Ray-traced weak lensing convergence in screened modified gravity theories

arXiv:2604.08393 · astro-ph.CO · Submitted 2026-04-09 · Read on arXiv

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Introduction to the show: ident: Astrophysics Radio. Generated commentary on the latest astrophysics papers.

Vera: Next we'll be talking about the paper "Ray-traced weak lensing convergence in screened modified gravity theories".

Jocelyn: The paper was written by Mattia Pantiri, Matthieu Schaller, Alessandra Silvestri, Jeger C. Broxterman and Joop Schaye from Lorentz Institute for Theoretical Physics, Leiden University and Leiden Observatory, Leiden University.

Vera: Stay tuned as we take you through the paper and discuss its implications.

Jocelyn: We also have Subrahmanyan with us today — guest researcher.

Vera: Alright, let's get started.

Summary: Vera: So, we’ve established that might not be it, but how does this paper summarize their approach?

Jocelyn: I see they are using FLAMINGO hydrodynamical simulations as their base data, which is a massive set of simulations that track both the dark matter and the baryonic gas.

Subrahmanyan: That's crucial because they aren't just using static density maps; they’re modeling complex, realistic structures, which adds a lot of fidelity to the results.

Vera: It sounds like they are testing two scenarios for how modified gravity—they call it MG—works in this environment.

Jocelyn: One scenario is when the modification is just dependent on time, which is relatively straightforward mathematically.

Subrahmanyan: The other scenario, which they find much more interesting, is when the modification depends on density and scale, showing how nature might hide or 'screen' these effects in dense areas.

Vera: This concept of screening seems to be the central idea that ties everything together when it comes to their modified gravity theories.

Jocelyn: It’s a way of saying that even though the theory is different, it behaves like standard physics where we expect it to, especially in places with lots of matter.

Subrahmanyan: Exactly; they are showing how this modification impacts the convergence power spectrum, which is the key observable we look at when measuring weak lensing.

Vera: It’s a really comprehensive approach that sets the stage for looking at specific measurement techniques in later segments.

Improvements and Methodology: Jocelyn: Moving on to their methodology, what improvements are they suggesting over existing work?

Subrahmanyan: The biggest improvement is that they are not just modifying the clustering side of things; they’re actually modifying the lensing equation itself using this mg function.

Vera: That's a huge gap in previous studies, so it's vital to see how this works at the non-linear level.

Jocelyn: They are implementing two specific ways to model this screening: one based on the halo's physical properties and another based on local overdensity.

Subrahmanyan: Both methods—the halo method and the overdensity method—are just different ways to phenomenologically achieve that idea of restoring general relativity in high-density environments.

Vera: It's interesting that they are comparing these two approaches, since we often see different behaviors depending on whether or not we focus on individual objects versus the general environment.

Jocelyn: And how does their ray-tracing method fit into this? Is it just a simple adjustment to existing code?

Subrahmanyan: No, they are using the full ray-tracing approach, which is much more accurate than simplified methods because it tracks how a light ray actually travels through the complex cosmic web.

Vera: This level of detail really helps us understand where the errors might be in any model, so it's a huge step forward in modeling precision cosmology.

Jocelyn: Before we look at the results, we need to understand how these two methods are going to show up in the actual measurements.

The Results: Vera: So, what do they find when they compare their modified lensing to standard GR lensing?

Subrahmanyan: They found that these modifications do produce a non-negligible signature in the convergence power spectrum, which is exactly what we are looking for.

Jocelyn: And perhaps even more surprising, they suggest that these MG effects can be larger than the variations caused by baryonic physics?

Vera: That's a huge claim; it means if we are trying to measure something in weak lensing, we might be misattributing the signal entirely.

Subrahmanyan: The results show that with both their screening methods, there is about a five percent discrepancy between GR and MG at the largest scales.

Jocelyn: But then it gets smaller at smaller scales, which makes sense since screening should kick in when things get very dense and small.

Vera: This means the effects are scale-dependent, so we have to be very careful about what parts of the power spectrum we decide to analyze.

Subrahmanyan: The way they've shown it, the halo method has this dip and then a recovery in power at smaller scales, which is a really distinct signature.

Jocelyn: It seems like these results are telling us that modified lensing shouldn't be an afterthought; it needs to be part of standard procedure for any simulation involving modified gravity.

Conclusion and Wrap-up: Vera: As we wrap up this discussion, the message from "Ray-traced weak lensing convergence in screened modified gravity theories" is clear that these modifications are very important.

Jocelyn: It really highlights how much we have to worry about when interpreting data from future Stage IV surveys, since they will be incredibly precise.

Subrahmanyan: We’ve seen that the bias introduced by ignoring MG effects can be huge, especially in parameters like S eight.

Vera: I'm just glad we got to see how these two screening methods perform so that we can understand the nuances of the data better.

Jocelyn: It's a real comfort knowing that this detailed ray-tracing approach is now a standard tool for any simulation involving modified gravity.

Subrahmanyan: I think this work confirms that, while is successful, we need to be very rigorous about exploring the alternatives.

Vera: We hope that by incorporating the results of "Ray-traced weak lensing convergence in screened modified gravity theories" we can make those future surveys even more accurate.

Jocelyn: We're excited to see how these findings are integrated into real observations.

Subrahmanyan: It’s a fascinating look at the big picture, bridging theory and real data.

Lorentz Institute for Theoretical Physics, Leiden University · Leiden Observatory, Leiden University

astro-ph.CO

Submitted: 2026-04-09

Updated: 2026-09-21

Comments: 11 pages, 10 figures, 3 tables; v2: updated discussion about Fig. 3

Journal ref: Mon Not R Astron Soc (2026)

DOI: 10.1093/mnras/stag1523

Code: https://github.com/JegerBroxterman/Lensing_raytrace_FLAMINGO

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Importance score: 85/100

The gist: I am prepared to execute this extraction with the utmost diligence.

Key concepts

Modified Gravity (MG)
A theoretical framework where gravitational forces are altered from standard physics. The study explores two scenarios: one where the modification depends only on time, and another where it depends on local density and scale, a process known as screening.
Weak Lensing Convergence
A key observable used in astronomy to measure how gravity warps light. This research focuses on the 'convergence power spectrum'—the measurable pattern of this signal—to determine how modified gravity alters the expected results compared to standard physics.
Screening Methods
The concept that modified gravity effects are hidden or 'screened' in dense areas, allowing the theory to behave like standard physics locally. The paper uses two methods: one based on a halo's physical properties and another based on local overdensity.
Ray-Tracing Method
A highly accurate modeling approach used in the simulation. Instead of simple adjustments, this method tracks exactly how a light ray travels through the complex structure of space, providing detailed precision for modeling cosmology.

Terminology

Summary

I am prepared to execute this extraction with the utmost diligence. Given that this is a high-stakes analysis of Ray-traced weak lensing convergence in screened modified gravity theories, precision and adherence to the source material are paramount.

Please provide the full text of the arXiv paper. Once I have access to the document, I will immediately generate a summary that meets all specified criteria: starting with a concise orienting paragraph, followed by 3–5 detailed sections with bold headers, incorporating key quotes, and maintaining a length of 450–600 words without adding any external commentary or interpretation.

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Improvements for AI systems

This field requires extreme rigor. Based on the cited literature—which spans large-scale structure formation, dark energy characterization, galaxy clustering analysis (DESI/Euclid), and N-body simulations—the primary computational bottlenecks are handling petabyte-scale data, navigating highly non-linear physical regimes, and efficiently exploring vast cosmological parameter spaces.

Here are three specific improvements for AI systems that integrate the scientific knowledge presented in this bibliography:

Improvement: Development of dedicated PINN architectures trained on the fundamental differential equations governing structure formation, such as the continuity and Euler equations used in hydrodynamical simulations (as referenced by Schaye J., Elbers W., et al.). Instead of running computationally prohibitive N-body or hydrodynamical simulations from first principles for every parameter set, the AI system acts as a high-fidelity surrogate model.

What the Improved AI System Can Do:

  • Predict Power Spectra and Clustering: The system can accurately predict the evolution of cosmological observables (like the matter power spectrum P(k) or two-point correlation functions) for a given set of initial cosmological parameters (m, sigma 8, w(z)) in minutes, rather than months.

  • Massive Parameter Space Mapping: It allows researchers to rapidly map the entire multi-dimensional parameter space (e.g., varying w vs. m) with unprecedented speed and precision, drastically reducing the time required to constrain Dark Energy models or test alternative gravity theories (as suggested by Will C. M., 2014).

  • Error Quantification: Because it is grounded in physics, the system can provide physically consistent error bounds and identify regions of parameter degeneracy that are computationally intractable with traditional methods.

Sources

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