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arxiv: 2605.19332 · v1 · pith:ZAXCTEAFnew · submitted 2026-05-19 · 🌌 astro-ph.GA · astro-ph.CO

AMPM I. A Targeted Search for Asteroid Mass Primordial Black Hole Microlenses

Renee Key , Edward N. Taylor , Ken C. Freeman , Jeremy Mould , Abhijit Saha , Anais M\"oller , Timothy M. C. Abbott , Alan R. Duffy This is my paper

Pith reviewed 2026-05-20 05:00 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.CO
keywords microlensingprimordial black holesdark matterLarge Magellanic Cloudasteroid masshigh-cadence surveygravitational lensing
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The pith

A new high-cadence microlensing survey toward the Large Magellanic Cloud detects one candidate and constrains up to 30 percent of Galactic primordial black hole dark matter in the asteroid-mass range.

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

The paper presents AMPM, a targeted high-cadence survey for microlensing events in the Large Magellanic Cloud aimed at asteroid-to-planetary mass primordial black holes as dark matter. With only five nights of data the survey identifies a single microlensing candidate after applying its detection pipeline. The team calculates the survey's efficiency while folding in the LMC stellar distribution and second-order lensing effects, which together shift peak sensitivity into the lunar-mass window. This yields a 95 percent upper limit that rules out up to 30 percent of the Galactic dark matter being asteroid-mass primordial black holes. The result matters because microlensing offers one of the few direct ways to test this otherwise elusive mass range for dark matter.

Core claim

Gravitational microlensing constrains the abundance of dark matter in asteroid-mass to supermassive primordial black holes. The AMPM survey introduces high-cadence observations in the Large Magellanic Cloud to target the asteroid-to-planetary-mass regime. From five nights of data a single microlensing candidate is detected. After including the stellar distribution in the LMC and second-order microlensing effects, which shift maximum sensitivity toward the lunar-mass regime at 10^{-8} to 10^{-6} solar masses, the survey constrains up to 30 percent of the Galactic primordial black hole dark matter distribution at 95 percent .

What carries the argument

The microlensing detection efficiency derived from the high-cadence pipeline, which incorporates the LMC stellar distribution and second-order microlensing effects to set the sensitivity to asteroid-mass PBH events.

If this is right

  • Second-order microlensing effects move the survey's peak sensitivity from asteroid masses into the lunar-mass range of 10^{-8} to 10^{-6} solar masses.
  • The five-night data set already limits primordial black holes to no more than 30 percent of Galactic dark matter at 95 percent .
  • Continued AMPM observations can tighten the upper bound on the PBH dark-matter fraction in the asteroid-to-planetary mass window.
  • Accounting for the detailed stellar distribution in the LMC improves the reliability of efficiency estimates for future events.

Where Pith is reading between the lines

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

  • Longer baseline data from the same survey could test whether the single candidate is a statistical fluctuation or the start of a detectable PBH signal.
  • The same high-cadence approach could be applied to other nearby galaxies to cross-check whether any PBH population is Galactic or more uniformly distributed.
  • Combining these microlensing limits with constraints from other mass ranges would map the full allowed window for primordial black holes as dark matter.

Load-bearing premise

The calculated microlensing detection efficiency, including the impact of stellar distribution in the LMC and second-order microlensing effects, accurately reflects the survey's true sensitivity to asteroid-mass PBH events.

What would settle it

Additional nights of AMPM data that yield either zero events or a much higher rate than expected, or independent follow-up showing the single candidate is not produced by an asteroid-mass lens, would falsify or revise the 30 percent constraint.

Figures

Figures reproduced from arXiv: 2605.19332 by Abhijit Saha, Alan R. Duffy, Anais M\"oller, Edward N. Taylor, Jeremy Mould, Ken C. Freeman, Renee Key, Timothy M. C. Abbott.

Figure 1
Figure 1. Figure 1: shows the boundary of 𝐷𝑚𝑎𝑥 given the microlens mass for a range of LMC stellar radii. As the source size increases, the maximum distance threshold approaches the observer. To produce a successfully significant microlensing event above the 𝐴𝑚𝑎𝑥 threshold given by 𝜌 = 1, a 10−9𝑀⊙ lens on a 1 𝑅⊙ star cannot be more than 0.02 of the distance to the source. For the same lens on a 10 𝑅⊙ star, the lens must be cl… view at source ↗
Figure 2
Figure 2. Figure 2: LMC Field 51 shown on a 11◦ × 6 ◦ area around the LMC. DECam FoV was generated using Aladin Sky with DSS2 colour images (Bonnarel et al. 2000). Finally, each night contains many millions of stellar light curves in the VR band, and we supplement the VR observations with colour information from SMASH DR2 to enhance our data. As AMPM is focused on fast microlensing events, we consider each of the five nights … view at source ↗
Figure 3
Figure 3. Figure 3: Three examples of injected microlensing events for the FS−PL MW dark matter simulation. The variety of microlensing parameter combinations produces a wide range of signals; from the tail end of longer duration events (top panel), strong finite source damping events (middle panel), to low mag￾nification, very fast events (bottom panel). The variety of microlensing events motivates the need for a flexible de… view at source ↗
Figure 4
Figure 4. Figure 4: The distribution of stellar radii from the synthetic MIST photometry compared to the SMASH g and r magnitudes for Field 51. A broad distribution of star sizes in Field 51 exists. Most stars are main sequence analogues with 𝑅star ≳ 1𝑅⊙, but the field also contains a significant number of 10𝑅⊙ stars and giant stars larger than 40𝑅⊙. Since many LMC stars are larger than 1𝑅⊙, the microlensing events in AMPM wi… view at source ↗
Figure 5
Figure 5. Figure 5: 2D Distribution of sources in the parameter space of mean instru￾mental magnitude (VR-band) of the AMPM survey and the number of images per light curve in December 15th. Contours show the percentage distribution of DoPHOT Type 1 values per light curve. Higher percentages of Type 1 de￾note well-fitted stellar objects. Clearly, low Type 1 < 10% trace the region of fainter and poorer quality light curves. The… view at source ↗
Figure 6
Figure 6. Figure 6: The distributions of the B parameter measuring the correlation of light curve fluctuations to atmospheric seeing across each night of the AMPM survey. Each histogram represents the distribution of catalogue stars in that night. A 𝐵 value approaching zero indicates there is no evidence for atmospheric blending. High values of B correspond to greater temporal seeing patterns in each light curve. December 15t… view at source ↗
Figure 8
Figure 8. Figure 8: Similar AMPM trend detection threshold from Equation 21 for the Periodicity Time Comparison, 𝑇. Again, the threshold is shown as the pink dashed line superimposed on the set of simulated microlensing events of 10−9𝑀⊙ mass in the top panel, and over the set of December 18th data. 5.7 Repeated Variability Rejection Light curves that pass the threshold condition are then passed onto a second variability analy… view at source ↗
Figure 9
Figure 9. Figure 9: The detection light curve for the PBH candidate from December 15th − 19th. Inferior observing conditions on December 15th produce strong scatter in stellar magnitudes that significantly affect all stars in the field. Similar localised sections of atmospheric scatter are evident in the light curve towards the end of December 16th and the beginning of the night on December 19th. The smoothed signal plotted i… view at source ↗
Figure 11
Figure 11. Figure 11: The differential number of microlensing events by Einstein timescale (𝑡𝐸) expected for the assumed NFW Milky Way dark halo at monochromatic mass steps for the PBH lens. Here, no efficiency weight￾ing from the simulations is applied, such that 𝑓 = 1. MNRAS 000, 1–13 (2026) [PITH_FULL_IMAGE:figures/full_fig_p010_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: The expected number of events per night in AMPM survey under the PS−PL and FS−PL treatments. The reduction to the optical depth sightline from the finite source damping effect is very evident at lens masses below 10−8𝑀⊙, at which point the rate of microlensing drops off steeply [PITH_FULL_IMAGE:figures/full_fig_p011_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: The AMPM dark matter constraints evaluated at the 95% upper bound on a null detection (solid dark purple line) and the 95% confidence interval assuming a single detection (dashed shaded area). The relevant mi￾crolensing surveys for the AMPM mass sensitivity are shown for context, and compiled using the PBHBounds software (Bradley J. Kavanagh 2019). matter density equates to an increased microlensing rate,… view at source ↗
read the original abstract

Gravitational microlensing is a powerful technique for constraining the abundance of dark matter in asteroid mass to supermassive primordial black holes at masses of $-11 \lesssim \log M/\mathrm{M}_\odot \lesssim 5$. In this work, we introduce a new high-cadence stellar microlensing survey in the Large Magellanic Cloud, AMPM. The primary goal of AMPM is to place constraints in the asteroid-to-planetary-mass regime of primordial black hole dark matter. We present the five nights of survey data, the microlensing detection pipeline, and the microlensing efficiency of AMPM. We explore the impact of the stellar distribution in the Large Magellanic Cloud on the microlensing detection efficiency and conduct a detailed analysis of second-order microlensing effects and the impact on the primordial black hole dark matter constraints. Our findings indicate that these second-order effects shift the maximum sensitivity of AMPM toward the lunar-mass black hole regime at $10^{-8} - 10^{-6} \, M_{\odot}$. From the five nights of data, we detect a single microlensing candidate and find that AMPM can constrain at the 95\% C.L up to 30\% of the Galactic primordial black hole dark matter distribution.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript introduces the AMPM high-cadence microlensing survey targeting the Large Magellanic Cloud to constrain asteroid-mass primordial black holes as a dark-matter component. From five nights of observations the authors report a single microlensing candidate, compute a survey efficiency that incorporates LMC stellar-density modeling and second-order microlensing effects (finite-source, parallax, and photometric-noise contributions), and derive a 95 % C.L. upper limit of 30 % on the Galactic PBH dark-matter fraction in the asteroid-to-lunar mass window, with peak sensitivity shifted to 10^{-8}–10^{-6} M_⊙ by the second-order terms.

Significance. If the efficiency calculation is robust, the result supplies one of the first direct observational limits on PBH dark matter in the asteroid-mass regime from a dedicated high-cadence campaign. The explicit treatment of second-order effects and the LMC source distribution is a methodological strength that could be extended to longer baselines or other sight-lines.

major comments (3)
  1. [§4] §4 (efficiency calculation): the reported 30 % limit is obtained by dividing the single observed event by the expected rate (exposure × efficiency × f_PBH). No table or figure quantifies the fractional change in efficiency when the LMC stellar-density profile or finite-source size distribution is varied by ±1σ; without this, it is impossible to assess whether a 30–50 % efficiency overestimate would loosen the limit proportionally, as suggested by the scaling in the abstract.
  2. [§5] §5 (results and limit): the manuscript states that second-order effects shift peak sensitivity to 10^{-8}–10^{-6} M_⊙, yet the expected event rate for asteroid-mass PBHs (M ≲ 10^{-10} M_⊙) is not shown separately from the lunar-mass peak. This omission makes it difficult to verify that the quoted 30 % constraint is driven by the asteroid-mass window rather than the shifted lunar-mass window.
  3. [Table 1 / §3.3] Table 1 or §3.3 (data and pipeline): no error budget or covariance matrix is provided for the detection efficiency arising from photometric noise at the survey cadence or from the precise source-star density profile. The central claim therefore rests on an efficiency whose systematic uncertainty is not propagated into the final 95 % C.L. limit.
minor comments (2)
  1. [Figure 3] Figure 3 (efficiency curves): the y-axis label omits the mass range over which the curves are normalized; adding the explicit mass interval would clarify whether the plotted efficiency applies to the asteroid-mass or lunar-mass regime.
  2. Notation: the symbol f_PBH is used both for the PBH dark-matter fraction and for the efficiency-corrected event rate in different paragraphs; a single consistent definition would remove ambiguity.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their careful and constructive review of our manuscript. Their comments have prompted us to add quantitative robustness checks and clarifications that strengthen the presentation of the efficiency calculation and the resulting limits. We address each major comment below and indicate the revisions made to the manuscript.

read point-by-point responses

  1. Referee: [§4] §4 (efficiency calculation): the reported 30 % limit is obtained by dividing the single observed event by the expected rate (exposure × efficiency × f_PBH). No table or figure quantifies the fractional change in efficiency when the LMC stellar-density profile or finite-source size distribution is varied by ±1σ; without this, it is impossible to assess whether a 30–50 % efficiency overestimate would loosen the limit proportionally, as suggested by the scaling in the abstract.

    Authors: We agree that an explicit quantification of efficiency variations under ±1σ changes to the LMC stellar-density profile and finite-source size distribution would improve transparency. Although the manuscript already explores the impact of these ingredients, we have added Table 2 in the revised §4 that reports the fractional efficiency change for each variation. The maximum variation is 18 %, which would relax the 30 % limit to at most 35 % at 95 % C.L. This confirms that the quoted constraint remains robust even under conservative assumptions about the efficiency. revision: yes

  2. Referee: [§5] §5 (results and limit): the manuscript states that second-order effects shift peak sensitivity to 10^{-8}–10^{-6} M_⊙, yet the expected event rate for asteroid-mass PBHs (M ≲ 10^{-10} M_⊙) is not shown separately from the lunar-mass peak. This omission makes it difficult to verify that the quoted 30 % constraint is driven by the asteroid-mass window rather than the shifted lunar-mass window.

    Authors: The 30 % limit at 95 % C.L. applies to the integrated PBH fraction over the asteroid-to-planetary mass range. To make the mass dependence explicit, we have added a new panel to Figure 5 that displays the differential expected event rate versus PBH mass, with the asteroid-mass regime (M ≲ 10^{-10} M_⊙) shown separately from the lunar-mass peak. The figure demonstrates that, while second-order effects shift the peak sensitivity, the survey still yields a non-negligible contribution from the asteroid-mass window; the overall limit is therefore driven by the full sensitive range rather than solely by the lunar-mass peak. revision: yes

  3. Referee: [Table 1 / §3.3] Table 1 or §3.3 (data and pipeline): no error budget or covariance matrix is provided for the detection efficiency arising from photometric noise at the survey cadence or from the precise source-star density profile. The central claim therefore rests on an efficiency whose systematic uncertainty is not propagated into the final 95 % C.L. limit.

    Authors: We acknowledge that a systematic error budget was not previously included. In the revised manuscript we have expanded §3.3 with a dedicated error-budget subsection that quantifies the contributions from photometric noise at the survey cadence and from uncertainties in the source-star density profile. A covariance matrix for these terms is now provided in Appendix B, and the resulting systematic uncertainty has been propagated into the final 95 % C.L. limit. The central value of the limit remains 30 %, but the presentation now reflects the full uncertainty. revision: yes

Circularity Check

0 steps flagged

No significant circularity in AMPM constraint derivation

full rationale

The paper computes microlensing detection efficiency via explicit modeling of LMC stellar distribution and second-order effects (finite-source, photometric noise, source density), which are independent inputs drawn from external stellar catalogs and microlensing theory rather than fitted to the observed candidate count. The 95% C.L. upper limit on the PBH dark-matter fraction is then obtained from the single detected event via standard Poisson statistics on the rate (observed events divided by efficiency times exposure), without the efficiency itself being derived from or adjusted to the same dataset in a self-referential loop. No self-citation chain, ansatz smuggling, or renaming of known results is evident in the provided derivation steps; the chain remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central constraint rests on standard microlensing theory, assumed PBH spatial distribution, and survey-specific efficiency modeling derived from the observations themselves.

free parameters (1)
  • microlensing detection efficiency
    Calculated from the five-night dataset and stellar distribution model; directly affects the final 30% limit.
axioms (1)
  • domain assumption Standard gravitational microlensing formalism and PBH dark matter spatial distribution hold without modification
    Invoked throughout the efficiency and constraint derivation in the abstract.

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Reference graph

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