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Romain Teyssier

Publications and source records attributed to Romain Teyssier.

At least 55 records · Page 3Linked to original sources

Comparison between a priori and a posteriori slope limiters for high-order finite volume schemes

High-order finite volume and finite element methods offer impressive accuracy and cost efficiency when solving hyperbolic conservation laws with smooth solutions. However, if the solution contains discontinuities, these high-order methods can introduce unphysical oscillations and severe overshoots/undershoots. Slope limiters are an effective remedy, combating these oscillations by preserving monotonicity. Some limiters can even maintain a strict maximum principle in the numerical solution. They can be classified into one of two categories: \textit{a priori} and \textit{a posteriori} limiters. The former revises the high-order solution based only on data at the current time $t^n$, while the latter involves computing a candidate solution at $t^{n+1}$ and iteratively recomputing it until some conditions are satisfied. These two limiting paradigms are available for both finite volume and finite element methods. In this work, we develop a methodology to compare \textit{a priori} and \textit{a posteriori} limiters for finite volume solvers at arbitrarily high order. We select the maximum principle preserving scheme presented in \cite{zhang2011maximum, zhang2010maximum} as our \textit{a priori} limited scheme. For \textit{a posteriori} limiting, we adopt the methodology presented in \cite{clain2011high} and search for so-called \textit{troubled cells} in the candidate solution. We revise them with a robust MUSCL fallback scheme. The linear advection equation is solved in both one and two dimensions and we compare variations of these limited schemes based on their ability to maintain a maximum principle, solution quality over long time integration and computational cost. ...

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The AGORA High-resolution Galaxy Simulations Comparison Project IV: Halo and Galaxy Mass Assembly in a Cosmological Zoom-in Simulation at $z\le2$

In this fourth paper from the AGORA Collaboration, we study the evolution down to redshift $z=2$ and below of a set of cosmological zoom-in simulations of a Milky Way mass galaxy by eight of the leading hydrodynamic simulation codes. We also compare this CosmoRun suite of simulations with dark matter-only simulations by the same eight codes. We analyze general properties of the halo and galaxy at $z=4$ and 3, and before the last major merger, focusing on the formation of well-defined rotationally-supported disks, the mass-metallicity relation, the specific star formation rate, the gas metallicity gradients, and the non-axisymmetric structures in the stellar disks. Codes generally converge well to the stellar-to-halo mass ratios predicted by semi-analytic models at $z\sim$2. We see that almost all the hydro codes develop rotationally-supported structures at low redshifts. Most agree within 0.5 dex with the observed MZR at high and intermediate redshifts, and reproduce the gas metallicity gradients obtained from analytical models and low-redshift observations. We confirm that the inter-code differences in the halo assembly history reported in the first paper of the collaboration also exist in CosmoRun, making the code-to-code comparison more difficult. We show that such differences are mainly due to variations in code-dependent parameters that control the time-stepping strategy of the gravity solver. We find that variations in the early stellar feedback can also result in differences in the timing of the low-redshift mergers. All the simulation data down to $z=2$ and the auxiliary data will be made publicly available.

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The AGORA High-resolution Galaxy Simulations Comparison Project. V: Satellite Galaxy Populations In A Cosmological Zoom-in Simulation of A Milky Way-mass Halo

We analyze and compare the satellite halo populations at $z\sim2$ in the high-resolution cosmological zoom-in simulations of a $10^{12}\,{\rm M}_{\odot}$ target halo ($z=0$ mass) carried out on eight widely-used astrophysical simulation codes ({\sc Art-I}, {\sc Enzo}, {\sc Ramses}, {\sc Changa}, {\sc Gadget-3}, {\sc Gear}, {\sc Arepo-t}, and {\sc Gizmo}) for the {\it AGORA} High-resolution Galaxy Simulations Comparison Project. We use slightly different redshift epochs near $z=2$ for each code (hereafter ``$z\sim2$') at which the eight simulations are in the same stage in the target halo's merger history. After identifying the matched pairs of halos between the {\it CosmoRun} simulations and the DMO simulations, we discover that each {\it CosmoRun} halo tends to be less massive than its DMO counterpart. When we consider only the halos containing stellar particles at $z\sim2$, the number of satellite {\it galaxies} is significantly fewer than that of dark matter halos in all participating {\it AGORA} simulations, and is comparable to the number of present-day satellites near the Milky Way or M31. The so-called ``missing satellite problem' is fully resolved across all participating codes simply by implementing the common baryonic physics adopted in {\it AGORA} and the stellar feedback prescription commonly used in each code, with sufficient numerical resolution ($\lesssim100$ proper pc at $z=2$). We also compare other properties such as the stellar mass$-$halo mass relation and the mass$-$metallicity relation. Our work highlights the value of comparison studies such as {\it AGORA}, where outstanding problems in galaxy formation theory are studied simultaneously on multiple numerical platforms.

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The AGORA High-resolution Galaxy Simulations Comparison Project. VI. Similarities and Differences in the Circumgalactic Medium

We analyze the circumgalactic medium (CGM) for eight commonly-used cosmological codes in the AGORA collaboration. The codes are calibrated to use identical initial conditions, cosmology, heating and cooling, and star formation thresholds, but each evolves with its own unique code architecture and stellar feedback implementation. Here, we analyze the results of these simulations in terms of the structure, composition, and phase dynamics of the CGM. We show properties such as metal distribution, ionization levels, and kinematics are effective tracers of the effects of the different code feedback and implementation methods, and as such they can be highly divergent between simulations. This is merely a fiducial set of models, against which we will in the future compare multiple feedback recipes for each code. Nevertheless, we find that the large parameter space these simulations establish can help disentangle the different variables that affect observable quantities in the CGM, e.g., showing that abundances for ions with higher ionization energy are more strongly determined by the simulation's metallicity, while abundances for ions with lower ionization energy are more strongly determined by the gas density and temperature.

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A new star formation recipe for magneto-hydrodynamics simulations of galaxy formation

Star formation has been observed to occur at globally low yet locally varying efficiencies. As such, accurate capture of star formation in numerical simulations requires mechanisms that can replicate both its smaller-scale variations and larger-scale properties. Magnetic fields are thought to play an essential role within the turbulent interstellar medium (ISM) and affect molecular cloud collapse. However, it remains to be fully explored how a magnetised model of star formation might influence galaxy evolution. We present a new model for a sub-grid star formation recipe that depends on the magnetic field. We run isolated disk galaxy simulations to assess its impact on the regulation of star formation using the code RAMSES. Building upon existing numerical methods, our model derives the star formation efficiency from local properties of the sub-grid magnetised ISM turbulence, assuming a constant Alfvén speed at sub-parsec scales. Compared to its non-magnetised counterpart, our star formation model suppresses the initial starburst by a factor of two, while regulating star formation later on to a nearly constant rate of $\sim 1~M_{\odot}~\mathrm{yr}^{-1}$. Differences also arise in the local Schmidt law with a shallower power law index for the magnetised star formation model. Our results encourage further examination into the notion that magnetic fields are likely to play a non-trivial role in our understanding of star and galaxy formation.

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Cosmology with Galaxy Photometry Alone

We present the first cosmological constraints using only the observed photometry of galaxies. Villaescusa-Navarro et al. (2022; arXiv:2201.02202) recently demonstrated that the internal physical properties of a single simulated galaxy contain a significant amount of cosmological information. These physical properties, however, cannot be directly measured from observations. In this work, we present how we can go beyond theoretical demonstrations to infer cosmological constraints from actual galaxy observables (e.g. optical photometry) using neural density estimation and the CAMELS suite of hydrodynamical simulations. We find that the cosmological information in the photometry of a single galaxy is limited. However, we combine the constraining power of photometry from many galaxies using hierarchical population inference and place significant cosmological constraints. With the observed photometry of $\sim$20,000 NASA-Sloan Atlas galaxies, we constrain $Ω_m = 0.323^{+0.075}_{-0.095}$ and $σ_8 = 0.799^{+0.088}_{-0.085}$.

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Cosmic Variance and the Inhomogeneous UV Luminosity Function of Galaxies During Reionization

When the first galaxies formed and starlight escaped into the intergalactic medium to reionize it, galaxy formation and reionization were both highly inhomogeneous in time and space, and fully-coupled by mutual feedback. To show how this imprinted the UV luminosity function (UVLF) of reionization-era galaxies, we use our large-scale, radiation-hydrodynamics simulation CoDa II to derive the time- and space-varying halo mass function and UVLF, from $z\simeq6$-15. That UVLF correlates strongly with local reionization redshift: earlier-reionizing regions have UVLFs that are higher, more extended to brighter magnitudes, and flatter at the faint end than later-reionizing regions observed at the same $z$. In general, as a region reionizes, the faint-end slope of its local UVLF flattens, and, by $z=6$ (when reionization ended), the global UVLF, too, exhibits a flattened faint-end slope, `rolling-over' at $M_\text{UV}\gtrsim-17$. CoDa II's UVLF is broadly consistent with cluster-lensed galaxy observations of the Hubble Frontier Fields at $z=6$-8, including the faint end, except for the faintest data point at $z=6$, based on one galaxy at $M_\text{UV}=-12.5$. According to CoDa II, the probability of observing the latter is $\sim5\%$. However, the effective volume searched at this magnitude is very small, and is thus subject to significant cosmic variance. We find that previous methods adopted to calculate the uncertainty due to cosmic variance underestimated it on such small scales by a factor of 2-4, primarily by underestimating the variance in halo abundance when the sample volume is small.

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Robust Field-level Likelihood-free Inference with Galaxies

We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our models are rotational, translational, and permutation invariant and do not impose any cut on scale. From galaxy catalogs that only contain $3$D positions and radial velocities of $\sim 1, 000$ galaxies in tiny $(25~h^{-1}{\rm Mpc})^3$ volumes our models can infer the value of $Ω_{\rm m}$ with approximately $12$ % precision. More importantly, by testing the models on galaxy catalogs from thousands of hydrodynamic simulations, each having a different efficiency of supernova and AGN feedback, run with five different codes and subgrid models - IllustrisTNG, SIMBA, Astrid, Magneticum, SWIFT-EAGLE -, we find that our models are robust to changes in astrophysics, subgrid physics, and subhalo/galaxy finder. Furthermore, we test our models on $1,024$ simulations that cover a vast region in parameter space - variations in $5$ cosmological and $23$ astrophysical parameters - finding that the model extrapolates really well. Our results indicate that the key to building a robust model is the use of both galaxy positions and velocities, suggesting that the network have likely learned an underlying physical relation that does not depend on galaxy formation and is valid on scales larger than $\sim10~h^{-1}{\rm kpc}$.

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Code Comparison in Galaxy Scale Simulations with Resolved Supernova Feedback: Lagrangian vs. Eulerian Methods

We present a suite of high-resolution simulations of an isolated dwarf galaxy using four different hydrodynamical codes: {\sc Gizmo}, {\sc Arepo}, {\sc Gadget}, and {\sc Ramses}. All codes adopt the same physical model which includes radiative cooling, photoelectric heating, star formation, and supernova (SN) feedback. Individual SN explosions are directly resolved without resorting to sub-grid models, eliminating one of the major uncertainties in cosmological simulations. We find reasonable agreement on the time-averaged star formation rates as well as the joint density-temperature distributions between all codes. However, the Lagrangian codes show significantly burstier star formation, larger supernova-driven bubbles, and stronger galactic outflows compared to the Eulerian code. This is caused by the behavior in the dense, collapsing gas clouds when the Jeans length becomes unresolved: gas in Lagrangian codes collapses to much higher densities than in Eulerian codes, as the latter is stabilized by the minimal cell size. Therefore, more of the gas cloud is converted to stars and SNe are much more clustered in the Lagrangian models, amplifying their dynamical impact. The differences between Lagrangian and Eulerian codes can be reduced by adopting a higher star formation efficiency in Eulerian codes, which significantly enhances SN clustering in the latter. Adopting a zero SN delay time reduces burstiness in all codes, resulting in vanishing outflows as SN clustering is suppressed.

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Cosmology with one galaxy? -- The ASTRID model and robustness

Recent work has pointed out the potential existence of a tight relation between the cosmological parameter $Ω_{\rm m}$, at fixed $Ω_{\rm b}$, and the properties of individual galaxies in state-of-the-art cosmological hydrodynamic simulations. In this paper, we investigate whether such a relation also holds for galaxies from simulations run with a different code that made use of a distinct subgrid physics: Astrid. We find that also in this case, neural networks are able to infer the value of $Ω_{\rm m}$ with a $\sim10\%$ precision from the properties of individual galaxies while accounting for astrophysics uncertainties as modeled in CAMELS. This tight relationship is present at all considered redshifts, $z\leq3$, and the stellar mass, the stellar metallicity, and the maximum circular velocity are among the most important galaxy properties behind the relation. In order to use this method with real galaxies, one needs to quantify its robustness: the accuracy of the model when tested on galaxies generated by codes different from the one used for training. We quantify the robustness of the models by testing them on galaxies from four different codes: IllustrisTNG, SIMBA, Astrid, and Magneticum. We show that the models perform well on a large fraction of the galaxies, but fail dramatically on a small fraction of them. Removing these outliers significantly improves the accuracy of the models across simulation codes.

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INFERNO: Galactic winds in dwarf galaxies with star-by-star simulations including runaway stars

The formation and evolution of galaxies have proved sensitive to the inclusion of stellar feedback, which is therefore crucial to any successful galaxy model. We present INFERNO, a new model for hydrodynamic simulations of galaxies, which incorporates resolved stellar objects with star-by-star calculations of when and where the injection of enriched material, momentum, and energy takes place. INFERNO treats early stellar kinematics to include phenomena such as walkaway and runaway stars. We employ this innovative model on simulations of a dwarf galaxy and demonstrate that our physically motivated stellar feedback model can drive vigorous galactic winds. This is quantified by mass and metal loading factors in the range of $10-100$, and an energy loading factor close to unity. Outflows are established close to the disc, are highly multi-phase, spanning almost $8$ orders of magnitude in temperature, and with a clear dichotomy between mass ejected in cold, slow-moving ($T\lesssim5\times10^4\,{\rm K}$, $v<100\,{\rm km\,s}^{-1}$) gas and energy ejected in hot, fast-moving ($T>10^6\,{\rm K}$, $v>100\,{\rm km\,s}^{-1}$) gas. In contrast to massive disc galaxies, we find a surprisingly weak impact of the early stellar kinematics, with runaway stars having little to no effect on our results, despite exploding in diffuse gas outside the dense star-forming gas, as well as outside the galactic disc entirely. We demonstrate that this weak impact in dwarf galaxies stems from a combination of strong feedback and a porous interstellar medium, which obscure any unique signatures that runaway stars provide.

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A universal equation to predict $Ω_{\rm m}$ from halo and galaxy catalogues

We discover analytic equations that can infer the value of $Ω_{\rm m}$ from the positions and velocity moduli of halo and galaxy catalogues. The equations are derived by combining a tailored graph neural network (GNN) architecture with symbolic regression. We first train the GNN on dark matter halos from Gadget N-body simulations to perform field-level likelihood-free inference, and show that our model can infer $Ω_{\rm m}$ with $\sim6\%$ accuracy from halo catalogues of thousands of N-body simulations run with six different codes: Abacus, CUBEP$^3$M, Gadget, Enzo, PKDGrav3, and Ramses. By applying symbolic regression to the different parts comprising the GNN, we derive equations that can predict $Ω_{\rm m}$ from halo catalogues of simulations run with all of the above codes with accuracies similar to those of the GNN. We show that by tuning a single free parameter, our equations can also infer the value of $Ω_{\rm m}$ from galaxy catalogues of thousands of state-of-the-art hydrodynamic simulations of the CAMELS project, each with a different astrophysics model, run with five distinct codes that employ different subgrid physics: IllustrisTNG, SIMBA, Astrid, Magneticum, SWIFT-EAGLE. Furthermore, the equations also perform well when tested on galaxy catalogues from simulations covering a vast region in parameter space that samples variations in 5 cosmological and 23 astrophysical parameters. We speculate that the equations may reflect the existence of a fundamental physics relation between the phase-space distribution of generic tracers and $Ω_{\rm m}$, one that is not affected by galaxy formation physics down to scales as small as $10~h^{-1}{\rm kpc}$.

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Spectral Difference method with a posteriori limiting: Application to the Euler equations in one and two space dimensions

We present a new numerical scheme which combines the Spectral Difference (SD) method up to arbitrary high order with \emph{a-posteriori} limiting using the classical MUSCL-Hancock scheme as fallback scheme. It delivers very accurate solutions in smooth regions of the flow, while capturing sharp discontinuities without spurious oscillations. We exploit the strict equivalence between the SD scheme and a Finite-Volume (FV) scheme based on the SD control volumes to enable a straightforward limiting strategy. At the end of each stage of our high-order time-integration ADER scheme, we check if the high-order solution is admissible under a number of numerical and physical criteria. If not, we replace the high-order fluxes of the troubled cells by fluxes from our robust second-order MUSCL fallback scheme. We apply our method to a suite of test problems for the 1D and 2D Euler equations. We demonstrate that this combination of SD and ADER provides a virtually arbitrary high order of accuracy, while at the same time preserving good sub-element shock capturing capabilities.

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Dust dynamics in RAMSES -- I. Methods and turbulent acceleration

Supernova ejecta and stellar winds are believed to produce interstellar dust grains with relatively large sizes. Smaller grains can be produced via the shattering of large grains that have been stochastically accelerated. To understand this stochastic acceleration, we have implemented novel magnetohydrodynamic(MHD)-particle-in-cell(PIC) methods into the astrophysical fluid code RAMSES. We treat dust grains as a set of massive ``superparticles'' that experience aerodynamic drag and Lorentz force. We subject our code to a range of numerical tests designed to validate our method in different physical conditions, as well as to illustrate possible mechanisms by which grains can be accelerated. As a final test as well as a foundation for future work, we present the results of decaying dusty MHD turbulence simulations with grain parameters chosen to resemble 1-2 $μ$m grains in typical cold neutral medium conditions. We find that in these conditions, these grains can be effectively accelerated to well beyond their shattering velocities. This is true for both electrically charged and neutral grains. While the peak of the gas-grain relative drift velocity distribution is higher for neutral grains, the drift velocity distribution of charged grains exhibits an extended exponential tail out to much greater velocities. Even so, the shapes of the distributions are such that the extra gas-grain coupling provided by the Lorentz force offers grains relative protection from shattering. We also discuss the connection between our simulations and the relatively pristine ~$μ$m sized presolar grains that do not appear to have undergone significant wear in their lifetimes.

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Robust field-level inference with dark matter halos

We train graph neural networks on halo catalogues from Gadget N-body simulations to perform field-level likelihood-free inference of cosmological parameters. The catalogues contain $\lesssim$5,000 halos with masses $\gtrsim 10^{10}~h^{-1}M_\odot$ in a periodic volume of $(25~h^{-1}{\rm Mpc})^3$; every halo in the catalogue is characterized by several properties such as position, mass, velocity, concentration, and maximum circular velocity. Our models, built to be permutationally, translationally, and rotationally invariant, do not impose a minimum scale on which to extract information and are able to infer the values of $Ω_{\rm m}$ and $σ_8$ with a mean relative error of $\sim6\%$, when using positions plus velocities and positions plus masses, respectively. More importantly, we find that our models are very robust: they can infer the value of $Ω_{\rm m}$ and $σ_8$ when tested using halo catalogues from thousands of N-body simulations run with five different N-body codes: Abacus, CUBEP$^3$M, Enzo, PKDGrav3, and Ramses. Surprisingly, the model trained to infer $Ω_{\rm m}$ also works when tested on thousands of state-of-the-art CAMELS hydrodynamic simulations run with four different codes and subgrid physics implementations. Using halo properties such as concentration and maximum circular velocity allow our models to extract more information, at the expense of breaking the robustness of the models. This may happen because the different N-body codes are not converged on the relevant scales corresponding to these parameters.

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Cosmological simulations of the same spiral galaxy: the impact of baryonic physics

The interplay of star formation and supernova (SN) feedback in galaxy formation is a key element for understanding galaxy evolution. Since these processes occur at small scales, it is necessary to have sub-grid models that recover their evolution and environmental effects at the scales reached by cosmological simulations. We simulate the same spiral galaxy inhabiting a Milky Way (MW) size halo in a cosmological environment changing the sub-grid models for SN feedback and star formation. We test combinations of the Schmidt law and a multi-freefall based star formation with delayed cooling feedback or mechanical feedback. We reach a resolution of 35 pc in a zoom-in box of 36 Mpc. For this, we use the code RAMSES with the implementation of gas turbulence in time and trace the local hydrodynamical features of the star-forming gas. Finally, we compare the galaxies at redshift 0 with global and interstellar medium observations in the MW and local spiral galaxies. The simulations show successful comparisons with observations. Nevertheless, diverse galactic morphologies are obtained from different numerical implementations. We highlight the importance of detailed modelling of the star formation and feedback processes, especially when increasing the resolution of simulations. Future improvements could alleviate the degeneracies exhibited in our simulated galaxies under different sub-grid models.

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Redshift and stellar mass dependence of intrinsic shapes of disc-dominated galaxies from COSMOS observations below $z = 1.0$

The high abundance of disc galaxies without a large central bulge challenges predictions of current hydrodynamic simulations of galaxy formation. We aim to shed light on the formation of these objects by studying the redshift and mass dependence of their intrinsic 3D shape distributions in the COSMOS galaxy survey below redshift $z=1.0$. This distribution is inferred from the observed distribution of 2D shapes, using a reconstruction method which we test using hydrodynamic simulations. Our tests reveal a moderate bias for the inferred average disc circularity and relative thickness, but a large bias on the dispersion of these quantities. Applying the reconstruction method on COSMOS data, we find variations of the average disc circularity and relative thickness with redshift of around $\sim1\%$ and $\sim10\%$ respectively, which is comparable to the error estimates on these quantities. The average relative disc thickness shows a significant mass dependence which can be accounted for by the scaling of disc radius with galaxy mass. We conclude that our data provides no evidence for a strong dependence of the average circularity and absolute thickness of disc-dominated galaxies on redshift and mass that is significant with respect to the statistical uncertainties in our analysis. These findings are expected in the absence of disruptive merging or feedback events that would affect galaxy shapes. They hence support a scenario where present-day discs form early ($z>1.0$) and subsequently undergo a tranquil evolution in isolation. However, more data and a better understanding of systematics are needed to reaffirm our results.

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The short ionizing photon mean free path at z=6 in Cosmic Dawn III, a new fully-coupled radiation-hydrodynamical simulation of the Epoch of Reionization

Recent determinations of the mean free path of ionising photons (mfp) in the intergalactic medium (IGM) at $\rm z=6$ are lower than many theoretical predictions. To gain insight into this issue, we investigate the evolution of the mfp in our new massive fully coupled radiation hydrodynamics cosmological simulation of reionization: Cosmic Dawn III (CoDaIII). CoDaIII's scale ($\rm 94^3 \, cMpc^3$) and resolution ($\rm 8192^3$ grid) make it particularly suitable to study the evolution of the IGM during Reionization. The simulation was performed with RAMSES-CUDATON on Summit, and used 131072 processors coupled to 24576 GPUs, making it the largest Reionization simulation, and largest RAMSES simulation ever performed. A superior agreement with global constraints on Reionization is obtained in CoDaIII over CoDaII especially for the evolution of the neutral hydrogen fraction and the cosmic photo-ionization rate, thanks to an improved calibration, later end of reionization ($\rm z=5.6$), and higher spatial resolution. Analyzing the mfp, we find that CoDaIII reproduces the most recent observations very well, from $\rm z=6$ to $\rm z=4.6$. We show that the distribution of the mfp in CoDaIII is bimodal, with short (neutral) and long (ionized) mfp modes, respectively, due to the patchiness of reionization and the co-existence of neutral versus ionized regions during Reionization. The neutral mode peaks at sub-kpc to kpc scales of mfp, while the ionized mode peak evolves from $\rm 0.1 Mpc/h$ at $\rm z=7$ to $\sim 10$ Mpc/h at $\rm z=5.2$. Computing the mfp as the average of the ionized mode provides the best match to the recent observational determinations. The distribution reduces to a single neutral (ionized) mode at $\rm z>13$ ($\rm z<5$).

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