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6G communication systems promise to deliver sensing capabilities by utilizing the orthogonal frequency division multiplexing (OFDM) communication signal for sensing. However, the cyclic prefix inherent in OFDM systems limits the sensing range, necessitating compensation techniques to detect small, distant targets like drones. In this paper, we show that state-of-the-art coherent compensation methods fail in scenarios involving multiple targets, resulting in an increased noise floor in the radar image. Our contributions include a novel multi target coherent compensation algorithm and a generalized signal-to-interference-and-noise ratio for multiple targets to evaluate the performance. Our algorithm achieves the same detection performance at long distances requiring only 3.6% of the radio resources compared to classical OFDM radar processing. This enables resource efficient sensing at long distances in multi target scenarios with legacy communications-only networks., Comment: Accepted at 14th International ITG Conference on Systems, Communications and Coding (SCC), Karlsruhe, Germany

We show that the extended Khovanov algebra $K^m_n$ is an $(|n-m|-1)$-faithful cover of the Khovanov arc algebra $H^m_n$.

We provide an ${\rm Ext}$-quiver and relations presentation of the Khovanov arc algebras and prove a precise analogue of the Kleshchev--Martin conjecture in this setting.

We investigate a monostatic orthogonal frequency-division multiplexing (OFDM)-based joint communication and sensing (JCAS) system for object tracking. Our setup consists of a transmitter and receiver equipped with an antenna array for fully digital beamforming. The native resolution of all radar-like sensing, including OFDM radar sensing, is limited by the observation time and bandwidth. In this work, we improve the parameter estimates through interpolation methods and tracking algorithms. We verify our method by comparing the root mean squared error (RMSE) of the estimated range, velocity and angle and by comparing the mean Euclidean distance between the estimated and true position. We demonstrate how both a Kalman filter for tracking, and interpolation methods using zero-padding and the chirp Z-transform (CZT) improve the estimation error. We discuss the computational complexity of the different methods. We propose the KalmanCZT approach that combines tracking via Kalman filtering and interpolation via the CZT, resulting in a solution with flexible resolution that significantly improves the range RMSE., Comment: Presented at SCC2025

We establish the spacetime Penrose inequality in spherical symmetry in spacetime dimensions $n+1\geq3$ with charge and cosmological constant from the initial data perspective. We also show that this result extends to the Gauss-Bonnet theory of gravity., Comment: 16 pages

4H-SiC low gain avalanche detectors (LGADs) have been fabricated and characterized. The devices employ a circular mesa design with low-resistivity contacts and an SiO$_2$ passivation layer. The I-V and C-V characteristics of the 4H-SiC LGADs are compared with complementary 4H-SiC PiN diodes to confirm a high breakdown voltage and low leakage current. Both LGADs and PiN diodes were irradiated with $\alpha$ particles from a $^{210}_{84}\rm{Po}$ source. The charge collected by each device was compared, and it was observed that low-gain charge carrier multiplication is achieved in the 4H-SiC LGAD.

Ultra-Wideband (UWB) technology re-emerges as a groundbreaking ranging technology with its precise micro-location capabilities and robustness. This paper highlights the security dimensions of UWB technology, focusing in particular on the intricacies of device fingerprinting for authentication, examined through the lens of state-of-the-art deep learning techniques. Furthermore, we explore various potential enhancements to the UWB standard that could realize a sovereign UWB data network. We argue that UWB data communication holds significant potential in healthcare and ultra-secure environments, where the use of the common unlicensed 2.4~GHz band-centric wireless technology is limited or prohibited. A sovereign UWB network could serve as an alternative, providing secure localization and short-range data communication in such environments., Comment: NetAISys Workshop at ACM Mobisys 2024

Nonclassical states of bosonic modes are important resources for quantum-enhanced technologies. Yet, quantifying nonclassicality of these states, in particular mixed states, can be a challenge. Here we present results of quantifying the nonclassicality of a bosonic mode in a mixed Fock state via the operational resource theory (ORT) measure [W. Ge, K. Jacobs, S. Asiri, M. Foss-Feig, and M. S. Zubairy, Phys. Rev. Res. 2, 023400 (2020)], which relates nonclassicality to metrological advantage. Generally speaking, evaluating a resource-theoretic measure for mixed states is challenging, since it involves finding a convex roof. However, we show that our problem can be reduced to a linear programming problem. By analyzing the results of numerical optimization, we are able to extract analytical results for the case where three or four neighboring Fock states have nonzero population. Interestingly, we find that such a mode can be in distinct phases, depending on the populations. Lastly, we demonstrate how our method is generalizable to density matrices of higher ranks. Our findings suggest a viable method for evaluating nonclassicality of arbitrary mixed bosonic states and potentially for solving other convex roof optimization problems., Comment: 13 pages, 5 figures

Cuspidal systems parameterize KLR algebra representations via root partitions $\pi$, where simple modules $L(\pi)$ arise as heads of proper standard modules. Working in affine type A with an arbitrary convex preorder, we construct explicit skew diagrams $\zeta(\pi)$ such that the skew Specht module $S^{\zeta(\pi)}$ has simple head $L(\pi)$ and a filtration by proper standard modules. This result arises from an in-depth study of the combinatorial interplay between cuspidal systems and RoCK cyclotomic KLR algebras., Comment: v2 adds a new theorem, appearing as Theorem F in the introduction. Other minor edits

Integrated sensing and communication (ISAC) has been defined as one goal for 6G mobile communication systems. In this context, this article introduces a bistatic ISAC system based on orthogonal frequency-division multiplexing (OFDM). While the bistatic architecture brings advantages such as not demanding full duplex operation with respect to the monostatic one, the need for synchronizing transmitter and receiver is imposed. In this context, this article introuces a bistatic ISAC signal processing framework where an incoming OFDM-based ISAC signal undergoes over-the-air synchronization based on preamble symbols and pilots. Afterwards, bistatic radar processing is performed using either only pilot subcarriers or the full OFDM frame. The latter approach requires estimation of the originally transmitted frame based on communication processing and therefore error-free communication, which can be achieved via appropriate channel coding. The performance and limitations of the introduced system based on both aforementioned approaches are assessed via an analysis of the impact of residual synchronization mismatches and data decoding failures on both communication and radar performances. Finally, the performed analyses are validated by proof-of-concept measurement results.

We evaluate the influence of multi-snapshot sensing and varying signal-to-noise ratio (SNR) on the overall performance of neural network (NN)-based joint communication and sensing (JCAS) systems. To enhance the training behavior, we decouple the loss functions from the respective SNR values and the number of sensing snapshots, using bounds of the sensing performance. Pre-processing is done through conventional sensing signal processing steps on the inputs to the sensing NN. The proposed method outperforms classical algorithms, such as a Neyman-Pearson-based power detector for object detection and ESPRIT for angle of arrival (AoA) estimation for quadrature amplitude modulation (QAM) at low SNRs., Comment: accepted to WSA2024

Aerosols influence weather and climate by interacting with radiation through absorption and scattering. These effects heavily rely on the optical properties of aerosols, which are mainly governed by attributes such as morphology, size distribution, and chemical composition. These attributes undergo continuous changes due to chemical reactions and aerosol micro-physics, resulting in significant spatio-temporal variations. Most atmospheric models struggle to incorporate this variability because they use pre-calculated tables to handle aerosol optics. This offline approach often leads to substantial errors in estimating the radiative impacts of aerosols alongwith posing significant computational burdens. To address this challenge, we introduce a novel and computationally efficient machine learning ap proach called MieAI. It allows for online calculation of the optical properties of internally mixed aerosols with a log-normal size distribution. Importantly, MieAI fully incorporates the variability in aerosol chemistry and microphysics. Our evaluation of MieAI against traditional Mie calculations, using number concentrations from ICOsahedral Nonhydrostatic model with Aerosol and Reactive Trace gases (ICON-ART) simulations, demonstrates that MieAI exhibits excellent predictive accuracy for aerosol optical properties. MieAI achieves this with errors well within 10%, and it operates more than 1000 times faster than the benchmark approach of Mie calculations. Due to its generalized nature, the MieAI approach can be implemented in any chemistry transport model which represents aerosol size distribution in the form of log-normally distributed internally mixed modes. This advancement has the potential to replace frequently employed lookup tables and play a substantial role in the ongoing attempts to reduce uncertainties in estimating aerosol radiative forcing., Comment: 26 pages, 7 main and 8 appendix figures, 3 main and 3 appendix tables

During a binary black hole merger, multiple intermediary marginally outer trapped tubes connect the initial pair of apparent horizons with the final (single) apparent horizon. The marginally outer trapped surfaces (MOTSs) that foliate these tubes can have complicated geometries as well as non-spherical topologies. In particular, toroidal MOTSs form inside both of the original black holes during the early stages of a head-on merger that starts from time-symmetric initial data [1]. We show that toroidal MOTSs also form in the maximal analytic extension of the Schwarzschild spacetime as Kruskal time advances from the $T=0$ moment of time symmetry. As for the merger simulations, they cross the Einstein-Rosen bridge and are tightly sandwiched between the apparent horizons in the two asymptotic regions at early times. This strongly suggests that their formation is a consequence of the initial conditions rather than merger physics. Finally, we consider MOTSs of spherical topology in the Kruskal-Szekeres slicing and study their properties. All of these are contained within the apparent horizon but some do not enclose the wormhole., Comment: 14 pages, 16 figures

This article introduces a bistatic joint radar-communication (RadCom) system based on orthogonal frequency-division multiplexing (OFDM). In this context, the adopted OFDM frame structure is described and system model encompassing time, frequency, and sampling synchronization mismatches between the transmitter and receiver of the bistatic system is outlined. Next, the signal processing approaches for synchronization and communication are discussed, and radar sensing processing approaches using either only pilots or a reconstructed OFDM frame based on the estimated receive communication data are presented. Finally, proof-of-concept measurement results are presented to validate the investigated system and a trade-off between frame size and the performance of the aforementioned processing steps is observed., Comment: Accepted for presentation at the focused session "Joint Communication and Radar Sensing - a step towards 6G'' of the EuMW 2023

Let $\mathbb{k}$ be a characteristic zero domain. For a locally unital $\mathbb{k}$-superalgebra $A$ with distinguished idempotents $I$and even subalgebra $a \subseteq A_{\bar 0}$, we define and study an associated diagrammatic monoidal $\mathbb{k}$-linear supercategory $\mathbf{Web}^{A,a}_I$. This supercategory yields a diagrammatic description of the generalized Schur algebras $T^A_a(n,d)$. We also show there is an asymptotically faithful functor from $\mathbf{Web}^{A,a}_I$ to the monoidal supercategory of $\mathfrak{gl}_n(A)$-modules generated by symmetric powers of the natural module. When this functor is full, the single diagrammatic supercategory $\mathbf{Web}^{A,a}_I$ provides a combinatorial description of this module category for all $n \geq 1$. We also use these results to establish Howe dualities between $\mathfrak{gl}_{m}(A)$ and $\mathfrak{gl}_{n}(A)$ when $A$ is semisimple., Comment: 64 pages. Numerous diagrams, best viewed in color

We investigate the potential of autoencoders (AEs) for building a joint communication and sensing (JCAS) system that enables communication with one user while detecting multiple radar targets and estimating their positions. Foremost, we develop a suitable encoding scheme for the training of the AE and for targeting a fixed false alarm rate of the target detection during training. We compare this encoding with the classification approach using one-hot encoding for radar target detection. Furthermore, we propose a new training method that complies with possible ambiguities in the target locations. We consider different options for training the detection of multiple targets. We can show that our proposed approach based on permuting and sorting can enhance the angle estimation performance so that single snapshot estimations with a low standard deviation become possible. We outperform an ESPRIT benchmark for small numbers of measurement samples., Comment: 6 pages, 4 figures, submitted to WSA & SCC 2023, code available at https://github.com/frozenhairdryer/JCAS_multitarg

The recently developed MOTSodesic method for locating marginally outer trapped surfaces was effectively restricted to non-rotating spacetimes. In this paper we extend the method to (multi-)axisymmetric time slices of (multi-)axisymmetric spacetimes of any dimension. We then apply this method to study marginally outer trapped surfaces (MOTSs) in the BTZ, Kerr and Myers-Perry black holes. While there are many similarities between the MOTSs observed in these spacetimes and those seen in Schwarzschild and Reissner-Nordstr\"om, details of the more complicated geometries also introduce some new, previously unseen, behaviours., Comment: 53 pages, 17 figures, V2: minor typos corrected, version submitted to journal

Many service systems rely on verifiable identity-related information of their users. Manipulation and unwanted exposure of this privacy-relevant information, however, must at the same time be prevented and avoided. Peer-to-peer blockchain-based decentralization with a smart contract-based execution model and verifiable off-chain computations leveraging zero-knowledge proofs promise to provide the basis for next-generation, non-disclosing credential management solutions. In this paper, we propose a novel credential on-chaining system that ensures blockchain-based transparency while preserving pseudonymity. We present a general model compliant to the W3C verifiable credential recommendation and demonstrate how it can be applied to solve existing problems that require computational identity-related attribute verification. Our zkSNARKs-based reference implementation and evaluation show that, compared to related approaches based on, e.g., CL-signatures, our approach provides significant performance advantages and more flexible proof mechanisms, underpinning our vision of increasingly decentralized, transparent, and trustworthy service systems.

Organic semiconductor crystals stand out as an efficient, cheap and diverse platform for realising optoelectronic applications. The optical response of these crystals is governed by a rich tapestry of exciton physics. So far, little is known on the phonon-driven singlet exciton dynamics in this class of materials. In this joint theory-experiment work, we combine the fabrication of a high-quality oligoacene semiconductor crystal and characterization via photoluminescence measurements with a sophisticated approach to the microscopic modeling in these crystals. This allows us to investigate singlet exciton optics and dynamics. We predict phonon-bottleneck effects in pentacene crystals, where we find dark excitons acting as crucial phonon-mediated relaxation scattering channels. While the efficient singlet fission in pentacene crystals hampers the experimental observation of this bottleneck effect, we reveal both in theory and experiment a distinct polarisation- and temperature-dependence in absorption and photoluminescence spectra of tetracene crystals, including microscopic origin of exciton linewidths, the activation of the higher Davydov states at large temperatures, and polarisation-dependent quenching of specific exciton resonances. Our joint theory-experiment study represents a significant advance in microscopic understanding of singlet exciton optics and dynamics in oligoacene crystals.

Tracking detectors are of vital importance for collider-based high energy physics (HEP) experiments. The primary purpose of tracking detectors is the precise reconstruction of charged particle trajectories and the reconstruction of secondary vertices. The performance requirements from the community posed by the future collider experiments require an evolution of tracking systems, necessitating the development of new techniques, materials and technologies in order to fully exploit their physics potential. In this article we summarize the discussions and conclusions of the 2022 Snowmass Instrumentation Frontier subgroup on Solid State and Tracking Detectors (Snowmass IF03)., Comment: for the Snowmass Instrumentation Frontier Solid State Detector and Tracking community

Blockchain-based systems have gained immense popularity as enablers of independent asset transfers and smart contract functionality. They have also, since as early as the first Bitcoin blocks, been used for storing arbitrary contents such as texts and images. On-chain data storage functionality is useful for a variety of legitimate use cases. It does, however, also pose a systematic risk. If abused, for example by posting illegal contents on a public blockchain, data storage functionality can lead to legal consequences for operators and users that need to store and distribute the blockchain, thereby threatening the operational availability of entire blockchain ecosystems. In this paper, we develop and apply a cloud-based approach for quickly discovering and classifying content on public blockchains. Our method can be adapted to different blockchain systems and offers insights into content-related usage patterns and potential cases of abuse. We apply our method on the two most prominent public blockchain systems - Bitcoin and Ethereum - and discuss our results. To the best of our knowledge, the presented study is the first to systematically analyze non-financial content stored on the Ethereum blockchain and the first to present a side-by-side comparison between different blockchains in terms of the quality and quantity of stored data., Comment: Accepted at 1st International Cryptoasset Analytics Workshop (CAAW), ACM TheWebConf 2022

4H-Silicon Carbide, when considered as a material for the fabrication of Low Gain Avalanche Detectors for particle timing and position measurement, offers potential advantages over Silicon. We discuss an ongoing study of this material aimed at the fabrication and test of prototype fast timing sensors. This work is well aligned with technical directions identified in the recent Department of Energy study, Basic Research Needs for High Energy Physics Detector Research and Development., Comment: Submitted to Snowmass 2021

We investigate the configuration space $\mathcal{S}_{G,b,\ell}$ associated with the movement of a robotic arm of length $\ell$ on a grid over an underlying graph $G$, anchored at a vertex $b \in G$. We study an associated PIP (poset with inconsistent pairs) $\text{IP}_{G,b,\ell}$ consisting of indexed paths on $G$. This PIP acts as a combinatorial model for the robotic arm, and we use $\text{IP}_{G,b,\ell}$ to show that the space $\mathcal{S}_{G,b,\ell}$ is a CAT(0) cubical complex, generalizing work of Ardila, Bastidas, Ceballos, and Guo. This establishes that geodesics exist within the configuration space, and yields explicit algorithms for moving the robotic arm between different configurations in an optimal fashion. We also give a tight bound on the diameter of the robotic arm transition graph (the maximal number of moves necessary to change from one configuration to another) and compute this diameter for a large family of underlying graphs $G$.

The Glashow resonance describes the resonant formation of a $W^-$ boson during the interaction of a high-energy electron antineutrino with an electron, peaking at an antineutrino energy of 6.3 petaelectronvolts (PeV) in the rest frame of the electron. Whereas this energy scale is out of reach for currently operating and future planned particle accelerators, natural astrophysical phenomena are expected to produce antineutrinos with energies beyond the PeV scale. Here we report the detection by the IceCube neutrino observatory of a cascade of high-energy particles (a particle shower) consistent with being created at the Glashow resonance. A shower with an energy of $6.05 \pm 0.72$ PeV (determined from Cherenkov radiation in the Antarctic Ice Sheet) was measured. Features consistent with the production of secondary muons in the particle shower indicate the hadronic decay of a resonant $W^-$ boson, confirm that the source is astrophysical and provide improved directional localization. The evidence of the Glashow resonance suggests the presence of electron antineutrinos in the astrophysical flux, while also providing further validation of the standard model of particle physics. Its unique signature indicates a method of distinguishing neutrinos from antineutrinos, thus providing a way to identify astronomical accelerators that produce neutrinos via hadronuclear or photohadronic interactions, with or without strong magnetic fields. As such, knowledge of both the flavour (that is, electron, muon or tau neutrinos) and charge (neutrino or antineutrino) will facilitate the advancement of neutrino astronomy., Comment: This work has been published in Nature and is available at https://www.nature.com/articles/s41586-021-03256-1

We establish classical and categorical Howe dualities between the Lie superalgebras $\mathfrak{p}(m)$ and $\mathfrak{p}(n)$, for $m,n \geq 1$. We also describe a presentation via generators and relations as well as a Kostant $\mathbb{Z}$-form for the universal enveloping superalgebra $U(\mathfrak{p}(m))$.