The 21 cm bispectrum (BS) offers a powerful probe of the Epoch of Reionization (EoR), but its observational access is severely hindered by dominant astrophysical foregrounds. Considering Murchison Widefield Array (MWA) observations at $154.2~\mathrm{MHz}$ ($z=8.2$), we mitigate the foregrounds with Smooth Component Filtering (SCF) and estimate the 21 cm BS. We validate the pipeline using a simulated 21 cm signal and show that the input BS is recovered for modes $k_{\parallel} \ge [k_\parallel]_f=0.135~{\rm Mpc}^{-1}$. Applied to actual data, the SCF produces substantial foreground suppression, reducing the amplitude of the cylindrical BS $B(k_{1\perp},k_{2\perp},k_{3\perp},k_{1\parallel},k_{2\parallel})$ by $3-4$ orders of magnitude. The artifacts due to the missing frequency channels in the data are also suppressed. The resulting EoR window is significantly cleaner at small $k_{\perp}$. We adopt the region $(k_{1 \perp},k_{2 \perp},k_{3 \perp})\leq 0.026~{\rm Mpc}^{-1}$ and $(k_{1\parallel},k_{2\parallel},k_{3\parallel})>0.135~{\rm Mpc}^{-1}$ to evaluate the 3D spherical BS and constrain the EoR signal. By combining estimates over all triangle shapes, we place the lower and upper limits on the mean cube brightness temperature fluctuations $Δ^3$. The estimates are consistent with statistical fluctuations from system noise. The most stringent lower limit $Δ^3_{\rm LL}=-(1.25\times 10^4)^3~{\rm mK}^3$ and upper limit $Δ^3_{\rm UL}=(1.22\times 10^4)^3~{\rm mK}^3$ are obtained at $k_1=0.281~{\rm Mpc}^{-1}$. Additional observing time will reduce the noise level and enable substantially tighter constraints on the EoR signal.

Building on hybrid quantum lattice gas algorithm, we revisit the possibilities of this quantum lattice model. By deriving a correction to the predicted viscosity, we provide analytical and numerical results that refine original formulation. We introduce a minimal 2D generalization of the algorithm, which allows to simulate anisotropic Burgerlike equations while retaining only two lattice velocities. This approach opens a promising route toward embedding momentum conservation and advancing toward NavierStokes dynamics in 2D, going beyond Frisch, Hasslacher and Pomeau (FHP) with a quantum native model.

This study reports on the optical, structural, and dielectric properties of aluminum tantalum oxide (Al$_x$Ta$_y$O$_z$) thin films deposited at low temperature on silicon and steel substrates by pulsed direct current reactive magnetron sputtering of a target containing 80 at.% aluminum and 20 at.% tantalum in Ar/O$_2$ atmosphere. Oxygen flow rates ranging from 5.0 to 20 sccm corresponded to O content changes from 57.7 to 69.6 at.% and resulted in large differences in dielectric behavior, from films with no measurable dielectric strength to a dielectric strength of 231 V$μ$m$^{-1}$, respectively. Ab initio calculations were employed to explain the large property changes, and we show that a decrease in the dielectric strength can be linked to the formation of metal-metal bonds in the material, when the O content is less than what would correspond to a stoichiometric Ta$_2$O$_5$ and Al$_2$O$_3$ mixture. The electronic states corresponding to the metal--metal bonds are located in the band gap close to the top of the valence band, leading to an effective band gap reduction, which is directly supported by X-ray photoelectron spectroscopy valence band measurements and by a broad optical absorption in the visible region.

Cryptographic security is traditionally formulated using game-based or simulation-based definitions. In this paper, we propose a structural reformulation of cryptographic security based on Grothendieck topologies and sheaf theory. Our key idea is to model attacker observations as a Grothendieck site, where covering families represent admissible decompositions of partial information determined by efficient simulation. Within this framework, protocol transcripts naturally form sheaves, and security properties arise as geometric conditions. As a first step, we focus on $Σ$-protocols. We show that the transcript structure of any $Σ$-protocol defines a torsor in the associated topos of sheaves. Local triviality of this torsor corresponds to zero-knowledge, while the absence of global sections reflects soundness. A concrete analysis of the Schnorr $Σ$-protocol is provided to illustrate the construction. This sheaf-theoretic perspective offers a conceptual explanation of simulation-based security and suggests a geometric foundation for further cryptographic abstractions.

We present a novel method to determine lepton energy scale and resolution corrections by means of an analytical likelihood maximization applied to Drell-Yan $Z \to \ell\ell$ events. The approach relies on an exact analytical treatment of the energy smearing, avoiding random-number-based convolution techniques. This formulation results in a fully differentiable likelihood enabling the use of automatic differentiation algorithms, and thus a substantial reduction in computational cost. The method, implemented in the \ijazz software, allows the simultaneous extraction of scale and resolution parameters across multiple lepton categories defined by detector or kinematic variables. We validate the technique using toy Monte Carlo studies and realistic Pythia-based simulations, demonstrating unbiased parameter recovery and accurate uncertainty estimates. Particular attention is given to categorizations involving lepton transverse momentum, for which a relative-$p_T$ strategy is introduced to mitigate biases induced by category migration and kinematic correlations. The method is further adapted to photon-energy scale measurement in $Z \to μ^-μ^+γ$ decays. Compared to conventional approaches, the analytical method improves numerical stability, robustness of the minimization, and computational performance, making it well suited for large-scale precision calibration tasks at the LHC.

This paper investigates the existence of a local-global principle for certain twists of abelian varieties defined over number fields. Our main focus is to determine when, for $m$ a positive integer, locally $m$-atic twists of an abelian variety $A$ over a number field $K$ are globally $m$-atic. We define and study a "Tate-Shafarevich cohomology set" that governs the obstruction to the local-global principle for $m$-atic twists. We prove that, under some mild assumptions, this set is finite, and give criteria for it to be trivial, i.e. for the local-global principle to be satisfied.

Nonlinear system identificationhas proven to be effective in obtaining accurate models from data for complex real-world systems. In particular, recent encoder-based methods with artificial neural network state-space (ANN-SS) models have achieved state-of-the-art performance on various benchmarks, using computationally efficient methods and offering consistent model estimation in the presence of noisy data. However, inclusion of prior knowledge of the system can be further exploited to increase (i) estimation speed, (ii) accuracy, and (iii) interpretability of the resulting models. This paper proposes a model augmentation method that incorporates prior knowledge from first-principles (FP) models in a flexible manner. We introduce a novel linear-fractional-representation (LFR) model structure that allows for the general representation of various augmentation structures including the ones that are commonly used in the literature, and an encoder-based identification algorithm for estimating the proposed structures together with appropriate initialisation methods. The performance and generalisation capabilities of the proposed method are demonstrated on the identification of a hardening mass-spring-damper system in a simulation study and on the data-driven modelling of the dynamics of an F1Tenth electric car using measured data.

Neural post-processing has been proposed as a lightweight route to enhance variational quantum eigensolvers by learning how to reweight measurement outcomes. In this work, we identify three general desiderata for such data-driven neural post-processing -- (i) self-contained training without prior knowledge, (ii) polynomial resources, and (iii) variational consistency -- and show that current approaches, such as diagonal non-unitary post-processing (DNP), cannot satisfy these requirements simultaneously. The obstruction is intrinsic: with finite sampling, normalization becomes a statistical bottleneck, and support mismatch between numerator and denominator estimators can render the empirical objective ill-conditioned and even sub-variational. Moreover, to reproduce the ground state with constant-depth ansatzes or with linear-depth circuits forming unitary 2-designs, the required reweighting range (and hence the sampling cost) grows exponentially with the number of qubits. Motivated by this no-go result, we develop a normalization-free alternative, the unitary variational quantum-neural hybrid eigensolver (U-VQNHE). U-VQNHE retains the practical appeal of a learnable diagonal post-processing layer while guaranteeing variational safety, and numerical experiments on transverse-field Ising models demonstrate improved accuracy and robustness over both VQE and DNP-based variants.

Artificial intelligence systems increasingly generate text intended to provide social and emotional support. Understanding how users perceive empathic qualities in such content is therefore critical. We examined differences in perceived empathy signals between human-written and large language model (LLM)-generated relationship advice, and the influence of authorship labels. Across two preregistered experiments (Study 1: n = 641; Study 2: n = 500), participants rated advice texts on overall quality and perceived cognitive, emotional, and motivational empathy. Multilevel models accounted for the nested rating structure. LLM-generated advice was consistently perceived as higher in overall quality, cognitive empathy, and motivational empathy. Evidence for a widely reported negativity bias toward AI-labelled content was limited. Emotional empathy showed no consistent source advantage. Individual differences in AI attitudes modestly influenced judgments but did not alter the overall pattern. These findings suggest that perceptions of empathic communication are primarily driven by linguistic features rather than authorship beliefs, with implications for the design of AI-mediated support systems.

We consider positive semidefinite kernels which have values given by bounded linear operators on certain bundles of Hilbert spaces and which are invariant under actions of $*$-semigroupoids. For these kernels, we prove that there exist generalised $*$-representations of the $*$-semigroupoids on the underlying reproducing kernel Hilbert spaces or, equivalently, on the underlying minimal linearisations, we characterise when the $*$-representations are performed by means of bounded operators and show that this always happens for inverse semigroupoids. Then, we consider Hermitian kernels which have values given by bounded linear operators on certain bundles of Hilbert spaces and which are invariant under actions of $*$-semigroupoids. Only those Hermitian kernels having certain boundedness properties can produce reproducing kernel Krein spaces but uniqueness is more complicated. However, for these kernels, generalised $*$-representations can be obtained. If $*$-representations with bounded linear operators are requested, then stronger boundedness conditions on the kernels are needed.

Anemia is a prevalent hematological disorder that requires frequent hemoglobin monitoring for early diagnosis and effective management. Conventional hemoglobin assessment relies on invasive blood sampling, limiting its suitability for large-scale or continuous screening. This paper presents a non-invasive framework for hemoglobin estimation and anemia screening using multichannel photoplethysmography (PPG) signals and explainable artificial intelligence. Four-wavelength PPG signals (660, 730, 850, and 940~nm) are processed to extract optical and cross-wavelength features, which are aggregated at the subject level to avoid data leakage. A gradient boosting regression model is employed to estimate hemoglobin concentration, followed by post-regression anemia screening using World Health Organization (WHO) thresholds. Model interpretability is achieved using SHapley Additive explanations (SHAP), enabling both global and subject-specific analysis of feature contributions. Experimental evaluation on a publicly available dataset demonstrates a mean absolute error of 8.50 plus minus 1.27 and a root mean squared error of 8.21~g/L on unseen test subjects, indicating the potential of the proposed approach for interpretable, non-invasive hemoglobin monitoring and preliminary anemia screening.

This paper investigates the limiting behaviour of degree-degree correlation metrics for sequences of random graphs under a general assumption of local convergence in probability. We establish convergence results for Pearson's correlation coefficient r, Spearman's rho, Kendall's tau, average nearest neighbour degree (ANND), and average nearest neighbour rank (ANNR). Our results explicitly show how the limits of these degree-degree correlation metrics depend on the local structure of the graph. We then apply our general results to study degree-degree correlations in rank-1 inhomogeneous random graphs and random geometric graphs, deriving explicit expressions for ANND in both models and for Pearson's correlation coefficient in the latter one. Keywords: random graphs, degree-degree metrics, neutral mixing

Given a semigroup $S$, a diagonal subsemigroup $ρ$ is defined to be a reflexive and compatible relation on $S$, i.e. a subsemigroup of the direct square $S\times S$ containing the diagonal $\{ (s,s)\colon s\in S\}$. When $S$ is finite, we define the DSC coefficient $χ(S)$ to be the ratio of the number of congruences to the number of diagonal subsemigroups. In a previous work we observed that $χ(S) = 1$ if and only if $S$ is a group. Here we show that for any rational $α$ with $0 < α\leq 1$, there exists a semigroup with $χ(S) = α$. We do this by utilizing the Rees matrix construction and adapting the congruence classification of such semigroups to describe their diagonal subsemigroups.

Processing sensory data close to the data source, often involving Edge devices, promises low latency for pervasive applications, like smart cities. This commonly involves a multitude of processing services, executed with limited resources; this setup faces three problems: first, the application demand and the resource availability fluctuate, so the service execution must scale dynamically to sustain processing requirements (e.g., latency); second, each service permits different actions to adjust its operation, so they require individual scaling policies; third, without a higher-level mediator, services would cannibalize any resources of services co-located on the same device. This demo first presents a platform for context-aware autoscaling of stream processing services that allows developers to monitor and adjust the service execution across multiple service-specific parameters. We then connect a scaling agent to these interfaces that gradually builds an understanding of the processing environment by exploring each service's action space; the agent then optimizes the service execution according to this knowledge. Participants can revisit the demo contents as video summary and introductory poster, or build a custom agent by extending the artifact repository.

We bring to light how some asylum seekers and refugees arriving in the UK experience border control and wider immigration systems, as well as the impact that these have on their subsequent lives in the UK. We do so through participant observation in a support organisation and interviews with caseworkers, asylum seekers and refugees. Specifically, our findings show how the first meeting with the border, combined with a 'hostile' immigration system, has a longer-term impact on their sense of belonging. Our observations highlight feelings of insecurity, anxiety and uncertainty that accompanied participants' experiences with immigration systems and processes. We contribute to the growing body of HCI scholarship on the tensions between immigration and (security) technology. In so doing, we point to future directions for participatory and collaborative design practices that centre on the lived experiences and everyday security of asylum seekers and refugees.

We consider a semilinear wave equation in the whole space with a deep potential well. We prove that as the depth of the well tends to infinity, the solutions of the equation converge to the solutions of a wave equation defined on the bottom of the well, with Dirichlet condition on the boundary.

Quantum computing is a significant risk to classical cryptographic, especially RSA, which depends on the difficulty of factoring large numbers. Classical factorization methods, such as Trial Division and Pollard's Rho, are inefficient for large keys, while Shor's quantum algorithm can break RSA efficiently in polynomial time. This research studies RSA's vulnerabilities under both classical and quantum attacks and designs a hybrid security framework to ensure data protection in the post-quantum era. The conceptual framework combines AES encryption for classical security, BB84 Quantum Key Distribution (QKD) for secure key exchange with eavesdropping detection, quantum state comparison for lightweight authentication, and a bio-inspired immune system for adaptive threat detection. RSA is vulnerable to Shor's algorithm, BB84 achieves full key agreement in ideal conditions, and it detects eavesdropping with high accuracy. The conceptual model includes both classical and quantum security methods, providing a scalable and adaptive solution for Post-Quantum encryption data protection. This work primarily proposes a conceptual framework. Detailed implementation, security proofs, and extensive experimental validation are considered future work.

A network is represented as a graph consisting of nodes and edges. A cut set for a source-destination pair in a network is a set of elements that, when failed, cause the source-destination pair to lose connectivity. A Minimal Cut Set (MCS) is a cut set that cannot be further reduced while maintaining its status as a cut set. MCSs are crucial in identifying the critical elements in the network that have the most significant impact on failure. This work introduces Fast-MCS, an open-source, scalable tool for evaluating MCSs in large, complex networks. Additionally, we compare the computation time of Fast-MCS with the state-of-the-art.

The share of construction trade jobs held by women and people with disabilities has remained stubbornly low in the face of chronic shortages of skilled labor. This study explores the potential of wearable assistive technologies to reduce these disparities. We use U.S. worker-level data to estimate employment and wage differences by gender and by mobility/strength impairments in construction and non-construction jobs. We also use occupational-level data to examine variations in workforce composition, physical skill requirements, and earnings across detailed construction occupations. Regression estimates indicate that being a woman and having strength and mobility impairments are associated with substantial employment and pay gaps in construction compared to non-construction jobs. Further analysis shows a high negative correlation between the representation of women and the ability levels required in those occupations. Finally, we discuss several wearable exoskeletons under development for people with upper-body and lower-body impairments, focusing on how these innovations could be integrated into construction jobs. These findings suggest that wearable exoskeletons that enhance manual dexterity, balance, and strength may improve the representation of women and people with disabilities in some of the higher-paying occupations in construction.

We study interacting bosons on a three-dimensional Bravais lattice with positive hopping amplitudes and on-site repulsive interactions. We prove that, in the dilute limit $ρ\to 0$, the ground state energy density satisfies $$e_0(ρ) = 4πa ρ^2 \big(1+O(ρ^{1/6})\big),$$ where $a$ is the lattice scattering length defined through the corresponding two-body problem. This establishes the analogue of the Dyson and Lieb-Yngvason theorems for the Bose-Hubbard gas. Our result shows that the leading-order energy is universal: although the lattice geometry affects the microscopic dispersion relation, it enters the leading order asymptotics only through the scattering length. In particular, it is independent of other features of the underlying Bravais lattice.

Rapid localisation and follow-up of gamma-ray bursts (GRBs) increasingly rely on low-latency triggers from new missions coupled to wide-field robotic optical facilities. We present the discovery and multi-wavelength follow-up of GRB 250818B, detected by the Space Variable Objects Monitor (SVOM) and localised optically by the Gravitational-wave Optical Transient Observer (GOTO). We compile and homogenise X-ray, optical/NIR, and radio data to build broadband light curves and spectral energy distributions. The afterglow is unusually luminous for a nominal short GRB, lying on the bright end of the short-GRB population in X-rays and optical and among the most luminous high-redshift short-GRB afterglows in the radio. MeerKAT detects the source at 3.1 GHz, while ALMA provides deep higher-frequency limits. Keck/LRIS spectroscopy shows continuum and metal absorption (Fe II, Mg II, Mg I), giving $z=1.216$. Synchrotron forward-shock modelling favours a constant-density medium and strongly prefers refreshed (energy-injection) emission, well described by a two-component jet with $E_{K,iso} \sim 4\times10^{52}$ erg, $n_0 \sim 3.6$ cm$^{-3}$, $θ_j \simeq 0.10$ rad ($\sim 5.7$ deg), and $p \simeq 1.64$. The host association is ambiguous: the nearest LS DR10 galaxy candidate ($r_{AB} \sim 24.7$) is offset by $\sim 4$ arcsec ($\sim 34$ kpc) with chance-alignment probability $P_{cc} \sim 0.2$, and current imaging does not exclude a fainter, near-coincident host. SED fitting of the candidate host suggests a low-mass galaxy. GRB 250818B highlights the power of rapid wide-field counterpart identification in the SVOM era, while host-association uncertainty can still limit offset-based interpretation.

We study the Lagarias inequality, an elementary criterion equivalent to the Riemann Hypothesis. Using a continuous extension of the harmonic numbers, we show that the sequence $B_n=\frac{H_n+e^{H_n}\log(H_n)}{n}$ is strictly increasing for $n\ge 1$. As a consequence, if the Lagarias inequality has counterexamples, then the least counterexample must be a superabundant number; equivalently, it suffices to verify the inequality on the superabundant numbers.

We digitally simulate quantum many-body dynamics in emergent curved backgrounds using 80 superconducting qubits on IBM Heron processors. By engineering spatially varying couplings in the spin-$\frac12$ XXZ chain, consistent with the low-energy description of the model in terms of an inhomogeneous Tomonaga-Luttinger liquid, we realize excitations that follow geodesics of an effective metric inherited from the underlying spatial deformation. Following quenches from Néel and few-spin-flip states, we observe curved light-cone propagation, horizon-induced freezing in the local magnetization, and position-dependent oscillation frequencies set by the engineered spatial deformation. Despite strong spatial inhomogeneity, unequal-time correlators reveal ballistic quasiparticle propagation in the spin chain. These results establish large-scale digital quantum processors as a flexible platform for detailed and controlled exploration of many-body dynamics in tunable and synthetic curved spacetimes.

The development of efficient hydrogen storage materials is crucial for advancing the hydrogen economy and meeting the U.S. Department of Energy's targets of 6.5 wt% and 50 g H₂/L for automotive applications. We present a computational study of ferrocene-functionalized covalent organic frameworks (COFs) for hydrogen storage. Following the <b>M</b>ulti-binding <b>S</b>ites <b>U</b>nited in <b>C</b>ovalent-<b>O</b>rganic <b>F</b>ramework (MSUCOF) approach, we introduce MSUCOF-4-FeCp, designed by incorporating ferrocene (FeCp₂) moieties into IRCOF-102. Notably, it achieves exceptional performance with gravimetric and volumetric uptakes of 18.0 wt% and 72.6 g H₂/L at 298 K and 700 bar. The material exhibits optimal binding energies (15-20 kJ/mol) ensuring both high storage capacity and deliverable hydrogen under practical conditions. This work establishes ferrocene functionalization as a cost-effective alternative to precious metal incorporation in COFs.

In this study, we aim to constrain the atmospheric composition of GJ 1214 b using all available transits observed with the upgraded CRIRES+ spectrograph at the VLT by searching for the signatures of water vapour, methane, and carbon dioxide. We analysed eight CRIRES+ transit datasets covering the K band (1.90-2.45 microns) at a resolving power of R ~ 100,000. We used the SysRem algorithm to correct for telluric and stellar contributions and employed the cross-correlation technique with templates from petitRADTRANS to search for H2O, CH4, and CO2. Injection-recovery tests across a grid of metallicities (Z) and cloud-deck pressures (pc) were performed to quantify detection limits. We also generated predictions for ANDES observations using end-to-end simulated datasets with EXoPLORE. We detect no significant H2O, CH4, or CO2 signatures. Injection-recovery tests show that such non-detections exclude atmospheres with low-altitude clouds and moderate or low metallicities. CH4 yields the tightest empirical limits, with CO2 unexpectedly ruling out intermediate metallicities (~ 100xsolar) with clouds deeper due to its rapidly rising opacity in compressed, high-Z atmospheres. Our constraints are in line with either a high-Z or a high-altitude aerosol layer, in agreement with recent JWST inferences. The combined analysis of eight CRIRES+ datasets provides the most stringent high-resolution constraints on the atmospheric properties of GJ 1214 b to date. Simulations of a single transit observed with ANDES on the ELT predict modest improvements for H2O, a substantially expanded detectable region for CH4, and the strongest gains for CO2, making the latter a particularly effective tracer for characterising high-metallicity atmospheres in sub-Neptunes.

We show that any (n+1)-term silting complex whose intermediate cohomology vanishes gives rise to an n-silting module, as recently introduced by Mao. Specializing to commutative noetherian rings, we show that this assignment induces a bijection on the respective equivalence classes. Furthermore, we prove in the same setting that the n-silting modules always correspond to a tilting complex, that is, the associated t-structure is of derived type. We use this to exhibit new examples of tilting complexes in the setting of Commutative Algebra and also to show that the finite type property for n-silting modules, as formulated by Mao, can in general fail.

J. B. Fourier in his \emph{Théorie Analytique de la Chaleur} of 1822 introduced, amongst other things, two ideas that have made a fundamental impact in fields as diverse as Mathematical Physics, Electrical Engineering, Computer Science, and Music. The first one of these, a method to find the coefficients for a trigonometric series describing an arbitrary function, was very early on picked up by G. Ohm and H. Helmholtz as the foundation for a theory of \emph{musical tones}. The second one, which is described by Fourier's double integral, became the basis for treating certain kinds of infinity in discontinuous functions, as shown by A. De Morgan in his 1842 \emph{The Differential and Integral Calculus}. Both make up the fundamental basis for what is now commonly known as the \emph{Fourier theorem}. With the help of P. A. M. Dirac's insights into the nature of these infinities, we can have a compact description of the frequency spectrum of a function of time, or conversely of a waveform corresponding to a given function of frequency. This paper, using solely primary sources, takes us from the physics of heat propagation to the modern theory of musical signals. It concludes with some considerations on the inherent duality of time and frequency emerging from Fourier's theorem.

MnTe has recently attracted exceptional attention due to its well-established altermagnetism, prompting a thorough reexamination of its properties. In particular, it was found that a Raman-active excitation at ~175 cm$^{-1}$, routinely assigned to the E2g phonon, is incompatible with this interpretation. It was further hypothesized that this mode is a "leakage", due to symmetry lowering, of an otherwise forbidden phonon. Here, using first-principles calculations, we decisively rule out this hypothesis and propose an alternative interpretation that the "mystery mode" is an electronic excitation, i.e., a plasmon, enabled by hole self-doping. The resolution of this mystery will require additional experiments and shed new light on the nature of electronic transport in MnTe.

Strong light fields have unlocked previously unthinkable possibilities to tailor coherent electron trajectories, engineer band structures and shape emergent phases of matter all-optically. Unravelling the underlying quantum mechanisms requires a visualisation of the lightwave-driven electron motion directly in the band structure. While photoelectron momentum microscopy has imaged optically excited electrons averaged over many cycles of light, actual subcycle band-structure videography has been limited to small electron momenta. Yet lightwave-driven elementary processes in quantum materials often occur throughout momentum space. Here, we introduce attosecond-precision, subcycle band-structure videography covering the entire first Brillouin zone (BZ) and visualize one of the most fundamental but notoriously elusive strong-field processes: non-adiabatic Landau-Zener-Majorana (LZM) tunnelling. The interplay of field-driven acceleration within the Dirac-like band structure of graphene and periodic LZM interband tunnelling manifest in a coherent displacement and distortion of the momentum distribution at the BZ edge. The extremely non-thermal electron distributions also allow us to disentangle competing scattering processes and assess their impact on coherent electronic control through electron redistribution and thermalization. Our panoramic view of strong-field-driven electron motion in quantum materials lays the foundation for a microscopic understanding of some of the most discussed light-driven phenomena in condensed matter physics.

Recently, astronomers discovered unusual Einstein cross images of the galaxy HerS-3, which feature a bright central spot. Motivated by studies of images produced by regular stars, it has been proposed that optical appearances caused by compact stars acting as gravitational lenses may account for this central bright spot. We further suggest that images produced by regular stars exhibit additional characteristics distinct from those of ordinary black holes, such as the possible partial or complete absence of secondary images. These phenomena may serve as favorable observational criteria for identifying regular stars in future searches.