Spin wave propagation and dynamic control are essential for reconfigurable magnonic and spintronic devices. Here, tunable mode coupling and band hybridisation are demonstrated in a nanopatterned bicomponent magnonic crystal consisting of a Permalloy/heavy metal bilayer patterned with a two dimensional array of Co nanodots. Using the plane wave method and the linearised Landau Lifshitz equation with a field like torque term, we show that inhomogeneous current induced spin torque produces periodic modulation of the magnonic frequency, enabling dynamic control of spin-wave dispersion. A pronounced avoided crossing between localised and propagating Damon Eshbach modes is observed, leading to tunable hybridisation gaps, band deformation, and enhanced mode mixing. The spin torque induced modulation enables controlled mode conversion and reconfigurable hybrid magnonic states, demonstrating efficient electrical tuning of nanoscale spin-wave dynamics.

This paper utilizes the {\it Black Hole Vision} smartphone application to catalyze a pedagogical shift in General Relativity education through the quantitative analysis of simulated black hole imaging. Presented here for the Schwarzschild spacetime, the investigation is designed with a hierarchical modularity suitable for undergraduate students, with an expanded version intended for graduate courses in General Relativity or Relativistic Astrophysics. By transforming the mobile device into an educational relativistic imaging tool, we triangulate the simulated Schwarzschild mass through independent probes and characterize anisotropic coordinate transformations via a Jacobian map. Global numerical consistency is investigated through integrated coordinate length, while the exponential instability of nearly bound orbits is quantified through a measurement of the simulated Lyapunov exponent. Finally, symmetry is constrained through a sub-pixel constraint on eccentricity in the simulated spacetime. By integrating this statistical framework, the paper enables students to explore the distinction between physical signatures and instrumental noise using established metrological protocols.

Altair is an A-type star known to have an appreciably oblate shape owing to its very fast rotation (~300 km/s). Despite of numerous publications on this star, its chemical abundances have been scarcely investigated so far, presumably because of the practical difficulty that spectral lines are considerably broadened by rapid rotation and badly blended with each other. Motivated by this situation, a spectroscopic analysis was conducted to study the photospheric abundances of Altair by using the synthetic spectrum-fitting technique, in order to clarify whether or not any chemical peculiarities exist. The microturbulent velocity was determined to be 2.9 (+/-0.9) km/s by requiring that the metallicity does not show any systematic region-dependence. Then, the abundances of 17 elements (C, N, O, Mg, Al, Si, S, Ca, Sc, Ti, Cr, Mn, Fe, Ni, Zn, Sr, Ba) were derived, where the non-LTE effect was taken into consideration as much as possible. The results revealed considerable region-by-region dispersion (several tenths dex or even more), reflecting the difficulty of reliable abundance determination for such a very rapid rotator. Nevertheless, the differential mean abundances relative to the Sun turned out to fall within -0.5 < [X/H] < +0.3 for all elements without any dependence upon the atomic number. Accordingly, we may conclude that (1) no appreciable anomalies of chemical abundance patterns exist in the atmosphere of Altair, (2) but its global metallicity is likely to be slightly subsolar (~-0.2 dex on the average).

We address the optimal control problems arising from partial differential equations with large discrete dimensional control systems. To obtain reduced order models, we find basis elements from the canonical polyadic (CP) decomposition. Tensor datasets are from snapshots of the large models. Our method to reduce the control system is to use dimensionality reduction approaches through sparse optimization and flexible hybrid methods is to obtain low rank CP tensor basis elements. The reduced optimal control problem leads to reduced state-dependent Riccati Equations which can be solved efficiently.

This article introduces estimators of trend and seasonality for time series of point processes. We assume the point processes follow a temporal or spatial doubly-stochastic Poisson model with log-Gaussian intensity functions. The proposed estimators are computationally simple M-estimators. Their asymptotic distribution is derived, and their finite-sample performance is studied by simulation. As an example of real-data application, we study the patterns of bike demand in the Divvy bike-sharing system of the city of Chicago.

A solution of a Riemann problem for a strictly hyperbolic system of conservation laws is traditionally expected to consist of rarefaction waves, jump discontinuities, and constant states. In this paper, we investigate whether a Riemann solution has this structure when the solution is only assumed to be measurable and essentially bounded. To discriminate continuous and discontinuous features in an $L^\infty$ solution, we introduce one-sided accumulation sets based on local essential images. Supposing that throughout a bounded open interval a solution is continuous in the essential image (ess-im) sense, we prove that it is a rarefaction wave if it is resonant (the characteristic speed equals $x/t$), and otherwise it is constant. Although an ess-im discontinuity might not be a jump discontinuity, we show that all ess-im accumulation states lie on a common Hugoniot locus and have the same speed. Anomalies are possible if there are limit points of ess-im discontinuities, but if the set of ess-im discontinuities is finite, then an $L^\infty$ Riemann solution has bounded variation and is composed of finitely many rarefaction waves, jump discontinuities, and constant states.

Device-independent quantum secret sharing (DI-QSS) provides high security by eliminating the need to trust devices, yet its practical performance is limited by channel loss and noise. This work extends advantage distillation from two-party quantum key distribution (QKD) to three-party DI-QSS, redesigning the corresponding data interaction and verification procedures. The technique is systematically applied to the basic protocol and three active improvement strategies: noise preprocessing, post-selection, and their combination. This approach enhances noise tolerance, reduces the required global detection efficiency threshold, and significantly extends the maximum secure communication distance. Numerical simulations demonstrate that for the basic protocol over fiber, the maximum secure distance increases from 0.16 km to 1.85 km, and the noise tolerance improves from 10.17% to 28.49%. The results show that generalizing advantage distillation to the three-party setting effectively strengthens the protocol's robustness and practicality, enhancing its adaptability to realistic noise and advancing the development of more reliable quantum secret sharing systems.

Time variability is a strong probe of energetic phenomena which occur at small spatial scales, like Active Galactic Nuclei (AGN). We use ALMA observations at 100 GHz executed over a period of 2.5 months to look for time variability in the Antennae galaxies, a prototypical early stage merger galaxy pair, for which there are no previous signatures of an AGN in the optical, infrared or X-ray. Most 100 GHz detections in the Antennae are spatially extended and associated with star forming regions, but two sources in the southern galaxy NGC 4039 are compact. One of these compact sources, S3, is offset by 1 arcsecond in the northeast direction from the stellar peak of NGC 4039, and marginally resolved at 10 parsec resolution. The other source, S4, is co-spatial with the stellar peak of NGC 4039 and unresolved even at a resolution of 4 parsec. We examine the time variability of these two sources using their power spectrum. We find that S4 varies with a characteristic timescale of 13+/-3 days, indicating that the phenomena responsible for the 100 GHz emission is smaller than 0.01 parsecs. By comparing the observed flux of the two sources with various candidate origins, we show that while S3 can be explained either by a young massive stellar cluster or an AGN, S4 is likely to be an AGN that is possibly Compton-thick.

Objective: Conventional urodynamics (UDS) provide critical diagnostic information, but requires invasive dual catheterization and manual labeling of clinically important events. Wireless, catheter-free bladder function tests are becoming available for home use, but only provide vesical pressure (Pves). We developed a machine learning framework that was trained and externally validated on UDS data for automated urological event classification from single-channel (Pves) recordings. Methods: We analyzed 118 annotated UDS traces segmented into 0.8-second Pves intervals. Using the discrete wavelet transform, we extracted 55 statistical features per segment. Consecutive segments (233,338 segments; three classes) sharing the same class, abdominal (ABD), detrusor overactivity (DO), or voiding contraction (VOID), were grouped into events, and median feature aggregation was applied to derive event-level representations. Using an imbalanced dataset, we trained a two-stage multilayer perceptron (MLP): Stage 1 distinguished VOID vs non-VOID, and Stage 2 classified non-VOID into ABD and DO. The model was trained on two independent datasets and externally validated on a third independent dataset. Additional cross-dataset training-validation permutations were performed to assess generalizability. Performance was evaluated using accuracy, F1-macro, sensitivity, specificity, and area under the curve (AUC). Results: Stage 1 (VOID vs. non-VOID) achieved 84% accuracy (balanced accuracy 76%), F1-macro 0.74, and AUC 0.85, while Stage 2 (ABD vs. DO) reached 90% accuracy (balanced accuracy 80%), F1-macro 0.80, and AUC 0.87. Permutation feature importance indicated that most features contributed meaningfully. Conclusion: Our machine learning approach enables accurate automated detection of urological events from Pves, demonstrating feasibility for single-channel monitoring and future ambulatory applications.

The stability number of a forbidden family measures how many different structures are needed to approximate all near-extremal constructions avoiding it. An infinite stability number means that no finite list of structures suffices. We construct a simple explicit $3$-graph whose stability number is infinite. This extends the infinite-stability phenomenon for finite forbidden families, established by Hou--Li--Liu--Mubayi--Zhang, to the single-forbidden setting, and further develops the single-$3$-graph direction of Balogh--Clemen--Luo, in which exponentially many exact extremal constructions coexist with stability.

We prove new results on the additive theory of reversed primes $\overleftarrow{p}$; that is, primes $p$ which are written backwards in a fixed base $b\geq 2$. In particular, we study a variant of Goldbach's conjecture, looking at representations of integers as the sum of primes and reversed primes. We show that: (1) Every large odd integer is the sum of a prime and two reversed primes ($N=p_1+\overleftarrow{p_2}+\overleftarrow{p_3}$). (2) Every large odd integer is the sum of two primes and a reversed prime ($N=p_1+p_2+\overleftarrow{p_3}$). (3) Almost all even integers are the sum of a prime and a reversed prime ($N=p_1+\overleftarrow{p_2}$). (4) All large integers are the sum of a reversed prime and a square-free number ($N=\overleftarrow{p}+η$, $μ^2(η)=1$). To obtain our results, along with associated asymptotics, we apply the Hardy--Littlewood circle method and a novel refinement of the ``Zsiflaw--Legeis" theorem on the distribution of reversed primes in arithmetic progressions. Notably, our variant of the Zsiflaw--Legeis theorem does not require one to fix the digit length unlike previous versions.

The African easterly jet (AEJ) is a prominent circulation feature in the tropical atmosphere. It transports mineral dust and generates easterly waves that serve as seeds for hurricanes. Conventional wisdom holds that the AEJ is in thermal wind balance with the positive meridional temperature gradient over North Africa. Here, using reanalysis data, we show that the negative meridional moisture gradient substantially counteracts the effect of the temperature gradient on density in that balance, diagnostically accounting for a 30\% reduction of the AEJ magnitude. Using CMIP6 data, we further show that this effect of vapor buoyancy on the AEJ strengthens under global warming, highlighting the critical role of the spatial distribution of moisture on large-scale circulation. Analysis of the AEJ in CMIP6 models confirms that some models do not include vapor buoyancy in their governing equations, raising questions about the relevance of their projections of climate change in that region.

We prove, for any W$^*$-probability space $(M,φ)$ where $M$ is a type $\mathrm{III}_1$ factor, any nontrivial, proper closed $F\subseteq \mathbb{R}$, and any nonprincipal ultrafilter $\mathcal{U}$ on $\mathbb{N}$, that the ultrapower $M(σ^φ,F)^{\mathcal{U}}$ of the spectral subspace $M(σ^φ,F)$ is a proper subset of the spectral subspace $M^{\mathcal{U}}(σ^{φ^{\mathcal{U}}},F)$. We discuss the model-theoretic implications of this result.

The effect of a moderate adverse pressure gradient (APG) on the structure of a high-Reynolds-number turbulent boundary layer (TBL) was investigated experimentally using complementary multi-point measurements. Unlike many previous studies, the present work focuses on the wake region and aims to characterise the turbulent motions that are energised by local APG conditions. Simultaneous two-point hot-wire measurements of the streamwise velocity were used to estimate the linear coherence spectrum (LCS), quantifying the wall-normal coherence between a wake-region reference point and the rest of the TBL. LCS-based decomposition of the spectral energy and variance showed that motions coherent with the wake reference account for a significant part of the APG-induced increase at large time scales, but not all of the enhanced energy. The remaining increase is associated with relatively smaller-scale motions that are not correlated with the selected wake location. High-spatial-resolution snapshot PIV measurements were then used to examine this broader range of energetic motions, which are associated with spanwise vortices in the wake region. Spanwise vorticity statistics were evaluated over 0.2 < z/δ < 0.4, where the largest APG-induced change in spectral energy was observed. Under APG, both the mean and variance of spanwise vorticity increased significantly in this region, while swirling-strength distributions confirmed a relative increase in both the population and magnitude of spanwise vortices. Finally, dynamically significant clockwise rotating spanwise vortices were identified using different swirling-strength thresholds. Higher thresholds produced conditionally averaged velocity fields that best captured the key wake-region dynamics, motivating their use for vortex-based conditional averaging in future analyses.

We study lepton-flavor-violating (LFV) decays of a heavy Higgs boson, $H \to μτ$, in the Type-III two-Higgs-doublet model by recasting the CMS search at $\sqrt{s} = 13$ TeV with 35.9 fb$^{-1}$ using fast detector simulation in the mass range 200-450 GeV. We develop a deep neural network (DNN) classifier trained on final-state kinematic variables that, with mass-dependent threshold optimization, reduces the expected 95% CL upper limits on the signal cross section by 42-46% in the 0-jet channel and 36-40% in the 1-jet channel relative to the standard collinear mass ($M_\mathrm{col}$) baseline. We apply SHAP interpretability analysis to identify the visible mass $m_\mathrm{vis}$ as one of the dominant discriminating feature, reflecting the characteristic neutrino momentum fraction of the $τ$ decay. We show that supplementing the $M_\mathrm{col}$ analysis with a simplified mass-dependent pre-selection, $m_\mathrm{vis} < f \cdot m_H$ with $f = 0.7$ (0-jet) and $f = 0.8$ (1-jet), consistently improves the sensitivity over the $M_\mathrm{col}$-only baseline without requiring multivariate infrastructure. In addition, a DNN regression model trained to predict the ratio $m_H/M_\mathrm{col}$ corrects the systematic prediction bias inherent in the collinear approximation, maintaining an absolute mass prediction error below 1 GeV for signals up to 400 GeV and improving the mass resolution by 12% (0-jet) and 21% (1-jet) at $m_H = 450$ GeV. These results demonstrate a clear path toward significantly enhanced sensitivity in LFV Higgs searches at the LHC.

Magic state distillation is a key component of fault-tolerant quantum computation, as it enables the implementation of non-Clifford gates such as the $T$ gate and the $CCZ$ gate via gate teleportation. However, conventional distillation protocols require a large number of logical qubits and introduce substantial spatial and temporal overhead, posing a significant bottleneck for scalable fault-tolerant quantum computation. In this work, we propose a zero-level distillation protocol that efficiently generates a high-fidelity logical $CCZ$ magic state using only physical qubits on a two-dimensional square lattice with nearest-neighbor interactions. Our method leverages the transversal $T/T^\dagger$ operation of the $[[ 8,3,2 ]]$ code to fault-tolerantly encode the state $\overline{CCZ}|+++\rangle$, which is subsequently teleported to three surface-code logical qubits via lattice surgery. To enable teleportation between codes with different distances, we introduce adaptively initialized teleportation (AIT), a tailored initialization procedure for the surface code. Numerical simulations demonstrate that the logical error rate scales as $p_L \simeq 300 \times p^2$ with respect to the physical error rate $p$. For example, the proposed method improves the logical error rate by approximately one and two orders of magnitude at $p = 10^{-3}$ and $p = 10^{-4}$, respectively, compared to conventional seven-$T$-gate approaches. The distillation circuit requires only 22 physical qubits, 3 logical qubits, and a circuit depth of 24, reducing the space-time overhead by a factor of approximately 5-10 compared to previous methods. This result highlights the practicality of $CCZ$-state distillation in early fault-tolerant quantum computation and offers a new direction toward resource-efficient physical-level magic state distillation beyond conventional $T$-state generation.

Let $q$ be an odd prime power, let $n\ge 2$, and let $V\subsetneq \mathbb F_{q^n}$ be a proper $\mathbb F_q$-vector subspace. Given a nonzero quadratic form $Q(X,Y)\in \mathbb F_{q^n}[X,Y]$, we consider the graph $Γ(Q,V)$ that naturally arises from the condition $Q(X,Y)\in V$. We determine all quadratic forms $Q$ for which $Γ(Q,V)$ is undirected for every $V$. Besides the case $Q(x,y)=XY$, studied earlier by the second author, this essentially leads to the forms $X^2\pm Y^2$ and the family $Q_b(X, Y):=X^2+bXY+Y^2, b\ne 0$. We then study connectedness and clique number for the corresponding graphs. Our results reveal a clear contrast between these cases. The graphs $Γ(X^2\pm Y^2, V)$ are well structured, disconnected and their clique number can be as large as $\# V$. On the other hand, the family $Q_b$ seems to yield less structured graphs: the graphs are connected (in fact, of diameter $2$) if $\# V\ge q^{3n/4}$ and, in many cases, their clique number is $o(\# V)$. Our proofs are mainly based on character sums, while requiring a few algebraic and combinatorial ideas. We end the paper with some open problems and remarks, including a short discussion of the complementary case where $q$ is even.

Data leakage from API responses has drawn wide attention. APIs are often not fully regulated, making them easy to abuse. One common solution is to embed watermarks into API responses for traceability. However, existing watermarking methods often require modifying database content or API response data. This forces changes to business system code, and may even disrupt normal business operations because data values are altered. In this paper, we propose an original pluggable watermarking scheme based on a watermark proxy gateway and PEMark (Position Encoding-based Watermarking). The key novelty of our approach is exploiting the inherent permutation redundancy in the ordering of JSON/XML key-value pairs -- an overlooked dimension that carries no semantic information yet provides abundant encoding capacity. First, we forward server responses to the watermark proxy gateway, a design that requires zero modification to existing business systems. Then, we embed a watermark into each API response using position encoding, which reorders keys without altering any data values. To the best of our knowledge, this is the first work to achieve distortion-free API response watermarking via position encoding over a proxy gateway. Our method does not modify any data values, so normal business operations continue seamlessly after watermark embedding. Experimental results show that our framework maintains business usability while ensuring that returned API data is traceable. Compared with current mainstream schemes, our method is robust against tampering and insertion attacks (100\% similarity), and can withstand certain levels of deletion attacks.

Understanding how typhoons respond to localized perturbations in their environmental fields is fundamental to assessing the limits of predictability and exploring the potential for track or intensity intervention. This study develops a dedicated simulation methodology testbed for typhoon sensitivity analysis by integrating the Pangu weather model, a high-precision AI forecasting system, with Proportional-Integral-Derivative (PID) closed-loop techniques. The testbed is constructed with modular functional blocks including a meteorological prediction module, an artificial perturbation input interface, a typhoon quantitative modeling module, and a PID closed-loop test module, implemented via a cross-platform MATLAB/ONNX technical framework. A Single-Input Single-Output (SISO) test system was built, with velocity and thermal perturbations set as the core inputs and typhoon track and intensity as the key output targets, to perform controlled perturbation-response experiments. The experiments reveal the feasible perturbation-response range, the parameter tuning behavior of the PID module, and the energy-scale response characteristics under different perturbation modes, and quantify the input-output coupling relationships of the test system. By constructing this testbed on an operational AI weather forecasting model, this study provides a framework that goes beyond idealized sensitivity studies typically validated only on low-order dynamical models. The testbed offers an expandable platform for investigating typhoon sensitivity to artificial environmental perturbations and provides a foundation for subsequent expansion toward multi-input multi-output architectures and advanced analysis strategies such as nonlinear PID or model predictive control.

We introduce a new measure of robustness for statistical estimators, which we call \emph{empirical sensitivity}. An estimator $\hat θ$ has bounded empirical sensitivity if, with high probability over a dataset $X = (X_1, \dots, X_n) \sim \mathcal{D}^{\otimes n}$, for any dataset $Y$ obtained by modifying at most $ηn$ points in $X$, we have that $\hat θ(Y)$ is close to $\hat θ(X)$. We study bounds on this quantity for the prototypical problem of Gaussian mean estimation. We prove new lower bounds, showing that for any estimator $\hat μ$ which achieves an optimal $\ell_2$-error bound of $O\left(\sqrt{d/n}\right)$, the empirical sensitivity is at least $Ω\left(η+ \sqrt{ηd/n}\right)$. The two terms arise due to obstructions on the mean and variance (via an Efron-Stein argument) of such an estimator. We show that this bound is tight up to logarithmic factors, by employing recent results for robust empirical mean estimation.

We introduce baseSPIDER and SPIDER, private information retrieval (PIR) schemes that embody two technical advancements. The baseSPIDER protocol operates with a single server and a stateful client that performs pre-processing and stores hints for future queries. In this setting, baseSPIDER introduces a new approach that matches the asymptotically optimal communication complexity of state-of-the-art schemes while improving constant factors--an advantage that is particularly significant for databases with large entries. In addition, baseSPIDER offers a conceptually simpler design relative to prior protocols. SPIDER operates over a default database interface and requires no cooperation from the server at any stage. To our knowledge, SPIDER is the first single-server PIR construction of this design, achieving privacy without specialized APIs, auxiliary server state, or protocol-specific interaction beyond conventional indexed access. SPIDER is built via a simple transformation of baseSPIDER to the default server setting, eliminating deployment barriers and enabling immediate applicability to existing systems. This transformation can be applied more broadly to three recent PIR solutions, adapting them for use in the default-server paradigm and yielding solutions of independent interest. SPIDER compares to the resulting modified solutions by exhibiting a simpler design while incurring higher client computational work.

We characterise the particlelike kinematics of charge-carrying topological defects in nematic media via a geometric field theory. This differs from the theory of electromagnetism, with which it is often compared, due to the absence of gauge-invariance. In both approaches, basic defect interactions are governed by a propagator, which depends upon the global topology and/or intrinsic geometry of the surface. For nematic materials, however, the minimisation of the free energy is sensitive to constraints that a gauge invariant theory would otherwise be indifferent to. Hodge theory is used to capture these as `harmonic' excitations, unifying two factors known to additionally affect the kinematics of defects in nematics: relative defect orientations and topological solitons. Perturbations to the form of the energy are also permitted in nematic materials due to gauge \emph{non}invariance. Those that introduce non-linearities in the corresponding Euler--Lagrange equations are shown to result in defect interactions that go beyond pairwise despite the otherwise abelian nature of the underlying U(1) symmetry. We show how this type of induced many-body effect manifests in the cases of non-zero extrinsic curvature and/or elastic anisotropy.

Reinforced random walks are random walks on graphs whose transition probabilities along edges from a vertex are proportional to the weights of those edges, but where the weight of an edge evolves in a way that depends on the past traversals across it. In an edge-reinforced random walk (ERRW), the weight of an edge increases by $1$ whenever that edge is traversed, in either direction. On a finite graph, an ERRW admits a remarkable representation as a random walk in a random environment. The law of the environment is given by the so-called {\em magic formula}, with this law depending on the initial edge weights. This representation provides a natural route for studying statistical properties of ERRWs. This work focuses on various information-theoretic quantities associated with ERRWs on finite graphs, motivated in part by the problem of statistically distinguishing between different ERRW models from observed trajectories. In particular, we study the entropy rate of an ERRW. We also study the Kullback--Leibler divergence (KL divergence) between two ERRW environment laws, and the KL divergence between the corresponding finite-trajectory distributions. Leveraging structural properties of the underlying random environment, we derive an annealed representation of the entropy rate, a closed-form formula for the environment-level KL divergence, and quantitative bounds on the convergence of trajectory-level KL divergence toward environment-level KL divergence. These information-theoretic quantities are motivated by the two-point hypothesis testing problem for ERRW trajectories, and in particular by the associated Stein exponent. We also expect them to play a fundamental role in the study of other testing problems for ERRWs, including identity testing and closeness testing.

Testing the equality of two high-dimensional mean vectors is a fundamental problem in multivariate analysis. While the classical Hotelling's $T^2$ test is optimal in low-dimensional settings, it fails when the dimension $p$ is comparable to or exceeds the sample size $n$. Several extensions, including the Diagonal Likelihood Ratio Test (DLRT), have been proposed under the working independence assumption among variables. However, such an assumption can lead to a substantial loss of power when correlations are present. In this paper, we propose a new test, the Block Independent Likelihood Ratio Test (BILT), which generalizes DLRT by relaxing the working independence assumption to a block independence assumption. We establish its asymptotic normality of the null distribution of the BILT statistic for 'increasing $p$ with small $n$' under mild regularity conditions. We further analyze the asymptotic power of BILT under a local alternatives. Extensive simulation studies show that BILT maintains Type I error control and achieves substantially higher power than DLRT across a wide range of covariance structures. An application to the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset further demonstrates the application of BILT to testing mean differences between two matrix-variate populations.

The ever increasing demand for ML-driven intelligence in a wide spectrum of domains has led to ubiquity of GPUs. At the same time, GPUs are notorious for their power consumption needs and often dominate power allocation in a typical ML datacenter. While datacenter-level power optimizations which focus on collection of GPUs are promising, in this work, we take a different tack -- namely, we take a closer look at power consumption inside a GPU. Specifically, as modern GPUs are comprised of integrated components, we make a case for component-awareness, termed CompPow in this work, for improved power management in modern GPUs. We demonstrate for a variety of ML operations and execution patterns, CompPow has the potential to deliver higher energy efficiency (10%) and even improved performance (5%). We conclude with recommendations on how component-aware software-hardware co-design can extract additional energy efficiency from modern GPUs.

We introduce a utility-driven bounded-confidence model of opinion dynamics in which opinions associated with higher utility exert stronger social influence. In the regime where all agents belong to a single opinion cluster, we derive a stochastic differential equation for the mean opinion and show that its stationary distribution is Gibbs-like, with an effective potential determined by the utility landscape and an inverse temperature controlled by the learning rate and the number of agents. For multimodal utility functions, the dynamics exhibit metastability and spontaneous switching between competing opinion states. The reduced stochastic description also captures the evolution and merging of multiple opinion clusters, in agreement with agent-based simulations.

The ternary transition-metal oxide Fe$_2$Mo$_3$O$_8$ is a polar magnet characterized by a layered structure of magnetic Fe honeycomb lattices and non-magnetic Mo kagome lattices. Whereas previous studies have primarily focused on the chemical substitution at the Fe sites to modulate the magnetic properties, the Mo sites have remained largely unexplored due to the strong spin-singlet trimerization of Mo$^{4+}$ ions. In this study, we investigated the effect of substituting non-magnetic Pb$^{4+}$ and Zr$^{4+}$ ions into the Mo sites to intentionally disrupt the Mo trimers. Our results reveal that the disruption of the Mo spin-singlet state induces active spins within the Mo layer, resulting in the emergence of a ferromagnetic-like behavior that persists even at room temperature. Quantitative analysis that takes into account the weight fraction of the main phase suggests an effective spin $S = 1/2$ state per active Mo ion upon trimer disruption. These findings demonstrate that controlling non-magnetic cluster states within a polar host via chemical substitution is a promising approach for designing room-temperature magnetoelectric materials.

A recent 2023 paper by Massaro et al. introduced the G4Jy-3CRE, a new catalog of the brightest radio sources in the southern hemisphere that serve as a southern equivalent to the Third Cambridge Catalog Revised (3CR). The G4Jy-3CRE catalog selected 264 sources from the GLEAM-4Jy survey based on the same criteria used to select the sources in the 3CR. In this paper, we present new Australian Square Kilometre Array Pathfinder (ASKAP) continuuum imaging of the G4Jy-3CRE catalog. We use the three most recent data releases from the Rapid ASKAP Continuum Survey (RACS), covering the sky south of +30°decl.: RACS-low1, RACS-mid, and RACS-high. Together, these data releases cover a range of frequencies from 600 to 1800 MHz. The RACS surveys have improved spatial resolution and sensitivity over archival surveys at the same frequency, enabling us to classify 173 sources (66% of the sample) with morphologies indicative of the presence of jets, 37 of which did not show jet activity on archival radio maps. We were able to effectively classify FRI/FRII galaxies up to a redshift of z = 1.35. Moreover, we identified six optical counterparts for sources that were either previously unidentified or ambiguous.

We present a simplified method for isolating the edges of a phase object from the edges of an amplitude object using a 4f system with an off-axis q-plate. Instead of the four off-axis shifts of the q-plate required in previous work, we need only two shifts (along +/- x) combined with linear polarizers at 45 degrees and 135 degrees. The number of measurements is reduced by half, potentially doubling the acquisition speed. We derive the theoretical basis, showing that the resulting intensity corresponds to the phase gradient squared, with amplitude-object contributions eliminated. Experiments on two phase-amplitude object samples demonstrate amplitude-edge reduction up to 97.6% and correlation coefficients up to 0.78 (sample 1) and 0.75 (sample 2). In overlapping regions, the phase edge is partially recovered; full recovery would require additional processing such as inverse filtering. This research is useful for biological imaging applications where fast and simple phase-edge isolation is desired.

We investigate the localization of fermionic fields in a five-dimensional braneworld scenario within the framework of modified teleparallel gravity described by a general $f(T,T_G)$ function. Considering a non-minimal coupling between a Dirac spinor and the torsional invariants, we derive the effective Schrödinger-like equations governing the Kaluza-Klein modes. We showed that the contribution of the teleparallel Gauss-Bonnet term significantly modifies the effective potentials and, consequently, the localization properties. The zero-mode analysis reveals that only one chiral component can be localized on the brane, with the degree of confinement depending on the chosen model. In the massive sector, the spectrum is continuous, but resonant states arise due to the internal structure of the potentials. Additionally, we employ information-theoretic measures, such as Shannon entropy and relative probability, to quantify the localization mechanism. Our results show that the torsional modifications induce a nontrivial redistribution of information, exhibiting stronger localization. These findings highlight the role of higher-order torsional terms in shaping fermionic localization and resonance structures in braneworld scenarios.