arxiv: 2601.10789 · v1 · submitted 2026-01-15 · 🌌 astro-ph.HE · astro-ph.GA· astro-ph.SR

Recognition: no theorem link

Astrometric microlensing probes of the isolated neutron star population with Roman

Zofia Kaczmarek , Abby Halasi-Kun , Peter McGill , Scott E. Perkins , William A. Dawson

Authors on Pith no claims yet

Pith reviewed 2026-05-16 13:34 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.GAastro-ph.SR

keywords neutron starsmicrolensingRoman Space TelescopeastrometryGalactic Bulgenatal kickscompact objects

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The pith

Roman will detect about 100 isolated neutron stars via astrometric microlensing in its Galactic Bulge survey.

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

The paper simulates realistic microlensing events for the Roman Space Telescope to demonstrate that astrometric signals can detect isolated neutron stars, which are otherwise hard to observe. It models four NS populations using Maxwellian natal kick velocities and state-of-the-art Galactic models, then applies Roman's expected precision, cadence, and detectability thresholds. A distinct feature emerges in the log10 event timescale versus log10 Einstein radius parameter space that marks NS lenses and enables construction of optimal candidate samples. The simulations forecast roughly 11,000 total events with both photometric and astrometric signals detectable, of which about 100 involve NS lenses, with yield dropping 38 percent if low-cadence gap-filling data are omitted.

Core claim

Using state-of-the-art Galactic models tailored for compact-object microlensing, the authors simulate events with neutron-star lenses drawn from Maxwellian kick distributions with means of 150, 250, 350, and 450 km/s. They show that the log10 t_E – log10 theta_E plane is maximally efficient for classifying stellar remnants and contains a feature characteristic of NS lenses that supports selection of high-purity candidate samples. The expected Roman yield is approximately 11,000 microlensing events whose photometric and astrometric signals are both detectable, including roughly 100 with NS lenses; the yield falls by 38 percent without gap-filling low-cadence observations.

What carries the argument

The log10 t_E – log10 theta_E parameter space, where t_E is the Einstein crossing time and theta_E is the Einstein radius, which exhibits a distribution feature that distinguishes neutron-star lenses from other compact objects.

If this is right

Optimal samples of NS candidates can be constructed from Roman-like datasets by selecting events near the characteristic feature in the log10 t_E – log10 theta_E plane.
Observable parameter distributions for NS events depend on the assumed mean natal kick velocity.
Complex and mutually counteracting effects of natal kicks imply that detailed dynamical studies of NS populations are needed before Roman data arrive.
Omitting gap-filling low-cadence observations reduces the total detectable microlensing event yield by 38 percent.

Where Pith is reading between the lines

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

Similar astrometric microlensing techniques could be extended to search for isolated black holes or other faint compact objects in future wide-field surveys.
Roman NS detections could provide empirical constraints on supernova explosion physics by testing which kick-velocity distributions best match the observed sample.
The publicly released simulated event catalogs allow independent groups to develop classification algorithms and forecast yields for modified survey strategies.

Load-bearing premise

The chosen Maxwellian natal kick distributions with mean velocities of 150 to 450 km/s and the state-of-the-art Galactic models accurately represent the true isolated neutron star population and its kinematics.

What would settle it

Roman observations yielding a number of NS microlensing events differing substantially from the predicted ~100, or showing no characteristic feature in the log10 t_E – log10 theta_E plane among candidate events.

Figures

Figures reproduced from arXiv: 2601.10789 by Abby Halasi-Kun, Peter McGill, Scott E. Perkins, William A. Dawson, Zofia Kaczmarek.

**Figure 1.** Figure 1: Layout of the simulation fields, overplotted on the Roman GBTDS footprint as recommended by the Roman Observations Time Allocation Committee. Colours represent the total number of simulated microlensing events per simulation field over the average for all fields in the run with the PopSyCLE (Lam et al. 2020) default 350 km/s mean NS kick velocity (before applying the detectability cuts). 3. Data 3.1. Sim… view at source ↗

**Figure 2.** Figure 2: Yield of events with NS lenses detectable with Roman in both photometry and astrometry over the entire GBTDS duration as a function of mean kick velocity vkick, before (green, dotted) and after (purple, solid) applying the effect of natal kicks on volume density of NS in the Galaxy. Errorbars represent Poisson noise; the σ 2 = P i w 2 i formula (Barlow 1987) is applied to weighted Poisson counts. While la… view at source ↗

**Figure 3.** Figure 3: Distributions of NS (purple) and non-NS (grey) events in log10 tE–log10 θE space. All simulated events regardless of passing detectability cuts are plotted; shade denotes iso-density levels estimated with a Gaussian KDE. Black circles highlight the NS events that passed the detectability cuts. The NS distribution exhibits a characteristic ‘spur’ feature that becomes stronger and more shifted leftwards with… view at source ↗

**Figure 4.** Figure 4: All six subplots present the same log10 tE–log10 θE space distribution of detectable NS lenses from the vkick = 450 km/s simulation run (coloured) compared to that of lenses from other (Star, WD, BH) classes (light grey). The NS lenses are coloured by event parameters: lens velocity vL, lens mass ML, source distance DL, lens distance µL, and a measure of background area subject to light deflection by the l… view at source ↗

**Figure 6.** Figure 6: Distributions of detectable NS lens distances for all four runs, with vkick increasing from top to bottom. The unweighted distance distribution is plotted with light purple, while the weighted (with post-kick Galactic density correction) distance distribution is plotted with dark purple with black contours. The distance distribution for all other detectable lenses (classL ∈ {Star, WD, BH}) is plotted in … view at source ↗

**Figure 7.** Figure 7: Left: Relative class probabilities in log10 tE–log10 πE – the space of observables accessible from photometric observations only. The probability map is constructed using all photometrically detectable events. Right: Relative class probabilities in log10 tE–log10 θE – the space of observables possible to measure with high precision with the combination of photometry and astrometry. The probability map is … view at source ↗

read the original abstract

Notoriously hard to detect and study, isolated neutron stars (NS) could provide valuable answers to fundamental questions about stellar evolution and explosion physics. With the upcoming Roman Space Telescope, scheduled for launch in 2026, a new and powerful channel for their detection - astrometric microlensing - will become available. We set out to create a realistic sample of simulated gravitational microlensing events as observed by Roman with the Galactic Bulge Time Domain Survey. We focus in particular on the population of NS lenses, which has until now been largely understudied. We use state-of-the-art Galactic models tailored for application to microlensing by compact objects. We simulate four different NS populations with Maxwellian natal kick distributions: $\bar{v} = (150, \ 250, \ 350, \ 450)$ km/s. We apply projected Roman precision, cadence, and detectability criteria. We find the parameter space $\log_{10} t_{\rm E}$ - $\log_{10} \theta_{\rm E}$, which will be accessible to Roman observations, to be maximally efficient for classification of stellar remnants. We find a feature in this space that is characteristic to NS; using this feature, optimal samples of NS candidates can be constructed from Roman-like datasets. We describe the dependence of observable parameter distributions on the assumed mean kick velocities. As the effects of natal kicks are very complex and mutually counteracting, we suggest more detailed studies focused on the dynamics of NS are needed in anticipation of Roman and future surveys. We estimate Roman will observe approximately $11\,000$ microlensing events - including $\sim100$ with NS lenses - whose both photometric and astrometric signal are detectable; the event yield decreases by $38\%$ if gap-filling low-cadence observations are not included. We make all simulated microlensing event datasets publicly available in preparation for Roman data.

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.

Desk Editor's Note private letter to a colleague

Roman NS microlensing forecast gives ~100 events and a useful classification feature in the t_E-theta_E plane, but the numbers sit on fixed kick velocities and one Galactic model without error bars or validation.

read the letter

The main takeaway is that this paper runs simulations of Roman's Galactic Bulge survey and predicts roughly 11,000 detectable microlensing events, of which about 100 should have neutron star lenses. They also point to a region in the log t_E versus log theta_E plane that stands out for NS lenses and could help build candidate samples. The datasets are made public, which is the most immediately useful part of the work. They run four Maxwellian kick distributions with means from 150 to 450 km/s and show how the observable distributions shift with those choices. That dependence is worth having on record for planning purposes. The setup uses standard Galactic models and applies the expected Roman cadence and precision, so the technical execution looks competent. The soft spots are straightforward. The headline yields are given as single numbers with no uncertainties attached, and there is no marginalization over the kick parameters or alternative Galactic realizations. The NS count is sensitive to the high-velocity tail, so a modest change in the assumed distribution or disk scale height can move the number by a factor of two, as the stress-test note flags. There is also no direct check against existing pulsar proper-motion data to see whether the chosen Maxwellians are realistic. This paper is aimed at people who will work with Roman data on compact objects or who need forecast numbers for survey planning. A reader who wants the public catalogs and the classification feature will find it worth downloading. It deserves a serious referee because the simulations are grounded in established methods, the public release is concrete, and the classification idea is worth testing even if the exact yields need more scrutiny on the assumptions. I would send it to peer review.

Referee Report

3 major / 2 minor

Summary. This paper simulates gravitational microlensing events observable by the Roman Space Telescope's Galactic Bulge Time Domain Survey, emphasizing isolated neutron star (NS) lenses. Using state-of-the-art Galactic models and four Maxwellian natal kick distributions with mean velocities of 150, 250, 350, and 450 km/s, the authors apply projected Roman precision, cadence, and detectability criteria in the log t_E - log θ_E plane. They estimate ~11,000 total detectable events including ~100 with NS lenses, identify a characteristic NS feature in this parameter space for classification, describe dependence on kick velocities, and release the simulated datasets publicly.

Significance. If the estimates hold, this provides a valuable forecast for Roman's ability to detect isolated neutron stars via combined photometric and astrometric microlensing, offering new probes of stellar evolution and explosion physics. The public release of the simulated event datasets is a clear strength that enables community follow-up. The analysis of how distributions vary with assumed kick velocities usefully illustrates the dynamical complexities involved.

major comments (3)

[Results section] Results section (yield estimates): The central claims of approximately 11,000 total events and ~100 NS-lens events are given as point estimates without quoted uncertainties, ranges, or sensitivity tests to the mean natal kick velocity (a free parameter in the simulations). The text notes that kick effects are complex and counteracting with exponential sensitivity in the high-velocity tail, so the NS count could shift by a factor of two under modest changes; this makes the headline numbers load-bearing but insufficiently robust.
[Simulation setup (Section 3)] Simulation setup (Section 3): The adopted Maxwellian kick distributions are not compared to or validated against observed pulsar proper-motion or velocity distributions. Given that the fraction of bound NS producing detectable θ_E > 0.1 mas events depends critically on the velocity tail, the lack of such anchoring or marginalization over kick parameters undermines in the ~100 NS yield.
[Parameter space analysis] Parameter space analysis: The claim that the log10 t_E - log10 θ_E space is 'maximally efficient for classification of stellar remnants' and contains a 'feature characteristic to NS' is presented qualitatively without supporting quantitative metrics such as classification efficiencies, ROC curves, or separation statistics between NS and other lenses.

minor comments (2)

[Abstract] Abstract: The 38% yield reduction without gap-filling low-cadence observations is stated but not tied to a specific figure or table; a brief cross-reference would improve clarity.
[Figures] Figure captions and text: Labels distinguishing the four kick-velocity cases (150-450 km/s) could be made more consistent across plots to aid reader comparison of distributions.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments on our manuscript. We address each major comment point by point below, indicating the revisions we will make where appropriate.

read point-by-point responses

Referee: [Results section] Results section (yield estimates): The central claims of approximately 11,000 total events and ~100 NS-lens events are given as point estimates without quoted uncertainties, ranges, or sensitivity tests to the mean natal kick velocity (a free parameter in the simulations). The text notes that kick effects are complex and counteracting with exponential sensitivity in the high-velocity tail, so the NS count could shift by a factor of two under modest changes; this makes the headline numbers load-bearing but insufficiently robust.

Authors: We agree that the yield estimates would be more robust with explicit sensitivity information. In the revised manuscript, we will report the NS event yields obtained from each of the four simulated kick velocity distributions (150, 250, 350, and 450 km/s), which span a factor of approximately two, and present the headline ~100 as the central value within this range. We will also clarify that the total event count of ~11,000 corresponds to the fiducial model and reiterate the 38% reduction when gap-filling observations are omitted. revision: yes
Referee: [Simulation setup (Section 3)] Simulation setup (Section 3): The adopted Maxwellian kick distributions are not compared to or validated against observed pulsar proper-motion or velocity distributions. Given that the fraction of bound NS producing detectable θ_E > 0.1 mas events depends critically on the velocity tail, the lack of such anchoring or marginalization over kick parameters undermines in the ~100 NS yield.

Authors: The four Maxwellian distributions were chosen to span a range of plausible mean natal kick velocities for isolated neutron stars. In the revised manuscript, we will add a brief discussion in Section 3 that places these values in the context of observed mean velocities from pulsar studies (typically 200-400 km/s). Full marginalization over the kick distribution or detailed comparison to proper-motion catalogs would require a separate population-synthesis effort that lies outside the scope of the present work; we retain our existing call for more detailed dynamical studies in the conclusions. revision: partial
Referee: [Parameter space analysis] Parameter space analysis: The claim that the log10 t_E - log10 θ_E space is 'maximally efficient for classification of stellar remnants' and contains a 'feature characteristic to NS' is presented qualitatively without supporting quantitative metrics such as classification efficiencies, ROC curves, or separation statistics between NS and other lenses.

Authors: We accept that the description of the parameter space as 'maximally efficient' and the identification of the NS feature rest on qualitative inspection of the simulated distributions. In the revised version, we will moderate the wording to 'particularly efficient' and add quantitative support, including the fraction of NS events lying in the characteristic short-t_E region relative to other lens populations and a simple measure of distributional overlap. While constructing full ROC curves would require defining an explicit classifier (which is not the focus of this work), these additions will provide a clearer quantitative basis for the utility of the space. revision: yes

Circularity Check

0 steps flagged

Forward simulation yields contain no circular reduction to inputs

full rationale

The reported event yields (~11,000 total, ~100 NS-lens) are produced by drawing NS lenses from four externally chosen Maxwellian kick distributions, embedding them in state-of-the-art Galactic models, and counting those that satisfy the adopted Roman photometric and astrometric cuts. No equation, fit, or self-citation chain equates the final counts to quantities defined by the same simulation; the derivation is a direct Monte Carlo forward pass whose numerical outputs are independent of any internal redefinition or renaming of the input assumptions.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central yield and classification claims rest on four chosen mean kick velocities treated as free parameters and on the assumption that the adopted Galactic models correctly describe the spatial and kinematic distribution of compact objects.

free parameters (1)

mean natal kick velocity = 150, 250, 350, 450 km/s
Four discrete values (150, 250, 350, 450 km/s) are selected to sample Maxwellian distributions for the NS populations.

axioms (1)

domain assumption State-of-the-art Galactic models tailored for microlensing by compact objects accurately represent the true distribution of isolated neutron stars.
Invoked to generate the simulated lens population and event rates.

pith-pipeline@v0.9.0 · 5672 in / 1276 out tokens · 32358 ms · 2026-05-16T13:34:00.112652+00:00 · methodology

discussion (0)

Reference graph

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