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We discuss the application of the Color Glass Condensate (CGC), an effective field theory of Quantum Chromodynamics (QCD), to describe high-energy nuclear interactions. We first provide an introduction to the methods and language of the CGC, its role in understanding gluon saturation in heavy-ion collisions at the LHC and RHIC, and its relevance in various scattering processes such as Deep Inelastic Scattering (DIS). The application of the CGC effective field theory to describe hadron-hadron collisions is discussed in the scope of asymmetric \textit{dilute-dense} collisions, and Heavy-Ion Collisions in the \textit{dense-dense} limit. The review covers theoretical foundations, recent advancements, and phenomenological applications, focusing on using the CGC to determine the initial conditions of heavy-ion collisions., Comment: 40 pages, 8 figures

This paper aims to provide physics teachers with tools to help deepen the understanding of the laws of electromagnetism. The fundamental contributions of our proposal are: a) to use quotes from mythical characters in the history of science as a motivating educational resource; b) to promote the discussion of striking and fundamental topics; c) to mention diverse approaches and stimulate the search for correct answers to provocative questions. Citations from Einstein refer to principal contributions made by Newton, Maxwell and himself. Emphasis is placed on the cognitive value of differential (local, infinitesimal) analysis of fundamental concepts (field structure, causality, field relativistic transformations). The unity of electromagnetism is analyzed from the point of view of special relativity. It is clarified that descriptions suggesting that the magnetic field is dispensable are contrary to the Einstenian approach: they assume that, to describe the interaction between moving charges, there is a preferred coordinate system for each particular problem. An introductory presentation of the tensor form of Maxwell equations is provided., Comment: Accepted for publication in Revista Mexicana de Fisica E

Submillimeter galaxies (SMGs) constitute a key population of bright star-forming galaxies at high redshift. These galaxies challenge galaxy formation models, particularly in reproducing their observed number counts and redshift distributions. Furthermore, although SMGs contribute significantly to the cosmic star formation rate density (SFRD), their precise role remains uncertain. Upcoming surveys, such as the Ultra Deep Survey with the TolTEC camera, are expected to offer valuable insights into SMG properties and their broader impact. Robust modeling of SMGs in a cosmologically representative volume is necessary to investigate their nature in preparation for next-generation submillimeter surveys. We implement and test parametric relations derived from radiative transfer calculations across three cosmological simulations: EAGLE, IllustrisTNG, and FLAMINGO. Particular emphasis is placed on the FLAMINGO due to their large volume and robust statistical sampling of SMGs. Based on the model that best reproduces observations, we forecast submillimeter fluxes within the simulations, analyze the properties of SMGs, and evaluate their evolution over cosmic time. Our results show that the FLAMINGO reproduces the observed redshift distribution and source number counts of SMGs without requiring a top-heavy initial mass function. On the other hand, the EAGLE and IllustrisTNG show a deficit of bright SMGs. We find that SMGs with S850 > 1 mJy contribute up to 27% of the SFRD at z=2.6 in the FLAMINGO, consistent with recent observations. Flux density functions reveal a rise in SMG abundance from z = 6 to 2.5, followed by a sharp decline in the number of brighter SMGs from z = 2.5 to 0. Leveraging the SMG population in FLAMINGO, we forecast that the TolTEC UDS will detect 80,000 sources over 0.8 deg^2 at 1.1 mm (at the 4{\sigma} detection limit), capturing about 50% of the cosmic SFRD at z=2.5., Comment: 19 pages, 13 figures, submitted to Astronomy & Astrophysics Journal, abstract is reduced to meet Arxiv character limit

In this work, we have investigated the sensitivity of the effectiveness (TCP) of molecular radiotherapy (MRT) treatment to uncertainties of the dose rate curves that may appear when reconstructing those curves. We generated different dose rate curves from experimental data, imposing the constraint of equal dose for each of them. Then, we computed TCPs and looked for correlations between metrics measuring the differences between the dose rate curves and differences in TCP. Finally, according to these results, we estimated the range of tolerable uncertainties in the dose rate curves. The study was performed for different radiopharmaceuticals and different radiosensitive parameters that can affect the dose rate response ($\alpha/\beta$, sub-lethal repair rate). The best correlation between differences in the dose rate curves and TCP was found for a metric that computes averaged linear differences between the curves. With this metric, we quantified differences in dose rate curves that would lead to differences in TCP of 0.02, a parameter denoted $m_{1,\: 0.02}$ that is a surrogate of the dependence of the TCP on the dose rate profile. The results showed that the sensitivity of the TCP to dose rate variations decreases (i.e. larger values of $m_{1,\: 0.02}$) with increasing $\alpha/\beta$ and sub-lethal damage repair rate of the tumor cells, and increasing biological half-life of the dose rate curves. The radiobiological effect of a MRT treatment on a tumor depends on the absorbed dose and the dose rate profile. Ideally, both magnitudes should be measured with accuracy in order to progress towards the optimization of individualized MRT treatments. Our study suggests that this would be more important for tumors with low $\alpha/\beta$ and moderately slow sub-lethal damage repair treated with fast-decaying radiopharmaceuticals.

Sub-nuclear fluctuations in the initial state of heavy-ion collisions impact not only transverse long-range correlations of small systems, but also the creation of longitudinal structures, seen in particle detectors as longitudinal decorrelation observables. In this work, we study the emergence of long-range rapidity correlations in nuclear collisions based on the 3D resolved McDIPPER initial state model, and for the first time, connect it to experimental observables using the 3+1D viscous hydrodynamics framework CLVisc. We include different sources of fluctuations at the nucleon and subnucleon level and study the effects of these additional fluctuation sources on the longitudinal structure of relevant observables, such as the flow decorrelations and directed flow.

In recent years, it has been shown empirically that standard disentangled latent variable models do not support robust compositional learning in the visual domain. Indeed, in spite of being designed with the goal of factorising datasets into their constituent factors of variations, disentangled models show extremely limited compositional generalisation capabilities. On the other hand, object-centric architectures have shown promising compositional skills, albeit these have 1) not been extensively tested and 2) experiments have been limited to scene composition -- where models must generalise to novel combinations of objects in a visual scene instead of novel combinations of object properties. In this work, we show that these compositional generalisation skills extend to this later setting. Furthermore, we present evidence pointing to the source of these skills and how they can be improved through careful training. Finally, we point to one important limitation that still exists which suggests new directions of research., Comment: As it appeared in the Compositional Learning Workshop, NeurIPS 2024; 14 pages (5 main text, 7 appendices, 2 references); 9 figures

We calculate the effects of doping nanostructuration and the patterning of thin films of high-temperature superconductors (HTS) with the aim of optimizing their functionality as sensing materials for resistive transition-edge bolometer devices (TES). We focus, in particular, on spatial variations of the carrier doping into the CuO$_2$ layers due to oxygen off-stoichiometry, (that induce, in turn, critical temperature variations) and explore following two major cases of such structurations: First, the random nanoscale disorder intrinsically associated to doping levels that do not maximize the superconducting critical temperature; our studies suggest that this first simple structuration already improves some of the bolometric operational parameters with respect to the conventional, nonstructured HTS materials used until now. Secondly, we consider the imposition of regular arrangements of zones with different nominal doping levels (patterning); we find that such regular patterns may improve the bolometer performance even further. We find one design that improves, with respect to nonstructured HTS materials, both the saturation power and the operating temperature width by more than one order of magnitude. It also almost doubles the response of the sensor to radiation., Comment: 37 pages, 5 figures, 1 table

Observational and/or astrophysical systematics modulating the observed number of luminous tracers can constitute a major limitation in the cosmological exploitation of surveys of the large scale structure of the universe. Part of this limitation arises on top of our ignorance on how such systematics actually impact the observed galaxy/quasar fields. In this work we develop a generic, hybrid model for an arbitrary number of systematics that may modulate observations in both an additive and a multiplicative way. This model allows us devising a novel algorithm that addresses the identification and correction for either additive and/or multiplicative contaminants. We test this model on galaxy mocks and systematics templates inspired from data of the third data release of the {\it Javalambre Photometric Local Universe Survey} (J-PLUS). We find that our method clearly outperforms standard methods that assume either an additive or multiplicative character for all contaminants in scenarios where both characters are actually acting on the observed data. In simpler scenarios where only an additive or multiplicative imprint on observations is considered, our hybrid method does not lie far behind the corresponding simplified, additive/multiplicative methods. Nonetheless, in scenarios of mild/low impact of systematics, we find that our hybrid approach converges towards the standard method that assumes additive contamination, as predicted by our model describing systematics. Our methodology also allows for the estimation of biases induced by systematics residuals on different angular scales and under different observational configurations, although these predictions necessarily restrict to the subset of {\em known/identified} potential systematics, and say nothing about ``unknown unknowns" possibly impacting the data., Comment: 17 pages, 9 figures, to be submitted to the Open Journal for Astrophysics. Comments welcome!

The {\it Javalambre Photometric Local Universe Survey} (J-PLUS) is a {\it spectro-photometric} survey covering about 3,000~deg$^2$ in its third data release (DR3), and containing about 300,000 galaxies with high quality ({\it odds}$>0.8$) photometric redshifts (hereafter photo-$z$s). We use this galaxy sample to conduct a tomographic study of the counts and redshift angular fluctuations under Gaussian shells sampling the redshift range $z\in[0.05,0.25]$. We confront the angular power spectra of these observables measured under shells centered on 11 different redshifts with theoretical expectations derived from a linear Boltzmann code ({\tt ARFCAMB}). Overall we find that J-PLUS DR3 data are well reproduced by our linear, simplistic model. We obtain that counts (or density) angular fluctuations (hereafter ADF) are very sensitive to the linear galaxy bias $b_g(z)$, although weakly sensitive to radial peculiar velocities of the galaxy field, while suffering from systematics residuals for $z>0.15$. Angular redshift fluctuations (ARF), instead, show higher sensitivity to radial peculiar velocities and also higher sensitivity to the average uncertainty in photo-$z$s ($\sigma_{\rm Err}$), with no obvious impact from systematics. For $z<0.15$ both ADF and ARF agree on measuring a monotonically increasing linear bias varying from $b_g(z=0.05)\simeq 0.9\pm 0.06$ up to $b_g(z=0.15)\simeq 1.5\pm 0.05$, while, by first time, providing consistent measurements of $\sigma_{\rm Err}(z)\sim 0.014$ that are $\sim 40~\%$ higher than estimates from the photo-$z$ code {\tt LePhare}, ($\sigma_{\rm Err}^{\rm LePhare}=0.010$). As expected, this photo-$z$ uncertainty level prevents the detection of radial peculiar velocities in the modest volume sampled by J-PLUS DR3, although prospects for larger galaxy surveys of similar (and higher) photo-$z$ precision are promising., Comment: About 20 pages and 14 figures, to be submitted to the Open Journal for Astrophysics. Comments welcome!

In the field of acoustic scene analysis, this paper presents a novel approach to find spatio-temporal latent representations from in-the-wild audio data. By using WE-LIVE, an in-house collected dataset that includes audio recordings in diverse real-world environments together with sparse GPS coordinates, self-annotated emotional and situational labels, we tackle the challenging task of associating each audio segment with its corresponding location as a pretext task, with the final aim of acoustically detecting violent (anomalous) contexts, left as further work. By generating acoustic embeddings and using the self-supervised learning paradigm, we aim to use the model-generated latent space to acoustically characterize the spatio-temporal context. We use YAMNet, an acoustic events classifier trained in AudioSet to temporally locate and identify acoustic events in WE-LIVE. In order to transform the discrete acoustic events into embeddings, we compare the information-retrieval-based TF-IDF algorithm and Node2Vec as an analogy to Natural Language Processing techniques. A VAE is then trained to provide a further adapted latent space. The analysis was carried out by measuring the cosine distance and visualizing data distribution via t-Distributed Stochastic Neighbor Embedding, revealing distinct acoustic scenes. Specifically, we discern variations between indoor and subway environments. Notably, these distinctions emerge within the latent space of the VAE, a stark contrast to the random distribution of data points before encoding. In summary, our research contributes a pioneering approach for extracting spatio-temporal latent representations from in-the-wild audio data., Comment: 9 pages, 6 figures

Investigating the assembly history of the most massive and passive galaxies will enhance our understanding of why galaxies exhibit such a remarkable diversity in structure and morphology. In this paper, we simultaneously investigate the assembly history and redshift evolution of semi-analytically modelled galaxy properties of central galaxies between 0.56 < z < 4.15, alongside their connection to their halos as a function of large-scale environment. We extract sub-samples of galaxies from a mock catalogue representative for the BOSS-CMASS sample, which includes the most massive and passively evolving system known today. Utilising typical galaxy properties such as star formation rate, (g-i) colour, or cold gas-phase metallicity (Zcold), we track the redshift evolution of these properties across the main progenitor trees. We present results on galaxy and halo properties, including their growth and clustering functions. Our findings indicate that galaxies in the highest stellar and halo mass regimes are least metal-enriched (using Zcold as a proxy) and consistently exhibit significantly larger black hole masses and higher clustering amplitudes compared to sub-samples selected by e.g. colour or star formation rate. This population forms later and also retains large reservoirs of cold gas. In contrast, galaxies in the intermediate and lower stellar/halo mass regimes consume their cold gas at higher redshift and were among the earliest and quickest to assemble. We observe a clear trend where the clustering of the galaxies selected according to their Zcold-values (either low-Zcold or high-Zcold) depends on the density of their location within the large-scale environment. We assume that in particular galaxies in the low/high-Zcold sub-samples form and evolve through distinct evolutionary channels, which are predetermined by their location within the large-scale environment of the cosmic web., Comment: 21 pages, 12 figures, accepted for publication in A&A

Phase-type distributions (PHDs), which are defined as the distribution of the lifetime up to the absorption in an absorbent Markov chain, are an appropriate candidate to model the lifetime of any system, since any non-negative probability distribution can be approximated by a PHD with sufficient precision. Despite PHD potential, friendly statistical programs do not have a module implemented in their interfaces to handle PHD. Thus, researchers must consider others statistical software such as R, Matlab or Python that work with the compilation of code chunks and functions. This fact might be an important handicap for those researchers who do not have sufficient knowledge in programming environments. In this paper, a new interactive web application developed with shiny is introduced in order to adjust PHD to an experimental dataset. This open access app does not require any kind of knowledge about programming or major mathematical concepts. Users can easily compare the graphic fit of several PHDs while estimating their parameters and assess the goodness of fit with just several clicks. All these functionalities are exhibited by means of a numerical simulation and modeling the time to live since the diagnostic in primary breast cancer patients.

This paper explores how competing interactions in the intermolecular potential of fluids affect their structural transitions. This study employs a versatile potential model with a hard core followed by two constant steps, representing wells or shoulders, analyzed in both one-dimensional (1D) and three-dimensional (3D) systems. Comparing these dimensionalities highlights the effect of confinement on structural transitions. Exact results are derived for 1D systems, while the rational function approximation is used for unconfined 3D fluids. Both scenarios confirm that when the steps are repulsive, the wavelength of the oscillatory decay of the total correlation function evolves with temperature either continuously or discontinuously. In the latter case, a discontinuous oscillation crossover line emerges in the temperature--density plane. For an attractive first step and a repulsive second step, a Fisher--Widom line appears. Although the 1D and 3D results share common features, dimensionality introduces differences: these behaviors occur in distinct temperature ranges, require deeper wells, or become attenuated in 3D. Certain features observed in 1D may vanish in 3D. We conclude that fluids with competing interactions exhibit a rich and intricate pattern of structural transitions, demonstrating the significant influence of dimensionality and interaction features., Comment: 20 pages, 9 figures; v2: one new figure and new references added

We study D4 brane domain walls in the scale-separated 4d $\mathcal{N}$=1 AdS$_4$ DGKT scenario. Classically, these are BPS and satisfy a no-force condition since their tension equals their charge. We show that this property is not stable against quantum corrections and that these increase the brane tension-to-charge ratio, rendering the branes self-attractive. As a result, DGKT seems to be in tension with the Weak Gravity Conjecture for membranes. The quantum effects we consider include non-perturbative gaugino condensation on the D4-brane worldvolume and Euclidean D2 brane instantons, which correct the tension-to-charge ratio because the DGKT construction breaks all parity symmetries. Similar results hold in other 4d $\mathcal{N}$=1 setups not protected by parity symmetries., Comment: 55 pages + appendices + references, 8 figures. v2: Bibliographical error corrected

The chemical enrichment in low-ionization nuclear emission-line regions (LINERs) is still an issue with spatial resolution spectroscopic data due to the lack of studies and the uncertainties in the nature of their ionizing source, despite being the most abundant type of active galaxies in the nearby Universe. Considering different scenarios for the ionizing source (hot old stellar populations, active galactic nuclei (AGN) or inefficient accretion disks), we analyze the implications of these assumptions to constrain the chemical content of the gas-phase interstellar medium (ISM). We used a sample of 105 galaxies from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, whose nuclear central spaxels show LINER-like emission. For each scenario considered, we built a grid of photoionization models (4928 models for each considered ionizing source) which are later used in the open-source code HII-CHI-Mistry, allowing us to estimate chemical abundance ratios such as 12+log(O/H) or log(N/O) and constrain the ionization parameter that characterize the ionized ISM in those galaxies. We obtain that oxygen abundances in the nuclear region of LINER-like galaxies spread over a wide range 8.08 < 12+log(O/H) < 8.89, with a median solar value (in agreement with previous studies) if AGN models are considered. Nevertheless, the derived nitrogen-to-oxygen ratio is much less affected by the assumptions on the ionizing source, and point towards suprasolar values (log(N/O) = -0.69). By comparing the different analyzed scenarios, we show that if hot old stellar populations were responsible of the ionization of the ISM a complex picture (such as outflows and/or inflows scaling with galaxy chemical abundance) would be needed to explain the chemical enrichment history, whereas the assumption of AGN activity is compatible with the standard scenario found in most galaxies., Comment: Revised version after language edition. 24 pages, 13 figures, 9 tables (5 as supplemented material). Accepted for publication in A&A

An FFT based method is proposed to simulate chemo-mechanical problems at the microscale including fracture, specially suited to predict crack formation during the intercalation process in batteries. The method involves three fields fully coupled, concentration, deformation gradient and damage. The mechanical problem is set in a finite strain framework and solved using Fourier Galerkin for non-linear problems in finite strains. The damage is modeled with Phase Field Fracture using a stress driving force. This problem is solved in Fourier space using conjugate gradient with an ad-hoc preconditioner. The chemical problem is modeled with the second Fick's law and physically based chemical potentials, is integrated using backward Euler and is solved by Newton-Raphson combined with a conjugate gradient solver. Buffer layers are introduced to break the periodicity and emulate Neumann boundary conditions for incoming mass flux. The framework is validated against Finite Elements the results of both methods are very close in all the cases. Finally, the framework is used to simulate the fracture of active particles of graphite during ion intercalation. The method is able to solve large problems at a reduced computational cost and reproduces the shape of the cracks observed in real particles., Comment: Accepted in Mechanics of Materials

We present cosmological results from the measurement of clustering of galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). We adopt the full-shape (FS) modeling of the power spectrum, including the effects of redshift-space distortions, in an analysis which has been validated in a series of supporting papers. In the flat $\Lambda$CDM cosmological model, DESI (FS+BAO), combined with a baryon density prior from Big Bang Nucleosynthesis and a weak prior on the scalar spectral index, determines matter density to $\Omega_\mathrm{m}=0.2962\pm 0.0095$, and the amplitude of mass fluctuations to $\sigma_8=0.842\pm 0.034$. The addition of the cosmic microwave background (CMB) data tightens these constraints to $\Omega_\mathrm{m}=0.3056\pm 0.0049$ and $\sigma_8=0.8121\pm 0.0053$, while further addition of the the joint clustering and lensing analysis from the Dark Energy Survey Year-3 (DESY3) data leads to a 0.4% determination of the Hubble constant, $H_0 = (68.40\pm 0.27)\,{\rm km\,s^{-1}\,Mpc^{-1}}$. In models with a time-varying dark energy equation of state, combinations of DESI (FS+BAO) with CMB and type Ia supernovae continue to show the preference, previously found in the DESI DR1 BAO analysis, for $w_0>-1$ and $w_a<0$ with similar levels of significance. DESI data, in combination with the CMB, impose the upper limits on the sum of the neutrino masses of $\sum m_\nu < 0.071\,{\rm eV}$ at 95% confidence. DESI data alone measure the modified-gravity parameter that controls the clustering of massive particles, $\mu_0=0.11^{+0.45}_{-0.54}$, while the combination of DESI with the CMB and the clustering and lensing analysis from DESY3 constrains both modified-gravity parameters, giving $\mu_0 = 0.04\pm 0.22$ and $\Sigma_0 = 0.044\pm 0.047$, in agreement with general relativity. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/). 55 pages, 10 figures

We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include matched sets of synthetic reference `randoms' and weights that account for variations in the observed density of the samples due to experimental design and varying instrument performance. We detail how we correct for variations in observational completeness, the input `target' densities due to imaging systematics, and the ability to confidently measure redshifts from DESI spectra. We then summarize how remaining uncertainties in the corrections can be translated to systematic uncertainties for particular analyses. We describe the weights added to maximize the signal-to-noise of DESI DR1 2-point clustering measurements. We detail measurement pipelines applied to the LSS catalogs that obtain 2-point clustering measurements in configuration and Fourier space. The resulting 2-point measurements depend on window functions and normalization constraints particular to each sample, and we present the corrections required to match models to the data. We compare the configuration- and Fourier-space 2-point clustering of the data samples to that recovered from simulations of DESI DR1 and find they are, generally, in statistical agreement to within 2\% in the inferred real-space over-density field. The LSS catalogs, 2-point measurements, and their covariance matrices will be released publicly with DESI DR1., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/)

We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range $0.1

The Dark Energy Spectroscopic Instrument (DESI) survey is mapping the large-scale distribution of millions of Emission Line Galaxies (ELGs) over vast cosmic volumes to measure the growth history of the Universe. However, compared to Luminous Red Galaxies (LRGs), very little is known about the connection of ELGs with the underlying matter field. In this paper, we employ a novel theoretical model, SHAMe-SF, to infer the connection between ELGs and their host dark matter subhaloes. SHAMe-SF is a version of subhalo abundance matching that incorporates prescriptions for multiple processes, including star formation, tidal stripping, environmental correlations, and quenching. We analyse the public measurements of the projected and redshift-space ELGs correlation functions at $z=1.0$ and $z=1.3$ from DESI One Percent data release, which we fit over a broad range of scales $r \in [0.1, 30]/h^{-1}$Mpc to within the statistical uncertainties of the data. We also validate the inference pipeline using two mock DESI ELG catalogues built from hydrodynamical (TNG300) and semi-analytical galaxy formation models (\texttt{L-Galaxies}). SHAMe-SF is able to reproduce the clustering of DESI-ELGs and the mock DESI samples within statistical uncertainties. We infer that DESI ELGs typically reside in haloes of $\sim 10^{11.8}h^{-1}$M$_{\odot}$ when they are central, and $\sim 10^{12.5}h^{-1}$M$_{\odot}$ when they are a satellite, which occurs in $\sim$30 \% of the cases. In addition, compared to the distribution of dark matter within halos, satellite ELGs preferentially reside both in the outskirts and inside haloes, and have a net infall velocity towards the centre. Finally, our results show evidence of assembly bias and conformity., Comment: 23 pages, 17 figures. To be submitted to A&A

The MUltiplexed Survey Telescope (MUST) is a 6.5-meter telescope under development. Dedicated to highly-multiplexed, wide-field spectroscopic surveys, MUST observes over 20,000 targets simultaneously using 6.2-mm pitch positioning robots within a ~5 deg2 field of view. MUST aims to carry out the first Stage-V spectroscopic survey in the 2030s to map the 3D Universe with over 100 million galaxies and quasars, spanning from the nearby Universe to redshift z~5.5, corresponding to around 1 billion years after the Big Bang. To cover this extensive redshift range, we present an initial conceptual target selection algorithm for different types of galaxies, from local bright galaxies, luminous red galaxies, and emission line galaxies to high-redshift (2 < z < 5.5) Lyman-break galaxies. Using Fisher forecasts, we demonstrate that MUST can address fundamental questions in cosmology, including the nature of dark energy, test of gravity theories, and investigations into primordial physics. This is the first paper in the series of science white papers for MUST, with subsequent developments focusing on additional scientific cases such as galaxy and quasar evolution, Milky Way physics, and dynamic phenomena in the time-domain Universe., Comment: To be submitted to SCPMA

The theory of interfacial properties in liquid-liquid or liquid-vapour systems is nearly 200 years old. The advent of computational tools has greatly advanced the field, mainly through the use of Molecular Dynamics simulations. Despite the successes and advances in the theory of interfacial phenomena for liquid-liquid systems, the study of solid-liquid interfaces remains a challenge both theoretically and experimentally. The main reason why the treatment of solid-liquid systems has fallen behind that of liquid-liquid systems is that there are complications that arise whenever an interface involving solid systems is considered involving both theory of the solid-liquid interface and the calculations using MD simulations. An example of the former is that, contrary to the liquid-liquid case, the interfacial properties of solids depend on the lattice orientation. The main complications in these calculations arise from the fact that for solids the ``mechanical route'' cannot be used. To overcome this problem, several numerical approaches were proposed. The main purpose of this review is to provide an overview of these different methodologies and to discuss their strengths and weaknesses. We classify these methodologies into two main groups: direct and indirect methods. Direct methods are those that can calculate directly the properties of interfaces, while in indirect approaches the properties of the interface are not the primary result of the simulations. We also included a discussion on the origin of the difficulties in considering solid interfaces from a thermodynamic point of view. In the second part of the review, we discuss two key related topics: nucleation theory and curved interfaces. They both represent an important problem in the study of interfaces and in the context of solid-liquid ones for which the research is still extremely active., Comment: 111 pages, 14 figures

Interoperability is the key to implementing a wide range of energy systems applications. It involves the seamless cooperation of different methods and components. With smart energy systems, interoperability faces challenges due to integrating differ-ent approaches and technologies. This includes dealing with heterogeneous approaches with various communication proto-cols and data formats. However, it is essential for smart energy systems to carry out thorough interoperability tests. They are usually diverse, and challenging, thus requiring careful consideration of compatibility issues and complex integration scenari-os. Overcoming these challenges requires a systematic approach that includes thorough test planning, rigorous testing, and continuous test monitoring. Although numerous testing approaches exist, most are more developed at the component/device level than at the system level. Consequently, there are few approaches and related facilities to test the interoperability of smart energy approaches and solutions at the system level. This work analyses existing interoperability test concepts, identi-fies enablers and the potential for harmonisation of procedures, and proposes further developments of these approaches., Comment: 14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion (MED POWER 2024)

Wireless communications are critical in the constantly changing environment of IoT and RFID technologies, where thousands of devices can be deployed across a wide range of scenarios. Whether connecting to cloud servers or local fog/edge devices, maintaining seamless communications is difficult, especially in demanding contexts like industrial warehouses or remote rural areas. Opportunistic networks, when combined with edge devices, provide a possible solution to this challenge. These networks enable IoT devices, particularly mobile devices, to redirect information as it passes via other devices until it reaches an edge node. Using different communication protocols, this paper investigates their effects on response times and total messages received for a opportunistic assisted RFID system. Specifically, this article compares two communications technologies (Bluetooth 5 and Wize) when used for building a novel Opportunistic Edge Computing (OEC) identification system based on low-cost Single-Board Computers (SBCs). For such a comparison, measurements have been performed for quantifying packet loss and latency. The tests consisted in two experiments under identical conditions and scenarios, with a node located roadside, transmitting identification information, and a node located inside a moving vehicle that was driven at varying vehicle speeds. The obtained results show for Bluetooth 5 average latencies ranging between 700 and 950 ms with packet losses between 7% and 27%, whereas for Wize the average delay as between 150 and 370 ms with packet losses between 20% and 52%., Comment: Paper accepted in IEEE RFID 2024

Obtaining well-calibrated photometric redshift probability densities for galaxies without a spectroscopic measurement remains a challenge. Deep learning discriminative models, typically fed with multi-band galaxy images, can produce outputs that mimic probability densities and achieve state-of-the-art accuracy. However, such models may be affected by miscalibration that would result in discrepancies between the model outputs and the actual distributions of true redshifts. Our work develops a novel method called the Contrastive Learning and Adaptive KNN for Photometric Redshift (CLAP) that resolves this issue. It leverages supervised contrastive learning (SCL) and k-nearest neighbours (KNN) to construct and calibrate raw probability density estimates, and implements a refitting procedure to resume end-to-end discriminative models ready to produce final estimates for large-scale imaging data. The harmonic mean is adopted to combine an ensemble of estimates from multiple realisations for improving accuracy. Our experiments demonstrate that CLAP takes advantage of both deep learning and KNN, outperforming benchmark methods on the calibration of probability density estimates and retaining high accuracy and computational efficiency. With reference to CLAP, we point out that miscalibration is particularly sensitive to the method-induced excessive correlations among data instances in addition to the unaccounted-for epistemic uncertainties. Reducing the uncertainties may not guarantee the removal of miscalibration due to the presence of such excessive correlations, yet this is a problem for conventional deep learning methods rather than CLAP. These discussions underscore the robustness of CLAP for obtaining photometric redshift probability densities required by astrophysical and cosmological applications. This is the first paper in our series on CLAP., Comment: 22 + 6 pages, 9 + 5 figures

The large-scale linear halo bias encodes the relation between the clustering of dark-matter (DM) halos and that of the underlying matter density field. Although the primary dependence of bias on halo mass is well understood in the context of structure formation, the physical origins of the multiple additional relations at fixed halo mass, commonly known as secondary halo bias, have not been fully elucidated. Of particular relevance is the secondary dependence on halo assembly history, known as halo assembly bias. Our goal is to determine whether the properties of the initial regions from which $z=0$ halos originate produce any secondary bias at $z=0$. By analyzing these initial dependencies in connection with halo assembly bias, we intend to provide insight on the physical origins of the effect. To this end, we select halos at $z=0$ in the IllustrisTNG DM-only simulation and trace back the positions and velocities of their DM particles to $z=12$. The resulting initial regions are characterized according to several shape-related and kinematic properties. The secondary bias signal produced by these properties at $z=0$ is measured using an object-by-object bias estimator, which offers significant analytical advantages. We show that, when split by the properties of their initial DM clouds, $z=0$ halos display significant secondary bias, clearly exceeding the amplitude of the well-known halo assembly bias signal produced by concentration and age. The maximum bias segregation is measured for cloud velocity dispersion and radial velocity, followed by cloud concentration, sphericity, ellipticity and triaxiality. We further show that both velocity dispersion and radial velocity are also the properties of the initial clouds that most strongly correlate with halo age and concentration at fixed halo mass. Our results highlight the importance of linear effects in shaping halo assembly bias., Comment: 9 pages, 5 figures. Submitted to A&A, comments welcome

The connection between galaxies and dark matter halos encompasses a range of processes and play a pivotal role in our understanding of galaxy formation and evolution. Traditionally, this link has been established through physical or empirical models. Machine learning techniques are adaptable tools that handle high-dimensional data and grasp associations between numerous attributes. In particular, probabilistic models capture the stochasticity inherent to these complex relations. We compare different probabilistic machine learning methods to model the uncertainty in the halo-galaxy connection and efficiently generate galaxy catalogs that faithfully resemble the reference sample by predicting joint distributions of central galaxy properties conditioned to their host halo features. The analysis is based on the IllustrisTNG300 simulation. The methods model the distributions in different ways. We compare a multilayer perceptron that predicts the parameters of a multivariate Gaussian distribution, a multilayer perceptron classifier, and the method of normalizing flows. The classifier predicts the parameters of a Categorical distribution, which are defined in a high-dimensional parameter space through a Voronoi cell-based hierarchical scheme. We evaluate the model's performances under various sample selections based on halo properties. The three methods exhibit comparable results, with normalizing flows showing the best performance in most scenarios. The models reproduce the main features of galaxy properties distributions with high-fidelity and reproduce the results obtained with traditional, deterministic, estimators. Our results also indicate that different halos and galaxy populations are subject to varying degrees of stochasticity, which has relevant implications for studies of large-scale structure., Comment: 14 pages, 8 figures, 6 tables

Magnetite, a naturally abundant mineral, frequently interacts with water in both natural settings and various technical applications, making the study of its surface chemistry highly relevant. In this work, we investigate the hydrogen bonding dynamics and the presence of hydroxyl species at the magnetite-water interface using a combination of neural network potential-based molecular dynamics simulations and sum frequency generation vibrational spectroscopy. Our simulations, which involved large water systems, allowed us to identify distinct interfacial species, such as dissociated hydrogen and hydroxide ions formed by water dissociation. Notably, water molecules near the interface exhibited a preference for dipole orientation towards the surface, with bulk-like water behavior only re-emerging beyond 60 {\AA} from the surface. The vibrational spectroscopy results aligned well with the simulations, confirming the presence of a hydrogen bond network in the surface ad-layers. The analysis revealed that surface-adsorbed hydroxyl groups orient their hydrogen atoms towards the water bulk. In contrast, hydrogen-bonded water molecules align with their hydrogen atoms pointing towards the magnetite surface.

Soft robots have the potential to revolutionize the use of robotic systems with their capability of establishing safe, robust, and adaptable interactions with their environment, but their precise control remains challenging. In contrast, traditional rigid robots offer high accuracy and repeatability but lack the flexibility of soft robots. We argue that combining these characteristics in a hybrid robotic platform can significantly enhance overall capabilities. This work presents a novel hybrid robotic platform that integrates a rigid manipulator with a fully developed soft arm. This system is equipped with the intelligence necessary to perform flexible and generalizable tasks through imitation learning autonomously. The physical softness and machine learning enable our platform to achieve highly generalizable skills, while the rigid components ensure precision and repeatability., Comment: Corrected missing citation

Air-vented ionization chambers exposed to clinical radiation beams may suffer from recombination during the drift of the charge carriers towards the electrodes. Thus, dosimetry protocols recommend the use of a correction factor, usually denominated saturation factor ($k_{\rm sat}$), to correct the ionization chamber readout for the incomplete collection of charge. The two-voltage method is the recommended methodology for the calculation of the saturation factor, however, it is based on the early Boag model, which only takes into account the presence of positive and negative ions in the ionization chamber and does not account for the electric field screening or the free electron contribution to the signal. The numerical simulation shows a better agreement with the experimental data than the current analytical theories in terms of charge collection efficiency. The classical two-voltage method, systematically overestimates the saturation factor, with differences increasing with dose per pulse also present at low dose per pulse. These results may have implications for the dosimetry with ionization chambers in therapy modalities that use a dose per pulse higher than conventional radiotherapy such as intraoperative radiotherapy but also in conventional dose per pulse for ionization chambers that suffer from significant charge recombination.

Background and purpose: IMPT faces challenges in lung cancer treatment, like maintaining plan robustness for moving tumors against setup, range errors, and interplay effects. Proton Arc Therapy (PAT) is an alternative to maintain target coverage, potentially improving organ at risk (OAR) sparing, reducing beam delivery time (BDT), and enhancing patient experience. We aim to perform a systematic plan comparison study between IMPT and ELSA-PAT to assess its potential for lung cancer treatment. Material and Methods: 14 Lung ELSA-PAT plans were compared retrospectively with IMPT plans. 4D worst-case minimax robust optimization was performed, including 84 scenarios (3%,3 mm). Dosimetry assessment included target (CTV) and important OARs, on nominal and worst-case scenarios. Most relevant normal tissue complication probabilities (NTCP), target coverage robustness against interplay effect and beam delivery time (BDT) were evaluated. Results: CTV D95% and D98% showed no significant difference in comparison. PAT demonstrated better conformality by 66% (p = 0.00012) but delivered a higher heart mean dose (HMD,23%). There was a 2% increase in NTCP 2-year mortality risk with PAT. Total BDT was comparable among techniques. IMPT was more robust than PAT against interplay effect, considering both D1% (1,0 $\pm$ 0.8 Gy vs 1.1 $\pm$ 1.4 Gy) and D98% bandwidths (0.9$\pm$0.9 Gy vs 1.1 $\pm$ 1.3 Gy). Interpretation: both techniques provide a similar level of dose coverage to the target volume. Although PAT improved dose conformality, higher HMD translated into increased heart toxicity, presumably due to chosen planning methodology and OAR proximity to target. Increased energy layers and spots raised PAT beam delivery time, although it could improve daily treatment workflow.

The tumultuous effects of ultraviolet photons that source cosmic reionization, the subsequent compression and shock-heating of low-density regions, and the modulation of baryons in shallow potential wells induced by the passage of ionization fronts, collectively introduce perturbations to the evolution of the intergalactic medium in the post-reionization era. These enduring fluctuations persist deep into the post-reionization era, casting a challenge upon precision cosmology endeavors targeting tracers in this cosmic era. Simultaneously, these relics from reionization also present a unique opportunity to glean insights into the astrophysics that govern the epoch of reionization. In this work, we propose a first study of the cross-correlation of \lya forest and 21 cm intensity mapping, accounting for the repercussions of inhomogeneous reionization in the post-reionization era. We investigate the ability of SKA $\times$ DESI-like, SKA $\times$ MUST-like, and PUMA $\times$ MUST-like instrumental setups to achieve a high signal-to-noise ratio (SNR) in the redshift range $3.5 \leq z \leq 4$. Moreover, we assess how alterations in integration time, survey area, and reionization scenarios impact the SNR. Furthermore, we forecast the cross-correlation's potential to constrain cosmological parameters under varying assumptions: considering or disregarding reionization relics, marginalizing over reionization astrophysics, and assuming perfect knowledge of reionization. Notably, our findings underscore the remarkable capability of a futuristic PUMA $\times$ MUST-like setup, with a modest 100-hour integration time over a 100 sq. deg. survey, to constrain the ionization efficiency error to $\sigma_\zeta = 3.42 $., Comment: Updated to match accepted version for publication

We compute baryon and electric charge deposition in high-energy heavy-ion collisions using the Color Glass Condensate (CGC) Effective Field Theory, where at leading order charge is deposited through multiple scatterings of valence quarks with a saturated gluon target. A simplified phenomenological formula is derived to describe charge deposition, from which the parametrical dependence with collisional energy and geometry can be extracted. We present an approximate analytical prediction of the so-called baryon stopping parameter $\alpha_B$, which shows excellent agreement with the state-of-the art extractions of $\alpha_B$ from experimental data. These results are further validated using the McDIPPER framework, by computing charge deposition at midrapidity across a range of collision energies ($\sqrt{s_{\rm NN}}= 62.4 - 5020$ GeV).

On large scales, the Lyman-$\alpha$ forest provides insights into the expansion history of the Universe, while on small scales, it imposes strict constraints on the growth history, the nature of dark matter, and the sum of neutrino masses. This work introduces ForestFlow, a novel framework that bridges the gap between large- and small-scale analyses, which have traditionally relied on distinct modeling approaches. Using conditional normalizing flows, ForestFlow predicts the two Lyman-$\alpha$ linear biases ($b_\delta$ and $b_\eta$) and six parameters describing small-scale deviations of the three-dimensional flux power spectrum ($P_\mathrm{3D}$) from linear theory as a function of cosmology and intergalactic medium physics. These are then combined with a Boltzmann solver to make consistent predictions, from arbitrarily large scales down to the nonlinear regime, for $P_\mathrm{3D}$ and any other statistics derived from it. Trained on a suite of 30 fixed-and-paired cosmological hydrodynamical simulations spanning redshifts from $z=2$ to 4.5, ForestFlow achieves 3 and 1.5\% precision in describing $P_\mathrm{3D}$ and the one-dimensional flux power spectrum ($P_\mathrm{1D}$) from linear scales to $k=5\,\mathrm{Mpc}^{-1}$ and $k_\parallel=4\,\mathrm{Mpc}^{-1}$, respectively. Thanks to its conditional parameterization, ForestFlow shows similar performance for ionization histories and two $\Lambda$CDM model extensions $\unicode{x2013}$ massive neutrinos and curvature $\unicode{x2013}$ even though none of these are included in the training set. This framework will enable full-scale cosmological analyses of Lyman-$\alpha$ forest measurements from the DESI survey., Comment: 18 pages, 12 figures. Accepted in A&A

This contribution summarizes the main activities and objectives of the outreach project Astroaccesible, whose main aim is to carry the teaching and diffusion of astronomy among all kinds of collectives, focusing on blind and visually impaired (BVI) people. This project is led by a blind astronomer and aims to use a variety of resources based on different sensory channels, avoiding limiting the transmission of concepts to visual perception. This principle favors inclusion and benefits everyone, as the information is not presented using just one channel. This strategy is especially convenient for the nowadays typical data acquisition, where a variety of sources of information, not solely based on the collection of different spectral domains of electromagnetic radiation, is used. Moreover, the study of new multi-messenger astronomy could be much better understood using a multi-messenger teaching approach, favoring inclusion, motivation, and creativity., Comment: To appear as a proceeding of the 13th Cosmic-Ray International Studies and Multi-messenger Astroparticle Conference held on June 2024 in Trapani (Sicily, Italy). 8 pages and 4 figures

The standard Poisson-Boltzmann model for molecular electrostatics assumes a sharp variation of the permittivity and salt concentration along the solute-solvent interface. The discontinuous field parameters are not only difficult numerically, but also are not a realistic physical picture, as it forces the dielectric constant and ionic strength of bulk in the near-solute region. An alternative to alleviate some of these issues is to represent the molecular surface as a diffuse interface, however, this also presents challenges. In this work we analysed the impact of the shape of the interfacial variation of the field parameters in solvation and binding energy. However we used a hyperbolic tangent function ($\tanh(k_p x)$) to couple the internal and external regions, our analysis is valid for other definitions. Our methodology was based on a coupled finite element (FEM) and boundary element (BEM) scheme that allowed us to have a special treatment of the permittivity and ionic strength in a bounded FEM region near the interface, while maintaining BEM elsewhere. Our results suggest that the shape of the function (represented by $k_p$) has a large impact on solvation and binding energy. We saw that high values of $k_p$ induce a high gradient on the interface, to the limit of recovering the sharp jump when $k_p\to\infty$, presenting a numerical challenge where careful meshing is key. Using the FreeSolv database to compare with molecular dynamics, our calculations indicate that an optimal value of $k_p$ for solvation energies was around 3. However, more challenging binding free energy tests make this conclusion more difficult, as binding showed to be very sensitive to small variations of $k_p$. In that case, optimal values of $k_p$ ranged from 2 to 20.

The magnetite/water interface is commonly found in nature and plays a crucial role in various technological applications. However, our understanding of its structural and dynamical properties at the molecular scale remains still limited. In this study, we develop an efficient Behler-Parrinello neural network potential (NNP) for the magnetite/water system, paying particular attention to the accurate generation of reference data with density functional theory. Using this NNP, we performed extensive molecular dynamics simulations of the magnetite (001) surface across a wide range of water coverages, from the single molecule to bulk water. Our simulations revealed several new ground states of low coverage water on the Subsurface Cation Vacancy (SCV) model and yielded a density profile of water at the surface that exhibits marked layering. By calculating mean square displacements, we obtained quantitative information on the diffusion of water molecules on the SCV for different coverages, revealing significant anisotropy. Additionally, our simulations provided qualitative insights into the dissociation mechanisms of water molecules at the surface.

Inspired by Bourqui's work on anticanonical height zeta functions on Hirzebruch surfaces, we study height zeta functions of split toric varieties with Picard rank 2 over global function fields, with respect to height functions associated with big metrized line bundles. We show that these varieties can be naturally decomposed into a finite disjoint union of subvarieties, where precise analytic properties of the corresponding height zeta functions can be given. As application, we obtain asymptotic formulas for the number of rational points of large height on each subvariety, with explicit leading constants and controlled error terms., Comment: Updated version including asymptotic formulas for the number of rational points of large height. Comments are welcome!

The calculation of the interfacial free energy between two thermodynamic phases is crucial across various fields, including materials science, chemistry, and condensed matter physics. In this study, we apply an existing thermodynamic approach, the Gibbs-Cahn integration method, to determine the interfacial free energy under different coexistence conditions, relying on data from a single-state calculation at specified pressure and temperature. This approach developed by Laird et al. [J. Chem. Phys. 131, 114110 (2009)] reduces computational demand and enhances efficiency compared to methods that require separate measurements at each thermodynamic state. The integration scheme computes the excess interfacial free energy using unbiased NVT simulations, where the two phases coexist, to provide input for the calculations. We apply this method to the Lennard-Jones and mW water models for liquid-solid interfaces, as well as the Lennard-Jones and TIP4P/2005 models for liquid-vapor interfaces. Our results demonstrate the accuracy and effectiveness of this integration route for estimating the interfacial free energy along a coexistence line., Comment: Main text: 15 pages and 9 figures. Supporting material: 9 pages and 7 figures

Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spatio-temporal resolutions. Earth System Data Cubes (ESDCs) have emerged as one suitable solution for transforming this flood of data into a simple yet robust data structure. ESDCs achieve this by organising data into an analysis-ready format aligned with a spatio-temporal grid, facilitating user-friendly analysis and diminishing the need for extensive technical data processing knowledge. Despite these significant benefits, the completion of the entire ESDC life cycle remains a challenging task. Obstacles are not only of a technical nature but also relate to domain-specific problems in Earth system research. There exist barriers to realising the full potential of data collections in light of novel cloud-based technologies, particularly in curating data tailored for specific application domains. These include transforming data to conform to a spatio-temporal grid with minimum distortions and managing complexities such as spatio-temporal autocorrelation issues. Addressing these challenges is pivotal for the effective application of Artificial Intelligence (AI) approaches. Furthermore, adhering to open science principles for data dissemination, reproducibility, visualisation, and reuse is crucial for fostering sustainable research. Overcoming these challenges offers a substantial opportunity to advance data-driven Earth system research, unlocking the full potential of an integrated, multidimensional view of Earth system processes. This is particularly true when such research is coupled with innovative research paradigms and technological progress.

We study the asymptotic growth of the number of rational points of bounded height on smooth projective split toric varieties with Picard rank 2 over number fields, with respect to Arakelov height functions associated with big metrized line bundles. We show that these varieties can be naturally decomposed into a finite disjoint union of subvarieties, where explicit asymptotic formulas for the number of rational points of bounded height can be given. Additionally, we present various examples, including the case of Hirzebruch surfaces.

Context. Mock galaxy catalogues are essential for correctly interpreting current and future generations of galaxy surveys. Despite their significance in galaxy formation and cosmology, little to no work has been done to validate the predictions of these mocks for high-order clustering statistics. Aims. We compare the predicting power of the latest generation of empirical models used in the creation of mock galaxy catalogues: a 13-parameter Halo Occupation Distribution (HOD) and an extension of the SubHalo Abundance Matching technique (SHAMe). Methods. We build GalaxyEmu-Planck, an emulator that makes precise predictions for the two-point correlation function, galaxy-galaxy lensing (restricted to distances greater than 1 $h^{-1} {\rm Mpc}$ to avoid baryonic effects), and other high-order statistics resulting from the evaluation of SHAMe and HOD models. Results. We evaluate the precision of GalaxyEmu-Planck using two galaxy samples extracted from the FLAMINGO hydrodynamical simulation that mimic the properties of DESI-BGS and BOSS galaxies, finding that the emulator reproduces all the predicted statistics precisely. The HOD showed comparable performance when fitting galaxy clustering and galaxy-galaxy lensing. In contrast, the SHAMe model showed better predictions for higher-order statistics, especially regarding the galaxy assembly bias. We also tested the performance of the models after removing some of their extensions, finding that we can withdraw two of the HOD parameters without a loss of performance. Conclusions. The results of this paper validate the current generation of empirical models as a way to reproduce galaxy clustering, galaxy-galaxy lensing and other high-order statistics. The excellent performance of the SHAMe model with a small number of free parameters suggests that it is a valid method to extract cosmological constraints from galaxy clustering., Comment: 22 pages, 12 figures, submitted to A&A. Comments welcomed!