In this paper, we investigate the generation of gravitational waves (GWs) from a first-order QCD confinement-deconfinement phase transition under external magnetic field from holography. We analyze the GWs spectra across both hard wall and soft wall models for Jouguet detonations and non-runaway scenarios. Our results indicate that increasing the magnetic field shifts the spectral peak to lower frequencies. The predicted GWs signals are potentially detectable by observatories such as IPTA, SKA, BBO and NANOGrav. Decomposing the spectra reveals that sound waves typically dominate the signal around the peak frequency, bubble collisions prevail at spectral extremities, and the contribution from MHD turbulence is significant only for non-runaway bubble scenarios at high frequencies. This work suggests that magnetized QCD phase transitions are viable cosmological sources for observable GW backgrounds, offering a potential pathway to constrain primordial magnetic fields through future PTA observations.

Superconductivity in the iron-chalcogenide series FeSe-Fe(Te, Se)-FeTe has been restricted to the near neighbor of iron selenide (FeSe), with a general consensus that iron telluride (FeTe) is not superconducting. In this study, we report the method to grow FeTe islands with atomically flat surface and hexagonal lattice on SrTiO3 (001) substrates, in which a gap structure with a gap-filling temperature close to 40 K is detected by scanning tunneling spectroscopy. Such signature is examined under various conditions and reminiscent of a superconducting gap structure. This work might offer a potential platform to explore new superconductors at ambient pressure.

Safety-critical motion planning in mixed traffic remains challenging for autonomous vehicles, especially when it involves interactions between the ego vehicle (EV) and surrounding vehicles (SVs). In dense traffic, the feasibility of a lane change depends strongly on how SVs respond to the EV motion. This paper presents an interaction-aware safety framework that incorporates such interactions into a control barrier function (CBF)-based safety assessment. The proposed method predicts near-future vehicle positions over a finite horizon, thereby capturing reactive SV behavior and embedding it into the CBF-based safety constraint. To address uncertainty in the SV response model, a robust extension is developed by treating the model mismatch as a bounded disturbance and incorporating an online uncertainty estimate into the barrier condition. Compared with classical environmental CBF methods that neglect SV reactions, the proposed approach provides a less conservative and more informative safety representation for interactive traffic scenarios, while improving robustness to uncertainty in the modeled SV behavior.

We prove that local weak solutions to nonlocal parabolic $p$-Laplace equations are locally Lipschitz continuous in space, uniformly in time for every $1<p<\infty$ and $s \in (0,1)$ whenever $sp > p-1$. Our results hold for symmetric, translation-invariant kernels satisfying standard ellipticity bounds, including kernels that may be discontinuous and require only that the tail of the solution be bounded. In the linear case, our proof provides a different route avoiding blow up arguments and Liouville theorems.

We investigate the mechanisms of formation of stable (2+1)-dimensional optical soliton molecules (SMs) and breather molecules (BMs) in a Rydberg atomic gas, highlighting the distinct roles of nonlocality. The underlying giant, nonlocal nonlinearity induced via Rydberg electromagnetically induced transparency (EIT), supports diverse, large-size lattice SMs (rhombic, square, checkerboard, hexagonal lattice SMs). Crucially, we identify two distinct formation regimes: In the nonlocal regime, long-range interactions alone stabilize the SMs without requiring initial motion. In contrast, within the strongly nonlocal regime, an initial velocity is essential to generate a centrifugal force that counteracts the strong attraction, resulting in rotating SMs. Furthermore, specific initial velocities can induce a periodic breathing instability, leading to the formation of BMs. Our study offers a new scheme for engineering SMs with diverse configurations and opens new avenues for data processing and transmission in optical systems.

High-dimensional biomedical studies require models that are simultaneously accurate, sparse, and interpretable, yet exact best subset selection for generalized linear models is computationally intractable. We develop a scalable method that combines a continuous Boolean relaxation of the subset problem with a Frank--Wolfe algorithm driven by envelope gradients. The resulting method, which we refer to as COMBSS-GLM, is simple to implement, requires one penalized generalized linear model fit per iteration, and produces sparse models along a model-size path. Theoretically, we identify a curvature-based parameter regime in which the relaxed objective is concave in the selection weights, implying that global minimizers occur at binary corners. Empirically, in logistic and multinomial simulations across low- and high-dimensional correlated settings, the proposed method consistently improves variable-selection quality relative to established penalised likelihood competitors while maintaining strong predictive performance. In biomedical applications, it recovers established loci in a binary-outcome rice genome-wide association study and achieves perfect multiclass test accuracy on the Khan SRBCT cancer dataset using a small subset of genes. Open-source implementations are available in R at https://github.com/benoit-liquet/COMBSS-GLM-R and in Python at https://github.com/saratmoka/COMBSS-GLM-Python.

We report a pilot dark-matter search with a cryogenic, magnetized, scaled-down DALI prototype. An analysis of 36 hours of data reveals no statistically significant excess attributable to axionlike particles. We therefore set new exclusion limits in the 6.883--6.920 GHz band, reaching an axion-photon coupling sensitivity of $g_{aγγ}\lesssim 1.27\times10^{-11}\,\mathrm{GeV}^{-1}$ at 28.54 $μ$eV. These results consolidate the DALI approach and motivate a next-stage haloscope to explore a broader mass range with upgraded instrumentation.

For a function $F$ represented as $F(x)=\sum_{n=0}^\infty{f_n (x) e^{2 πi λ_n x}},$ where each $f_n$ satisfies $\operatorname{spec}(f_n) \subset [0, 1]$ and $(λ_n)_{n\geq 0}\subset \mathbb{R}_+$ is a lacunary sequence, we obtain $$ \|F\|_{L^2(\mathbb{R})}\lesssim \|Fχ_{E}\|_{L^2(\mathbb{R})} $$ provided that $E$ is a thick subset of $\mathbb{R}$. This extends the Logvinenko-Sereda theorem and answers a question posed by Kovrizhkin for functions with positive frequencies.

Strong call-by-need combines full normalization with the sharing discipline of lazy evaluation, yet no prior implementation achieved both simplicity and efficiency. We introduce RKNL, an abstract machine that realizes strong call-by-need with bilinear overhead. The machine has been derived automatically from a higher-order evaluator that uses the technique of memothunks to implement laziness. By employing an off-the-shelf transformation tool implementing the ``functional correspondence'' between higher-order interpreters and abstract machines, we obtained a simple and concise description of the machine. We prove that the resulting machine conservatively extends the lazy version of Krivine machine for the weak call-by-need strategy, and that it simulates the normal-order strategy in a bilinear number of steps, i.e., linear in both the number of beta-reductions and the size of the input term.

Audio-Visual Semantic Segmentation (AVSS) aligns audio and video at the pixel level but requires costly per-frame annotations. We introduce Weakly Supervised Audio-Visual Semantic Segmentation (WSAVSS), which uses only video-level labels to generate per-frame semantic masks of sounding objects. We decompose WSAVSS into looking, listening, and segmentation, and propose Progressive Cross-modal Alignment for Semantics (PCAS) with two modules: *Looking-before-Listening* and *Listening-before-Segmentation*. PCAS builds a classification task to train the audio-visual encoder using video labels, injects visual semantic prompts to enhance frame-level audio understanding, and then applies progressive contrastive alignment to map audio categories to image regions without mask annotations. Experiments show PCAS achieves state-of-the-art performance among weakly supervised methods on AVS and remains competitive with fully supervised baselines on AVSS, validating its effectiveness.

In the presence of spacetime boundaries, diffeomorphisms in gravitational theories can become physical and acquire non-vanishing Noether charges. These charges obey an algebra which, within the extended phase-space formalism, faithfully realizes diffeomorphism algebra. The corner proposal takes this algebra of physical corner symmetries as a fundamental ingredient of quantum gravity, in close analogy with the role of the Poincaré group in quantum field theory. In this thesis we develop the quantum corner framework in the two-dimensional setting. We give the full representation theory of the two-dimensional extended corner symmetry group, which may be interpreted either as the symmetry group of two-dimensional gravity or as the corner symmetry group relevant for four-dimensional spherically symmetric gravity. Within the corner proposal, the resulting representation spaces are then interpreted as candidate Hilbert spaces for quantum gravity. This representation-theoretic structure naturally enables a description of local subsystems. In particular, we present a gluing procedure that constructs quantum states associated with an entangling corner between two spacetime subregions, and use it to compute the entanglement entropy between the two regions. To connect the quantum observables to the classical corner charges, we construct the coadjoint orbits of the quantum corner symmetry group and relate them to the classical structure through twisted moment maps and to the quantum structure through generalized Perelomov coherent states. This provides a notion of semiclassical limit within the corner framework. Finally, in the context of static, spherically symmetric spacetimes, we show that a distinguished family of coherent states reproduces the horizon area law for entropy in the semiclassical limit, yielding a quantum, symmetry-based explanation of the Bekenstein--Hawking formula.

The Schwinger model is perhaps the simplest non-trivial exactly-solvable QFT. In this note we examine the perturbative structure of the theory on the sphere and show that its quantum corrections match those predicted by the expansion of the exact solution.

We investigate the tension between symplecticity and gauge covariance in classical Hamiltonian mechanics. The pursuit of manifest covariance over manifest symplecticity results in a unique geometric formulation. Firstly, covariant yet non-canonical coordinates are employed by adopting Souriau's approach to minimal coupling. Secondly, covariant yet non-coordinate frames arise from Ehresmann connections in phase space. Thirdly, the concept of covariant Poisson bracket is introduced, facilitating direct derivations of covariant equations of motion. In this way, we establish manifestly covariant Hamiltonian formulations of particles coupled to background gauge and gravitational fields, with or without spin. The variational principle and path integral origins of our framework are also explicated.

This paper models firm-to-firm trade in a production network as a set of double auctions. Firms have multilateral market power, namely, can affect prices in both input and output markets. The size and division of surplus are endogenous and depend only on technology, network position, and consumer preferences. The standard simplifying assumption of price-taking on input markets (unilateral market power) has systematic effects: it underestimates the final price and overestimates the surplus going upstream. These phenomena affect the model predictions for the welfare impact of mergers.

Inspired by the MacDowell-Mansouri formulation of four-dimensional General Relativity, we study a class of four-dimensional gauge-theoretic functionals obtained from the Pontryagin density of a G-connection by inserting, under the trace, a matrix that breaks the gauge group G to a subgroup H. Concretely, we study the model with the pair (G,H) given by (SU(3), U(2)). We show that the critical points of the resulting functional are constant scalar curvature almost-Kahler 4-manifolds. On compact 4-manifolds, a stronger conclusion holds under the additional assumption that the scalar curvature is non-negative and the first Chern class is such that an Einstein metric can exist. In this case, results in the literature imply that the critical points are Kahler-Einstein 4-manifolds.

We present a novel classification of unitarizable supermodules over special linear Lie superalgebras using an algebraic quadratic Dirac operator introduced by Huang and Pandžić and a corresponding Dirac inequality.

State-of-the-art metallic terahertz (THz) emitters rely predominantly on spintronic heterostructures, where heavy metals serve as passive spin-to-charge converters. Here, we demonstrate efficient THz radiation from standalone Pt nanofilms at cryogenic temperatures and under external magnetic fields. The governing mechanism is identified as the ultrafast photo-Nernst effect, wherein a transient thermal gradient drives a transverse charge current. The THz emission polarity is directly dictated by the sign of the Nernst coefficient, as verified by the phase reversal observed between Pt and W or Ta. Remarkably, both thickness scaling and alloying-induced suppression of thermal conductivity independently amplify the single-layer emission to levels comparable with benchmark spintronic bilayers. These findings redefine the established role of heavy metals from passive spin-sinks to active THz emitters, uncovering a universal emission paradigm applicable across diverse spintronic and quantum materials.

With the rapid advancement of 6G, identity authentication has become increasingly critical for ensuring wireless security. The lightweight and keyless Physical Layer Authentication (PLA) is regarded as an instrumental security measure in addition to traditional cryptography-based authentication methods. However, existing PLA schemes often struggle to adapt to dynamic radio environments. To overcome this limitation, we propose the Adaptive PLA with Channel Extrapolation and Generative AI (APEG), designed to enhance authentication robustness in dynamic scenarios. Leveraging Generative AI (GAI), the framework adaptively generates Channel State Information (CSI) fingerprints, thereby improving the precision of identity verification. To refine CSI fingerprint generation, we propose the Collaborator-Cleaned Masked Denoising Diffusion Probabilistic Model (CCMDM), which incorporates collaborator-provided fingerprints as conditional inputs for channel extrapolation. Additionally, we develop the Cross-Attention Denoising Diffusion Probabilistic Model (CADM), employing a cross-attention mechanism to align multi-scale channel fingerprint features, further enhancing generation accuracy. Simulation results demonstrate the superiority of the APEG framework over existing time-sequence-based PLA schemes in authentication performance. Notably, CCMDM exhibits a significant advantage in convergence speed, while CADM, compared with model-free, time-series, and VAE-based methods, achieves superior accuracy in CSI fingerprint generation. The code is available at https://github.com/xiqicheng192-del/APEG

The magnetocaloric effect in the quantum dipolar magnet Yb$_3$Ga$_5$O$_{12}$ is studied both for pure material and with non-magnetic substitution: (Yb$_{1-x}$Y$_x$)$_3$Ga$_5$O$_{12}$. Magnetization measurements have been performed on a single crystal, $x=0$, and on powder samples with $x = 0.2$ and 0.4 in the temperature range between 70 mK to 300 K and in magnetic fields up to 8 T. The magnetic entropy change $ΔS_m$, a key figure of merit for adiabatic demagnetization refrigeration, has been derived from the magnetization data. The $x=0.2$ sample exhibits the volumetric entropy variation comparable to, and at low fields even enhanced relative to, the pure compound. In contrast, the 40\%\ diluted sample shows a reduced effect, consistent with the conventional dilution picture. The Curie-Weiss law fits reveal positive Curie temperatures in both diluted samples, indicating the persistence of ferromagnetic correlations. The robustness of the magnetocaloric response upon moderate dilution highlights the potential of YbGG-based materials for low-temperature magnetic cooling applications, particularly in addressing thermal conductivity challenges through the chemical substitution without compromising cooling power.

This paper investigates ensemble Kalman inversion (EKI) for variational inverse problems with convex, potentially non-smooth regularization. While deterministic EKI and its Tikhonov-regularized variants have primarily been analyzed for smooth objectives, a corresponding framework accommodating subgradient dynamics has not yet been established. To address this gap, we introduce a subgradient-based formulation of EKI (SEKI) that incorporates non-smooth regularizers through a covariance-preconditioned differential inclusion for the ensemble mean. In the linear forward-model setting, well-posedness of the resulting continuous-time particle system is established under minimal assumptions on the regularization functional using maximal monotone operator theory and Yosida approximations. Motivated by the continuous-time dynamics, we propose an explicit discrete-time scheme that preserves the derivative-free structure of EKI and analyze its convergence as an optimization method in the strongly convex case. Numerical experiments in computed tomography with total variation regularization and sparse recovery with $\ell_1$ penalties illustrate that non-smooth regularization can be incorporated into ensemble Kalman inversion in a stable and principled manner.

Virtual Reality (VR) emphasizes immersive experiences, while text entry often requires hands or visual attention, which may disrupt the interaction flows in VR. We present AnkleType, a hand- and eye-free text-entry technique that leverages ankle-based gestures for both standing and sitting situations. We began with two preliminary studies: one investigated the movement range of users' ankles, and the other elicited user-preferred ankle gestures for text-entry-related operations. The findings of these two studies guided our design of AnkleType. To optimize AnkleType's keyboard layout for eye-free input, we conducted a user study to capture the users' natural ankle spatial awareness with a computer-simulated language test. Through a pairwise comparison study, we designed a bipedal input strategy for sitting (BPSit) and a unipedal input strategy for standing (UPStand). Our first in-VR text-entry evaluation with 16 participants demonstrated that our methods could support the average typing speed from 8.99 WPM (BPSit) to 9.13 WPM (UPStand) for our first-time users. We further evaluated our design with a 7-day longitudinal study with twelve participants. Participants achieved an average typing speed of 15.05 WPM with UPStand and 16.70 WPM with BPSit in the visual condition, and 11.15 WPM and 12.87 WPM, respectively in the eyes-free condition.

We study identifiability of finite mixtures of Dirichlet distributions on the interior of the simplex. We first prove a shift identity showing that every Dirichlet density can be written as a mixture of $J$ shifted Dirichlet densities, where $J-1$ is the dimension of the simplex support, which yields non-identifiability on the full parameter space. We then show that identifiability is recovered on a fixed-total parameter slice and on restricted box-type regions. On the full parameter space, we prove that any nontrivial linear relation among Dirichlet kernels must involve at least $J$ coefficients sharing a common sign, and deduce that mixtures with fewer than $J$ atoms are identifiable. We further report direct non-identifiability implications for unrestricted finite mixtures of generalized Dirichlet, Dirichlet-multinomial, fixed-topic-matrix latent Dirichlet allocation, Beta-Liouville, and inverted Beta-Liouville models.

Context: Composite galaxies that contain both Seyfert and starburst components may produce very high-energy (VHE; >100 GeV) gamma-ray emission at a wide range of spatial scales, from a few Schwarzschild radii of a supermassive black hole to dimensions of kiloparsec-size jet-driven outflows. In addition to supernova remnants, various sources have been suggested to explain data collected on composite galaxies, including multi-messenger neutrino and ultra-high-energy cosmic-ray data. Aims: The closest composite Seyfert-starburst galaxies (NGC 1068, the Circinus galaxy, and NGC 4945) are observed with the High Energy Stereoscopic System (H.E.S.S.) to provide constraints on cosmic-ray populations in these systems. Methods: Data obtained in H.E.S.S. observations have been analyzed to search for VHE gamma-ray counterparts to the GeV gamma-ray signals detected with Fermi-LAT and for potential spectral components in the VHE range. Results: No significant signals have been found in these H.E.S.S. data. Upper limits on the VHE gamma-ray fluxes were applied to constrain theoretical models involving different spectral components.

In this article, we study the impact of self-heating effects (SHEs) and middle of line (MOL) and back-end of line (BEOL) induced parasitics on multi-tier CFET design, where multiple nanosheet devices are vertically stacked. We analyze and compare the 4-tier CFET design with the conventional 2-tier CFET, using TCAD models calibrated to experimental measurements. Additionally, TCAD simulations are used to model and analyze SHE-induced heat distribution and temperature profiles and to extract the detailed parasitic RC network from 3D models of CMOS inverters designed with full MOL and BEOL interconnects. At the device level, the maximum temperature rise (TMAX) caused by SHE in nFET and pFET devices of the 2-tier CFET architecture is 62 K and 74 K, respectively. Due to the increased distance from the substrate heat sink, the upper-tier nFET and pFET devices in the 4-tier design show higher TMAX of 83.5 K and 98.5 K and more heat trapping in the stacked layers. Furthermore, in the 4-tier CFET-based CMOS inverters, the BEOL-induced parasitic RCs are, respectively, 10 and 6.5 times higher in the top-tier than in the 2-tier CFET-based inverters. In the bottom tier, the corresponding parasitic RC elements are 6.26 and 2 times higher, respectively, than in the 2-tier inverters. Finally, compared to the 4-tier design without parasitics, the propagation delay of the top and bottom tier inverters increases by 10% and 8.2%, respectively, due to the interconnect parasitic RCs. For the conventional 2-tier inverter, the corresponding degradation of delay with parasitic RCs is 37.25%.

The transient time correlation function method (TTCF) has emerged as a powerful methodology for accurately probing systems at low shear rates. In the present study, TTCF was used to evaluate the shear rate dependence of the slip length in a high-slip system consisting of water confined between graphene walls at experimentally accessible shear rates, for which classical nonequilibrium molecular dynamics (NEMD) is unfeasible. The corresponding Navier friction coefficient was computed for all shear rates spanning six orders of magnitude and compared with the equilibrium limit. We report for the first time NEMD results obtained at experimentally accessible shear rates using the TTCF approach for a system that has attracted significant interest over the past decades. The slip length calculated with TTCF is in good agreement with previous equilibrium molecular dynamics simulations and experiments. Our aim here is to highlight the extraordinary power of TTCF, particularly for high-slip (low strain-rate) systems, and to verify that equilibrium methods directly match NEMD measurements at experimentally accessible strain rates.

Density functional theory (DFT) is the most promising method for calculating quantum properties of molecules and materials at moderate and large scales. However, commonly used density functional approximations (DFAs) have systematic delocalization error, as demonstrated by underestimated band gaps, over-delocalized charges, and energy level misalignment at interfaces, which limits its quantitative prediction. Extensive efforts, such as the $GW$ approximation to many-body perturbation theory, system-specific tuning of DFA parameters, and correction functionals have been developed to address delocalization error. However, an accurate, efficient, and unified solution to describe total energy, charge density and band structure for both finite systems and materials is still not available. Building on the linear-response localized orbital scaling correction (lrLOSC), we introduce olLOSC: a localized orbital scaling correction with curvature calculated by orbital-free electronic linear response. olLOSC has comparable accuracy to lrLOSC, but is much more computationally efficient. olLOSC corrects delocalization error - especially underestimated gaps, but also the total energy - both in molecules and in materials with small and moderate band gaps, within the same orbital-free approximation. Critically, with a a unified approximation, olLOSC opens the path for robust and efficient DFT applications across molecules, materials, and interfaces.

Shock wave-droplet interactions have been receiving increasing attention due to their relevance in aviation fuel combustion and minimally invasive medical treatments, yet quantifying them experimentally remains a challenge. In this study, we propose a background-oriented schlieren (BOS) technique for quantitative spatiotemporal measurements of shock wave-droplet interaction, employing a novel ray-tracing correction, a synchronization system, and a projected background. Underwater shock waves propagating both inside and outside a millimetric perfluorohexane droplet immersed in water are experimentally measured. The quantified density-gradient and pressure fields are compared with numerical simulations, and the BOS measurements-including sound speeds, the shock-focusing location, and the maximum pressure-are found to be in close agreement with the numerical results. Notably, the technique successfully captures the phase shift before and after shock focusing that had previously only been hypothesized.

Nuclear isotensor spectroscopy as accessible in nuclear double charge exchange (DCE) reactions is indispensable for quantitative studies of lepton number violation as in double beta decay (DBD). For such studies heavy ion double single charge exchange (DSCE) and direct Majorana double charge exchange (MDCE) reactions are discussed. Isotensor two-body transition densities are investigated for the first time. Pion-potentials, mirroring neutrino potentials, and isotensor short range correlations are explored. Lepton DCE (LDCE) reactions on nuclei at accelerators are introduced as a promising new approach to investigate lepton number violation.

In this paper, we consider the elliptic operators $\mathcal{L}_\varepsilon = -\nabla\cdot (A(X/\varepsilon) \nabla )$ with periodic coefficients in a bounded domain $Ω$ without any local smoothness assumption on $A = A(Y)$, where $\varepsilon \ll \text{diam}(Ω)$ is a microscopic scale. Due to the irregularity of the coefficients at $\varepsilon$ scale, we introduce the correct forms of the large-scale nontangential maximal functions for the Dirichlet, Neumann and regularity problems that measure the behaviors of solutions at an $\varepsilon$ distance away from the boundary. The $L^p$ estimates uniform in $\varepsilon$ are established for these nontangential maximal functions for the same and optimal ranges of $p$ as the Laplace operator in the Lipschitz or $C^1$ domains. With some additional regularity assumption on the coefficients, the large-scale estimates combined with the small-scale estimates recover the classical full-scale estimates of the nontangential maximal functions. Our proofs are based on the notion of large-scale $\mathcal{L}_\varepsilon$-harmonic measures, the periodic structure of operators in the transversal direction to the boundaries, and the homogenization tools, including convergence rates and large-scale regularity.

We demonstrate how steepest descent arguments and singularity analysis from analytic combinatorics allow for an accurate description of the behavior of linear numerical schemes -- including the notorious leap-frog scheme -- in presence of stable and unstable boundary conditions in the long-time limit.