the headline result holds: 1.3e5 RR Lyrae stars at 10 cm/s/decade should pin down the Yukawa coupling beta to about ±0.35, roughly an order of magnitude better than the rotation-curve posterior. Globular clusters need about 0.6 cm/s/decade to become competitive. That GC-vs-RR Lyrae difference is the paper's real contribution and a useful guide for designing radial-velocity programs.

What's good: the authors use full MCMC posteriors rather than Fisher forecasts, which matters because the rotation-curve posteriors for beta and lambda are non-Gaussian. The spherical NFW + Yukawa potential treatment is correct and follows the earlier rotation-curve work. The globular cluster sample is standard, and the Gaia DR3 RR Lyrae sample is well motivated. The paper is honest about what it omits: deviations from spherical symmetry, baryonic modeling uncertainties, and perspective acceleration are all stated up front.

The soft spots: the forecast assumes the baryonic disk and bulge masses are exact. In a real analysis you would marginalize over them, and since beta and log lambda are degenerate with the total mass profile, the quoted 1-sigma intervals are optimistic. That is not fatal for the relative comparison between tracers, but the absolute statement "10 cm/s/decade is enough" should be read as "enough under this specific baryonic model." Also the fiducial beta = -4 is the best fit, whereas the rotation-curve posterior median is -7; the forecast is conditioned on that choice, and a robustness check with a different fiducial would strengthen it. Minor: Eq. (4.6) and the text say "30% constraint" for lambda, but a width of ±0.03 in log10 lambda is about 7% in linear lambda; something is off in that sentence.

Who it's for: people planning next-generation spectrograph surveys or testing modified gravity in the Milky Way. The precision thresholds are useful. It deserves a serious referee; the main requested changes would be a baryonic-marginalization check or at least an explicit estimate of how much the intervals would broaden, plus a corrected Section 5. I'd send it to review.

Referee Report

3 major / 4 minor

Summary. The paper presents a forecasting study of line-of-sight (LOS) acceleration measurements of Milky Way targets as a test of a Yukawa correction to the Newtonian potential. The authors first fit a baryonic model plus an NFW dark halo, with and without the Yukawa term, to Galactic rotation-curve data, obtaining fiducial parameters. They then simulate LOS accelerations for 165 globular clusters and about 1.3e5 RR Lyrae stars, add Gaussian noise with assumed precision sigma_a, and run MCMC forecasts. They find that globular clusters require sigma_a of about 0.6 cm/s/decade or better to match rotation-curve constraints, while RR Lyrae stars with sigma_a = 10 cm/s/decade yield beta = -3.98+0.33/-0.37 and log10 lambda = -0.10+0.03/-0.03, comparable to or better than the rotation-curve posteriors for the Yukawa parameters.

Significance. If the forecast is correct at face value, the paper identifies a promising observational route: a large RR Lyrae sample with decade-baseline radial velocities could provide an independent, direct-acceleration constraint on modified-gravity parameters that is substantially tighter than current rotation-curve constraints on beta and lambda. The paper's strengths include using full MCMC rather than Fisher forecasts, testing a range of assumed precisions, and comparing two target populations. It also identifies specific targets, five globular clusters and about one hundred RR Lyrae stars, with large Newtonian-versus-Yukawa acceleration differences. The main caveat is that the quantitative result is conditional on a fixed baryonic model and on a binned RR Lyrae likelihood that is not fully specified; the paper acknowledges but does not propagate baryonic uncertainties.

major comments (3)

[Section 4.3] The Yukawa RR Lyrae forecast is the central positive result, but the analysis is performed on data binned in log r and cos(alpha) without specifying the binned likelihood. Equation (4.1) is written for individual targets; no equation defines the observable, weights, or scatter of each bin, and no validation is shown that the binning recovers the input parameters in a controlled test. As written, the posteriors in Table 2 and Eq. (4.6) are not reproducible. Please provide the exact binned likelihood and demonstrate, for example on a subset by comparing unbinned and binned analyses, that the binning does not bias the recovered beta and log10 lambda.
[Section 1 and Section 4.1] The forecast fixes the bulge and disk masses and scale lengths to the single model in Table 1, and Section 1 explicitly excludes "uncertainties in the baryonic modeling of the bulge and disk." Because beta and lambda are degenerate with the total mass budget, the quoted 1-sigma intervals in Table 2 and Eq. (4.6) are conditional on the baryonic model being exact and likely understate the error budget of a real measurement. I request either marginalization over baryonic parameters with plausible priors, at least for the RR Lyrae forecast, or a clear statement that the reported constraints are sensitivity forecasts for a fixed baryonic model rather than predictions of the total measurement power.
[Section 4.3 and Table 2] The RR Lyrae forecast uses fiducial beta = -4 (Eq. 4.2), which is the rotation-curve best fit, while the rotation-curve posterior median is beta = -7.04 (Table 2). Since the amplitude of the Yukawa signal depends on beta, the headline conclusion that sigma_a = 10 cm/s/decade is sufficient should be checked at the posterior median or at several points within the posterior. Without such a robustness test, Eq. (4.6) is a forecast tied to one particular, non-median parameter choice.

minor comments (4)

[Eq. (4.6) and Table 2] In Eq. (4.6) the second result is written as lambda = -0.1+0.03/-0.03, but lambda has units of kpc and cannot be negative; this should be log10(lambda/kpc) or log10 lambda, consistent with Table 2.
[Eq. (3.8c)] The expression for Psi_dm,Y appears garbled in the typeset version: the last factor seems to contain a product of two exponential-integral functions. Please correct the typesetting and verify the formula against reference [18].
[Section 4.1] Please clarify whether sigma_a denotes the acceleration uncertainty over a one-decade baseline or is derived from per-epoch radial-velocity errors; two radial-velocity measurements with sigma_v = 10 cm/s separated by one decade give sigma_a approximately sqrt(2)*sigma_v per decade, about 14 cm/s/decade, rather than 10 cm/s/decade.
[Figure 10] The legend inside the right panel of Figure 10 says "GC" but the text and caption describe the RR Lyrae sample; please correct the legend to avoid confusion.

Circularity Check

0 steps flagged · score 2.0 of 10

Conditional sensitivity forecast with a minor non-load-bearing self-citation; no circular reduction of the central claim.

full rationale

The paper is a forecasting exercise, not a circular derivation. The authors first fit the Milky Way rotation curve to obtain fiducial parameters (Section 3.3, Eq. 4.2), then simulate future LOS acceleration data from those fiducial values using Eq. 3.3 and the Gaussian likelihood in Eq. 4.1, and finally MCMC-recover the parameters and compare posterior widths with the rotation-curve posteriors. The simulated LOS likelihood depends only on the fiducial model and the assumed noise level, not on the rotation-curve data itself, so the comparison is a conditional sensitivity forecast rather than a fitted input being renamed as a prediction. The reported RR Lyrae values in Eq. 4.6, beta = -3.98+0.33/-0.37 and log10 lambda = -0.10+0.03/-0.03, are the median and 1-sigma width of a mock posterior centered near the fiducial point (beta = -4, log10 lambda = -0.1); the paper explicitly labels these as 'forecast' constraints in Sections 2 and 5. The only notable self-citation with author overlap is Ref. [18] (Amendola is a coauthor), which supplies the Yukawa potential form, the priors, and the rotation-curve minimum uncertainty floor; however, the Yukawa correction also derives from Refs. [15,16], and the LOS acceleration forecast itself is new and self-contained. The fixed baryonic model (Pouliasis et al. Model I) and the exclusion of baryonic uncertainties are stated limitations in Section 1, but this affects robustness and systematic error, not circularity. No step in the derivation is equivalent to its inputs by construction.

Assumptions & free parameters 5 free parameters · 6 assumptions · 0 invented entities

The forecast rests on a fixed baryonic template and a set of model parameters fitted to rotation curve data. No new entities are postulated; the Yukawa correction and NFW halo are imported from prior literature. The main free quantities are the halo/Yukawa parameters and the RR Lyrae binning scheme.

free parameters (5)

NFW log10 rho_s = 7.28 (fiducial; M_sun/kpc^3)
Fitted to Galaxy rotation curve data and used as fiducial for the LOS acceleration forecast.
NFW log10 r_s = 1.03 (fiducial; kpc)
Fitted to rotation curve data and used as fiducial.
Yukawa coupling beta = -4 (fiducial; rotation curve MCMC median is -7.04)
Fiducial value from best fit to rotation curve; forecast constraints depend on this choice.
Yukawa range log10 lambda = -0.1 (fiducial; kpc)
Fiducial value from rotation curve best fit; forecast constraints depend on this choice.
RR Lyrae binning scheme = radial multiplicative step 1.1, cos(alpha) bin width 0.04
Chosen by hand for computational cost; alters the effective likelihood for RR Lyrae data.

assumptions (6)

domain assumption The Galaxy's gravitational potential is modeled as spherical bulge + thin and thick exponential disks + spherical NFW halo.
Invoked in Section 3; the entire forecast inherits this modeling choice.
domain assumption Baryonic masses and scale lengths are fixed to the Pouliasis et al. (2017) Model I values without uncertainty.
Section 3.1, Table 1; the paper acknowledges baryonic modeling uncertainty but does not include it in posteriors.
domain assumption The dark matter halo is spherically symmetric for the LOS acceleration difference, giving delta|a_los| proportional to cos(alpha).
Used in Eq. (4.4) to reduce the acceleration difference; deviations from sphericity are listed but not modeled.
domain assumption Rotation curve data (Eilers et al. 2019, galkin) with r > 5 kpc and at least 5% velocity error are adequate for the fiducial fit.
Section 3.3; these cuts are inherited from [18] and affect the fiducial Yukawa parameters.
domain assumption The LOS acceleration measurement is the radial acceleration -hat(u) dot grad Psi_T, with no Sun orbital term or perspective acceleration; real observations can correct for these.
Eq. (3.3), stated in Section 2; the forecast assumes the corrected observable equals the model acceleration.
domain assumption Flat priors in the ranges of Eq. (3.11) and Gaussian likelihood in Eq. (4.1) give unbiased posteriors for the forecast.
Sections 3.3 and 4.1; prior choices matter for the non-Gaussian beta/lambda parameters.

how reviews work

0 comments

Cite this review

Pith. "Pith review of Line-of-sight acceleration as a test of the Galactic Yukawa potential." pith.science (2026). https://pith.science/paper/FLPDVB7V

@misc{pith2026250624002,
  author       = {Pith},
  title        = {Pith review of: Line-of-sight acceleration as a test of the Galactic Yukawa potential},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FLPDVB7V}},
  note         = {Machine review of arXiv:2506.24002}
}

abstract

We forecast the impact of direct radial acceleration measurements, based on two redshift measurements of the same target one decade apart, on constraining the Yukawa correction to the Newtonian potential in the Milky Way. The Galaxy's matter distribution is modeled as the sum of a spherical bulge, a spherical dark matter halo, and two axially symmetric disks. Considering a sample of 165 Milky Way globular clusters, we find that the precision of next-generation spectrographs ($\sim$ 10 cm s$^{-1}$) is not sufficient to provide competitive constraints compared to rotation curve data using the same baryonic matter distribution. The latter sample only becomes competitive for a precision better than 0.6 cm s$^{-1}$. On the other hand, we find that adopting a population of $1.3 \times 10^5$ RR Lyrae stars as targets, a precision of $\sim$ 10 cm s$^{-1}$ can achieve constraints on the Yukawa parameters as strong as with the rotation curves.

Figures

Figures reproduced from arXiv: 2506.24002 by the authors.

**Figure 2.** Best fit and corresponding Galaxy rotation curve of Newtonian, [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗

**Figure 3.** Rotation curve MCMC analysis. Left. The plot assumes Newtonian gravity with NFW dark matter profile with parameters ρs [M⊙/kpc3 ] and rs [kpc]. Vertical dashed lines denote the quantiles 0.16, 0.5, and 0.84, implying a 1σ region. Right. The plot includes the Yukawa gravity correction, which depends on the parameters β and λ. 6 [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗

Figures from the paper (7 more)

**Figure 4.** Figure 4: Left. Total line of sight acceleration calculated with the Newtonian and Yukawa best fits [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]

**Figure 5.** Figure 5: Newtonian (left) and Yukawa gravity (right) posteriors from globular clusters with [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]

**Figure 6.** Figure 6: Marginalized errors from globular clusters for Newtonian gravity. The shaded red re [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]

**Figure 7.** Figure 7: The blue data points with 1σ errorbars denote the marginalized parameter results from globular clusters data, for different alos precision values (σa). The shaded red region denotes the 1σ interval from the Galaxy rotation curve data and the red line the corresponding …

**Figure 8.** Figure 8: Left. Newtonian Galaxy rotation curve (blue) and globular cluster LOS (red) posteriors with σa = 1 cm s−1 decade−1 . Right. Yukawa Galaxy rotation curve (blue) and globular cluster LOS (red) posteriors with σa = 0.6 cm s−1 decade−1 . between GCs and RR Lyrae stars aris…

**Figure 9.** Figure 9: Left. The 100 RR-Lyrae stars with the largest LOS acceleration values. Right. 100 highest differences in LOS acceleration between Newtonian and Yukawa gravity. The color variable, 0 ≤ x ≤ 1, is the normalized difference between the absolute value of cos(α) and its mini…

**Figure 10.** Figure 10: Left. Newtonian Galaxy rotation curve (blue) and RR-Lyrae LOS (red) posteriors with σa = 10 cm s−1 decade−1 . Right. Yukawa gravity Galaxy rotation curve (blue) and RR-Lyrae LOS posteriors with σa = 10 cm s−1 decade−1 . 12 [PITH_FULL_IMAGE:figures/full_fig_p012_10.png]

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

32 extracted references · 14 canonical work pages

[1]

Performance Verification of the EXtreme PREcision Spectrograph

R. T. Blackman et al. “Performance Verification of the EXtreme PREcision Spectrograph”. In: Astron. J. 159.5, 238 (May 2020), p. 238. doi: 10 . 3847 / 1538 - 3881 / ab811d. arXiv: 2003.08852 [astro-ph.IM]

arXiv 2020
[2]

Real-time Cosmology

C. Quercellini, L. Amendola, A. Balbi, P. Cabella, and M. Quartin. “Real-time Cosmology”. In: Phys. Rept. 521 (2012), pp. 95–134. doi: 10.1016/j.physrep.2012.09.002 . arXiv: 1011.2646 [astro-ph.CO]

arXiv 2012
[3]

Stellar accelerations and the galactic gravitational field

H. Silverwood and R. Easther. “Stellar accelerations and the galactic gravitational field”. In: Publications of the Astronomical Society of Australia36 (2019), e038.doi: 10.1017/pasa. 2019.25

doi:10.1017/pasa 2019
[4]

Radial Velocities as an Exoplanet Discovery Method

J. T. Wright. “Radial Velocities as an Exoplanet Discovery Method”. In:Handbook of Exo- planets. Ed. by H. J. Deeg and J. A. Belmonte. 2018, 4, p. 4.doi: 10.1007/978- 3- 319- 55333-7_4

doi:10.1007/978- 2018
[5]

Toward a Direct Measure of the Galactic Acceleration

S. Chakrabarti et al. “Toward a Direct Measure of the Galactic Acceleration”. In:The As- trophysical Journal Letters902.1 (Oct. 2020), p. L28.issn: 2041-8213. doi: 10.3847/2041- 8213/abb9b5

doi:10.3847/2041- 2020
[6]

Inside MOND: Testing Gravity with Stellar Accelerations

M. Finan-Jenkin and R. Easther. “Inside MOND: testing gravity with stellar accelerations”. In: JCAP 2023.11, 035 (Nov. 2023), p. 035.doi: 10.1088/1475-7516/2023/11/035. arXiv: 2306.15939 [astro-ph.GA]. 13

work page Pith review arXiv 2023
[7]

Probing Dark Matter Using Precision Measurements of Stellar Accelerations

A. Ravi et al. “Probing Dark Matter Using Precision Measurements of Stellar Accelerations”. In: Physical Review Letters123.9 (Aug. 2019).issn: 1079-7114.doi: 10.1103/physrevlett. 123.091101

doi:10.1103/physrevlett 2019
[8]

Pulsar-based map of galactic acceleration

A. Moran, C. M. F. Mingarelli, K. Van Tilburg, and D. Good. “Pulsar-based map of galactic acceleration”. In: Physical Review D 109.12 (June 2024). issn: 2470-0029. doi: 10 . 1103 / physrevd.109.123015

work page 2024

Show all 32 references

[9]

Milky Way Accelerometry via Millisecond Pulsar Timing

D. F. Phillips, A. Ravi, R. Ebadi, and R. L. Walsworth. “Milky Way Accelerometry via Millisecond Pulsar Timing”. In:Phys. Rev. Lett.126 (14 Apr. 2021), p. 141103.doi: 10. 1103/PhysRevLett.126.141103

2021
[10]

Eclipse Timing the Milky Way’s Gravitational Potential

S. Chakrabarti et al. “Eclipse Timing the Milky Way’s Gravitational Potential”. In: The Astrophysical Journal Letters 928.2 (Apr. 2022), p. L17. issn: 2041-8213. doi: 10 . 3847 / 2041-8213/ac5c43

2022
[11]

LISA double white dwarf binaries as Galactic accelerometers

R. Ebadi, V. Strokov, E. H. Tanin, E. Berti, and R. L. Walsworth. “LISA double white dwarf binaries as Galactic accelerometers”. In:Phys. Rev. D 111.4 (2025), p. 044023. doi: 10.1103/PhysRevD.111.044023. arXiv: 2405.13109 [gr-qc]

2025
[12]

Galactic Potential and Dark Matter Density from Angular Stellar Accelerations

M. Buschmann, B. R. Safdi, and K. Schutz. “Galactic Potential and Dark Matter Density from Angular Stellar Accelerations”. In:Physical Review Letters127.24 (Dec. 2021). issn: 1079-7114. doi: 10.1103/physrevlett.127.241104

2021 doi
[13]

Mapping the galactic gravitational potential with peculiar acceleration

C. Quercellini, L. Amendola, and A. Balbi. “Mapping the galactic gravitational potential with peculiar acceleration”. In:Mon. Not. Roy. Astron. Soc.391 (2008), pp. 1308–1314.doi: 10.1111/j.1365-2966.2008.13968.x. arXiv: 0807.3237 [astro-ph]

2008
[14]

The Imprint of Dark Matter on the Galactic Acceleration Field

A. Arora et al. “The Imprint of Dark Matter on the Galactic Acceleration Field”. In:Astro- phys. J.974.2, 223 (Oct. 2024), p. 223.doi: 10.3847/1538-4357/ad71c4. arXiv:2406.12957 [astro-ph.GA]

2024 arXiv
[15]

Effective gravitational couplings for cosmo- logical perturbations in the most general scalar-tensor theories with second-order field equa- tions

A. De Felice, T. Kobayashi, and S. Tsujikawa. “Effective gravitational couplings for cosmo- logical perturbations in the most general scalar-tensor theories with second-order field equa- tions”. In:Phys. Lett. B706 (2011), pp. 123–133.doi: 10.1016/j.physletb.2011.11.028. arXiv...

2011 arXiv
[16]

Stable and unstable cosmological models in bimetric massive gravity

F. Koennig, Y. Akrami, L. Amendola, M. Motta, and A. R. Solomon. “Stable and unstable cosmological models in bimetric massive gravity”. In:Phys. Rev. D90 (2014), p. 124014.doi: 10.1103/PhysRevD.90.124014. arXiv: 1407.4331 [astro-ph.CO]

2014 arXiv
[17]

Measurementofgravitationalcoupling between millimetre-sized masses

T.Westphal,H.Hepach,J.Pfaff,andM.Aspelmeyer.“Measurementofgravitationalcoupling between millimetre-sized masses”. In:Nature 591.7849 (2021), pp. 225–228.doi: 10.1038/ s41586-021-03250-7. arXiv: 2009.09546 [gr-qc]

2021 arXiv
[18]

Testing gravity with the Milky Way: Yukawa potential

J. Henrichs, M. Lembo, F. Iocco, and L. Amendola. “Testing gravity with the Milky Way: Yukawa potential”. In:Physical Review D104.4 (Aug. 2021).issn: 2470-0029.doi: 10.1103/ physrevd.104.043009

2021
[19]

emcee: The MCMC Ham- mer

D. Foreman-Mackey, D. W. Hogg, D. Lang, and J. Goodman. “emcee: The MCMC Ham- mer”. In: PASP 125.925 (Mar. 2013), p. 306. doi: 10 . 1086 / 670067. arXiv: 1202 . 3665 [astro-ph.IM]

2013
[20]

Astropy: A community Python package for astronomy

Astropy Collaboration et al. “Astropy: A community Python package for astronomy”. In: Astron. Astrophys.558, A33 (Oct. 2013), A33.doi: 10.1051/0004-6361/201322068. arXiv: 1307.6212 [astro-ph.IM]

2013 arXiv
[21]

The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package

Astropy Collaboration et al. “The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package”. In:Astron. J. 156.3, 123 (Sept. 2018), p. 123.doi: 10. 3847/1538-3881/aabc4f. arXiv: 1801.02634 [astro-ph.IM]

2018 arXiv
[22]

The Astropy Project: Sustaining and Growing a Community- oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package

Astropy Collaboration et al. “The Astropy Project: Sustaining and Growing a Community- oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package”. In: Astrophys. J. 935.2, 167 (Aug. 2022), p. 167. doi: 10 . 3847 / 1538 - 4357 / ac7c74. arXiv: 2206.14...

2022 arXiv
[23]

Perspective secular changes in stellar proper motion, radial velocity and parallax

P. van de Kamp. “Perspective secular changes in stellar proper motion, radial velocity and parallax”. In: Vistas in Astronomy 21.3 (Jan. 1977), pp. 289–310. doi: 10 . 1016 / 0083 - 6656(77)90034-4. 14

1977
[24]

The Circular Velocity Curve of the Milky Way from 5 to 25 kpc

A.-C. Eilers, D. W. Hogg, H.-W. Rix, and M. K. Ness. “The Circular Velocity Curve of the Milky Way from 5 to 25 kpc”. In:The Astrophysical Journal871.1 (Jan. 2019), p. 120.issn: 1538-4357. doi: 10.3847/1538-4357/aaf648

2019 doi
[25]

A Milky Way with a massive, centrally concen- trated thick disc: new Galactic mass models for orbit computations

E. Pouliasis, P. Di Matteo, and M. Haywood. “A Milky Way with a massive, centrally concen- trated thick disc: new Galactic mass models for orbit computations”. In:Astron. Astrophys. 598 (Feb. 2017), A66.issn: 1432-0746. doi: 10.1051/0004-6361/201527346

2017 doi
[26]

A Universal density profile from hierarchical clustering

J. F. Navarro, C. S. Frenk, and S. D. White. “A Universal density profile from hierarchical clustering”. In:Astrophys. J.490 (1997), pp. 493–508.doi: 10.1086/304888. arXiv: astro- ph/9611107 [astro-ph]

1997
[27]

The Inner structure of Lambda-CDM halos 3: Universality and asymp- totic slopes

J. F. Navarro et al. “The Inner structure of Lambda-CDM halos 3: Universality and asymp- totic slopes”. In: Mon.Not.Roy.Astron.Soc. 349 (2004), p. 1039. doi: 10 . 1111 / j . 1365 - 2966.2004.07586.x. arXiv: astro-ph/0311231

2004
[28]

Evidence for dark matter in the inner Milky Way

F. Iocco, M. Pato, and G. Bertone. “Evidence for dark matter in the inner Milky Way”. In: Nature Phys. 11 (2015), pp. 245–248. doi: 10 . 1038 / nphys3237. arXiv: 1502 . 03821 [astro-ph.GA]

2015
[29]

galkin: A new compilation of Milky Way rotation curve data

M. Pato and F. Iocco. “galkin: A new compilation of Milky Way rotation curve data”. In: SoftwareX 6 (Jan. 2017), pp. 54–62.doi: 10.1016/j.softx.2016.12.006 . arXiv: 1703. 00020 [astro-ph.GA]

2017 doi
[30]

Photometric Metallicity and Distance Estimates for 136,000 RR Lyrae Stars from Gaia Data Release 3

X.-Y. Li, Y. Huang, G.-C. Liu, T. C. Beers, and H.-W. Zhang. “Photometric Metallicity and Distance Estimates for 136,000 RR Lyrae Stars from Gaia Data Release 3”. In:Astro- phys. J.944.1, 88 (Feb. 2023), p. 88.doi: 10.3847/1538-4357/acadd5. arXiv: 2206.07668 [astro-ph.SR]

2023 arXiv
[31]

Accurate distances to Galactic globular clusters through a combination of Gaia EDR3, HST, and literature data

H. Baumgardt and E. Vasiliev. “Accurate distances to Galactic globular clusters through a combination of Gaia EDR3, HST, and literature data”. In:Mon. Not. R. Astron. Soc. 505.4 (Aug. 2021), pp. 5957–5977. doi: 10 . 1093 / mnras / stab1474. arXiv: 2105 . 09526 [astro-ph.GA]

2021
[32]

GaiaData Release 3: Specific processing and validation of all-sky RR Lyrae and Cepheid stars: The RR Lyrae sample

G. Clementini et al. “GaiaData Release 3: Specific processing and validation of all-sky RR Lyrae and Cepheid stars: The RR Lyrae sample”. In:Astron. Astrophys.674 (June 2023), A18. issn: 1432-0746. doi: 10.1051/0004-6361/202243964. 15

2023 doi

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.

[1] [1]

Performance Verification of the EXtreme PREcision Spectrograph

R. T. Blackman et al. “Performance Verification of the EXtreme PREcision Spectrograph”. In: Astron. J. 159.5, 238 (May 2020), p. 238. doi: 10 . 3847 / 1538 - 3881 / ab811d. arXiv: 2003.08852 [astro-ph.IM]

arXiv 2020

[2] [2]

Real-time Cosmology

C. Quercellini, L. Amendola, A. Balbi, P. Cabella, and M. Quartin. “Real-time Cosmology”. In: Phys. Rept. 521 (2012), pp. 95–134. doi: 10.1016/j.physrep.2012.09.002 . arXiv: 1011.2646 [astro-ph.CO]

arXiv 2012

[3] [3]

Stellar accelerations and the galactic gravitational field

H. Silverwood and R. Easther. “Stellar accelerations and the galactic gravitational field”. In: Publications of the Astronomical Society of Australia36 (2019), e038.doi: 10.1017/pasa. 2019.25

doi:10.1017/pasa 2019

[4] [4]

Radial Velocities as an Exoplanet Discovery Method

J. T. Wright. “Radial Velocities as an Exoplanet Discovery Method”. In:Handbook of Exo- planets. Ed. by H. J. Deeg and J. A. Belmonte. 2018, 4, p. 4.doi: 10.1007/978- 3- 319- 55333-7_4

doi:10.1007/978- 2018

[5] [5]

Toward a Direct Measure of the Galactic Acceleration

S. Chakrabarti et al. “Toward a Direct Measure of the Galactic Acceleration”. In:The As- trophysical Journal Letters902.1 (Oct. 2020), p. L28.issn: 2041-8213. doi: 10.3847/2041- 8213/abb9b5

doi:10.3847/2041- 2020

[6] [6]

Inside MOND: Testing Gravity with Stellar Accelerations

M. Finan-Jenkin and R. Easther. “Inside MOND: testing gravity with stellar accelerations”. In: JCAP 2023.11, 035 (Nov. 2023), p. 035.doi: 10.1088/1475-7516/2023/11/035. arXiv: 2306.15939 [astro-ph.GA]. 13

work page Pith review arXiv 2023

[7] [7]

Probing Dark Matter Using Precision Measurements of Stellar Accelerations

A. Ravi et al. “Probing Dark Matter Using Precision Measurements of Stellar Accelerations”. In: Physical Review Letters123.9 (Aug. 2019).issn: 1079-7114.doi: 10.1103/physrevlett. 123.091101

doi:10.1103/physrevlett 2019

[8] [8]

Pulsar-based map of galactic acceleration

A. Moran, C. M. F. Mingarelli, K. Van Tilburg, and D. Good. “Pulsar-based map of galactic acceleration”. In: Physical Review D 109.12 (June 2024). issn: 2470-0029. doi: 10 . 1103 / physrevd.109.123015

work page 2024