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Rodrigo Ibata

Publications and source records attributed to Rodrigo Ibata.

At least 37 records · Page 2Linked to original sources
arXiv2024

Scale-dependent local primordial non-Gaussianity as a solution to the $S_8$ tension

For the last decade, several probes have pointed to a cosmological tension between the amplitude of density fluctuations extrapolated from the cosmic microwave background within the standard cosmological model and the one encapsulated by the $S_8$ parameter from large scale structure. The origin of this $S_8$ tension has not yet been elucidated and may hint at systematics in the data, unaccounted effects from baryonic physics, or new physics beyond the standard model of cosmology. Baryonic physics may in principle provide a nonlinear solution to the tension by suppressing the matter power spectrum more strongly on nonlinear scales than is traditionally assumed. Such a solution would not worsen the Hubble tension, contrary to many other proposed solutions to the $S_8$ tension. However, no realistic baryonic feedback in hydrodynamical simulations provides the needed suppression as a function of redshift. Here, we point out that a scale-dependence of local-type primordial non-Gaussianities (PNG), with significant PNG at scales of a few Mpc, can provide the needed suppression, since such PNG can suppress the power spectrum at slightly larger scales than baryons do. We demonstrate this by devising collisionless numerical simulations of structure formation in boxes of 0.5 Gpc/$h$ with scale-dependent local-type PNG. Our simple models show that, as a proof of principle, scale-dependent PNG, with a Gaussian random field for primordial density fluctuations on large scales and $f_{\rm NL} \simeq -300$ at $\lesssim 10$ Mpc scales, together with state-of-the-art baryonification of the matter power spectrum, can in principle solve the $S_8$ tension. The $S_8$ tension would then be a smoking-gun of non-trivial inflationary physics.

astro-ph.CO↗
arXiv2024

Simulations of cluster ultra-diffuse galaxies in MOND

Ultra-diffuse galaxies (UDGs) in the Coma cluster have velocity dispersion profiles that are in full agreement with the predictions of Modified Newtonian Dynamics (MOND) in isolation. However, the external field effect (EFE) from the cluster seriously deteriorates this agreement. It has been suggested that this could be related to the fact that UDGs are out-of-equilibrium objects whose stars have been heated by the cluster tides or that they recently fell onto the cluster on radial orbits, such that their velocity dispersion may not reflect the EFE at their instantaneous distance from the cluster center. Here, we simulate UDGs within the Coma cluster in MOND, using the Phantom of Ramses (\textsc{por}) code, and show that if UDGs are initially at equilibrium within the cluster, tides are not sufficient to increase their velocity dispersions to values as high as the observed ones. On the other hand, if they are on a first radial infall onto the cluster, they can keep high velocity dispersions without being destroyed until their first pericentric passage. We conclude that, without alterations such as a screening of the EFE in galaxy clusters or much higher baryonic masses than currently estimated, in the MOND context UDGs must be out-of-equilibrium objects on their first infall onto the cluster.

astro-ph.GA↗
arXiv2024

Class Symbolic Regression: Gotta Fit 'Em All

We introduce 'Class Symbolic Regression' (Class SR) a first framework for automatically finding a single analytical functional form that accurately fits multiple datasets - each realization being governed by its own (possibly) unique set of fitting parameters. This hierarchical framework leverages the common constraint that all the members of a single class of physical phenomena follow a common governing law. Our approach extends the capabilities of our earlier Physical Symbolic Optimization ($Φ$-SO) framework for Symbolic Regression, which integrates dimensional analysis constraints and deep reinforcement learning for unsupervised symbolic analytical function discovery from data. Additionally, we introduce the first Class SR benchmark, comprising a series of synthetic physical challenges specifically designed to evaluate such algorithms. We demonstrate the efficacy of our novel approach by applying it to these benchmark challenges and showcase its practical utility for astrophysics by successfully extracting an analytic galaxy potential from a set of simulated orbits approximating stellar streams.

cs.LG↗
arXiv2024

Micro galaxies in LCDM

A fundamental prediction of the Lambda Cold Dark Matter (LCDM) cosmology is the centrally divergent cuspy density profile of dark matter haloes. Density cusps render CDM haloes resilient to tides, and protect dwarf galaxies embedded in them from full tidal disruption. The hierarchical assembly history of the Milky Way may therefore give rise to a population of micro galaxies; i.e., heavily stripped remnants of early accreted satellites, which may reach arbitrarily low luminosity. Assuming that the progenitor systems are dark matter dominated, we use an empirical formalism for tidal stripping to predict the evolution of the luminosity, size, and velocity dispersion of such remnants, tracing their tidal evolution across multiple orders of magnitude in mass and size. The evolutionary tracks depend sensitively on the progenitor distribution of stellar binding energies. We explore three cases that likely bracket most realistic models of dwarf galaxies: one where the energy distribution of the most tightly bound stars follows that of the dark matter, and two where stars are defined by either an exponential density or surface brightness profile. The tidal evolution in the size-velocity dispersion plane is quite similar for these three models, although their remnants may differ widely in luminosity. Micro galaxies are therefore best distinguished from globular clusters by the presence of dark matter; either directly, by measuring their velocity dispersion, or indirectly, by examining their tidal resilience. Our work highlights the need for further theoretical and observational constraints on the stellar energy distribution in dwarf galaxies.

astro-ph.GA↗
arXiv2024

From inflation to dark matter halo profiles: the impact of primordial non-Gaussianities on the central density cusp

It has recently been shown that local primordial non-Gaussianities (PNG) with significant amplitude ($|f_{\rm NL}| \sim 1000$), at small (Mpc) scales, can help in forming simulated galaxies with more disky baryonic kinematics than in the Gaussian case, while generating matter power spectra that can differ by up to 20% from the Gaussian case at non-linear scales. Here, we explore in detail the consequences of such small-scale PNG on the dark matter halo profiles. We show in particular that, for negative $f_{\rm NL}$, dark matter halos formed in collisionless simulations are not always well described by the traditional Navarro-Frenk-White (NFW) profiles, as supported by their sparsity distribution. We conclude that NFW profiles are not as clear attractors for the density profiles of dark matter halos in the presence of PNG than in the case of a Gaussian contrast density field. We show how alternatives to the NFW profile can describe halos both in the Gaussian and non-Gaussian cases. From the combination of our sparsity analysis and the quality of the adjustments of the density profiles with a minimal extension to NFW, we conclude that $z=1$ halos carry the most interesting information about PNG

astro-ph.CO↗
arXiv2024

Typhon: a polar stream from the outer halo raining through the Solar neighborhood

We report on the discovery in the Gaia DR3 astrometric and spectroscopic catalog of a new polar stream that is found as an over-density in action space. This structure is unique as it has an extremely large apocenter distance, reaching beyond 100 kpc, and yet is detected as a coherent moving structure in the Solar neighborhood with a width of $\sim 4$ kpc. A sub-sample of these stars that was fortuitously observed by LAMOST has a mean spectroscopic metallicity of $\langle {\rm [Fe/H]}\rangle = -1.60^{+0.15}_{-0.16}$ dex and possesses a resolved metallicity dispersion of $σ({\rm [Fe/H]}) = 0.32^{+0.17}_{-0.06}$ dex. The physical width of the stream, the metallicity dispersion and the vertical action spread indicate that the progenitor was a dwarf galaxy. The existence of such a coherent and highly radial structure at their pericenters in the vicinity of the Sun suggests that many other dwarf galaxy fragments may be lurking in the outer halo.

astro-ph.GA↗
arXiv2023

Physical Symbolic Optimization

We present a framework for constraining the automatic sequential generation of equations to obey the rules of dimensional analysis by construction. Combining this approach with reinforcement learning, we built $Φ$-SO, a Physical Symbolic Optimization method for recovering analytical functions from physical data leveraging units constraints. Our symbolic regression algorithm achieves state-of-the-art results in contexts in which variables and constants have known physical units, outperforming all other methods on SRBench's Feynman benchmark in the presence of noise (exceeding 0.1%) and showing resilience even in the presence of significant (10%) levels of noise.

cs.LG↗
arXiv2023

Charting the Galactic acceleration field II. A global mass model of the Milky Way from the STREAMFINDER Atlas of Stellar Streams detected in Gaia DR3

We present an atlas and follow-up spectroscopic observations of 87 thin stream-like structures detected with the STREAMFINDER algorithm in Gaia DR3, of which 29 are new discoveries. Here we focus on using these streams to refine mass models of the Galaxy. Fits with a double power law halo with the outer power law slope set to $-β_h=3$ yield an inner power law slope $-γ_h=0.97^{+0.17}_{-0.21}$, a scale radius of $r_{0, h}=14.7^{+4.7}_{-1.0}$ kpc, a halo density flattening $q_{m, h}=0.75\pm0.03$, and a local dark matter density of $ρ_{h, \odot}=0.0114\pm0.0007 {\rm M_\odot pc^{-3}}$. Freeing $β$ yields $β=2.53^{+0.42}_{-0.16}$, but this value is heavily influenced by our chosen virial mass limit. The stellar disks are found to have a combined mass of $4.20^{+0.44}_{-0.53}\times10^{10} {\rm M_\odot}$, with the thick disk contributing $12.4\pm0.7$\% to the local stellar surface density. The scale length of the thin and thick disks are $2.17^{+0.18}_{-0.08}$ kpc and $1.62^{+0.72}_{-0.13}$ kpc, respectively, while their scale heights are $0.347^{+0.007}_{-0.010}$ kpc and $0.86^{+0.03}_{-0.02}$ kpc, respectively. The virial mass of the favored model is $M_{200}=1.09^{+0.19}_{-0.14}\times 10^{12} {\rm M_\odot}$, while the mass inside of 50 kpc is $M_{R<50}=0.46\pm0.03\times 10^{12} {\rm M_\odot}$. We introduce the Large Magellanic Cloud (LMC) into the derived potential models, and fit the "Orphan" stream therein, finding a mass for the LMC that is consistent with recent estimates. Some highlights of the atlas include the nearby trailing arm of $ω$-Cen, and a nearby very metal-poor stream that was once a satellite of the Sagittarius dwarf galaxy. Finally, we unambiguously detect a hot component around the GD-1 stream, consistent with it having been tidally pre-processed within its own DM subhalo.

astro-ph.GA↗
arXiv2023

SSG2: A new modelling paradigm for semantic segmentation

State-of-the-art models in semantic segmentation primarily operate on single, static images, generating corresponding segmentation masks. This one-shot approach leaves little room for error correction, as the models lack the capability to integrate multiple observations for enhanced accuracy. Inspired by work on semantic change detection, we address this limitation by introducing a methodology that leverages a sequence of observables generated for each static input image. By adding this "temporal" dimension, we exploit strong signal correlations between successive observations in the sequence to reduce error rates. Our framework, dubbed SSG2 (Semantic Segmentation Generation 2), employs a dual-encoder, single-decoder base network augmented with a sequence model. The base model learns to predict the set intersection, union, and difference of labels from dual-input images. Given a fixed target input image and a set of support images, the sequence model builds the predicted mask of the target by synthesizing the partial views from each sequence step and filtering out noise. We evaluate SSG2 across three diverse datasets: UrbanMonitor, featuring orthoimage tiles from Darwin, Australia with five spectral bands and 0.2m spatial resolution; ISPRS Potsdam, which includes true orthophoto images with multiple spectral bands and a 5cm ground sampling distance; and ISIC2018, a medical dataset focused on skin lesion segmentation, particularly melanoma. The SSG2 model demonstrates rapid convergence within the first few tens of epochs and significantly outperforms UNet-like baseline models with the same number of gradient updates. However, the addition of the temporal dimension results in an increased memory footprint. While this could be a limitation, it is offset by the advent of higher-memory GPUs and coding optimizations.

cs.CV↗
arXiv2023

Deep symbolic regression for physics guided by units constraints: toward the automated discovery of physical laws

Symbolic Regression is the study of algorithms that automate the search for analytic expressions that fit data. While recent advances in deep learning have generated renewed interest in such approaches, the development of symbolic regression methods has not been focused on physics, where we have important additional constraints due to the units associated with our data. Here we present $Φ$-SO, a Physical Symbolic Optimization framework for recovering analytical symbolic expressions from physics data using deep reinforcement learning techniques by learning units constraints. Our system is built, from the ground up, to propose solutions where the physical units are consistent by construction. This is useful not only in eliminating physically impossible solutions, but because the "grammatical" rules of dimensional analysis restrict enormously the freedom of the equation generator, thus vastly improving performance. The algorithm can be used to fit noiseless data, which can be useful for instance when attempting to derive an analytical property of a physical model, and it can also be used to obtain analytical approximations to noisy data. We test our machinery on a standard benchmark of equations from the Feynman Lectures on Physics and other physics textbooks, achieving state-of-the-art performance in the presence of noise (exceeding 0.1%) and show that it is robust even in the presence of substantial (10%) noise. We showcase its abilities on a panel of examples from astrophysics.

astro-ph.IM↗
arXiv2023

Reionisation time fields reconstruction from 21 cm signal maps

During the Epoch of reionisation, the intergalactic medium is reionised by the UV radiation from the first generation of stars and galaxies. One tracer of the process is the 21 cm line of hydrogen that will be observed by the Square Kilometre Array (SKA) at low frequencies, thus imaging the distribution of ionised and neutral regions and their evolution. To prepare for these upcoming observations, we investigate a deep learning method to predict from 21 cm maps the reionisation time field (treion(r)), i.e. the time at which each location has been reionised. treion(r) encodes the propagation of ionisation fronts in a single field, gives access to times of local reionisation or to the extent of the radiative reach of early sources. Moreover it gives access to the time evolution of ionisation on the plane of sky, when such evolution is usually probed along the line-of-sight direction. We trained a convolutional neural network (CNN) using simulated 21 cm maps and reionisation times fields produced by the simulation code 21cmFAST . We also investigate the performance of the CNN when adding instrumental effects. Globally, we find that without instrumental effects the 21 cm maps can be used to reconstruct the associated reionisation times field in a satisfying manner: the quality of the reconstruction is dependent on the redshift at which the 21 cm observation is being made and in general it is found that small scale (<10cMpc/h) features are smoothed in the reconstructed field, while larger scale features are well recovered. When instrumental effects are included, the scale dependance of reconstruction is even further pronounced, with significant smoothing on small and intermediate scales.

astro-ph.CO↗
arXiv2023

Impact of the Galactic bar on tidal streams within the Galactic disc: The case of the tidal stream of the Hyades

Tidal streams of disrupted clusters are routinely detected in the halo of the Milky Way. It was recently shown that tidal streams of open clusters can now also be detected within the disc. In this work, we highlight the fact that tidal streams provide a powerful new diagnostic of the non-axisymmetric disc potential and may provide a new constraint on the pattern speed of the Galactic bar. In particular, we show how the stream-orbit misalignment for an open cluster on a quasi-circular orbit in the solar vicinity varies as a function of the position w.r.t the bar resonances. The angular shift rises beyond corotation, reaching values as high as $30^\circ$ close to the outer Lindblad resonance (OLR), then dropping again and reversing its sign beyond the OLR. We applied this mechanism to the recently detected the Hyades stream. We note that the stream would be very similar when taking a potential with no bar or with a fast pattern speed of 55 km.s$^{-1}$ kpc$^{-1}$. However, we find that the stream is different than previously detected when adopting a potential with a bar pattern speed of $39$ km.s$^{-1}$ kpc$^{-1}$. Previously detected Hyades candidate members would, on the other hand, favour a barless or a fast bar galaxy. Interestingly, the previously reported asymmetry in star counts within the leading and trailing tails of the Hyades tidal stream persists in all cases. Our study conclusively demonstrates that the effect of disc non-axisymmetries cannot be neglected when searching for tidal streams of open clusters and that current candidate members of the Hyades stream should not be trusted beyond a distance of 200 pc from the cluster. Moreover, our study allows for ideal targets to be provided for high-resolution spectroscopy follow-ups, which will enable conclusive identifications of the Hyades stream track and provide novel independent constraints on the bar pattern speed in the MW.

astro-ph.GA↗
arXiv2023

Hydrodynamical simulations of galaxy formation with non-Gaussian initial conditions

Collisionless simulations of structure formation with significant local primordial non-Gaussianities at Mpc scales have shown that a non-Gaussian tail favouring underdensities, with a negative $f_{\rm NL}$ parameter, can significantly change the merging history of galaxy-sized dark matter halos, which then typically assemble later than in vanilla $Λ$CDM. Moreover, such a small-scale negative $f_{\rm NL}$ could have interesting consequences for the cosmological $S_8$ tension. Here, we complement our previous work on collisionless simulations with new hydrodynamical simulations of galaxy formation in boxes of 30 Mpc/$h$, using the {\sc RAMSES} code. In particular, we show that all feedback prescriptions being otherwise identical, simulations with a negative $f_{\rm NL} \sim -1000$ on small scales, hence forming galaxies a bit later than in vanilla $Λ$CDM, allow to form simulated galaxies with more disky kinematics than in the vanilla case. Therefore, such small-scale primordial non-Gaussianities could potentially help alleviate, simultaneously, tensions in cosmology and galaxy formation. These hydrodynamical simulations on small scales will need to be complemented with larger box simulations with scale-dependent non-Gaussianities, to statistically confirm these trends and explore their observational consequences in further detail.

astro-ph.CO↗
arXiv2023

Do old globular clusters in low mass galaxies disprove modified gravity?

The controversy "dark matter vs. modified gravity" constitutes a major topic of discussion. It was proposed that dynamical friction could be used to discriminate between the two alternatives. Analytic calculations indicate that, with modified gravity, globular clusters (GCs) of low-mass galaxies experience much stronger dynamical friction than in the equivalent system with Newtonian gravity and dark matter. As a result, in modified gravity the old GCs of low mass galaxies should have already settled in the centers of the galaxies. This is not observed. Here we report on our efforts to verify the analytic results by self-consistent simulations with the MOND-type (modified Newtonian dynamics) gravity. The core stalling mechanism, that was not considered in the analytic calculations, prevents GCs to settle in centers of ultra-diffuse galaxies. For isolated dwarf galaxies, which are gas-rich objects, supernova explosions prevent the GCs from settling.

astro-ph.GA↗
arXiv2023

Disk galaxies are self-similar: the universality of the HI-to-Halo mass ratio for isolated disks

Observed scaling relations in galaxies between baryons and dark matter global properties are key to shed light on the process of galaxy formation and on the nature of dark matter. Here, we study the scaling relation between the neutral hydrogen (HI) and dark matter mass in isolated rotationally-supported disk galaxies at low redshift. We first show that state-of-the-art galaxy formation simulations predict that the HI-to-dark halo mass ratio decreases with stellar mass for the most massive disk galaxies. We then infer dark matter halo masses from high-quality rotation curve data for isolated disk galaxies in the local Universe, and report on the actual universality of the HI-to-dark halo mass ratio for these observed galaxies. This scaling relation holds for disks spanning a range of 4 orders of magnitude in stellar mass and 3 orders of magnitude in surface brightness. Accounting for the diversity of rotation curve shapes in our observational fits decreases the scatter of the HI-to-dark halo mass ratio while keeping it constant. This finding extends the previously reported discrepancy for the stellar-to-halo mass relation of massive disk galaxies within galaxy formation simulations to the realm of neutral atomic gas. Our result reveals that isolated galaxies with regularly rotating extended HI disks are surprisingly self-similar up to high masses, which hints at mass-independent self-regulation mechanisms that have yet to be fully understood.

astro-ph.GA↗
arXiv2023

RomAndromeda: The Roman Survey of the Andromeda Halo

As our nearest large neighbor, the Andromeda Galaxy provides a unique laboratory for investigating galaxy formation and the distribution and substructure properties of dark matter in a Milky Way-like galaxy. Here, we propose an initial 2-epoch ($Δt\approx 5$yr), 2-band Roman survey of the entire halo of Andromeda, covering 500 square degrees, which will detect nearly every red giant star in the halo (10$σ$ detection in F146, F062 of 26.5, 26.1AB mag respectively) and yield proper motions to $\sim$25 microarcsec/year (i.e., $\sim$90 km/s) for all stars brighter than F146 $\approx 23.6$ AB mag (i.e., reaching the red clump stars in the Andromeda halo). This survey will yield (through averaging) high-fidelity proper motions for all satellites and compact substructures in the Andromeda halo and will enable statistical searches for clusters in chemo-dynamical space. Adding a third epoch during the extended mission will improve these proper motions by $\sim t^{-1.5}$, to $\approx 11$ km/s, but this requires obtaining the first epoch in Year 1 of Roman operations. In combination with ongoing and imminent spectroscopic campaigns with ground-based telescopes, this Roman survey has the potential to yield full 3-d space motions of $>$100,000 stars in the Andromeda halo, including (by combining individual measurements) robust space motions of its entire globular cluster and most of its dwarf galaxy satellite populations. It will also identify high-velocity stars in Andromeda, providing unique information on the processes that create this population. These data offer a unique opportunity to study the immigration history, halo formation, and underlying dark matter scaffolding of a galaxy other than our own.

astro-ph.GA↗
arXiv2023

NANCY: Next-generation All-sky Near-infrared Community surveY

The Nancy Grace Roman Space Telescope is capable of delivering an unprecedented all-sky, high-spatial resolution, multi-epoch infrared map to the astronomical community. This opportunity arises in the midst of numerous ground- and space-based surveys that will provide extensive spectroscopy and imaging together covering the entire sky (such as Rubin/LSST, Euclid, UNIONS, SPHEREx, DESI, SDSS-V, GALAH, 4MOST, WEAVE, MOONS, PFS, UVEX, NEO Surveyor, etc.). Roman can uniquely provide uniform high-spatial-resolution (~0.1 arcsec) imaging over the entire sky, vastly expanding the science reach and precision of all of these near-term and future surveys. This imaging will not only enhance other surveys, but also facilitate completely new science. By imaging the full sky over two epochs, Roman can measure the proper motions for stars across the entire Milky Way, probing 100 times fainter than Gaia out to the very edge of the Galaxy. Here, we propose NANCY: a completely public, all-sky survey that will create a high-value legacy dataset benefiting innumerable ongoing and forthcoming studies of the universe. NANCY is a pure expression of Roman's potential: it images the entire sky, at high spatial resolution, in a broad infrared bandpass that collects as many photons as possible. The majority of all ongoing astronomical surveys would benefit from incorporating observations of NANCY into their analyses, whether these surveys focus on nearby stars, the Milky Way, near-field cosmology, or the broader universe.

astro-ph.IM↗
arXiv2023

An end-to-end strategy for recovering a free-form potential from a snapshot of stellar coordinates

New large observational surveys such as Gaia are leading us into an era of data abundance, offering unprecedented opportunities to discover new physical laws through the power of machine learning. Here we present an end-to-end strategy for recovering a free-form analytical potential from a mere snapshot of stellar positions and velocities. First we show how auto-differentiation can be used to capture an agnostic map of the gravitational potential and its underlying dark matter distribution in the form of a neural network. However, in the context of physics, neural networks are both a plague and a blessing as they are extremely flexible for modeling physical systems but largely consist in non-interpretable black boxes. Therefore, in addition, we show how a complementary symbolic regression approach can be used to open up this neural network into a physically meaningful expression. We demonstrate our strategy by recovering the potential of a toy isochrone system.

astro-ph.GA↗