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We initiate the study of differentially private data-compression schemes motivated by the insecurity of the popular "Compress-Then-Encrypt" framework. Data compression is a useful tool which exploits redundancy in data to reduce storage/bandwidth when files are stored or transmitted. However, if the contents of a file are confidential then the length of a compressed file might leak confidential information about the content of the file itself. Encrypting a compressed file does not eliminate this leakage as data encryption schemes are only designed to hide the content of confidential message instead of the length of the message. In our proposed Differentially Private Compress-Then-Encrypt framework, we add a random positive amount of padding to the compressed file to ensure that any leakage satisfies the rigorous privacy guarantee of $(\epsilon,\delta)$-differential privacy. The amount of padding that needs to be added depends on the sensitivity of the compression scheme to small changes in the input, i.e., to what degree can changing a single character of the input message impact the length of the compressed file. While some popular compression schemes are highly sensitive to small changes in the input, we argue that effective data compression schemes do not necessarily have high sensitivity. Our primary technical contribution is analyzing the fine-grained sensitivity of the LZ77 compression scheme (IEEE Trans. Inf. Theory 1977) which is one of the most common compression schemes used in practice. We show that the global sensitivity of the LZ77 compression scheme has the upper bound $\mathcal{O}(W^{2/3}\log n)$ where $W\leq n$ denotes the size of the sliding window. When $W=n$, we show the lower bound $\Omega(n^{2/3}\log^{1/3}n)$ for the global sensitivity of the LZ77 compression scheme which is tight up to a sublogarithmic factor., Comment: 31 pages, 6 figures

Background: Data collected in controlled settings typically results in high-quality datasets. However, in real-world applications, the quality of data collection is often compromised. It is well established that the quality of a dataset significantly impacts the performance of machine learning models. Methods: A rudimentary error rate metric was developed to evaluate textual dataset quality at the token level. Mixtral Large Language Model (LLM) was used to quantify and correct errors in low quality datasets. The study analyzed two healthcare datasets: the high-quality MIMIC-III public hospital dataset and a lower-quality private dataset from Australian aged care homes. Errors were systematically introduced into MIMIC at varying rates, while the ACH dataset quality was improved using the LLM. Results: For the sampled 35,774 and 6,336 patients from the MIMIC and ACH datasets respectively, we used Mixtral to introduce errors in MIMIC and correct errors in ACH. Mixtral correctly detected errors in 63% of progress notes, with 17% containing a single token misclassified due to medical terminology. LLMs demonstrated potential for improving progress note quality by addressing various errors. Under varying error rates, feature representation performance was tolerant to lower error rates (<10%) but declined significantly at higher rates. Conclusions: The study revealed that models performed relatively well on datasets with lower error rates (<10%), but their performance declined significantly as error rates increased (>=10%). Therefore, it is crucial to evaluate the quality of a dataset before utilizing it for machine learning tasks. For datasets with higher error rates, implementing corrective measures is essential to ensure the reliability and effectiveness of machine learning models.

The mass of galaxy clusters derived from weak-lensing observations is sensitive to projection effects, and, on average, it is biased low with respect to the true cluster mass, with a mass and redshift dependence. In this work, we leverage state-of-the-art hydrodynamical simulations of galaxy clusters carried out with GadgetX and GIZMO-SIMBA as part of the Three Hundred Project. We use them to quantify weak-lensing mass biases with respect also to the results from dark matter-only simulations. We also investigate how the biases of the weak-lensing mass estimates propagate into the richness-mass relation. Future wide-field weak-lensing surveys require per cent accuracy on the characterisation of cluster masses in order to use galaxy cluster number count and clustering as complementary probes for cosmological analyses. We aim to shed light on the effect of the presence of baryons on the weak-lensing mass bias and also whether this bias depends on the galaxy formation recipe; in addition, we seek to model the richness-mass relation that can be used as guidelines for observational experiments for cluster cosmology. We produce weak-lensing simulations of random projections to model the expected excess surface mass density profile of clusters up to redshift $z=1$. We derive the weak-lensing mass-richness relation and find consistency within 1$\sigma$ uncertainties across hydrodynamical simulations. The scatter in observed richness at a fixed weak-lensing mass, or vice versa, increases linearly with redshift at a fixed stellar mass cut. Importantly, we observe that the scatter in richness at a given true mass is smaller than at a given weak-lensing mass. Our results align well with SDSS redMaPPer cluster observations. (Abridged), Comment: submitted to A&A, comments are welcome

Investigations of trajectories of various objects orbiting the Milky Way (MW) halo with modern precision, achievable in observations by GAIA, requires sophisticated, non-stationary models of the Galactic potential. In this paper we analyze the evolution of the spherical harmonics expansion of MW analogues potential in constrained simulations of the Local Group (LG) from the HESTIA suite. We find that at distances $r>50$~kpc the anisotropic part of the potential demonstrates a significant impact of the environment: ignoring the mass distribution outside the virial radius of the MW results in 20\% errors in the potential quadrupole at these distances. Spherical harmonics vary significantly during the last 6 Gyr. We attribute variations of the potential at $r\ge 30$~kpc to the motions of MW satellites and LG galaxies. We also predict that the anisotropy of the real MW potential should grow with distance in the range $r_\mathrm{vir}

Magnetic fields are ubiquitous across different physical systems of current interest; from the early Universe, compact astrophysical objects and heavy-ion collisions to condensed matter systems. A proper treatment of the effects produced by magnetic fields during the dynamical evolution of these systems, can help to understand observables that otherwise show a puzzling behavior. Furthermore, when these fields are comparable to or stronger than \Lambda_QCD, they serve as excellent probes to help elucidate the physics of strongly interacting matter under extreme conditions of temperature and density. In this work we provide a comprehensive review of recent developments on the description of QED and QCD systems where magnetic field driven effects are important. These include the modification of meson static properties such as masses and form factors, the chiral magnetic effect, the description of anomalous transport coefficients, superconductivity in extreme magnetic fields, the properties of neutron stars, the evolution of heavy-ion collisions, as well as effects on the QCD phase diagram. We describe recent theory and phenomenological developments using effective models as well as LQCD methods. The work represents a state-of-the-art review of the field, motivated by presentations and discussions during the "Workshop on Strongly Interacting Matter in Strong Electromagnetic Fields" that took place in the European Centre for Theoretical Studies in Nuclear Physics and Related Areas (ECT*) in the city of Trento, Italy, September 25-29, 2023., Comment: 325 pages-long review of recent topics of interest in the field of magnetic field effects on QED and QCD matter. To be susbmitted to PNPP

In this article, we analyze the effects of stochastic magnetic fluctuations with respect to an intense magnetic field background over the yields for photon and dilepton emission processes in a thermalized quark-gluon plasma phase. Such stochastic fluctuations model the effects of nearly random initial conditions for the nuclei participating in non-central heavy-ion collisions, which are the sources of the background magnetic field. Our theoretical results predict significant anisotropic effects due to stochastic magnetic noise over the angular distribution for photon and dilepton production rates in this scenario., Comment: 13 pages, 12 figures

The paper introduces a novel approach for estimating soil moisture in vegetated surfaces, specifically focusing on sugarcane crops throughout various growth stages in agriculture applications. While existing models typically address bare soil scenarios, this model utilizes data from P-, L-, and C-band Synthetic Aperture Radar (SAR) to estimate soil moisture. The semi-empirical Dubois model forms the basis of the proposed model, which has been adapted to accommodate multiband operation and crop height variations. Synthetic datasets are generated using the adjusted model to train two neural networks incorporated into the overall model. Additionally, a linear expression for estimating crop height is integrated into the model. The model is validated in an Experimental Site at the School of Agricultural Engineering, UNICAMP, and an independent area at the Sugarcane Technology Center in Piracicaba, Brazil. The model utilizes a multiband drone-borne SAR system with a 3-meter image resolution and radiometric accuracy of 0.5 dB. The results indicate that the model can estimate soil moisture with root-mean-square errors of 0.05 cm3.cm-3 (5 vol. %) across crop heights ranging from zero to 2.5 meters., Comment: 9 pages, 12 figures, 2 tables, 17 equations

This study investigates the applicability of Singular Value Decomposition for the image classification of specific breeds of cats and dogs using fur color as the primary identifying feature. Sequential Quadratic Programming (SQP) is employed to construct optimally weighted templates. The proposed method achieves 69% accuracy using the Frobenius norm at rank 10. The results partially validate the assumption that dominant features, such as fur color, can be effectively captured through low-rank approximations. However, the accuracy suggests that additional features or methods may be required for more robust classification, highlighting the trade-off between simplicity and performance in resource-constrained environments., Comment: 10 pages, 7 figures

The thermal Sunyaev-Zel'dovich (tSZ) effect arises from inverse Compton scattering of low energy photons onto thermal electrons, proportional to the integrated electron pressure, and is usually observed from galaxy clusters. However, we can expect that the Epoch of Reionization (EoR) also contributes to this signal, but that contribution has not been previously evaluated. In this work we analyse a suite of fully-coupled radiation-hydrodynamics simulations based on RAMSES-CUDATON to calculate and study the tSZ signal from the Reionization Epoch. We construct lightcones of the electron pressure in the intergalactic medium for $6

We study the influence of thermal fluctuations on the two-time correlation functions of bosonic baths within a superstatistics framework by assuming that fluctuations follow the gamma distribution. We further establish a connection between superstatistics and Tsallis non-additive thermodynamics by introducing a temperature-renormalizing parameter. Our results show that, for an Ohmic model, the system's correlation functions exhibit diverse time-dependent behaviors, with the real and imaginary parts displaying enhancement or suppression depending on temperature and fluctuation strength. Additionally, we analyze the impact of these fluctuations on the quantum master equation of a damped two-level atom coupled to an out-of-equilibrium radiation bath. We demonstrate that while the equation's algebraic structure remains intact, the coupling constants are modified by the fluctuation parameters and cavity volume. Specifically, we observe that the AC Stark effect undergoes significant modifications, with fluctuations influencing the transition between repulsive and attractive energy levels., Comment: 16 pages, 6 figures

Dispersion measures (DM) of fast radio bursts (FRBs) probe the density of electrons in the intergalactic medium (IGM) along their lines-of-sight, including the average density versus distance to the source and its variations in direction. While previous study focused on low-redshift, FRBs are potentially detectable out to high redshift, where their DMs can, in principle, probe the epoch of reionization (EOR) and its patchiness. We present the first predictions from large-scale, radiation-hydrodynamical simulation of fully-coupled galaxy formation and reionization, using Cosmic Dawn (``CoDa")~II to model the density and ionization fields of the universe down to redshifts through the end of the EOR at $z_{re}\approx6.1$. Combining this with an N-body simulation CoDa~II--Dark Matter of the fully-ionized epoch from the EOR to the present, we calculate the mean and standard deviation of FRB DMs as functions of their source redshift. The mean and standard deviation of DM increase with redshift, reaching a plateau by $z(x_{HII}\lesssim0.25)\gtrsim8$, i.e. well above $z_{re}$. The mean-DM asymptote $\mathcal{DM}_{max} \approx 5900~\mathrm{pc\, cm^{-3}}$ reflects the end of the EOR and its duration. The standard deviation there is $\sigma_{DM, max}\approx497 ~\mathrm{pc\, cm^{-3}}$, reflecting inhomogeneities of both patchy reionization and density. Inhomogeneities in ionization during the EOR contribute $\mathcal{O}(1$ per cent) of this value of $\sigma_{DM,max}$ from FRBs at redshifts $z\gtrsim 8$. Current estimates of FRB rates suggest this may be detectable within a few years of observation., Comment: 14 pages, 10 figures, 2 tables, 2 appendices

The new generation of upcoming deep photometric and spectroscopic surveys will allow us to measure the astrophysical properties of faint galaxies in massive clusters. This would demand to produce simulations of galaxy clusters with better mass resolution than the ones available today if we want to make comparisons between the upcoming observations and predictions of cosmological models. But producing full-physics hydrodynamical simulations of the most massive clusters is not an easy task. This would involve billions of computational elements to reliably resolve low mass galaxies similar to those measured in observations. On the other hand, dark matter only simulations of cluster size halos can be done with much larger mass resolution but at the cost of having to apply a model that populate galaxies within each of the subhalos in these simulations. In this paper we present the results of a new set of dark matter only simulations with different mass resolutions within the THE THREE HUNDRED project. We have generated catalogs of galaxies with stellar and luminosity properties by applying the SAGE Semi-Analytical Model of galaxy formation. To obtain the catalogs consistent with the results from hydrodynamical simulations, the internal physical parameters of SAGE were calibrated with the Particle Swarm Optimization method using a subset of full-physics runs with the same mass resolution than the dark matter only ones., Comment: To appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

According to CMB measurements, baryonic matter constitutes about $5\%$ of the mass-energy density of the universe. A significant population of these baryons, for a long time referred to as `missing', resides in a low density, warm-hot intergalactic medium (WHIM) outside galaxy clusters, tracing the ``cosmic web'', a network of large scale dark matter filaments. Various studies have detected this inter-cluster gas, both by stacking and by observing individual filaments in compact, massive systems. In this paper, we study short filaments (< 10 Mpc) connecting massive clusters ($M_{500} \approx 3\times 10^{14} M_{\odot}$) detected by the Atacama Cosmology Telescope (ACT) using the scattering of CMB light off the ionised gas, a phenomenon known as the thermal Sunyaev-Zeldovich (tSZ) effect. The first part of this work is a search for suitable candidates for high resolution follow-up tSZ observations. We identify four cluster pairs with an intercluster signal above the noise floor (S/N $>$ 2), including two with a tentative $>2\sigma$ statistical significance for an intercluster bridge from the ACT data alone. In the second part of this work, starting from the same cluster sample, we directly stack on ${\sim}100$ cluster pairs and observe an excess SZ signal between the stacked clusters of $y=(7.2^{+2.3}_{-2.5})\times 10^{-7}$ with a significance of $3.3\sigma$. It is the first tSZ measurement of hot gas between clusters in this range of masses at moderate redshift ($\langle z\rangle\approx 0.5$). We compare this to the signal from simulated cluster pairs with similar redshifts and separations in the THE300 and MAGNETICUM Pathfinder cosmological simulations and find broad consistency. Additionally, we show that our measurement is consistent with scaling relations between filament parameters and mass of the embedded halos identified in simulations., Comment: 37 pages, 17 images

We analyse the maps of the Sunyaev-Zel'dovich (SZ) signal of local galaxy clusters ($z<0.1$) observed by the $Planck$ satellite in order to classify their dynamical state through morphological features. To study the morphology of the cluster maps, we apply a method recently employed on mock SZ images generated from hydrodynamical simulated galaxy clusters in THE THREE HUNDRED (THE300) project. Here, we report the first application on real data. The method consists in modelling the images with a set of orthogonal functions defined on circular apertures, the Zernike polynomials. From the fit we compute a single parameter, $\mathcal{C}$, that quantifies the morphological features present in each image. The link between the morphology of 2D images and the dynamical state of the galaxy clusters is well known, even if not obvious. We use mock $Planck$-like Compton parameter maps generated for THE300 clusters to validate our morphological analysis. These clusters, in fact, are properly classified for their dynamical state with the relaxation parameter, $\chi$, by exploiting 3D information from simulations. We find a mild linear correlation of $\sim 38\%$ between $\mathcal{C}$ and $\chi$ for THE300 clusters, mainly affected by the noise present in the maps. In order to obtain a proper dynamical-state classification for the $Planck$ clusters, we exploit the conversion from the $\mathcal{C}$ parameter derived in each $Planck$ map in $\chi$. A fraction of the order of $63\%$ of relaxed clusters is estimated in the selected $Planck$ sample. Our classification is then compared with those of previous works that have attempted to evaluate, with different indicators and/or other wavelengths, the dynamical state of the same $Planck$ objects. The agreement with the other works is larger than $58\%$., Comment: 15 pages, 7 figures, 2 tables. Submitted to A&A

Recently, NIRSpec PRISM/CLEAR observations by JWST have begun providing rest-frame UV continuum measurements of galaxies at $z\gtrsim7$, revealing signatures of Ly$\alpha$ damping-wing (DW) absorption by the intergalactic medium (IGM). We develop a methodology to constrain the global ionization fraction of the IGM $(Q_{\rm HII})$ using low-resolution spectra, employing the random forest classification (RFC) method. We construct mock spectra using the simulated galaxies and the IGM from the Cosmic Dawn II simulation and train RFC models to estimate $Q_{\rm HII}$ at the redshift of the source and to detect the presence of a damped Ly$\alpha$ absorber (DLA). We find that individual galaxy spectra with spectral bins between 1220 and 1270 {\AA} and with signal-to-noise ratios greater than 20 can place tight constraints on $Q_{\rm HII}$, provided the UV continuum is accurately modeled. This method is particularly effective for the early phase of reionization ($Q_{\rm HII}<50\%$), when the IGM opacity is high in the DW. As a demonstration, we apply our model to existing NIRSpec PRISM/CLEAR spectra, placing upper bounds of $Q_{\rm HII}=59.6\%$, $5.6\%$, and $18.5\%$ at $z=7.7,~9.4,$ and $10.6$, respectively, with $68\%$ confidence, though several modeling uncertainties remain to be discussed. These constraints favor late-starting reionization models, where $\gtrsim 80\%$ of the IGM is ionized after $z=8$. We conclude that high SNR observations of carefully selected targets around $z\sim7-9$ can effectively constrain reionization models., Comment: 20 pages, 11 figures, submitted to ApJ

Over 90% of dark matter haloes in cosmological simulations are unresolved. This hinders the dynamic range of simulations and also produces systematic biases when modelling cosmological tracers. Current methods cannot accurately preserve the multi-dimensional assembly bias found in simulations. Here we aim to enhance the unresolved structural and dynamic properties of haloes. We have developed HALOSCOPE, a machine learning technique using multi-variate conditional probability distribution functions given the input from haloes' local environment. In this work, we use HALOSCOPE to enhance the properties (concentration, spin and two shape parameters) of unresolved dark matter haloes in a low-resolution simulation. The algorithm trained on a high-resolution simulation allows to recover the multi-dimensional halo assembly bias, i.e. the correlations of different combinations of halo properties with the large-scale environment, in addition to the mean and distribution of the halo properties. This is achieved by including the linear halo-by-halo bias and tidal anisotropy in the set of input training parameters. We also study how the halo assembly bias produces galaxy assembly bias and how resolution effects can propagate errors into galaxy clustering. For this purpose, we have generated catalogues of central galaxies using two implementations of the assembly bias in a halo occupation distribution model. The clustering of central model galaxies is improved by a factor of three at $0.009

Hydrodynamical simulations play a fundamental role in modern cosmological research, serving as a crucial bridge between theoretical predictions and observational data. However, due to their computational intensity, these simulations are currently constrained to relatively small volumes. Therefore, this study investigates the feasibility of utilising dark matter-only simulations to generate observable maps of galaxy clusters using a deep learning approach based on the U-Net architecture. We focus on reconstructing Compton-y parameter maps (SZ maps) and bolometric X-ray surface brightness maps (X-ray maps) from total mass density maps. We leverage data from \textsc{The Three Hundred} simulations, selecting galaxy clusters ranging in mass from $10^{13.5} h^{-1}M_{\odot}\leq M_{200} \leq 10^{15.5} h^{-1}M_{\odot}$. Despite the machine learning models being independent of baryonic matter assumptions, a notable limitation is their dependency on the underlying physics of hydrodynamical simulations. To evaluate the reliability of our generated observable maps, we employ various metrics and compare the observable-mass scaling relations. For clusters with masses greater than $2 \times 10^{14} h^{-1} M_{\odot}$, the predictions show excellent agreement with the ground-truth datasets, with percentage errors averaging (0.5 $\pm$ 0.1)\% for the parameters of the scaling laws., Comment: 16 pages, 13 Figures, comments are welcome. Submitted to RASTI

The James Webb Space Telescope (JWST) has uncovered an abundance of $z>10$ galaxies bright in the ultraviolet (UV) that has challenged traditional theoretical models at high redshifts. Recently, various new models have emerged to address this discrepancy by refining their description of star formation. Here we investigate whether modifications to the stellar initial mass function (IMF) alone can reproduce the $z>10$ UV luminosity functions (UV LFs) when the star formation rate is used as a proxy for the fraction of massive stars. We incorporate an Evolving IMF into the {\sc astraeus} galaxy evolution and reionisation simulation framework, which becomes increasingly top-heavy as the gas density in a galaxy rises above a given threshold. Our implementation accounts for the IMF's effects on supernova (SN) feedback, metal enrichment, and the UV and ionising emissivities. For this Evolving IMF model, we find that (i) the maximum UV luminosity enhancement is twice as large in massive galaxies ($\Delta M_\mathrm{UV}\simeq2.6$) than those where star formation is strongly limited by SN feedback ($\Delta M_\mathrm{UV}\simeq1.3$); (ii) it successfully reproduces the observed UV LFs at $z=5-15$; (iii) galaxies with top-heavy IMFs exhibit the highest star formation rates, driven by their location in local density peaks, which facilitates higher gas accretion rates; (iv) the $1\sigma$ variances in the UV luminosity are only slightly higher compared to when assuming a Salpeter IMF, but the $2\sigma$ variances are significantly increased by a factor of $1.4-2$ boosting the abundance of UV-bright galaxies at $z>10$; (v) reionisation begins earlier with more extended large ionised regions and fewer smaller ones during its initial stages, though these differences diminish at lower redshifts, leading to a similar end of reionisation at $z\simeq5.6$.}, Comment: 13 pages, 8 figures. Accepted for publication in A&A

Galaxy cluster mergers are believed to generate large-scale shock waves that are ideal sites for electron acceleration. We compute radio emission light curves for galaxy group and cluster mergers simulated in a cosmological context to study the dependence of radio luminosity on cluster mass, redshift, and impact parameter. We used model galaxy clusters from The Three Hundred project to identify cluster mergers characterised by the two main merging structures and follow their evolution throughout the simulated cosmic history. We found that the median non-thermal radio relic luminosity light curve produced in galaxy cluster mergers can be described by a skewed Gaussian function abruptly rising after core-passage of the secondary cluster that peaks after $\sim0.1-0.8\,$Gyr as a function of $M_{200,1}$, the mass of the primary, displaying a mass-dependent luminosity output increase of $\lesssim10$ to about $\gtrsim10-50$ times relative to the radio emission measured at core-passage for galaxy groups and clusters, respectively. In general, most merger orbits are fairly radial with a median opening angle of $\sim20^{\circ}$ before the collision. We also found that, independent of the cluster mass, less radial mergers tend to last longer, although the trend is weak. Finally, we found that the peak radio luminosity shows a significant correlation with mass, $P_{1.4}\propto M_{200,1}^{2.05}$, demonstrating that this relation holds all the way up from galaxy group scales to the most massive galaxy clusters. We conclude that cluster mass is the primary driver for radio `gischt' median luminosity, although there are significant variations for a given cluster mass. Our simulations suggest that the shock-driven, non-thermal radio emission observed on cluster outskirts are the result of massive galaxy cluster mergers at $z\lesssim1$, peaking at $z\sim0-0.5$., Comment: 15 pages, 10 figures. Accepted for publication in A&A

We investigate the spatial offsets between dust and ultraviolet (UV) emission in high-redshift galaxies using the Cosmic Dawn III (CoDa III) simulation, a state-of-the-art fully coupled radiation-hydrodynamics cosmological simulation. Recent observations have revealed puzzling spatial disparities between ALMA dust continuum and UV emission as seen by HST and JWST in galaxies at z=5-7, compelling us to propose a physical interpretation of such offsets. Our simulation, which incorporates a dynamical dust model, naturally reproduces these offsets in massive, UV-bright galaxies (log$_{10}$(M$_{\rm{DM}}$/M$_{\odot}$)>11.5, M$_{\rm{AB1500}}$<-20). We find that dust-UV offsets increase with halo mass and UV brightness, reaching up to $\sim 2$ pkpc for the most massive systems, in good agreement with observational data from the ALPINE and REBELS surveys. Our analysis reveals that these offsets primarily result from severe dust extinction in galactic centers rather than a misalignment between dust and stellar mass distributions. The dust remains well-aligned with the bulk stellar component, and we predict the dust continuum should therefore align well with the stellar rest-frame NIR component, less affected by dust attenuation. This study provides crucial insights into the complex interplay between star formation, dust distribution, and observed galaxy morphologies during the epoch of reionization, highlighting the importance of dust in shaping the appearance of early galaxies at UV wavelengths., Comment: 9 pages, 5 figures, submitted to A&A

The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard $\Lambda$-cold-dark-matter ($\Lambda$CDM) paradigm and in many non-standard models beyond $\Lambda$CDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard $\Lambda$CDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid., Comment: 22 pages, 7 figures

In Sunyaev-Zeldovich (SZ) cluster cosmology, two tools are needed to be able to exploit data from large scale surveys in the millimeter-wave domain. An accurate description of the IntraCluster Medium (ICM) pressure profile is needed along with the scaling relation connecting the SZ brightness to the mass. With its high angular resolution and large field of view, The NIKA2 camera, operating at 150 and 260 GHz, is perfectly suited for precise cluster SZ mapping. The SZ Large Program (LPSZ) of the NIKA2 collaboration is dedicated to the observation of a sample of 38 SZ-selected clusters at intermediate to high redshift and observed both in SZ and X-ray. The current status is that all LPSZ clusters have been observed and the analysis toward the final results is ongoing. We present in detail how NIKA2-LPSZ will obtain a robust estimation of the SZ-Mass scaling relation and how it will be used to obtain cosmological constraints., Comment: 4 pages, 3 figures, contribution to the 2024 Cosmology session of the 58th Rencontres de Moriond

This paper focuses on the educational journey of a computer engineering undergraduate student venturing into the domain of computer vision and robotics. It explores how optical flow and its applications can be used to detect moving objects when a camera undergoes translational motion, highlighting the challenges encountered and the strategies used to overcome them. Furthermore, the paper discusses not only the technical skills acquired by the student but also interpersonal skills as related to teamwork and diversity. In this paper, we detail the learning process, including the acquisition of technical and problem-solving skills, as well as out-of-the-box thinking., Comment: 20 Pages

In this article, we consider the propagation of QED fermions in the presence of a classical background magnetic field with white-noise stochastic fluctuations. The effects of the magnetic field fluctuations are incorporated into the fermion and photon propagators in a quasi-particle picture, which we developed in previous works using the {\it replica trick}. By considering the strong-field limit, here we explicitly calculate the fermion self-energy involving radiative contributions at first-order in $\alpha_\text{em}$, in order to obtain the noise-averaged mass of the fermion propagating in the fluctuating magnetized medium. Our analytical results reveal a leading double-logarithmic contribution $\sim \left[\ln \left( |e B|/m^2 \right)\right]^2$ to the mass, with an imaginary part representing a spectral broadening proportional to the magnetic noise auto-correlation $\Delta$. While a uniform magnetic field already breaks Lorentz invariance, inducing the usual separation into two orthogonal subspaces (perpendicular and parallel with respect to the field), the presence of magnetic noise further breaks the remaining symmetry, thus leading to distinct spectral widths associated with fermion and anti-fermion, and their spin projection in the quasi-particle picture., Comment: 6 pages (main text), 14 pages (with appendix), 6 figures

Galaxy clusters are located in the densest areas of the universe and are intricately connected to larger structures through the filamentary network of the Cosmic Web. In this scenario, matter flows from areas of lower density to higher density. As a result, the properties of galaxy clusters are deeply influenced by the filaments that are attached to them, which are quantified by a parameter known as connectivity. We explore the dependence of gas-traced filaments connected to galaxy clusters on the mass and dynamical state of the cluster. Moreover, we evaluate the effectiveness of the cosmic web extraction procedure from the gas density maps of simulated cluster regions. Using the DisPerSE cosmic web finder, we identify filamentary structures from 3D gas particle distribution in 324 simulated regions of $30 \, h^{-1}$ Mpc side from The Three Hundred hydrodynamical simulation at redshifts z=0, 1, and 2. We estimate the connectivity at various apertures for $\sim3000$ groups and clusters spanning a mass range from $10^{13} \, h^{-1} \, M_{\odot}$ to $10^{15} \, h^{-1} \, M_{\odot}$. Relationships between connectivity and cluster properties like radius, mass, dynamical state and hydrostatic mass bias are explored. We show that the connectivity is strongly correlated with the mass of galaxy clusters, with more massive clusters being on average more connected. This finding aligns with previous studies in literature, both from observational and simulated data sets. Additionally, we observe a dependence of the connectivity on the aperture at which it is estimated. We find that connectivity decreases with cosmic time, while no dependencies on the dynamical state and hydrostatic mass bias of the cluster are found. Lastly, we observe a significant agreement between the connectivity measured from gas-traced and mock-galaxies-traced filaments in the simulation., Comment: 12 pages, 11 figures Accepted for publication in A&A on 28/10/2024. Reproduced with permission from Astronomy & Astrophysics, copyright ESO

A classical inequality by Gr\"unbaum provides a sharp lower bound for the ratio $\mathrm{vol}(K^{-})/\mathrm{vol}(K)$, where $K^{-}$ denotes the intersection of a convex body with non-empty interior $K\subset\mathbb{R}^n$ with a halfspace bounded by a hyperplane $H$ passing through the centroid $\mathrm{g}(K)$ of $K$. In this paper we extend this result to the case in which the hyperplane $H$ passes by any of the points lying in a whole uniparametric family of $r$-powered centroids associated to $K$ (depending on a real parameter $r\geq0$), by proving a more general functional result on concave functions. The latter result further connects (and allows one to recover) various inequalities involving the centroid, such as a classical inequality (due to Minkowski and Radon) that relates the distance of $\mathrm{g}(K)$ to a supporting hyperplane of $K$, or a result for volume sections of convex bodies proven independently by Makai Jr. & Martini and Fradelizi.

Galaxy clusters are composed of dark matter, gas and stars. Their dark matter component, which amounts to around 80\% of the total mass, cannot be directly observed but traced by the distribution of diffused gas and galaxy members. In this work, we aim to infer the cluster's projected total mass distribution from mock observational data, i.e. stars, Sunyaev-Zeldovich, and X-ray, by training deep learning models. To this end, we have created a multiview images dataset from {\sc{The Three Hundred}} simulation that is optimal for training Machine Learning models. We further study deep learning architectures based on the U-Net to account for single-input and multi-input models. We show that the predicted mass distribution agrees well with the true one., Comment: To appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

Gamma-ray bursts are promising candidate sources of high-energy astrophysical neutrinos. The recent GRB 221009A event, identified as the brightest gamma-ray burst ever detected, provides a unique opportunity to investigate hadronic emissions involving neutrinos. The KM3NeT undersea neutrino detectors participated in the worldwide follow-up effort triggered by the event, searching for neutrino events. In this letter, we summarize subsequent searches, in a wide energy range from MeV up to a few PeVs. No neutrino events are found in any of the searches performed. Upper limits on the neutrino emission associated with GRB 221009A are computed., Comment: 11 pages, 2 PDF figures. Submitted to JCAP

The abundance of galaxy clusters with mass and redshift is a well-known cosmological probe. The cluster mass is a key parameter for studies that aim to constrain cosmological parameters using galaxy clusters, making it critical to understand and properly account for the errors in its estimates. Subsequently, it becomes important to correctly calibrate scaling relations between observables like the integrated Compton parameter and the mass of the cluster. The NIKA2 Sunyaev-Zeldovich Large program (LPSZ) enables one to map the intracluster medium profiles in the mm-wavelength band with great details (resolution of $11 \ \mathrm{\&}\ 17^{\prime \prime}$ at $1.2 \ \mathrm{\&}\ 2 $ mm, respectively) and hence, to estimate the cluster hydrostatic mass more precisely than previous SZ observations. However, there are certain systematic effects which can only be accounted for with the use of simulations. For this purpose, we employ THE THREE HUNDRED simulations which have been modelled with a range of physics modules to simulate galaxy clusters. The so-called twin samples are constructed by picking synthetic clusters of galaxies with properties close to the observational targets of the LPSZ. In particular, we use the Compton parameter maps and projected total mass maps of these twin samples along 29 different lines of sight. We investigate the scatter that projection induces on the total masses. Eventually, we consider the statistical values along different lines of sight to construct a kind of 3D scaling law between the integrated Compton parameter, total mass, and overdensity of the galaxy clusters to determine the overdensity that is least impacted by the projection effect., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

The KM3NeT/ARCA neutrino detector is currently under construction at 3500 m depth offshore Capo Passero, Sicily, in the Mediterranean Sea. The main science objectives are the detection of high-energy cosmic neutrinos and the discovery of their sources. Simulations were conducted for the full KM3NeT/ARCA detector, instrumenting a volume of 1 km$^3$, to estimate the sensitivity and discovery potential to point-like neutrino sources and an all-sky diffuse neutrino flux. This paper covers the reconstruction of track- and shower-like signatures, as well as the criteria employed for neutrino event selection. By leveraging both the track and shower observation channels, the KM3NeT/ARCA detector demonstrates the capability to detect the diffuse astrophysical neutrino flux within half a year of operation, achieving a 5$\sigma$ statistical significance. With an angular resolution below 0.1$^\circ$ for tracks and under 2$^\circ$ for showers, the sensitivity to point-like neutrino sources surpasses existing observed limits across the entire sky., Comment: 20 pages, 30 figures, Published by EPJ-C

Chunking information is a key step in Retrieval Augmented Generation (RAG). Current research primarily centers on paragraph-level chunking. This approach treats all texts as equal and neglects the information contained in the structure of documents. We propose an expanded approach to chunk documents by moving beyond mere paragraph-level chunking to chunk primary by structural element components of documents. Dissecting documents into these constituent elements creates a new way to chunk documents that yields the best chunk size without tuning. We introduce a novel framework that evaluates how chunking based on element types annotated by document understanding models contributes to the overall context and accuracy of the information retrieved. We also demonstrate how this approach impacts RAG assisted Question & Answer task performance. Our research includes a comprehensive analysis of various element types, their role in effective information retrieval, and the impact they have on the quality of RAG outputs. Findings support that element type based chunking largely improve RAG results on financial reporting. Through this research, we are also able to answer how to uncover highly accurate RAG.

In this work, we calculate the one-loop contribution to the polarization tensor for photons (and gluons) in the presence of a classical background magnetic field with white-noise stochastic fluctuations. The magnetic field fluctuations are incorporated into the fermion propagator in a quasi-particle picture, which we developed in previous works using the {\it replica trick}. By focusing on the strong-field limit, here we explicitly calculate the polarization tensor. Our results reveal that it does not satisfy the transversality conditions outlined by the Ward identity, thus breaking the $U(1)$ symmetry. As a consequence, in the limit of vanishing photon four-momenta, the tensor coefficients indicate the emergence of an effective magnetic mass induced on photons (and gluons) by these stochastic fluctuations, leading to the interpretation of a dispersive medium with a noise-dependent index of refraction., Comment: 18 pages, 5 figures

In this work, we study the effects of random temperature fluctuations on the equation of state of a non-interacting, relativistic fermion gas by means of the replica method. This picture provides a conceptual model for a non-equilibrium system, depicted as an ensemble of subsystems at different temperatures, randomly distributed with respect to a given mean value. We then assume the temperature displays stochastic fluctuations $T = T_0 + \delta T$ with respect to its ensemble average value $T_0$, with zero mean $\overline{\delta T} = 0$ and standard deviation $\overline{\delta T^2} = \Delta$. By means of the replica method, we obtain the average grand canonical potential, leading to the equation of state of the fermion gas expressed in terms of the excess pressure caused by these fluctuations with respect to the ideal gas at uniform temperature. We further extend our results for the ideal Bose gas as well. Our findings reveal an increase in pressure as the system's ensemble average temperature $T_0$ rises, consistently exceeding the pressure observed in an equilibrium state. Finally, we explore the implications for the deconfinement transition in the context of the simple Bag model, where we show that the critical temperature decreases., Comment: 9 pages, 3 figures

Emission line galaxies (ELGs) are targeted by the new generation of spectroscopic surveys to make unprecedented measurements in cosmology from their distribution. Accurately interpreting this data requires understanding the imprints imposed by the physics of galaxy formation and evolution on galaxy clustering. In this work we utilize a semi-analytical model of galaxy formation (SAGE) to explore the necessary components for accurately reproducing the clustering of ELGs. We focus on developing a Halo Occupation Distribution (HOD) prescription able to reproduce the clustering of SAGE galaxies. Typically, HOD models assume that satellite and central galaxies of a given type are independent events. We investigate the need for conformity, i.e. whether the average satellite occupation depends on the existence of a central galaxy of a given type. Incorporating conformity into HOD models is crucial for reproducing the clustering in the reference galaxy sample. Another aspect we investigate is the radial distribution of satellite galaxies within haloes. The traditional density profile models, NFW and Einasto profiles, fail to accurately replicate the small-scale clustering measured for SAGE satellite galaxies. To overcome this limitation, we propose a generalization of the NFW profile, thereby enhancing our understanding of galaxy clustering., Comment: 17 pages, 12 figures and 5 tables

We present the largest full N-body simulation to date with local primordial non-Gaussianities (L-PNG), the \textsc{PNG-UNITsim}. It tracks the evolution of $4096^3$ particles within a periodic box with $L_{\rm box} = 1 \; h^{-1}\,{\rm Gpc}$, leading to a mass resolution of $m_{p} = 1.24\times 10^{9}\; h^{-1}\,M_\odot$. This is enough to resolve galaxies targeted by stage-IV spectroscopic surveys. The \textsc{PNG-UNIT} has \textit{Fixed} initial conditions whose phases are also \textit{Matched} to the pre-existing \textsc{UNIT} simulation. These two features in the simulations reduce our uncertainty significantly so we use 100 \textsc{FastPM} mocks to estimate this reduction. The amplitude of the non-Gaussianities used to set the initial conditions of this new simulation is $f_{\rm NL}^{\rm local} = 100$. In this first study, we use mass selected dark matter haloes from the \textsc{PNG-UNIT} simulation to constrain the local PNG parameters. PNG induce a scale dependent bias, parameterised through \bp or $p$, which might depend on the type of cosmological tracer. Those cases when $p=1$ are referred to as the {\it universality relation}. We measure $p$ as a function of the halo mass. Haloes with masses between $1\times 10^{12}$ and $2\times 10^{13} \, h^{-1} M_\odot$ are well described by the {\it universality relation}. For haloes with masses between $2\times 10^{10}$ and $1\times 10^{12} \, h^{-1} M_\odot$ we find that $p<1$ at $3\sigma$. Combining all the mass bins, we find $p$ consistent with a value of $0.955\pm0.013$, which is $3\sigma$ away from \textit{universality}, as low mass haloes are more numerous. We also study the effect of using priors on $p$ when constraining $f_{\rm NL}$. Using the values we obtain for $b_\phi$ as priors, we forecast that a DESI-like (stage-IV) survey will be able to constrain $f_{\rm NL}$ better than if the universality relation is assumed., Comment: 19 pages, 11 figures. Accepted for publication in A&A

Observations with JWST have revealed an unexpected high abundance of bright z>10 galaxy candidates. We explore whether a stellar initial mass function (IMF) that becomes increasingly top-heavy towards higher redshifts and lower gas-phase metallicities results in a higher abundance of bright objects in the early universe and how it affects the evolution of galaxy properties compared to a constant IMF. We incorporate such an evolving IMF into the Astraeus framework that couples galaxy evolution and reionisation in the first billion years. Our implementation accounts for the IMF dependence of supernova feedback, metal enrichment, ionising and ultraviolet radiation emission. We conduct two simulations: one with a Salpeter IMF and one with the evolving IMF. Compared to a constant Salpeter IMF, we find that (i) the higher abundance of massive stars in the evolving IMF results in more light per unit stellar mass, a slower build-up of stellar mass and lower stellar-to-halo mass ratio; (ii) due to the self-similar growth of the underlying dark matter halos, the evolving IMF's star formation main sequence hardly deviates from that of the Salpeter IMF; (iii) the evolving IMF's stellar mass-metallicity relation shifts to higher metallicities while its halo mass-metallicity relation remains unchanged; (iv) the evolving IMF's median dust-to-metal mass ratio is lower due to its stronger SN feedback; (v) the evolving IMF requires lower values of the escape fraction of ionising photons and exhibits a flatter median relation and smaller scatter between the ionising photons emerging from galaxies and the halo mass. Yet, the topology of the ionised regions hardly changes compared to the Salpeter IMF. These results suggest that a top-heavier IMF alone is unlikely to explain the higher abundance of bright z>10 sources, since the lower mass-to-light ratio is counteracted by the stronger stellar feedback., Comment: 19 pages, 13 figures, Accepted for publication in Astronomy & Astrophysics

An accurate reconstruction of galaxy cluster masses is key to use this population of objects as a cosmological probe. In this work we present a study on the hydrostatic-to-lensing mass scaling relation for a sample of 53 clusters whose masses were reconstructed homogeneously in a redshift range between $z= 0.05$ and $1.07$. The $M_{500}$ mass for each cluster was indeed inferred from the mass profiles extracted from the X-ray and lensing data, without using a priori observable-mass scaling relations. We assessed the systematic dispersion of the masses estimated with our reference analyses with respect to other published mass estimates. Accounting for this systematic scatter does not change our main results, but enables the propagation of the uncertainties related to the mass reconstruction method or used dataset. Our analysis gives a hydrostatic-to-lensing mass bias of $(1-b) =0.739^{+0.075}_{-0.070}$ and no evidence of evolution with redshift. These results are robust against possible subsample differences.