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We present measurements of the gas-phase Oxygen and Nitrogen abundances obtained by applying the direct method to JWST NIRspec $R\sim1000$ spectroscopy for 6 galaxies at redshift greater than 3. Our measurements are based on rest-frame optical Nitrogen [N II]$_{\lambda\lambda6548,6583}$ lines and are complemented by 6 additional objects from the literature at $3\leq z \leq 6$. We find that 9 out of 12 objects have values of log(N/O) that are compatible with those found for low-redshift, metal-poor, dwarf galaxies and for HII regions of more luminous local galaxies. However, 3 out of 12 objects have log(N/O) values that are overabundant compared to what is expected on the basis of their Oxygen abundance. We explore a few standard scenarios to explain the observations and conclude that, within the limited statistics available to us, none of them can be definitely excluded even though we prefer dilution by pristine gas infall in between star formation bursts as this is predicted by simulations to take place as a natural part of bursty star formation., Comment: Submitted to ApJ

This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

We discuss the low-energy properties of binary superfluids with density-dependent interactions. Adding an intra-species coupling that induces an explicit soft symmetry-breaking, we determine the background pressure and we show that the low-energy spectrum consists of a massless Nambu- Goldstone boson and a massive (pseudo) Nambu-Goldstone boson. When the background velocities of the two superfluids are transonic, the system is characterized by two distinct acoustic horizons: the hydrodynamic analogue of the black hole event horizon. The Hawking-like emission occurring at these horizons produces an effective friction on the fluids. We compute the viscosity-to-entropy ratios close to the two acoustic horizons, finding that the emission of pseudo Nambu-Goldstone bosons violates the bound conjectured by Kovtun, Son and Starinet., Comment: 20 pages

Low-energy (<300 keV) protons entering the field of view of XMM-Newton are observed in the form of a sudden increase in the background level, the so-called soft proton flares, affecting up to 40% of the mission observing time. In-flight XMM-Newton's observations of soft protons represent a unique laboratory to validate and improve our understanding of their interaction with the mirror, optical filters, and X-ray instruments. At the same time, such models would link the observed background flares to the primary proton population encountered by the telescope, converting XMM-Newton into a monitor for soft protons. We built a Geant4 simulation of XMM-Newton, including a verified mass model of the X-ray mirror, the focal plane assembly, and the EPIC MOS and pn-CCDs. We encoded the energy redistribution and proton transmission efficiency into a redistribution matrix file (RMF) and an auxiliary response file (ARF). For the validation, three averaged soft proton spectra, one for each filter configuration, were extracted from a collection of 13 years of MOS observations of the focused non X-ray background and analysed with Xspec. The best-fit model is in agreement with the power-law distribution predicted from independent measurements for the XMM-Newton orbit, spent mostly in the magnetosheath and nearby regions. For the first time we are able to link detected soft proton flares with the proton radiation environment in the Earth's magnetosphere, while proving the validity of the simulation chain in predicting the background of future missions. Benefiting from this work and contributions from the Athena instrument consortia, we also present the response files for the Athena mission and updated estimates for its focused charged background.

Effective fall risk assessment is critical for post-stroke patients. The present study proposes a novel, data-informed fall risk assessment method based on the instrumented Timed Up and Go (ITUG) test data, bringing in many mobility measures that traditional clinical scales fail to capture. IFRA, which stands for Instrumented Fall Risk Assessment, has been developed using a two-step process: first, features with the highest predictive power among those collected in a ITUG test have been identified using machine learning techniques; then, a strategy is proposed to stratify patients into low, medium, or high-risk strata. The dataset used in our analysis consists of 142 participants, out of which 93 were used for training (15 synthetically generated), 17 for validation and 32 to test the resulting IFRA scale (22 non-fallers and 10 fallers). Features considered in the IFRA scale include gait speed, vertical acceleration during sit-to-walk transition, and turning angular velocity, which align well with established literature on the risk of fall in neurological patients. In a comparison with traditional clinical scales such as the traditional Timed Up & Go and the Mini-BESTest, IFRA demonstrates competitive performance, being the only scale to correctly assign more than half of the fallers to the high-risk stratum (Fischer's Exact test p = 0.004). Despite the dataset's limited size, this is the first proof-of-concept study to pave the way for future evidence regarding the use of IFRA tool for continuous patient monitoring and fall prevention both in clinical stroke rehabilitation and at home post-discharge., Comment: 26 pages, 2 figures, submitted for review dec 2024

Observations of massive supermassive black holes (SMBHs) in the early universe challenge existing black hole formation models. We propose that soliton cores in fuzzy dark matter (FDM) offer a potential solution to this timing problem. Our FDM cosmological zoom-in simulations confirm that for a particle mass $m_{\rm FDM}\sim 10^{-22}~{\rm eV}$, solitons are well developed at redshift $z \sim 7$ with masses of $\sim10^9~M_\odot$, comparable to the observed SMBHs. We then demonstrate using hydrodynamic simulations that, compared to cold dark matter, these high-$z$ massive FDM solitons with mass $M_s$ can provide additional gravitational potential to accrete gas and boost the Bondi accretion rate of a growing black hole seed with mass $M_{\rm BH}$ by up to two to four orders of magnitude, in the regime of efficient cooling and negligible radiation pressure. This accretion boosting mechanism is effective for $10^{-22}~{\rm eV} \lesssim m_{\rm FDM} \lesssim 10^{-20}~{\rm eV}$ and potentially beyond as long as $M_s > M_{\rm BH}$. The simulation code GAMER is accessible at https://github.com/gamer-project/gamer., Comment: 9 pages, 4 figures, 1 table. Accepted for publication in Physical Review Letters

The James Webb Space Telescope, launched in 2021, is an infrared observatory of novel design: deployable, with active optics, fully open to space for radiative cooling and orbiting the Lagrange point no. 2. This article explains the rationale leading to this specific design and describes the various other architectures that were considered along the way: from a monolithic 10-meter telescope in geosynchronous orbit to a 6-meter one in High Earth Orbit, then a 16-meter observatory on the Moon, a 4- or 6-meter one in an elliptical heliocentric orbit, and a segmented 8-meter one passively cooled to 50 K at L2, which was finally descoped to 6.6 meters. It also addresses the optimization for scientific performance, the challenge of dealing with such an ultra-low operating temperature, cost issues, supporting technology, modifications made during final design and, finally, how the architecture performs on orbit., Comment: 36 pages, 37 figures, submitted to Journal of Astronomical Telescopes, Instruments and Systems (JATIS)

We present integral field unit observations of the Phoenix Cluster with the JWST Mid-infrared Instrument's Medium Resolution Spectrometer (MIRI/MRS). We focus this study on the molecular gas, dust, and star formation in the brightest cluster galaxy (BCG). We use precise spectral modeling to produce maps of the silicate dust, molecular gas, and polycyclic aromatic hydrocarbons (PAHs) in the inner $\sim$50 kpc of the cluster. We have developed a novel method for measuring the optical depth from silicates by comparing the observed H$_2$ line ratios to those predicted by excitation models. We provide updated measurements of the total molecular gas mass of $2.2^{+0.4}_{-0.1} \times 10^{10}$ ${\rm M}_\odot$, which agrees with CO-based estimates, providing an estimate of the CO-to-H$_2$ conversion factor of $\alpha_{\rm CO} = 0.9 \pm 0.2\,{\rm M}_{\odot}\,{\rm pc}^{-2}\,({\rm K}\,{\rm km}\,{\rm s}^{-1})^{-1}$; an updated stellar mass of $M_* = 2.6 \pm 0.5 \times 10^{10}$ ${\rm M}_\odot$; and star formation rates averaged over 10 and 100 Myr of $\langle{\rm SFR}\rangle_{\rm 10} = 1340 \pm 100$ ${\rm M}_\odot\,{\rm yr}^{-1}$ and $\langle{\rm SFR}\rangle_{\rm 100} = 740 \pm 80$ ${\rm M}_\odot\,{\rm yr}^{-1}$, respectively. The H$_2$ emission seems to be powered predominantly by star formation within the central $\sim 20$ kpc, with no need for an extra particle heating component as is seen in other BCGs. Additionally, we find nearly an order of magnitude drop in the star formation rates estimated by PAH fluxes in cool core BCGs compared to field galaxies, suggesting that hot particles from the intracluster medium are destroying PAH grains even in the centralmost 10s of kpc., Comment: 21 pages, 13 figures, 2 tables. Submitted to ApJ. Comments welcome!

As the lynchpin of all quantum correlations, quantum coherence is fundamental for distinguishing quantum systems from classical ones and is essential for realizing quantum advantages in areas such as computation, communication, and metrology. In this study, we investigate the relationship between quantum coherence and neutrino oscillations by mapping the neutrino state as a multi-mode quantum system into qubit and qutrit frameworks. Our analysis extends beyond the commonly used $l_1$-norm and relative entropy of coherence to include all relevant measures of coherence such as robustness of coherence, coherence concurrence, trace-norm distance measure of coherence, coherence of formation, Schatten-$p$-norm-based functionals, geometric coherence and logarithmic coherence rank, each offering unique insights into the quantum correlations in these systems. Notably, while the $l_1$-norm and relative entropy-based measures apply to general quantum states, the other measures are particularly relevant for entangled systems, highlighting the critical role of entanglement in neutrino oscillations. We present a detailed methodology for calculating coherence measures in both two-flavor and three-flavor mixing scenarios, contributing to a deeper understanding of how quantum coherence manifests and evolves in mode-entangled neutrino systems. Our findings emphasize the potential of these systems as robust candidates for quantum information tasks, facilitated by the weak interaction nature of neutrinos., Comment: 39 pages, 6 figures

We performed a detailed spectroscopic analysis of three extremely metal-poor RR Lyrae stars, exploring uncharted territories at these low metallicities for this class of stars. Using high-resolution spectra acquired with HARPS-N at TNG, UVES at VLT, and PEPSI at LBT, and employing Non-Local Thermodynamic Equilibrium (NLTE) spectral synthesis calculations, we provide abundance measurements for Fe, Al, Mg, Ca, Ti, Mn, and Sr. Our findings indicate that the stars have metallicities of [Fe/H] = -3.40 \pm 0.05, -3.28 \pm 0.02, and -2.77 \pm 0.05 for HD 331986, DO Hya, and BPS CS 30317-056, respectively. Additionally, we derived their kinematic and dynamical properties to gain insights into their origins. Interestingly, the kinematics of one star (HD 331986) is consistent with the Galactic disc, while the others exhibit Galactic halo kinematics, albeit with distinct chemical signatures. We compared the [Al/Fe] and [Mg/Mn] ratios of the current targets with recent literature estimates to determine whether these stars were either accreted or formed in situ, finding that the adopted chemical diagnostics are ineffective at low metallicities ([Fe/H] $\lesssim -$1.5). Finally, the established horizontal branch evolutionary models, indicating that these stars arrive at hotter temperatures on the Zero-Age Horizontal Branch (ZAHB) and then transition into RR Lyrae stars as they evolve, fully support the existence of such low-metallicity RR Lyrae stars. As a consequence, we can anticipate detecting more of them when larger samples of spectra become available from upcoming extensive observational campaigns., Comment: Accepted for publication in Astronomy & Astrophysics; 13 pages. Appendices D-E available on Zenodo

Thermally-driven semi-crystalline polymer networks are capable to achieve both the one-way shape-memory effect and two-way shape-memory effect under stress and stress-free conditions, therefore representing an appealing class of polymers for applications requiring autonomous reversible actuation and shape changes. In these materials, the shape-memory effects are achieved by leveraging the synergistic interaction between one or more crystalline phases and the surrounding amorphous ones that are present within the network itself. The present paper introduces a general framework for the finite strain continuum phenomenological modeling of the thermo-mechanical and shape-memory behavior of multi-phase semi-crystalline polymer networks. Model formulation, including the definition of phase and control variables, kinematic assumptions, and constitutive specifications, is introduced and thoroughly discussed. Theoretical derivations are general and easily adaptable to all cross-linked systems which include two or more crystalline domains or a single crystalline phase with a wide melting range and manifest macroscopically the one-way shape-memory effect and the two-way shape-memory effect under stress and stress-free conditions. Model capabilities are validated against experimental data for copolymer networks with two different crystalline phases characterized by well-separated melting and crystallization transitions. Results demonstrate the accuracy of the proposed model in predicting all the phenomena involved and in furnishing a useful support for future material and application design purposes., Comment: This work was funded by the European Union ERC CoDe4Bio Grant ID 101039467 under the funding programme Horizon Europe

This paper aims to describe the Pointing Reconstruction Model (PRM) and the prototype Star Tracker, which will be mounted on LSPE-Strip, a microwave Q- and W-band CMB telescope planned for installation at the "Observatorio del Teide" in Tenerife. The PRM integrates information on the instantaneous attitude provided by the telescope control system to determine the actual pointing direction and focal plane orientation of the telescope. It accounts for various non-idealities in the telescope setup, represented by eight configuration angles, which will be calibrated using the Star Tracker. Following the derivation of the PRM formalism and its implementation, we investigate the pointing errors caused by incorrect calibration of these configuration angles to validate the required 1 arcminute maximum systematic pointing error for the LSPE-Strip survey. This paper also describes the main structure and operations of the Star Tracker and presents the results of a campaign of actual sky observations conducted with a prototype. The results demonstrate a Star Tracker RMS accuracy of approximately 3 arcseconds, while systematic errors remain below 10 arcseconds. Based on these results, we analyzed the problem of reconstructing the PRM configuration angles. Two methods for intercalibrating the Star Tracker's pointing direction with respect to the focal plane's pointing direction were examined: (1) observations of planets and (2) observations of a drone carrying both an optical beacon and a radio beacon. In the first case, an intercalibration accuracy between 1/3 arcminute and 1 arcminute is achievable. In the second case, the expected intercalibration accuracy ranges from 0.25 arcminute to 1 arcminute., Comment: 37 pages; 16 figures; 5 tables; the limited length of the arXiv abstract required shortening the original abstract, which is presented in its full length in the PDF; paper accepted for pubblication 2025 jan 06 in the Journal of Instrumentation (JINST)

Graph Neural Networks (GNNs) excel at learning from graph-structured data but are limited to modeling pairwise interactions, insufficient for capturing higher-order relationships present in many real-world systems. Topological Deep Learning (TDL) has allowed for systematic modeling of hierarchical higher-order interactions by relying on combinatorial topological spaces such as simplicial complexes. In parallel, Quantum Neural Networks (QNNs) have been introduced to leverage quantum mechanics for enhanced computational and learning power. In this work, we present the first Quantum Topological Deep Learning Model: Quantum Simplicial Networks (QSNs), being QNNs operating on simplicial complexes. QSNs are a stack of Quantum Simplicial Layers, which are inspired by the Ising model to encode higher-order structures into quantum states. Experiments on synthetic classification tasks show that QSNs can outperform classical simplicial TDL models in accuracy and efficiency, demonstrating the potential of combining quantum computing with TDL for processing data on combinatorial topological spaces., Comment: 35 pages, 8 tables, 6 figures

Following the recent interest in applying the Hyperdimensional Computing paradigm in medical context to power up the performance of general machine learning applied to biomedical data, this study represents the first attempt at employing such techniques to solve the problem of classification of Attention Deficit Hyperactivity Disorder using electroencephalogram signals. Making use of a spatio-temporal encoder, and leveraging the properties of HDC, the proposed model achieves an accuracy of 88.9%, outperforming traditional Deep Neural Networks benchmark models. The core of this research is not only to enhance the classification accuracy of the model but also to explore its efficiency in terms of the required training data: a critical finding of the study is the identification of the minimum number of patients needed in the training set to achieve a sufficient level of accuracy. To this end, the accuracy of our model trained with only $7$ of the $79$ patients is comparable to the one from benchmarks trained on the full dataset. This finding underscores the model's efficiency and its potential for quick and precise ADHD diagnosis in medical settings where large datasets are typically unattainable., Comment: 25 pages, 7 figures, 1 table

Polymers exhibiting the stress-free two-way shape-memory effect (SME) represent an appealing solution to achieve self-standing reversible actuation that is a fundamental feature required by numerous applications. The present paper proposes a one-dimensional continuum phenomenological framework to model single-component semi-crystalline polymer networks exhibiting both the one-way SME and the two-way SME under stress and stress-free conditions. A comprehensive experimental campaign is first performed on semi-crystalline networks based on poly($\varepsilon$-caprolactone) (PCL) to characterize the mechanical and thermal properties as well as the one-way and two-way shape memory behavior of the material under different thermo-mechanical conditions. The results guide the formulation of the model, elucidating the selection of the control and phase variables and motivating the choice of their evolution laws. Model capabilities are then demonstrated against experimental data. All the phenomena that influence the stress-free two-way SME, including the actuation temperature, heating/cooling rates, applied stress/strain, and the amount of skeleton and actuation phase, are analyzed and discussed, giving new important insight for application development., Comment: This work was funded by the European Union ERC CoDe4Bio Grant ID 101039467 under the funding programme Horizon Europe

We propose an approach to 4D print solvent-triggered, gradient-based bilayers made of semi-crystalline crosslinked polymer networks. Out-of-plane bending is obtained after immersion in the solvent, exploiting the different swelling degrees of the layers resulting from crosslinking gradients. Lastly, a beam model of the shape transformation is applied and experimentally validated., Comment: This work was funded by the European Union ERC CoDe4Bio Grant ID 101039467 under the funding programme Horizon Europe

Linear solvers are key components in any software platform for scientific and engineering computing. The solution of large and sparse linear systems lies at the core of physics-driven numerical simulations relying on partial differential equations (PDEs) and often represents a significant bottleneck in datadriven procedures, such as scientific machine learning. In this paper, we present an efficient implementation of the preconditioned s-step Conjugate Gradient (CG) method, originally proposed by Chronopoulos and Gear in 1989, for large clusters of Nvidia GPU-accelerated computing nodes. The method, often referred to as communication-reduced or communication-avoiding CG, reduces global synchronizations and data communication steps compared to the standard approach, enhancing strong and weak scalability on parallel computers. Our main contribution is the design of a parallel solver that fully exploits the aggregation of low-granularity operations inherent to the s-step CG method to leverage the high throughput of GPU accelerators. Additionally, it applies overlap between data communication and computation in the multi-GPU sparse matrix-vector product. Experiments on classic benchmark datasets, derived from the discretization of the Poisson PDE, demonstrate the potential of the method.

We consider the optimisation problem of adding $k$ links to a given network, such that the resulting effective graph resistance is as small as possible. The problem was recently proven to be NP-hard, such that optimal solutions obtained with brute-force methods require exponentially many computation steps and thus are infeasible for any graph of realistic size. Therefore, it is common in such cases to use a simple greedy algorithm to obtain an approximation of the optimal solution. It is known that if the considered problem is submodular, the quality of the greedy solution can be guaranteed. However, it is known that the optimisation problem we are facing, is not submodular. For such cases one can use the notion of generalized submodularity, which is captured by the submodularity ratio $\gamma$. A performance bound, which is a function of $\gamma$, also exists in case of generalized submodularity. In this paper we give an example of a family of graphs where the submodularity ratio approaches zero, implying that the solution quality of the greedy algorithm cannot be guaranteed. Furthermore, we show that the greedy algorithm does not always yield the optimal solution and demonstrate that even for a small graph with 10 nodes, the ratio between the optimal and the greedy solution can be as small as 0.878., Comment: 21 pages, 14 figures

The problem is posed of establishing a possible relationship between a new type of Multi-verse representation, G\"odel undecidability theorems and the logic of classical, quantum mechanics and quantum gravity. For this purpose example cases of multi-verses are first discussed in the context of non-relativistic classical, quantum mechanics and quantum gravity. As a result, it is confirmed that thanks to G\"odel theorems non-relativistic classical and quantum mechanics, as well as quantum gravity theory are incomplete. As a consequence, they necessarily admit undecidable logical propositions and therefore obey a three-way boolean logical, i.e., a propositional logic with the three different logical truth values true, false and undecidable.

Massive galaxies in cooling flow clusters display clear evidence of feedback from Active Galactic Nuclei (AGN). Joint X-ray and radio observations have shown that AGN radio jets push aside the surrounding hot gas and form cavities in the hot intracluster medium (ICM). These systems host complex, kiloparsec-scale, multiphase filamentary structures, from warm ionized (10,000 K) to cold molecular ($<$100 K). These striking clumpy filaments are believed to be a natural outcome of thermally unstable cooling from the hot ICM, likely triggered by feedback processes while contributing to feeding the AGN via Chaotic Cold Accretion (CCA). However, the detailed constraints on the formation mechanism of the filaments are still uncertain, and the connection between the different gas phases has to be fully unveiled. By leveraging a sample of seven X-ray bright cooling-flow clusters, we have discovered a tight positive correlation between the X-ray surface brightness and the H$\alpha$ surface brightness of the filaments over two orders of magnitude, as also found in stripped tails., Comment: Accepted for publication in Nature Astronomy, 32 pages, 10 figures

Variational quantum algorithms are hybrid quantum-classical approaches extensively studied for their potential to leverage near-term quantum hardware for computational advantages. In this work, we successfully execute two variational quantum algorithms on a silicon photonic integrated circuit at room temperature: a variational quantum eigensolver for the Hydrogen molecule and a variational quantum factorization for semi-prime numbers. In our reconfigurable silicon photonic circuit, four identical spontaneous-four-wave-mixing-based integrated photon pair sources are used to prepare two path-entangled ququarts, whose correlation gives rise to the resource for generic trial states' preparation. This marks a first demonstration of variational quantum algorithms on a photonic quantum simulator with integrated photon pair sources., Comment: 42 pages, 13 figures

The effects of the many-body correlations with respect the MF description characterizing the Constrained Molecular Dynamics are discussed in the case of finite and zero range effective microscopic interactions. In particular, for the system $^{64}Ni+^{48}Ca$ fusion-fission cross-sections, IMF production and transversal flow have been evaluated in the framework of the CoMD model at different incident energies. The results obtained significantly depend on whether the effects of the above-mentioned correlations are taken into account in the corresponding EoS., Comment: arXiv admin note: substantial text overlap with arXiv:2309.02878

One of the most challenging and fascinating issues in mathematical and theoretical physics concerns identifying the common logic, if any, which underlies the physical world. More precisely, this involves the search of the possibly-unique axiomatic logical proposition calculus to apply simultaneously both to classical and quantum realms of physics and to be consistent with the corresponding mathematical and filosophysical setups. Based on the recent establishment of quantum logic, which has been shown to apply both to Quantum Mechanics and Quantum Gravity, the crucial remaining step involves the identification of the appropriate axiomatic logical proposition calculus to be associated with Classical Mechanics. In this paper the issue is posed for a fundamental example of Classical Mechanics, which is represented by the so-called Boltzmann-Sinai dynamical system. This is realized by the ensemble of classical smooth hard-spheres, which is set at the basis of Classical Statistical Mechanics and is also commonly regarded as a possible realization of Classical Newtonian Cosmology. Depending on the initial conditions which are prescribed for such a system, its classical state is shown to obey the propositional calculus of non-classical logic. In particular, the latter is expressed by the 3-way Principle of Non-Contradiction, namely the same logical principle that holds for quantum logic. The result therefore permits to question on a mathematical basis the principles of deterministic classical logic and the validity of their character within the domain of Classical Physics. Such a conclusion represents a potential notable innovation in the logical dicotomy true/false, a crucial topic which has crossed millennia through philosophy, logic, mathematics and physics.

Causal abstractions allow us to relate causal models on different levels of granularity. To ensure that the models agree on cause and effect, frameworks for causal abstractions define notions of consistency. Two distinct methods for causal abstraction are common in the literature: (i) graphical abstractions, such as Cluster DAGs, which relate models on a structural level, and (ii) functional abstractions, like $\alpha$-abstractions, which relate models by maps between variables and their ranges. In this paper we will align the notions of graphical and functional consistency and show an equivalence between the class of Cluster DAGs, consistent $\alpha$-abstractions, and constructive $\tau$-abstractions. Furthermore, we extend this alignment and the expressivity of graphical abstractions by introducing Partial Cluster DAGs. Our results provide a rigorous bridge between the functional and graphical frameworks and allow for adoption and transfer of results between them.

The EuPRAXIA project aims to construct two state-of-the-art accelerator facilities based on plasma accelerator technology. Plasma-based accelerators offer the possibility of a significant reduction in facility size and cost savings over current radio frequency (RF) accelerators. The two facilities - one laser-driven one a beam-driven - are envisioned to provide electron beams with an energy in the range of 1-5 GeV and beam quality comparable to existing RF machines. This will enable a versatile portfolio of applications from compact free-electron laser (FEL) drivers to sources for medical and industrial imaging. At the heart of both facilities is the use of plasma-based accelerator components and systems which encompass not only the accelerating medium itself, but also a range of auxiliary systems such as plasma-based electron beam optics and plasma-based mirrors for high-intensity lasers. From a technical standpoint, a high-degree of control over these plasma devices will be essential for EuPRAXIA to achieve its target performance goals. The ability to diagnose and characterize these plasma devices and to simulate their operation will be further essential success factors. Additionally, compatibility with extended operation at high-repetition rates and integration into the accelerator beamline will also prove crucial. In this work, we aim to review the current status of plasma components and related systems for both laser-driven and beam-driven plasma accelerators and to assess challenges to be addressed regarding implementation at future EuPRAXIA facilities., Comment: 25 pages, 11 figures

Estimating the evolution of the battery's State of Charge (SoC) in response to its usage is critical for implementing effective power management policies and for ultimately improving the system's lifetime. Most existing estimation methods are either physics-based digital twins of the battery or data-driven models such as Neural Networks (NNs). In this work, we propose two new contributions in this domain. First, we introduce a novel NN architecture formed by two cascaded branches: one to predict the current SoC based on sensor readings, and one to estimate the SoC at a future time as a function of the load behavior. Second, we integrate battery dynamics equations into the training of our NN, merging the physics-based and data-driven approaches, to improve the models' generalization over variable prediction horizons. We validate our approach on two publicly accessible datasets, showing that our Physics-Informed Neural Networks (PINNs) outperform purely data-driven ones while also obtaining superior prediction accuracy with a smaller architecture with respect to the state-of-the-art.

Integrated photonic microresonators have become an essential resource for generating photonic qubits for quantum information processing, entanglement distribution and networking, and quantum communications. The pair generation rate is enhanced by reducing the microresonator radius, but this comes at the cost of increasing the frequency mode spacing and reducing the quantum information spectral density. Here, we circumvent this rate-density trade-off in an AlGaAs-on-insulator photonic device by multiplexing an array of 20 small-radius microresonators each producing a 650-GHz-spaced comb of time-energy entangled-photon pairs. The resonators can be independently tuned via integrated thermo-optic heaters, enabling control of the mode spacing from degeneracy up to a full free spectral range. We demonstrate simultaneous pumping of five resonators with up to $50$ GHz relative comb offsets, where each resonator produces pairs exhibiting time-energy entanglement visibilities up to 95$\%$, coincidence-to-accidental ratios exceeding 5,000, and an on-chip pair rate up to 2.6 GHz/mW$^2$ per comb line -- more than 40 times improvement over prior work. As a demonstration, we generate frequency-bin qubits in a maximally entangled two-qubit Bell state with fidelity exceeding 87$\%$ (90$\%$ with background correction) and detected frequency-bin entanglement rates up to 7 kHz ($\sim 70$ MHz on-chip pair rate) using $\sim 250$ $\mu$W pump power. Multiplexing small-radius microresonators combines the key capabilities required for programmable and dense photonic qubit encoding while retaining high pair-generation rates, heralded single-photon purity, and entanglement fidelity.

Heart rate (HR) estimation from photoplethysmography (PPG) signals is a key feature of modern wearable devices for health and wellness monitoring. While deep learning models show promise, their performance relies on the availability of large datasets. We present EnhancePPG, a method that enhances state-of-the-art models by integrating self-supervised learning with data augmentation (DA). Our approach combines self-supervised pre-training with DA, allowing the model to learn more generalizable features, without needing more labelled data. Inspired by a U-Net-like autoencoder architecture, we utilize unsupervised PPG signal reconstruction, taking advantage of large amounts of unlabeled data during the pre-training phase combined with data augmentation, to improve state-of-the-art models' performance. Thanks to our approach and minimal modification to the state-of-the-art model, we improve the best HR estimation by 12.2%, lowering from 4.03 Beats-Per-Minute (BPM) to 3.54 BPM the error on PPG-DaLiA. Importantly, our EnhancePPG approach focuses exclusively on the training of the selected deep learning model, without significantly increasing its inference latency, Comment: 5 pages, 3 figures, 2 tables

We propose to explore the potential advantages of a new class of tracking algorithms loosely inspired by the Hough transform concept and where we include the time of arrival of each hit as an additional coordinate to be treated in the same way as a spatial coordinate. A remarkable property of this algorithm is that the execution time is proportional to the total number of hits to be processed, making it particularly attractive for high occupancy situations expected at future colliders. The particular structure of the algorithm also lends itself naturally to parallel hardware implementations which, combined to its intrinsic flexibility, should provide a powerful tool for triggering at future colliders. To probe the effectiveness of the algorithm, we apply it to a quasi-realistic simulated environment of a possible future muon collider experiment and report the performance.

The timeline of the expansion rate ultimately defines the interplay between high energy physics, astrophysics and cosmology. The guiding theme of this topical review is provided by the scrutiny of the early history of the space-time curvature through the diffuse backgrounds of gravitational radiation that are sensitive to all the stages of the evolution of the plasma. Due to their broad spectrum (extending from the aHz region to the THz domain) they bridge the macroworld described by general relativity and the microworld of the fundamental constituents of matter. It is argued that during the next score year the analysis of the relic gravitons may infirm or confirm the current paradigm where a radiation plasma is assumed to dominate the whole post-inflationary epoch. The role of high frequency and ultra-high frequency signals between the MHz and the THz is emphasized in the perspective of quantum sensing. The multiparticle final state of the relic gravitons and its macroscopic quantumness is also discussed with particular attention to the interplay between the entanglement entropy and the maximal frequency of the spectrum., Comment: 91 pages, 18 figures

The sphaleron rate is a key phenomenological quantity both for the axion thermal production in the Early Universe and the Chiral Magnetic Effect occurring in the Quark-Gluon Plasma in presence of a background magnetic field. In this talk we present an extension of our recent determination of the sphaleron rate, in the SU(3) gauge theory, based on the determination of the two-point function of the topological charge density at finite temperature., Comment: 11 pages, 3 figures, contribution for the Proceedings of the 41st International Symposium on Lattice Field Theory (Lattice 2024), 28 July - 3 August 2024, Liverpool, UK

The origin of cool-core (CC) and non-cool-core (NCC) dichotomy of galaxy clusters remains uncertain. Previous simulations have found that cluster mergers are effective in destroying CCs but fail to prevent overcooling in cluster cores when radiative cooling is included. Feedback from active galactic nuclei (AGN) is a promising mechanism for balancing cooling in CCs; however, the role of AGN feedback in CC/NCC transitions remains elusive. In this work, we perform three-dimensional binary cluster merger simulations incorporating AGN feedback and radiative cooling, aiming to investigate the heating effects from mergers and AGN feedback on CC destruction. We vary the mass ratio and impact parameter to examine the entropy evolution of different merger scenarios. We find that AGN feedback is essential in regulating the merging clusters, and that CC destruction depends on the merger parameters. Our results suggest three scenarios regarding CC/NCC transitions: (1) CCs are preserved in minor mergers or mergers that do not trigger sufficient heating, in which cases AGN feedback is crucial for preventing the cooling catastrophe; (2) CCs are transformed into NCCs by major mergers during the first core passage, and AGN feedback is subdominant; (3) in major mergers with a large impact parameter, mergers and AGN feedback operate in concert to destroy the CCs., Comment: 20 pages, 10 figures. Submitted to ApJ

The European project SCARLET aims to study and realize a demonstrator of a MVDC (Medium Voltage Direct Current) high-power superconducting cable. This device might be employed to connect offshore wind farms with land, expecting to significantly simplify the offshore platform by eliminating the need for its conversion function. For this purpose, windmill conversion chain must be modified to directly produce the MVDC export voltage. In this scenario, this paper presents the case of a 1GW offshore windmill superconducting link and outlines the design consideration for a 1 GW onshore converter. For this cable, a protection strategy that combines DC circuit breakers with a Resistive Superconducting Fault Current Limiter is proposed. Moreover, this works demonstrates how a superconducting cable can be modelled as an electrical circuit to be integrated into a network simulation tool, enabling the investigation of various fault scenarios and protection strategies. Finally, a specific result is discussed to exemplify how the proposed approach can benefit the design of both the electrical network and the superconducting cable itself.

We present an experimental and numerical study of a piezoelectric energy harvester driven by broadband vibrations. This device can extract power from random fluctuations and can be described by a stochastic model, based on an underdamped Langevin equation with white noise, which mimics the dynamics of the piezoelectric material. A crucial point in the modelisation is represented by the appropriate description of the coupled load circuit that is necessary to harvest electrical energy. We consider a linear load (resistance) and a nonlinear load (diode bridge rectifier connected to the parallel of a capacitance and a load resistance), and focus on the characteristic curve of the extracted power as a function of the load resistance, in order to estimate the optimal values of the parameters that maximise the collected energy. In both cases, we find good agreement between the numerical simulations of the theoretical model and the results obtained in experiments. In particular, we observe a non-monotonic behaviour of the characteristic curve which signals the presence of an optimal value for the load resistance at which the extracted power is maximised. We also address a more theoretical issue, related to the inference of the non-equilibrium features of the system from data: we show that the analysis of high-order correlation functions of the relevant variables, when in the presence of nonlinearities, can represent a simple and effective tool to check the irreversible dynamics., Comment: 11 pages, 13 figures

Previous Hubble Space Telescope (HST) observations of the star-forming cluster NGC 346 in the Small Magellanic Cloud (SMC) had revealed a large population of pre-main sequence (PMS) candidates, characterised by Halpha excess emission in their photometry. However, without access to spectroscopy, the nature of these objects remained unclear. Using the NIRSpec instrument on board JWST, we studied a sample of these stars, with masses in the range ~0.9-1.8 Msun, effective temperatures in the range 4,500-8,000 K, and PMS ages between ~0.1 and 30 Myr. Here we present the first spectra of solar-mass PMS stars in the metal-poor SMC (Z=1/8 Zsun) and discuss the physical properties of ten representative sources with good signal-to-noise ratio. The observations indicate that even the oldest of these PMS candidates are still accreting gas with typical rates of ~10^{-8} Msun/yr for stars older than ~10 Myr, confirming their PMS nature. The spectra also reveal near-infrared excess and molecular hydrogen excitation lines consistent with the presence of discs around these stars. These findings suggest that in a low-metallicity environment circumstellar discs can live longer than previously thought., Comment: 17 pages, 7 figures, to be published in The Astrophysical Journal, Vol 977, Article 214

A (vertex) colouring of graph is \emph{acyclic} if it contains no bicoloured cycle. In 1979, Borodin proved that planar graphs are acyclically 5-colourable. In 2010, Kawarabayashi and Mohar proved that locally planar graphs are acyclically 7-colourable. In 2002, Borodin, Fon-Der-Flaass, Kostochka, Raspaud, and Sopena proved that planar graphs are acyclically 7-list-colourable. We prove that locally planar graphs are acyclically 9-list-colourable\textemdash no bound for acyclic list colouring locally planar graphs for any fixed number of colours was previously known., Comment: 19 pages, 4 figures

We investigate mixed (50/50) clusters of parahydrogen and orthodeuterium at low temperature, by means of Quantum Monte Carlo simulations. Our results provide evidence of liquid-like behavior and partial isotopic separation in a cluster of 640 molecules, at temperature T=10 K. As the temperature is lowered below ~6 K, crystallization occurs, with no indication that the liquid phase is more resilient at low temperature in a mixed cluster. Isotopic separation is therefore predicted to take place at low temperature only through the slow process of molecular self-diffusion in a crystalline matrix., Comment: Thirteen manuscript pages, three figures in color

In this work we discuss our preliminary results regarding the so-called Roberge-Weiss (RW) transition, which is found for imaginary values of the baryon chemical potential, in the presence of a background magnetic field. We perform lattice QCD simulations on $N_t = 6, 8$ lattices with $2+1$ flavors of stout-staggered fermions at physical quark masses and the tree-level Symanzik improved gauge action. We determine the location the RW endpoint at finite magnetic fields and we study the order of the transition., Comment: 11 pages, 8 figures, Proceedings of the 41st International Symposium on Lattice Field Theory, 28 July - 3 August, 2024, Liverpool, UK

The hot plasma in galaxy clusters, the intracluster medium (ICM), is expected to be shaped by subsonic turbulent motions, which are key for heating, cooling, and transport mechanisms. The turbulent motions contribute to the non-thermal pressure which, if not accounted for, consequently imparts a hydrostatic mass bias. Accessing information about turbulent motions is thus of major astrophysical and cosmological interest. Characteristics of turbulent motions can be indirectly accessed through surface brightness fluctuations. This study expands on our pilot investigations of surface brightness fluctuations in the SZ and X-ray by examining, for the first time, a large sample of 60 clusters using both SPT-SZ and XMM-Newton data and span the redshift range $0.2 < z < 1.5$, thus constraining the respective pressure and density fluctuations within 0.6~$R_{500}$. We deem density fluctuations to be of sufficient quality for 32 clusters, finding mild correlations between the peak of the amplitude spectra of density fluctuations and various dynamical parameters. We infer turbulent velocities from density fluctuations with an average Mach number $\mathcal{M}_{\text{3D}} = 0.52 \pm 0.14$, in agreement with numerical simulations. For clusters with inferred turbulent Mach numbers from both pressure, $\mathcal{M}_{\text{P}}$ and density fluctuations, $\mathcal{M}_{\rho}$, we find broad agreement between $\mathcal{M}_{\text{P}}$ and $\mathcal{M}_{\rho}$. Our results suggest a bimodal Mach number distribution, with the majority of clusters being turbulence-dominated (subsonic) while the remainder are shock-dominated (supersonic)., Comment: 18 pages, 10 figures, 4 tables. Submitted to ApJ; comments welcome

The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those leveraging automation and Large Language Models (LLMs) for web interaction tasks. Many existing benchmarks suffer from fragmentation and inconsistent evaluation methodologies, making it challenging to achieve reliable comparisons and reproducible results. BrowserGym aims to solve this by providing a unified, gym-like environment with well-defined observation and action spaces, facilitating standardized evaluation across diverse benchmarks. Combined with AgentLab, a complementary framework that aids in agent creation, testing, and analysis, BrowserGym offers flexibility for integrating new benchmarks while ensuring consistent evaluation and comprehensive experiment management. This standardized approach seeks to reduce the time and complexity of developing web agents, supporting more reliable comparisons and facilitating in-depth analysis of agent behaviors, and could result in more adaptable, capable agents, ultimately accelerating innovation in LLM-driven automation. As a supporting evidence, we conduct the first large-scale, multi-benchmark web agent experiment and compare the performance of 6 state-of-the-art LLMs across all benchmarks currently available in BrowserGym. Among other findings, our results highlight a large discrepancy between OpenAI and Anthropic's latests models, with Claude-3.5-Sonnet leading the way on almost all benchmarks, except on vision-related tasks where GPT-4o is superior. Despite these advancements, our results emphasize that building robust and efficient web agents remains a significant challenge, due to the inherent complexity of real-world web environments and the limitations of current models.

We introduce the Bias-free Extragalactic Analysis for Cosmic Origins with NIRCam (BEACON) survey, a JWST Cycle2 program allocated up to 600 pure-parallel hours of observations. BEACON explores high-latitude areas of the sky with JWST/NIRCam over $\sim100$ independent sightlines, totaling $\sim0.3$deg$^2$, reaching a median F444W depth of $\approx28.2$AB mag (5$\sigma$). Based on existing JWST observations in legacy fields, we estimate that BEACON will photometrically identify 25--150 galaxies at $z>10$ and 500--1000 at $z\sim7$--10 uniquely enabled by an efficient multiple filter configuration spanning $0.9$--5.0$\mu$m. The expected sample size of $z>10$ galaxies will allow us to obtain robust number density estimates and to discriminate between different models of early star formation. In this paper, we present an overview of the survey design and initial results using the first 19 fields. We present 129 galaxy candidates at $z>7$ identified in those fields, including 11 galaxies at $z>10$ and several UV-luminous ($M_{\rm UV}<-21$mag) galaxies at $z\sim8$. The number densities of $z<13$ galaxies inferred from the initial fields are overall consistent with those in the literature. Despite reaching a considerably large volume ($\sim10^5$Mpc$^3$), however, we find no galaxy candidates at $z>13$, providing us with a complimentary insight into early galaxy evolution with minimal cosmic variance. We publish imaging and catalog data products for these initial fields. Upon survey completion, all BEACON data will be coherently processed and distributed to the community along with catalogs for redshift and other physical quantities., Comment: Submitted to ApJ; DR1 data release will be made on the team website (https://beacon-jwst.github.io); Fig. 8 has been updated

Background and objective: Diabetes is one of the four leading causes of death worldwide, necessitating daily blood glucose monitoring. While sweat offers a promising non-invasive alternative for glucose monitoring, its application remains limited due to the low to moderate correlation between sweat and blood glucose concentrations, which has been obtained until now by assuming a linear relationship. This study proposes a novel model-based strategy to estimate blood glucose concentrations from sweat samples, setting the stage for non-invasive glucose monitoring through sweat-sensing technology. Methods: We first developed a pharmacokinetic glucose transport model that describes the glucose transport from blood to sweat. Secondly, we designed a novel optimization strategy leveraging the proposed model to solve the inverse problem and infer blood glucose levels from measured glucose concentrations in sweat. To this end, the pharmacokinetic model parameters with the highest sensitivity were also optimized so as to achieve a personalized estimation. Our strategy was tested on a dataset composed of 108 samples from healthy volunteers and diabetic patients. Results: Our glucose transport model improves over the state-of-the-art in estimating sweat glucose concentrations from blood levels (higher accuracy, p<0.001). Additionally, our optimization strategy effectively solved the inverse problem, yielding a Pearson correlation coefficient of 0.98 across all 108 data points, with an average root-mean-square-percent-error of 12%+/-8%. This significantly outperforms the best sweat-blood glucose correlation reported in the existing literature (0.75). Conclusion: Our innovative optimization strategy, also leveraging more accurate modeling, shows promising results, paving the way for non-invasive blood glucose monitoring and, possibly, improved diabetes management.

Working in momentum space and at linear order in the gravitational coupling, we derive the most general class of energy-momentum tensors associated with a given multipolar structure of the spacetime in arbitrary dimensions, and built out of a mass and an angular momentum, at any order in the spin expansion. In this formalism, we are able to derive directly the full multipolar structure of any solution from the multipole expansion of the energy-momentum tensor, in complete analogy to Newtonian gravity. In particular, we identify the recurrence relations that allow obtaining the multipolar structure of the Kerr and the Myers-Perry black hole solutions, defining source multipoles in a General Relativity context for the first time. For these solutions, we are able to resum the energy-momentum tensor in momentum space at all orders in the angular momentum, and compute its real-space version. In the Kerr case we exactly obtain the matter source found by Israel, namely an equatorial, pressureless thin disk rotating at superluminal speed. For Myers-Perry in five dimensions, the matter distribution is a three-ellipsoid in four spatial dimensions with nontrivial stresses. Remarkably, for any dimensions, the matter configuration is a lower-dimensional distribution which has the same singularity structure as the fully non-linear black-hole solution. Our formalism underscores the advantage of working in momentum space to generate nontrivial matter sources for non-linear spacetimes, and could be used to construct regular non-exotic matter configurations that source spinning black hole solutions or horizonless compact objects with the same multipolar structure as black holes., Comment: 15+7 pages

Free associations have been extensively used in cognitive psychology and linguistics for studying how conceptual knowledge is organized. Recently, the potential of applying a similar approach for investigating the knowledge encoded in LLMs has emerged, specifically as a method for investigating LLM biases. However, the absence of large-scale LLM-generated free association norms that are comparable with human-generated norms is an obstacle to this new research direction. To address this limitation, we create a new dataset of LLM-generated free association norms modeled after the "Small World of Words" (SWOW) human-generated norms consisting of approximately 12,000 cue words. We prompt three LLMs, namely Mistral, Llama3, and Haiku, with the same cues as those in the SWOW norms to generate three novel comparable datasets, the "LLM World of Words" (LWOW). Using both SWOW and LWOW norms, we construct cognitive network models of semantic memory that represent the conceptual knowledge possessed by humans and LLMs. We demonstrate how these datasets can be used for investigating implicit biases in humans and LLMs, such as the harmful gender stereotypes that are prevalent both in society and LLM outputs., Comment: 16 pages, 11 figures, associated Github page with dataset available at: https://github.com/LLMWorldOfWords/LWOW

Creativity is a fundamental skill of human cognition. We use textual forma mentis networks (TFMN) to extract network (semantic/syntactic associations) and emotional features from approximately one thousand human- and GPT3.5-generated stories. Using Explainable Artificial Intelligence (XAI), we test whether features relative to Mednick's associative theory of creativity can explain creativity ratings assigned by humans and GPT-3.5. Using XGBoost, we examine three scenarios: (i) human ratings of human stories, (ii) GPT-3.5 ratings of human stories, and (iii) GPT-3.5 ratings of GPT-generated stories. Our findings reveal that GPT-3.5 ratings differ significantly from human ratings not only in terms of correlations but also because of feature patterns identified with XAI methods. GPT-3.5 favours 'its own' stories and rates human stories differently from humans. Feature importance analysis with SHAP scores shows that: (i) network features are more predictive for human creativity ratings but also for GPT-3.5's ratings of human stories; (ii) emotional features played a greater role than semantic/syntactic network structure in GPT-3.5 rating its own stories. These quantitative results underscore key limitations in GPT-3.5's ability to align with human assessments of creativity. We emphasise the need for caution when using GPT-3.5 to assess and generate creative content, as it does not yet capture the nuanced complexity that characterises human creativity.

Integrating multiple (sub-)systems is essential to create advanced Information Systems (ISs). Difficulties mainly arise when integrating dynamic environments across the IS lifecycle. A traditional approach is a registry that provides the API documentation of the systems' endpoints. Large Language Models (LLMs) have shown to be capable of automatically creating system integrations (e.g., as service composition) based on this documentation but require concise input due to input token limitations, especially regarding comprehensive API descriptions. Currently, it is unknown how best to preprocess these API descriptions. Within this work, we (i) analyze the usage of Retrieval Augmented Generation (RAG) for endpoint discovery and the chunking, i.e., preprocessing, of OpenAPIs to reduce the input token length while preserving the most relevant information. To further reduce the input token length for the composition prompt and improve endpoint retrieval, we propose (ii) a Discovery Agent that only receives a summary of the most relevant endpoints and retrieves details on demand. We evaluate RAG for endpoint discovery using the RestBench benchmark, first, for the different chunking possibilities and parameters measuring the endpoint retrieval recall, precision, and F1 score. Then, we assess the Discovery Agent using the same test set. With our prototype, we demonstrate how to successfully employ RAG for endpoint discovery to reduce the token count. While revealing high values for recall, precision, and F1, further research is necessary to retrieve all requisite endpoints. Our experiments show that for preprocessing, LLM-based and format-specific approaches outperform na\"ive chunking methods. Relying on an agent further enhances these results as the agent splits the tasks into multiple fine granular subtasks, improving the overall RAG performance in the token count, precision, and F1 score.

We study the radiated energy by a scalar particle moving on a circular orbit (smeared in the extra dimension) in the spacetime of a topological star, extending a previous study [Phys. Rev. D {\bf 110}, 084077 (2024)]. We discuss motion in the presence of self-force effects too., Comment: 17 pages, 5 figures, revtex macros

This paper proposes a novel canonical correlation analysis for semiparametric inference in $I(1)/I(0)$ systems via functional approximation. The approach can be applied coherently to panels of $p$ variables with a generic number $s$ of stochastic trends, as well as to subsets or aggregations of variables. This study discusses inferential tools on $s$ and on the loading matrix $\psi$ of the stochastic trends (and on their duals $r$ and $\beta$, the cointegration rank and the cointegrating matrix): asymptotically pivotal test sequences and consistent estimators of $s$ and $r$, $T$-consistent, mixed Gaussian and efficient estimators of $\psi$ and $\beta$, Wald tests thereof, and misspecification tests for checking model assumptions. Monte Carlo simulations show that these tools have reliable performance uniformly in $s$ for small, medium and large-dimensional systems, with $p$ ranging from 10 to 300. An empirical analysis of 20 exchange rates illustrates the methods.

The exponential growth of astronomical data from large-scale surveys has created both opportunities and challenges for the astrophysics community. This paper explores the possibilities offered by transfer learning techniques in addressing these challenges across various domains of astronomical research. We present a set of recent applications of transfer learning methods for astronomical tasks based on the usage of a pre-trained convolutional neural networks. The examples shortly discussed include the detection of candidate active galactic nuclei (AGN), the possibility of deriving physical parameters for galaxies directly from images, the identification of artifacts in time series images, and the detection of strong lensing candidates and outliers. We demonstrate how transfer learning enables efficient analysis of complex astronomical phenomena, particularly in scenarios where labeled data is scarce. This kind of method will be very helpful for upcoming large-scale surveys like the Rubin Legacy Survey of Space and Time (LSST). By showcasing successful implementations and discussing methodological approaches, we highlight the versatility and effectiveness of such techniques., Comment: proceeding of the Seventeenth Marcel Grossmann Meeting

We present a suite of zoom-in cosmological simulations of Milky Way-like galaxies with a prominent disc component and a strong bar in their centre, based on a subsample of barred galaxies from the TNG50 magneto-hydrodynamic simulation. We modify the physical models that regulate star formation, namely, supernova feedback and black hole quasar feedback, to examine how they affect the disc and bar formation. We find that the morphology remains consistent in all the galaxies that develop a massive stellar disc ($>10^{10}\Msun$), which is dominant in comparison with the bulge mass. The black hole quasar feedback models used in this work do not affect bar formation, although they can affect the properties of the bar. The energy released by the supernovae causes a delay in the time of bar formation and, in models with strong feedback, stops bar formation. This could be understood since supernova feedback affects the assembly of the disc and bulge and their structural properties, such as the mass content, size, and radial velocity dispersion. We compared our predictions to three bar instability criteria proposed in the literature. We find that galaxies with varying supernovae and black hole quasar feedback satisfy these criteria at the moment of bar formation, except in extreme cases where the galaxy does not have or has weak supernova feedback, where for some galaxies, they fail to predict the existence (or no existence) of bars. Our findings provide insights into the physical process behind bar formation while putting constraints on the analytic prescriptions that predict bar formation., Comment: 21 pages, 11 figures, submitted to A&A. Comments are welcome