High-order harmonic generation (HHG) in solids - the frequency up-conversion of an optical signal - is governed by symmetries. At terahertz (THz) frequencies, HHG is a key technology to access high frequency spectral windows that are usually difficult to cover using conventional solid state laser technologies. This effect has been recently exploited in graphene where HHG has been demonstrated, albeit only at odd multiples of the driving frequency owing to its inherent centro-symmetry. In topological insulators (TIs), the combination of spin-orbit interaction and time-reversal symmetry create an insulating bulk state with an inverted band order, inseparably connected with conducting surface states. TIs have been predicted to support unconventional high harmonic generation from the bulk and topological surface, which are usually difficult to be distinguished. However, no experimental results have been provided, so far. Here, we exploit the strong optical field amplification provided by an array of single or double split ring resonators, with embedded Bi2Se3 or (InxBi(1-x))2Se3/ Bi2Se3 van der Waals heterostructures, to achieve up-conversion in the 6.4 (even) - 9.7 (odd) THz frequency range. This results from bulk centro-symmetry (odd states) and symmetry breaking in the topological surface states (odd and even).

Functional logic languages are a high-level approach to programming by combining the most important declarative features. They abstract from small-step operational details so that programmers can concentrate on the logical aspects of an application. This is supported by appropriate evaluation strategies. Demand-driven evaluation from functional programming is amalgamated with non-determinism from logic programming so that solutions or values are computed whenever they exist. This frees the programmer from considering the influence of an operational strategy on the success of a computation, but it is a challenge to the language implementer. A non-deterministic demand-driven strategy might duplicate unevaluated choices of an expression, which could duplicate the computational effort. In recent implementations, this problem has been tackled by adding a kind of memoization of non-deterministic choices to the expression under evaluation. Since this has been implemented in imperative target languages, it was unclear whether this could also be supported in a functional programming environment like Haskell. This paper presents a solution to this challenge by transforming functional logic programs into a monadic representation. Although this transformation is not new, we present an implementation of the monadic interface which supports memoization in non-deterministic branches. Additionally, we include more advanced features of functional logic languages, namely functional patterns and encapsulated search, in our approach. By optimizing our implementation for purely functional computations with both a static and dynamic approach, we are able to achieve a promising performance that outperforms current compilers for Curry.

In Mixed-Criticality (MC) systems, although the high Worst-Case Execution Time (WCET) serves as a conservative upper bound representing the task's maximum execution time under all conditions, obtaining a low WCET is essential for representing realistic executions and improving utilization and Quality-of-Service (QoS). Nevertheless, determining appropriate low WCET(s) for lower-criticality (LO) modes poses a significant challenge. Opting for a very low value of this WCET enhances processor utilization by scheduling more tasks in LO mode. Conversely, employing a larger WCET ensures fewer mode switches, thereby enhancing QoS, albeit at the cost of processor utilization. This paper proposes an analytical approach, AnTi-MiCS, to determine the appropriate low WCET through design-time analysis of task executions. In some cases, a single low WCET may not be adequate to capture large variations in the execution time distribution, for example, in scenarios like bimodal distributions. Therefore, we further propose a scalable approach, MulTi-MiCS, to compute multiple appropriate low WCETs. This approach exploits the temporal correlation between subsequent inputs presented to the application. Experimental results, conducted on a real platform with embedded real-time benchmarks, demonstrate the efficacy of our proposed scheme, in which QoS is improved by 30.27% on average while reducing utilization waste by 35.89%, compared to existing approaches. Besides, MulTi-MiCS improves QoS by 6.41% compared to AnTi-MiCS while reducing utilization waste by 8.23%.

We report the formation of large-scale steady-state whirlpools in a GaAs-based two-dimensional electron liquid and demonstrate them by straightforward transport measurements. A whirlpool forming inside a circular cavity adjoining a wide conducting channel appears as a negative four-terminal resistance over a broad range of temperatures and cavity sizes. The effect scales with the Gurzhi length, in quantitative accord with the hydrodynamic analogy. Obtained results firmly establish this analogy and probe the limits of its applicability.

The third law of thermodynamics forbids cooling a physical system to absolute zero in a finite number of operational steps. Although this unattainability principle has been quantified for specific state-to-state transitions, a universal, dynamics-independent bound for implementing a state-agnostic reset map remains elusive. In this work, we unveil the fundamental limits of physical map implementation by deriving a trade-off relation based on geometric complexity. By analyzing continuous paths of maps on a geometric manifold, we prove that the geometric complexity of any classical stochastic map or quantum channel is bounded from below by its execution error. As a consequence, we show that achieving zero error in a state-reset operation requires a divergent geometric complexity -- a unified measure that naturally incorporates disparate physical resources, including infinite time, energetic cost, or control bandwidth. This unattainability principle holds universally across both classical and quantum regimes, establishing a strict geometric limit on the physical realization of reset operations in thermodynamic control and quantum computation.

We report a comprehensive investigation of the excitation spectrum of ErFeO$_3$ orthoferrite by means of time-of-flight neutron spectroscopy. The spectrum consists of two distinct components: strongly dispersive spin wave excitations of the Fe$^{3+}$ sublattice spanning $\approx$~9 - 65 meV, and crystal electric field (CEF) excitations of Er$^{3+}$ ions below 36 meV. The observed spin wave dispersions and spectral weight are well captured within linear spin wave theory, enabling extraction of the key Fe-Fe exchange parameters. Low-energy incident neutrons with their enhanced energy resolution, further revealed the dispersive character and splitting of Kramers-degenerate CEF levels. We show that the dispersion is caused by the exchange coupling between Er$^{3+}$ ions, while the degeneracy is lifted by interactions between the Er$^{3+}$ and Fe$^{3+}$ sublattices. We further explore the influence of dipolar and antisymmetric exchange interactions with the focus on the magnetic ground state of ErFeO$_3$, with particular attention to the low-temperature spin arrangement. Taken together, our results provide a detailed account of the spin dynamics in ErFeO$_3$ and reveal a hierarchy of interactions scales characteristic for orthoferrites.

A pygmy shrew (\textit{Suncus etruscus}, ${\approx}2$\,g) sustains a resting heart rate near $1{,}000$\,beats\,min$^{-1}$ and dies within two years; an African elephant (${\approx}4{,}000$\,kg) beats at $28$\,beats\,min$^{-1}$ and lives seven decades. Their chronological lifespans differ by a factor of 35, yet each accumulates close to $10^9$ cardiac cycles before death -- a near-constancy first noted by Rubner~(1908) and quantified by Lindstedt and Calder~(1981)~\cite{lindstedt1981}, but never subjected to multi-clade statistical testing, phylogenetic correction, or explicit falsifiability criteria with a large modern dataset. We address this gap with a curated 230-species vertebrate dataset spanning non-primate placentals ($n=43$), primates ($n=18$), marsupials and monotremes ($n=19$), duty-cycle-corrected bats ($n=31$), dive-corrected cetaceans ($n=12$), birds ($n=78$), and Arrhenius-corrected ectotherms ($n=26$), and subject the log-invariant $\ell = \log_{10}(N^{\!\star})$ -- where $N^{\!\star} = f_H\,L\times 525{,}960$ cardiac cycles -- to four independent tests.

NetSatBench is a distributed emulation platform for evaluating communication protocols and application workloads over large-scale LEO satellite systems. Satellites, gateways, and user terminals are implemented as Linux containers distributed across a cluster of bare-metal or virtual machines, while emulated links are realized through a Layer-2 VXLAN overlay. The system state is maintained in an Etcd key-value store and updated through epoch files, which propagate link and task changes to local control agents running inside the emulated nodes. In contrast to library-oriented tools that require users to write control programs, NetSatBench adopts a higher-level declarative workflow based on JSON "scenario files" and a command-line interface. The platform decouples physical-layer and routing modeling from the emulator core through external plug-ins, while providing built-in support for IPv4 and IPv6 routing, including IS-IS and ideal time-varying routing. Rather than focusing on emulator micro-performance alone, we illustrate what NetSatBench enables through an SRv6-based LEO architecture in which control procedures manage data tunnels between users and gateways under different handover policies. This case study shows how NetSatBench can support protocol-level experimentation under time-varying LEO dynamics and highlights the importance of end-to-end handover strategies that jointly account for the satellites serving both the user and the gateway.

An innovative path for the detectors at future colliders to achieve higher performances is to use a Particle Flow approach, which requires highly granular calorimeters to image individual showers. The silicon-tungsten electromagnetic calorimeter (SiW-ECAL) aims at fulfilling all the expected physical and technical requirements. SiW-ECAL has been developed by the CALICE and ILD collaborations for more than two decades and is now reaching maturity, for linear machines. However, with the tendency towards circular machines, the progress of electronics and the rapid advancement of machine learning (ML) techniques, the SiW-ECAL design needs to be reoptimised to enhance its performance. This study develops ML-based reconstruction approaches for SiW-ECAL, achieving an approximate 20% improvement in energy resolution in the low-energy range and effectively correcting energy leakage in the high-energy range. Subsequently, the SiW-ECAL design is reoptimized based on this method.

Fractal structures naturally emerge in quantum systems whose initial states exhibit spatial discontinuities, a phenomenon first identified by Berry in the paradigmatic case of a particle confined in an infinite potential well. While previous analyses of quantum fractals have mainly relied on spectral decompositions and geometric scaling arguments, their quantitative characterization often depends on scale choices and truncation effects. Here we present a wavelet-based multiresolution framework that enables a direct and assumption-free quantification of quantum fractality. Fractal dimensions are extracted from the scale-dependent distribution of wavelet energies, without invoking prior power-law hypotheses. The method is applied to space and time quantum fractals arising in confined dynamics, as well as to dynamical curves generated by the associated quantum probability flux. These flux-driven trajectories provide a natural space--time parametrization of the underlying fractal structure and yield scaling properties fully consistent with Berry's predictions for space--time fractals. The resulting fractal dimensions are shown to be robust with respect to the choice of wavelet family, numerical cutoffs, and system parameters. Beyond validating earlier conjectures, the present framework offers a unified and computationally efficient tool for the multiscale analysis of quantum fractality in confined and interference-driven quantum dynamics. That is, it provides an operational, scale-adaptive criterion that unifies the characterization of space, time, and space--time quantum fractals within a single, hypothesis-free approach.

We measured the rectification of an ac voltage in a structure of superconducting circularly-asymmetric aluminum rings in series, permeated with a magnetic flux and biased with a low-frequency alternating current (without a dc component). This rectification is due to the shift of the maxima of the critical currents of different polarity relative to the zero flux in opposite directions along the flux axis in the asymmetric ring. For the first time, we propose a model for a temperature-dependent phase shift equal to difference between dimensionless kinetic inductances of wide and narrow semirings having the same length and thickness. The shift is not zero in the case of different critical currents densities in both semirings. This is possible only in a situation of different critical temperatures of both semirings. The model describes well the temperature-dependent shift of the maxima of the critical currents, answers the long-standing mysterious challenge of the shift and removes extremely strange contradiction between the results of different measurements, previously found in circularly-asymmetric aluminum structures.

J. Conway defined useful operations on the Class of combinatorial games and also introduced a notion of equivalence between games. Conway showed that, under his equivalence, games form a Group. However, Conway product is not well defined on equivalence classes of arbitrary games (though it is well defined for surreals). We consider an equivalence relation finer than Conway's and show that under such a relation combinatorial games actually form a Ring. We hint to other possible relations on the Class of combinatorial games.

Using the SIMBA, EAGLE, and IllustrisTNG-100 galaxy formation simulations, we examine the anisotropy of the satellite distribution and its dependencies on central galaxies, host halos, and cosmic filaments. We find that in all simulations the satellite anisotropy is robustly aligned with the halo/central galaxy major axis. This correlation is both redshift- and halo-mass-dependent and also extends to filamentary structures outside the halo to several virial radii. The alignment persists up to $z=1.5$ at high redshifts, and the mass dependence remains down to $M_\mathrm{200c} \approx 10^{11}M_{\odot}$. We identify a clear $3σ$ scale-dependent transition in the structural tracers of satellite anisotropy: satellite distributions correlate with central galaxy morphology at small scales ($<0.3R_{\rm 200c}$), are governed by host halo triaxiality at halo scales ($0.3$-$2R_{\rm 200c}$), and align with cosmic filaments beyond $2R_{\rm 200c}$. By tracing satellite trajectories in SIMBA, we uncover the kinematic origin of this transition, demonstrating that satellites prefer halo major-axis aligned regions because their trajectories intersect this axis far more frequently and stay in it for a longer time under the host's gravitational potential. This dynamical processing effectively erases primordial filament-related signals upon accretion ($<2R_{\rm 200c}$), explaining the shift in dominant structural tracers across scales.

Negatively charged boron vacancy (VB-) defects in hexagonal boron nitride (hBN) are promising for nanoscale-proximity quantum sensing. To evaluate their performance, it is important to characterize the spin coherence times T2* and T2. In this study, we realized sub-GHz Rabi oscillations of VB- using an isotopically enriched hBN thin film directly stamped onto a narrow gold wire. Using these strong microwave pulses, we performed Ramsey interference and Hahn echo measurements. The Ramsey interference signal showed Gaussian-like decay, yielding T2* = 13.8 ns. The Hahn echo measurement gave T2 = 108.7 ns and a stretch factor of α= 1.25. These results experimentally clarify the spin coherence properties of VB- and provide an effective method for evaluating the coherence of spin defects in van der Waals thin films with broad resonance linewidths.

We study structural properties of the free Banach lattice $FBL\langle L\rangle$ generated by a distributive lattice $L$. We characterize when $FBL\langle L\rangle$ has a strong unit, compute its density character, analyze the density character of order intervals and study when is $FVL\langle L\rangle$ order dense in $FBL\langle L\rangle$. We also study projection bands, quasi-interior points, and Banach lattice homomorphisms induced by lattice homomorphisms. Finally, we show that $FBL\langle L\rangle$ is lattice isometric to $FBL\langle L^{\mathrm{op}}\rangle$, where $L^{\mathrm{op}}$ denotes the opposite lattice.

In this paper we study a variant of the uncentred Hardy--Littlewood maximal operator on Damek--Ricci spaces in which balls are replaced by suitable half balls. Perhaps surprisingly, such modified maximal operator has better boundedness properties than the classical one. In particular, it satisfies an $L\log L$ endpoint estimate and it is bounded on $L^p$ for every $p$ in $(1,\infty]$.

Characterizing quantum systems by learning their underlying Hamiltonians is a central task in quantum information science. While recent algorithmic advances have achieved near-optimal efficiency in this task, they critically rely on accessing arbitrarily short-time dynamics. This reliance poses severe experimental challenges due to finite control bandwidth and transient pulse errors. In this work, we demonstrate that Heisenberg-limited Hamiltonian learning can be achieved without short-time control. We introduce a framework in which every query to the unknown dynamics has duration at least a prescribed minimum time $T$, and show that this restriction does not preclude Heisenberg-limited scaling. The key ingredient is a method for emulating the continuous quantum control required by iterative learning algorithms using only such lower-bounded evolution times. This reduces the learning task to sparse pure-state tomography. Notably, for logarithmically sparse Hamiltonians, our algorithm achieves the information-theoretically optimal $1/\varepsilon$ scaling in total evolution time for any arbitrary constant minimum evolution time $T$. For many-body (polynomially sparse) systems, we uncover a rigorous quantitative tradeoff, showing that the minimum required evolution time can be significantly relaxed from the standard limit at a polynomial cost in total evolution time. Our results affirmatively resolve a prominent open problem in the field and reveal that high-bandwidth, ultra-short pulses are not fundamentally necessary for optimal quantum learning.

This paper investigates two optimal insurance contracting problems under distributional uncertainty from the perspective of a potential policyholder, utilizing a Bregman-Wasserstein (BW) ball to characterize the ambiguity set of loss distributions. Unlike the $p$-Wasserstein distance, BW divergence enables asymmetric penalization of deviations from the benchmark distribution. The first problem examines an insurance demand model where the policyholder adopts an $α$-maxmin preference with Value-at-Risk (VaR). We derive the optimal indemnity function in closed form and study, both analytically and numerically, how the asymmetry inherent in BW divergence influences the optimal indemnity structure. The second problem employs a robust optimization framework, where the policyholder aims to secure robust insurance indemnity by minimizing the worst-case convex distortion risk measure while adhering to a guaranteed VaR constraint. In this context, we provide explicit characterizations of both the optimal indemnity and the worst-case distribution in closed form through a combined approach using the Lagrangian method and modification arguments. To illustrate the practical implications of our theoretical findings, we include a concrete example based on Tail Value-at-Risk (TVaR).

Practical applicability of quantum optimisation on near term devices is constrained by limited qubit counts and hardware noise, which restricts the scalability of quantum optimisation algorithms for combinatorial problems. The simulation of large quantum circuits is also difficult and constrained by memory requirement. The Hamiltonian Auto Decomposition Optimisation Framework (HADOF) addresses this by decomposing large QUBOs into smaller subproblems that can be solved iteratively on quantum or classical backends. This allows the scalability of quantum QUBO algorithms beyond device limits, as well as their simulation on classical devices. In this research, we extend the evaluation of HADOF by benchmarking on real IBM QPUs across sequential, single-QPU parallel, and multi-QPU parallel execution modes, advancing toward High Performance Quantum (HPQ) computing for combinatorial optimisation problems. Experimental results on IBM quantum hardware demonstrate up to 3-4x reduction in wall clock time when utilising four QPUs compared to sequential execution baseline, while maintaining comparable solution quality. Notably, even single QPU execution benefits from parallelised job orchestration and execution, yielding up to 3x speedup. Simulated results predict over 5x speed-up in parallel execution mode. We further validate the practical applicability of the approach on real world genome assembly instances, showing that both sequential and parallel HADOF variants achieve competitive accuracy while significantly improving time to solution. These results highlight the importance of parallelism at both the algorithmic and system levels, positioning HADOF as a viable pathway toward scalable quantum optimisation.

The 'Species Scale' has proved to be an important concept when studying consistent effective actions in Quantum Gravity. This is a short summary of my contribution to the Corfu Summer Institute in September 2025, in which I covered two topics, both related in different ways to the fact that the Species Scale is moduli dependent. In the first, based on work done in collaboration with C. Aoufia and A. Castellano, we show how the one-loop Wilson coefficients $\mathcal{F}_n^{(d)}$ multiplyiing BPS protected ${\cal R}^{2n}$ operators obey Laplace-like eigenvalue differential equations of the form $\mathcal{D}^2_{\bf {\cal M}} \mathcal{F}^{(d)}_n = η_d\, \mathcal{F}^{(d)}_n$. This is true both for $n=2$ with 32 and 16 SUSY generators in 10,9,8 dimensions and theories with 8 SUSY generators in 6,5,4 dimensions $(n=1)$. We argue that this fact is at the root of some Swampland conjectures put forward in the past, like bounds on the dumping rates for the tower scales and the exponential behaviour in the Swampland Distance Conjecture. For the second topic, based on work done in collaboration with G.F. Casas, we discuss the one loop potential of the no-scale moduli in GKP-like Type IIB 4d orientifolds. To compute this potential we sum both over light and heavy (tower) modes using the Species Scale as a UV cut-off. We find a generic form $V_{1-loop}\sim g^2m_{3/2}^2M_p^2(g^{i{\bar i}}(\partial_iΛ)(\partial_{\bar i}Λ))/Λ^2$, with $Λ$ the Species Scale. This has minima at the $desert$ $points$ in moduli space and exponentially decreases at large moduli, with a dS hill in between. We argue that this potential may lead to the stabilisation of some or all Kahler moduli at the desert points in 4d Type IIB orientifolds of phenomenological interest.

We study hypergeometric functions of nilpotent operators in finite-dimensional settings, motivated by the algebraic structure of exceptional points in non-Hermitian quantum mechanics. Our starting point is the following exact result: if N is a nilpotent operator of index m+1 in an associative algebra over C, then every generalized hypergeometric function pFq evaluated at N reduces to a finite polynomial in N of degree at most m, without any analytic convergence requirement. This "functional collapse" is distinct from the classical parameter-termination mechanism and arises purely from the nilpotent structure of the argument. The main result is a "nilpotent depth criterion" (Theorem 2): if the first non-constant coefficient of a formal series F appears in degree r >= 1, then the nilpotent part F(N) - F(0)I has nilpotency index bounded above by ceil((m+1)/r). We apply this criterion to Hamiltonians at exceptional points, where H = lambda I + N with N^{m+1} = 0. Theorem 3 establishes that a function F analytic at lambda reduces the Jordan depth of the exceptional point from m+1 to at most ceil((m+1)/r), where r is the contact order of F at lambda. As consequences: the time evolution operator e^{tH} preserves the full Jordan depth for all t != 0; a function with a zero of order m+1 at lambda annihilates the entire Jordan structure; and the order of the pole of the modified resolvent is reduced from m+1 to at most m+1-r. Results are illustrated with explicit 3x3 Jordan block computations for 1F1, 2F1, and the time evolution operator, confirming sharpness of the bounds.

In \cite{Bedford}, the dynamics of a particular polynomial diffeomorphism of $\mathbb{C}^N$, called a polynomial shift-like map of type $ν$, has been studied as a higher dimensional analog of Hénon maps. In this note, we prove that the Julia set of their transcendental counterpart is non-empty. In addition, an example of a transcendental shift-like map with an escaping wandering domain has been provided which, in fact, showcases a contrast with the dynamics of a polynomial shift map.

Plant breeding and variety trials are usually conducted in multiple environments sampled from a defined target population of environments in order to characterize the performance of breeding lines or varieties. When the population is large and heterogeneous, it may be sub-divided into sub-regions or zones according to administrative and agro-ecological criteria. Analysis then focuses on prediction of performance in the individual sub-regions. Modelling the genotype effect in each sub-region as random, information can be borrowed across sub-regions using best linear unbiased prediction based on a suitable variance-covariance matrix for the genotype-zone effects. Here, we consider the important case where kinship of pedigree information is available for the genotypes under test. This information can be integrated into the variance-covariance matrix for genotype-zone effects. The objective we pursue here is to determine the optimal allocation of a fixed budget of trials to sub-regions. This design problem is solved using a combination of theory and explicit equations on one hand and numerical optimization on the other hand. Our proposed novel approach allows obtaining the optimal allocation when the number of genotypes is in the hundreds, a common setting in large plant breeding programs as well as in variety testing for economically important crops.

System auditing on Android faces two problems. First, existing syscall tracers lose events under load, silently overwriting entries faster than a user space reader can drain them. Second, security-relevant application behavior is mediated through Binder, Android's kernel IPC mechanism, and is therefore hidden from the syscall layer. The Binder parcels that the kernel does see carry no method names or typed arguments, a disconnect between low-level events and high-level behavior known as the semantic gap. Existing approaches address the semantic gap either by modifying the Android platform, making them difficult to adjust to OS updates, or by instrumenting the traced application in user space, which sophisticated adversaries can evade by bypassing the instrumented framework APIs. We present WOOTdroid, a design and prototype for on-device tracing on stock Android that addresses both problems without OS modification or application instrumentation. WDSys, an eBPF port of eAudit-style syscall auditing, runs on current Android with at most 3.6% Geekbench overhead and traces 33% more syscalls than ftrace. WDBind captures Binder parcels in the kernel and decodes them out-of-process against a framework signature table extracted via Java reflection. We demonstrate WOOTdroid on Pixel 9 devices running Android 16 with an end-to-end case study reconstructing ten security-relevant Binder transactions.

We propose a method for constructing multi-qubit entangled quantum states representing weighted tripartite graphs. An expression for the entanglement distance for multi-qubit states corresponding to arbitrary tripartite graph structures is obtained. The entanglement of a qubit with the rest of the system in a quantum graph state is determined by the weights of the edges in the closed neighborhood of the corresponding vertex and by its degree with respect to other sets. We also calculate quantum correlators in the general case of tripartite quantum graph states. We establish a relationship between these quantum properties and the structural properties of the corresponding tripartite graphs, including the number of non-overlapping neighbors, the number of common neighbors of the corresponding vertices, and the number of 4-cycles. As an illustrative example, we consider a tripartite graph forming a triangle and compute the entanglement distance using quantum simulations on the AerSimulator with noise models. The numerical results are consistent with the theoretical predictions. The obtained results demonstrate that quantum graph states provide an effective framework for studying structural properties of tripartite graphs. They open up the possibility of investigating such properties using quantum programming. It is worth highlighting that tripartite graphs have applications in solving practical problems such as resource allocation, scheduling, and database and hypergraph modeling.

Open clusters are fundamental laboratories for investigating stellar and Galactic evolution, and serve as important benchmarks for asteroseismic analyses. Using a boutique method to analyze TESS photometry, we study red giants in two old metal-rich open clusters: NGC 188 & NGC 6791. By comparing Kepler and TESS observations for NGC 6791, similar oscillation mode frequencies are recovered, however we find a systematic offset of 2.2% with a scatter of 9% in the $ν_{\text{max}}$ measurements. We attribute this discrepancy to the lower signal-to-noise of the TESS data for these relatively faint stars. For the brighter cluster NGC 188, we present new seismic measurements in 17 red giants. We estimate average seismic masses for the RGB of $M_{\text{RGB,NGC188}} = 1.13\pm0.04$(rand)$^{+0.12}_{-0.19}$(sys) $M_{\odot}$ and RC of $M_{\text{RC,NGC188}} = 1.11\pm0.01$(rand)$^{+0.11}_{-0.19}$(sys) $M_{\odot}$, consistent with independent mass estimates for this cluster and with similar precision to previous Kepler studies. From the difference between the average evolutionary phase masses, we estimate an integrated RGB mass loss of $ΔM = 0.02 \pm 0.04$(rand)$\pm0.01$(sys) $M_{\odot}$, supporting the evidence for lower mass loss at higher metallicities. Using asteroseismology and chemical abundances, we identify three binary interaction candidates: two under-massive stars and one over-massive star potentially exhibiting dipole-mode suppression. Finally, we derive an average seismic cluster age of $7.0\pm0.9$ Gyrs, in good agreement with previous literature ages. Our analysis demonstrates the strong potential of TESS asteroseismology for open clusters, and motivates extending this investigation to other TESS clusters that span a wider range of ages and metallicities.

We analyze the mixing, migration and spreading of a gravity current in a heterogeneous porous medium using high-fidelity numerical simulations. Heterogeneity is represented by log-normal permeability fields of varying correlation lengths and variance. Stable and unstable density stratification scenarios are considered through linear and non-monotonic density laws, respectively. Heterogeneity reduces dissolution and increases the speed of the gravity current proportionally to the Rayleigh number. In the unstable case, heterogeneity accelerates the onset of convection. Convection-driven dissolution slows down the gravity current and counteracts the dispersive effect of heterogeneity resulting in a narrower interface and higher dissolution than in the stable case. Permeability anisotropy reduces dissolution because of the barrier effect of low permeability regions, except when blobs of buoyant fluid are trapped in low permeability structures and rapidly dissolve. The variance of the log-permeability field enhances dissolution. However, the homogeneous case outperforms heterogeneous cases except when Rayleigh number is small. This suggest an interaction between the size of the instabilities, the correlation length of the permeability field and the dispersive and barrier effects of the permeability field that controls dissolution efficiency.

Degradation of near surface nitrogen vacancy (NV) centers in diamond under optical illumination has restricted their deployment in applications such as scanning NV magnetomety, particularly under harsh environment such as low temperatures and vacuum. Previously, alumina passivation of planar diamond samples has been shown to reduce the degradation of near surface ensemble NV centers in vacuum. Here, we expand this study to incorporate photonic nanostructures by analyzing the single photon emission characteristics of NV centers embedded in an array of alumina-coated diamond nanopillars in high vacuum and low temperature (6K, high vacuum) environments under non-resonant (522 nm) laser exposure. We find that, in contrast to the oxygen-terminated diamond nanopillars, NV centers in the alumina-coated nanopillars demonstrate negligible change in the single photon purity and brightness over the course of laser exposure in vacuum. At low temperature, NV centers under alumina termination demonstrate stable single photon emission, whereas under oxygen termination the single photon purity degrades under high intensity laser exposure. Alumina surface passivation is therefore shown as a viable path toward the realization of robust NV-diamond based nanoscale sensing under non-ambient atmospheric environments, including using diamond scanning probes.

AI integration in automotive perception systems shifts requirements from static specifications to continuously evolving entities shaped by data, models, and operating contexts. When such changes are not consistently documented, validated, and traced, they accumulate as Requirements Debt (ReD), an underexplored but critical subtype of technical debt. This study conceptualises and empirically investigates how evolving functional and non-functional requirements create and propagate ReD across the AI-enabled automotive perception system lifecycle. We conducted 16 semi-structured interviews with experts from 13 international automotive companies and 3 European research institutes, and analysed the data using thematic analysis. As one of the first empirical studies connecting technical debt theory with RE4AI, the work identifies key ReD mechanisms. Evolving functional requirements (e.g., algorithm updates, sensor fusion, architectural changes, real-time constraints) drive semantic drift, validation backlogs, and integration debt when verification lags behind rapid iteration. In parallel, evolving non-functional requirements (e.g., safety, cybersecurity, reliability, scalability, transparency, trustworthiness) create assurance lag, compliance misalignment, and transparency and reliability debt as standards and ethical expectations shift. These interacting mechanisms propagate ReD across data, models, and system artefacts, undermining auditability, reliability, and certification readiness in safety-critical perception systems.

Accurately characterizing multipartite entangled states is a critical challenge in quantum information processing. In this work, we focus on applying compressed sensing techniques to efficiently estimate the fidelity of Greenberger-Horne-Zeilinger (GHZ) states. By exploiting the inherent sparsity of these states, our compressed sensing protocol drastically reduces the measurement overhead traditionally required for state verification while maintaining high accuracy. To evaluate the practical performance of this approach, we test the protocol on GHZ states using both quantum simulators and Quantinuum's trapped-ion hardware. Furthermore, we implement error detection techniques during our hardware evaluations, demonstrating the robustness and viability of compressed sensing for fidelity estimation in noisy experimental environments.