Search

Sparse AutoEnocders (SAEs) have recently been employed as an unsupervised approach for understanding the inner workings of Large Language Models (LLMs). They reconstruct the model's activations with a sparse linear combination of interpretable features. However, training SAEs is computationally intensive, especially as models grow in size and complexity. To address this challenge, we propose a novel training strategy that reduces the number of trained SAEs from one per layer to one for a given group of contiguous layers. Our experimental results on Pythia 160M highlight a speedup of up to 6x without compromising the reconstruction quality and performance on downstream tasks. Therefore, layer clustering presents an efficient approach to train SAEs in modern LLMs.

The Central Molecular Zone (CMZ) is the largest reservoir of dense molecular gas in the Galaxy and is heavily obscured in the optical and near-IR. We present an overview of the far-IR dust continuum, where the molecular clouds are revealed, provided by Herschel in the inner 40\deg($|l| <$ 20\deg) of the Milky Way with a particular focus on the CMZ. We report a total dense gas ($N$(H$_2$) $> 10^{23}$ cm$^{-2}$) CMZ mass of M=$2\substack{+2 \\ -1} \times 10^7$ M$_{\odot}$ and confirm that there is a highly asymmetric distribution of dense gas, with about 70-75% at positive longitudes. We create and publicly release complete fore/background-subtracted column density and dust temperature maps in the inner 40\deg ($|l| <$ 20\deg) of the Galaxy. We find that the CMZ clearly stands out as a distinct structure, with an average mass per longitude that is at least $3\times$ higher than the rest of the inner Galaxy contiguously from 1.8\deg $> \ell >$ -1.3\deg. This CMZ extent is larger than previously assumed, but is consistent with constraints from velocity information. The inner Galaxy's column density peaks towards the SgrB2 complex with a value of about 2 $\times$ 10$^{24}$ cm$^{-2}$, and typical CMZ molecular clouds are about N(H$_2$)=10$^{23}$ cm$^{-2}$. Typical CMZ dust temperatures range from about $12-35$ K with relatively little variation. We identify a ridge of warm dust in the inner CMZ that potentially traces the base of the northern Galactic outflow seen with MEERKAT., Comment: Submitted to ApJ, 16 pages, project website: https://centralmolecularzone.github.io/3D_CMZ/

The Central Molecular Zone (CMZ) is the way station at the heart of our Milky Way Galaxy, connecting gas flowing in from Galactic scales with the central nucleus. Key open questions remain about its 3-D structure, star formation properties, and role in regulating this gas inflow. In this work, we identify a hierarchy of discrete structures in the CMZ using column density and dust temperature maps from Paper I (Battersby et al., submitted). We calculate the physical ($N$(H$_2$), $T_{\rm{dust}}$, mass, radius) and kinematic (HNCO, HCN, and HC$_3$N moments) properties of each structure as well as their bolometric luminosities and star formation rates (SFRs). We compare these properties with regions in the Milky Way disk and external galaxies. We perform power-law fits to the column density probability distribution functions (N-PDFs) of the inner 100 pc, SgrB2, and the outer 100 pc of the CMZ as well as several individual molecular cloud structures and find generally steeper power-law slopes ($-9<\alpha<-2$) compared with the literature ($-6 < \alpha < -1$). We find that individual CMZ structures require a large external pressure ($P_e$/k$_B$ $> 10^{7-9}$ K cm$^{-3}$) to be considered bound. Despite the fact that the CMZ overall is well below the Gao-Solomon dense gas star-formation relation (and in modest agreement with the Schmidt-Kennicutt relation), individual structures on the scale of molecular clouds generally follow these star-formation relations and agree well with other Milky Way and extragalactic regions., Comment: Submitted to ApJ, 22 pages, project website: https://centralmolecularzone.github.io/3D_CMZ/

We present a fully implicit formulation of coupled fluid flow and geomechanics for fluid injection/withdrawal in fractured reservoirs in the context of CO2storage. Utilizing a Galerkin finite-element approach, both flow and poroelasticity equations are discretized on a shared three-dimensional mesh. The fluid flow is assumed to be single-phase. The hydraulic behaviour of fractures is represented through a double-nodes flow element, which allows to efficiently model longitudinal and transversal fracture permeabilities. In addressing the mechanical subproblem, fractures are explicitly modelled using cohesive elements to account for contact, friction and opening phenomena. The nonlinear set of equations is solved implicitly through an iterative partitioned conjugate gradient procedure, extending its traditional application to continuous problems to those involving explicit discontinuities such as faults and fractures. The model's accuracy is verified against analytical solutions for different geomechanical problems, notably for the growth of a frictional slip rupture along a fault due to fluid injection. Such a particularly challenging benchmark for a critically stressed fault is here reproduced for the first time by a finite-element based scheme. The capabilities of the developed parallel solver are then illustrated through a scenario involving CO2 injection into a faulted aquifer. The original solver code, tutorials, and data visualization routines are publicly accessible.

The quest for radio signals from technologically-advanced extraterrestrial intelligence has traditionally concentrated on the vicinity of 1.4 GHz. In this paper, we extend the search to unprecedented territories, detailing our extensive observations at 6 GHz and initiating the first-ever survey at 18 GHz with the Sardinia Radio Telescope (SRT). Our strategy entailed rigorous observation sessions, totaling 36 hours, directed towards the Galactic Center and 72 selected TESS targets-making this the most comprehensive high-frequency technosignature search to date. Our narrowband signal search found no definitive evidence of drifting signals that could suggest an extraterrestrial origin from the surveyed regions. Nevertheless, our efforts have enabled us to set new constraints on the presence of radio emissions from approximately $5\times 10^{5}$ stars, establishing an isotropic radiated power limit of $1.8\times 10^{19} W$. We also provide a comparative analysis of the 'hits' recorded across both frequencies to highlight the significance of pursuing technosignature searches at higher frequencies, where the spectral landscape is less congested and more conducive to detection., Comment: Submitted to Acta Astronautica

During the first charge-discharge cycle, silicon-based batteries show an important capacity loss because of the formation of the solid electrolyte interphase (SEI) and morphological changes due to expansion-contraction sequence upon alloying. To understand this first-cycle irreversibility, quantitative methods are needed to characterize the chemical environment of silicon and lithium in the bulk of the cycled electrodes. Here we report a methodology based on multi-edge X-ray Raman Scattering performed on model silicon electrodes prepared in fully lithiated and fully delithiated states after the first cycle. The spectra were recorded at the C, O, F and Li K edges, as well as Si L2,3 edge. They were analysed using linear combinations of both experimental and computed reference spectra. We used prototypical SEI compounds as Li2CO3, LiF and LiPF6, as well as electrode constituents as binder and conductive carbon, cristalline Si, native SiO2,LixSi phases (x being the lithiation index) to identify the main species, isolate their relative contributions, and quantitatively evaluate the proportions of organic and inorganic products. We find that 30% of the carbonates formed in the SEI during the lithiation are dissolved on delithiation, and that part of the Li15Si4 alloys remain present after delithiation. By combining electrochemical analysis and XRS results, we identify that 17% of the lithium lost in the first cycle is trapped in disconnected silicon particles, while 30% form a fluorine-rich stable SEI and 53% a carbonate-rich partially-dissolvable SEI. These results pave the way to systematic, reference data-informed, and modelling assisted studies of SEI characteristics in the bulk of electrodes prepared under controlled state-of-charge and state-of-health conditions.

We derive the analog of the Tolman-Oppenheimer-Volkoff equation in conformal Killing gravity in a static spherically symmetric spacetime, sourced by perfect fluid matter. It differs from the original by `dark terms' associated to the conformal Killing tensor. Then we study the junction conditions for a sphere of perfect fluid in the Conformal Killing Gravity vacuum (dark fluid environment), and solve the equations for the sphere with uniform matter density., Comment: 11 pages, 2 figures

Developing sophisticated control architectures has endowed robots, particularly humanoid robots, with numerous capabilities. However, tuning these architectures remains a challenging and time-consuming task that requires expert intervention. In this work, we propose a methodology to automatically tune the gains of all layers of a hierarchical control architecture for walking humanoids. We tested our methodology by employing different gradient-free optimization methods: Genetic Algorithm (GA), Covariance Matrix Adaptation Evolution Strategy (CMA-ES), Evolution Strategy (ES), and Differential Evolution (DE). We validated the parameter found both in simulation and on the real ergoCub humanoid robot. Our results show that GA achieves the fastest convergence (10 x 10^3 function evaluations vs 25 x 10^3 needed by the other algorithms) and 100% success rate in completing the task both in simulation and when transferred on the real robotic platform. These findings highlight the potential of our proposed method to automate the tuning process, reducing the need for manual intervention.

This work proposes a robust data-driven tube-based zonotopic predictive control (TZPC) approach for discrete-time linear systems, designed to ensure stability and recursive feasibility in the presence of bounded noise. The proposed approach consists of two phases. In an initial learning phase, we provide an over-approximation of all models consistent with past input and noisy state data using zonotope properties. Subsequently, in a control phase, we formulate an optimization problem, which by integrating terminal ingredients is proven to be recursively feasible. Moreover, we prove that implementing this data-driven predictive control approach guarantees robust exponential stability of the closed-loop system. The effectiveness and competitive performance of the proposed control strategy, compared to recent data-driven predictive control methods, are illustrated through numerical simulations., Comment: Accepted for presentation and publication at the 63rd IEEE Conference on Decision and Control (CDC)

The exponential growth in data sizes and storage costs has brought considerable challenges to the data science community, requiring solutions to run learning methods on such data. While machine learning has scaled to achieve predictive accuracy in big data settings, statistical inference and uncertainty quantification tools are still lagging. Priority scientific fields collect vast data to understand phenomena typically studied with statistical methods like regression. In this setting, regression parameter estimation can benefit from efficient computational procedures, but the main challenge lies in computing error process parameters with complex covariance structures. Identifying and estimating these structures is essential for inference and often used for uncertainty quantification in machine learning with Gaussian Processes. However, estimating these structures becomes burdensome as data scales, requiring approximations that compromise the reliability of outputs. These approximations are even more unreliable when complexities like long-range dependencies or missing data are present. This work defines and proves the statistical properties of the Generalized Method of Wavelet Moments with Exogenous variables (GMWMX), a highly scalable, stable, and statistically valid method for estimating and delivering inference for linear models using stochastic processes in the presence of data complexities like latent dependence structures and missing data. Applied examples from Earth Sciences and extensive simulations highlight the advantages of the GMWMX.

We use data from the ALMA Evolutionary Study of High Mass Protocluster Formation in the Galaxy (ALMAGAL) survey to study 100 ALMAGAL regions at $\sim$ 1 arsecond resolution located between $\sim$ 2 and 6 kpc distance. Using ALMAGAL $\sim$ 1.3mm line and continuum data we estimate flow rates onto individual cores. We focus specifically on flow rates along filamentary structures associated with these cores. Our primary analysis is centered around position velocity cuts in H$_2$CO (3$_{0,3}$ - 2$_{0,2}$) which allow us to measure the velocity fields, surrounding these cores. Combining this work with column density estimates we derive the flow rates along the extended filamentary structures associated with cores in these regions. We select a sample of 100 ALMAGAL regions covering four evolutionary stages from quiescent to protostellar, Young Stellar Objects (YSOs), and HII regions (25 each). Using dendrogram and line analysis, we identify a final sample of 182 cores in 87 regions. In this paper, we present 728 flow rates for our sample (4 per core), analysed in the context of evolutionary stage, distance from the core, and core mass. On average, for the whole sample, we derive flow rates on the order of $\sim$10$^{-4}$ M$_{sun}$yr$^{-1}$ with estimated uncertainties of $\pm$50%. We see increasing differences in the values among evolutionary stages, most notably between the less evolved (quiescent/protostellar) and more evolved (YSO/HII region) sources. We also see an increasing trend as we move further away from the centre of these cores. We also find a clear relationship between the flow rates and core masses $\sim$M$^{2/3}$ which is in line with the result expected from the tidal-lobe accretion mechanism. Overall, we see increasing trends in the relationships between the flow rate and the three investigated parameters; evolutionary stage, distance from the core, and core mass., Comment: 11 pages, 11 figures, accepted for publication in A&A

(Abridged) Observational surveys of entire star-forming regions have provided evidence of power-law correlations between the disc properties and the stellar mass, especially the disc mass (${M_d \propto M_*}^{\lambda_m}$) and the accretion rate ($\dot M \propto {M_*}^{\lambda_{acc}}$). Whether the secular disc evolution affects said correlations is still debated: while the purely viscous scenario has been probed, other mechanisms could impact differently. We study the evolution of the slopes $\lambda_m$ and $\lambda_{acc}$ in the wind-driven and hybrid case and compare it to the viscous prediction, using a combination of analytical calculations and numerical simulations (performed with the 1D population synthesis code Diskpop, that we also present and release). Assuming $M_d(0) \propto {M_*}^{\lambda_{m, 0}}$ and $\dot M(0) \propto {M_*}^{\lambda_{acc, 0}}$ as initial conditions, we find that viscous and hybrid accretion preserve the shape of the correlations and evolve their slope; on the other hand, MHD winds change the shape of the correlations, bending them according to the scaling of the accretion timescale with the stellar mass. We also show how a spread in the initial conditions conceals this behaviour. We then analyse the impact of disc dispersal, and find that the currently available sample sizes ($\sim 30$ discs at 5 Myr) introduce stochastic oscillations in the slopes evolution, which dominate over the physical signatures. Increasing the sample size could mitigate this issue: $\sim 140$ discs at 5 Myr, corresponding to the complete Upper Sco sample, would give small enough error bars to use the evolution of the slopes as a proxy for the driving mechanism of disc evolution. Finally, we discuss how the observational claim of steepening slopes necessarily leads to an initially steeper $M_d - M_*$ correlation with respect to $\dot M - M_*$., Comment: 14 pages, 5 figures and 3 tables (plus Appendix). Accepted for publication in A&A. Includes Diskpop and popcorn software release

Stellar blends, where two or more stars appear blended in an image, pose a significant visualization challenge in astronomy. Traditionally, distinguishing these blends from single stars has been costly and resource-intensive, involving sophisticated equipment and extensive expert analysis. This is especially problematic for analyzing the vast data volumes from surveys, such as Legacy Survey of Space and Time (LSST), Sloan Digital Sky Survey (SDSS), Dark Energy Spectroscopic Instrument (DESI), Legacy Imaging Survey and the Zwicky Transient Facility (ZTF). To address these challenges, we apply different normalizations and data embeddings on low resolution images of single stars and stellar blends, which are passed as inputs into machine learning methods and to a computationally efficient Gaussian process model (MuyGPs). MuyGPs consistently outperforms the benchmarked models, particularly on limited training data. Moreover, MuyGPs with $r^\text{th}$ root local min-max normalization achieves 83.8% accuracy. Furthermore, MuyGPs' ability to produce confidence bands ensures that predictions with low confidence can be redirected to a specialist for efficient human-assisted labeling.

To model rupture dynamics, a friction law must be assumed. Commonly used constitutive laws for modeling friction include slip-weakening laws which are characterized by a drop from static to dynamic frictional stress. Within this framework, the prevailing understanding asserts that the frictional behavior is solely controlled by the fracture energy -- the area beneath the frictional stress versus the cumulative slip curve. In particular, it is claimed that the curve's shape itself has no influence on the system's response. Here we perform fully dynamic rupture simulations to challenge prevailing beliefs by demonstrating that the constitutive law shape exerts an intimate control over rupture profiles. For a consistent fracture energy but varying constitutive law shapes, the velocity profile is different: each abrupt slope transition leads to the localization of a distinct velocity peak. For example, in the case of a bilinear slip-weakening law featuring two different slopes, the rupture exhibits two distinct velocity peaks. This phenomenon arises from the transition between a constant weakening rate to another. However, this distinction does not seem to influence how a rupture responds to a stress barrier or the cumulative radiated energy emitted. These results are derived through two separate numerical schemes (spectral boundary integral and finite element methods) ensuring their independence from the computational approach employed., Comment: 12 pages, 7 figures

In this contribution, we aim to summarise the efforts of the Italian SKA scientific community in conducting surveys of star-forming regions within our Galaxy, in the development of astrochemical research on protostellar envelopes and disks, and in studying the planet formation process itself. The objective is dual: Firstly, to investigate the accumulation and development of dust throughout the formation of planets, and secondly, to chemically examine protoplanetary disks and protostellar envelopes by studying heavy molecules, such as chains and rings containing over seven carbon atoms, which exhibit significantly reduced strength at millimeter wavelengths., Comment: Mem. S.A.It. in press

The Extremely Large Telescopes (ELTs), thanks to their large apertures and cutting-edge Multi-Conjugate Adaptive Optics (MCAO) systems, promise to deliver sharper and deeper data even than the JWST. SHARP is a concept study for a near-IR (0.95-2.45 $\mu$m) spectrograph conceived to fully exploit the collecting area and the angular resolution of the upcoming generation of ELTs. In particular, SHARP is designed for the 2nd port of MORFEO@ELT. Composed of a Multi-Object Spectrograph, NEXUS, and a multi-Integral Field Unit, VESPER, MORFEO-SHARP will deliver high angular ($\sim$30 mas) and spectral (R$\simeq$300, 2000, 6000, 17000) resolution, outperforming NIRSpec@JWST (100 mas). SHARP will enable studies of the nearby Universe and the early Universe in unprecedented detail. NEXUS is fed by a configurable slit system deploying up to 30 slits with $\sim$2.4 arcsec length and adjustable width, over a field of about 1.2"$\times$1.2" (35 mas/pix). Each slit is fed by an inversion prism able to rotate by an arbitrary angle the field that can be seen by the slit. VESPER is composed of 12 probes of 1.7"$\times$1.5" each (spaxel 31 mas) probing a field 24"$\times$70". SHARP is conceived to exploit the ELTs apertures reaching the faintest flux and the sharpest angular resolution by joining the sensitivity of NEXUS and the high spatial sampling of VESPER to MORFEO capabilities. This article provides an overview of the scientific design drivers, their solutions, and the resulting optical design of the instrument achieving the required optical performance., Comment: Proceedings of the SPIE Astronomical Telescopes and Instrumentation 2024, Volume 13096, Paper No. 130965I, 11 pp, 11 figs

We identify an anisotropic divergence-free conformal Killing tensor $K_{jl}$ for static spherically symmetric spacetimes, and write the conformal Killing gravity equations as Einstein equations augmented by this tensor. The field equations are of second order: this fact allows for analytic solutions and considerably simplifies the derivation of results of previous studies based on the original Harada equations. In particular, we prove the equivalence of the known third order field equations, with the second order ones obtained by us in the conformal Killing parametrization. The structure of the Ricci tensor and of the conformal Killing tensor are compatible with both anisotropic fluid sources and (non)-linear electrodynamics. We reobtain covariantly and in simple steps the general static spherical solutions for vacuum and linear electrodynamics. Moreover we recover the purely magnetic Lagrangian functions that induce metrics of interest for black holes., Comment: Final version (typos in eqs 19, 20 corrected)

We test the null hypothesis that two parameters $(\mu_1,\mu_2)$ have the same sign, assuming that (asymptotically) normal estimators $(\hat{\mu}_1,\hat{\mu}_2)$ are available. Examples of this problem include the analysis of heterogeneous treatment effects, causal interpretation of reduced-form estimands, meta-studies, and mediation analysis. A number of tests were recently proposed. We recommend a test that is simple and rejects more often than many of these recent proposals. Like all other tests in the literature, it is conservative if the truth is near $(0,0)$ and therefore also biased. To clarify whether these features are avoidable, we also provide a test that is unbiased and has exact size control on the boundary of the null hypothesis, but which has counterintuitive properties and hence we do not recommend. We use the test to improve p-values in Kowalski (2022) from information contained in that paper's main text and to establish statistical significance of some key estimates in Dippel et al. (2021)., Comment: Minor update that mostly reflects learning of new relevant references. No change to results

The chiral anomaly, a hallmark of chiral spin-1/2 Weyl fermions, is an imbalance between left- and right-moving particles that underpins both high and low energy phenomena, including particle decay and negative longitudinal magnetoresistance in Weyl semimetals. The discovery that chiral crystals can host higher-spin generalizations of Weyl quasiparticles without high-energy counterparts, known as multifold fermions, raises the fundamental question of whether the chiral anomaly is a more general phenomenon. Answering this question requires materials with chiral quasiparticles within a sizable energy window around the Fermi level, that are unaffected by trivial extrinsic effects such as current jetting. Here we report the chiral anomaly of multifold fermions in CoSi, which features multifold bands within about 0.85 eV around the Fermi level. By excluding current jetting through the squeezing test, we measure an intrinsic, longitudinal negative magnetoresistance. We develop the semiclassical theory of magnetotransport of multifold fermions that shows that the negative magnetoresistance originates in their chiral anomaly, despite a sizable and detrimental orbital magnetic moment contribution, previously unaccounted for. A concomitant nonlinear Hall effect supports the multifold-fermion origin of magnetotransport. Our work confirms the chiral anomaly of higher-spin generalizations of Weyl fermions, currently inaccessible outside the solid-state.

We introduce Sinyukov-like tensors, a special kind of conformal Killing tensors. In Robertson-Walker space-times they have the perfect-fluid form and only depend on two constants and the scale factor. They are the candidate for the dark term of the newly proposed Conformal Killing Gravity, by Harada. In addition to ordinary matter, the Friedmann equations contain a dark term and a Lambda term that parametrize the Sinyukov-like tensor. The expression of H(z) is tested on cosmological data based on cosmic chronometers CC or including baryon acoustic oscillations BAO. There is a large incertitude in Omega_Lambda and Omega_dark that may become negative, but their sum is close to Omega_Lambda of Lambda-CDM. In any case, there is a future singularity, that is a big rip for all Omegas positive. We solve the equation for the evolution, in linear approximation, of the density contrast in matter-dominated universe. The dark sector and the Lambda term give no significative deviation from Lambda-CDM and GR results., Comment: 20 pages, 6 figures. Introduction reviewed, with references. Section on H(z) and datasets reviewed with improved figures, evolution of dark energy density and pressure, future singularities

HAT-P-67 b is one of the lowest-density gas giants known to date, making it an excellent target for atmospheric characterization through the transmission spectroscopy technique. In the framework of the GAPS large programme, we collected four transit events, with the aim of studying the exoplanet atmosphere and deriving the orbital projected obliquity. We exploited the high-precision GIARPS observing mode of the TNG, along with additional archival TESS photometry, to explore the activity level of the host star. We performed transmission spectroscopy, both in the VIS and in the nIR wavelength range, and analysed the RML effect both fitting the RVs and the Doppler shadow. Based on the TESS photometry, we redetermined the transit parameters of HAT-P-67 b. By modelling the RML effect, we derived a sky-projected obliquity of ($2.2\pm0.4$){\deg} indicating an aligned planetary orbit. The chromospheric activity index $\log\,R^{\prime}_{\rm HK}$, the CCF profile, and the variability in the transmission spectrum of the H$\alpha$ line suggest that the host star shows signatures of stellar activity and/or pulsations. We found no evidence of atomic or molecular species in the VIS transmission spectra, with the exception of pseudo-signals corresponding to Cr I, Fe I, H$\alpha$, Na I, and Ti I. In the nIR range, we found an absorption signal of the He I triplet of 5.56$^{+0.29}_{-0.30}$%(19.0$\sigma$), corresponding to an effective planetary radius of $\sim$3$R_p$ (where $R_p\sim$2$R_J$) which extends beyond the planet's Roche Lobe radius. Owing to the stellar variability, together with the high uncertainty of the model, we could not confirm the planetary origin of the signals found in the optical transmission spectrum. On the other hand, we confirmed previous detections of the infrared He I triplet, providing a 19.0$\sigma$ detection. Our finding indicates that the planet's atmosphere is evaporating., Comment: Accepted for publication in A&A

Obtaining reliable distance estimates to gas clouds within the Milky Way is challenging in the absence of certain tracers. The kinematic distance approach has been used as an alternative, derived from the assumption of circular trajectories around the Galactic centre. Consequently, significant errors are expected in regions where gas flow deviates from purely circular motions. We aim to quantify the systematic errors that arise from the kinematic distance method in the presence of a Galactic potential that is non-axisymmetric. We investigate how these errors differ in certain regions of the Galaxy and how they relate to the underlying dynamics. We perform 2D isothermal hydrodynamical simulation of the gas disk with the moving-mesh code Arepo, adding the capability of using an external potential provided by the Agama library for galactic dynamics. We introduce a new analytic potential of the Milky Way, taking elements from existing models and adjusting parameters to match recent observational constraints. We find significant errors in the kinematic distance estimate for gas close to the Sun, along sight lines towards the Galactic centre and anti-centre, and significant deviations associated with the Galactic bar. Kinematic distance errors are low within the spiral arms as gas resides close to local potential minima and the resulting line-of-sight velocity is close to what is expected for an axisymmetric potential. Interarm regions exhibit large deviations at any given Galactic radius. This is caused by the gas being sped up or slowed down as it travels into or out of the spiral arm. We are able to define 'zones of avoidance' in the lv-diagram, where the kinematic distance method is particularly unreliable and should only be used with caution. We report a power law relation between the kinematic distance error and the deviation of the project line-of-sight velocity from circular motion., Comment: 23 pages, 22 figures, 6 tables, submitted to A&A

We present detailed forecasts for the constraints on primordial magnetic fields (PMFs) that will be obtained with the LiteBIRD satellite. The constraints are driven by the effects of PMFs on the CMB anisotropies: the gravitational effects of magnetically-induced perturbations; the effects on the thermal and ionization history of the Universe; the Faraday rotation imprint on the CMB polarization; and the non-Gaussianities induced in polarization anisotropies. LiteBIRD represents a sensitive probe for PMFs and by exploiting all the physical effects, it will be able to improve the current limit coming from Planck. In particular, thanks to its accurate $B$-mode polarization measurement, LiteBIRD will improve the constraints on infrared configurations for the gravitational effect, giving $B_{\rm 1\,Mpc}^{n_{\rm B} =-2.9} < 0.8$ nG at 95% C.L., potentially opening the possibility to detect nanogauss fields with high significance. We also observe a significant improvement in the limits when marginalized over the spectral index, $B_{1\,{\rm Mpc}}^{\rm marg}< 2.2$ nG at 95% C.L. From the thermal history effect, which relies mainly on $E$-mode polarization data, we obtain a significant improvement for all PMF configurations, with the marginalized case, $\sqrt{\langle B^2\rangle}^{\rm marg}<0.50$ nG at 95% C.L. Faraday rotation constraints will take advantage of the wide frequency coverage of LiteBIRD and the high sensitivity in $B$ modes, improving the limits by orders of magnitude with respect to current results, $B_{1\,{\rm Mpc}}^{n_{\rm B} =-2.9} < 3.2$ nG at 95% C.L. Finally, non-Gaussianities of the $B$-mode polarization can probe PMFs at the level of 1 nG, again significantly improving the current bounds from Planck. Altogether our forecasts represent a broad collection of complementary probes, providing conservative limits on PMF characteristics that will be achieved with LiteBIRD., Comment: 51 pages, 24 figures, abstract shortened

This paper introduces a distributed control method for multi-agent robotic systems employing Over the Air Consensus (OtA-Consensus). Designed for agents with decoupled single-integrator dynamics, this approach aims at efficient formation achievement and collision avoidance. As a distinctive feature, it leverages OtA's ability to exploit interference in wireless channels, a property traditionally considered a drawback, thus enhancing communication efficiency among robots. An analytical proof of asymptotic convergence is established for systems with time-varying communication topologies represented by sequences of strongly connected directed graphs. Comparative evaluations demonstrate significant efficiency improvements over current state-of-the-art methods, especially in scenarios with a large number of agents., Comment: Submitted to CDC 2024

In this work an electron radiation detector microdevices were fabricated and characterized. The devices consisted of a conductive electrospun mat made of polycaprolactone loaded with multiwalled carbon nanotubes and fullerene C60 deposited onto gold interdigitated microelectrodes. They were capable of permanently increase their conductivity upon exposure to electron beam irradiation from 0.02 pC/{\mu}m2 accelerated at 10 and 20 keV. This phenomenon could be explained due to the ability of C60 to trap and stabilize negative charges and thus contribute to the conductivity of the polymer composite. The devices achieved their maximum conductivity at an irradiation between 0.22 and 0.27 pC/{\mu}m2 and this maximum was dependent of the electron acceleration. Montecarlo simulations were performed to explain dependence as function of electron penetration in the polymer composite. Moreover, the devices irradiated at 20keV maintained their final conductivity and the devices irradiated at 10keV increased their final conductivity after 6 days from irradiation. Fullerenes proved to act as highly efficient electron scavengers within the polymer composite and contribute to its conductivity, and the microdevice has potential application as beta radiation sensors., Comment: 18 pages, 5 figures, 2 tables

Over-the-Air Computation is a beyond-5G communication strategy that has recently been shown to be useful for the decentralized training of machine learning models due to its efficiency. In this paper, we propose an Over-the-Air federated learning algorithm that aims to provide fairness and robustness through minmax optimization. By using the epigraph form of the problem at hand, we show that the proposed algorithm converges to the optimal solution of the minmax problem. Moreover, the proposed approach does not require reconstructing channel coefficients by complex encoding-decoding schemes as opposed to state-of-the-art approaches. This improves both efficiency and privacy., Comment: 6 Pages, 2 figures. arXiv admin note: text overlap with arXiv:2305.04630

In this paper, we study how the Koopman operator framework can be combined with kernel methods to effectively control nonlinear dynamical systems. While kernel methods have typically large computational requirements, we show how random subspaces (Nystr\"om approximation) can be used to achieve huge computational savings while preserving accuracy. Our main technical contribution is deriving theoretical guarantees on the effect of the Nystr\"om approximation. More precisely, we study the linear quadratic regulator problem, showing that the approximated Riccati operator converges at the rate $m^{-1/2}$, and the regulator objective, for the associated solution of the optimal control problem, converges at the rate $m^{-1}$, where $m$ is the random subspace size. Theoretical findings are complemented by numerical experiments corroborating our results.

Ionic liquids (ILs) are an exciting class of electrolytes finding applications in many areas from energy storage to solvents, where they have been touted as ``designer solvents'' as they can be mixed to precisely tailor the physiochemical properties. As using machine learning interatomic potentials (MLIPs) to simulate ILs is still relatively unexplored, several questions need to be answered to see if MLIPs can be transformative for ILs. Since ILs are often not pure, but are either mixed together or contain additives, we first demonstrate that a MLIP can be trained to be compositionally transferable, i.e., the MLIP can be applied to mixtures of ions not directly trained on, whilst only being trained on a few mixtures of the same ions. We also investigate the accuracy of MLIPs for a novel IL, which we experimentally synthesize and characterize. Our MLIP trained on $\sim$200 DFT frames is in reasonable agreement with our experiments and DFT.

The atmospheric characterisation of hot and warm Neptune-size exoplanets is challenging due to their small radius and atmospheric scale height. The warm-Neptune HAT-P-11b is a remarkable target for such characterisation due to the large brightness of its host star (V=9.46 mag; H=7.13 mag). The aims of this work are to review the main physical and architectural properties of the HAT-P-11 planetary system, and to probe the presence of 8 molecular species in the atmosphere of HAT-P-11b at high spectral resolution in the near-infrared. The planetary system was reviewed by analysing transits and occultations of HAT-P-11b from the Kepler data set as well as HIRES at Keck archival radial-velocity (RV) data. We modelled the latter with Gaussian-process regression and a combined quasi-periodic and squared-exponential kernel to account for stellar variations on both (short-term) rotation and (long-term) activity-cycle timescales. In order to probe the atmospheric composition of HAT-P-11b, we observed 4 transits of this target with GIANO-B at TNG. We find that the long-period ($P\sim9.3$ years) RV signal previously attributed to planet HAT-P-11c is more likely due to the stellar magnetic activity cycle. Nonetheless, the Hipparcos-Gaia difference in the proper-motion anomaly suggests that an outer-bound companion might still exist. For HAT-P-11b, we measure a radius $R_{\rm p}=0.4466\pm0.0059\,R_{\rm J}$, a mass $M_{\rm p}=0.0787\pm0.0048\,M_{\rm J}$, and an eccentricity $e=0.2577^{+0.0033}_{-0.0025}$, in accordance with values in the literature. Probing its atmosphere, we detect $NH_3$ (S/N$=5.3$, significance$=5.0\sigma$) and confirm the presence of $H_2O$ (S/N$=5.1$, significance$=3.4\sigma$). We also tentatively detect the signal of $CO_2$ (S/N$=3.0$, significance$=3.2\sigma$) and $CH_4$ (S/N$=4.8$, significance$=2.6\sigma$), whose presence need to be confirmed by further observations., Comment: 25 pages, 19 figures, accepted for publication in Astronomy & Astrophysics (A&A) journal. Version corrected by the language editor, title edited

Molecular clouds (MC) are structures of dense gas in the interstellar medium (ISM), that extend from ten to a few hundred parsecs and form the main gas reservoir available for star formation. Hydrodynamical simulations of varying complexity are a promising way to investigate MC evolution and their properties. However, each simulation typically has a limited range in resolution and different cloud extraction algorithms are used, which complicates the comparison between simulations. In this work, we aim to extract clouds from different simulations covering a wide range of spatial scales. We compare their properties, such as size, shape, mass, internal velocity dispersion and virial state. We apply the Hop cloud detection algorithm on (M)HD numerical simulations of stratified ISM boxes and isolated galactic disk simulations that were produced using Flash Ramses and Arepo We find that the extracted clouds are complex in shape ranging from round objects to complex filamentary networks in all setups. Despite the wide range of scales, resolution, and sub-grid physics, we observe surprisingly robust trends in the investigated metrics. The mass spectrum matches in the overlap between simulations without rescaling and with a high-mass slope of $\mathrm{d} N/\mathrm{d}\ln M\propto-1$ in accordance with theoretical predictions. The internal velocity dispersion scales with the size of the cloud as $\sigma\propto R^{0.75}$ for large clouds ($R\gtrsim3\,\mathrm{pc}$). For small clouds we find larger sigma compared to the power-law scaling, as seen in observations, which is due to supernova-driven turbulence. Almost all clouds are gravitationally unbound with the virial parameter scaling as $\alpha_\mathrm{vir}\propto M^{-0.4}$, which is slightly flatter compared to observed scaling, but in agreement given the large scatter., Comment: 22 pages, 16 figures, proposed for acceptance in A&A

Decision-making processes increasingly rely on the use of algorithms. Yet, algorithms' predictive ability frequently exhibit systematic variation across subgroups of the population. While both fairness and accuracy are desirable properties of an algorithm, they often come at the cost of one another. What should a fairness-minded policymaker do then, when confronted with finite data? In this paper, we provide a consistent estimator for a theoretical fairness-accuracy frontier put forward by Liang, Lu and Mu (2023) and propose inference methods to test hypotheses that have received much attention in the fairness literature, such as (i) whether fully excluding a covariate from use in training the algorithm is optimal and (ii) whether there are less discriminatory alternatives to an existing algorithm. We also provide an estimator for the distance between a given algorithm and the fairest point on the frontier, and characterize its asymptotic distribution. We leverage the fact that the fairness-accuracy frontier is part of the boundary of a convex set that can be fully represented by its support function. We show that the estimated support function converges to a tight Gaussian process as the sample size increases, and then express policy-relevant hypotheses as restrictions on the support function to construct valid test statistics.

The emergence of statistical complexity in frictional systems, manifested in broad distributions of various observables, is not yet understood. We study this problem in velocity-driven, homogeneous (no quenched disorder) unstable frictional systems of height $H$. The latter are described at the continuum scale within a realistic rate-and-state friction interfacial constitutive framework, where elasto-frictional instabilities emerge from rate-weakening friction. For large $H$, such frictional systems were recently shown to undergo continuous coarsening until settling into a spatially periodic traveling solution. We show that when the system's height-to-length ratio becomes small, coarsening is less effective and the periodic solution is dynamically avoided. Instead, and consistently with previous reports, the system settles into a stochastic, statistically stationary state. The latter features slip bursts, classified into predominantly non-propagating small bursts and propagating large bursts, which are non-trivially distributed. The statistical distributions emerge from dynamically self-generated heterogeneity, where both the non-equilibrium history of the interface and wave reflections from finite boundaries, mediated by material inertia, play central roles. Specifically, the dynamics and statistics of large bursts reveal a timescale $\sim\!H/c_{\rm s}$, where $c_{\rm s}$ is the shear wave-speed. We discuss the robustness of our findings against variations of the frictional parameters, most notably affecting the magnitude of frictional rate-weakening, as well as against different interfacial state evolution laws. Finally, we demonstrate a reverse transition in which statistical complexity disappears in favor of the spatially periodic traveling solution. Overall, our results elucidate how relatively simple physical ingredients can give rise to the emergence of slip complexity., Comment: v2: new results on the robustness of complexity and a reverse complexity-to-coarsening transition, including new section, figures (Figs. 4 & 5) and appendix

Clement and Noiucer submitted a note {\tt arXiv:2401.16008 [gr-qc]} replying to our criticism {\tt arXiv:2401.10479 [gr-qc]} of their previous submission. We reply to the contents of this note and remark that these authors have not addressed our arguments. This will be our last response to them. Readers are advised to look at all material and judge by themselves, Comment: 2 pages, 6 references

Planets in binary systems are a fascinating and yet poorly understood phenomenon. Since there are only a few known large-separation systems in which both components host planets, characterizing them is a key target for planetary science. In this paper, we aim to carry out an exhaustive analysis of the interesting XO-2 system, where one component appears to be a system with only one planet, while the other has at least three planets. Over the last 9 years, we have collected 39 spectra of XO-2N and 106 spectra of XO-2S with the High Accuracy Radial velocity Planet Searcher for the Northern emisphere (HARPS-N) in the framework of the Global Architecture of Planetary Systems project, from which we derived precise radial velocity and activity indicator measurements. Additional spectroscopic data from the High Resolution Echelle Spectrometer and from the High Dispersion Spectrograph, and the older HARPS-N data presented in previous papers, have also been used to increase the total time span. We also used photometric data from TESS to search for potential transits that have not been detected yet. For our analysis, we mainly used PyORBIT, an advanced Python tool for the Bayesian analysis of RVs, activity indicators, and light curves. We found evidence for an additional long-period planet around XO-2S and characterized the activity cycle likely responsible for the long-term RV trend noticed for XO-2N. The new candidate is an example of a Jovian analog with $m\sin i \sim 3.7$ M$_J$, $a \sim 5.5$ au, and $e = 0.09$. We also analyzed the stability and detection limits to get some hints about the possible presence of additional planets. Our results show that the planetary system of XO-2S is at least one order of magnitude more massive than that of XO-2N. The implications of these findings for the interpretation of the previously known abundance difference between components are also discussed.

Sensitive wide-field observations of polarized thermal emission from interstellar dust grains will allow astronomers to address key outstanding questions about the life cycle of matter and energy driving the formation of stars and the evolution of galaxies. Stratospheric balloon-borne telescopes can map this polarized emission at far-infrared wavelengths near the peak of the dust thermal spectrum - wavelengths that are inaccessible from the ground. In this paper we address the sensitivity achievable by a Super Pressure Balloon (SPB) polarimetry mission, using as an example the Balloon-borne Large Aperture Submillimeter Telescope (BLAST) Observatory. By launching from Wanaka, New Zealand, BLAST Observatory can obtain a 30-day flight with excellent sky coverage - overcoming limitations of past experiments that suffered from short flight duration and/or launch sites with poor coverage of nearby star-forming regions. This proposed polarimetry mission will map large regions of the sky at sub-arcminute resolution, with simultaneous observations at 175, 250, and 350 $\mu m$, using a total of 8274 microwave kinetic inductance detectors. Here, we describe the scientific motivation for the BLAST Observatory, the proposed implementation, and the forecasting methods used to predict its sensitivity. We also compare our forecasted experiment sensitivity with other facilities., Comment: Published in PASP

Simultaneously performing variable selection and inference in high-dimensional regression models is an open challenge in statistics and machine learning. The increasing availability of vast amounts of variables requires the adoption of specific statistical procedures to accurately select the most important predictors in a high-dimensional space, while controlling the False Discovery Rate (FDR) arising from the underlying multiple hypothesis testing. In this paper we propose the joint adoption of the Mirror Statistic approach to FDR control, coupled with outcome randomisation to maximise the statistical power of the variable selection procedure. Through extensive simulations we show how our proposed strategy allows to combine the benefits of the two techniques. The Mirror Statistic is a flexible method to control FDR, which only requires mild model assumptions, but requires two sets of independent regression coefficient estimates, usually obtained after splitting the original dataset. Outcome randomisation is an alternative to Data Splitting, that allows to generate two independent outcomes, which can then be used to estimate the coefficients that go into the construction of the Mirror Statistic. The combination of these two approaches provides increased testing power in a number of scenarios, such as highly correlated covariates and high percentages of active variables. Moreover, it is scalable to very high-dimensional problems, since the algorithm has a low memory footprint and only requires a single run on the full dataset, as opposed to iterative alternatives such as Multiple Data Splitting.

Protoplanetary disks, which are the natural consequence of the gravitational collapse of the dense molecular cloud cores, host the formation of the known planetary systems in our universe. Substantial efforts have been dedicated to investigating the properties of these disks in the more mature Class II stage, either via numerical simulations of disk evolution from a limited range of initial conditions or observations of their dust continuum and line emission from specific molecular tracers. The results coming from these two standpoints have been used to draw comparisons. However, few studies have investigated the main limitations at work when measuring the embedded Class 0/I disk properties from observations, especially in a statistical fashion. In this study, we provide a first attempt to compare the accuracy of some critical disk parameters in Class 0/I systems, as derived on real ALMA observational data, with the corresponding physical parameters that can be directly defined by theoreticians and modellers in numerical simulations. The approach we follow here is to provide full post-processing of the numerical simulations and apply it to the synthetic observations the same techniques used by observers to derive the physical parameters. We performed 3D Monte Carlo radiative transfer and mock interferometric observations of the disk populations formed in a magnetohydrodynamic (MHD) simulation model of disk formation through the collapse of massive clumps with the tools \textsc{Radmc-3d} and \textsc{Casa}, respectively, to obtain their synthetic observations. With these observations, we re-employed the techniques commonly used in disk modelling from their continuum emissions to infer the properties that would most likely be obtained with real interferometers. We then demonstrated how these properties may vary with respect to the gas kinematics analyses and dust continuum modelling., Comment: Accepted for publication in Astronomy & Astrophysics, 32 pages, 28 figures

This paper proposes an information-based inference method for partially identified parameters in incomplete models that is valid both when the model is correctly specified and when it is misspecified. Key features of the method are: (i) it is based on minimizing a suitably defined Kullback-Leibler information criterion that accounts for incompleteness of the model and delivers a non-empty pseudo-true set; (ii) it is computationally tractable; (iii) its implementation is the same for both correctly and incorrectly specified models; (iv) it exploits all information provided by variation in discrete and continuous covariates; (v) it relies on Rao's score statistic, which is shown to be asymptotically pivotal.