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Distant quasars (QSOs) in galaxy overdensities are considered key actors in the evolution of the early Universe. In this work, we studied the kinematic and physical properties of the BR1202-0725 system at z=4.7, one of the most overdense fields known in the early Universe, consisting of a QSO, a submillimeter galaxy (SMG), and three Lyman-$\alpha$ emitters. We used data from the JWST/NIRSpec Integral Field Unit (IFU) to analyze the rest-frame optical emission of each source in the system. We estimated a bolometric luminosity of log($L_{\rm bol}/$[erg/s]) = 47.2 $\pm$ 0.4 and a black hole mass of log($M_{\rm BH}/M_\odot$) = 10.1 $\pm$ 0.5 for the QSO, which are consistent with previous measurements obtained with ground-based observations. The NIRSpec spectra of the SMG revealed instead unexpected [OIII] and H$\alpha$+[NII] profiles. The overall [OIII] line profile is blue-shifted by more than 700 km/s relative to the systemic velocity of the galaxy. Additionally, both the [OIII] and H$\alpha$+[NII] lines show prominent broad (1300 km/s), blueshifted wings associated with outflowing ionized gas. The analysis of NIRSpec and X-ray observations indicates that the SMG likely hosts an accreting supermassive black hole as supported by the following results: (i) the excitation diagnostic diagram is consistent with ionization from an active galactic nucleus (AGN); (ii) the X-ray luminosity is higher than $10^{44}$ erg/s; and (iii) it hosts a fast outflow ($v_{\rm out}$ = 5000 km/s), comparable to those observed in luminous QSOs. Therefore, the QSO-SMG pair represents one of the highest-redshift double AGN to date, with a projected separation of 24 kpc. Finally, we investigated the environment of this system and found four new galaxies at the same redshift of the QSO and within a projected distance of 5 kpc from it. This overdense system includes at least ten galaxies in only 980 kpc$^2$., Comment: 21 pages, 19 figures, Submitted to Astronomy & Astrophysics

To address the challenge posed by noise in real quantum devices, quantum error mitigation techniques play a crucial role. These techniques are resource-efficient, making them suitable for implementation in noisy intermediate-scale quantum devices, unlike the more resource-intensive quantum error correction codes. A notable example of such a technique is Clifford Data Regression, which employs a supervised learning approach. This work investigates two variants of this technique, both of which introduce a non-trivial set of gates into the original circuit. The first variant uses multiple copies of the original circuit, while the second adds a layer of single-qubit rotations. Different characteristics of these methods are analyzed theoretically, such as their complexity, or the scaling of the error with various parameters. Additionally, the performance of these methods is evaluated through numerical experiments, demonstrating a reduction in root mean square error.

A set of n non-collinear points in the Euclidean plane defines at least n different lines. Chen and Chv\'tal in 2008 conjectured that the same results is true in metric spaces for an adequate definition of line. More recently, it was conjectured in 2018 by Aboulker et al. that any large enough bridgeless graph on n vertices defines a metric space that has at least n lines. We study the natural extension of Aboulker et al.'s conjecture into the context of quasi-metric spaces defined by digraphs of low diameter. We prove that it is valid for quasi-metric spaces defined by bipartite digraphs of diameter at most three, oriented graphs of diameter two and, digraphs of diameter three and directed girth four.

For a digraph $D$ of order $n$ and an integer $1 \leq k \leq n-1$, the $k$-token digraph of $D$ is the graph whose vertices are all $k$-subsets of vertices of $D$ and, given two such $k$-subsets $A$ and $B$, $(A,B)$ is an arc in the $k$-token digraph whenever $\{a\} = A \setminus B$, $\{b\} = B \setminus A$, and there is an arc $(a,b)$ in $D$. Token digraphs are a generalization of token graphs. In this paper, we study some properties of token digraphs, including strong and unilateral connectivity, kernels, girth, circumference and Eulerianity. We also extend some known results on the clique and chromatic numbers of $k$-token graphs, addressing the bidirected clique number and dichromatic number of $k$-token digraphs. Additionally, we prove that determining whether $2$-token digraphs have a kernel is NP-complete., Comment: 24 pages, 9 figures

In the frame of the linear sigma model and working in the weak field approximation, we discuss the role played by an external electric field on the behavior of $\pi$-$\pi$ scattering lengths. For this purpose, we have considered all relevant one-loop diagrams in the $s$, $t$, and $u$ channels where we have Schwinger propagators for charged pions. An important novelty of our analysis, compared with previous existing discussions in the literature, is the explicit calculation of box diagrams which were previously not considered in discussions regarding magnetic corrections to $\pi$-$\pi$ scattering lengths. Our analysis shows that electric field corrections have an opposite effect with respect to the previously calculated magnetic corrections., Comment: Contribution to the 27th High-Energy Physics Conference in Quantum Chromodynamics, Montpellier, 2024. To appear in Nuclear and Particle Physics Proceedings

We present an analysis of Bogot'{a}'s sports sector through thermostatistical models applied to economic systems. The study investigates the cross-price elasticity of income ($\lambda$) to determine whether sports services in Bogot'{a} are normal or inferior goods. Analyzing data from the Sports Satellite Account of Bogot'{a} (CSDB) from 2018 to 2022, we find that demand for sports services is highly elastic, particularly during economic upturns, indicating they are seen as normal or luxury goods. We also calculate the partition function, entropy, and heat capacity, showing consistency with the Boltzmann Principle, which indicates a strong correlation between microstates and the macroeconomic state, supporting the statistical thermodynamic framework. Furthermore, the study employs geometrothermodynamics to assess system stability using Kretschmann and Ricci scalars to identify economic singularities, especially during the pandemic, highlighting its disruptive impact. This approach provides a nuanced understanding of system stability and the effects of external shocks like COVID-19 on the economic structure. Our analysis demonstrates that Bogot'{a}'s sports sector responds elastically to GDP changes, with stability influenced by various macroeconomic factors. However, a decline in heat capacity as economic temperature rises suggests potential growth limitations, necessitating further research to fully grasp the sector's long-term outlook., Comment: 25 pages, 19 figures

In this paper, we study the effects of vorticity on the QCD phase transition using the Linear Sigma Model coupled to quarks. By going beyond the mean-field approximation and incorporating screening effects via ring diagrams, we explore the chiral symmetry restoration in extreme conditions, such as high temperatures, high densities, and large angular velocities. Our analysis reveals how the critical temperature decreases as the angular velocity increases, suggesting that vorticity catalyzes the symmetry restoration. Additionally, we observe a shift in the Critical End Point (CEP) in the effective QCD phase diagram, where higher angular velocities move the CEP to lower quark chemical potentials and higher temperatures. Moreover, we analyze the baryon number fluctuations through the normalized fourth moment $\kappa \sigma^2 = c_4/c_2$ as a function of the collision energy in heavy-ion reactions $\sqrt{s_{NN}}$, which serves as a key observable to identify the CEP. Our study reveals that for high collision energies, $\kappa \sigma^2$ remains nearly constant; however, as the system approaches the CEP, the ratio increases sharply, indicating the proximity of the critical region. This rise is influenced by the presence of vorticity, which causes the CEP to shift to higher collision energies. These findings provide insight into the role of vorticity in heavy-ion collisions, Comment: 11 pages, 7 figures

The internal structure of the lowest-lying pseudo-scalar mesons with heavy-light quark content is thoroughly studied using an algebraic model that has been successfully applied to similar physical observables of pseudoscalar and vector mesons with hidden-flavor quark content, ranging from light to heavy quark sectors. This model is based on constructing simple and evidence-based ans\"atze for the mesons' Bethe-Salpeter amplitude (BSA) and quark propagator, allowing the Bethe-Salpeter wave function (BSWF) to be computed algebraically. Its projection onto the light front yields the corresponding light-front wave function (LFWF), which provides easy access to the valence-quark Parton Distribution Amplitude (PDA) by integrating over the transverse momentum squared. We leverage our current knowledge of the PDAs of the lowest-lying pseudo-scalar heavy-light mesons to compute their Generalized Parton Distributions (GPDs) via the overlap representation of the LFWFs. From this three-dimensional information, various limits and projections allow us to deduce the related Parton Distribution Functions (PDFs), Electromagnetic Form Factors (EFFs), and Impact Parameter Space GPDs (IPS-GPDs). Whenever possible, we make explicit comparisons with available experimental results and previous theoretical predictions., Comment: Submitted to the proceedings of the 10th International Conference on Quarks and Nuclear Physics (QNP2024), PoS format

This work describes the elaboration of rutile titanium dioxide films with high refractive indices and low scattering by sol-gel process and controlled crystallization. The evolutions of the optical properties and crystalline structure of sol-gel processed titania coatings on fused silica were investigated for different thermal budgets of the annealing post-treatment using ellipsometry, spectrophotometry, X-ray diffraction and electronic microscopy. It reveals that anatase and rutile coatings with refractive indices of 2.5 and 2.7 can be prepared with associated optical loss of 0.5% and 1%, respectively, which are excellent compromise for applications in integrated photonics. These evolutions are associated to the thermally induced mass transfer and phase transitions occurring during thermal annealing that involves first the nucleation growth and sintering of anatase polyoriented nanocrystals, followed by the transformation into rutile polyoriented nanocrystals. Concomitantly, rutile crystals with (110) faces parallel to the surface consume surrounding anatase and rutile nanocrystals by diffusive sintering to yield micron-size rutile monocrystalline and monooriented platelets patchwork, exhibiting refractive index of 2.73 and 1.2% optical loss. The formation of these platelets is governed by surface energies and is responsible for the increase in optical loss.

Data-driven methods have shown great potential in solving challenging manipulation tasks, however, their application in the domain of deformable objects has been constrained, in part, by the lack of data. To address this, we propose PokeFlex, a dataset featuring real-world paired and annotated multimodal data that includes 3D textured meshes, point clouds, RGB images, and depth maps. Such data can be leveraged for several downstream tasks such as online 3D mesh reconstruction, and it can potentially enable underexplored applications such as the real-world deployment of traditional control methods based on mesh simulations. To deal with the challenges posed by real-world 3D mesh reconstruction, we leverage a professional volumetric capture system that allows complete 360{\deg} reconstruction. PokeFlex consists of 18 deformable objects with varying stiffness and shapes. Deformations are generated by dropping objects onto a flat surface or by poking the objects with a robot arm. Interaction forces and torques are also reported for the latter case. Using different data modalities, we demonstrated a use case for the PokeFlex dataset in online 3D mesh reconstruction. We refer the reader to our website ( https://pokeflex-dataset.github.io/ ) for demos and examples of our dataset.

We present VLT/MUSE integral-field spectroscopy ($R\approx 1\,800$) of four giant gravitational arcs exhibiting strong C IV absorption at 8 intervening redshifts, $z_{abs}\approx 2.0$--$2.5$. We detect C IV absorption in a total of 222 adjacent and seeing-uncorrelated sightlines, whose spectra sample beams of ("de-lensed") linear size $\approx 1$ kpc. Our data show that (1) absorption velocities cluster at all probed transverse scales, $\Delta r_\perp\approx0$--$15$ kpc, depending on system; (2) the (transverse) velocity dispersion never exceeds the mean (line-of-sight) absorption spread; and (3) the (transverse) velocity autocorrelation function does not resolve kinematic patterns at the above spatial scales, but its velocity projection, $\xi^{arc}(\Delta v)$, exhibits a similar shape to the known two-point correlation function toward quasars, $\xi^{QSO}(\Delta v)$. An empirical kinematic model suggests that these results are a natural consequence of wide-beam observations of an unresolved clumpy medium. Our model recovers both the underlying velocity dispersion of the clumps ($70$--$170$ \kms) and the mean number of clumps per unit area ($2$--$13$ kpc$^{-2}$). The latter constrains the projected mean inter-clump distance to within $\approx0.3$--$0.8$ kpc, which we argue is a measure of clump size for near-unity covering fraction. The model is also able to predict $\xi^{arc}(\Delta v)$ from $\xi^{QSO}(\Delta v)$, suggesting that the strong systems that shape the former and the line-of-sight velocity components that define the latter trace the same kinematic population. Consequently, the clumps must possess an internal density structure that generates both weak and strong components. We discuss how our interpretation is consistent with previous observations using background galaxies and multiple quasars., Comment: Accepted for publication in A&A

Advancing robotic manipulation of deformable objects can enable automation of repetitive tasks across multiple industries, from food processing to textiles and healthcare. Yet robots struggle with the high dimensionality of deformable objects and their complex dynamics. While data-driven methods have shown potential for solving manipulation tasks, their application in the domain of deformable objects has been constrained by the lack of data. To address this, we propose PokeFlex, a pilot dataset featuring real-world 3D mesh data of actively deformed objects, together with the corresponding forces and torques applied by a robotic arm, using a simple poking strategy. Deformations are captured with a professional volumetric capture system that allows for complete 360-degree reconstruction. The PokeFlex dataset consists of five deformable objects with varying stiffness and shapes. Additionally, we leverage the PokeFlex dataset to train a vision model for online 3D mesh reconstruction from a single image and a template mesh. We refer readers to the supplementary material and to our website ( https://pokeflex-dataset.github.io/ ) for demos and examples of our dataset., Comment: Extended Abstract, 40th Anniversary of the IEEE International Conference on Robotics and Automation. (ICRA@40 Rotterdam 2024)

We explore the Schmidt-Kennicutt (SK) relations and the star formation efficiency per free-fall time ($\eff$), mirroring observational studies, in numerical simulations of filamentary molecular clouds undergoing gravitational contraction. We find that {\it a)} collapsing clouds accurately replicate the observed SK relations for galactic clouds and {\it b)} the so-called efficiency per free-fall time ($\eff$) is small and constant in space and in time, with values similar to those found in local clouds. This constancy is a consequence of the similar radial scaling of the free-fall time and the internal mass in density structures with spherically-averaged density profiles near $r^{-2}$. We additionally show that {\it c)} the star formation rate (SFR) increases rapidly in time; {\it d)} the low values of $\eff$ are due to the different time periods over which $\tauff$ and $\tausf$ are evaluated, together with the fast increasing SFR, and {\it e)} the fact that star clusters are significantly denser than the gas clumps from which they form is a natural consequence of the fast increasing SFR, the continuous replenishment of the star-forming gas by the accretion flow, and the near $r^{-2}$ density profile generated by the collapse Finally, we argue that the interpretation of $\eff$ as an efficiency is problematic because its maximum value is not bounded by unity, and because the total gas mass in the clouds is not fixed, but rather depends on the environment where clouds are embedded. In summary, our results show that the SK relation, the typical observed values of $\eff$, and the mass density of clusters arise as a natural consequence of gravitational contraction., Comment: Submitted to MNRAS

Coastal marine ecosystems face mounting pressures from anthropogenic activities and climate change, necessitating advanced monitoring and modeling approaches for effective management. This paper pioneers the development of a Marine Digital Twin Platform aimed at modeling the Mar Menor Coastal Lagoon Ecosystem in the Region of Murcia. The platform leverages Artificial Intelligence to emulate complex hydrological and ecological models, facilitating the simulation of what-if scenarios to predict ecosystem responses to various stressors. We integrate diverse datasets from public sources to construct a comprehensive digital representation of the lagoon's dynamics. The platform's modular design enables real-time stakeholder engagement and informed decision-making in marine management. Our work contributes to the ongoing discourse on advancing marine science through innovative digital twin technologies.

A search for Dark Sectors is performed using the unique M2 beam line at the CERN Super Proton Synchrotron. New particles ($X$) could be produced in the bremsstrahlung-like reaction of high energy 160 GeV muons impinging on an active target, $\mu N\rightarrow\mu NX$, followed by their decays, $X\rightarrow\text{invisible}$. The experimental signature would be a scattered single muon from the target, with about less than half of its initial energy and no activity in the sub-detectors located downstream the interaction point. The full sample of the 2022 run is analyzed through the missing energy/momentum channel, with a total statistics of $(1.98\pm0.02)\times10^{10}$ muons on target. We demonstrate that various muon-philic scenarios involving different types of mediators, such as scalar or vector particles, can be probed simultaneously with such a technique. For the vector-case, besides a $L_\mu-L_\tau$ $Z'$ vector boson, we also consider an invisibly decaying dark photon ($A'\rightarrow\text{invisible}$). This search is complementary to NA64 running with electrons and positrons, thus, opening the possibility to expand the exploration of the thermal light dark matter parameter space by combining the results obtained with the three beams., Comment: 24 pages, 22 figures

We present a novel metric designed, among other applications, to quantify biased behaviors of machine learning models. As its core, the metric consists of a new similarity metric between score distributions that balances both their general shapes and tails' probabilities. In that sense, our proposed metric may be useful in many application areas. Here we focus on and apply it to the operational evaluation of face recognition systems, with special attention to quantifying demographic biases; an application where our metric is especially useful. The topic of demographic bias and fairness in biometric recognition systems has gained major attention in recent years. The usage of these systems has spread in society, raising concerns about the extent to which these systems treat different population groups. A relevant step to prevent and mitigate demographic biases is first to detect and quantify them. Traditionally, two approaches have been studied to quantify differences between population groups in machine learning literature: 1) measuring differences in error rates, and 2) measuring differences in recognition score distributions. Our proposed Comprehensive Equity Index (CEI) trade-offs both approaches combining both errors from distribution tails and general distribution shapes. This new metric is well suited to real-world scenarios, as measured on NIST FRVT evaluations, involving high-performance systems and realistic face databases including a wide range of covariates and demographic groups. We first show the limitations of existing metrics to correctly assess the presence of biases in realistic setups and then propose our new metric to tackle these limitations. We tested the proposed metric with two state-of-the-art models and four widely used databases, showing its capacity to overcome the main flaws of previous bias metrics., Comment: Accepted paper for the 27th International Conference on Pattern Recognition (ICPR) 2024

The main purpose of this work is the derivation of a functional partial differential equation (FPDE) for the calculations of equity-linked insurance policies, where the payment stream may depend on the whole past history of the financial asset. To this end, we employ variational techniques from the theory of functional It\^o calculus.

Ultralight dark matter, such as kinetically mixed dark-photon dark matter (DPDM) or axionlike-particle dark matter (axion DM), can source an oscillating magnetic-field signal at Earth's surface. Previous work searched for this signal in a publicly available dataset of global magnetometer measurements maintained by the SuperMAG collaboration. This "low-fidelity" dataset reported measurements with a 1-minute time resolution, allowing the search to set leading direct constraints on DPDM and axion DM with Compton frequencies $f_\mathrm{DM}\leq1/(1\,\mathrm{min})$ [corresponding to masses $m_\mathrm{DM}\leq7\times10^{-17}\,\mathrm{eV}$]. More recently, a dedicated experiment undertaken by the SNIPE Hunt collaboration has also searched for this same signal at higher frequencies $f_\mathrm{DM}\geq0.5\,\mathrm{Hz}$ (or $m_\mathrm{DM}\geq2\times10^{-15}\,\mathrm{eV}$). In this work, we search for this signal of ultralight DM in the SuperMAG "high-fidelity" dataset, which features a 1-second time resolution, allowing us to probe the gap in parameter space between the low-fidelity dataset and the SNIPE Hunt experiment. The high-fidelity dataset exhibits lower geomagnetic noise than the low-fidelity dataset and features more data than the SNIPE Hunt experiment, making it a powerful probe of ultralight DM. Our search finds no robust DPDM or axion DM candidates. We set constraints on DPDM and axion DM parameter space for $10^{-3}\,\mathrm{Hz}\leq f_\mathrm{DM}\leq0.98\,\mathrm{Hz}$ (or $4\times10^{-18}\,\mathrm{eV}\leq m_\mathrm{DM}\leq4\times10^{-15}\,\mathrm{eV}$). Our results are the leading direct constraints on both DPDM and axion DM in this mass range, and our DPDM constraint surpasses the leading astrophysical constraint in a narrow range around $m_{A'}\approx2\times10^{-15}\,\mathrm{eV}$., Comment: 18 pages, 5 figures

The emergence of cognition requires a framework that bridges evolutionary principles with neurocomputational mechanisms. This paper introduces the novel "thoughtseed" framework, proposing that cognition arises from the dynamic interaction of self-organizing units of embodied knowledge called "thoughtseeds" within the Global Workspace of consciousness. Leveraging foundational concepts from evolutionary theory, neuronal packets, and free energy principle, we propose a hierarchical model of cognitive states, comprising Neuronal Packet Domains (NPDs), Knowledge Domains (KDs), the thoughtseed network, and meta-cognition. This hierarchical interplay, mediated by nested Markov blankets and reciprocal message passing, facilitates the emergence of thoughtseeds as coherent patterns of activity that guide perception, action, and learning. Thoughtseeds, posited as fundamental units of thought, compete for dominance within the Global Workspace, with the dominant thoughtseed shaping conscious experience and guiding behavior. We present a mathematical framework grounded in active inference and dynamical systems theory to model thoughtseed dynamics and their contribution to the unitary nature of consciousness. The thoughtseed framework offers a promising step towards a novel, biologically-grounded model for understanding the organizing principles and emergence of embodied cognition, offering a unified account of cognitive phenomena, with potential applications in understanding consciousness, attention, and decision-making., Comment: 2nd version. Reduced in size from 88 pages to 48 pages, to focus on the core framework. Items removed: Detailed discussions on Evolutionary Biology, contemplative traditions and computational theories of Mind. Replaced Inner Screen Model with Global Workspace Theory. Mathematical equations have been streamlined and is better organized. preprint arXiv:2408.15982

In various industrial sectors, inspection and maintenance tasks using UAV (Unmanned Aerial Vehicle) require substantial force application to ensure effective adherence and stable contact, posing significant challenges to existing solutions. This paper addresses these industrial needs by introducing a novel lightweight aerial platform (3.12kg) designed to exert high pushing forces on non-horizontal surfaces. To increase maneuverability, the proposed platform incorporates tiltable rotors with 5-DoF (Degree of Freedom) actuation. Moreover, it has an innovative shifting-mass mechanism that dynamically adjusts the system's CoM (Center of Mass) during contact-based task execution. A compliant EE (End-Effector) is applied to ensure a smooth interaction with the work surface. We provide a detailed study of the UAV's overall system design, hardware integration of the developed physical prototype, and software architecture of the proposed control algorithm. Physical experiments were conducted to validate the control design and explore the force generation capability of the designed platform via a pushing task. With a total mass of 3.12kg, the UAV exerted a maximum pushing force of above 28N being almost equal to its gravity force. Furthermore, the experiments illustrated the benefits of having displaced CoM by benchmarking with a fixed CoM configuration.

We explain the large variety of star formation laws in terms of one single, simple law that can be inferred from the definition of the star formation rate and basic algebra. The resulting equation, $\SFR = \eff\ \Mcollapsing/\tauff$, although it has been presented elsewhere, is interpreted in terms of clouds undergoing collapse { rather than being turbulence-supported, an idea that different groups have pursued this century}. Under such assumption, one can explain the constancy of $\eff$, the different intra-cloud correlations observed in Milky Way's molecular clouds, as well as the resolved and unresolved extragalactic relationships between SFR and a measurement of the mass in CO, HCN, and CO+HI. We also explain why the slope of the correlation changes when the orbital time $\tauorb$ is considered instead of the free-fall time, and why estimations of the free-fall time from extragalactic observations skew the correlation, providing a false sublinear correlation. We furthermore show that the apparent nearly linear correlation between the star formation rate and the dynamical equilibrium pressure in the midplane of the galaxies, $\PDE$, is just a consequence of $\PDE$ values being dominated by the variation of the column density of molecular gas. All in all, we argue that the star formation law is driven by the collapse of cold, dense gas, which happens to be primarily molecular in the present Universe, and that the role of stellar feedback is just to shut down the star formation process, not to shape the star formation law., Comment: 17 pages, one figure. Accepted by MNRAS

The indeque number of a graph is largest set of vertices that induce an independent set of cliques. We study the extremal value of this parameter for the class and subclasses of planar graphs, most notably for forests and graphs of pathwidth at most $2$.

Given $G$ an algebraic reductive group over an algebraically closed field of characteristic zero and $\Gamma$ a finitely generated group, we provide a stratification of the $G$-character variety of $\Gamma$ in terms of conjugacy classes of parabolic subgroups of $G$. Each stratum has the structure of a pseudo-quotient, which is a relaxed GIT notion capturing the topology of the quotient and, therefore, behaving well for motivic computations of invariants of the character varieties. These stratifications are constructed by analyzing the root datum of $G$ to encode parabolic classes. Finally, detailed and explicit motivic formulae are provided for cases with Dynkin diagram of types $A$, $B$, $C$ and $D$., Comment: 29 pages. Comments are welcome!

Galactic outflows driven by star formation or active galactic nuclei are typically formed by multi-phase gas whose temperature spans over 4 orders of magnitude. Probing the different outflow components requires multi-wavelength observations and long exposure times, especially in the distant Universe. So far, most of the high-z studies have focused on a single gas phase, but this kind of analysis may potentially miss a non-negligible fraction of the total outflowing gas content. In this work, we analyze the spatially resolved rest-frame UV and optical emission from HZ4, the highest redshift main sequence star-forming galaxy having a detected [C II] outflow, which traces the neutral gas component. Our goal is to study the ionized interstellar medium in the galaxy and the properties of the ionized outflow as traced by the [O III]$\lambda$5007\r{A} and H$\alpha$ emission lines. We exploit JWST/NIRSpec observations in the integral field spectroscopy mode to investigate the galaxy properties by making use of the brightest rest-frame optical emission lines. Their high spectral and spatial resolution allows us to trace the ionized outflow from broad line wings and spatially resolve it. We also re-analyze the [C II] ALMA data to compare the neutral atomic and ionized outflow morphologies, masses, and energetics. We find that the system consists of a galaxy merger, instead of a rotating disk as originally inferred from low-resolution [C II] observations, and hosts an extended ionized outflow. The ionized outflow is being launched from a region hosting an intense burst of star formation and extends over 4 kpc from the launch site. The neutral and ionized outflows are almost co-spatial, but the mass loading factor in the ionized gas phase is two orders of magnitude smaller than in the neutral phase, as found for other lower redshift multi-phase outflows., Comment: 22 pages, 20 figures, submitted to A&A

The strength distributions of the Isoscalar Giant Monopole Resonance (ISGMR) and Isoscalar Giant Quadrupole Resonance (ISGQR) in 142,146-150Nd have been determined via inelastic alpha-particle scattering with the Grand Raiden (GR) Spectrometer at the Research Center for Nuclear Physics (RCNP), Japan. In the deformed nuclei 146-150Nd, the ISGMR strength distributions exhibit a splitting into two components, while the nearly spherical nucleus 142Nd displays a single peak in the ISGMR strength distribution. A noteworthy achievement in this study is the first-time detection of overtones in the Isoscalar Giant Quadrupole Resonance (ISGQR) strength distributions within Nd isotopes at an excitation energy around 25 MeV obtained through Multipole Decomposition Analysis (MDA)., Comment: Accepted for publication in Physics Letters B

Detecting and classifying lesions in breast ultrasound images is a promising application of artificial intelligence (AI) for reducing the burden of cancer in regions with limited access to mammography. Such AI systems are more likely to be useful in a clinical setting if their predictions can be explained to a radiologist. This work proposes an explainable AI model that provides interpretable predictions using a standard lexicon from the American College of Radiology's Breast Imaging and Reporting Data System (BI-RADS). The model is a deep neural network featuring a concept bottleneck layer in which known BI-RADS features are predicted before making a final cancer classification. This enables radiologists to easily review the predictions of the AI system and potentially fix errors in real time by modifying the concept predictions. In experiments, a model is developed on 8,854 images from 994 women with expert annotations and histological cancer labels. The model outperforms state-of-the-art lesion detection frameworks with 48.9 average precision on the held-out testing set, and for cancer classification, concept intervention is shown to increase performance from 0.876 to 0.885 area under the receiver operating characteristic curve. Training and evaluation code is available at https://github.com/hawaii-ai/bus-cbm., Comment: Submitted version of manuscript accepted at MICCAI 2024. This preprint has not undergone peer review or any post-submission improvements or corrections

Isoscalar giant resonances are nuclear collective excitations associated with the oscillation in phase of protons and neutrons according to a certain multipolarity $L$. In particular, the isoscalar giant monopole resonance ($L=0$) is the strongest nuclear compression mode, and its excitation energy is directly related to the compression modulus for finite nuclei. Typically, microscopic calculations are utilized to establish a relationship between the experimental compression modulus and the nuclear incompressibility that is a crucial parameter of the equation of state for nuclear matter. The incompressibility of nuclear matter has been determined with an accuracy of 10 to 20\% using relativistic and non-relativistic microscopic models for describing the monopole distributions in ${}^{208}$Pb and ${}^{90}$Zr isotopes. However, the same theoretical models are not able to describe data for open-shell nuclei, such as those of tin and cadmium isotopes. In fact, only effective interactions with a softer nuclear-matter incompressibility are able to predict the centroid energy of monopole distributions for open-shell nuclei. An unified description of the monopole resonance in ${}^{208}$Pb and other open-shell nuclei remains unsolved from the theory side. Most of this uncertainty is due to our poor knowledge of the symmetry energy, which is another essential component of the equation of state of nuclear matter. Therefore, new experimental data along isotopic chains covering a wide range in $N/Z$ ratios, including neutron-deficient and neutron-rich nuclei, are of paramount importance for determining both the nuclear-matter incompressibility and the symmetry energy more precisely., Comment: In Oxford Research Encyclopedia of Physics

We derive a semi-analytical pricing formula for European VIX call options under the Heston-Hawkes stochastic volatility model introduced in arXiv:2210.15343. This arbitrage-free model incorporates the volatility clustering feature by adding an independent compound Hawkes process to the Heston volatility. Using the Markov property of the exponential Hawkes an explicit expression of $\text{VIX}^2$ is derived as a linear combination of the variance and the Hawkes intensity. We apply qualitative ODE theory to study the existence of some generalized Riccati ODEs. Thereafter, we compute the joint characteristic function of the variance and the Hawkes intensity exploiting the exponential affine structure of the model. Finally, the pricing formula is obtained by applying standard Fourier techniques., Comment: 28 pages

Insects represent half of all global biodiversity, yet many of the world's insects are disappearing, with severe implications for ecosystems and agriculture. Despite this crisis, data on insect diversity and abundance remain woefully inadequate, due to the scarcity of human experts and the lack of scalable tools for monitoring. Ecologists have started to adopt camera traps to record and study insects, and have proposed computer vision algorithms as an answer for scalable data processing. However, insect monitoring in the wild poses unique challenges that have not yet been addressed within computer vision, including the combination of long-tailed data, extremely similar classes, and significant distribution shifts. We provide the first large-scale machine learning benchmarks for fine-grained insect recognition, designed to match real-world tasks faced by ecologists. Our contributions include a curated dataset of images from citizen science platforms and museums, and an expert-annotated dataset drawn from automated camera traps across multiple continents, designed to test out-of-distribution generalization under field conditions. We train and evaluate a variety of baseline algorithms and introduce a combination of data augmentation techniques that enhance generalization across geographies and hardware setups., Comment: Published at ECCV 2024. The dataset is publicly available at https://github.com/RolnickLab/ami-dataset

For a polycyclic group $\Lambda$, $\text{rank} ( \Lambda )$ is defined as the number of $\mathbb{Z}$ factors in a polycyclic decomposition of $\Lambda$. For a finitely generated group $G$, $\text{rank} (G)$ is defined as the infimum of $ \text{rank} (\Lambda )$ among finite index polycyclic subgroups $\Lambda \leq G$. For a compact $\text{RCD} (K,N)$ space $(X,\mathsf{d}, \mathfrak{m})$ with $\text{diam} (X) \leq \varepsilon (K,N)$, the rank of $\pi_1(X)$ is at most $N$. In this note we show that in case of equality, $X$ is homeomorphic to an infranilmanifold, generalizing to the non-smooth setting a result by Kapovitch--Wilking. We also fill a gap in the proof that if $\pi_1(X) = \mathbb{Z}^N$, then $X$ is bi-H\"older homeomorphic to a flat torus (diffeomorphic in the smooth case)., Comment: Updated references

We present the first results from a proof-of-concept search for dark sectors via invisible decays of pseudoscalar $\eta$ and $\eta'$ mesons in the NA64h experiment at the CERN SPS. Our novel technique uses the charge-exchange reaction of 50 GeV $\pi^-$ on nuclei of an active target as the source of neutral mesons. The $\eta, \eta' \to invisible$ events would exhibit themselves via a striking signature - the complete disappearance of the incoming beam energy in the detector. No evidence for such events has been found with $2.9\times10^{9}$ pions on target accumulated during one day of data taking. This allows us to set a stringent limit on the branching ratio ${\rm Br}(\eta' \to invisible) < 2.1 \times 10^{-4}$ improving the current bound by a factor of $\simeq3$. We also set a limit on ${\rm Br}(\eta \to invisible) < 1.1 \times 10^{-4}$ comparable with the existing one. These results demonstrate the great potential of our approach and provide clear guidance on how to enhance and extend the sensitivity for dark sector physics from future searches for invisible neutral meson decays., Comment: 5 pages, 3 figures

Motion in bounded domains is a fundamental concept in various fields, including billiard dynamics and random walks on finite lattices, with important applications in physics, ecology and biology. An important universal property related to the average return time to the boundary, the Mean Path Length Theorem (MPLT), has been proposed theoretically and confirmed experimentally in various contexts. In this discussion, we investigate a wide range of mechanisms that lead to deviations from this universal behavior, such as boundary effects, reorientation and memory processes. In particular, this study investigates the dynamics of run-and-tumble particles within a confined two-dimensional circular domain. Through a combination of theoretical approaches and numerical simulations, we validate the MPLT under uniform and isotropic particle inflow conditions. The research demonstrates that although the MPLT is generally applicable for different step length distributions, deviations occur for non-uniform angular distributions, non-elastic boundary conditions or memory processes. These results underline the crucial influence of boundary interactions and angular dynamics on the behaviour of particles in confined spaces. Our results provide new insights into the geometry and dynamics of motion in confined spaces and contribute to a better understanding of a broad spectrum of phenomena ranging from the motion of bacteria to neutron transport. This type of analysis is crucial in situations where inhomogeneity occurs, such as multiple real-world scenarios within a limited domain. This bridges the gap between theoretical models and practical applications in biological and physical systems since the study of the statistics of movement in confined settings can bring some light in explaining the mobility mechanism of active agents.

This paper introduces TVB C++, a streamlined and fast C++ Back-End for The Virtual Brain (TVB), a renowned platform and a benchmark tool for full-brain simulation. TVB C++ is engineered with speed as a primary focus while retaining the flexibility and ease of use characteristic of the original TVB platform. Positioned as a complementary tool, TVB serves as a prototyping platform, whereas TVB C++ becomes indispensable when performance is paramount, particularly for large-scale simulations and leveraging advanced computation facilities like supercomputers. Developed as a TVB-compatible Back-End, TVB C++ seamlessly integrates with the original TVB implementation, facilitating effortless usage. Users can easily configure TVB C++ to execute the same code as in TVB but with enhanced performance and parallelism capabilities.

In the last three decades it has become clear that cortical regions, interconnected via white-matter fibers, form a modular and hierarchical network. This organization, which has also been seen at the microscopic level in the form of interconnected neural assemblies, is believed to support the coexistence of segregation (specialization) and integration (binding) of information. A fundamental open question is to understand how this complex structure can emerge in the brain. Here, we made a first step to address this question and propose that adaptation to various inputs could be the key driving mechanism for the formation of structural assemblies. To test this idea, we develop a model of quadratic integrate-and-fire spiking neurons, trained to stimuli targetting distinct sub-populations. The model is designed to satisfy several biologically plausible constraints: (i) the network contains excitatory and inhibitory neurons with Hebbian and anti-Hebbian STDP; and (ii) neither the neuronal activity nor the synaptic weights are frozen after the learning phase. Instead, the network continues firing spontaneously while synaptic plasticity remains active. We find that only the combination of the two inhibitory STDP sub-populations allows for the formation of stable modular organization in the network, with each sub-population playing a distinct role. The Hebbian sub-population controls for the firing rate and the anti-Hebbian mediates pattern selectivity. After the learning phase, the network activity settles into an asynchronous irregular resting-state, resembling the behaviour typically observed in-vivo in the cortex. This post-learning activity also displays spontaneous memory recalls, which are fundamental for the long-term consolidation of the learned memory items. The model introduced represents a starting point for the joint investigation of neural dynamics, connectivity and plasticity., Comment: 28 pages, 11 figures

We present the electrostatic control of photoluminescence of monolayer MoS$_2$ at room temperature via integration of free-standing BaTiO$_3$ (BTO), a ferroelectric perovskite oxide, layers. We show that the use of BTO leads to highly tunable exciton emission of MoS$_2$ in a minimal range of gate voltages, effectively controlling the neutral excitons to charged excitons (trions) conversion. Due to BTO's ferroelectric polarization-induced doping we observe large peak emission shifts as well as a large and tunable A trion binding energy in the range of 40-100 meV. To further investigate the efficacy of electrostatic control, we compared our measurements with those carried out when the BTO is replaced by a hexagonal boron nitride (hBN) dielectric layer of comparable thickness, confirming BTO's superior gating properties and thus lower power consumption. Additionally, we take advantage of the ferroelectric switching of BTO by fabricating devices where the BTO layer is decoupled from the gate electrode with a SiO$_2$ layer. Choosing to isolate the BTO allows us to induce large remanent behavior of MoS$_2$'s excitonic features, observing hysteretic behavior in the peak energy ratio between A exciton and its trion, as well as hysteretic behavior in the doping-related trion energy shift. This study illustrates the rich physics involved in combining free-standing complex oxide layers with two-dimensional materials.

We have determined the depth-dose curve, the penetration range, and the water equivalent ratio (WER), for proton beams of clinical energies in cortical bone, by means of a detailed and accurate simulation that combines molecular dynamics and Monte Carlo techniques. The fundamental input quantities (stopping power and energy loss straggling) for the simulation were obtained from a reliable electronic excitation spectrum of the condensed-phase target, which takes into account the organic and mineral phases that form it. Our simulations with these inputs, that are in excellent agreement with the scarce data available for a cortical bone target, deviate from simulations performed using other stopping quantities, such as those provided by the International Commission on Radiation Units and Measurements (ICRU) in its widely used Report 49. The results of this work emphasize the importance of an accurate determination of the stopping quantities of cortical bone in order to advance towards the millimetric precision for the proton penetration ranges and deposited dose needed in radiotherapy., Comment: Accepted version in Physical Review E (see published version in: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.034405), 20 pages, 6 figures

The phenomenon of Anderson localization, occurring in a disordered medium, significantly influences the dynamics of quantum particles. A fascinating manifestation of this is the "quantum boomerang effect" (QBE), observed when a quantum particle, propelled with a finite initial velocity, reverses its average trajectory, eventually halting at its starting point. This effect has recently been demonstrated in an experiment replicating the quantum kicked-rotor model. This research delves into the classical analog of QBE. We uncover evidence of a similar effect in classical systems, characterized by the absence of typical diffusion processes. Our investigation encompasses both simplified probabilistic models and more complex phenomenological models that link classical with quantum mechanics. The results indicate that the boomerang effect is not confined to the quantum realm and may also be present in diverse systems exhibiting subdiffusive behavior., Comment: 6 figures

The Spin Physics Detector collaboration proposes to install a universal detector in the second interaction point of the NICA collider under construction (JINR, Dubna) to study the spin structure of the proton and deuteron and other spin-related phenomena using a unique possibility to operate with polarized proton and deuteron beams at a collision energy up to 27 GeV and a luminosity up to $10^{32}$ cm$^{-2}$ s$^{-1}$. As the main goal, the experiment aims to provide access to the gluon TMD PDFs in the proton and deuteron, as well as the gluon transversity distribution and tensor PDFs in the deuteron, via the measurement of specific single and double spin asymmetries using different complementary probes such as charmonia, open charm, and prompt photon production processes. Other polarized and unpolarized physics is possible, especially at the first stage of NICA operation with reduced luminosity and collision energy of the proton and ion beams. This document is dedicated exclusively to technical issues of the SPD setup construction.

The inclusion of an additional $U(1)$ gauge $L_\mu-L_\tau$ symmetry would release the tension between the measured and the predicted value of the anomalous muon magnetic moment: this paradigm assumes the existence of a new, light $Z^\prime$ vector boson, with dominant coupling to $\mu$ and $\tau$ leptons and interacting with electrons via a loop mechanism. The $L_\mu-L_\tau$ model can also explain the Dark Matter relic abundance, by assuming that the $Z'$ boson acts as a "portal" to a new Dark Sector of particles in Nature, not charged under known interactions. In this work we present the results of the $Z'$ search performed by the NA64-$e$ experiment at CERN SPS, that collected $\sim 9\times10^{11}$ 100 GeV electrons impinging on an active thick target. Despite the suppressed $Z'$ production yield with an electron beam, NA64-$e$ provides the first accelerator-based results excluding the $g-2$ preferred band of the $Z'$ parameter space in the 1 keV $ < m_{Z'} \lesssim 2$ MeV range, in complementarity with the limits recently obtained by the NA64-$\mu$ experiment with a muon beam., Comment: 15 pages, 5 figures. New version with extended exclusion limits down to 1 keV in Z' mass

The spin-orbit splitting between neutron 1$p$ orbitals at $^{33}$Si has been deduced using the single-neutron-adding ($d$,$p$) reaction in inverse kinematics with a beam of $^{32}$Si, a long-lived radioisotope. Reaction products were analyzed by the newly implemented SOLARIS spectrometer at the reaccelerated-beam facility at the National Superconducting Cyclotron Laboratory. The measurements show reasonable agreement with shell-model calculations that incorporate modern cross-shell interactions, but they contradict the prediction of proton density depletion based on relativistic mean-field theory. The evolution of the neutron 1$p$-shell orbitals is systematically studied using the present and existing data in the isotonic chains of $N=17$, 19, and 21. In each case, a smooth decrease in the separation of the $1p_{3/2}$-$1p_{1/2}$ orbitals is seen as the respective $p$-orbitals approach zero binding, suggesting that the finite nuclear potential strongly influences the evolution of nuclear structure in this region., Comment: 10 pages, 5 figures