arXiv preprints from January 1, 2026 through September 8, 2026 — 22:18:35 EST
Nitrogen rates for winter wheat are set before the season, under unknown prices and weather. The standard UK advice does not respond to prices, yet recent price swings moved the most profitable rate by tens of kilograms per hectare. Machine learning is often proposed as the fix. However, it is usually judged on prediction accuracy,...
Threshold-driven activation governs a wide range of collective phenomena, yet the microscopic origins of its phase transitions in spatial systems remain unresolved.Here, we show that spatial activation systems undergo multiple distinct routes to phase transitions, controlled by a single parameter---the interaction range.We uncover a...
A known necessary condition for Fisher consistency of the structured support vector machine requires the task loss to be a metric for which every output triple has a common geodesic point. We show that this condition is not sufficient for the canonical coordinate-wise argmax decoder. A four-output unit star admits an exactly optimal...
We determine the strong converse exponent for the entanglement cost of quantum state merging, showing that it is characterized by the optimized $α$-$z$ conditional Rényi entropies with $z=α/2\in[1/2,1]$. This contrasts with the sandwiched conditional Rényi entropies that typically govern strong converse exponents in quantum...
Biological reaction networks often exhibit complex transient behavior that cannot be explained solely by the analysis of steady states or long-term persistence. Existing structural approaches identify persistent system properties and have considered transitions between organizations, but do not provide a general criterion for...
The inverse Lieb lattice has recently emerged as a promising platform for altermagnetism, with several materials with this structure proposed as $d$-wave altermagnetic candidates. Here, we develop a symmetry-based microscopic Hamiltonian for these materials that includes both sublattice and orbital degrees of freedom, going beyond the...
Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal models has made them widely associated with text-to-image applications running on large datacentres. However, vision generative models are equally needed in applications that operate under...
To achieve sustainable intelligent mobility, 6G-empowered robotic vehicles (RVs) require high-fidelity visual perception under stringent bandwidth and energy constraints. Semantic communication offers a spectral-efficient solution but suffers from severe interference in uplink non-orthogonal multiple access (NOMA) RV networks. To...
Gamma-ray bursts (GRBs) have long been considered candidate sources of ultrahigh-energy cosmic rays (UHECRs) due to their large energy release and relativistic outflows. The detection of multi-TeV $γ$-rays from GRB~221009A and its rarity have renewed interest in this connection and motivate considering an additional narrow-jet long...
In 2025, the US government launched an unprecedented series of attacks on its own scientific research groups. A year later GitHub dropped below 90% availability for the first time, while wildfires in Canada, France, Spain, and elsewhere forced researchers from the homes and labs. These events and others have reminded us just how...
Time-reversal-symmetry-broken Weyl semimetals are known to have at least two nodes in their electronic band structure, separated in momentum space and acting as sources and sinks of Berry curvature. This gives rise to a transverse Hall conductivity, known as the anomalous Hall effect (AHE), which, in the simplest two-node picture, is...
This paper explores design considerations for egocentric network layouts in immersive environments, providing fresh empirical insights that enhance egocentric network analysis. An egocentric network focuses on the topological and semantic relationships around a focal node (ego) and its neighboring nodes (alters), targeting local...
We present discussions on the possibility of emerging hidden scale symmetry, as a pseudo-conformal phase in super dense baryonic matter, using the velocity of sound as a criterion for a scale symmetry window in hadronic dense matter. In the density dependent mean field approach à la Brown-Rho scaling, it has been observed that the...
We propose a new technique for dynamic video reconstruction of radio interferometric data using the optimal transport (OT) distance as a regularizer within the regularized maximum likelihood (RML) framework. Compared to other commonly used regularization terms in RML and related prior-based approaches, the OT distance more naturally...
The growing availability of tensor-valued data across multiple institutions creates opportunities for collaborative analysis, but also raises challenges related to data privacy, high dimensionality, and client heterogeneity. This paper introduces a personalized federated tensor regression framework that addresses all three...
Accurate 3D segmentation of cone-beam CT (CBCT) is critical for interventional and radiation therapy applications, yet it remains limited by two compounding challenges: the scarcity of annotated CBCT data and the large domain shift from diagnostic CT. Interventional CBCT exhibits fundamental modality differences from conventional CT,...
Decentralized wireless collectives including vehicular swarms, IoT clusters, and edge AI networks require communication protocols that maintain robustness under dynamic topologies and heterogeneous link quality. While Random Linear Network Coding (RLNC) provides algebraic resilience against packet erasures, its performance degrades...
In medical imaging, it is common to use learned perceptual image patch similarity (LPIPS) to compare images semantically in feature space. Although backbones pretrained on natural images are widely used for LPIPS computation, B-mode ultrasound images possess distinct speckle patterns and acoustic-specific image statistics that are...
Datacenters consume many megawatts of power, and regularly encounter scenarios that require modulating their power draw. These scenarios include datacenter infrastructure failures, power grid failures, grid services, and more, spanning a diverse range of requirements in terms of the power magnitude, the scope of the reduction, the...
Redirecting unmanned aerial vehicles (UAVs) from their intended mission trajectories has been an active area of research. However, existing UAV redirection attacks lack reliability, precision, and covertness for a targeted diversion. They primarily rely on physical capture, communication hijacking, or sensor spoofing. Yet, physical...
Conversational systems, such as duplex speech language models (SLMs), still lack a streaming, accurate, and empathetic memory system as their soul. We introduce VoiceMem, a simple memory architecture with a parallel informational left brain, an emotional right brain, and streaming memory I/O mechanisms. We further build a complete...
Wireless multipath propagation, beamforming, and polarization are central concepts in radio systems, but they are difficult to observe directly because radio-frequency fields are invisible to humans. This paper presents an augmented-reality visualization system that turns phase-coherent WiFi channel measurements from the ESPARGOS...
The modular commutator $J(A,B,C) = i\langle[K_{AB},K_{BC}]\rangle$ extracts the chiral central charge $c_-$ from a single bulk wavefunction of a \emph{gapped} 2d state, where $3J/π=c_-$. Inspired by the recent developments in the field of gapless symmetry-protected topological phases, we ask: what does the modular commutator measure,...
Radio emission from particle air showers is one of the most promising detection techniques to achieve an experiment with a large exposure in ultra-high-energy astroparticle physics. In this regime, above $10^{17}$ eV, the detailed calculation of the radio emission from Monte Carlo particle showers is sufficiently CPU intensive that...
Localized surface plasmons (LSPs) supported by metallic nanostructures exhibit a great tunability of their resonance frequencies and associated spatial field distributions. In particular, nanoscale gaps and sharp corners exhibit promising near-field enhancements for applications such as biochemical sensing and nanoantennas. In this...