Richard Brooks

Simulation Based Inference

3 related publications

• The Milky Way–Large Magellanic Cloud interaction with simulation-based inferenceBrooks et al. 2026b · MNRAS 550, stag1254
• Quantifying the Milky Way, LMC and their interaction using all-sky kinematics of outer halo starsBrooks et al. 2026a · MNRAS 549, stag926
• A simulation-based inference approach to the dynamics of the MW–LMC system — validationBrooks et al. 2025b · MNRAS 545, staf2111

Simulation Based Inference (SBI) is a technique to infer parameters of interest from some given dataset. SBI is a powerful method for estimating the parameter posterior distributions when a likelihood function cannot be explicitly defined, or is intractable from simulation. Instead, forward simulations of the model are used to generate samples of the data and parameters. This technique is also known as “Likelihood Free Inference" or “Distribution Free inference". Although these names are slightly misleading as the inference is not likelihood-free, rather we avoid explicitly defining a likelihood and instead model it using many forward simulations. SBI has been applied across many fields of research: from mathematics, to quantitative finance, to seismology. Increasingly, SBI is being used throughout astrophysics as well. Therefore, SBI is set to become an effective lingua franca for facilitating communication across many scientific disciplines. The simplest form of SBI is known as Approximate Bayesian Computation (ABC). The ABC framework selects forward simulations that are the most similar to the observed data based on some distance measure involving the summary statistics of the simulation. Another way to get the posterior is via Density Estimation Likelihood Free Inference (DELFI). In this approach, all existing forward simulations are used to learn a conditional density distribution of the data given the simulation parameters using a density estimation algorithm, e.g., normalising flows that utilise a series of transformations to convert a simple base distribution into the desired probability distribution. DELFI is advantageous over the simpler ABC approach as it does not rely on a choice of a distance measure and it uses all available forward simulations to build the posterior distribution, making it far more efficient. Additionally, once a normalising flow has been trained on a precomputed simulation dataset, the posterior can be returned for many observations without having to retrain the flow. This is known as amortisation and is a benefit over more classical approaches to estimate the posterior, e.g., Markov Chain Monte Carlo, as these methods need to be re-evaluated every time a new observation becomes available. Our approach in (Brooks et al. 2025b) is to use SBI in order to better understand the dynamics of the MW-LMC merger.

In my latest work I have applied this SBI architecture to data from the Dark Energy Spectroscopic Instrument blue horizontal branch and H3+SEGUE+MagE red giant branch datasets to provide constraints on the MW and LMC dark matter masses, and the reflex motion (Brooks et al. 2026b). For the H3+SEGUE+MagE data, I found that the total mass of the LMC must be at least 10% of the Milky Way's total mass. This framework allows us to explore the effects of survey sky coverage and the availability of velocity information for stars in the outer halo on parameter constraints. Given these vary between surveys, this flexible and reliable SBI technique will be highly consequential to constrain the dark matter content of the MW and LMC, plus the reflex velocity, given the upcoming influx of outer halo datasets.

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Stellar Streams

2 related publications

• LMC Calls, Milky Way Halo Answers: Disentangling the Effects of the MW–LMC Interaction on Stellar Stream PopulationsBrooks et al. 2025a · ApJ 978, 79
• Action and energy clustering of stellar streams in deforming Milky Way dark matter haloesBrooks et al. 2024 · MNRAS 532, 2657

The dark matter halo of a galaxy has an abundance of substructure. This substructure results from the process of accreting material from smaller satellite galaxies. Debris from the satellites is tidally stripped by the central galaxy, forming long tidal streams of stars. These structures are of interest as they reveal something about the gravitational potential of the central galaxy, and hence the underlying dark matter distribution. Perturbations to the gravitational potential over time can be investigated using streams. Particularly those that pass close to the source of the perturbation. Of note is the recent major merger of the Milky Way with the Large Magellanic Cloud (LMC). Modelling tidal streams is often a complex process in phase-space coordinates. An alternative approach is to model streams in the action-angle space. By transformation to this canonical coordinate system, the actions represent constants of motion along a particle's orbit in the host galaxy's potential, while the angles determine the position of the particle through its orbit. The time-dependent nature of the Milky Way's history raises the question that these actions may not be invariant over time as thought to be in the time-independent histories (Brooks et al. 2024) More generally, the dynamical perturbations that the LMC induced on the population of stellar streams in the Milky Way is an exciting way to decipher properties of the LMC and the adopted dark matter model (Brooks et al. 2025a)

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Galaxy Merger with the Large Magellanic Cloud

5 related publications

• The Milky Way–Large Magellanic Cloud interaction with simulation-based inferenceBrooks et al. 2026b · MNRAS 550, stag1254
• Quantifying the Milky Way, LMC and their interaction using all-sky kinematics of outer halo starsBrooks et al. 2026a · MNRAS 549, stag926
• A simulation-based inference approach to the dynamics of the MW–LMC system — validationBrooks et al. 2025b · MNRAS 545, staf2111
• LMC Calls, Milky Way Halo Answers: Disentangling the Effects of the MW–LMC Interaction on Stellar Stream PopulationsBrooks et al. 2025a · ApJ 978, 79
• Action and energy clustering of stellar streams in deforming Milky Way dark matter haloesBrooks et al. 2024 · MNRAS 532, 2657

LCDM cosmological models predict the shapes of dark matter haloes to be triaxial. From observations, the shapes of dark matter haloes can be very different. The evolution and properties of a galaxy are strongly influenced by merger events. Within the Local Group, the MW is undergoing a merger with the Large Magellanic Cloud (LMC). The LMC is thought to be on its first pericentric passage and has a merger ratio with the Milky Way (MW) of ~1:8. The LMC has been observed to generate significant disequilibrium in the MW gravitational potential, e.g. displacing the MW disc, creating a stellar over-density, and generating the reflex motion of the stellar halo. Due to the merger with the LMC, the potential of the MW is unlikely to be invariant and will deform non-linearly. Basis function expansions (BFEs) act to reduce non-linear systems to linear ones by the transformation to a well-motivated choice of basis functions. As such, BFEs offer the flexibility to model the deformations of the dark matter haloes captured in N-body simulations. The MW-LMC N-body simulations of Lilleengen et al. 2023 infer a BFE description using the EXP toolkit. The harmonic orders of the BFE will develop over the entire simulation. At the beginning of the live simulation, and for all prior times, there has yet to be any response of the MW's dark matter halo due to the passage of the LMC. The in-fall of the LMC as the satellite galaxy onto the MW as the central host generates density wakes. The classical `conic' wake trailing the LMC is described as the transient response, whereas the response elsewhere in the MW halo is the collective response. In the below animation, you can see the temporal development of the MW halo density contrast due to the LMC's passage for both isolated harmonic subsets and the full basis expansion simulation of the MW--LMC simulation.

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Dark Matter Paradigms

2 related publications

• The north–south asymmetry of the ALFALFA HI velocity width functionBrooks, Oman & Frenk 2023a · MNRAS 522, 4043
• Origins of the north–south asymmetry in the ALFALFA HI velocity width functionBrooks, Oman & Frenk 2023b · Proc. IAU 19 (IAUS 379), 324

To this day, the fiducial Lambda Cold Dark Matter (LCDM) model still competes against alternative models that can potentially alleviate some tensions found with LCDM. A novel way to constrain dark matter models is possible through measuring the kinematic signatures of atomic hydrogen (HI) in galaxies. The 21-cm emission line of HI gas is broadened due to a galaxy's rotation. The extent of such broadening in a given galaxy is sensitive to the size, and hence mass of the dark matter halo hosting the gas. The use of HI gas as a visible tracer for the dark matter distribution allows us to connect the dark universe to measurable quantities. (Brooks, Oman & Frenk 2023a)

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Galactic Chemical Evolution Models

Coming soon!

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Publications

9 publications · 7 first author

The full list is also on NASA ADS and arXiv.

2026

• The Milky Way–Large Magellanic Cloud interaction with simulation-based inferenceR. A. N. Brooks, J. L. Sanders, V. Chandra, et al.MNRAS 550, stag1254
• The Velocity Field of Our Milky Way Outer Stellar Halo Based on DESI DR2S. Li, W. Wang, S. E. Koposov, et al. (including R. A. N. Brooks)ApJ 1005, 19
• Quantifying the Milky Way, LMC and their interaction using all-sky kinematics of outer halo starsR. A. N. Brooks, J. L. Sanders, A. M. Dillamore, et al.MNRAS 549, stag926
• GSE versus LMC: reshaping of radially biased stellar haloes by satellitesA. M. Dillamore, J. L. Sanders, R. A. N. BrooksMNRAS 549, stag1110

2025

• A simulation-based inference approach to the dynamics of the MW–LMC system — validationR. A. N. Brooks, J. L. Sanders, A. M. Dillamore, et al.MNRAS 545, staf2111
• LMC Calls, Milky Way Halo Answers: Disentangling the Effects of the MW–LMC Interaction on Stellar Stream PopulationsR. A. N. Brooks, N. Garavito-Camargo, K. V. Johnston, et al.ApJ 978, 79

2024

• Action and energy clustering of stellar streams in deforming Milky Way dark matter haloesR. A. N. Brooks, J. L. Sanders, S. Lilleengen, et al.MNRAS 532, 2657

2023

• Origins of the north–south asymmetry in the ALFALFA HI velocity width functionR. A. N. Brooks, K. A. Oman, C. S. FrenkProc. IAU 19, 324
• The north–south asymmetry of the ALFALFA HI velocity width functionR. A. N. Brooks, K. A. Oman, C. S. FrenkMNRAS 522, 4043

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Invited Talks & Seminars

15 talks

2026

• ‘Measuring the Dynamics of the MW–LMC Interaction with Simulation-Based Inference’Departmental seminar · University of LundApril 2026
• ‘The effects of the Milky Way – Large Magellanic Cloud interaction on stellar streams’Departmental seminar · Niels Bohr Institute, University of CopenhagenApril 2026
• ‘Measuring the Dynamics of the MW–LMC Interaction with Simulation-Based Inference’Friday Late Afternoon Talk · University College LondonMarch 2026
• ‘The Milky Way in Dynamical Disequilibrium’Departmental seminar · University of SurreyMarch 2026

2025

• ‘Measuring the Dynamics of the MW–LMC Interaction with Simulation-Based Inference’Invited talk · Galaxies group meeting, Columbia UniversityOctober 2025
• ‘Measuring the Dynamics of the MW–LMC Interaction with Simulation-Based Inference’Invited talk · Institute for Theory and Computation Luncheon Talk, Harvard University, Center for AstrophysicsOctober 2025
• ‘Studying the Milky Way and Large Magellanic Cloud using Simulation Based Inference’Invited talk · Center for Doctoral Training in Data Intensive Science, University College LondonMay 2025

2024

• ‘Stream actions and energies in deforming Milky Way haloes’Invited talk · MAT talk, Massachusetts Institute of TechnologyMay 2024
• ‘Stream actions and energies in deforming Milky Way haloes’Invited talk · Conroy and Hernquist group meetings, Harvard University, Center for AstrophysicsMarch 2024
• ‘Stream actions and energies in deforming Milky Way haloes’Invited talk · Coffee talk, Institute for Advanced Study, Princeton UniversityMarch 2024
• ‘Stream actions and energies in deforming Milky Way haloes’Invited talk · Robyn Sanderson group meeting, University of PennsylvaniaMarch 2024
• ‘Stream actions and energies in deforming Milky Way haloes’Invited talk · Milky Way Stars group meeting, Columbia UniversityMarch 2024

2023

• ‘Action and energy clustering of stellar streams in deforming Milky Way dark matter haloes’Invited talk · Surrey London Astro Meeting, University of SurreyDecember 2023
• ‘ΛCDM survives another day: Origins of the asymmetry in the ALFALFA survey’Invited talk · Institute for Computational Cosmology, Durham UniversityApril 2023
• ‘ΛCDM survives another day: Origins of the asymmetry in the ALFALFA survey’Invited talk · University of HelsinkiMarch 2023

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Conference Talks

10 talks

2026

• ‘Quantifying the MW–LMC Interaction with Simulation-Based Inference’Contributed talk · Simulation Based Inference for Galaxy Evolution Conference, University of CambridgeJune 2026

2025

• ‘The impact of the Milky Way – Large Magellanic Cloud interaction on stellar stream populations’Contributed talk · IAU 403 Conference: The Hidden Beauty of the Galactic Outskirts, CórdobaOctober 2025
• ‘Studying the Milky Way and Large Magellanic Cloud using Simulation Based Inference’Contributed talk · National Astronomy Meeting, Durham UniversityJuly 2025
• ‘Stellar streams and disequilibrium in the Milky Way’Contributed talk · National Astronomy Meeting, Durham UniversityJuly 2025
• ‘Stellar streams and disequilibrium in the Milky Way’Contributed talk · Milky Clouds over Yellowstone workshop, Bozeman, MontanaMay 2025

2024

• ‘Stellar streams and disequilibrium in the Milky Way’Contributed talk · Streams24 Workshop, Durham UniversityAugust 2024
• ‘Stellar streams and disequilibrium in the Milky Way’Flash talk · Small Galaxies, Cosmic Questions II, Durham UniversityJuly 2024
• ‘Stellar streams and disequilibrium in the Milky Way: The influence of the Large Magellanic Cloud’Symposium talk · CCA Pre-Doc Symposium, Flatiron Institute, Center for Computational AstrophysicsJune 2024
• ‘Stream actions and energies in deforming Milky Way haloes’Contributed talk · Milky Clouds over Manhattan workshop, Flatiron Institute, Center for Computational AstrophysicsFebruary 2024

2023

• ‘The north-south asymmetry of the ALFALFA HI velocity width function’Poster and flash talk · IAUS 379: Dynamical Masses of Local Group GalaxiesMarch 2023

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