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We classify four-dimensional connected simply-connected indecomposable Lorentzian symmetric spaces $M$ with connected nontrivial isotropy group furnishing solutions of the Einstein-Yang-Mills equations. Those solutions with respect to some invariant metric connection $\Lambda$ in the bundle of orthonormal frames of $M$ and some diagonal metric on the holonomy algebra corresponding to $\Lambda$.

In this paper, we introduce holiAtlas, a holistic, multimodal and high-resolution human brain atlas. This atlas covers different levels of details of the human brain anatomy, from the organ to the substructure level, using a new dense labelled protocol generated from the fusion of multiple local protocols at different scales. This atlas has been constructed averaging images and segmentations of 75 healthy subjects from the Human Connectome Project database. Specifically, MR images of T1, T2 and WMn (White Matter nulled) contrasts at 0.125 $mm^{3}$ resolution that were nonlinearly registered and averaged using symmetric group-wise normalisation to construct the atlas. At the finest level, the holiAtlas protocol has 350 different labels derived from 10 different delineation protocols. These labels were grouped at different scales to provide a holistic view of the brain at different levels in a coherent and consistent manner. This multiscale and multimodal atlas can be used for the development of new ultra-high resolution segmentation methods that can potentially leverage the early detection of neurological disorders., Comment: 22 pages

This work explores the combination of liquid xenon as a scintillating medium and silicon photomultipliers as a readout in Positron Emission Tomography (PET) for enhanced Time-Of-Flight resolution. We present the results of our first prototype optimized to maximize light collection using high-PDE, VUV-sensitive sensors and to minimize time fluctuations. We report a coincidence time resolution of 281 $\pm$ 2 ps FWHM, obtained using a $^{22}$Na calibration source. This result is competitive with the current state-of-the-art PET scanners and represents a significant step forward in the development of liquid xenon as a viable alternative to conventional scintillators in PET technology.

We present the first analysis of Dark Matter axion detection applying neural networks for the improvement of sensitivity. The main sources of thermal noise from a typical read-out chain are simulated, constituted by resonant and amplifier noises. With this purpose, an advanced modal method employed in electromagnetic modal analysis for the design of complex microwave circuits is applied. A feedforward neural network is used for a boolean decision (there is axion or only noise), and robust results are obtained: the neural network can improve by a factor of $5\cdot 10^{3}$ the integration time needed to reach a given signal to noise ratio. This could either significantly reduce measurement times or achieve better sensitivities with the same exposure durations., Comment: 6 pages, 6 figures, 1 table

The outskirts of the Milky Way disc have been known to be warped since the late 1950s. Although various stellar populations have shown an underlying warped distribution, the relation between the age of the population and the warp they trace remains an open question. Our goal in this work is to detect the presence of the warp in the RR Lyrae (RRL) population of the Galactic disc. We use a compilation of public catalogues of RRL stars, precise photometric distances ($\sim 5\%$) and Gaia DR3 proper motions to kinematically select a sample of thin disc RRL in the Galactic anticentre, where the tangential velocity best approximates the azimuthal velocity to differentiate between disc and halo. For disc-like RRL we analyse their mean vertical height and mean vertical velocity. We show, for the first time, that RRL stars with thin disc-like kinematics trace the warp. In the anticentre direction, the RRL population reaches a minimum in mean vertical height of $\approx 0.4$ kpc, with a trend systematically lower than the one found with Classical Cepheids. The kinematical signal of the RRL warp starts at $R\approx 10$ kpc and, rather than resembling the Cepheid's, shows a similar trend to the Red Clump population from previous works, reaching a maximum value of $\approx 7$ km/s in vertical velocity. We also obtain an estimation of the pattern speed of the RRL warp with a prograde rotation of $\approx 13 \pm 2 $ km/s/kpc, compatible with results obtained from Cepheids. Finally, we obtain a vertical velocity dispersion $\approx 17 $km/s, inconsistent with the kinematics of a canonical old age ($> 10$ Gyr) disc population and, instead, favouring a population dominated by intermediate-age ($3-4$ Gyr). Our results indicate that the thin disc RRL stars are a dynamical intermediate-age tracer of the warp, opening a new window to study the dependency of the warp with stellar age., Comment: 6 pages, 5 figures. 2 pages with 2 figures in the appendices. Submitted to A&A

The Zirconium (Z = 40) isotopic chain has attracted interest for more than four decades. The abrupt lowering of the energy of the first $2^+$ state and the increase in the transition strength B(E2; $2_1^\rightarrow 0_1^+$ going from $^{98}$Zr to $^{100}$Zr has been the first example of "quantum phase transition" in nuclear shapes, which has few equivalents in the nuclear chart. Although a multitude of experiments have been performed to measure nuclear properties related to nuclear shapes and collectivity in the region, none of the measured lifetimes were obtained using the Recoil Distance Doppler Shift method in the $\gamma\gamma$-coincidence mode where a gate on the direct feeding transition of the state of interest allows a strict control of systematical errors. This work reports the results of lifetime measurements for the first yrast excited states in $^{98-104}$Zr carried out to extract reduced transition probabilities. The new lifetime values in $\gamma\gamma$-coincidence and $\gamma$-single mode are compared with the results of former experiments. Recent predictions of the Interacting Boson Model with Configuration Mixing, the Symmetry Conserving Configuration Mixing model based on the Hartree-Fock-Bogoliubov approach and the Monte Carlo Shell Model are presented and compared with the experimental data.

We present the first measurement of the $^{47}$K($d,p\gamma$)$^{48}$K transfer reaction, performed in inverse kinematics using a reaccelerated beam of $^{47}$K. The level scheme of $^{48}$K has been greatly extended with nine new bound excited states identified and spectroscopic factors deduced. Detailed comparisons with SDPF-U and SDPF-MU shell-model calculations reveal a number of discrepancies with these results, and a preference for SDPF-MU is found. Intriguingly, an apparent systematic overestimation of spectroscopic factors and a poor reproduction of the energies for 1$^-$ states suggests that the mixing between the $\pi s^{\,\,\,1}_{1/2} d^{\,\,\,4}_{3/2}$ and $\pi s^{\,\,\,2}_{1/2} d^{\,\,\,3}_{3/2}$ proton configurations in $^{48}$K is not correctly described using current interactions, challenging our descriptions of light $N=28$ nuclei., Comment: 7 pages, 3 figures, 1 table

Diffusion regulates numerous natural processes and the dynamics of many successful generative models. Existing models to learn the diffusion terms from observational data rely on complex bilevel optimization problems and model only the drift of the system. We propose a new simple model, JKOnet*, which bypasses the complexity of existing architectures while presenting significantly enhanced representational capabilities: JKOnet* recovers the potential, interaction, and internal energy components of the underlying diffusion process. JKOnet* minimizes a simple quadratic loss and outperforms other baselines in terms of sample efficiency, computational complexity, and accuracy. Additionally, JKOnet* provides a closed-form optimal solution for linearly parametrized functionals, and, when applied to predict the evolution of cellular processes from real-world data, it achieves state-of-the-art accuracy at a fraction of the computational cost of all existing methods. Our methodology is based on the interpretation of diffusion processes as energy-minimizing trajectories in the probability space via the so-called JKO scheme, which we study via its first-order optimality conditions., Comment: Accepted for presentation at, and publication in the proceedings of, the 38th Conference on Neural Information Processing Systems (NeurIPS 2024, oral)

The first systematic experimental study of the neutron-rich Br isotopes with two complementary state-of-the-art techniques is presented. These isotopes have been populated in the fission process at two different facilities, GANIL and ILL. New spectroscopic information has been obtained for odd-even $^{87-93}$Br isotopes and the experimental results have been compared with state-of-the-art Large-Scale Shell-Model and DNO Shell-Model calculations. As a result of such theoretical approaches, a transition from prolate ($^{87,89}$Br) to oblate ($^{91,93}$Br) shapes is obtained from the subtle balance between proton and neutron quadrupole deformations, as a clear signature of pseudo-SU3 quadrupole regime., Comment: 17 pages, 24 figures, 5 tables

The excited states of unstable $^{20}$O were investigated via $\gamma$-ray spectroscopy following the $^{19}$O$(d,p)^{20}$O reaction at 8 $A$MeV. By exploiting the Doppler Shift Attenuation Method, the lifetime of the 2$^+_2$ and 3$^+_1$ states were firmly established. From the $\gamma$-ray branching and E2/M1 mixing ratios for transitions deexciting the 2$^+_2$ and 3$^+_1$ states, the B(E2) and B(M1) were determined. Various chiral effective field theory Hamiltonians, describing the nuclear properties beyond ground states, along with a standard USDB interaction, were compared with the experimentally obtained data. Such a comparison for a large set of $\gamma$-ray transition probabilities with the valence space in medium similarity renormalization group ab-initio calculations was performed for the first time in a nucleus far from stability. It was shown that the ab-initio approaches using chiral EFT forces are challenged by detailed high-precision spectroscopic properties of nuclei. The reduced transition probabilities were found to be a very constraining test of the performance of the ab-initio models., Comment: Supplemental Material available

A great deal of interest is directed nowadays towards the development of innovative technologies in the field of quantum information and quantum computing, with emphasis on obtaining reliable qubits as building blocks. The realization of highly stable, controllable and accessible hole spin qubits is strongly dependent on the quality of the materials hosting them. Ultra-clean germanium/silicon-germanium heterostructures have been predicted and proven to be promising candidates and due to their large scalability potential, they are opening the door towards the development of realistic and reliable solid state, all-electric, silicon-based quantum computers. In order to obtain ultra-clean germanium/silicon-germanium heterostructures in a reverse grading approach, the understanding and control over the growth of Ge virtual substrates and thin films is key. Here, we present a detailed study on the growth kinetics, morphology, and crystal quality of Ge thin films grown via chemical vapor deposition by investigating the effects of growth temperature, partial pressure of the precursor gas and the use of Ar or H2 atmosphere. The presence of carrier gases catalyzes the deposition rate and induces a smoothening on the surfaces of films grown at low temperatures. We investigated the surface roughness and threading dislocation density as a function of deposition temperature, partial pressure and gas mixture. Ge thin films deposited by diluting GeH4 in Ar or H2 were employed as virtual substrates for the growth of full Ge/SiGe QW heterostructures. Their defect density was analyzed and their electric transport properties were characterized via Hall measurements. Similar results were obtained for both carrier gases used.

Information Extraction processes in handwritten documents tend to rely on obtaining an automatic transcription and performing Named Entity Recognition (NER) over such transcription. For this reason, in publicly available datasets, the performance of the systems is usually evaluated with metrics particular to each dataset. Moreover, most of the metrics employed are sensitive to reading order errors. Therefore, they do not reflect the expected final application of the system and introduce biases in more complex documents. In this paper, we propose and publicly release a set of reading order independent metrics tailored to Information Extraction evaluation in handwritten documents. In our experimentation, we perform an in-depth analysis of the behavior of the metrics to recommend what we consider to be the minimal set of metrics to evaluate a task correctly.

This paper explores the enhancement of solution diversity in evolutionary algorithms (EAs) for the maximum matching problem, concentrating on complete bipartite graphs and paths. We adopt binary string encoding for matchings and use Hamming distance to measure diversity, aiming for its maximization. Our study centers on the $(\mu+1)$-EA and $2P-EA_D$, which are applied to optimize diversity. We provide a rigorous theoretical and empirical analysis of these algorithms. For complete bipartite graphs, our runtime analysis shows that, with a reasonably small $\mu$, the $(\mu+1)$-EA achieves maximal diversity with an expected runtime of $O(\mu^2 m^4 \log(m))$ for the small gap case (where the population size $\mu$ is less than the difference in the sizes of the bipartite partitions) and $O(\mu^2 m^2 \log(m))$ otherwise. For paths, we establish an upper runtime bound of $O(\mu^3 m^3)$. The $2P-EA_D$ displays stronger performance, with bounds of $O(\mu^2 m^2 \log(m))$ for the small gap case, $O(\mu^2 n^2 \log(n))$ otherwise, and $O(\mu^3 m^2)$ for paths. Here, $n$ represents the total number of vertices and $m$ the number of edges. Our empirical studies, which examine the scaling behavior with respect to $m$ and $\mu$, complement these theoretical insights and suggest potential for further refinement of the runtime bounds.

The warp is a well-known undulation of the Milky Way disc. Its structure has been widely studied, but only since Gaia DR2 has it been possible to reveal its kinematic signature beyond the solar neighbourhood. In this work we present an analysis of the warp traced by Classical Cepheids by means of a Fourier decomposition of their height ($Z$) and, for the first time, of their vertical velocity ($V_z$). We find a clear but complex signal that in both variables reveals an asymmetrical warp. In $Z$ we find the warp to be almost symmetric in amplitude at the disc's outskirts, with the two extremes never being diametrically opposed at any radius and the line of nodes presenting a twist in the direction of stellar rotation for $R>11$ kpc. For $V_z$, in addition to the usual $m=1$ mode, an $m=2$ mode is needed to represent the kinematic signal of the warp, reflecting its azimuthal asymmetry. The line of maximum vertical velocity is similarly twisted as the line of nodes and trails behind by $\approx 25^\circ$. We develop a new formalism to derive the pattern speed and change in amplitude with time $\dot{A}$ of each Fourier mode at each radius, via a joint analysis of the Fourier decomposition in $Z$ and $V_z$. By applying it to the Cepheids we find, for the $m=1$ mode, a constant pattern speed in the direction of stellar rotation of $9.2\pm3.1$ km/s/kpc, a negligible $\dot{A}$ up to $R\approx 14$ kpc and a slight increase at larger radii, in agreement with previous works., Comment: Accepted for publication in MNRAS. 15 pages, 10 figures, 4 tables (+ Appendices). Full version of tables 1 and 2 included

This paper introduces a novel multimodal and high-resolution human brain cerebellum lobule segmentation method. Unlike current tools that operate at standard resolution ($1 \text{ mm}^{3}$) or using mono-modal data, the proposed method improves cerebellum lobule segmentation through the use of a multimodal and ultra-high resolution ($0.125 \text{ mm}^{3}$) training dataset. To develop the method, first, a database of semi-automatically labelled cerebellum lobules was created to train the proposed method with ultra-high resolution T1 and T2 MR images. Then, an ensemble of deep networks has been designed and developed, allowing the proposed method to excel in the complex cerebellum lobule segmentation task, improving precision while being memory efficient. Notably, our approach deviates from the traditional U-Net model by exploring alternative architectures. We have also integrated deep learning with classical machine learning methods incorporating a priori knowledge from multi-atlas segmentation, which improved precision and robustness. Finally, a new online pipeline, named DeepCERES, has been developed to make available the proposed method to the scientific community requiring as input only a single T1 MR image at standard resolution., Comment: 20 pages

Determining whether Global Average Temperature (GAT) is an integrated process of order 1, I(1), or is a stationary process around a trend function is crucial for detection, attribution, impact and forecasting studies of climate change. In this paper, we investigate the nature of trends in GAT building on the analysis of individual temperature grids. Our 'micro-founded' evidence suggests that GAT is stationary around a non-linear deterministic trend in the form of a linear function with a one-period structural break. This break can be attributed to a combination of individual grid breaks and the standard aggregation method under acceleration in global warming. We illustrate our findings using simulations.

While most theoretical run time analyses of discrete randomized search heuristics focused on finite search spaces, we consider the search space $\mathbb{Z}^n$. This is a further generalization of the search space of multi-valued decision variables $\{0,\ldots,r-1\}^n$. We consider as fitness functions the distance to the (unique) non-zero optimum $a$ (based on the $L_1$-metric) and the \ooea which mutates by applying a step-operator on each component that is determined to be varied. For changing by $\pm 1$, we show that the expected optimization time is $\Theta(n \cdot (|a|_{\infty} + \log(|a|_H)))$. In particular, the time is linear in the maximum value of the optimum $a$. Employing a different step operator which chooses a step size from a distribution so heavy-tailed that the expectation is infinite, we get an optimization time of $O(n \cdot \log^2 (|a|_1) \cdot \left(\log (\log (|a|_1))\right)^{1 + \epsilon})$. Furthermore, we show that RLS with step size adaptation achieves an optimization time of $\Theta(n \cdot \log(|a|_1))$. We conclude with an empirical analysis, comparing the above algorithms also with a variant of CMA-ES for discrete search spaces.

The strategic selection of resources by selfish agents is a classic research direction, with Resource Selection Games and Congestion Games as prominent examples. In these games, agents select available resources and their utility then depends on the number of agents using the same resources. This implies that there is no distinction between the agents, i.e., they are anonymous. We depart from this very general setting by proposing Resource Selection Games with heterogeneous agents that strive for joint resource usage with similar agents. So, instead of the number of other users of a given resource, our model considers agents with different types and the decisive feature is the fraction of same-type agents among the users. More precisely, similarly to Schelling Games, there is a tolerance threshold $\tau \in [0,1]$ which specifies the agents' desired minimum fraction of same-type agents on a resource. Agents strive to select resources where at least a $\tau$-fraction of those resources' users have the same type as themselves. For $\tau=1$, our model generalizes Hedonic Diversity Games with a peak at $1$. For our general model, we consider the existence and quality of equilibria and the complexity of maximizing social welfare. Additionally, we consider a bounded rationality model, where agents can only estimate the utility of a resource, since they only know the fraction of same-type agents on a given resource, but not the exact numbers. Thus, they cannot know the impact a strategy change would have on a target resource. Interestingly, we show that this type of bounded rationality yields favorable game-theoretic properties and specific equilibria closely approximate equilibria of the full knowledge setting., Comment: full version of the article at the 32nd International Joint Conference on Artificial Intelligence (IJCAI-2023)

The release of Microsoft's HoloLens headset addresses new types of issues that would have been difficult to design without such a hardware. This semi-transparent visor headset allows the user who wears it to view the projection of 3D virtual objects placed in its real environment. The user can also interact with these 3D objects, which can interact with each other. The framework of this new technology is called mixed reality. We had the opportunity to numerically transform a conventional human nutrition workshop for patients waiting for bariatric surgery by developing a software called HOLO_NUTRI using the HoloLens headset. Unlike our experience of user and conventional programmer specialized in the development of interactive 3D graphics applications, we realized that such a mixed reality experience required specific programming concepts quite different from those of conventional software or those of virtual reality applications, but above all required a thorough reflection about communication for users. In this article, we propose to explain our design of communication (graphic supports, tutorials of use of material, explanatory videos), a step which was crucial for the good progress of our project. The software was used by thirty patients from Le Puy-en-Velay Hospital during 10 sessions of one hour and a half during which patients had to take in hand the headset and software HOLO_NUTRI. We also proposed a series of questions to patients to have an assessment of both the adequacy and the importance of this communication approach for such experience. As the mixed reality technology is very recent but the number of applications based on it significantly increases, the reflection on the implementation of the elements of communication described in this article (videos, exercise of learning for the use of the headset, communication leaflet, etc.) can help developers of such applications., Comment: 19 pages, 14 figures

In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning. Using techniques of Symbolic Computation and Computer Algebra, we apply the concept of persistent homology to obtain a new semi-supervised learning method., Comment: In Proceedings of XVII Encuentro \'algebra computacional y aplicaciones (EACA 2022). arXiv admin note: text overlap with arXiv:2205.09617

Climate change is a non-uniform phenomenon. This paper proposes a new quantitative methodology to characterize, measure, and test the existence of climate change heterogeneity. It consists of three steps. First, we introduce a new testable warming typology based on the evolution of the trend of the whole temperature distribution and not only on the average. Second, we define the concepts of warming acceleration and warming amplification in a testable format. And third, we introduce the new testable concept of warming dominance to determine whether region A is suffering a worse warming process than region B. Applying this three-step methodology, we find that Spain and the Globe experience a clear distributional warming process (beyond the standard average) but of different types. In both cases, this process is accelerating over time and asymmetrically amplified. Overall, warming in Spain dominates the Globe in all the quantiles except the lower tail of the global temperature distribution that corresponds to the Arctic region. Our climate change heterogeneity results open the door to the need for a non-uniform causal-effect climate analysis that goes beyond the standard causality in mean as well as for a more efficient design of the mitigation-adaptation policies. In particular, the heterogeneity we find suggests that these policies should contain a common global component and a clear local-regional element. Future climate agreements should take the whole temperature distribution into account., Comment: 36 pages, 7 figures, 10 tables, and 6 pages appendix

We report on a new measurement of the energy resolution that can be attained in liquid xenon when recording only the scintillation light. Our setup is optimised to maximise light collection, and uses state-of-the-art, high-PDE, VUV-sensitive silicon photomultipliers. We find a value of 4.2% +- 0.2% FWHM at 511 keV, a result much better than previous measurements and close to the Poissonian resolution that we expect in our setup (5.4% +- 0.8% FWHM at 511 keV). Our results are compatible with a null value of the intrinsic energy resolution in liquid xenon, with an upper bound of 0.4% FWHM at 95% CL at 511 keV, to be compared with 3--4% FWHM in the same region found by theoretical estimations which have been standing for the last twenty years. Our work opens new possibilities for apparatus based on liquid xenon and using scintillation only. In particular it suggests that modular scintillation detectors using liquid xenon can be very competitive as building blocks in segmented calorimeters, with applications to nuclear and particle physics as well as Positron Emission Tomography technology.