Search

Photometric galaxy surveys, despite their limited resolution along the line of sight, encode rich information about the large-scale structure (LSS) of the Universe thanks to the large number density and extensive depth of the data. However, the complicated selection effects in wide and deep surveys will potentially cause significant bias in the angular two-point correlation function (2PCF) measured from those surveys. In this paper, we measure the 2PCF from the newly published KiDS-Legacy sample. Given an $r$-band $5\sigma$ magnitude limit of $24.8$ and survey footprint of $1347$ deg$^2$, it achieves an excellent combination of sky coverage and depth for such a measurement. We find that complex selection effects, primarily induced by varying seeing, introduce over-estimation of the 2PCF by approximately an order of magnitude. To correct for such effects, we apply a machine learning-based method to recover an ``organised random'' (OR) that presents the same selection pattern as the galaxy sample. The basic idea is to find the selection-induced clustering of galaxies using a combination of self-organising maps (SOM) and hierarchical clustering (HC). This unsupervised machine learning method is able to recover complicated selection effects without specifying their functional forms. We validate this ``SOM+HC'' method on mock deep galaxy samples with realistic systematics and selections derived from the KiDS-Legacy catalogue. Using mock data, we demonstrate that the OR delivers unbiased 2PCF cosmological parameter constraints, removing the $27\sigma$ offset in the galaxy bias parameter that is recovered when adopting uniform randoms. Blinded measurements on the real KiDS-Legacy data show that the corrected 2PCF is robust to the SOM+HC configuration near the optimal setup suggested by the mock tests. Our software is open-source for future usage., Comment: 29 pages, 27 figures, 4 tables

We investigate the effect of primordial non-Gaussianities on halo number counts using N-body simulations with different values of $f_{\rm NL}^{\rm loc}$. We show how current theoretical models fail to adequately describe the non-Gaussian mass function of halos identified with different overdensity thresholds, $\Delta_{\rm b}$. We explain how these discrepancies are related to a variation in the density profile of dark matter halos, finding that the internal steepness (i.e. the compactness) of halos depends on the value of $f_{\rm NL}^{\rm loc}$. We then parametrize these deviations in halo number counts with a factor $\kappa(\Delta_{\rm b})$ that modifies the linear density threshold for collapse according to the halo identification threshold used, defined with respect to the Universe background density. We rely on a second-degree polynomial to describe $\kappa$ and employ a Bayesian analysis to determine the coefficients of this polynomial. In addition, we verify the independence of the latter on the sign and absolute value of $f_{\rm NL}^{\rm loc}$. Finally, we show how this re-parametrization prevents the extraction of biased constraints on $f_{\rm NL}^{\rm loc}$, correcting for large systematic errors especially in the case of halos identified with high density thresholds. This improvement is crucial in the perspective of deriving cosmological constraints with the non-Gaussian mass function from real data, as different mass definitions can be employed depending on the properties of the survey., Comment: 28 pages, 8 figures, to be submitted to JCAP

The pepenaactivity is part of the informal sector, characterized by precariousness and social invisibility; however, it is a key element in the recycling production chain, providing an economic income for many people. In the city of Chihuahua, this activity is carried out on a significant scale. Therefore, this study analyzes and dignifies the recycling of urban solid waste from the perspective of scavengers, also explaining their relationship with other social actors at the city's final disposal site. The study starts from the premise that waste picking is, in the current era of global environmental crisis, an effective way to conserve resources and reduce environmental impacts. Methodologically, participatory action research was used as a strategy to raise awareness among scavengers about the importance of their work and to present their community organization as an example to other urban waste picking groups in different locations. Finally, we found issues in these groups such as informality, lack of legal support,specific health risks, and, more broadly, the absence of public policies to recognize this activity as valuable in addressing the global environmental crisis, Comment: in Spanish language

This paper studies moving 180-degree N\'eel walls in ferromagnetic thin films under the reduced model for the in-plane magnetization proposed by Capella, Melcher and Otto [5], in the case when a sufficiently weak external magnetic field is applied. It is shown that the linearization around the moving N\'eel wall's phase determines a spectral problem that is a relatively bounded perturbation of the linearization around the static N\'eel wall, which is the solution when the external magnetic field is set to zero and which is spectrally stable. Uniform resolvent-type estimates for the linearized operator around the static wall are established in order to prove the spectral stability of the moving wall upon application of perturbation theory for linear operators. The spectral analysis is the basis to prove, in turn, both the decaying properties of the generated semigroup and the nonlinear stability of the moving N\'eel wall under small perturbations, in the case of a sufficiently weak external magnetic field. The stability of the static N\'eel wall, which was established in a companion paper [4], plays a key role to obtain the main result., Comment: 40 pages, 4 figures

Small business owners stand to benefit from generative AI technologies due to limited resources, yet they must navigate increasing legal and ethical risks. In this paper, we interview 11 entrepreneurs and support personnel to investigate existing practices of how entrepreneurs integrate generative AI technologies into their business workflows. Specifically, we build on scholarship in HCI which emphasizes the role of small, offline networks in supporting entrepreneurs' technology maintenance. We detail how entrepreneurs resourcefully leveraged their local networks to discover new use cases of generative AI (e.g., by sharing accounts), assuage heightened techno-anxieties (e.g., by recruiting trusted confidants), overcome barriers to sustained use (e.g., by receiving wrap-around support), and establish boundaries of use. Further, we suggest how generative AI platforms may be redesigned to better support entrepreneurs, such as by taking into account the benefits and tensions of use in a social context., Comment: 6 pages, 2 figures, to be published in Companion of the 2024 Computer-Supported Cooperative Work and Social Computing (CSCW Companion '24), November 9-13, 2024, San Jose, Costa Rica

The spatial distribution of galaxy clusters is a valuable probe for inferring fundamental cosmological parameters. We measured the clustering properties of dark matter haloes from the \textsc{Pinocchio} simulations, in the redshift range $0.2 < z < 1.0$ and with virial masses $M_\mathrm{vir} > 10^{14} M_\odot \, h^{-1}$, which reproduce the expected mass selection of galaxy cluster samples. The past-light cones we analysed have an angular size of 60 degrees, which approximately corresponds to a quarter of the sky. We adopted a linear power spectrum model, accounting for nonlinear corrections at the baryon acoustic oscillations scale, to perform a comparative study between 3D and 2D tomographic clustering. For this purpose, we modelled the multipoles of the 3D two-point correlation function, $\xi(r)$, the angular correlation function, $w(\theta)$, and the angular power spectrum, $C_\ell$. We considered observational effects such as redshift-space distortions, produced by the peculiar velocities of tracers, and redshift errors. We found that photometric redshift errors have a more severe consequence on the 3D than on the 2D clustering, as they affect only the radial separation between haloes and not the angular one, with a relevant impact on the 3D multipoles. Using a Bayesian analysis, we explored the posterior distributions of the considered probes with different tomographic strategies, in the $\Omega_m-\sigma_8$ plane, focusing on the summary parameter $S_8\equiv \sigma_8\sqrt{\Omega_m/0.3}$. Our results show that in the presence of large photometric errors the 2D clustering can provide competitive cosmological constraints with respect to the full 3D clustering statistics, and can be successfully applied to analyse the galaxy cluster catalogues from the ongoing and forthcoming Stage-III and Stage-IV photometric redshift surveys., Comment: 24 pages, 16 figures, submitted to Astronomy & Astrophysics

By studying the total fusion and breakup cross-sections in the interaction of the neutron-halo $^{11}{\rm Be}$ projectile on the lead target $^{208}$Pb, it is shown that, even for the neutron-halo projectile, the breakup channel remains the most dominant reaction channel at sub-barrier energies, following a characteristic behavior that was also previously verified for the case of the proton-halo projectile $^8{\rm B}$. This feature is found to emanate from the enhancement of the breakup cross-section, due to the continuum-continuum couplings coming exclusively from its Coulomb component. We further speculate that the enhancement of the Coulomb breakup cross-section at sub-barrier incident energies by the continuum-continuum couplings could be associated with the projectile breaking up on the outgoing trajectory, provided these couplings can be proven to delay the breakup process., Comment: 8 pages, 7 figures

We present the results of a set of cosmological N-body simulations with standard $\Lambda$CDM cosmology but characterized by a scale-dependent primordial non-Gaussianity of the local type featuring a power-law dependence of the $f_{\rm NL}^{\rm loc}(k)$ at large scales followed by a saturation to a constant value at smaller scales where non-linear growth leads to the formation of collapsed cosmic structures. Such models are built to ensure consistency with current Cosmic Microwave Background bounds on primordial non-Gaussianity yet allowing for large effects of the non-Gaussian statistics on the properties of non-linear structure formation. We show the impact of such scale-dependent non-Gaussian scenarios on a wide range of properties of the resulting cosmic structures, such as the non-linear matter power spectrum, the halo and sub-halo mass functions, the concentration-mass relation, the halo and void density profiles, and we highlight for the first time that some of these models might mimic the effects of Warm Dark Matter for several of such observables, Comment: 21 pages, 9 figures, 2 tables; to be submitted to JCAP

This work identifies 18 foundational challenges in assuring the alignment and safety of large language models (LLMs). These challenges are organized into three different categories: scientific understanding of LLMs, development and deployment methods, and sociotechnical challenges. Based on the identified challenges, we pose $200+$ concrete research questions.

This work aims at assessing the impact of DM self-interactions on the properties of galaxy clusters. In particular, the goal is to study the angular dependence of the cross section by testing rare (large angle scattering) and frequent (small angle scattering) SIDM models with velocity-dependent cross sections. We re-simulate six galaxy cluster zoom-in initial conditions with a dark matter only run and with a full-physics setup simulations that includes a self-consistent treatment of baryon physics. We test the dark matter only setup and the full physics setup with either collisionless cold dark matter, rare self-interacting dark matter, and frequent self-interacting dark matter models. We then study their matter density profiles as well as their subhalo population. Our dark matter only SIDM simlations agree with theoretical models, and when baryons are included in simulations, our SIDM models substantially increase the central density of galaxy cluster cores compared to full-physics simulations using collisionless dark matter. SIDM subhalo suppression in full-physics simulations is milder compared to the one found in dark matter only simulations, because of the cuspier baryionic potential that prevent subhalo disruption. Moreover SIDM with small-angle scattering significantly suppress a larger number of subhaloes compared to large angle scattering SIDM models. Additionally, SIDM models generate a broader range of subhalo concentration values, including a tail of more diffuse subhaloes in the outskirts of galaxy clusters and a population of more compact subhaloes in the cluster cores., Comment: 14 pages, 15 figures, abstract abridged to fit arXiv character limit, submitted to Astronomy and Astrophysics

A visually rich document (VRD) utilizes visual features along with linguistic cues to disseminate information. Training a custom extractor that identifies named entities from a document requires a large number of instances of the target document type annotated at textual and visual modalities. This is an expensive bottleneck in enterprise scenarios, where we want to train custom extractors for thousands of different document types in a scalable way. Pre-training an extractor model on unlabeled instances of the target document type, followed by a fine-tuning step on human-labeled instances does not work in these scenarios, as it surpasses the maximum allowable training time allocated for the extractor. We address this scenario by proposing a Noise-Aware Training method or NAT in this paper. Instead of acquiring expensive human-labeled documents, NAT utilizes weakly labeled documents to train an extractor in a scalable way. To avoid degradation in the model's quality due to noisy, weakly labeled samples, NAT estimates the confidence of each training sample and incorporates it as uncertainty measure during training. We train multiple state-of-the-art extractor models using NAT. Experiments on a number of publicly available and in-house datasets show that NAT-trained models are not only robust in performance -- it outperforms a transfer-learning baseline by up to 6% in terms of macro-F1 score, but it is also more label-efficient -- it reduces the amount of human-effort required to obtain comparable performance by up to 73%.

The Wide-field Spectroscopic Telescope (WST) is proposed as a new facility dedicated to the efficient delivery of spectroscopic surveys. This white paper summarises the initial concept as well as the corresponding science cases. WST will feature simultaneous operation of a large field-of-view (3 sq. degree), a high multiplex (20,000) multi-object spectrograph (MOS) and a giant 3x3 sq. arcmin integral field spectrograph (IFS). In scientific capability these requirements place WST far ahead of existing and planned facilities. Given the current investment in deep imaging surveys and noting the diagnostic power of spectroscopy, WST will fill a crucial gap in astronomical capability and work synergistically with future ground and space-based facilities. This white paper shows that WST can address outstanding scientific questions in the areas of cosmology; galaxy assembly, evolution, and enrichment, including our own Milky Way; origin of stars and planets; time domain and multi-messenger astrophysics. WST's uniquely rich dataset will deliver unforeseen discoveries in many of these areas. The WST Science Team (already including more than 500 scientists worldwide) is open to the all astronomical community. To register in the WST Science Team please visit https://www.wstelescope.com/for-scientists/participate, Comment: 194 pages, 66 figures. Comments are welcome (wstelescope@gmail.com)

Multiband superconductors have featured one of the main challenges to achieve a comprehensive understanding of unconventional superconductivity. Here, the multiband character is studied separately as orbital and sublattice degrees of freedom, as they have different effects for the superconducting and magnetic or charge orders. We build on the framework of the matrix random-phase approximation (RPA), which accounts for the RPA Feynman diagrams and also vertex corrections, to treat the electron-electron interactions in an off-site degenerate Hubbard model. As a result, systems without a sublattice degree of freedom tend to be dominated by spin fluctuations, while systems with multiple sublattice sites and orbitals have the charge fluctuations favored. Finally, we explicitly demonstrate that the known suppression of the superconducting pairing strength $\lambda$ by spin fluctuations from repulsive interactions at zero momentum transfer $\boldsymbol{q}$ is countered by the finite-$\boldsymbol{q}$ pairing, which always improves $\lambda$., Comment: 10 + 6 pages, 2 figures

Context. Weak gravitational lensing offers a powerful method to investigate the projected matter density distribution within galaxy clusters, granting crucial insights into the broader landscape of dark matter on cluster scales. Aims. In this study, we make use of the large photometric galaxy cluster data set derived from the publicly available Third Data Release of the Kilo-Degree Survey, along with the associated shear signal. Our primary objective is to model the peculiar sharp transition in the cluster profile slope, that is what is commonly referred to as the splashback radius. The data set under scrutiny includes 6962 galaxy clusters, selected by AMICO - an optimised detection algorithm of galaxy clusters - on the KiDS-DR3 data, in the redshift range of 0.1 < z < 0.6, all observed at a signal-to-noise ratio greater than 3.5. Methods. Employing a comprehensive Bayesian analysis, we model the stacked excess surface mass density distribution of the clusters. We adopt a model from recent results on numerical simulations that capture the dynamics of both orbiting and infalling materials, separated by the region where the density profile slope undergoes a pronounced deepening. Results. We find that the adopted profile successfully characterizes the cluster masses, consistent with previous works, and models the deepening of the slope of the density profiles measured with weak-lensing data up to the outskirts. Moreover, we measure the splashback radius of galaxy clusters and show that its value is close to the radius within which the enclosed overdensity is 200 times the mean matter density of the Universe, while theoretical models predict a larger value consistent with a low accretion rate. This points to a potential bias of optically selected clusters preferentially characterized by a high density at small scales compared to a pure mass-selected cluster sample., Comment: Accepted for publication in A&A. Added a discussion about prior parameters, as suggested by the reviewer. arXiv admin note: text overlap with arXiv:2103.05653

According to a particular interpretation of quantum mechanics, the causal role of human consciousness in the measuring process is called upon to solve a foundational problem called the "measurement problem". Traditionally, this interpretation is tied up with the metaphysics of substance dualism. As such, this interpretation of quantum mechanics inherits the dualist's mind-body problem. Our working hypothesis is that a process-based approach to the consciousness causes collapse interpretation (CCCI) -- leaning on Whitehead's solution to the mind-body problem -- offers a better metaphysical understanding of consciousness and its role in interpreting quantum mechanics. This article is the kickoff for such a research program in the metaphysics of science., Comment: Forthcoming in Manuscrito vol. 47, n.1, 2024. Special issue: "Scientific Process Ontology and Metaphysics". Url: https://www.scielo.br/j/man/i/2024.v47n1

We study interaction-mediated magnetism on the surface of ABC-multilayer graphene driven by its zero-energy topological flat bands. Using the random-phase approximation we treat onsite Hubbard repulsion and find multiple competing magnetic states, due to both intra- and inter-valley scattering, with the latter causing an enlarged magnetic unit cell. At half-filling and when the Hubbard repulsion is weak, we observe two different ferromagnetic orders. Once the Hubbard repulsion becomes more realistic, new ferrimagnetic orders arise with distinct incommensurate intra- or inter-valley scattering vectors depending on interaction strength and doping, leading to a multitude of competing magnetic states., Comment: Main text: 7 pages and 4 figures, Supplementary Material: 11 pages and 8 figures

Quantum turbulence indicators in dipolar Bose-Einstein condensed fluids, following emissions of vortex-antivortex pairs generated by a circularly moving detuned laser, are being provided by numerical simulations of the corresponding quasi-two-dimensional Gross-Pitaevskii formalism with repulsive contact interactions combined with tunable dipole-dipole strength. The critical velocities of two variants of a circularly moving obstacle are determined and analyzed for vortex-antivortex nucleation in the form of regular and cluster emissions. The turbulent dynamical behavior is predicted to follow closely the initial emission of vortex-antivortex pairs, relying on the expected Kolmogorov's classical scaling law, which is verified by the spectral analysis of the incompressible part of the kinetic energy. Within our aim to provide further support in the up-to-now investigations of quantum turbulence, which have been focused on non-dipolar Bose-Einstein condensates, we emphasize the role of dipole-dipole interactions in the fluid dynamics.

We present a new galaxy cluster search in the COSMOS field through the use of the Adaptive Matched Identifier of Clustered Objects (AMICO). We produced a new cluster and group catalogue up to $z=2$, by performing an innovative application of AMICO with respect to previous successful applications to wide-field surveys, in terms of depth (down to $r < 26.7$), small area covered ($1.69 deg^2$ of unmasked area) and redshift extent. This sample, and the comparative analysis we performed with the X-rays, allowed for the calibration of mass-proxy scaling relations up to $z=2$ and down to less than $10^{13} M_{sun}$ and constitutes the base for the refinement of the cluster model for future applications of AMICO, like the analysis of upcoming Euclid data. AMICO is based on an optimal linear matched filter and detects clusters in photometric galaxy catalogues using galaxy location, photometric redshift and, in the simplest case, one galaxy property. We used one magnitude as galaxy property, avoiding explicit use of galaxy colour, and performed 3 independent runs in the r, Y and H bands using both COSMOS2020 and COSMOS2015 galaxy catalogues. The final catalogue resulting from matching the results of the three runs contains 1269 and 666 candidate clusters with $S/N >3.0$ and $>3.5$, respectively. Most of the unmatched ones have $S/N <3.5$ which can be chosen as cut for a more robust sample. We assigned X-ray properties to our detections via matching with a public X-ray group sample and by estimating, for unmatched detections, X-ray properties at the location of AMICO candidates based on Chandra+XMM-Newton data. 622 are the candidates with X-ray flux estimate. This large sample allowed for the calibration of the scaling relations between AMICO mass-proxies and X-ray mass and the study of their redshift dependence for the selection of the most stable photometric bands., Comment: 16 pages, 15 figures, 3 tables, submitted to Astronomy & Astrophysics (A&A)

Successful data-driven science requires complex data engineering pipelines to clean, transform, and alter data in preparation for machine learning, and robust results can only be achieved when each step in the pipeline can be justified, and its effect on the data explained. In this framework, our aim is to provide data scientists with facilities to gain an in-depth understanding of how each step in the pipeline affects the data, from the raw input to training sets ready to be used for learning. Starting from an extensible set of data preparation operators commonly used within a data science setting, in this work we present a provenance management infrastructure for generating, storing, and querying very granular accounts of data transformations, at the level of individual elements within datasets whenever possible. Then, from the formal definition of a core set of data science preprocessing operators, we derive a provenance semantics embodied by a collection of templates expressed in PROV, a standard model for data provenance. Using those templates as a reference, our provenance generation algorithm generalises to any operator with observable input/output pairs. We provide a prototype implementation of an application-level provenance capture library to produce, in a semi-automatic way, complete provenance documents that account for the entire pipeline. We report on the ability of our implementations to capture provenance in real ML benchmark pipelines and over TCP-DI synthetic data. We finally show how the collected provenance can be used to answer a suite of provenance benchmark queries that underpin some common pipeline inspection questions, as expressed on the Data Science Stack Exchange., Comment: 37 pages, 27 figures, submitted to a journal

By studying the dynamic stability of Bose-Einstein condensed binary mixtures trapped on the surface of an ideal two-dimensional spherical bubble, we show how the Rabi coupling between the species can modulate the interactions leading to parametric resonances. In this spherical geometry, the discrete unstable angular modes drive both phase separations and spatial patterns, with Faraday waves emerging and coexisting with an immiscible phase. Noticeable is the fact that, in the context of discrete kinetic energy spectrum, the only parameters to drive the emergence of Faraday waves are the $s-wave$ contact interactions and the Rabi coupling. Once analytical solutions for population dynamics are obtained, the stability of homogeneous miscible species is investigated through Bogoliubov-de Gennes and Floquet methods, with predictions being analysed by full numerical solutions applied to the corresponding time-dependent coupled formalism., Comment: 17 pages, 15 figures

In this study, we investigate a recent finding based on strong lensing observations, which suggests that the sub-halos observed in clusters exhibit greater compactness compared to those predicted by $\Lambda$CDM simulations. To address this discrepancy, we performed a comparative analysis by comparing the cumulative mass function of sub-halos and the $M_{\text{sub}}$-$V_{\text{circ}}$ relation between observed clusters and 324 simulated clusters from The Three Hundred project, focusing on re-simulations using GADGET-X and GIZMO-SIMBA baryonic models. The sub-halos' cumulative mass function of the GIZMO-SIMBA simulated clusters agrees with observations, while the GADGET-X simulations exhibit discrepancies in the lower sub-halo mass range possibly due to its strong SuperNova feedback. Both GADGET-X and GIZMO-SIMBA simulations demonstrate a redshift evolution of the sub-halo mass function and the $V_{max}$ function, with slightly fewer sub-halos observed at lower redshifts. Neither the GADGET-X nor GIZMO-SIMBA(albeit a little closer) simulated clusters' predictions for the $M_{\text{sub}}$-$V_{\text{circ}}$ relation align with the observational result. Further investigations on the correlation between sub-halo/halo properties and the discrepancy in the $M_{\text{sub}}$-$V_{\text{circ}}$ relation reveals that the sub-halo's half mass radius and galaxy stellar age, the baryon fraction and sub-halo distance from the cluster's centre, as well as the halo relaxation state play important roles on this relation. Nevertheless, we think it is still challenging in accurately reproducing the observed $M_{\text{sub}}$-$V_{\text{circ}}$ relation in our current hydrodynamic cluster simulation under the standard $\Lambda$CDM cosmology., Comment: see the companion paper, Meneghetti et al. (2023), on today's arxiv list

Previous studies have revealed that the estimated probability of galaxy-galaxy strong lensing in observed galaxy clusters exceeds the expectations from the $\Lambda$ Cold Dark Matter cosmological model by one order of magnitude. We aim to understand the origin of this excess by analyzing a larger set of simulated galaxy clusters and investigating how the theoretical expectations vary under different adopted prescriptions and numerical implementations of star formation and feedback in simulations. We perform a ray-tracing analysis of 324 galaxy clusters from the Three Hundred project, comparing the Gadget-X and Gizmo-Simba runs. These simulations, which start from the same initial conditions, are performed with different implementations of hydrodynamics and galaxy formation models tailored to match different observational properties of the Intra-Cluster-Medium and cluster galaxies. We find that galaxies in the Gizmo-Simba simulations develop denser stellar cores than their Gadget-X counterparts. Consequently, their probability for galaxy-galaxy strong lensing is higher by a factor of $\sim 3$. This increment is still insufficient to fill the gap with observations, as a discrepancy by a factor $\sim 4$ still persists. In addition, we find that several simulated galaxies have Einstein radii that are too large compared to observations. We conclude that a persistent excess of galaxy-galaxy strong lensing exists in observed galaxy clusters. The origin of this discrepancy with theoretical predictions is still unexplained in the framework of the cosmological hydrodynamical simulations. This might signal a hitherto unknown issue with either the simulation methods or our assumptions regarding the standard cosmological model., Comment: 6 pages, 2 figures, accepted for publication on A&A Letters. See companion paper Srivastava et al. (2023)

Magic-angle twisted bilayer graphene (MATBG) has been extensively explored both theoretically and experimentally as a suitable platform for a rich and tunable phase diagram that includes ferromagnetism, charge order, broken symmetries, and unconventional superconductivity. In this work, we investigate the intricate interplay between long-range electron-electron interactions, spin fluctuations, and superconductivity in MATBG. By employing a low-energy model for MATBG that captures the correct shape of the flat bands, we explore the effects of short- and long-range interactions on spin fluctuations and their impact on the superconducting (SC) pairing vertex in the Random Phase Approximation (RPA). We find that the SC state is notably influenced by the strength of long-range Coulomb interactions. Interestingly, our RPA calculations indicate that there is a regime where the system can traverse from a magnetic phase to the SC phase by \emph{increasing} the relative strength of long-range interactions compared to the on-site ones. These findings underscore the relevance of electron-electron interactions in shaping the intriguing properties of MATBG and offer a pathway for designing and controlling its SC phase., Comment: Revised and expanded version. 11 pages, 7 figures

We constrain the $\Lambda$CDM cosmological parameter $\sigma_{8}$ by applying the extreme value statistics for galaxy cluster mass on the AMICO KiDS-DR3 catalog. We sample the posterior distribution of the parameters by considering the likelihood of observing the largest cluster mass value in a sample of $N_{\textrm{obs}} = 3644$ clusters with intrinsic richness $\lambda^{*} > 20$ in the redshift range $z\in[0.10, 0.60]$. We obtain $\sigma_{8}=0.90_{-0.18}^{+0.20}$, consistent within $1\sigma$ with the measurements obtained by the Planck collaboration and with previous results from cluster cosmology exploiting AMICO KiDS-DR3. The constraints could improve by applying this method to forthcoming missions, such as $\textit{Euclid}$ and LSST, which are expected to deliver thousands of distant and massive clusters., Comment: 11 pages, 9 figures, 4 tables

Reinforcement learning from human feedback (RLHF) is a technique for training AI systems to align with human goals. RLHF has emerged as the central method used to finetune state-of-the-art large language models (LLMs). Despite this popularity, there has been relatively little public work systematizing its flaws. In this paper, we (1) survey open problems and fundamental limitations of RLHF and related methods; (2) overview techniques to understand, improve, and complement RLHF in practice; and (3) propose auditing and disclosure standards to improve societal oversight of RLHF systems. Our work emphasizes the limitations of RLHF and highlights the importance of a multi-faceted approach to the development of safer AI systems.

Although a superconductor has no DC losses, a superconducting system does have significant losses, especially when it comes to power supply. Here, we study two different power supply systems. The first, a conventional one, consists of a transformer and a diode bridge operating at room temperature, plus current leads that allow the current to flow from the room-temperature medium to the cryogenic medium. The second consists of a transformer with a superconducting secondary winding, combined with a diode bridge operating at cryogenic temperature, thus dispensing with the need for current leads. We are experimentally comparing the performance of conventional and superconducting transformers, as well as the performance of a diode bridge at ambient and cryogenic temperatures. Our results indicate that the prototype superconducting transformer developed has lower winding resistance and secondary leakage inductance than the conventional transformer. In addition, we found that only certain diodes are suitable for operation at cryogenic temperatures. Finally, the diode bridge made from adapted diodes shows reduced losses at cryogenic temperature. This experimental work is the first step towards the realization of a complete power supply system for a superconducting device., Comment: in French language, Symposium de Genie Electrique (SGE 2023), Jul 2023, Lille, France

The effect of two- and three-body interactions on the modulation instability (MI) domain formation of a spin-orbit (SO) and Rabi-coupled Bose-Einstein condensate is studied within a quasi-one-dimensional model. To this aim, we perform numerical and analytical investigations of the associated dispersion relations derived from the corresponding coupled Gross-Pitaevskii equation. The interplay between the linear (SO and Rabi) couplings with the nonlinear cubic-quintic interactions are explored in the mixture, considering miscible and immiscible configurations, with a focus on the impact in the analysis of experimental realizations with general binary coupled systems, in which nonlinear interactions can be widely varied together with linear couplings., Comment: 11 pages, 10 figures

In the anti-Stokes excitation of trivalent rare-earth ions (RE3+), the excitation photons energy is smaller than that of a given absorption transition, and the energy mismatch can be compensated by phonons annihilation from the host lattice. Since the phonon occupation number increases with temperature, heating the system generally increases the efficiency of anti-Stokes excitation. Here, we exploited the intrinsic heating associated with light-to-heat conversion in the interaction of excitation laser light with metallic nanoparticles (Ag or Au) on the surface of submicrometric particles of NdxY1.00-xAl3(BO3)4 (x = 0.10, 0.20, and 1.00) in order to enhance the efficiency of the anti-Stokes excitation at 1064 nm. Several upconversion emissions are observed from 600 nm to 880 nm, the most intense being at 750 nm due to the Nd3+ transition {4F7/2, 4S3/2} - 4I9/2. Giant enhancements are demonstrated, when compared to undecorated NdxY1.00-xAl3(BO3)4 particles. The present results can be expanded to other luminescent materials as well as excitation wavelengths.