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Graphene spintronics offers a promising route to achieve low power 2D electronics for next generation classical and quantum computation. As device length scales are reduced to the limit of the electron mean free path, the transport mechanism crosses over to the ballistic regime. However, ballistic transport has yet to be shown in a graphene spintronic device, a necessary step towards realising ballistic spintronics. Here, we report ballistic injection of spin polarised carriers via one-dimensional contacts between magnetic nanowires and a high mobility graphene channel. The nanowire-graphene interface defines an effective constriction that confines charge carriers over a length scale smaller than that of their mean free path. This is evidenced by the observation of quantised conductance through the contacts with no applied magnetic field and a transition into the quantum Hall regime with increasing field strength. These effects occur in the absence of any constriction in the graphene itself and occur across several devices with transmission probability in the range T = 0.08 - 0.30., Comment: 4 figures

Artificial intelligence and machine learning applications in archaeology have increased significantly in recent years, and these now span all subfields, geographical regions, and time periods. The prevalence and success of these applications have remained largely unexamined, as recent reviews on the use of machine learning in archaeology have only focused only on specific subfields of archaeology. Our review examined an exhaustive corpus of 135 articles published between 1997 and 2022. We observed a significant increase in the number of relevant publications from 2019 onwards. Automatic structure detection and artefact classification were the most represented tasks in the articles reviewed, followed by taphonomy, and archaeological predictive modelling. From the review, clustering and unsupervised methods were underrepresented compared to supervised models. Artificial neural networks and ensemble learning account for two thirds of the total number of models used. However, if machine learning is gaining in popularity it remains subject to misunderstanding. We observed, in some cases, poorly defined requirements and caveats of the machine learning methods used. Furthermore, the goals and the needs of machine learning applications for archaeological purposes are in some cases unclear or poorly expressed. To address this, we proposed a workflow guide for archaeologists to develop coherent and consistent methodologies adapted to their research questions, project scale and data. As in many other areas, machine learning is rapidly becoming an important tool in archaeological research and practice, useful for the analyses of large and multivariate data, although not without limitations. This review highlights the importance of well-defined and well-reported structured methodologies and collaborative practices to maximise the potential of applications of machine learning methods in archaeology.

In this article, we construct a broad family of spacetimes with spherically symmetric thin shells in unimodular gravity. We analyze the dynamical stability of the configurations under perturbations preserving the symmetry. In particular, we consider the case of thin shells with charge surrounding vacuum, obtaining stable configurations for suitable values of the parameters. We compare our results with those corresponding to general relativity., Comment: 16 pages, 3 figures

In (super)gravity theories, T-duality relates solutions with an exact isometry which can have wildly different asymptotic behaviors: a well-known example is the duality between BTZ black holes and (non-extremal) three-dimensional black strings. Using this dual pair, we show how the knowledge of a phase space which includes one set of solutions (here, BTZ black holes embedded in the Brown-Henneaux phase space) allows to obtain a phase space for the dual set via an asymptotic notion of T-duality. The resulting asymptotic symmetry algebras can be very different. For our particular example, we find a large algebra of symmetries for the black string phase space which includes as subalgebras $\mathfrak{bms}_2$, $\mathfrak{bms}_3$, and a twisted warped conformal algebra. On the way, we show that a chiral half of the Brown-Henneaux boundary conditions are dual to the Comp\`ere-Song-Strominger ones., Comment: 19 pages + 3 appendices, ancillary Mathematica file with some computations of charges

The NAHU$^2$ project is a Franco-Mexican collaboration aimed at building the $\pi$-YALLI corpus adapted to machine learning, which will subsequently be used to develop computer resources for the Nahuatl language. Nahuatl is a language with few computational resources, even though it is a living language spoken by around 2 million people. We have decided to build $\pi$-YALLI, a corpus that will enable to carry out research on Nahuatl in order to develop Language Models (LM), whether dynamic or not, which will make it possible to in turn enable the development of Natural Language Processing (NLP) tools such as: a) a grapheme unifier, b) a word segmenter, c) a POS grammatical analyser, d) a content-based Automatic Text Summarization; and possibly, e) a translator translator (probabilistic or learning-based)., Comment: 9 pages, in French language, 2 figures

Controlling electron dynamics at optical clock rates is a fundamental challenge in lightwave-driven nanoelectronics. Here, we demonstrate ultrafast charge-state manipulation of individual selenium vacancies in monolayer and bilayer tungsten diselenide (WSe$_2$) using picosecond terahertz (THz) source pulses, focused onto the picocavity of a scanning tunneling microscope (STM). Using THz pump--THz probe time-domain sampling of the defect charge population, we capture atomic-scale snapshots of the transient Coulomb blockade, a signature of charge transport via quantized defect states. We identify back tunneling of localized charges to the tip electrode as a key challenge for lightwave-driven STM when probing electronic states with charge-state lifetimes exceeding the pulse duration. However, we show that back tunneling can be mitigated by the Franck-Condon blockade, which limits accessible vibronic transitions and promotes unidirectional charge transport. Our rate equation model accurately reproduces the time-dependent tunneling process across the different coupling regimes. This work builds on recent progress in imaging coherent lattice and quasiparticle dynamics with lightwave-driven STM and opens new avenues for exploring ultrafast charge dynamics in low-dimensional materials, advancing the development of lightwave-driven nanoscale electronics.

We present a novel approach for enhancing human-robot collaboration using physical interactions for real-time error correction of large language model (LLM) powered robots. Unlike other methods that rely on verbal or text commands, the robot leverages an LLM to proactively executes 6 DoF linear Dynamical System (DS) commands using a description of the scene in natural language. During motion, a human can provide physical corrections, used to re-estimate the desired intention, also parameterized by linear DS. This corrected DS can be converted to natural language and used as part of the prompt to improve future LLM interactions. We provide proof-of-concept result in a hybrid real+sim experiment, showcasing physical interaction as a new possibility for LLM powered human-robot interface., Comment: 7 pages, 3 figures; Generative Modeling meets HRI - RSS'24 Workshop

The paper introduces a novel approach for estimating soil moisture in vegetated surfaces, specifically focusing on sugarcane crops throughout various growth stages in agriculture applications. While existing models typically address bare soil scenarios, this model utilizes data from P-, L-, and C-band Synthetic Aperture Radar (SAR) to estimate soil moisture. The semi-empirical Dubois model forms the basis of the proposed model, which has been adapted to accommodate multiband operation and crop height variations. Synthetic datasets are generated using the adjusted model to train two neural networks incorporated into the overall model. Additionally, a linear expression for estimating crop height is integrated into the model. The model is validated in an Experimental Site at the School of Agricultural Engineering, UNICAMP, and an independent area at the Sugarcane Technology Center in Piracicaba, Brazil. The model utilizes a multiband drone-borne SAR system with a 3-meter image resolution and radiometric accuracy of 0.5 dB. The results indicate that the model can estimate soil moisture with root-mean-square errors of 0.05 cm3.cm-3 (5 vol. %) across crop heights ranging from zero to 2.5 meters., Comment: 9 pages, 12 figures, 2 tables, 17 equations

Leaf-cutting ants, notorious for causing defoliation in commercial forest plantations, significantly contribute to biomass and productivity losses, impacting forest producers in Brazil. These ants construct complex underground nests, highlighting the need for advanced monitoring tools to extract subsurface information across large areas. Synthetic Aperture Radar (SAR) systems provide a powerful solution for this challenge. This study presents the results of electromagnetic simulations designed to detect leaf-cutting ant nests in industrial forests. The simulations modeled nests with 6 to 100 underground chambers, offering insights into their radar signatures. Following these simulations, a field study was conducted using a drone-borne SAR operating in the P-band. A helical flight pattern was employed to generate high-resolution ground tomography of a commercial eucalyptus forest. A convolutional neural network (CNN) was implemented to detect ant nests and estimate their sizes from tomographic data, delivering remarkable results. The method achieved an ant nest detection accuracy of 100%, a false alarm rate of 0%, and an average error of 21% in size estimation. These outcomes highlight the transformative potential of integrating Synthetic Aperture Radar (SAR) systems with machine learning to enhance monitoring and management practices in commercial forestry., Comment: 8 pages, 22 figures, 4 tables

Accurate noise characterization is essential for reliable quantum computation. Effective Pauli noise models have emerged as powerful tools, offering detailed description of the error processes with a manageable number of parameters, which guarantees the scalability of the characterization procedure. However, a fundamental limitation in the learnability of Pauli fidelities impedes full high-accuracy characterization of both general and effective Pauli noise, thereby restricting e.g., the performance of noise-aware error mitigation techniques. We introduce Multi-Layer Cycle Benchmarking (MLCB), an enhanced characterization protocol that improves the learnability associated with effective Pauli noise models by jointly analyzing multiple layers of Clifford gates. We show a simple experimental implementation and demonstrate that, in realistic scenarios, MLCB can reduce unlearnable noise degrees of freedom by up to $75\%$, improving the accuracy of sparse Pauli-Lindblad noise models and boosting the performance of error mitigation techniques like probabilistic error cancellation. Our results highlight MLCB as a scalable, practical tool for precise noise characterization and improved quantum computation., Comment: 22 pages, 9 figures

Coronary Artery Disease (CAD) and Coronary Microvascular Disease (CMD) can lead to insufficient blood flow to the myocardium, affecting millions of people globally. Coronary angiography, one of the most commonly used imaging modalities, offers valuable information that assists in diagnosing these diseases. However, these benefits are not fully understood or utilized in current clinical practice. In this study, a 3D-0D coupled multi-physics computational fluid dynamics (CFD) model was developed and calibrated to simulate and better understand the process of contrast injection and washout during clinical angiography. A contrast intensity profile (CIP) was introduced to capture the dynamics of coronary angiography data. Additionally, a sensitivity study was conducted to assess the influence of various coronary artery model parameters on CIP. The results demonstrate that the calibrated 3D-0D coupled multi-physics models are physiologically meaningful and produce accurate hemodynamic results. The sensitivity study further reveals that resistance has a greater impact on CIP than capacitance, with higher resistance amplifying this effect., Comment: 21 pages, 12 figures

Shadows are often under-considered or even ignored in image editing applications, limiting the realism of the edited results. In this paper, we introduce MetaShadow, a three-in-one versatile framework that enables detection, removal, and controllable synthesis of shadows in natural images in an object-centered fashion. MetaShadow combines the strengths of two cooperative components: Shadow Analyzer, for object-centered shadow detection and removal, and Shadow Synthesizer, for reference-based controllable shadow synthesis. Notably, we optimize the learning of the intermediate features from Shadow Analyzer to guide Shadow Synthesizer to generate more realistic shadows that blend seamlessly with the scene. Extensive evaluations on multiple shadow benchmark datasets show significant improvements of MetaShadow over the existing state-of-the-art methods on object-centered shadow detection, removal, and synthesis. MetaShadow excels in image-editing tasks such as object removal, relocation, and insertion, pushing the boundaries of object-centered image editing.

This study examines the impact of lifelong learning on the professional lives of employed and unemployed individuals. Lifelong learning is a crucial factor in securing employment or enhancing one's existing career prospects. To achieve this objective, this study proposes the implementation of a multi-criteria decision support system for the evaluation of training courses in accordance with their capacity to enhance the employability of the students. The methodology is delineated in four stages. Firstly, a `working life curve' was defined to provide a quantitative description of an individual's working life. Secondly, an analysis based on K-medoids clustering defined a control group for each individual for comparison. Thirdly, the performance of a course according to each of the four predefined criteria was calculated using a t-test to determine the mean performance value of those who took the course. Ultimately, the unweighted TOPSIS method was used to evaluate the efficacy of the various training courses in relation to the four criteria. This approach effectively addresses the challenge of using extensive datasets within a system while facilitating the application of a multi-criteria unweighted TOPSIS method. The results of the multi-criteria TOPSIS method indicated that training courses related to the professional fields of administration and management, hostel and tourism and community and sociocultural services have positive impact on employability and improving the working conditions of citizens. However, courses that demonstrate the greatest effectiveness in ranking are the least demanded by citizens. The results will help policymakers evaluate the effectiveness of each training course offered by the regional government., Comment: 24 pages, 12 figures

Shock tubes are instrumental in studying high-temperature kinetics and simulating high-speed flows. They swiftly elevate the thermodynamic conditions of test gases, making them ideal for examining rapid chemical reactions and generating high-enthalpy flows for aerodynamic research. However, non-ideal effects, stemming from factors like diaphragm opening processes and viscous effects, can significantly influence thermodynamic conditions behind the shock wave. This study investigates the impact of various diaphragm opening patterns on the shock parameters near the driven section end-wall. Experiments were conducted using helium and argon as driver and driven gases, respectively, at pressures ranging from 1.32 to 2.09 bar and temperatures from 1073 to 2126 K behind the reflected shock. High-speed imaging captured different diaphragm rupture profiles, classified into four distinct types based on their dynamics. Results indicate that the initial stages of diaphragm opening, including the rate and profile of opening, play crucial roles in resulting incident shock Mach number and test time. A sigmoid function was employed to fit the diaphragm opening profiles, allowing for accurate categorization and analysis. New correlations were developed to predict the incident shock attenuation rate and post-shock pressure rise, incorporating parameters such as diaphragm opening time, rupture profile constants, and normalized experimental Mach number. The results emphasize the importance of considering diaphragm rupture dynamics in shock tube experiments to achieve accurate predictions of shock parameters., Comment: 13 pages, 8 figures

The use of multicore optical fibers is now recognized as one of the most promising methods to implement the space-division multiplexing techniques required to overcome the impending capacity limit of conventional single-mode optical fibers. Nonetheless, new devices for networking operations compatible with these fibers will be required in order to implement the next-generation high-capacity optical networks. In this work, we develop a new architecture to build a high-speed core-selective switch, critical for efficiently distributing signals over the network. The device relies on multicore interference, and can change among outputs in less than 0.7 us, while achieving less than -18 dB of average inter-core crosstalk, making it compatible with a wide range of network switching tasks. The functionality of the device was demonstrated by routing a 1GBs optical signal and by successfully switching signals over a field-installed multicore fiber network. Our results demonstrate for the first time the operation of a multicore optical fiber switch functioning under real-world conditions, with switching speeds that are three orders of magnitude faster than current commercial devices. This new optical switch design is also fully compatible with standard multiplexing techniques and, thus, represents an important achievement towards the integration of high-capacity multicore telecommunication networks., Comment: 8 pages, 5 figures

We study in detail the fully inhomogeneous non-linear dynamics of axion inflation, identifying three regimes: weak-, mild-, and strong-backreaction, depending on the duration of inflation. We use lattice techniques that explicitly preserve gauge invariance and shift symmetry, and which we validate against other computational methods of the linear dynamics and of the homogeneous backreaction regime. Notably, we demonstrate that the latter fails to accurately describe the truly local dynamics of strong backreaction. We investigate the convergence of simulations of local backreaction, determining the requirements to achieve an accurate description of the dynamics, and providing useful parametrizations of the delay of the end of inflation. Additionally, we identify key features emerging from a proper local treatment of strong backreaction: the dominance of magnetic energy against the electric counterpart, the excitation of the longitudinal mode, and the generation of a scale-dependent chiral (im)balance. Our results underscore the necessity to accurately capture the local nature of the non-linear dynamics of the system, in order to correctly assess phenomenological predictions, such as e.g. the production of gravitational waves and primordial black holes., Comment: 39 pages, 25 figures

This work analytically compares the growth of Backward Stimulated Raman Scattering (B-SRS) induced by temporal laser pulses on the order of a few tens of laser cycles or a couple of picoseconds for nominally 10 um wavelength IR pulse with Gaussian versus the constant intensity profile assumed in the original theory, both delivering an equivalent energy. By evaluating the growth factors of these two pulse shapes, we demonstrate that the temporal structure of the laser pulse significantly influences the maximum growth rate of the instability. Specifically, while the growth rate for a square pulse increases linearly with time, the Gaussian pulse resultant growth rate tracks with the temporal intensity profile of the pulse. We utilize the newly calculated total maximum growth that a temporally varying pulse delivers above the B-SRS threshold and then determine the normalized intensity for a pulse that has same duration. and contains the same amount of total energy. We show that these energy equivalent square pulses yield the same total B-SRS growth as the Gaussian pulses., Comment: 7 pages, 3 figures, 1 table

The orbital period of a cataclysmic variable stands as a crucial parameter for investigating the structure and physics of these binary systems, as well as understanding their evolution. We use photometric Gaia data for dwarf novae (DNe) in the quiescent state which are available for a number of years to determine new orbital periods and improve/modify previously suggested values. Two approaches are implemented for selecting high-inclination targets, either eclipsing or with ellipsoidal variations. We determine new orbital periods for 75 DNe and improve ephemerides for 27 more (three of which change significantly), contributing 9.4% of the known DNe periods of 0.05-2.0 days, and doubling the number of known periods exceeding 0.44 days. Their phase-folded light curves are presented and arranged by orbital period, illustrating the transition from short-period systems, dominated by radiation from the accretion disc and the hot spot, to longer-period DNe, where the Roche-lobe-filling secondary star is the primary visual flux source. This transition -- which occurs around the well-known period gap (around 2-3 hours) -- is expected, as DNe with larger orbital periods typically harbour more massive donors, which contribute to the visible flux. However, this transition is not abrupt. Within the same range of periods, we observe systems dominated by ellipsoidal variations, where the companion star is clearly visible, as well as others dominated by the disc and hot spot. The presence of some DNe with ellipsoidal variations near the lower edge of the period gap is striking, as the companions in these systems are expected to be cool low-mass M-dwarfs not visible in the light curve. This could indicate that we are observing systems where the donor star was originally much more massive and underwent significant nuclear evolution before mass-transfer began, as has been suggested previously for QZ Ser., Comment: Accepted for publication in A&A, 15 pages, 3 figures

We analyse the evolution of the reduced density matrix of inflationary perturbations, coupled to a heavy entropic field via the leading-order term within the Effective Field Theory of Inflation, for two nearly de Sitter backgrounds. We perform a full quantum treatment of the open system and derive a Fokker-Planck equation to describe decoherence and the entanglement structure of the adiabatic perturbations. We find that exotic phenomena, such as recoherence and transient negative growth of entanglement entropy, appearing for the attractor solution, are absent for the non-attractor background. We comment on the relationship of these to the non-Markovian nature of the system. Finally, we generalise to the case where a few e-folds of ultra-slow roll evolution are sandwiched between phases of slow-roll inflation to find its (memory) effects on the curvature perturbation., Comment: 42 pages, 14 figures

In this article, we give a characterization of log Calabi--Yau pairs of complexity zero and arbitrary index. As an application, we show that a log Calabi--Yau pair of birational complexity zero admits a crepant birational model which is a generalized Bott tower., Comment: 36 pages, comments welcome

Let $B\subset \mathbb{P}^3$ be an slc quartic surface. The existence of an embedding $\mathbb{G}_m^3\hookrightarrow \mathbb{P}^3\setminus B$ implies that $B$ has coregularity zero. In this article, we initiate the classification of coregularity zero slc quartic surfaces $B\subset \mathbb{P}^3$ for which $\mathbb{P}^3\setminus B$ contains an algebraic torus $\mathbb{G}_m^3$. Equivalently, the classification of cluster type pairs $(\mathbb{P}^3,B)$. Along the way, we give criteria for a log Calabi--Yau pair $(X,B)$ over a toric variety $T$ to be of cluster type., Comment: 24 pages

We propose an object-centric recovery policy framework to address the challenges of out-of-distribution (OOD) scenarios in visuomotor policy learning. Previous behavior cloning (BC) methods rely heavily on a large amount of labeled data coverage, failing in unfamiliar spatial states. Without relying on extra data collection, our approach learns a recovery policy constructed by an inverse policy inferred from object keypoint manifold gradient in the original training data. The recovery policy serves as a simple add-on to any base visuomotor BC policy, agnostic to a specific method, guiding the system back towards the training distribution to ensure task success even in OOD situations. We demonstrate the effectiveness of our object-centric framework in both simulation and real robot experiments, achieving an improvement of 77.7% over the base policy in OOD. Project Website: https://sites.google.com/view/ocr-penn, Comment: Accepted for Spotlight (5 out of 21 papers) at CoRL 2024 Workshop on Lifelong Learning for Home Robots

Context. Green valley (GV) galaxies are objects defined on a color-magnitude, or color-mass, diagram which are associated with a transition from a star-forming to a quiescent state (quenching), or vice versa (rejuvenation). Aims. We study the sub-mm emission of galaxies in the GV and link it with their physical evolutionary properties. Methods. We exploit a semi-analytic model (SAM) for galaxy evolution which includes a detailed treatment of dust production and evolution in galactic contexts. We model the observational properties of simulated galaxies by post-processing the SAM catalogs with the spectral synthesis and radiative transfer code GRASIL. Results. Our model produces a clear bimodality (and thus a GV) in the color-mass diagram, although some tensions arise when compared to observations. After having introduced a new criterion for identifying the GV in any dataset, we find that most blue and GV galaxies in our model are emitters at $250\,{\mu \rm m}$ (with fluxes $\geq 25\,{\rm mJy}$), in keeping with GAMA results. In the color-$S_{250\, \mu \rm m}$ diagram, GV galaxies exhibit intermediate colors yet maintain significant sub-mm fluxes. This occurs because, while specific star formation rates drop sharply during quenching, the dust content remains relatively high during the GV transition, powering sub-mm emission. Rejuvenating galaxies in the GV, which were previously red, have experienced a star formation burst that shifts their color to green, but their $S_{250\, \mu \rm m}$ fluxes remain low due to still low dust mass. Conclusions. Our galaxy evolution model highlights the delay between star formation and dust evolution, showing that sub-mm emission is not always a safe indicator of star formation activity, with quenching (rejuvenating) GV galaxies featuring relatively large (low) sub-mm emission., Comment: 12 pages, 13 figures. Submitted to A&A

The University of the Philippines Open University has been at the forefront of providing Massive Open Online Courses to address knowledge and skill gaps, aiming to make education accessible and contributing to societal goals. Recognising challenges in student engagement and completion rates within Massive Open Online Courses, the authors conducted a study by incorporating gamification into one of the University of the Philippines Open University's Massive Open Online Courses to assess its impact on these aspects. Gamification involves integrating game elements to motivate and engage users. This study explored the incorporation of Moodle elements such as badges, leaderboards, and progress bars. Using Moodle analytics, the study also tracked student engagement, views, and posts throughout the course, offering valuable insights into the influence of gamification on user behaviour. Furthermore, the study delved into participant feedback gathered through post-evaluation surveys, providing a comprehensive understanding of their experiences with the gamified course design. With a 28.86% completion rate and positive participant reception, the study concluded that gamification can enhance learner motivation, participation, and overall satisfaction. This research contributes to the ongoing discourse on innovative educational methods, positioning gamification as a promising avenue for creating interactive and impactful online learning experiences in the Philippines and beyond.

While the power of quantum computers is commonly acknowledged to rise exponentially, it is often overlooked that the complexity of quantum noise mechanisms generally grows much faster. In particular, quantifying whether the instructions on a quantum processor are close to being unitary has important consequences concerning error rates, e.g., for the confidence in their estimation, the ability to mitigate them efficiently, or their relation to fault-tolerance thresholds in error correction. However, the complexity of estimating the coherence, or unitarity, of noise generally scales exponentially in system size. Here, we obtain an upper bound on the average unitarity of Pauli noise and develop a protocol allowing us to estimate the average unitarity of operations in a digital quantum device efficiently and feasibly for mid-size quantum systems. We demonstrate our results through both experimental execution on IQM Spark (TM), a 5-qubit superconducting quantum computer, and in simulation with up to 10 qubits, discussing the prospects for extending our technique to arbitrary scales., Comment: 11+21 pages, 10 figures

Constraint-aware estimation of human intent is essential for robots to physically collaborate and interact with humans. Further, to achieve fluid collaboration in dynamic tasks intent estimation should be achieved in real-time. In this paper, we present a framework that combines online estimation and control to facilitate robots in interpreting human intentions, and dynamically adjust their actions to assist in dynamic object co-manipulation tasks while considering both robot and human constraints. Central to our approach is the adoption of a Dynamic Systems (DS) model to represent human intent. Such a low-dimensional parameterized model, along with human manipulability and robot kinematic constraints, enables us to predict intent using a particle filter solely based on past motion data and tracking errors. For safe assistive control, we propose a variable impedance controller that adapts the robot's impedance to offer assistance based on the intent estimation confidence from the DS particle filter. We validate our framework on a challenging real-world human-robot co-manipulation task and present promising results over baselines. Our framework represents a significant step forward in physical human-robot collaboration (pHRC), ensuring that robot cooperative interactions with humans are both feasible and effective., Comment: RSS24 version with typos fixed

Cooperative multi-monostatic sensing enables accurate positioning of passive targets by combining the sensed environment of multiple base stations (BS). In this work, we propose a novel fusion algorithm that optimally finds the weight to combine the time-of-arrival (ToA) and angle-of-arrival (AoA) likelihood probability density function (PDF) of multiple BSs. In particular, we employ a log-linear pooling function that fuses all BSs' PDFs using a weighted geometric average. We formulated an optimization problem that minimizes the Reverse Kullback Leibler Divergence (RKLD) and proposed an iterative algorithm based on the Monte Carlo importance sampling (MCIS) approach to obtain the optimal fusion weights. Numerical results verify that our proposed fusion scheme with optimal weights outperforms the existing benchmark in terms of positioning accuracy in both unbiased (line-of-sight only) and biased (multipath-rich environment) scenarios., Comment: 6 pages, 5 figures. Accepted for presentation in Globecom 2024

The structural and chemical properties of metal nanoparticles are often dictated by their interactions with molecular ligand shells. These interactions are highly material-specific and can vary significantly even among elements within the same group or materials with similar crystal structure. Precise characterization of ligand-metal interactions is crucial for the rational design of ligands and the functionalization of nanoparticles. In this study, we found that the ligation behavior with m-terphenyl isocyanide molecule differs significantly between Au and Ag nanoparticles, with distinct ligand extraction efficiencies and size dependencies. Surface-enhanced Raman spectroscopy measurements revealed unique enhancement factors for two molecular vibrational modes between two metal surfaces, indicating different ligand binding geometries. Molecular-level characterization using scanning tunneling microscopy allowed us to directly visualize these variations between Ag and Au surfaces, which we assign as two distinct binding mechanisms. This molecular-scale visualization provides clear insights into the different ligand-metal interactions, as well as the chemical behavior and spectroscopic characteristics of isocyanide-functionalized nanoparticles.

A study of the dynamical and thermodynamical stability of a charged thin-shell wormhole built by gluing two Reissner-Nordstr\"{o}m geometries is presented. The charge on the shell is linearly related to the matter content. For the dynamical stability, a concise inequality is obtained, valid for any barotropic equation of state that relates the pressure with the energy density at the throat. A thermodynamical description of the system is introduced, which leads to the temperature and the electric potentials. Adopting a linear equation of state for the pressure and a definite form for the entropy function, the set of equilibrium configurations that are both dynamically and thermodynamically stable is found., Comment: 27 pages, 3 figures; v3: corrected typos in references

Quantum computing has tremendous potential to overcome some of the fundamental limitations present in classical information processing. Yet, today's technological limitations in the quality and scaling prevent exploiting its full potential. Quantum computing based on superconducting quantum processing units (QPUs) is among the most promising approaches towards practical quantum advantage. In this article the basic technological approach of IQM Quantum Computers is described covering both the QPU and the rest of the full-stack quantum computer. In particular, the focus is on a 20-qubit quantum computer featuring the Garnet QPU and its architecture, which we will scale up to 150 qubits. We also present QPU and system-level benchmarks, including a median 2-qubit gate fidelity of 99.5% and genuinely entangling all 20 qubits in a Greenberger-Horne-Zeilinger (GHZ) state.

Understanding phonon and charge propagation in superconducting devices plays an important role in both performing low-threshold dark matter searches and limiting correlated errors in superconducting qubits. The Geant4 Condensed Matter Physics (G4CMP) package, originally developed for the Cryogenic Dark Matter Search (CDMS) experiment, models charge and phonon transport within silicon and germanium detectors and has been validated by experimental measurements of phonon caustics, mean charge-carrier drift velocities, and heat pulse propagation times. In this work, we present a concise framework for expanding the capabilities for phonon transport to a number of other novel substrate materials of interest to the dark matter and quantum computing communities, including sapphire (Al$_{2}$O$_{3}$), gallium arsenide (GaAs), lithium fluoride (LiF), calcium tungstate (CaWO$_{4}$), and calcium fluoride (CaF$_{2}$). We demonstrate the use of this framework in generating phonon transport properties of these materials and compare these properties with experimentally-determined values where available., Comment: 18 pages, 13 figures, 6 Tables

Axion-like particles (ALPs) arise from well-motivated extensions to the Standard Model and could account for dark matter. ALP dark matter would manifest as a field oscillating at an (as of yet) unknown frequency. The frequency depends linearly on the ALP mass and plausibly ranges from $10^{-22}$ to $10$ eV/$c^2$. This motivates broadband search approaches. We report on a direct search for ALP dark matter with an interferometer composed of two atomic K-Rb-$^3$He comagnetometers, one situated in Mainz, Germany, and the other in Krak\'ow, Poland. We leverage the anticipated spatio-temporal coherence properties of the ALP field and probe all ALP-gradient-spin interactions covering a mass range of nine orders of magnitude. No significant evidence of an ALP signal is found. We thus place new upper limits on the ALP-neutron, ALP-proton and ALP-electron couplings reaching below $g_{aNN}<10^{-9}$ GeV$^{-1}$, $g_{aPP}<10^{-7}$ GeV$^{-1}$ and $g_{aee}<10^{-6}$ GeV$^{-1}$, respectively. These limits improve upon previous laboratory constraints for neutron and proton couplings by up to three orders of magnitude.

Using lattice field simulations of the Abelian-Higgs model, we characterize the simultaneous emission of (scalar and gauge) particles and gravitational waves (GWs) by local string loops. We use {\it network} loops created in a phase transition, and {\it artificial} loops formed by either crossing straight-boosted or curved-static infinite strings. Loops decay via both particle and GW emission, on time scales $\Delta t_{\rm dec} \propto L^p$, where $L$ is the loop length. For particle production, we find $p \simeq 2$ for artificial loops and $p \lesssim 1$ for network loops, whilst for GW emission, we find $p \simeq 1$ for all loops. We find that below a critical length, artificial loops decay primarily through particle production, whilst for larger loops GW emission dominates. However, for network loops, which represent more realistic configurations, particle emission always dominates, as supported by our data with length-to-core ratios up to $L/r_\text{c} \lesssim 3500$. Our results indicate that the GW background from a local string network should be greatly suppressed compared to estimations that ignore particle emission., Comment: 5 pages + Supplemental material, 2+3 figures, 2 tables

We present Adaptic, a novel "hybrid" active/passive haptic device that can change shape to act as a proxy for a range of virtual objects in VR. We use Adaptic with haptic retargeting to redirect the user's hand to provide haptic feedback for several virtual objects in arm's reach using only a single prop. To evaluate the effectiveness of Adaptic with haptic retargeting, we conducted a within-subjects experiment employing a docking task to compare Adaptic to non-matching proxy objects (i.e., Styrofoam balls) and matching shape props. In our study, Adaptic sat on a desk in front of the user and changed shapes between grasps, to provide matching tactile feedback for various virtual objects placed in different virtual locations. Results indicate that the illusion was convincing: users felt they were manipulating several virtual objects in different virtual locations with a single Adaptic device. Docking performance (completion time and accuracy) with Adaptic was comparable to props without haptic retargeting., Comment: 10 Pages

A Waveguide Port Boundary Condition (WPBC) based on the restriction of the approximation space is presented in the context of Finite Element Analysis. As well as reducing the computational domain in the same manner as the traditional WPBC, the proposed scheme further reduces the degrees of freedom at the waveguide ports, simplifies the implementation and seamlessly provides post-processing results such as the reflected power in each waveguide mode. The boundary condition is thoroughly derived, and numerical examples are used as a support for the discussion on topics such as the needed number of modes to be employed at a waveguide port. Finally, a nanograting-based plasmonic sensor is analysed to illustrate further possibilities of the scheme., Comment: Preprint submitted to Engineering With Computers, by Springer

Self-Supervised Learning (SSL) has become a prominent approach for acquiring visual representations across various tasks, yet its application in fine-grained visual recognition (FGVR) is challenged by the intricate task of distinguishing subtle differences between categories. To overcome this, we introduce an novel strategy that boosts SSL's ability to extract critical discriminative features vital for FGVR. This approach creates synthesized data pairs to guide the model to focus on discriminative features critical for FGVR during SSL. We start by identifying non-discriminative features using two main criteria: features with low variance that fail to effectively separate data and those deemed less important by Grad-CAM induced from the SSL loss. We then introduce perturbations to these non-discriminative features while preserving discriminative ones. A decoder is employed to reconstruct images from both perturbed and original feature vectors to create data pairs. An encoder is trained on such generated data pairs to become invariant to variations in non-discriminative dimensions while focusing on discriminative features, thereby improving the model's performance in FGVR tasks. We demonstrate the promising FGVR performance of the proposed approach through extensive evaluation on a wide variety of datasets., Comment: Accepted by ECCV 2024

We address the Poincar\'e-Perron's classical problem of approximation for high order linear differential equations in the class of almost periodic type functions, extending the results for a second order linear differential equation in [23]. We obtain explicit formulae for solutions of these equations, for any fixed order $n\ge 3$, by studying a Riccati type equation associated with the logarithmic derivative of a solution. Moreover, we provide sufficient conditions to ensure the existence of a fundamental system of solutions. The fixed point Banach argument allows us to find almost periodic and asymptotically almost periodic solutions to this Riccati type equation. A decomposition property of the perturbations induces a decomposition on the Riccati type equation and its solutions. In particular, by using this decomposition we obtain asymptotically almost periodic and also $p$-almost periodic solutions to the Riccati type equation. We illustrate our results for a third order linear differential equation., Comment: arXiv admin note: text overlap with arXiv:2111.05467

We present an analysis method to search for exotic low-mass field (ELF) bursts generated during large energy astrophysical events such as supernovae, binary black hole or binary neutron star mergers, and fast radio bursts using the Global Network of Optical Magnetometers for Exotic physics searches (GNOME). In our model, the associated gravitational waves or electromagnetic signals herald the arrival of the ELF burst that interacts via coupling to the spin of fermions in the magnetometers. This enables GNOME to serve as a tool for multi-messenger astronomy. The algorithm employs a model-agnostic excess-power method to identify network-wide candidate events to be subjected to a model-dependent generalized likelihood-ratio test to determine their statistical significance. We perform the first search with this technique on GNOME data coincident with the binary black hole merger S200311bg detected by LIGO/Virgo on the 11th of March 2020 and find no significant events. We place the first lab-based limits on combinations of ELF production and coupling parameters.

In this work, we consider the propagation of acoustic waves in unbounded domains characterized by a constant wavenumber, except possibly in a bounded region. The geometry of this inhomogeneity is assumed to be uncertain, and we are particularly interested in studying the propagation of this behavior throughout the physical model considered. A key step in our analysis consists of recasting the physical model-originally set in an unbounded domain-into a computationally manageable formulation based on Volume Integral Equations (VIEs), particularly the Lippmann-Schwinger equation. We show that both the leading operator in this volume integral formulation and its solution depend holomorphically on shape variations of the support of the aforementioned inhomogeneity. This property, known as shape holomorphy, is crucial in the analysis and implementation of various methods used in computational Uncertainty Quantification (UQ). We explore the implications of this result in forward and inverse UQ and provide numerical experiments illustrating and confirming the theoretical predictions.