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This paper introduces a new method for change detection in psychometric studies based on the recently introduced pseudo Score statistic, for which the sampling distribution under the alternative hypothesis has been determined. Our approach has the advantage of simplicity in its computation, eliminating the need for resampling or simulations to obtain critical values. Additionally, it comes with a known null/alternative distribution, facilitating easy calculations for power levels and sample size planning. The paper indeed also discusses the topic of power analysis in segmented regression, namely the estimation of sample size or power level when the study data being collected focuses on a covariate expected to affect the mean response via a piecewise relationship with an unknown breakpoint. We run simulation results showing that our method outperforms other Tests for a Change Point (TFCP) with both normally distributed and binary data and carry out a real SAT Critical reading data analysis. The proposed test contributes to the framework of psychometric research, and it is available on the Comprehensive R Archive Network (CRAN) and in a more user-friendly Shiny App, both illustrated at the end of the paper.

Recent advancements in Large Language Models (LLMs) have showcased their proficiency in answering natural language queries. However, their effectiveness is hindered by limited domain-specific knowledge, raising concerns about the reliability of their responses. We introduce a hybrid system that augments LLMs with domain-specific knowledge graphs (KGs), thereby aiming to enhance factual correctness using a KG-based retrieval approach. We focus on a medical KG to demonstrate our methodology, which includes (1) pre-processing, (2) Cypher query generation, (3) Cypher query processing, (4) KG retrieval, and (5) LLM-enhanced response generation. We evaluate our system on a curated dataset of 69 samples, achieving a precision of 78\% in retrieving correct KG nodes. Our findings indicate that the hybrid system surpasses a standalone LLM in accuracy and completeness, as verified by an LLM-as-a-Judge evaluation method. This positions the system as a promising tool for applications that demand factual correctness and completeness, such as target identification -- a critical process in pinpointing biological entities for disease treatment or crop enhancement. Moreover, its intuitive search interface and ability to provide accurate responses within seconds make it well-suited for time-sensitive, precision-focused research contexts. We publish the source code together with the dataset and the prompt templates used., Comment: 10 pages, 7 figures

We consider the free boundary problem for a 3-dimensional, incompressible, irrotational liquid drop of nearly spherical shape with capillarity. We study the problem from scratch, extending some classical results from the flat case (capillary water waves) to the spherical geometry: the reduction to a problem on the boundary, its Hamiltonian structure, the analyticity and tame estimates for the Dirichlet-Neumann operator in Sobolev class, and a linearization formula for it, both with the method of the good unknown of Alinhac and by a differential geometry approach. Then we prove the bifurcation of traveling waves, which are nontrivial (i.e., nonspherical) fixed profiles rotating with constant angular velocity.

Photoexcited organic chromophores appended to molecular qubits can serve as a source of spin initialization or multi-level qudit generation for quantum information applications. So far, this approach has been primarily investigated in chromophore/stable radical systems. Here, we extend this concept to a meso-meso linked oxovanadium(IV) porphyrin - free base porphyrin dimer. Femtosecond transient absorption experiments reveal that photoexcitation of the free base porphyrin leads to picosecond triplet state formation via enhanced intersystem crossing. Time-resolved electron paramagnetic resonance (TREPR) experiments carried out at both 85 K and room temperature reveal the formation of a long-lived spin-polarized quartet state through triplet-doublet spin mixing. Notably, a distinct hyperfine structure arising from the interaction between the electron spin quartet state and the vanadyl nucleus (51V, I=7/2) is evident, with the quartet state exhibiting long-lived spin polarization even at room temperature. Theoretical simulations of the TREPR spectra confirm the photogenerated quartet state and provide insights into the non-Boltzmann spin populations. Exploit-ing this phenomenon affords the possibility of using photoinduced triplet states in porphyrins for quantum information as a resource to polarize and magnetically couple molecular electronic or nuclear spin qubits and qudits.

Fast emitting polymeric scintillators are requested in advanced applications where high-speed detectors with large signal-to-noise ratio are needed. However, their low density implies a weak stopping power of high energy radiations, thus a limited light output and sensitivity. To enhance their performances, polymeric scintillators can be loaded with dense nanoparticles (NPs). We investigate the properties of a series of polymeric scintillators by means of photoluminescence and scintillation spectroscopy, comparing standard scintillators with a composite system loaded with dense hafnium dioxide (HfO2) NPs. The nanocomposite shows a scintillation yield enhancement of +100% with unchanged time response. We provide for the first time an interpretation of this effect, pointing out the local effect of NPs in the generation of emissive states upon interaction with the ionizing radiation. The obtained results indicate that coupling of fast conjugated emitters with optically inert dense NPs could allow to surpass the actual limits of pure polymeric scintillators., Comment: 14 pages, 4 figures

We investigate the choice behavior of a decision maker (DM) who harms herself, by maximizing in each menu some distortion of her true preference, in which the first i alternatives are moved to the bottom, in a reversed order. The deterministic declination of our pattern has no empirical power, but it allows to define a degree of self-punishment, which measures the extent of the denial of pleasure adopted by the DM in her decision. We analyze irrational choices that display the lowest degree of self-punishment, and a characterization of them is provided. Moreover, we characterize the choice behavior that exhibits the highest degree of self-punishment, and we show that it comprises almost all choices. We also characterize stochastic self-punishment, which collects all the Random Utility Models (RUMs) whose support is restricted to the harmful distortions of some preference. Necessary and sufficient conditions for a full identification of the DM's preference and randomization over its harmful distortions are singled out. Finally, the degree of self-punishment of harmful stochastic choices is characterized.

The orbits of close-in exoplanets provide clues to their formation and evolutionary history. Many close-in exoplanets likely formed far out in their protoplanetary disks and migrated to their current orbits, perhaps via high-eccentricity migration (HEM), a process that can also excite obliquities. A handful of known exoplanets are perhaps caught in the act of HEM, as they are observed on highly eccentric orbits with tidal circularization timescales shorter than their ages. One such exoplanet is Kepler-1656 b, which is also the only known non-giant exoplanet (<100 $M_\oplus$) with an extreme eccentricity (e=0.84). We measured the sky-projected obliquity of Kepler-1656 b by observing the Rossiter-McLaughlin effect during a transit with the Keck Planet Finder. Our data are consistent with an aligned orbit, but are also consistent with moderate misalignment with $\lambda < 50$ deg at 95% confidence, with the most likely solution of $35^{+14.9}_{-21.6}$ deg. A low obliquity would be an unlikely outcome of most eccentricity-exciting scenarios, but we show that the properties of the outer companion in the system are consistent with the coplanar HEM mechanism. Alternatively, if the system is not relatively coplanar (<20 deg mutual inclination), Kepler-1656 b may be presently at a rare snapshot of long-lived eccentricity oscillations that do not induce migration. Kepler-1656 b is only the fourth exoplanet with e>0.8 to have its obliquity constrained; expanding this population will help establish the degree to which orbital misalignment accompanies migration. Future work that constrains the mutual inclinations of outer perturbers will be key for distinguishing plausible mechanisms., Comment: 11 pages, 5 figures, accepted to ApJL

We investigate the robustness of the many-body localized (MBL) phase to the quantum-avalanche instability by studying the dynamics of a localized spin chain coupled to a $T=\infty$ thermal bath through its leftmost site. By analyzing local magnetizations, we estimate the size of the thermalized sector of the chain and find that it increases logarithmically slowly in time. This logarithmically slow propagation of the thermalization front allows us to lower bound the slowest thermalization time, and find a broad parameter range where it scales fast enough with the system size that MBL is robust against thermalization induced by avalanches. The further finding that the imbalance -- a global quantity measuring localization -- thermalizes over a time scale exponential both in disorder strength and system size is in agreement with these results., Comment: 12 pages, 8 figures. More references on logarithmic light cones in MBL. Discussion on the particle-number nonconserving case added

Correlation Plenoptic Imaging (CPI) is a novel technological imaging modality enabling to overcome drawbacks of standard plenoptic devices, while preserving their advantages. However, a major challenge in view of real-time application of CPI is related with the relevant amount of required frames and the consequent computational-intensive processing algorithm. In this work, we describe the design and implementation of an optimized processing algorithm that is portable to an efficient computational environment and exploits the highly parallel algorithm offered by GPUs. Improvements by a factor ranging from 20x, for correlation measurement, to 500x, for refocusing, are demonstrated. Exploration of the relation between the improvement in performance achieved and actual GPU capabilities, also indicates the feasibility of near-real time processing capability, opening up to the potential use of CPI for practical real-time application., Comment: 17 pages, 13 figures

Precise spectroscopic classification of planet hosts is an important tool of exoplanet research at both the population and individual system level. In the era of large-scale surveys, data-driven methods offer an efficient approach to spectroscopic classification that leverages the fact that a subset of stars in any given survey has stellar properties that are known with high fidelity. Here, we use The Cannon, a data-driven framework for modeling stellar spectra, to train a generative model of spectra from the Gaia Data Release 3 Radial Velocity Spectrometer. Our model derives stellar labels with precisions of 72 K in Teff , 0.09 dex in log g, 0.06 dex in [Fe/H], 0.05 dex in [{\alpha}/Fe] and 1.9 km/s in vbroad for main-sequence stars observed by Gaia DR3 by transferring GALAH labels, and is publicly available at https://github.com/isabelangelo/gaiaspec. We validate our model performance on planet hosts with available Gaia RVS spectra at SNR>50 by showing that our model is able to recover stellar parameters at {\geq}20% improved accuracy over the existing Gaia stellar parameter catalogs, measured by the agreement with high-fidelity labels from the Spectroscopic Observations of Cool Stars (SPOCS) survey. We also provide metrics to test for stellar activity, binarity, and reliability of our model outputs and provide instructions for interpreting these metrics. Finally, we publish updated stellar labels and metrics that flag suspected binaries and active stars for Kepler Input Catalog objects with published Gaia RVS spectra., Comment: Published in ApJ; 19 pages, 8 figures

In the context of the CERN EP R&D on monolithic sensors and the ALICE ITS3 upgrade, the Tower Partners Semiconductor Co (TPSCo) 65 nm process has been qualified for use in high energy physics, and adopted for the ALICE ITS3 upgrade. An Analog Pixel Test Structure (APTS) featuring fast per pixel operational-amplifier-based buffering for a small matrix of four by four pixels, with a sensor with a small collection electrode and a very non-uniform electric field, was designed to allow detailed characterization of the pixel performance in this technology. Several variants of this chip with different pixel designs have been characterized with a (120 GeV/$c$) positive hadron beam. This result indicates that the APTS-OA prototype variants with the best performance achieve a time resolution of 63 ps with a detection efficiency exceeding 99% and a spatial resolution of 2 $\mu$m, highlighting the potential of TPSCo 65nm CMOS imaging technology for high-energy physics and other fields requiring precise time measurement, high detection efficiency, and excellent spatial resolution.

With the emergence of Transformers and Vision-Language Models (VLMs) such as CLIP, fine-tuning large pre-trained models has recently become a prevalent strategy in Continual Learning. This has led to the development of numerous prompting strategies to adapt transformer-based models without incurring catastrophic forgetting. However, these strategies often compromise the original zero-shot capabilities of the pre-trained CLIP model and struggle to adapt to domains that significantly deviate from the pre-training data. In this work, we propose Continual Generative training for Incremental prompt-Learning, a simple and novel approach to mitigate forgetting while adapting CLIP. Briefly, we employ Variational Autoencoders (VAEs) to learn class-conditioned distributions within the embedding space of the visual encoder. We then exploit these distributions to sample new synthetic visual embeddings and train the corresponding class-specific textual prompts during subsequent tasks. Through extensive experiments on different domains, we show that such a generative replay approach can adapt to new tasks while improving zero-shot capabilities, evaluated using a novel metric tailored for CL scenarios. Notably, further analysis reveals that our approach can bridge the gap with joint prompt tuning. The codebase is available at https://github.com/aimagelab/mammoth., Comment: 15 pages, 1 figure. Accepted as ORAL at the The 35th British Machine Vision Conference 2024 (BMVC 2024), Glasgow, UK

The field of Continual Learning (CL) has inspired numerous researchers over the years, leading to increasingly advanced countermeasures to the issue of catastrophic forgetting. Most studies have focused on the single-class scenario, where each example comes with a single label. The recent literature has successfully tackled such a setting, with impressive results. Differently, we shift our attention to the multi-label scenario, as we feel it to be more representative of real-world open problems. In our work, we show that existing state-of-the-art CL methods fail to achieve satisfactory performance, thus questioning the real advance claimed in recent years. Therefore, we assess both old-style and novel strategies and propose, on top of them, an approach called Selective Class Attention Distillation (SCAD). It relies on a knowledge transfer technique that seeks to align the representations of the student network -- which trains continuously and is subject to forgetting -- with the teacher ones, which is pretrained and kept frozen. Importantly, our method is able to selectively transfer the relevant information from the teacher to the student, thereby preventing irrelevant information from harming the student's performance during online training. To demonstrate the merits of our approach, we conduct experiments on two different multi-label datasets, showing that our method outperforms the current state-of-the-art Continual Learning methods. Our findings highlight the importance of addressing the unique challenges posed by multi-label environments in the field of Continual Learning. The code of SCAD is available at https://github.com/aimagelab/SCAD-LOD-2024., Comment: Accepted at LOD 2024

A spectator axion-gauge sector, minimally coupled to the inflaton, with the axion experiencing a momentary stage of fast roll during cosmological inflation, can generate unique signatures in primordial density fluctuations and the gravitational wave background. We present the first lattice simulation of this system using a novel hybrid numerical scheme. This approach solves the fully nonlinear dynamics of the axion-gauge sector while treating the gravitational interaction between the axion and inflaton linearly. Initially, we test the validity of the WKB approximation in the linear regime. We then investigate strong backreaction dynamics within the axion-gauge sector. Our findings reveal that backreaction significantly suppresses the growth of the gauge field and the amplitude of scalar perturbations. The simulation also allows us to analyze the non-Gaussianity of scalar fluctuations, including higher-order statistics. We show that, although non-Gaussianity is suppressed by strong backreaction, it remains higher than in the minimal model where the axion coincides with the inflaton. Our results highlight the need for simulations to make robust predictions to test against data from gravitational wave interferometers and large-scale structure surveys., Comment: 31 pages, 25 figures

Identifying the reason for which an author cites another work is essential to understand the nature of scientific contributions and to assess their impact. Citations are one of the pillars of scholarly communication and most metrics employed to analyze these conceptual links are based on quantitative observations. Behind the act of referencing another scholarly work there is a whole world of meanings that needs to be proficiently and effectively revealed. This study emphasizes the importance of trustfully classifying citation intents to provide more comprehensive and insightful analyses in research assessment. We address this task by presenting a study utilizing advanced Ensemble Strategies for Citation Intent Classification (CIC) incorporating Language Models (LMs) and employing Explainable AI (XAI) techniques to enhance the interpretability and trustworthiness of models' predictions. Our approach involves two ensemble classifiers that utilize fine-tuned SciBERT and XLNet LMs as baselines. We further demonstrate the critical role of section titles as a feature in improving models' performances. The study also introduces a web application developed with Flask and currently available at http://137.204.64.4:81/cic/classifier, aimed at classifying citation intents. One of our models sets as a new state-of-the-art (SOTA) with an 89.46% Macro-F1 score on the SciCite benchmark. The integration of XAI techniques provides insights into the decision-making processes, highlighting the contributions of individual words for level-0 classifications, and of individual models for the metaclassification. The findings suggest that the inclusion of section titles significantly enhances classification performances in the CIC task. Our contributions provide useful insights for developing more robust datasets and methodologies, thus fostering a deeper understanding of scholarly communication., Comment: 42 pages, 14 figures, 1 table, submitted to Scientometrics Journal

Hyperspectral imaging aims at providing information on both the spatial and the spectral distribution of light, with high resolution. However, state-of-the-art protocols are characterized by an intrinsic trade-off imposing to sacrifice either resolution or image acquisition speed. We address this limitation by exploiting light intensity correlations, which are shown to enable overcoming the typical downsides of traditional hyperspectral imaging techniques, both scanning and snapshot. The proposed approach also opens possibilities that are not otherwise achievable, such as sharper imaging and natural filtering of broadband spectral components that would otherwise hide the spectrum of interest. The enabled combination of high spatial and spectral resolution, high speed, and insensitivity to undesired spectral features shall lead to a paradigm change in hyperspectral imaging devices and open-up new application scenarios., Comment: 11 pages, 4 figures

The dynamics of a quantum-many body system subject to measurements is naturally described by an ensemble of quantum trajectories, which can feature measurement-induced phase transitions (MIPTs). This phenomenon cannot be revealed through ensemble-averaged observables, but it requires the ability to discriminate each trajectory separately, making its experimental observation extremely challenging. We explore the fate of MIPTs under an observer's reduced ability to discriminate each measurement outcome. This introduces uncertainty in the state of the system, causing observables to probe a restricted subset of trajectories rather than a single one. By introducing an exactly-solvable Liouvillian model, we examine how long-time spatial correlations are influenced by varying degrees of trajectory averaging. We compute exactly the correlation matrix, Liouvillian gap, and entanglement negativity to demonstrate that averaging over multiple realizations introduces an effective finite lengthscale, beyond which long-range correlations are suppressed. This suggests that partial averaging over trajectories conceals the critical features of individual realizations, thereby blurring away the signatures of distinct measurement-induced phases., Comment: 11 pages, 6 figures

The scientific impact of GW170817 strongly supports the need for an efficient electromagnetic follow-up campaign to gravitational-wave event candidates. The success of such campaigns depends critically on a fast and accurate localization of the source. In this paper, we present SKYFAST, a new pipeline for rapid localization of gravitational-wave event hosts. SKYFAST runs alongside a full parameter estimation (PE) algorithm, from which posterior samples are taken. It uses these samples to reconstruct an analytical posterior for the sky position, luminosity distance, and inclination angle using a Dirichlet Process Gaussian Mixture Model, a Bayesian non-parametric method. This approach allows us to provide an accurate localization of the event using only a fraction of the total samples produced by the full PE analysis. Depending on the PE algorithm employed, this can lead to significant time savings, which is crucial for identifying the electromagnetic counterpart. Additionally, in a few minutes, SKYFAST generates a ranked list of the most probable galaxy hosts from a galaxy catalog of choice. This list includes information on the inclination angle posterior conditioned to the position of each candidate host, which is useful for assessing the detectability of gamma-ray burst structured jet emissions., Comment: 10 pages, 9 figures

The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accelerator complex, detectors and physics for a future muon collider. In 2023, European Commission support was obtained for a design study of a muon collider (MuCol) [3]. This project started on 1st March 2023, with work-packages aligned with the overall muon collider studies. In preparation of and during the 2021-22 U.S. Snowmass process, the muon collider project parameters, technical studies and physics performance studies were performed and presented in great detail. Recently, the P5 panel [4] in the U.S. recommended a muon collider R&D, proposed to join the IMCC and envisages that the U.S. should prepare to host a muon collider, calling this their "muon shot". In the past, the U.S. Muon Accelerator Programme (MAP) [5] has been instrumental in studies of concepts and technologies for a muon collider., Comment: This document summarises the International Muon Collider Collaboration (IMCC) progress and status of the Muon Collider R&D programme

The Berry phase is a fundamental concept in quantum mechanics with profound implications for understanding topological properties of quantum systems. This tutorial provides a comprehensive introduction to the Berry phase, beginning with the essential mathematical framework required to grasp its significance. We explore the intrinsic link between the emergence of a non-trivial Berry phase and the presence of topological characteristics in quantum systems, showing the connection between the Berry phase and the band structure as well as the phase's gauge-invariant nature during cyclic evolutions. The tutorial delves into various topological effects arising from the Berry phase, such as the quantum, anomalous, and spin Hall effects, which exemplify how these quantum phases manifest in observable phenomena. We then extend our discussion to cover the transport properties of topological insulators, elucidating their unique behaviour rooted in Berry phase physics. This tutorial aims at equipping its readers with a robust understanding of the basic theory around the Berry phase and its pivotal role in the realm of topological quantum phenomena., Comment: 24 pages, 11 figures

We present multiwavelength polarization measurements of the luminous blazar Mrk~501 over a 14-month period. The 2--8 keV X-ray polarization was measured with the Imaging X-ray Polarimetry Explorer (IXPE) with six 100-ks observations spanning from 2022 March to 2023 April. Each IXPE observation was accompanied by simultaneous X-ray data from NuSTAR, Swift/XRT, and/or XMM-Newton. Complementary optical-infrared polarization measurements were also available in the B, V, R, I, and J bands, as were radio polarization measurements from 4.85 GHz to 225.5 GHz. Among the first five IXPE observations, we did not find significant variability in the X-ray polarization degree and angle with IXPE. However, the most recent sixth observation found an elevated polarization degree at $>3\sigma$ above the average of the other five observations. The optical and radio measurements show no apparent correlations with the X-ray polarization properties. Throughout the six IXPE observations, the X-ray polarization degree remained higher than, or similar to, the R-band optical polarization degree, which remained higher than the radio value. This is consistent with the energy-stratified shock scenario proposed to explain the first two IXPE observations, in which the polarized X-ray, optical, and radio emission arises from different regions., Comment: Accepted for publication in ApJ

We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables

The initial conditions on the anisotropies of the stochastic gravitational-wave background of cosmological origin (CGWB) largely depend on the mechanism that generates the gravitational waves. Since the CGWB is expected to be non-thermal, the computation of the initial conditions could be more challenging w.r.t. the Cosmic Microwave Background (CMB), whose interactions with other particles in the early Universe lead to a blackbody spectrum. In this paper, we show that the initial conditions for the cosmological background generated by quantum fluctuations of the metric during inflation deviate from adiabaticity. These primordial gravitational waves are indeed generated by quantum fluctuations of two independent degrees of freedom (the two polarization states of the gravitons). Furthermore, the CGWB plays a negligible role in the Einstein's equations, because its energy density is subdominant w.r.t. ordinary matter. Therefore, the only possible way to compute the initial conditions for inflationary gravitons is to perturb the energy-momentum tensor of the gravitational field defined in terms of the small-scale tensor perturbation of the metric. This new and self-consistent approach shows that a large, non-adiabatic initial condition is present even during the single-field inflation. Such a contribution enhances the total angular power spectrum of the CGWB compared to the standard adiabatic case, increasing also the sensitivity of the anisotropies to the presence of relativistic and decoupled particles in the early Universe. In this work we have also proved that our findings are quite general and apply to both single-field inflation and other scenarios in which the CGWB is generated by the quantum fluctuations of the metric, like the curvaton., Comment: Accepted for publication on JCAP. arXiv admin note: text overlap with arXiv:2307.11043

In 1935, Einstein, Podolsky, and Rosen argued that quantum mechanics is incomplete, based on the assumption that local actions cannot influence elements of reality at a distant location (local realism). In this work, using a recently defined quantum reality quantifier, we show that Alice's local quantum operations can be correlated with the erasure of the reality of observables in Bob's causally disconnected laboratory. To this end, we implement a modified optical quantum eraser experiment, ensuring that Alice's and Bob's measurements remain causally disconnected. Using an entangled pair of photons and quantum state tomography, we experimentally verify that, even with the total absence of any form of classical communication, the choice of quantum operation applied by Alice on her photon is correlated with the erasure of a spatial element of reality of Bob's photon. In this case, it is shown that Bob's photon can entangle two extra non-interacting degrees of freedom, thus confirming that Bob's photon path is not an element of physical reality.

Although attention mechanisms have achieved considerable progress in Transformer-based architectures across various Artificial Intelligence (AI) domains, their inner workings remain to be explored. Existing explainable methods have different emphases but are rather one-sided. They primarily analyse the attention mechanisms or gradient-based attribution while neglecting the magnitudes of input feature values or the skip-connection module. Moreover, they inevitably bring spurious noisy pixel attributions unrelated to the model's decision, hindering humans' trust in the spotted visualization result. Hence, we propose an easy-to-implement but effective way to remedy this flaw: Smooth Noise Norm Attention (SNNA). We weigh the attention by the norm of the transformed value vector and guide the label-specific signal with the attention gradient, then randomly sample the input perturbations and average the corresponding gradients to produce noise-free attribution. Instead of evaluating the explanation method on the binary or multi-class classification tasks like in previous works, we explore the more complex multi-label classification scenario in this work, i.e., the driving action prediction task, and trained a model for it specifically. Both qualitative and quantitative evaluation results show the superiority of SNNA compared to other SOTA attention-based explainable methods in generating a clearer visual explanation map and ranking the input pixel importance., Comment: 10 pages, 10 figures

More than half of all main-sequence (MS) stars have one or more companions, and many of those with initial masses <8 M$_\odot$ are born in hierarchical triples. These systems feature two stars in a close orbit (the inner binary) while a tertiary star orbits them on a wider orbit (the outer binary). In hierarchical triples, three-body dynamics combined with stellar evolution drives interactions and, in many cases, merges the inner binary entirely to create a renovated `Post-Merger Binary' (PMB). By leveraging dynamical simulations and tracking binary interactions, we explore the outcomes of merged triples and investigate whether PMBs preserve signatures of their three-body history. Our findings indicate that in 26-54% of wide double WD binaries (s>100 au), the more massive white dwarf (WD) is a merger product, implying that these DWD binaries were previously triples. Overall, we estimate that $44\pm14\%$ of observed wide DWDs originated in triple star systems and thereby have rich dynamical histories. Additionally, our results suggest that the separations of inner and outer binaries are uncorrelated at birth, providing insights into stellar formation processes. We also examine MS+MS and MS+Red Giant mergers manifesting as Blue Straggler stars (BSSs). These PMBs have orbital configurations and ages similar to most observed BSS binaries. While the triple+merger formation channel can explain the observed chemical abundances, moderate eccentricities, and companion masses in BSS binaries, it likely only accounts for $\sim$20-25% of BSSs. Meanwhile, we predict that the majority of observed single BSSs formed as collisions in triples and harbor long-period (>10 yr) companions. Furthermore, both BSS binaries and DWDs exhibit signatures of WD birth kicks., Comment: Accepted for publication to ApJ. Additional comments are welcome

Increasingly, business opportunities available to fabless design teams in the semiconductor industry far exceed those addressable with on-prem compute resources. An attractive option to capture these electronic design automation (EDA) design opportunities is through public cloud bursting. However, security concerns with public cloud bursting arise from having to protect process design kits, third party intellectual property, and new design data for semiconductor devices and chips. One way to address security concerns for public cloud bursting is to leverage confidential containers for EDA workloads. Confidential containers add zero trust computing elements to significantly reduce the probability of intellectual property escapes. A key concern that often follows security discussions is whether EDA workload performance will suffer with confidential computing. In this work we demonstrate a full set of EDA confidential containers and their deployment and characterize performance impacts of confidential elements of the flow including storage and networking. A complete end-to-end confidential container-based EDA workload exhibits 7.13% and 2.05% performance overheads over bare-metal container and VM based solutions, respectively.

Various scenarios of cosmic inflation enhance the amplitude of the stochastic gravitational wave background (SGWB) at frequencies detectable by the LISA detector. We develop tools for a template-based analysis of the SGWB and introduce a template databank to describe well-motivated signals from inflation, prototype their template-based searches, and forecast their reconstruction with LISA. Specifically, we classify seven templates based on their signal frequency shape, and we identify representative fundamental physics models leading to them. By running a template-based analysis, we forecast the accuracy with which LISA can reconstruct the template parameters of representative benchmark signals, with and without galactic and extragalactic foregrounds. We identify the parameter regions that can be probed by LISA within each template. Finally, we investigate how our signal reconstructions shed light on fundamental physics models of inflation: we discuss their impact for measurements of \emph{e.g.,} ~the couplings of inflationary axions to gauge fields; the graviton mass during inflation; the fluctuation seeds of primordial black holes; the consequences of excited states during inflation, and the presence of small-scale spectral features., Comment: 82 pages, 29 figures; v2 matches version published in JCAP

This letter investigates the problem of controlling an aerial manipulator, composed of an omnidirectional tilting drone equipped with a five-degrees-of-freedom robotic arm. The robot has to interact with the environment to inspect structures and perform non-destructive measurements. A parallel force-impedance control technique is developed to establish contact with the designed surface with a desired force profile. During the interaction, a pushing phase is required to create a vacuum between the surface and the echometer sensor mounted at the end-effector, to measure the thickness of the interaction surface. Repetitive measures are performed to show the repeatability of the algorithm., Comment: In proceedings of 18th International Symposium on Experimental Robotics (ISER 2023)

The use of skeletal data allows deep learning models to perform action recognition efficiently and effectively. Herein, we believe that exploring this problem within the context of Continual Learning is crucial. While numerous studies focus on skeleton-based action recognition from a traditional offline perspective, only a handful venture into online approaches. In this respect, we introduce CHARON (Continual Human Action Recognition On skeletoNs), which maintains consistent performance while operating within an efficient framework. Through techniques like uniform sampling, interpolation, and a memory-efficient training stage based on masking, we achieve improved recognition accuracy while minimizing computational overhead. Our experiments on Split NTU-60 and the proposed Split NTU-120 datasets demonstrate that CHARON sets a new benchmark in this domain. The code is available at https://github.com/Sperimental3/CHARON., Comment: Accepted at ICPR 2024

The slow neutron capture ($s$-process) synthesises ~50% of all elements in the universe heavier than iron, whose abundances are determined by the competition between neutron capture and nuclear $\beta$-decay rates. The latter are expected to vary inside hot and dense plasmas such as those found in $s$-process nucleosynthesis sites. Here, we present a new and general theoretical study of the effect of local and non-local thermodynamic equilibrium ((N)LTE) plasmas on $\beta$-decays, using orbital electron capture (EC) decays in $^{7}$Be as a model case. We begin from the model of Takahashi and Yokoi to calculate the lepton phase volume of $^{7}$Be as a function of its ionisation state and excitation level, and consequently, the configuration-dependent EC decay rate. We then calculate the in-plasma ion charge state distribution (CSD) and level population distribution (LPD) for a grid of plasma density and temperatures, using the population kinetics code FLYCHK. By combining the configuration-dependent EC rate with the CSD and LPD, we calculate the in-plasma orbital EC rate in $^{7}$Be. The results show a strong correlation between the half-life and thermodynamic conditions of the plasma, underlining the importance of measuring decay rates in laboratory plasmas and the relevance of high precision atomic configuration models. The model discussed in this work is capable of calculating EC and bound state $\beta$ decay (BSBD) rates in both low-density NLTE and high-density LTE plasmas. We conclude by validating our model with state-of-the-art data in literature on isotopes of Pr and Dy, and by proposing future extension of the model to laboratory magnetoplasmas and stellar interiors aimed at improving nucleosynthesis models., Comment: 24 pages, 12 figures, 2 tables. Submitted to Nature Communications

Recent advancements in quantum technologies and advanced detection experiments have underscored the pressing need for the detection of exceedingly weak signals within the microwave frequency spectrum. Addressing this challenge, the Josephson Traveling Wave Parametric Amplifier (JTWPA) has been proposed as a cryogenic front-end amplifier capable of approaching the quantum noise limit while providing a relevant bandwidth. This research is centered on a comprehensive numerical investigation of the JTWPA, without resorting to simplifications regarding the nonlinearity of the essential components. Specifically, this study focuses on a thorough examination of the system, characterized by coupled nonlinear differential equations representing all components of the device. Proper input and output signals at the device's boundaries are considered. The analysis of the output signals undergoing the parametric amplification process involves a detailed exploration of phase-space dynamics and Fourier spectral analysis of the output voltage. This study is conducted while considering the parameters ruling the response of the device under pump and signal excitations. In addition to the expected signal amplification, the findings reveal that the nonlinear nature of the system can give rise to unforeseen phenomena, depending on the system's operational conditions, which include: the generation of pump tone harmonics, modulation of the signal gain, and incommensurate frequency generation-effects that are not easily accommodated by simplistic linearized approaches, Comment: 5 pages, 4 figures, DARTWARS project - INFN (Italy)

Noise at the quantum limit over a broad bandwidth is a fundamental requirement for future cryogenic experiments for neutrino mass measurements, dark matter searches and Cosmic Microwave Background (CMB) measurements as well as for fast high-fidelity read-out of superconducting qubits. In the last years, Josephson Parametric Amplifiers (JPA) have demonstrated noise levels close to the quantum limit, but due to their narrow bandwidth, only few detectors or qubits per line can be read out in parallel. An alternative and innovative solution is based on superconducting parametric amplification exploiting the travelling-wave concept. Within the DARTWARS (Detector Array Readout with Travelling Wave AmplifieRS) project, we develop Kinetic Inductance Travelling-Wave Parametric Amplifiers (KI-TWPAs) for low temperature detectors and qubit read-out. KI-TWPAs are typically operated in a threewave mixing (3WM) mode and are characterised by a high gain, a high saturation power, a large amplification bandwidth and nearly quantum limited noise performance. The goal of the DARTWARS project is to optimise the KI-TWPA design, explore new materials, and investigate alternative fabrication processes in order to enhance the overall performance of the amplifier. In this contribution we present the advancements made by the DARTWARS collaboration to produce a working prototype of a KI-TWPA, from the fabrication to the characterisation.

Superconducting parametric amplifiers offer the capability to amplify feeble signals with extremely low levels of added noise, potentially reaching quantum-limited amplification. This characteristic makes them essential components in the realm of high-fidelity quantum computing and serves to propel advancements in the field of quantum sensing. In particular, Traveling-Wave Parametric Amplifiers (TWPAs) may be especially suitable for practical applications due to their multi-Gigahertz amplification bandwidth, a feature lacking in Josephson Parametric Amplifiers (JPAs), despite the latter being a more established technology. This paper presents recent developments of the DARTWARS (Detector Array Readout with Traveling Wave AmplifieRS) project, focusing on the latest prototypes of Kinetic Inductance TWPAs (KITWPAs). The project aims to develop a KITWPA capable of achieving $20\,$ dB of amplification. To enhance the production yield, the first prototypes were fabricated with half the length and expected gain of the final device. In this paper, we present the results of the characterization of one of the half-length prototypes. The measurements revealed an average amplification of approximately $9\,$dB across a $2\,$GHz bandwidth for a KITWPA spanning $17\,$mm in length.

The reptation Monte Carlo algorithm is a simple, physically motivated and efficient method for equilibrating semi-dilute solutions of linear polymers. Here we propose two simple generalizations for the analogue {\it Amoeba} algorithm for randomly branching chains, which allow to efficiently deal with random trees with controlled branching activity. We analyse the rich relaxation dynamics of Amoeba algorithms and demonstrate the existence of an unexpected scaling regime for the tree relaxation. In particular, our results suggests that the equilibration time for Amoeba algorithms scales in general like $N^2 \langle n_{\rm lin}\rangle^\Delta$, where $N$ denotes the number of tree nodes, $\langle n_{\rm lin}\rangle$ the mean number of linear segments the trees are composed of and $\Delta \simeq 0.4$., Comment: 17 pages, 5 figures; Physical Review E, in press

The possibility that gravity plays a role in the collapse of the quantum wave function has been considered in the literature, and it is of relevance not only because it would provide a solution to the measurement problem in quantum theory, but also because it would give a new and unexpected twist to the search for a unified theory of quantum and gravitational phenomena, possibly overcoming the current impasse. The Di\'osi-Penrose model is the most popular incarnation of this idea. It predicts a progressive breakdown of quantum superpositions when the mass of the system increases; as such, it is susceptible to experimental verification. Current experiments set a lower bound $R_0\gtrsim 4 \times 10^{-10}$ m for the free parameter of the model, excluding some versions of it. In this work we search for an upper bound, coming from the request that the collapse is effective enough to guarantee classicality at the macroscopic scale: we find out that not all macroscopic systems collapse effectively. If one relaxes this request, a reasonable (although to some degree arbitrary) bound is found to be: $R_0\lesssim 10^{-4}$ m. This will serve to better direct future experiments to further test the model.

We present optical spectroscopy of 710 solar neighborhood stars collected over twenty years to catalog chromospheric activity and search for stellar activity cycles. The California Legacy Survey stars are amenable to exoplanet detection using precise radial velocities, and we present their Ca II H and K time series as a proxy for stellar and chromospheric activity. Using the HIRES spectrometer at Keck Observatory, we measured stellar flux in the cores of the Ca II H and K lines to determine S-values on the Mt. Wilson scale and the log(R'HK) metric, which is comparable across a wide range of spectral types. From the 710 stars, with 52,372 observations, 285 stars are sufficiently sampled to search for stellar activity cycles with periods of 2-25 years, and 138 stars show stellar cycles of varying length and amplitude. S-values can be used to mitigate stellar activity in the detection and characterization of exoplanets. We use them to probe stellar dynamos and to place the Sun's magnetic activity into context among solar neighborhood stars. Using precise stellar parameters and time-averaged activity measurements, we find tightly constrained cycle periods as a function of stellar temperature between log(R'HK) of -4.7 and -4.9, a range of activity in which nearly every star has a periodic cycle. These observations present the largest sample of spectroscopically determined stellar activity cycles to date., Comment: 40 pages, 26 figures, submitted to ApJS

The Event Horizon Telescope has produced resolved images of the supermassive black holes Sgr A* and M87*, which present the largest shadows on the sky. In the next decade, technological improvements and extensions to the array will enable access to a greater number of sources, unlocking studies of a larger population of supermassive black holes through direct imaging. In this paper, we identify 12 of the most promising sources beyond Sgr A* and M87* based on their angular size and millimeter flux density. For each of these sources, we make theoretical predictions for their observable properties by ray tracing general relativistic magnetohydrodynamic models appropriately scaled to each target's mass, distance, and flux density. We predict that these sources would have somewhat higher Eddington ratios than M87*, which may result in larger optical and Faraday depths than previous EHT targets. Despite this, we find that visibility amplitude size constraints can plausibly recover masses within a factor of 2, although the unknown jet contribution remains a significant uncertainty. We find that the linearly polarized structure evolves substantially with Eddington ratio, with greater evolution at larger inclinations, complicating potential spin inferences for inclined sources. We discuss the importance of 345 GHz observations, milli-Jansky baseline sensitivity, and independent inclination constraints for future observations with upgrades to the Event Horizon Telescope (EHT) through ground updates with the next-generation EHT (ngEHT) program and extensions to space through the Black Hole Explorer (BHEX)., Comment: 21 pages, 9 figures, 1 table, submitted to ApJ

Flattery is an important aspect of human communication that facilitates social bonding, shapes perceptions, and influences behavior through strategic compliments and praise, leveraging the power of speech to build rapport effectively. Its automatic detection can thus enhance the naturalness of human-AI interactions. To meet this need, we present a novel audio textual dataset comprising 20 hours of speech and train machine learning models for automatic flattery detection. In particular, we employ pretrained AST, Wav2Vec2, and Whisper models for the speech modality, and Whisper TTS models combined with a RoBERTa text classifier for the textual modality. Subsequently, we build a multimodal classifier by combining text and audio representations. Evaluation on unseen test data demonstrates promising results, with Unweighted Average Recall scores reaching 82.46% in audio-only experiments, 85.97% in text-only experiments, and 87.16% using a multimodal approach., Comment: Interspeech 2024

We consider an infinite-range interacting quantum spin-1/2 model, undergoing periodic kicking and dissipatively coupled with an environment. In the thermodynamic limit, it is described by classical mean-field equations that can show regular and chaotic regimes. At finite size, we describe the system dynamics using stochastic quantum trajectories. We find that the asymptotic nonstabilizerness (alias the magic, a measure of quantum complexity), averaged over trajectories, mirrors to some extent the classical chaotic behavior, while the entanglement entropy has no relation with chaos in the thermodynamic limit., Comment: 16 pages, 15 figures

We present a lattice model for polymer solutions, explicitly incorporating interactions with solvent molecules and the contribution of vacancies. By exploiting the well-known analogy between polymer systems and the $O(n)$-vector spin model in the limit $n \to 0$, we derive an exact field-theoretic expression for the partition function of the system. The latter is then evaluated at the saddle-point, providing a mean-field estimate of the free energy. The resulting expression, which conforms to the Flory-Huggins type, is then used to analyze the system's stability with respect to phase separation, complemented by a numerical approach based on convex hull evaluation. We demonstrate that this simple lattice model can effectively explain the behavior of polymer systems in explicit solvent, which has been predominantly investigated through numerical simulations. This includes both single-chain systems and polymer solutions. Our findings emphasize the fundamental role of vacancies whose presence, rendering the system a ternary mixture, is a crucial factor in the observed phase behavior., Comment: 7 pages, 4 figures (main); 11 pages, 4 figures (suppl info); submitted for publication

Measuring Deeply Virtual Compton Scattering on the neutron is one of the necessary steps to understand the structure of the nucleon in terms of Generalized Parton Distributions (GPDs). Neutron targets play a complementary role to transversely polarized proton targets in the determination of the GPD $E$. This poorly known and poorly constrained GPD is essential to obtain the contribution of the quarks' angular momentum to the spin of the nucleon. DVCS on the neutron was measured for the first time selecting the exclusive final state by detecting the neutron, using the Jefferson Lab longitudinally polarized electron beam, with energies up to 10.6 GeV, and the CLAS12 detector. The extracted beam-spin asymmetries, combined with DVCS observables measured on the proton, allow a clean quark-flavor separation of the imaginary parts of the GPDs $H$ and $E$., Comment: 7 pages, 6 figures

We introduce the Parity-Odd Power (POP) spectra, a novel set of observables for probing parity violation in cosmological $N$-point statistics. POP spectra are derived from composite fields obtained by applying nonlinear transformations, involving also gradients, curls, and filtering functions, to a scalar field. This compresses the parity-odd trispectrum into a power spectrum. These new statistics offer several advantages: they are computationally fast to construct, estimating their covariance is less demanding compared to estimating that of the full parity-odd trispectrum, and they are simple to model theoretically. We measure the POP spectra on simulations of a scalar field with a specific parity-odd trispectrum shape. We compare these measurements to semi-analytic theoretical calculations and find agreement. We also explore extensions and generalizations of these parity-odd observables., Comment: 18 pages, 5 figures