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Federated Learning (FL) allows collaboration between different parties, while ensuring that the data across these parties is not shared. However, not every collaboration is helpful in terms of the resulting model performance. Therefore, it is an important challenge to select the correct participants in a collaboration. As it currently stands, most of the efforts in participant selection in the literature have focused on Horizontal Federated Learning (HFL), which assumes that all features are the same across all participants, disregarding the possibility of different features across participants which is captured in Vertical Federated Learning (VFL). To close this gap in the literature, we propose a novel method VFL-RPS for participant selection in VFL, as a pre-training step. We have tested our method on several data sets performing both regression and classification tasks, showing that our method leads to comparable results as using all data by only selecting a few participants. In addition, we show that our method outperforms existing methods for participant selection in VFL.

Multi-antenna channel sounding is a technique for measuring the propagation characteristics of electromagnetic waves that is commonly employed for parameterizing channel models. Channel sounders are usually custom-built from many Software Defined Radio receivers, making them expensive to procure and difficult to operate, which constrains the set of users to a few specialized scientific institutions and industrial research laboratories. Recent developments in Joint Communications and Sensing (JCaS) extend the possible uses of channel data to applications like human activity recognition, human presence detection, user localization and wireless Channel Charting, all of which are of great interest to security researchers, experts in industrial automation and others. However, due to a lack of affordable, easy-to-use and commercially available multi-antenna channel sounders, those scientific communities can be hindered by their lack of access to wireless channel measurements. To lower the barrier to entry for channel sounding, we develop an ultra low-cost measurement hardware platform based on mass-produced WiFi chips, which is easily affordable to research groups and even hobbyists.

In semiconducting-superconducting hybrid devices, Andreev bound states (ABSs) can mediate the coupling between quantum dots (QDs), allowing for the realisation of artificial Kitaev chains. In order to engineer Majorana bound states (MBSs) in these systems, one must control the energy of the ABSs. In this work, we show how extended ABSs in a flux tunable Josephson junction can be used to control the coupling between distant quantum dots separated by $\approx$ 1 $\mathrm{\mu}$m. In particular, we demonstrate that the combination of electrostatic control and phase control over the ABSs significantly increases the parameter space in which MBSs are observed. Finally, by employing an additional spectroscopic probe in the hybrid region between the QDs, we gain information about the spatial distribution of the Majorana wave function in a two-site Kitaev chain., Comment: 13 pages - 4 main figures, 10 supplementary figures

We formalize and study the problem of repairing database queries based on user feedback in the form of a collection of labeled examples. We propose a framework based on the notion of a proximity pre-order, and we investigate and compare query repairs for conjunctive queries (CQs) using different such pre-orders. The proximity pre-orders we consider are based on query containment and on distance metrics for CQs., Comment: Full version of ICDT 2025 paper

In this paper, a novel network architecture that deploys the multi-functional reconfigurable intelligent surface (MF-RIS) in low-Earth orbit (LEO) is proposed. Unlike traditional RIS with only signal reflection capability, the MF-RIS can reflect, refract, and amplify signals, as well as harvest energy from wireless signals. Given the high energy demands in shadow regions where solar energy is unavailable, MF-RIS is deployed in LEO to enhance signal coverage and improve energy efficiency (EE). To address this, we formulate a long-term EE optimization problem by determining the optimal parameters for MF-RIS configurations, including amplification and phase-shifts, energy harvesting ratios, and LEO transmit beamforming. To address the complex non-convex and non-linear problem, a federated learning enhanced multi-agent deep deterministic policy gradient (FEMAD) scheme is designed. Multi-agent DDPG of each agent can provide the optimal action policy from its interaction to environments, whereas federated learning enables the hidden information exchange among multi-agents. In numerical results, we can observe significant EE improvements compared to the other benchmarks, including centralized deep reinforcement learning as well as distributed multi-agent deep deterministic policy gradient (DDPG). Additionally, the proposed LEO-MF-RIS architecture has demonstrated its effectiveness, achieving the highest EE performance compared to the scenarios of fixed/no energy harvesting in MF-RIS, traditional reflection-only RIS, and deployment without RISs/MF-RISs.

Narrowing the performance gap between optimal and feasible detection in inter-symbol interference (ISI) channels, this paper proposes to use graph neural networks (GNNs) for detection that can also be used to perform joint detection and decoding (JDD). For detection, the GNN is build upon the factor graph representations of the channel, while for JDD, the factor graph is expanded by the Tanner graph of the parity-check matrix (PCM) of the channel code, sharing the variable nodes (VNs). A particularly advantageous property of the GNN is a) the robustness against cycles in the factor graphs which is the main problem for sum-product algorithm (SPA)-based detection, and b) the robustness against channel state information (CSI) uncertainty at the receiver. Additionally, we propose using an input embedding resulting in a GNN independent of the channel impulse response (CIR). Consequently, a fully deep learning-based receiver enables joint optimization instead of individual optimization of the components, so-called end-to-end learning. Furthermore, we propose a parallel flooding schedule that also reduces the latency, which turns out to improve the error correcting performance. The proposed approach is analyzed and compared to state-of-the-art baselines for different modulations and codes in terms of error correcting capability and latency. The gain compared to SPA-based detection might be explained with improved messages between nodes and adaptive damping of messages. For a higher order modulation in a high-rate turbo detection and decoding (TDD) scenario the GNN shows a, at first glance, surprisingly high gain of 6.25 dB compared to the best, feasible non-neural baseline., Comment: Submitted to Transactions on Communications. arXiv admin note: text overlap with arXiv:2401.16187

Hybrid multiterminal Josephson junctions (JJs) are expected to harbor a novel class of Andreev bound states (ABSs), including topologically nontrivial states in four-terminal devices. In these systems, topological phases emerge when ABSs depend on at least three superconducting phase differences, resulting in a three-dimensional (3D) energy spectrum characterized by Weyl nodes at zero energy. Here, we realize a four-terminal JJ in a hybrid Al/InAs heterostructure, where ABSs form a synthetic 3D band structure. We probe the energy spectrum using tunneling spectroscopy and identify spectral features associated with the formation of a tri-Andreev molecule, a bound state whose energy depends on three superconducting phases and, therefore, is able to host topological ABSs. The experimental observations are well described by a numerical model. The calculations predict the appearance of four Weyl nodes at zero energy within a gap smaller than the experimental resolution. These topological states are theoretically predicted to remain stable within an extended region of the parameter space, well accessible by our device. These findings establish an experimental foundation to study high-dimensional synthetic band structures in multiterminal JJs, and to realize topological Andreev bands.

W Serpentis is an eclipsing binary system and the prototype of the Serpentid class of variable stars. These are interacting binaries experiencing intense mass transfer and mass loss. However, the identities and properties of both stars in W Ser remain a mystery. Here we present an observational analysis of high quality, visible-band spectroscopy made with the Apache Point Observatory 3.5 m telescope and ARCES spectrograph plus the first near-IR, long-baseline interferometric observations obtained with the CHARA Array. We present examples of the appearance and radial velocities of the main spectral components: prominent emission lines, strong shell absorption lines, and weak absorption lines. We show that some of the weak absorption features are associated with the cool mass donor, and we present the first radial velocity curve for the donor star. The donor's absorption lines are rotationally broadened, and we derive a ratio of donor to gainer mass of 0.36 +/- 0.09 based on the assumptions that the donor fills its Roche lobe and rotates synchronously with the orbit. We use a fit of the ASAS light curve to determine the orbital inclination and mass estimates of 2.0 and 5.7 solar masses for the donor and gainer, respectively. The partially resolved interferometric measurements of orbital motion are consistent with our derived orbital properties and the distance from Gaia EDR3. Spectroscopic evidence indicates that the gainer is enshrouded in an opaque disk that channels the mass transfer stream into an outflow through the L3 region and into a circumbinary disk., Comment: Published in ApJ

The goal of thermodynamic optimal control theory is to find protocols to change the state of a system from an initial to a desired final distribution, within a finite time, with the least possible expenditure of work. The optimal protocol is closely linked to the intrinsic dynamics of the system at hand. The fact that these dynamics can vary widely has made a general solution elusive. Recent years have seen great progress by recasting the question in terms of a quantity called total activity, i.e. the average number of jumps between states of the system, rather than the time that the operation is allowed to take. This perspective has allowed for general expressions for the minimal work as a function of the total activity, and the minimal total activity required for a given work. The expression for minimal total activity can be recast as an apparent minimal operation time or speed limit. However, it is unclear whether protocols optimized under a constrained activity actually require the lowest work input for a given operation time. In the context of bit reset, we show that directly minimizing work for a given operation time leads to protocols that require significantly less work to perform the operation than the activity-constrained protocol of the same duration. We show how the resulting protocols differ. One reason for the difference is the fact that the activity rate is not constant over the course of the protocol: it depends on both the transition rates and the distribution of the bit, both of which change during the copy operation. In the limit of long protocol duration, we find an expression for the difference between the resulting minimal work for both optimization schemes, for a general class of dynamics. The time-constrained approach always outperforms the activity-constrained approach for a given constrained duration, and the difference in work can be arbitrarily large., Comment: 15 pages, 3 figures

Labeled examples (i.e., positive and negative examples) are an attractive medium for communicating complex concepts. They are useful for deriving concept expressions (such as in concept learning, interactive concept specification, and concept refinement) as well as for illustrating concept expressions to a user or domain expert. We investigate the power of labeled examples for describing description-logic concepts. Specifically, we systematically study the existence and efficient computability of finite characterisations, i.e. finite sets of labeled examples that uniquely characterize a single concept, for a wide variety of description logics between EL and ALCQI, both without an ontology and in the presence of a DL-Lite ontology. Finite characterisations are relevant for debugging purposes, and their existence is a necessary condition for exact learnability with membership queries., Comment: Published in the Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI)

Understanding and classifying chiral structural color of scarab beetles across the phylogenetic tree is an important scientific tool to explore the origins of the homochiral optical response in biological structures with a potential relation to the homochirality of (chitin) molecules. We report hyperspectral polarization resolved images of the scarab beetle \textit{Protaetia speciosa jousselini} (Gory \& Percheron, 1833) and resolve the state of polarization as a function of both position (spatial resolution of $\sim$20 $\mu$m $\times$ 10 $\mu$m) and wavelength (spectral resolution of 5.5 nm). We observe a strong left-handed chiral Bragg reflection and analyze the center wavelength and width of the spectrum. The reflection and state of polarization scale with the center wavelength of the Bragg reflection, while the relative width of reflection spectrum is characterized by a chiral photonic strength parameter $\psi_C \approx 0.14$ that is independent of the reflected color and position. Based on the self-similarity of the reflection spectra we interpret variation in reflectivity as variations in the thickness of the chiral Bragg reflector across the beetle., Comment: 13 pages, 8 figures

The theory of pebble accretion (PA) has become a popular planet formation theory during the past decade. However, PA studies generally rely on large planetary embryos, much larger than those expected from the streaming instability. This study analyses the formation of terrestrial planets around stars with masses ranging from 0.09 to 1.00 M$_\odot$ through PA, starting with small planetesimals with radii between 175 and 450 km. We perform numerical simulations, using a modified version of the N-body simulator SyMBA, which includes pebble accretion, type I and II migration, and eccentricity and inclination damping. Two prescriptions for the pebble accretion rate are analysed. We find that Earth-mass planets are consistently formed around 0.49, 0.70 and 1.00 M$_\odot$ stars, irrespective of the pebble accretion model. However, Earth-like planets seldom remain in the habitable zone, for they rapidly migrate to the inner edge of the disc. Furthermore, we find that pebble accretion onto small planetesimals cannot produce Earth-mass planets around 0.09 and 0.20 M$_\odot$, challenging the proposed narrative of the formation of the TRAPPIST-1 system. Further research is needed to determine if models with a lower pebble mass flux, or additional migration traps, could produce solar-system-like planetary systems in which Earth-like planets remain in the habitable zone., Comment: 29 pages, 20 figures, submitted to A&A

Channel Charting is a dimensionality reduction technique that learns to reconstruct a low-dimensional, physically interpretable map of the radio environment by taking advantage of similarity relationships found in high-dimensional channel state information. One particular family of Channel Charting methods relies on pseudo-distances between measured CSI datapoints, computed using dissimilarity metrics. We suggest several techniques to improve the performance of dissimilarity metric-based Channel Charting. For one, we address an issue related to a discrepancy between Euclidean distances and geodesic distances that occurs when applying dissimilarity metric-based Channel Charting to datasets with nonconvex low-dimensional structure. Furthermore, we incorporate the uncertainty of dissimilarities into the learning process by modeling dissimilarities not as deterministic quantities, but as probability distributions. Our framework facilitates the combination of multiple dissimilarity metrics in a consistent manner. Additionally, latent space dynamics like constrained acceleration due to physical inertia are easily taken into account thanks to changes in the training procedure. We demonstrate the achieved performance improvements for localization applications on a measured channel dataset

Kleene Algebra with Tests (KAT) provides an elegant algebraic framework for describing non-deterministic finite-state computations. Using a small finite set of non-deterministic programming constructs (sequencing, non-deterministic choice, and iteration) it is able to express all non-deterministic finite state control flow over a finite set of primitives. It is natural to ask whether there exists a similar finite set of constructs that can capture all deterministic computation. We show that this is not the case. More precisely, the deterministic fragment of KAT is not generated by any finite set of regular control flow operations. This generalizes earlier results about the expressivity of the traditional control flow operations, i.e., sequential composition, if-then-else and while.

Cepheid masses are particularly necessary to help solving the mass discrepancy, while independent distance determinations provide crucial test of the period-luminosity relation and Gaia parallaxes. We used CHARA/MIRC to measure the astrometric positions of the high-contrast companion orbiting the Cepheid SU Cygni. We also present new radial velocity measurements from the HST. The combination of interferometric astrometry with optical and ultraviolet spectroscopy provides the full orbital elements of the system, in addition to component masses and the distance to the Cepheid system. We measured the mass of the Cepheid, $M_A = 4.859\pm0.058M_\odot$, and its two companions, $M_{Ba} = 3.595 \pm 0.033 M_\odot$ and $M_{Bb} = 1.546 \pm 0.009 M_\odot$. This is the most accurate existing measurement of the mass of a Galactic Cepheid (1.2%). Comparing with stellar evolution models, we show that the mass predicted is higher than the measured mass of the Cepheid, similar to conclusions of our previous work. We also measured the distance to the system to be $926.3 \pm 5.0$pc, i.e. an unprecedented parallax precision of $6\mu$as (0.5%), being the most precise and accurate distance for a Cepheid. Such precision is similar to what is expected by Gaia for the last data release (DR5 in $\sim$ 2030) for single stars fainter than G = 13, but is not guaranteed for stars as bright as SU Cyg. We demonstrated that evolutionary models remain inadequate in accurately reproducing the measured mass, often predicting higher masses for the expected metallicity, even when factors such as rotation or convective core overshooting are taken into account. Our precise distance measurement allowed us to compare prediction period-luminosity relations. We found a disagreement of 0.2-0.5 mag with relations calibrated from photometry, while relations calibrated from direct distance measurement are in better agreement., Comment: Accepted for publication in A&A

This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

We present a systematic derivation of three mathematical models of increasing complexity for optical design, based on Hamilton's characteristic functions and conservation of luminous flux, and briefly explain the connection with the mathematical theory of optimal transport. We outline several iterative least-squares solvers for our models and demonstrate their performance for a few challenging problems., Comment: 23 pages

In this paper, we discuss a mathematical model for inverse freeform design of an optical system with two reflectors in which light transfers from a point source to a point target. In this model, the angular light intensity emitted from the point source and illuminance arriving at the point target are specified by distributions. To determine the optical mapping and the shape of the reflectors, we use the optical path length and take energy conservation into account, through which we obtain a generated Jacobian equation. We express the system in both spherical and stereographic coordinates, and solve it using a sophisticated least-squares algorithm. Several examples illustrate the algorithm's capabilities to tackle complicated light distributions., Comment: 12 pages

To alleviate the suboptimal performance of belief propagation (BP) decoding of short low-density parity-check (LDPC) codes, a plethora of improved decoding algorithms has been proposed over the last two decades. Many of these methods can be described using the same general framework, which we call ensemble decoding: A set of independent constituent decoders works in parallel on the received sequence, each proposing a codeword candidate. From this list, the maximum likelihood (ML) decision is designated as the decoder output. In this paper, we qualitatively and quantitatively compare different realizations of the ensemble decoder, namely multiple-bases belief propagation (MBBP), automorphism ensemble decoding (AED), scheduling ensemble decoding (SED), noise-aided ensemble decoding (NED) and saturated belief propagation (SBP). While all algorithms can provide gains over traditional BP decoding, ensemble methods that exploit the code structure, such as MBBP and AED, typically show greater performance improvements., Comment: 6 pages, 7 figures, submitted to IEEE for possible publication

In this paper, we propose a data-driven algorithm to design rate- and length-flexible polar codes. While the algorithm is very general, a particularly appealing use case is the design of codes for automorphism ensemble decoding (AED), a promising decoding algorithm for ultra-reliable low-latency communications (URLLC) and massive machine-type communications (mMTC) applications. To this end, theoretic results on nesting of symmetric polar codes are derived, which give hope in finding a fully nested, rate-compatible sequence suitable for AED. Using the proposed algorithms, such a flexible polar code design for automorphism ensemble successive cancellation (SC) decoding is constructed, outperforming existing code designs for AED and also the 5G polar code under cyclic redundancy check (CRC)-aided successive cancellation list (SCL) decoding., Comment: 6 pages, 2 figures, submitted to IEEE for possible publication

We present a framework for modeling liver regrowth on the organ scale that is based on three components: (1) a multiscale perfusion model that combines synthetic vascular tree generation with a multi-compartment homogenized flow model, including a homogenization procedure to obtain effective parameters; (2) a poroelastic finite growth model that acts on all compartments and the synthetic vascular tree structure; (3) an evolution equation for the local volumetric growth factor, driven by the homogenized flow rate into the microcirculation as a measure of local hyperperfusion and well-suited for calibration with available data. We apply our modeling framework to a prototypical benchmark and a full-scale patient-specific liver, for which we assume a common surgical cut. Our simulation results demonstrate that our model represents hyperperfusion as a consequence of partial resection and accounts for its reduction towards a homeostatic perfusion state, exhibiting overall regrowth dynamics that correspond well with clinical observations. In addition, our results show that our model also captures local hypoperfusion in the vicinity of orphan vessels, a key requirement for the prediction of ischemia or the preoperative identification of suitable cut patterns.

The distributed nature of cellular networks is one of the main enablers for integrated sensing and communication (ISAC). For target positioning and tracking, making use of bistatic measurements is non-trivial due to their non-linear relationship with Cartesian coordinates. Most of the literature proposes geometric-based methods to determine the target's location by solving a well-defined set of equations stemming from the available measurements. The error covariance to be used for Bayesian tracking is then derived from local Taylor expansions. In our work we adaptively fuse any subset of bistatic measurements using a maximum likelihood (ML) framework, allowing to incorporate every possible combination of available measurements, i.e., transmitter angle, receiver angle and bistatic range. Moreover, our ML approach is intrinsically flexible, as it can be extended to fuse an arbitrary number of measurements by multistatic setups. Finally, we propose both a fixed and dynamic way to compute the covariance matrix for the position error to be fed to Bayesian tracking techniques, like a Kalman filter. Numerical evaluations with realistic cellular communications parameters at mmWave frequencies show that our proposal outperforms the considered baselines, achieving a location and velocity root mean square error of 0.25 m and 0.83 m/s, respectively., Comment: 6 pages, 6 figures, 3 tables

Distributed massive MIMO is considered a key advancement for improving the performance of next-generation wireless telecommunication systems. However, its efficacy in scenarios involving user mobility is limited due to channel aging. To address this challenge, channel prediction techniques are investigated to forecast future channel state information (CSI) based on previous estimates. We propose a new channel prediction method based on channel charting, a self-supervised learning technique that reconstructs a physically meaningful latent representation of the radio environment using similarity relationships between CSI samples. The concept of inertia within a channel chart allows for predictive radio resource management tasks through the latent space. We demonstrate that channel charting can be used to predict future CSI by exploiting spatial relationships between known estimates that are embedded in the channel chart. Our method is validated on a real-world distributed massive MIMO dataset, and compared to a Wiener predictor and the outdated CSI in terms of achievable sum rate.

A chain of quantum dots (QDs) coupled via semiconductor-superconductor hybrid regions can form an artificial Kitaev chain hosting Majorana bound states (MBSs). These zero-energy states are expected to be localised on the edges of the chain, at the outermost QDs. The remaining QDs, comprising the bulk, are predicted to host an excitation gap that protects the MBSs at the edges from local on-site perturbations. In this work, we demonstrate this connection between the bulk and edges in a minimal system, by engineering a three-site Kitaev chain in a two-dimensional electron gas. Through direct tunneling spectroscopy on each site, we show that the appearance of stable zero-bias conductance peaks at the outer QDs is correlated with the presence of an excitation gap in the middle QD. Furthermore, we show that this gap can be controlled by applying a superconducting phase difference between the two hybrid segments, and that the MBSs are robust only when the excitation gap is present. We find a close agreement between experiments and the original Kitaev model, thus confirming key predictions for MBSs in a three-site chain., Comment: 26 pages, 15 figures

Terahertz (THz) enables promising Tbps-level wireless transmission thanks to its prospect of ultra-huge spectrum utilization and narrow beamforming in the next sixth-generation (6G) communication system. Compared to millimeter wave (mmWave), THz intrinsically possesses compellingly severer molecular absorption and high pathloss serving confined coverage area. These defects should be well conquered under the employment of ultra-thin 3D beamforming with enormous deployed antennas with high beam gains. However, pencil-beams require substantially high overhead of time and power to train its optimal THz beamforming direction. We propose an energy efficient (EE) oriented THz beamforming (EETBF) scheme by separating the original complex problem into beamforming training (EETBF-BT) acquirement and learning-enabled training power assignment (EETBF-PA). The historical beam data is employed to update next beam selection policy. The performance results have demonstrated that the proposed EETBF outperforms the existing benchmarks leveraging full beam search, iterative search, linear/binary search as well as non-power-control based mechanism in open literature. Our proposed EETBF scheme results in the lowest training latency and power consumption, achieving the highest effective rate and EE performance., Comment: Accepted by IEEE TVT

Speech recordings are being more frequently used to detect and monitor disease, leading to privacy concerns. Beyond cryptography, protection of speech can be addressed by approaches, such as perturbation, disentanglement, and re-synthesis, that eliminate sensitive information of the speaker, leaving the information necessary for medical analysis purposes. In order for such privacy protective approaches to be developed, clear and systematic specifications of assumptions concerning medical settings and the needs of medical professionals are necessary. In this paper, we propose a Scenario of Use Scheme that incorporates an Attacker Model, which characterizes the adversary against whom the speaker's privacy must be defended, and a Protector Model, which specifies the defense. We discuss the connection of the scheme with previous work on speech privacy. Finally, we present a concrete example of a specified Scenario of Use and a set of experiments about protecting speaker data against gender inference attacks while maintaining utility for Parkinson's detection., Comment: Accepted and published at SPSC Symposium 2024 4th Symposium on Security and Privacy in Speech Communication. Interspeech 2024

The ability to quantify the directional flow of information is vital to understanding natural systems and designing engineered information-processing systems. A widely used measure to quantify this information flow is the transfer entropy. However, until now, this quantity could only be obtained in dynamical models using approximations that are typically uncontrolled. Here we introduce a computational algorithm called Transfer Entropy-Path Weight Sampling (TE-PWS), which makes it possible, for the first time, to quantify the transfer entropy and its variants exactly for any stochastic model, including those with multiple hidden variables, nonlinearity, transient conditions, and feedback. By leveraging techniques from polymer and path sampling, TE-PWS efficiently computes the transfer entropy as a Monte-Carlo average over signal trajectory space. We apply TE-PWS to linear and nonlinear systems to reveal how transfer entropy can overcome naive applications of the data processing inequality in the presence of feedback., Comment: 17 pages, 4 figures

For asynchronous transmission of short blocks, preambles for packet detection contribute a non-negligible overhead. To reduce the required preamble length, joint detection and decoding (JDD) techniques have been proposed that additionally utilize the payload part of the packet for detection. In this paper, we analyze two instances of JDD, namely hybrid preamble and energy detection (HyPED) and decoder-aided detection (DAD). While HyPED combines the preamble with energy detection for the payload, DAD also uses the output of a channel decoder. For these systems, we propose novel achievability and converse bounds for the rates over the binary-input additive white Gaussian noise (BI-AWGN) channel. Moreover, we derive a general bound on the required blocklength for JDD. Both the theoretical bound and the simulation of practical codebooks show that the rate of DAD quickly approaches that of synchronous transmission., Comment: 6 Pages, 3 Figures, submitted to IEEE for possible publication

The use of WiFi signals to sense the physical environment is gaining popularity, with some common applications being motion detection and transmitter localization. Standard-compliant WiFi provides a cost effective, easy and backward-compatible approach to Joint Communication and Sensing and enables a seamless transfer of results from experiments to practical applications. However, most WiFi sensing research is conducted on channel state information (CSI) data from current-generation devices, which are usually not meant for sensing applications and thus lack sufficient spatial diversity or phase synchronization. With ESPARGOS, we previously developed a phase-coherent, real-time capable many-antenna WiFi channel sounder specifically for wireless sensing. We describe how we use ESPARGOS to capture large CSI datasets that we make publicly available. The datasets are extensively documented and labeled, for example with information from reference positioning systems, enabling data-driven and machine learning-based research.

Semiconductor-superconductor hybrid materials are used as a platform to realise Andreev bound states, which hold great promise for quantum applications. These states require transparent interfaces between the semiconductor and superconductor, which are typically realised by in-situ deposition of an Al superconducting layer. Here we present a hybrid material based on an InAs two-dimensional electron gas (2DEG) combined with in-situ deposited Nb and NbTi superconductors, which offer a larger operating range in temperature and magnetic field due to their larger superconducting gap. We overcome the inherent difficulty associated with the formation of an amorphous interface between III-V semiconductors and Nb-based superconductors by introducing a 7 nm Al interlayer. The Al interlayer provides an epitaxial connection between an in-situ magnetron sputtered Nb or NbTi thin film and a shallow InAs 2DEG. This metal-to-metal epitaxy is achieved by optimization of the material stack and results in an induced superconducting gap of approximately 1 meV, determined from transport measurements of superconductor-semiconductor Josephson junctions. This induced gap is approximately five times larger than the values reported for Al-based hybrid materials and indicates the formation of highly-transparent interfaces that are required in high-quality hybrid material platforms.

As artificial intelligence (AI) technology advances, ensuring the robustness and safety of AI-driven systems has become paramount. However, varying perceptions of robustness among AI developers create misaligned evaluation metrics, complicating the assessment and certification of safety-critical and complex AI systems such as autonomous driving (AD) agents. To address this challenge, we introduce Simulation-Based Robustness Assessment Framework (S-RAF) for autonomous driving. S-RAF leverages the CARLA Driving simulator to rigorously assess AD agents across diverse conditions, including faulty sensors, environmental changes, and complex traffic situations. By quantifying robustness and its relationship with other safety-critical factors, such as carbon emissions, S-RAF aids developers and stakeholders in building safe and responsible driving agents, and streamlining safety certification processes. Furthermore, S-RAF offers significant advantages, such as reduced testing costs, and the ability to explore edge cases that may be unsafe to test in the real world. The code for this framework is available here: https://github.com/cognitive-robots/rai-leaderboard

MIRC-X and MYSTIC are six-telescope near-infrared beam (1.08-2.38 ${\mu}$m) combiners at the CHARA Array on Mt Wilson CA, USA. Ever since the commissioning of MIRC-X (J and H bands) in 2018 and MYSTIC (K bands) in 2021, they have been the most popular and over-subscribed instruments at the array. Observers have been able to image stellar objects with sensitivity down to 8.1 mag in H and 7.8 mag in K-band under the very best conditions. In 2022 MYSTIC was upgraded with a new ABCD mode using the VLTI/GRAVITY 4-beam integrated optics chip, with the goal of improving the sensitivity and calibration. The ABCD mode has been used to observe more than 20 T Tauri stars; however, the data pipeline is still being developed. Alongside software upgrades, we detail planned upgrades to both instruments in this paper. The main upgrades are: 1) Adding a motorized filter wheel to MIRC-X along with new high spectral resolution modes 2) Updating MIRC-X optics to allow for simultaneous 6T J+H observations 3) Removing the warm window between the spectrograph and the warm optics in MYSTIC 4) Adding a 6T ABCD mode to MIRC-X in collaboration with CHARA/SPICA 5) Updating the MIRC-X CRED-ONE camera funded by Prof. Kraus from U. Exeter 6) Carrying out science verification of the MIRC-X polarization mode 7) Developing new software for ABCD-mode data reduction and more efficient calibration routines. We expect these upgrades to not only improve the observing experience, but also increase the sensitivity by 0.4 mag in J+H-bands, and 1 mag in K-band., Comment: 11 pages, 9 figures, Submitted to SPIE in Yokohama 2024

Massive evolved stars such as red supergiants and hypergiants are potential progenitors of Type II supernovae, and they are known for ejecting substantial amounts of matter, up to half their initial mass, during their final evolutionary phases. The rate and mechanism of this mass loss play a crucial role in determining their ultimate fate and the likelihood of their progression to supernovae. However, the exact mechanisms driving this mass ejection have long been a subject of research. Recent observations, such as the Great Dimming of Betelgeuse, have suggested that the activity of large convective cells, combined with pulsation, could be a plausible explanation for such mass loss events. In this context, we conducted interferometric observations of the famous yellow hypergiant, $\rho$ Cassiopeiae using the CHARA Array in H and K-band wavelengths. $\rho$ Cas is well known for its recurrent eruptions, characterized by periods of visual dimming ($\sim$1.5-2 mag) followed by recovery. From our observations, we derived the diameter of the limb-darkened disk and found that this star has a radius of $1.04\pm0.01$ milliarcseconds (mas), or $564 - 700 R_\odot$. We performed image reconstructions with three different image reconstruction software packages, and they unveiled the presence of giant hot and cold spots on the stellar surface. We interpret these prominent hot spots as giant convection cells, suggesting a possible connection to mass ejections from the star's envelope. Furthermore, we detected spectral CO emission lines in the K-band ($\lambda=2.31-2.38 \mu$m), and the image reconstructions in these spectral lines revealed an extended circumstellar envelope with a radius of $1.45\pm0.10$ mas., Comment: 21 pages, 13 figures, 4 tables, Accepted by ApJ

Over the past few decades, numerous $N$-phase incompressible diffuse-interface flow models with non-matching densities have been proposed. Despite aiming to describe the same physics, these models are generally distinct, and an overarching modeling framework is absent. This paper provides a unified framework for $N$-phase incompressible Navier-Stokes Cahn-Hilliard Allen-Cahn mixture models with a single momentum equation. The framework naturally emerges from continuum mixture theory, exhibits an energy-dissipative structure, and is invariant to the choice of fundamental variables. This opens the door to exploring connections between existing $N$-phase models and facilitates the computation of $N$-phase flow models rooted in continuum mixture theory., Comment: Preprint, 45 pages

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) provides a promising way to expand coverage in wireless communications. However, limitation of single STAR-RIS inspire us to integrate the concept of multi-hop transmissions, as focused on RIS in existing research. Therefore, we propose the novel architecture of multi-hop STAR-RISs to achieve a wider range of full-plane service coverage. In this paper, we intend to solve active beamforming of the base station and passive beamforming of STAR-RISs, aiming for maximizing the energy efficiency constrained by hardware limitation of STAR-RISs. Furthermore, we investigate the impact of the on-off state of STAR-RIS elements on energy efficiency. To tackle the complex problem, a Multi-Agent Global and locAl deep Reinforcement learning (MAGAR) algorithm is designed. The global agent elevates the collaboration among local agents, which focus on individual learning. In numerical results, we observe the significant improvement of MAGAR compared to the other benchmarks, including Q-learning, multi-agent deep Q network (DQN) with golbal reward, and multi-agent DQN with local rewards. Moreover, the proposed architecture of multi-hop STAR-RISs achieves the highest energy efficiency compared to mode switching based STAR-RISs, conventional RISs and deployment without RISs or STAR-RISs., Comment: Accepted by Proc. IEEE VTC-fall

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

The ability of Language Models (LMs) to understand natural language makes them a powerful tool for parsing human instructions into task plans for autonomous robots. Unlike traditional planning methods that rely on domain-specific knowledge and handcrafted rules, LMs generalize from diverse data and adapt to various tasks with minimal tuning, acting as a compressed knowledge base. However, LMs in their standard form face challenges with long-horizon tasks, particularly in partially observable multi-agent settings. We propose an LM-based Long-Horizon Planner for Multi-Agent Robotics (LLaMAR), a cognitive architecture for planning that achieves state-of-the-art results in long-horizon tasks within partially observable environments. LLaMAR employs a plan-act-correct-verify framework, allowing self-correction from action execution feedback without relying on oracles or simulators. Additionally, we present MAP-THOR, a comprehensive test suite encompassing household tasks of varying complexity within the AI2-THOR environment. Experiments show that LLaMAR achieves a 30% higher success rate than other state-of-the-art LM-based multi-agent planners in MAP-THOR and Search \& Rescue tasks. Code can be found at https://github.com/nsidn98/LLaMAR, Comment: 27 pages, 4 figures, 5 tables

Quantum dot-superconductor arrays have emerged as a new and promising material platform for realizing topological Kitaev chains. So far, experiments have implemented a two-site chain with limited protection. Here we propose an experimentally feasible protocol for scaling up the chain in order to enhance the protection of the Majorana zero modes. To this end, we make use of the fact that the relative sign of normal and superconducting hoppings mediated by an Andreev bound state can be changed by electrostatic gates. In this way, our method only relies on the use of individual electrostatic gates on hybrid regions, quantum dots, and tunnel barriers, respectively, without the need for individual magnetic flux control, greatly simplifying the device design. Our work provides guidance for realizing a topologically protected Kitaev chain, which is the building block of error-resilient topological quantum computation., Comment: 9 pages, 6 figures

The newly installed Silmaril beam combiner at the CHARA array is designed to observe previously inaccessible faint targets, including Active Galactic Nuclei and T-Tauri Young Stellar Objects. Silmaril leverages cutting-edge optical design, low readout noise, and a high-speed C-RED1 camera to realize its sensitivity objectives. In this presentation, we offer a comprehensive overview of the instrument's software, which manages critical functions, including camera data acquisition, fringe tracking, automatic instrument alignment, and observing interfaces, all aimed at optimizing on-sky data collection. Additionally, we offer an outline of the data reduction pipeline, responsible for converting raw instrument data products into the final OIFITS used by the standard interferometry modeling software. The purpose of this paper is to provide a solid reference for studies based on Silmaril data., Comment: Presented at 2024 SPIE Astronomical Telescopes + Instrumentation conference

The proliferation of Internet of Things (IoT) embedded devices is expected to reach 30 billion by 2030, creating a dynamic landscape where diverse devices must coexist. This presents challenges due to the rapid expansion of different architectures and platforms. Addressing these challenges requires a unifi ed solution capable of accommodating various devices while offering a broad range of services to connect them to the Internet effectively. This white paper introduces CROSSCON, a three-year Research and Innovation Action funded under Horizon Europe. CROSSCON aims to tackle current IoT challenges by developing a new open, modular, and universally compatible IoT security stack. This stack is designed to be highly portable and vendor-independent, enabling its deployment across different devices with heterogeneous embedded hardware architectures, including ARM and RISC-V. The CROSSCON consortium consists of 11 partners spanning 8 European countries. This consortium includes 4 academic institutions, 1 major industrial partner, and 5 small to medium-sized enterprises (SMEs).