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Motivation Network visualization is critical for effective communication in various fields of knowledge. Currently, a gap separates network manipulation from network visualization in programming environments. Users often export network data to be laid out in external interactive software, like Cytoscape and Gephi. We argue the current R package ecosystem lacks an interactive layout engine well integrated with common data analysis workflows. Results We present easylayout, an R package that bridges network manipulation and visualization by leveraging interactive force simulations within the IDE itself (e.g., RStudio, VSCode). It is not yet another visualization library, but instead aims to interconnect existing libraries and streamline their usage into the R ecosystem. easylayout takes an igraph object and serializes it into a web application integrated with the IDE's interface through a Shiny server. The app lays out the network by simulating attraction and repulsion forces. Simulation parameters can be adjusted in real-time. An editing mode allows moving and rotating nodes. The implementation aims for performance, so that even lower-end devices are able to work with relatively large networks. Once the user finishes tweaking the layout, it is sent back to the R session to be plotted through popular libraries like ggraph, igraph or even the base package itself. The current implementation focuses on the R ecosystem, but using web technologies makes it easily portable to similar environments, like Python/Jupyter Notebooks. We expect this tool to reduce the time spent searching for suitable network layouts, ultimately allowing researchers to generate more compelling figures. Availability and implementation easylayout is freely available under an MIT license on GitHub (https://github.com/dalmolingroup/easylayout). The package is implemented in R/Shiny and JavaScript/Svelte.

For over 25 years, the DAMA/LIBRA collaboration has claimed to observe an annual modulation signal, suggesting the existence of dark matter interactions. However, no other experiments have replicated their result using different detector materials. To address this puzzle, the COSINE-100 collaboration conducted a model-independent test using 106 kg of sodium iodide as detectors, the same target material as DAMA/LIBRA. Analyzing data collected over 6.4 years, with improved energy calibration and time-dependent background description, we found no evidence of an annual modulation signal, challenging the DAMA/LIBRA result with a confidence level greater than 3$\sigma$. This finding represents a significant step toward resolving the long-standing debate surrounding DAMA/LIBRA's dark matter claim, indicating that the observed modulation is unlikely to be caused by dark matter interactions.

This paper investigates the behavior of fermions in the vicinity of Sung-Won-Kim wormholes \cite{SW Kim PRD 1996} within the framework of a generalized Kaluza-Klein gravity. The study explores the geometric and quantum implications of introducing an extra dimension into the Sung-Won-Kim wormhole model. The impact of this additional dimension on the stability and traversability of the wormholes, as well as on the fermionic equations of motion, is analyzed. By examining the modified Dirac equation in this extended framework, the emergence of geometric phases and quantum holonomies is discussed, providing insights into the topological aspects of fermion dynamics in curved spacetimes.

In this paper, we discuss an extension of the geometric description of graphene wormholes in a non-inertial situation. We present an effective metric that describes the wormhole connection between two graphene sheets with matter content in rotation. Additionally, a stretching term as a function of the classical redshift of space has been found and discussed. We also explore the influence of a rotation term on quantum holonomy, recovering previous results found for the static case.

In this paper, a discussion about quantum holonomies around a possible bridge between two graphene sheets has been made. That bridge is widely known as a graphene wormhole, and some of its characteristics are also showed up here. As well as their build as a zigzag junction between a baggy nanotube and the graphene lattices. And how the localized electronic states could be mimicked by gauge fields in a low-energy regime. Further, the possibility to build holonomies handle by an effective flux from topological defects in junctions of that bridge has been discussed.

DarkSide-20k (DS-20k) is a dark matter detection experiment under construction at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It utilises ~100 t of low radioactivity argon from an underground source (UAr) in its inner detector, with half serving as target in a dual-phase time projection chamber (TPC). The UAr cryogenics system must maintain stable thermodynamic conditions throughout the experiment's lifetime of >10 years. Continuous removal of impurities and radon from the UAr is essential for maximising signal yield and mitigating background. We are developing an efficient and powerful cryogenics system with a gas purification loop with a target circulation rate of 1000 slpm. Central to its design is a condenser operated with liquid nitrogen which is paired with a gas heat exchanger cascade, delivering a combined cooling power of >8 kW. Here we present the design choices in view of the DS-20k requirements, in particular the condenser's working principle and the cooling control, and we show test results obtained with a dedicated benchmarking platform at CERN and LNGS. We find that the thermal efficiency of the recirculation loop, defined in terms of nitrogen consumption per argon flow rate, is 95 % and the pressure in the test cryostat can be maintained within $\pm$(0.1-0.2) mbar. We further detail a 5-day cool-down procedure of the test cryostat, maintaining a cooling rate typically within -2 K/h, as required for the DS-20k inner detector. Additionally, we assess the circuit's flow resistance, and the heat transfer capabilities of two heat exchanger geometries for argon phase change, used to provide gas for recirculation. We conclude by discussing how our findings influence the finalisation of the system design, including necessary modifications to meet requirements and ongoing testing activities., Comment: 45 pages, 24 figures

COSINE-100 is a direct dark matter search experiment, with the primary goal of testing the annual modulation signal observed by DAMA/LIBRA, using the same target material, NaI(Tl). In previous analyses, we achieved the same 1 keV energy threshold used in the DAMA/LIBRA's analysis that reported an annual modulation signal with 11.6$\sigma$ significance. In this article, we report an improved analysis that lowered the threshold to 0.7 keV, thanks to the application of Multi-Layer Perception network and a new likelihood parameter with waveforms in the frequency domain. The lower threshold would enable a better comparison of COSINE-100 with new DAMA results with a 0.75 keV threshold and account for differences in quenching factors. Furthermore the lower threshold can enhance COSINE-100's sensitivity to sub-GeV dark matter searches.

We study quasinormal modes of massive scalar perturbations in Kerr black holes using the isomonodromic method. For arbitrary scalar masses $M \mu$ and black hole spins $a/M$, we numerically determine the quasinormal frequencies for various orbital $\ell$, azimuthal $m$, and overtone $n$ numbers. In particular, we derive an analytic expression for frequencies of the zero-damping modes near the extremal limit $a/M \rightarrow 1$. For $\ell=m=1$, we reveal that the fundamental mode becomes a damped mode (rather than a zero-damping mode) if the scalar field is sufficiently heavy. By exploring the parameter space, we find numerical evidence for level-crossing between the longest-living mode and the first overtone at an exceptional point $(M\mu)_c \simeq 0.3704981$ and $(a/M)_c\simeq 0.9994660$., Comment: 20 pages, 13 graphics, 2 figures, 2 tables

We propose a method for predicting the location of user equipment (UE) using wireless fingerprints in dynamic indoor non-line-of-sight (NLoS) environments. In particular, our method copes with the challenges posed by the drift, birth, and death of scattering clusters resulting from dynamic changes in the wireless environment. Prominent examples of such dynamic wireless environments include factory floors or offices, where the geometry of the environment undergoes changes over time. These changes affect the distribution of wireless fingerprints, demonstrating some similarity between the distributions before and after the change. Consequently, the performance of a location estimator initially designed for a specific environment may degrade significantly when applied after changes have occurred in that environment. To address this limitation, we propose a domain adaptation framework that utilizes neural networks to align the distributions of wireless fingerprints collected both before and after environmental changes. By aligning these distributions, we design an estimator capable of predicting UE locations from their wireless fingerprints in the new environment. Experiments validate the effectiveness of the proposed methods in localizing UEs in dynamic wireless environments.

COSINE-100 aims to conclusively test the claimed dark matter annual modulation signal detected by DAMA/LIBRA collaboration. DAMA/LIBRA has released updated analysis results by lowering the energy threshold to 0.75 keV through various upgrades. They have consistently claimed to have observed the annual modulation. In COSINE-100, it is crucial to lower the energy threshold for a direct comparison with DAMA/LIBRA, which also enhances the sensitivity of the search for low-mass dark matter, enabling COSINE-100 to explore this area. Therefore, it is essential to have a precise and quantitative understanding of the background spectrum across all energy ranges. This study expands the background modeling from 0.7 to 4000 keV using 2.82 years of COSINE-100 data. The modeling has been improved to describe the background spectrum across all energy ranges accurately. Assessments of the background spectrum are presented, considering the nonproportionality of NaI(Tl) crystals at both low and high energies and the characteristic X-rays produced by the interaction of external backgrounds with materials such as copper. Additionally, constraints on the fit parameters obtained from the alpha spectrum modeling fit are integrated into this model. These improvements are detailed in the paper.

In recent years, deep learning techniques have been used to develop sign language recognition systems, potentially serving as a communication tool for millions of hearing-impaired individuals worldwide. However, there are inherent challenges in creating such systems. Firstly, it is important to consider as many linguistic parameters as possible in gesture execution to avoid ambiguity between words. Moreover, to facilitate the real-world adoption of the created solution, it is essential to ensure that the chosen technology is realistic, avoiding expensive, intrusive, or low-mobility sensors, as well as very complex deep learning architectures that impose high computational requirements. Based on this, our work aims to propose an efficient sign language recognition system that utilizes low-cost sensors and techniques. To this end, an object detection model was trained specifically for detecting the interpreter's face and hands, ensuring focus on the most relevant regions of the image and generating inputs with higher semantic value for the classifier. Additionally, we introduced a novel approach to obtain features representing hand location and movement by leveraging spatial information derived from centroid positions of bounding boxes, thereby enhancing sign discrimination. The results demonstrate the efficiency of our handcrafted features, increasing accuracy by 7.96% on the AUTSL dataset, while adding fewer than 700 thousand parameters and incurring less than 10 milliseconds of additional inference time. These findings highlight the potential of our technique to strike a favorable balance between computational cost and accuracy, making it a promising approach for practical sign language recognition applications., Comment: 28 pages, 12 figures, submitted to Image and Vision Computing Journal

We employ the isomonodromic method to study linear scalar massive perturbations of Kerr black holes for generic scalar masses $M\mu$ and generic black hole spins $a/M$. A degeneracy between the longest-living quasinormal mode and the first overtone is found for $(M\mu)_c \simeq 0.3704981$ and $(a/M)_c\simeq 0.9994660$. We show that the longest-living mode and the first overtone change continuously into each other as we vary the parameters around the point of degeneracy, providing evidence for the existence of a geometric phase around an exceptional point. We interpret our findings through a thermodynamic analogy., Comment: v2: 8 pages, 4 figures. Typos corrected and references added

The dual-phase liquid argon time projection chamber is presently one of the leading technologies to search for dark matter particles with masses below 10 GeV/c$^2$. This was demonstrated by the DarkSide-50 experiment with approximately 50 kg of low-radioactivity liquid argon as target material. The next generation experiment DarkSide-20k, currently under construction, will use 1,000 times more argon and is expected to start operation in 2027. Based on the DarkSide-50 experience, here we assess the DarkSide-20k sensitivity to models predicting light dark matter particles, including Weakly Interacting Massive Particles (WIMPs) and sub-GeV/c$^2$ particles interacting with electrons in argon atoms. With one year of data, a sensitivity improvement to dark matter interaction cross-sections by at least one order of magnitude with respect to DarkSide-50 is expected for all these models. A sensitivity to WIMP--nucleon interaction cross-sections below $1\times10^{-42}$ cm$^2$ is achievable for WIMP masses above 800 MeV/c$^2$. With 10 years exposure, the neutrino fog can be reached for WIMP masses around 5 GeV/c$^2$., Comment: submitted to Nature Communications

Multi-core vector processor architectures excel in handling computationally intensive vectorizable tasks but struggle to achieve optimal resource utilization when facing sequential and control tasks that cannot be vectorized. This work presents Spatzformer, the first reconfigurable RISC-V V (RVV) architecture developed from a baseline open-source dual-core cluster based on Snitch scalar cores augmented with compact Spatz vector units. Spatzformer operates in two distinct modes: split mode, working as a dual-core vector architecture to handle vectorizable tasks concurrently, and merge mode, where two vector units are driven by a single scalar core, allowing the remaining scalar core to handle non-vectorizable control tasks. We implement Spatzformer in a 12-nm technology node and characterize the cost of the added architectural reconfigurability. We show that merge mode accelerates mixed scalar-vector kernels by up to 1.8x compared to split mode. Moreover, it accelerates the vector kernels that require fine-grained synchronization (such as FFT) by up to 20% with respect to the baseline. The reconfigurability features do not degrade the architecture's maximum frequency (1.2GHz, TT, 0.8V, 25C) and have a negligible area impact (+1.4%), with a worst-case energy efficiency drop of only 7% with respect to the non-reconfigurable baseline., Comment: To be published in the 2024 IEEE 35th International Conference on Application Specific Systems (ASAP), Architectures and Processors

We present Occamy, a 432-core RISC-V dual-chiplet 2.5D system for efficient sparse linear algebra and stencil computations on FP64 and narrow (32-, 16-, 8-bit) SIMD FP data. Occamy features 48 clusters of RISC-V cores with custom extensions, two 64-bit host cores, and a latency-tolerant multi-chiplet interconnect and memory system with 32 GiB of HBM2E. It achieves leading-edge utilization on stencils (83 %), sparse-dense (42 %), and sparse-sparse (49 %) matrix multiply., Comment: 2 pages, 7 figures. Accepted at the 2024 IEEE Symposium on VLSI Technology & Circuits

In this paper, we compute the second variation of the first Dirichlet eigenvalue on extremal domains in general Riemannian manifolds and establish a criterion for stability. We classify the stable extremal domains in the 2-sphere and higher-dimensional spheres when the boundary is minimal. Additionally, we establish topological bounds for stable domains in a general compact Riemannian surface, assuming either nonnegative total Gaussian curvature or small volume., Comment: This new version includes a new theorem (Theorem 1.3) and additional references. 23 pages. Comments and feedback are welcome!

Let $\Sigma$ denote a closed surface with constant mean curvature in $\mathbb{G}^3$, a 3-dimensional Lie group equipped with a bi-invariant metric. For such surfaces, there is a harmonic Gauss map which maps values to the unit sphere within the Lie algebra of $\mathbb{G}$. We prove that the energy index of the Gauss map of $\Sigma$ is bounded below by its topological genus. We also obtain index estimates in the case of complete non compact surfaces., Comment: 11 pages

In this paper, we obtain geometric upper bounds for the first eigenvalue $\lambda_1^J$ of the Jacobi operator for both closed and compact with boundary hypersurfaces having constant mean curvature (CMC). As an application, we derive new rigidity results for the area of CMC hypersurfaces under suitable conditions on $\lambda_1^J$ and the curvature of the ambient space. We also address the Jacobi-Steklov problem, proving geometric upper bounds for its first eigenvalue $\sigma_1^J$ and deriving rigidity results related to the length of the boundary. Additionally, we present some results in higher dimensions related to the Yamabe invariants., Comment: 17 pages. Comments welcome!

Radio Access Networks (RAN) workloads are rapidly scaling up in data processing intensity and throughput as the 5G (and beyond) standards grow in number of antennas and sub-carriers. Offering flexible Processing Elements (PEs), efficient memory access, and a productive parallel programming model, many-core clusters are a well-matched architecture for next-generation software-defined RANs, but staggering performance requirements demand a high number of PEs coupled with extreme Power, Performance and Area (PPA) efficiency. We present the architecture, design, and full physical implementation of Terapool-SDR, a cluster for Software Defined Radio (SDR) with 1024 latency-tolerant, compact RV32 PEs, sharing a global view of a 4MiB, 4096-banked, L1 memory. We report various feasible configurations of TeraPool-SDR featuring an ultra-high bandwidth PE-to-L1-memory interconnect, clocked at 730MHz, 880MHz, and 924MHz (TT/0.80 V/25 {\deg}C) in 12nm FinFET technology. The TeraPool-SDR cluster achieves high energy efficiency on all SDR key kernels for 5G RANs: Fast Fourier Transform (93GOPS/W), Matrix-Multiplication (125GOPS/W), Channel Estimation (96GOPS/W), and Linear System Inversion (61GOPS/W). For all the kernels, it consumes less than 10W, in compliance with industry standards., Comment: 6 pages, 6 figures and 3 tables

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.

We consider the optimal control of switching on a coupling term between two quantum many-body systems. Specifically, we (i) quantify the energetic cost of establishing a weak junction between two quantum spin-$1/2$ chains in finite time $\tau$ and (ii) identify the energetically optimal protocol to realize it. For linear driving protocols, we find that for long times the excess (irreversible) work scales as $\tau^{-\eta}$, where $\eta=1, 2$ or a nonuniversal number depending on the phase of the chains. Interestingly, increasing a $J_z$ anisotropy in the chains suppresses the excess work thus promoting quasi-adiabaticity. The general optimal control problem is solved, employing a Chebyshev ansatz. We find that the optimal control protocol is intimately sensitive to the chain phases., Comment: 13 pages, 6 figures

In this paper, we formalize an optimization framework for analog beamforming in the context of monostatic integrated sensing and communication (ISAC), where we also address the problem of self-interference in the analog domain. As a result, we derive semidefinite programs to approach detection-optimal transmit and receive beamformers, and we devise a superiorized iterative projection algorithm to approximate them. Our simulations show that this approach outperforms the detection performance of well-known design techniques for ISAC beamforming, while it achieves satisfactory self-interference suppression., Comment: 7 pages, 4 figures. Published at IEEE International Conference on Communications (ICC) 2024. IEEE Copyright protected

The stellar rotation has an essential role in modifying the structure of the star and, therefore, the way these different interplays arise. On the other hand, changes in orbits impact the star's rotation and its evolution. The evolution of the star's rotation accounts for the angular momentum exchange with the planet and follows the effects of the internal transport of angular momentum and metallicity. Several models in the literature have aimed to find a theoretical way to study these interactions between the planet's orbital evolution and the star's rotation. Our work is a promising attempt to investigate these interactions from a model based on a new statistical approach. To this end, we propose a ``tidal interaction index'' that carries all the parameters of the star-planet system that can affect the transport of angular momentum and, consequently, the evolution of stellar rotation. This index is similar to the ``magnetic braking index'' whose most successful value equals 3, which expresses the seminal Skumunich law. Our model is computed for masses of the host star less than the Kraft limit for three orbital-rotation period regimes and the semi-major axis less than 1 AU. We consider planets with masses between 0.4M$_{\oplus}$ and 20M$_{\rm J}$ with orbital periods between 0.3 and 225 days. We show that the tidal index $q$ segregated by stellar mass without wind magnetic braking during the main-sequence phase is strongly anti-correlated with planetary mass. Finally, we conclude that in cases where planets retain less than 84\% of the total angular momentum within the system, the magnetic braking mechanism proves to be more effective than tidal interactions, irrespective of whether the planets' angular momentum surpasses that of the host star., Comment: 21 pages, 2 tables, submitted to Icarus

Modern systems are increasingly connected and more integrated with other existing systems, giving rise to \textit{systems-of-systems} (SoS). An SoS consists of a set of independent, heterogeneous systems that interact to provide new functionalities and accomplish global missions through emergent behavior manifested at runtime. The distinctive characteristics of SoS, when contrasted to traditional systems, pose significant research challenges within Software Engineering. These challenges motivate the need for a paradigm shift and the exploration of novel approaches for designing, developing, deploying, and evolving these systems. The \textit{International Workshop on Software Engineering for Systems-of-Systems} (SESoS) series started in 2013 to fill a gap in scientific forums addressing SoS from the Software Engineering perspective, becoming the first venue for this purpose. This article presents a study aimed at outlining the evolution and future trajectory of Software Engineering for SoS based on the examination of 57 papers spanning the 11 editions of the SESoS workshop (2013-2023). The study combined scoping review and scientometric analysis methods to categorize and analyze the research contributions concerning temporal and geographic distribution, topics of interest, research methodologies employed, application domains, and research impact. Based on such a comprehensive overview, this article discusses current and future directions in Software Engineering for SoS., Comment: Submitted (under evaluation) to the Journal of Software: Evolution and Process

Cosmic ray muons prove valuable across various fields, from particle physics experiments to non-invasive tomography, thanks to their high flux and exceptional penetrating capability. Utilizing a scintillator detector, one can effectively study the topography of mountains situated above tunnels and underground spaces. The Hankuk Atmospheric-muon Wide Landscaping (HAWL) project successfully charts the mountainous region of eastern Korea by measuring cosmic ray muons with a detector in motion. The real-time muon flux measurement shows a tunnel length accuracy of 6.0 %, with a detectable overburden range spanning from 8 to 400 meter-water-equivalent depth. This is the first real-time portable muon tomography., Comment: 10pages, 12 figures