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Lattice reduction is a combinatorial optimization problem aimed at finding the most orthogonal basis in a given lattice. In this work, we address lattice reduction via deep learning methods. We design a deep neural model outputting factorized unimodular matrices and train it in a self-supervised manner by penalizing non-orthogonal lattice bases. We incorporate the symmetries of lattice reduction into the model by making it invariant and equivariant with respect to appropriate continuous and discrete groups., Comment: Symmetry and Geometry in Neural Representations - NeurReps Workshop @ NeurIPS 2023

We have carried out HST snapshot observations at 1.1 $\mu$m of 281 candidate strongly lensed galaxies identified in the wide-area extragalactic surveys conducted with the Herschel space observatory. Our candidates comprise systems with flux densities at $500\,\mu$m$ S_{500}\geq 80$ mJy. We model and subtract the surface brightness distribution for 130 systems, where we identify a candidate for the foreground lens candidate. After combining visual inspection, archival high-resolution observations, and lens subtraction, we divide the systems into different classes according to their lensing likelihood. We confirm 65 systems to be lensed. Of these, 30 are new discoveries. We successfully perform lens modelling and source reconstruction on 23 systems, where the foreground lenses are isolated galaxies and the background sources are detected in the HST images. All the systems are successfully modelled as a singular isothermal ellipsoid. The Einstein radii of the lenses and the magnifications of the background sources are consistent with previous studies. However, the background source circularised radii (between 0.34 kpc and 1.30 kpc) are $\sim$3 times smaller than the ones measured in the sub-mm/mm for a similarly selected and partially overlapping sample. We compare our lenses with those in the SLACS survey, confirming that our lens-independent selection is more effective at picking up fainter and diffuse galaxies and group lenses. This sample represents the first step towards characterising the near-IR properties and stellar masses of the gravitationally lensed dusty star-forming galaxies., Comment: 57 pages, 18 figures, 11 tables. Accepted for publication in MNRAS

Spatiotemporal patterns in multicellular systems are important to understanding tissue dynamics, for instance, during embryonic development and disease. Here, we use a multiphase field model to study numerically the behavior of a near-confluent monolayer of deformable cells with intercellular friction. Varying friction and cell motility drives a solid-liquid transition, and near the transition boundary, we find the emergence of nematic order of cell deformation driven by shear-aligning cellular flows. Intercellular friction endows the monolayer with a finite viscosity, which significantly increases the spatial correlation in the flow and, concomitantly, the extent of nematic order. We also show that hexatic and nematic order are tightly coupled and propose a mechanical-geometric model for the colocalization of +1/2 nematic defects and 5-7 disclination pairs, which are the structural defects in the hexatic phase. Such topological defects coincide with regions of high cell-cell overlap, suggesting that they may mediate cellular extrusion from the monolayer, as found experimentally. Our results delineate a mechanical basis for the recent observation of nematic and hexatic order in multicellular collectives in experiments and simulations and pinpoint a generic pathway to couple topological and physical effects in these systems.

The Milky Way Bulge extra-tidal star survey (MWBest) is a spectroscopic survey with the goal of identifying stripped globular cluster stars from inner Galaxy clusters. In this way, an indication of the fraction of metal-poor bulge stars that originated from globular clusters can be determined. We observed and analyzed stars in and around BH 261, an understudied globular cluster in the bulge. From seven giants within the tidal radius of the cluster, we measured an average heliocentric radial velocity of = -61 +- 2.6 km/s with a radial velocity dispersion of \sigma = 6.1 +- 1.9 km/s. The large velocity dispersion may have arisen from tidal heating in the cluster's orbit about the Galactic center, or because BH 261 has a high dynamical mass as well as a high mass-to-light ratio. From spectra of five giants, we measure an average metallicity of <[Fe/H]> = -1.1 +- 0.2 dex. We also spectroscopically confirm an RR Lyrae star in BH 261, which yields a distance to the cluster of 7.1 +- 0.4~kpc. Stars with 3D velocities and metallicities consistent with BH 261 reaching to ~0.5 degrees from the cluster are identified. A handful of these stars are also consistent with the spatial distribution of that potential debris from models focussing on the most recent disruption of the cluster., Comment: accepted for publication in The Astronomical Journal

The Gaia mission has provided us full astrometric solutions for over 1.5B sources. However, only the brightest 34M of those have radial velocity measurements. As a proof of concept, this paper aims to close that gap, by obtaining radial velocity estimates from the low-resolution BP/RP spectra that Gaia now provides. These spectra are currently published for about 220M sources, with this number increasing to the full $\sim 2$B Gaia sources with Gaia Data Release 4. To obtain the radial velocity measurements, we fit Gaia BP/RP spectra with models based on a grid of synthetic spectra, with which we obtain the posterior probability on the radial velocity for each object. Our measured velocities show systematic biases that depend mainly on colours and magnitudes of stars. We correct for these effects by using external catalogues of radial velocity measurements. We present in this work a catalogue of about 6.4M sources with our most reliable radial velocity measurements and uncertainties $<300$ km s$^{-1}$ obtained from the BP/RP spectra. About 23% of these have no previous radial velocity measurement in Gaia RVS. Furthermore, we provide an extended catalogue containing all 125M sources for which we were able to obtain radial velocity measurements. The latter catalogue, however, also contains a fraction of measurements for which the reported radial velocities and uncertainties are inaccurate. Although typical uncertainties in the catalogue are significantly higher compared to those obtained with precision spectroscopy instruments, the number of potential sources for which this method can be applied is orders of magnitude higher than any previous radial velocity catalogue. Further development of the analysis could therefore prove extremely valuable in our understanding of Galactic dynamics., Comment: 15 pages, 18 figures, accepted in A&A

A major challenge at the interface of quantum gravity and cosmology is to explain the emergence of the large-scale structure of the Universe from Planck scale physics. In this letter, we extract the dynamics of scalar isotropic cosmological perturbations from full quantum gravity, as described by the causally complete Barrett-Crane group field theory model. From the perspective of the underlying quantum gravity theory, cosmological perturbations are represented as nearest-neighbor two-body entanglement of group field theory quanta. Their effective dynamics is obtained via mean-field methods and described relationally with respect to a causally coupled physical Lorentz frame. We quantitatively study these effective dynamical equations and show that at low energies they are perfectly consistent with those of General Relativity, while for trans-Planckian scales quantum effects become important. These results therefore not only provide crucial insights into the potentially purely quantum gravitational nature of cosmological perturbations, but also offer rich phenomenological implications for the physics of the early Universe., Comment: 7+1 pages, 3 figures

The Blanco DECam Bulge Survey (BDBS) provides near-ultraviolet to near-infrared photometry for ~250 million unique stars. By combining BDBS photometry with the latest Gaia astrometry, we characterize the chemo-dynamics of red clump stars across the BDBS footprint, using an unprecedented sample size and sky coverage. We construct a sample of ~2.3 million red clump giants in the bulge with photometric metallicities, BDBS photometric distances, and proper motions. We study the kinematics of the red clump stars as a function of sky position and metallicity, by investigating proper motion rotation curves, velocity dispersions, and proper motion correlations across the southern Galactic bulge. We find that metal-poor red clump stars exhibit lower rotation amplitudes, at ~29 km s$^{-1}$ kpc^{-1}. The peak of the angular velocity is ~39 km s^{-1} kpc^{-1} for [Fe/H] ~ -0.2 dex, exhibiting declining rotation at higher [Fe/H]. The velocity dispersion is higher for metal-poor stars, while metal-rich stars show a steeper gradient with Galactic latitude, with a maximum dispersion at low latitudes along the bulge minor axis. Only metal-rich stars ([Fe/H] >~ -0.5 dex) show clear signatures of the bar in their kinematics, while the metal-poor population exhibits isotropic motions with an axisymmetric pattern around Galactic longitude l = 0. This work reports the largest sample of bulge stars with distance, metallicity, and astrometry and shows clear kinematic differences with metallicity. The global kinematics over the bulge agrees with earlier studies. However, we see striking changes with increasing metallicity and for the first time, see kinematic differences for stars with [Fe/H]>-0.5, suggesting that the bar itself may have kinematics that depends on metallicity., Comment: 12 pages, Accepted for publication in A&A

In this paper we combine the Early Science radio continuum data from the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey, with optical and near-infrared data and release the cross-matched catalogues. The radio data used in this work covers $0.86$ deg$^2$ of the COSMOS field, reaches a thermal noise of $1.7$ $\mu$Jy/beam and contains $6102$ radio components. We visually inspect and cross-match the radio sample with optical and near-infrared data from the Hyper Suprime-Cam (HSC) and UltraVISTA surveys. This allows the properties of active galactic nuclei and star-forming populations of galaxies to be probed out to $z \approx 5$. Additionally, we use the likelihood ratio method to automatically cross-match the radio and optical catalogues and compare this to the visually cross-matched catalogue. We find that 94 per cent of our radio source catalogue can be matched with this method, with a reliability of $95$ per cent. We proceed to show that visual classification will still remain an essential process for the cross-matching of complex and extended radio sources. In the near future, the MIGHTEE survey will be expanded in area to cover a total of $\sim$20~deg$^2$; thus the combination of automated and visual identification will be critical. We compare redshift distribution of SFG and AGN to the SKADS and T-RECS simulations and find more AGN than predicted at $z \sim 1$., Comment: 15 pages, 15 figures. Accepted for publication in MNRAS

We proposed a formally exact, probabilistic method to assess the validity of the Thomas-Fermi potential for three-dimensional condensed matter systems where electron dynamics is constrained to the Fermi surface. Our method, which relies on accurate solutions of the radial Schr\"{o}dinger equation, yields the probability density function for momentum transfer. This allows for the computation of its expectation values, which can be compared with unity to confirm the validity of the Thomas-Fermi approximation. We applied this method to three {\it n}-type direct-gap III-V model semiconductors (GaAs, InAs, InSb) and found that the Thomas-Fermi approximation is certainly valid at high electron densities. In these cases, the probability density function exhibits the same profile, irrespective of the material under scrutiny. Furthermore, we show that this approximation can lead to serious errors in the computation of observables when applied to GaAs at zero temperature for most electron densities under scrutiny., Comment: 9 pages, 4 figures. Revised preprint of the one uploaded on 6 October 2023. Preliminary results were presented at GW goes large-scale (GW-XL) Workshop in Helsinki and at International Workshop on Recent Developments in Electronic Structure (ES21), New York

We address the problem of learning representations from observations of a scene involving an agent and an external object the agent interacts with. To this end, we propose a representation learning framework extracting the location in physical space of both the agent and the object from unstructured observations of arbitrary nature. Our framework relies on the actions performed by the agent as the only source of supervision, while assuming that the object is displaced by the agent via unknown dynamics. We provide a theoretical foundation and formally prove that an ideal learner is guaranteed to infer an isometric representation, disentangling the agent from the object and correctly extracting their locations. We evaluate empirically our framework on a variety of scenarios, showing that it outperforms vision-based approaches such as a state-of-the-art keypoint extractor. We moreover demonstrate how the extracted representations enable the agent to solve downstream tasks via reinforcement learning in an efficient manner.