arXiv preprints from January 1, 2026 through September 23, 2026 — 21:56:15 EST
A new adaptation of the Find Erasures and Decode algorithm from classical to quantum expander codes is presented. It runs in linear time and is parallelizable to logarithmic depth. Compared to Small Set Flip and Small Set Find, the new algorithm avoids the overhead of considering the subsets of stabilizer generators, requires less...
In Abner J. Salgado and Ignacio Tomas. Diagonally implicit Runge-Kutta schemes: discrete energy-balance laws and compactness properties. J. Number. Math., 31(4):313-341, 2023, the notion of $U$-stability for Diagonally Implicit Runge-Kutta (DIRK) schemes was introduced. Here we establish the equivalence between $U$- and $B$-...
The quotient-affine metric gives an intrinsic Riemannian geometry to full-rank correlation matrices, but its geodesic distance has no closed form and we are not aware of an analytic asymptotic null distribution for it. We connect this geometry, introduced in 2019, with Jennrich's 1970 asymptotic test for equality of correlation...
In this paper, we compute the (shifted) Hankel determinants of Catalan-like sequences, which arise naturally from the weighted enumerations of nonintersecting Motzkin meanders. Among these determinant evaluations, one and a half are newly discovered, featuring generic shifted Hankel determinants; two were formulated earlier by Cigler...
Wastewater-based epidemiology has emerged as a valuable tool for monitoring community-level infectious disease dynamics, providing population-wide signals that complement clinical surveillance. However, wastewater measurements are often observed as aggregated values over irregular spatial units. This work develops an approach to link...
Vision-Language Models (VLMs) demonstrate exceptional visual reasoning capabilities, yet their inference costs escalate rapidly with the proliferation of visual tokens. Existing visual token pruning methods exhibit two fundamental limitations. First, most approaches operate exclusively post-vision encoder, leaving the substantial...
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...