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Dense linear layers are the dominant computational bottleneck in large neural networks, presenting a critical need for more efficient alternatives. Previous efforts focused on a small number of hand-crafted structured matrices and neglected to investigate whether these structures can surpass dense layers in terms of compute-optimal scaling laws when both the model size and training examples are optimally allocated. In this work, we present a unifying framework that enables searching among all linear operators expressible via an Einstein summation. This framework encompasses many previously proposed structures, such as low-rank, Kronecker, Tensor-Train, Block Tensor-Train (BTT), and Monarch, along with many novel structures. To analyze the framework, we develop a taxonomy of all such operators based on their computational and algebraic properties and show that differences in the compute-optimal scaling laws are mostly governed by a small number of variables that we introduce. Namely, a small $\omega$ (which measures parameter sharing) and large $\psi$ (which measures the rank) reliably led to better scaling laws. Guided by the insight that full-rank structures that maximize parameters per unit of compute perform the best, we propose BTT-MoE, a novel Mixture-of-Experts (MoE) architecture obtained by sparsifying computation in the BTT structure. In contrast to the standard sparse MoE for each entire feed-forward network, BTT-MoE learns an MoE in every single linear layer of the model, including the projection matrices in the attention blocks. We find BTT-MoE provides a substantial compute-efficiency gain over dense layers and standard MoE., Comment: NeurIPS 2024. Code available at https://github.com/AndPotap/einsum-search

This study presents the design, simulation, and experimental characterization of a superconducting transmon qubit circuit prototype for potential applications in dark matter detection experiments. We describe a planar circuit design featuring two non-interacting transmon qubits, one with fixed frequency and the other flux tunable. Finite-element simulations were employed to extract key Hamiltonian parameters and optimize component geometries. The qubit was fabricated and then characterized at $20$ mK, allowing for a comparison between simulated and measured qubit parameters. Good agreement was found for transition frequencies and anharmonicities (within 1\% and 10\% respectively) while coupling strengths exhibited larger discrepancies (30\%). We discuss potential causes for measured coherence times falling below expectations ($T_1\sim\,$1-2 \textmu s) and propose strategies for future design improvements. Notably, we demonstrate the application of a hybrid 3D-2D simulation approach for energy participation ratio evaluation, yielding a more accurate estimation of dielectric losses. This work represents an important first step in developing planar Quantum Non-Demolition (QND) single-photon counters for dark matter searches, particularly for axion and dark photon detection schemes.

Stereoelectroencephalography (SEEG) is an invasive surgical procedure to record the electrical activities in cortical brain regions, aiming at identifying the Epileptogenic Zone (EZ) in patients with drug-resistant epilepsy. To improve the accuracy of the EZ definition, SEEG analysis can be supported by computational tools, among which the Epileptogenic Index (EI) represents the most common solution. However, the scientific community has still not found an agreement on which quantitative biomarkers can characterize the cortical sites within the EZ. In this work, we design a new algorithm, named Desynchronization Index (DI), to assist neurophysiologists in SEEG interpretation. Our algorithm estimates the effective connectivity between cortical sites and hypothesizes that the EZ is identified by those sites getting abnormally desynchronized from the network during the seizure generation. We test the proposed method over a SEEG dataset of 10 seizures, comparing its accuracy in terms of EZ definition against the EI algorithm and clinical ground truth. Our results indicate that the DI algorithm underscores specific connectivity dynamics that can hardly be identified with a pure visual analysis, increasing sensitivity in detecting epileptogenic cortical sites.

Haldane's seminal work established two fundamentally different types of excitation spectra for antiferromagnetic Heisenberg quantum spin chains: gapped excitations in integer-spin chains and gapless excitations in half-integer-spin chains. In finite-length half-integer spin chains, quantization, however, induces a gap in the excitation spectrum, with the upper bound given by the Lieb-Schulz-Mattis (LSM) theorem. Here, we investigate the length-dependent excitations in spin-1/2 Heisenberg chains obtained by covalently linking olympicenes--Olympic rings shaped nanographenes carrying spin-1/2--into one-dimensional chains. The large exchange interaction (J~38 mV) between olympicenes and the negligible magnetic anisotropy in these nanographenes make them an ideal platform for studying quantum spin excitations, which we directly measure using inelastic electron tunneling spectroscopy. We observe a power-law decay of the lowest excitation energy with increasing chain length L, remaining below the LSM boundary. In a long chain with L = 50, a nearly V-shaped excitation continuum is observed, reinforcing the system's gapless nature in the thermodynamic limit. Finally, we visualize the standing wave of a single spinon confined in odd-numbered chains using low-bias current maps. Our results provide compelling evidence for the realization of a one-dimensional analog of a gapless spin liquid., Comment: 5 figures. arXiv admin note: text overlap with arXiv:2402.13590

We present a fully explicit dynamic formulation for geometrically exact shear-deformable beams. The starting point of this work is an existing isogeometric collocation (IGA-C) formulation which is explicit in the strict sense of the time integration algorithm, but still requires a system matrix inversion due to the use of a consistent mass matrix. Moreover, in that work, the efficiency was also limited by an iterative solution scheme needed due to the presence of a nonlinear term in the time-discretized rotational balance equation. In the present paper, we address these limitations and propose a novel fully explicit formulation able to preserve high-order accuracy in space. This is done by extending a predictor--multicorrector approach, originally proposed for standard elastodynamics, to the case of the rotational dynamics of geometrically exact beams. The procedure relies on decoupling the Neumann boundary conditions and on a rearrangement and rescaling of the mass matrix. We demonstrate that an additional gain in terms of computational cost is obtained by properly removing the angular velocity-dependent nonlinear term in the rotational balance equation without any significant loss in terms of accuracy. The high-order spatial accuracy and the improved efficiency of the proposed formulation compared to the existing one are demonstrated through some numerical experiments covering different combinations of boundary conditions.

This work aims to develop explainable models to predict the interactions between bitter molecules and TAS2Rs via traditional machine-learning and deep-learning methods starting from experimentally validated data. Bitterness is one of the five basic taste modalities that can be perceived by humans and other mammals. It is mediated by a family of G protein-coupled receptors (GPCRs), namely taste receptor type 2 (TAS2R) or bitter taste receptors. Furthermore, TAS2Rs participate in numerous functions beyond the gustatory system and have implications for various diseases due to their expression in various extra-oral tissues. For this reason, predicting the specific ligand-TAS2Rs interactions can be useful not only in the field of taste perception but also in the broader context of drug design. Considering that in-vitro screening of potential TAS2R ligands is expensive and time-consuming, machine learning (ML) and deep learning (DL) emerged as powerful tools to assist in the selection of ligands and targets for experimental studies and enhance our understanding of bitter receptor roles. In this context, ML and DL models developed in this work are both characterized by high performance and easy applicability. Furthermore, they can be synergistically integrated to enhance model explainability and facilitate the interpretation of results. Hence, the presented models promote a comprehensive understanding of the molecular characteristics of bitter compounds and the design of novel bitterants tailored to target specific TAS2Rs of interest.

The Cryogenic Underground Observatory for Rare Events (CUORE) is a detector array comprised by 988 5$\;$cm$\times$5$\;$cm$\times$5$\;$cm TeO$_2$ crystals held below 20 mK, primarily searching for neutrinoless double-beta decay in $^{130}$Te. Unprecedented in size amongst cryogenic calorimetric experiments, CUORE provides a promising setting for the study of exotic through-going particles. Using the first tonne-year of CUORE's exposure, we perform a search for hypothesized fractionally charged particles (FCPs), which are well-motivated by various Standard Model extensions and would have suppressed interactions with matter. No excess of FCP candidate tracks is observed over background, setting leading limits on the underground FCP flux with charges between $e/24-e/5$ at 90\% confidence level. Using the low background environment and segmented geometry of CUORE, we establish the sensitivity of tonne-scale sub-Kelvin detectors to diverse signatures of new physics., Comment: 7 pages, 5 figures

It is proven that a matched pair of actions on a Hopf algebra $H$ is equivalent to the datum of a Yetter-Drinfeld brace, which is a novel structure generalising Hopf braces. This improves a theorem by Angiono, Galindo and Vendramin, originally stated for cocommutative Hopf braces. These Yetter-Drinfeld braces produce Hopf algebras in the category of Yetter-Drinfeld modules over $H$, through an operation that generalises Majid's transmutation. A characterisation of Yetter-Drinfeld braces via 1-cocycles, in analogy to the one for Hopf braces, is given. Every coquasitriangular Hopf algebra $H$ will be seen to yield a Yetter-Drinfeld brace, where the additional structure on $H$ is given by the transmutation. We compute explicit examples of Yetter-Drinfeld braces on the Sweedler's Hopf algebra, on the algebras $E(n)$, on $\mathrm{SL}_{q}(2)$, and an example in the class of Suzuki algebras., Comment: 29 pages

The theory of Group Equivariant Non-Expansive Operators (GENEOs) was initially developed in Topological Data Analysis for the geometric approximation of data observers, including their invariances and symmetries. This paper departs from that line of research and explores the use of GENEOs for distinguishing $r$-regular graphs up to isomorphisms. In doing so, we aim to test the capabilities and flexibility of these operators. Our experiments show that GENEOs offer a good compromise between efficiency and computational cost in comparing $r$-regular graphs, while their actions on data are easily interpretable. This supports the idea that GENEOs could be a general-purpose approach to discriminative problems in Machine Learning when some structural information about data and observers is explicitly given.

We report on the development of thermal detectors based on large-size tellurium dioxide crystals (45x45x45 mm), containing tellurium enriched in $^{130}$Te to about 91%, for the CROSS double-beta decay experiment. A powder used for the crystals growth was additionally purified by the directional solidification method, resulting in the reduction of the concentration of impurities by a factor 10, to a few ppm of the total concentration of residual elements (the main impurity is Fe). The purest part of the ingot (the first ~200 mm, about 80% of the total length of the cylindrical part of the ingot) was determined by scanning segregation profiles of impurities and used for the $^{130}$TeO$_2$ powder production with no evidence of re-contamination. The crystal growth was verified with precursors produced from powder with natural Te isotopic composition, and two small-size (20x20x10 mm) samples were tested at a sea-level laboratory showing high bolometric and spectrometric performance together with acceptable $^{210}$Po content (below 10 mBq/kg). This growth method was then applied for the production of six large cubic $^{130}$TeO$_2$ crystals and 4 of them were taken randomly to be characterized at the Canfranc underground laboratory, in the CROSS-dedicated low-background cryogenic facility. Two $^{130}$TeO$_2$ samples were coated with a thin, $O$(100 nm), metal film in form of Al layer (on 4 sides) or AlPd grid (on a single side) to investigate the possibility to tag surface events by pulse-shape discrimination. Similarly to the small natural precursors, large-volume $^{130}$TeO$_2$ bolometers show high performance and even better internal purity ($^{210}$Po activity $\sim$ 1 mBq/kg, while activities of $^{228}$Th and $^{226}$Ra are below 0.01 mBq/kg), satisfying requirements for the CROSS and, potentially, next-generation experiments., Comment: Submitted to JINST; 22 pages, 11 figures, 4 tables

The CROSS experiment will search for neutrinoless double-beta decay using a specific mechanical structure to hold thermal detectors. The design of the structure was tuned to minimize the background contribution, keeping an optimal detector performance. A single module of the structure holds two scintillating bolometers (with a crystal size of 45x45x45 mm and a Ge slab facing the crystal's upper side) in the Cu frame, allowing for a modular construction of a large-scale array. Two designs are released: the initial $Thick$ version contains around 15% of Cu over the crystal mass (lithium molybdate, LMO), while this ratio is reduced to ~6% in a finer ($Slim$) design. Both designs were tested extensively at aboveground (IJCLab, France) and underground (LSC, Spain) laboratories. In particular, at LSC we used a pulse-tube-based CROSS facility to operate a 6-crystal array of LMOs enriched/depleted in $^{100}$Mo. The tested LMOs show high spectrometric performance in both designs; notably, the measured energy resolution is 5--7 keV FWHM at 2615 keV $\gamma$s, nearby the Q-value of $^{100}$Mo (3034 keV). Due to the absence of a reflective cavity around LMOs, a low scintillation signal is detected by Ge bolometers: ~0.3 keV (150 photons) for 1-MeV $\gamma$($\beta$) LMO-event. Despite that, an acceptable separation between $\alpha$ and $\gamma$($\beta$) events is achieved with most devices. The highest efficiency is reached with light detectors in the $Thick$ design thanks to a lower baseline noise width (0.05--0.09 keV RMS) when compared to that obtained in the $Slim$ version (0.10--0.35 keV RMS). Given the pivotal role of bolometric photodetectors for particle identification and random coincidences rejection, we will use the structure here described with upgraded light detectors, featuring thermal signal amplification via the Neganov-Trofimov-Luke effect, as also demonstrated in the present work., Comment: Submitted to JINST; 31 pages, 16 figures, 5 tables

The entry of new technological infrastructures into the financial markets poses serious concerns about the misuse of the economic system for illicit purposes, such as money laundering and financing of terrorism. Although there are cases in which this connection has already been discovered by malicious actors, distributed ledger technologies can nevertheless represent a powerful tool at the disposal of competent authorities to trace illicit flows and to better monitor risks in financial markets. However, this possibility may go through an interdisciplinary analysis of the phenomena. The search for alternative systems to move funds, rather than the traditional financial intermediaries, such as banks, is not a new circumstance and not necessarily for criminal purposes. Nevertheless, some of the already-known value transfer systems may benefit from the use of distributed ledger technology and make their detection more difficult. The European institutions are discussing the needed legislative packages to enforce the current regulations and to extend their application to the crypto space, as well as the establishment of a new competent authority.

We present the model we developed to reconstruct the CUORE radioactive background based on the analysis of an experimental exposure of 1038.4 kg yr. The data reconstruction relies on a simultaneous Bayesian fit applied to energy spectra over a broad energy range. The high granularity of the CUORE detector, together with the large exposure and extended stable operations, allow for an in-depth exploration of both spatial and time dependence of backgrounds. We achieve high sensitivity to both bulk and surface activities of the materials of the setup, detecting levels as low as 10 nBq kg$^{-1}$ and 0.1 nBq cm$^{-2}$, respectively. We compare the contamination levels we extract from the background model with prior radio-assay data, which informs future background risk mitigation strategies. The results of this background model play a crucial role in constructing the background budget for the CUPID experiment as it will exploit the same CUORE infrastructure.

The current experiments searching for neutrinoless double-$\beta$ ($0\nu\beta\beta$) decay also collect large statistics of Standard Model allowed two-neutrino double-$\beta$ ($2\nu\beta\beta$) decay events. These can be used to search for Beyond Standard Model (BSM) physics via $2\nu\beta\beta$ decay spectral distortions. $^{100}$Mo has a natural advantage due to its relatively short half-life, allowing higher $2\nu\beta\beta$ decay statistics at equal exposures compared to the other isotopes. We demonstrate the potential of the dual read-out bolometric technique exploiting a $^{100}$Mo exposure of 1.47 kg $\times$ y, acquired in the CUPID-Mo experiment at the Modane underground laboratory (France). We set limits on $0\nu\beta\beta$ decays with the emission of one or more Majorons, on $2\nu\beta\beta$ decay with Lorentz violation, and $2\nu\beta\beta$ decay with a sterile neutrino emission. In this analysis, we investigate the systematic uncertainty induced by modeling the $2\nu\beta\beta$ decay spectral shape parameterized through an improved model, an effect never considered before. This work motivates searches for BSM processes in the upcoming CUPID experiment, which will collect the largest amount of $2\nu\beta\beta$ decay events among the next-generation experiments.

The matter-antimatter asymmetry underlines the incompleteness of the current understanding of particle physics. Neutrinoless double-beta ($0\nu \beta\beta$) decay may help explain this asymmetry, while unveiling the Majorana nature of the neutrino. The CUORE experiment searches for $0\nu \beta\beta$ decay of $^{130}$Te using a tonne-scale cryogenic calorimeter operated at milli-kelvin temperatures. We report no evidence for $0\nu \beta\beta$ decay and place a lower limit on the half-life of T$_{1/2}$ $>$ 3.8 $\times$ 10$^{25}$ years (90% C.I.) with over 2 tonne$\cdot$year TeO$_2$ exposure. The tools and techniques developed for this result and the 5 year stable operation of nearly 1000 detectors demonstrate the infrastructure for a next-generation experiment capable of searching for $0\nu \beta\beta$ decay across multiple isotopes.

A common way of learning to perform a task is to observe how it is carried out by experts. However, it is well known that for most tasks there is no unique way to perform them. This is especially noticeable the more complex the task is because factors such as the skill or the know-how of the expert may well affect the way she solves the task. In addition, learning from experts also suffers of having a small set of training examples generally coming from several experts (since experts are usually a limited and expensive resource), being all of them positive examples (i.e. examples that represent successful executions of the task). Traditional machine learning techniques are not useful in such scenarios, as they require extensive training data. Starting from very few executions of the task presented as activity sequences, we introduce a novel inductive approach for learning multiple models, with each one representing an alternative strategy of performing a task. By an iterative process based on generalisation and specialisation, we learn the underlying patterns that capture the different styles of performing a task exhibited by the examples. We illustrate our approach on two common activity recognition tasks: a surgical skills training task and a cooking domain. We evaluate the inferred models with respect to two metrics that measure how well the models represent the examples and capture the different forms of executing a task showed by the examples. We compare our results with the traditional process mining approach and show that a small set of meaningful examples is enough to obtain patterns that capture the different strategies that are followed to solve the tasks., Comment: 32 pages, Github repository, published paper, authors' version

The analysis of glioblastoma (GB) cell locomotion and its modeling inspired by Levy random walks is presented herein. We study such walks occurring on a two-dimensional plane where the walk is similar to the motion of a bird flying with a constant velocity, but with random changes of direction in time. The intelligence of the bird is signaled by the instantaneous changes of flying direction, which become invisible in the time series obtained by projecting the 2D walk either on the x axis or the y axis. We establish that the projected 1D time series share the statistical complexity of time series frequently used to monitor physiological processes, shedding light on the role of crucial events (CE-s) in pathophysiology. Such CE-s are signified by abrupt changes of flying direction which are invisible in the 1D physiological time series. We establish a connection between the complex scaling index \delta generated by the CE-s through \mu_{R} = 2 - \delta , where \mu_{R} is the inverse power law index of the probability density function of the time interval between consecutive failures of the process of interest. We argue that the identification of empirical indices along with their theoretical relations afford important measures to control cancer., Comment: 30 pages, 44 references, 13 figures

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)

We prove a conjecture of Guarnieri and Vendramin on the number of braces of a given order whose multiplicative group is a generalised quaternion group. At the same time, we give a similar result where the multiplicative group is dihedral. We also enumerate Hopf-Galois structures of abelian type on Galois extensions with generalised quaternion or dihedral Galois group., Comment: 25 pages. Additional references included

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.

BINGO is a project aiming to set the grounds for large-scale bolometric neutrinoless double-beta-decay experiments capable of investigating the effective Majorana neutrino mass at a few meV level. It focuses on developing innovative technologies (a detector assembly, cryogenic photodetectors and active veto) to achieve a very low background index, of the order of $10^{-5}$ counts/(keV kg yr) in the region of interest. The BINGO demonstrator, called MINI-BINGO, is designed to investigate the promising double-beta-decay isotopes $^{100}$Mo and $^{130}$Te and it will be composed of Li$_2$MoO$_4$ and TeO$_2$ crystals coupled to bolometric light detectors and surrounded by a Bi$_4$Ge$_3$O$_{12}$-based veto. This will allow us to reject a significant background in bolometers caused by surface contamination from $\alpha$-active radionuclides by means of light yield selection and to mitigate other sources of background, such as surface contamination from $\beta$-active radionuclides, external $\gamma$ radioactivity, and pile-up due to random coincidence of background events. This paper describes an R\&D program towards the BINGO goals, particularly focusing on the development of an innovative assembly designed to reduce the passive materials within the line of sight of the detectors, which is expected to be a dominant source of background in next-generation bolometric experiments. We present the performance of two prototype modules -- housing four cubic (4.5-cm side) Li$_2$MoO$_4$ crystals in total -- operated in the Canfranc underground laboratory in Spain within a facility developed for the CROSS double-beta-decay experiment., Comment: Submitted to Nucl. Instr. Meth. A; 28 pages, 11 figures, 4 tables

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.

Classical molecular dynamics simulations of hydrogen plasmas have been performed with emphasis on the analysis of equilibration process. Theoretical basis of simulation model as well as numerically relevant aspects -- such as the proper choice and definition of simulation units -- are discussed in detail, thus proving a thorough implementation of the computer simulation technique. Because of lack of experimental data, molecular dynamics simulations are often considered as "idealized computational experiments" for benchmarking of theoretical models. However, these simulations are certainly challenging and consequently a validation procedure is also demanded. In this work we develop an analytical statistical equilibrium model for computational validity assessment of plasma particle dynamics simulations. Remarkable agreement between model and molecular dynamics results including a classical treatment of ionization-recombination mechanism is obtained for a wide range of plasma coupling parameter. Furthermore, the analytical model provides guidance to securely terminate simulation runs once the equilibrium stage has been reached, which in turn gives confidence on the statistics that potentially may be extracted from time-histories of simulated physical quantities.

Sonic crystal acoustic screens have been in progressive research and development in the last two decades as a technical solution for mitigating traffic noise. Their behaviour is quite different from that observed in classical barriers, with the latter being based on physically blocking the direct sound propagation path (only allowing diffracted noise to reach sensible receivers), and sonic crystals providing attenuation efficiency based on the creation of band-gaps at specific frequency ranges, due to the Bragg's interference phenomenon. The distinct physical mechanisms of these two types of noise barriers complicates the use of classical simplified or even numerical models developed for traditional barriers to simulate and predict the attenuation performance of a sonic crystal, and alternative methods become thus required. In the acoustics scientific literature, several authors have proposed estimation and simulation methods based on different numerical tools to predict the sound insulation provided by these new noise abatement solutions. This paper presents a comparative evaluation of some of these methods, with emphasis to the assessment of their accuracy versus memory usage in order to determine which one is the most suitable for optimization methodologies in the design of new devices with improved acoustic performance., Comment: 18 pages, 4 figures

In this work we present an integrated photogrammetric-acoustic technique that, together with the construction of a scaled wind tunnel, allows us to experimentally analyze the permeability behavior of a new type of acoustic screens based on a material called sonic crystal. Acoustic screens are devices used to reduce the noise, mostly due to the communication infrastructures, in its transmission phase from the source to the receiver. The main constructive difference between these new screens and the classic ones is that the first ones are formed by arrays of acoustic scatterers while the second ones are formed by continuous walls. This implies that, due to their geometry, screens based on sonic crystals are permeable to wind and water, unlike the classic ones. This fact may allow the use of these new screens in sandy soils, where sand would pass through the screen avoiding the formation of sand dunes that are formed in classic screens and drastically reduce their acoustic performance. In this work, the movement of the sand and the resulting acoustic attenuation in these new screens are analyzed qualitatively comparing the results with those obtained with the classic ones, obtaining interesting results under the acoustic point of view, Comment: 17 pages, 8 figures

The correction of transcranial focused ultrasound aberrations is a relevant topic for enhancing various non-invasive medical treatments. Nowadays, the most widely accepted method to improve focusing is the emission through multi-element phased arrays; however, a new disruptive technology, based on 3D printed holographic acoustic lenses, has recently been proposed overcoming the spatial limitations of phased arrays due to the submillimetric precision of the latest generation of 3D printers. This works aims to optimize this recent solution; particularly, the preferred acoustic properties of the polymers used for printing the lens are systematically analyzed, paying special attention to the effect of p-wave speed and its relationship to the achievable voxel size of 3D printers. Results from simulations and experiments clearly show that there are optimal ranges for lens thickness and p-wave speed, fairly independent of the emitted frequency, the transducer aperture, or the transducer-target distance, given a particular voxel size, Comment: 24 pages, 9 figures

This article presents the use of advanced tools applied to the design of devices that can solve specific acoustic problems, improving the already existing devices based on classic technologies. Specifically, we have used two different configurations of a material called Sonic Crystals, which is formed by arrays of acoustic scatterers, to obtain acoustic screens with high diffusion properties by means of an optimization process. This design procedure has been carried out using a multiobjective evolutionary algorithm along to an acoustic simulation model developed with the numerical method called Finite Difference Time Domain (FDTD). The results obtained are discussed in terms of both the acoustic performance and the robustness of the devices achieved., Comment: 19 pages, 5 figures

In traditional machine teaching, a teacher wants to teach a concept to a learner, by means of a finite set of examples, the witness set. But concepts can have many equivalent representations. This redundancy strongly affects the search space, to the extent that teacher and learner may not be able to easily determine the equivalence class of each representation. In this common situation, instead of teaching concepts, we explore the idea of teaching representations. We work with several teaching schemas that exploit representation and witness size (Eager, Greedy and Optimal) and analyze the gains in teaching effectiveness for some representational languages (DNF expressions and Turing-complete P3 programs). Our theoretical and experimental results indicate that there are various types of redundancy, handled better by the Greedy schema introduced here than by the Eager schema, although both can be arbitrarily far away from the Optimal. For P3 programs we found that witness sets are usually smaller than the programs they identify, which is an illuminating justification of why machine teaching from examples makes sense at all., Comment: 16 pages, 3 figures, 3 tables

This paper presents the development process of a natural language to SQL model using the T5 model as the basis. The models, developed in August 2022 for an online transaction processing system and a data warehouse, have a 73\% and 84\% exact match accuracy respectively. These models, in conjunction with other work completed in the research project, were implemented for several companies and used successfully on a daily basis. The approach used in the model development could be implemented in a similar fashion for other database environments and with a more powerful pre-trained language model.

Motivated by recent experimental breakthroughs, we propose a strategy to design two-dimensional spin lattices with competing interactions that lead to non-trivial emergent quantum states. We consider $S=1/2$ nanographenes with $C_3$ symmetry as building blocks, and we leverage the potential to control both the sign and the strength of exchange with first neighbours to build a family of spin models. Specifically, we consider the case of a Heisenberg model in a triangle-decorated honeycomb lattice with competing ferromagnetic and antiferromagnetic interactions whose ratio can be varied in a wide range. Based on exact diagonalization of both fermionic and spin models we predict a quantum phase transition between a valence bond crystal of spin singlets with triplon excitations living in a Kagom\'e lattice and a N\'eel phase of effective $S=3/2$ in the limit of dominant ferromagnetic interactions., Comment: 6 pages, 4 figures

This study is concerned with the estimation of long-term fatigue damage for a floating offshore wind turbine. With the ultimate goal of efficient evaluation of fatigue limit states for floating offshore wind turbine systems, a detailed computational framework is introduced and used to develop a surrogate model using Gaussian process regression. The surrogate model, at first, relies only on a small subset of representative sea states and, then, is supplemented by the evaluation of additional sea states that leads to efficient convergence and accurate prediction of fatigue damage. A 5-MW offshore wind turbine supported by a semi-submersible floating platform is selected to demonstrate the proposed framework. The fore-aft bending moment at the turbine tower base and the fairlead tension in the windward mooring line are used for evaluation. Metocean data provide information on joint statistics of the wind and wave along with their relative likelihoods for the installation site in the Mediterranean Sea, near the coast of Sicily. \textcolor{black}{A coupled frequency-domain model} provides needed power spectra for the desired response processes. The proposed approach offers an efficient and accurate alternative to the exhaustive evaluation of a larger number of sea states and, as such, avoids excessive response simulations.