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At least 289 records · Page 16Linked to original sources
arXiv2026

Highly Scalable Selectorless Cryogenic Memory Array Using Ferroelectric Josephson Field-Effect Transistors

Scalable memory systems that satisfy the temperature, speed, and energy requirements of cryogenic environments are essential for the development of large-scale quantum computers. They may also benefit high-performance computing and space applications. However, existing cryogenic memory technologies often suffer from limited scalability, low operating speed, and/or high power consumption, restricting the scalability of target applications. Ferroelectric Josephson field-effect transistors (Fe-JoFETs), which combine ferroelectric polarization with the superconducting properties of Josephson junctions, offer a promising solution. The ferroelectric layer enables nonvolatile storage capability, while the Josephson junction supports high-speed, energy-efficient operations. In this work, we leverage Fe-JoFETs to develop a highly scalable, ultra-low-power, nonvolatile cryogenic memory array that does not need additional selector devices for random access. Moreover, the superconducting component of Fe-JoFET provides a binary decision during read, eliminating the need for sensing peripheral circuitry. We first develop a physics-based Verilog-A compact model for Fe-JoFETs and use it to verify the functionality of the proposed memory array. By eliminating both selector and sensing circuitry, the proposed memory architecture offers higher scalability than existing technologies. The ultra-low-power operation of this memory also makes it compatible with strict power budgets of cryogenic applications.

cs.ET↗
arXiv2026

Realignment of ferroelectric nematic by photoinduced electric field

Liquid crystal displays (LCDs) employ thin pixels of a paraelectric nematic, confined between two glass plates with transparent indium tin oxide (ITO) electrodes. A voltage applied to the electrodes realigns the molecules, changing the optical appearance of the pixel. Here we demonstrate that a similar molecular realignment can be triggered by low-power light irradiation when the paraelectric nematic in the cell with ITO electrodes is replaced with a ferroelectric nematic (NF). Irradiation creates an intrinsic electric field that is strong enough to realign the NF but too weak to affect the paraelectric nematic. The extraordinary sensitivity of the ITO/NF pair to light irradiation creates a platform for optical control of ferroelectric polarization and applications in photonics, sensing, smart windows, and beyond.

cond-mat.soft↗
arXiv2026

SkillRefine: Cross-Source Skill Induction and Execution Validation for LLM Agents in Refinery Planning Software

Operating industrial planning software such as AspenTech PIMS (Process Industry Modeling System) requires an LLM agent to combine structural knowledge, procedural knowledge from expert records, and constraints revealed only during execution. These evidence sources are heterogeneous and individually incomplete: documentation describes tables and interfaces but omits task-level coordination, expert CASE records expose multi-table modification patterns without explicit schema grounding, and execution feedback reveals latent constraints only when a plan is executed. We present \textsc{SkillRefine}, a framework that exploits the Documentation--Practice Gap between documented structure and expert practice to extract candidate coordination patterns, ground them against table definitions and COM specifications, and compile them into progressively disclosed skill packages with provenance. The library is then refined through label-free compliance screening, oracle-based match decomposition over table, row, column, and value dimensions, and signal-conditioned trajectory attribution for localized repair. We evaluate \textsc{SkillRefine} on PIMS-Bench, a benchmark built from two AspenTech PIMS demonstration models, using disjoint construction and held-out test tasks. On the held-out test set, \textsc{SkillRefine} achieves absolute component match F1 gains of 14\%--30\% across four LLM backbones, with the largest gains on complex multi-table coordination tasks.

cs.CE↗
arXiv2026

On the support of double Grothendieck polynomials

We prove that the support of every double Grothendieck polynomial is an $M^\natural$-convex set. Our main new tool is a rigidity result for the $K$-classes of multiprojective varieties with rational singularities.

math.AG↗
arXiv2026

Can a Robot Read Braille? - Learning to Adapt Contact via Imitation Learning for Tactile Braille Recognition

For people who are blind, touch provides an essen-tial channel for accessing written information through Braille. Bringing a similar capability to robots requires them not only to recognize tactile patterns, but also to actively establish physical contact that makes those patterns readable. Yet existing robotic Braille readers largely focus on recognition after contact, leaving contact establishment itself insufficiently addressed. We present an adaptive-contact framework for robotic tactile Braille reading that assesses contact quality and physically corrects unsuitable contact before recognition and reconstruc-tion. Multi-Head Policy Learning uses expert-guided contact-adjustment demonstrations to jointly learn contact acceptability and pose corrections. During deployment, the robot iteratively evaluates and re-establishes contact, retaining reliable tactile observations for pose-aware fusion and Braille reconstruction. Across 20 physical Braille plates used for learning and eval-uation, the proposed approach achieves 94.0% tactile quality and 88.6% tactile reconstruction on the ten online-evaluation plates. These results demonstrate the importance of actively establishing readable contact, rather than relying solely on recognition under imperfect tactile observations, for reliable robotic Braille reading.

cs.RO↗
arXiv2026

Electrochemical Growth of Full Volume Meissner Effect Superconducting BKBO

In this work we show the results of electrochemical synthesis of BKBO crystals using three different experimental setup configurations. The setups differ between each other by varying level of control over physical variables and progressing from a two-electrode to a three-electrode configuration using highly oriented platinum counter electrode. By systematic analysis of the temperature dependence of the magnetic susceptibility at the superconducting transition of the collected crystals we observe that an order of magnitude sharper superconducting transition is achieved for the most comprehensive three-electrode setup. In addition, the level of chemical substitution can be controlled by the value of the overpotential versus reference electrode. We demonstrate that with this technique a full volume Meissner effect can be achieved with a sharp transition temperature for the superconducting crystal.

cond-mat.supr-con↗
arXiv2026

Simulation-Efficient Analog Circuit Yield Optimization via Monte Carlo Zeroth-Order Gradient Estimation

Yield optimization under process variation is expensive because each candidate design must be evaluated across many Monte Carlo SPICE samples. The resulting finite-sample yield is also piecewise constant in the design parameters, providing little local information for optimization. We introduce zeroth-order Monte Carlo stochastic gradient descent (ZO-MC-SGD), a black-box method that converts continuous specification margins into stochastic descent directions. Each update evaluates opposite design perturbations under shared process samples, allowing a small simulation batch to estimate a local direction without differentiating SPICE or fitting a global surrogate model. A Spearman rank-correlation test checks that the margin-based loss orders designs consistently with empirical yield. We prove that the estimator is unbiased for a Gaussian-smoothed surrogate and derive variance and sample-complexity bounds with no explicit dependence on process dimension. Across five analog circuit benchmarks with up to 30 design variables and 42 process variables, ZO-MC-SGD reaches a mean yield of 0.95 on four circuits within 50--200 simulations and the empirical yield ceiling on the fifth. Relative to the best of five black-box and learning-based baselines, it reduces the required simulation budget by up to a factor of eight.

cs.CE↗
arXiv2026

Design-Ignoring versus Design-Respecting World Models for Epidemiology

World models for epidemiology learn from records shaped by study designs, including assignment, sampling, measurement, and related processes. A model may therefore reconstruct observed trajectories while learning an intervention contrast that depends on how records were collected. We formalize study design as constraints on a world model latent-world interface, action mechanism, observation likelihood, and target readout. This distinguishes design-respecting models, which encode these constraints, from design-ignoring models, which fit selected records without relating assignment and observation to the intended intervention question. Using a large scale cluster-randomized test-negative trial, we hold the latent structure and fitting settings fixed and compare a design-ignoring case-count model with a design-respecting test-negative observation model. Both models achieve comparable factual reconstruction. Yet across 500 paired resampling experiments at different relative sampling intensity, median contrast changes are substantial for the design-ignoring model, versus merely marginal for the design-respecting model. The same qualitative separation holds when sampling also varies across clusters. Thus, factual reconstruction alone does not establish design alignment; testing whether fitted contrasts preserve design-implied observation-process invariances provides a sharper evaluation.

stat.ME↗
arXiv2026

A Log-Star Comparison Between Expectation Threshold and Fractional Expectation Threshold

We proved a log-star comparison between the expectation threshold $q(\mathcal F)$ and the fractional expectation threshold $q_f(\mathcal F)$ for any nontrivial increasing family $\mathcal F$ on a finite ground set $V$ of size $|V|=N$. Specifically, we show that $$q_f(\mathcal F)\le64\log_2^*(N+2)\,q(\mathcal F),$$ where we define $\log_2^* x$ to be the least integer $k\ge0$ such that applying $\log_2$ repeatedly $k$ times gives a number at most $1$.

math.CO↗
arXiv2026

Long-time reduction for the biharmonic nonlinear Schrödinger equation

In this article, we study the reduction of the one-dimensional biharmonic nonlinear Schrödinger equation to the cubic nonlinear Schrödinger equation in the vanishing higher-order dispersion limit. In the intermediate regularity regime $0<s<2$, where the energy conservation law does not control the $H^s$--norm, we prove the long-time $L^2$--convergence of $H^s$--solutions with an exponential-in-time approximation bound. The argument relies mainly on persistence of regularity. This result provides a simple example of its use in limit problems without relying on higher-order conservation laws.

math.AP↗
arXiv2026

Structure-Guided Masked Autoencoders for Ultra-High Resolution Scientific Image Understanding

Self-supervised pre-training with Vision Transformers, including Masked Autoencoders (MAE), is difficult to apply to gigapixel scientific images. Random masking is poorly matched to the structured, multi-scale morphology of scientific data, while uniform tokenization produces prohibitively long sequences that make $O(N^2)$ attention impractical. We propose SGMA, a structure-guided masked autoencoding framework for ultra-high-resolution scientific images. SGMA couples two components: a content-adaptive quadtree tokenizer that compresses gigapixel images into a fixed-length sequence, and a structure-conditioned masking process that biases reconstruction toward spatially informative regions. To stabilize this process across scales, we introduce Damped Accumulation (DA), which aggregates signal-dependent responses across the tree into a structure canvas used to guide masking. The resulting pre-training task preserves fine microstructure while remaining compatible with standard ViT encoders and MAE-style reconstruction. Across electron microscopy, whole-slide optical microscopy, and X-ray CT datasets, SGMA consistently outperforms MAE baselines. It achieves 95.68% Dice on the 8K x 8K x 28K SpringXCT dataset, improving over the same-architecture MAE baseline by +13.00 points, and 83.21% Dice on the 32K^2 WSI PAIP dataset, improving by +16.84 points, while providing up to a 24.8x inference speedup.

cs.CV↗
arXiv2026

A Large-Scale Empirical Study of Modern Phishing Email Content

Phishing remains one of the most pervasive threats to Internet users, and email remains its predominant delivery channel. Email content is the attack surface of phishing: it is what the victim reads and what automated defenses inspect. Yet the composition of modern phishing content is poorly measured. Prior work has characterized dimensions such as theme, call-to-action (CTA), and impersonation, but not at scale, and their associations and temporal changes remain unclear, owing to small or source-specific corpora, bag-of-words topic models, and a focus on text alone. We present a content-focused measurement study of 2.9M distinct real-world phishing emails collected over 13 months (June 2025 - June 2026) in collaboration with the Anti-Phishing Working Group (APWG). We treat each email as a composite artifact comprising message text and its attachments: 272K images, 143K PDFs, and 57K calendar invitations. Using an LLM pipeline validated against human-annotated samples, we analyze these components along three dimensions (theme, CTA, and impersonation), examine the associations among them, and measure longer-term change against a historical dataset. We find that attackers diversify what they use to deceive but converge on how victims should respond: no theme exceeds 21.3% of emails, while a single CTA, URL navigation, accounts for 73.0%. CTA and impersonation choices are conditioned on theme. Attachments play three roles: images supplement the message text, PDFs substitute for it by carrying the pretext, and calendar invitations reinforce it by replicating interaction endpoints into a persistent medium. Over the longer term, the dominant CTA for invoice-themed phishing shifted from URL navigation to offline communication, rising from 6.7% in 2015 to 46.9% in 2025.

cs.CR↗
arXiv2026

PixSim: a calibrated open-source simulator of instant-payment fraud, recovery and interdiction under analyst capacity constraints

Brazil's Pix settles about 5.9 billion instant, irreversible transfers a month. A fraudulent transfer can be recovered only while the funds remain in a traceable account, and in 2025 the Central Bank's recovery mechanism (MED) returned 9% of accepted contested value. Interdiction therefore has to happen before settlement, by routing each transaction to pass, human review or block, under a finite analyst team and a regulatory hold window. To our knowledge no public simulator jointly models irreversible settlement, a regulated recovery mechanism, downstream fund dispersal and capacity-constrained review. We present PixSim, an open-source simulator of the Pix rail with these elements, calibrated to Banco Central do Brasil open data, with every parameter sourced, calibrated to one published observable, or registered as an assumption. With the model frozen, full-scale runs reproduce the 2025 recovery rate within 0.006 and its decomposition within 0.02; the February-April 2026 window is reported as a misfit and the May 2026 tracing regime as a projection. On a benchmark with a payer-side scorer, four reference policies and ten scenarios, within the simulated mule model: recovery after settlement is constrained by dispersal speed; staffing by the arrival profile cuts a fixed rule's alert expiry from 52% to 2% at constant hours; halving the team removes a fixed threshold-and-block rule's advantage over a queue-aware rule, on loss and on loss plus false-block harm (+0.106 of victim value, positive on all twenty paired seeds), while a reversal at two thirds of the team was not confirmed on independent seeds; and a synthetic scorer of held-out AUC 0.82 cuts lost value by about a quarter. Code and data: https://doi.org/10.5281/zenodo.22948895

cs.LG↗
arXiv2026

Positive scalar curvature on products of noncompact manifolds

We prove that the product of three connected noncompact smooth manifolds without boundary admits a complete metric of uniformly positive scalar curvature. The proof uses the additivity of Morse indices on products and an orientation-free version of Das's open Morse--surgery construction. We also give an example of two open manifolds whose product admits no complete metric of nonnegative scalar curvature.

math.DG↗
arXiv2026

A 2D autocorrelation-based frequency estimator reflecting spatial tissue distribution to improve Ultrasound H-scan tissue characterization

H-scan is a promising quantitative ultrasound technique that estimates the frequency content of backscattered signals and maps the estimated frequencies onto a red/blue color scale to reflect underlying tissue properties. Although it relies on matched filters tuned to different frequencies, the broad spectral bandwidth of ultrasound produces noisy, granular displays. Here, we introduce an adaptive frequency estimator designed to suppress the noise within homogeneous regions while preserving sharpness across tissue boundaries. The method combines 2D autocorrelation with a matched filter. In the first stage, a matched-filter-based estimation yields an a priori map of the spatial distribution of frequencies. The local heterogeneity of these estimates then defines a 2D weighting function that guides a second estimation stage. Drawing on the concept of Loupas's blood velocity estimator, we apply autocorrelation over a 2D spatial kernel to recover the axial frequency components, employing a weighted summation that accounts for the spatial frequency distribution within the kernel. We benchmarked the proposed estimator against conventional approaches, including the short-time Fourier transform, the H-scan matched filter, and standard autocorrelation, using both Field II simulations and in vivo data from human subjects with hepatic steatosis. In simulation, our adaptive estimator reduced the noisy texture in homogeneous regions while retaining clear boundary delineation, whereas the other estimators could achieve only one of these objectives. Applied to the in vivo human liver, the estimator improved H-scan image quality by lowering noise and enhancing the discrimination of steatotic liver from adjacent gallbladder and skin layers.

physics.med-ph↗
arXiv2026

Particle Trajectories Beneath Fully Nonlinear Waves Generated by Horizontal Seabed Motion

We investigate fully nonlinear water waves and fluid-particle dynamics generated by the horizontal motion of a seabed obstacle with prescribed time-dependent velocity. The governing equations are the full Euler equations, formulated in a time-dependent conformal domain that simultaneously maps the moving free surface and seabed onto fixed boundaries. The main contribution of this work is a Lagrangian formulation for computing particle trajectories in the resulting genuinely unsteady conformal domain. We derive a closed-form trajectory system in the canonical domain in which the time dependence of the conformal map is entirely represented by the real and imaginary parts of an analytic function that can be evaluated spectrally from the surface. We apply the formulation to waves generated by horizontal submarine landslide motion and characterize particle displacements throughout the fluid as functions of the initial particle position and Froude number. Our findings identify distinct regions in which particle motion is predominantly associated with the moving seabed, the generated wave, or the combined action of both. The results reveal a transition in the dominant mechanism driving particle motion: at low Froude numbers, particle displacements are primarily associated with the moving seabed, whereas at high Froude numbers the generated wave becomes increasingly dominant, particularly near the free surface and away from the obstacle path.The numerical predictions are benchmarked against laboratory data available in the literature, showing good agreement and providing a quantitative assessment of the model accuracy. Moreover, laboratory topographies beyond those considered here can be readily incorporated into the numerical framework through a Hermite interpolation procedure.

physics.flu-dyn↗
arXiv2026

Comment on "Symmetric Pseudo-Random Matrices"

In 2018, Soloveychik, Xiang and Tarokh considered a pseudo-random symmetric circulant matrix constructed from binary Golomb sequences of length $n=2^m-1$, and claimed a proof that its empirical spectral distribution converges almost surely to the semicircle law as $n$ grows to infinity by the method of moments. In this comment note we show that their argument contains several technical flaws and inappropriate applications of technical lemmas. Instead we demonstrate that the eigenvalues of the matrix are simply a normalized twisted Kloosterman sum varying over the multiplicative character, to which we apply Katz's result directly to establish the asymptotically semicircle spectral distribution deterministically.

math.PR↗
arXiv2026

Threat-Aware Energy-Efficient Deployment for Dynamic UAV Networks: A Multi-Agent RL Approach

Ensuring operational safety in threat-prone environments remains a critical challenge for multi-UAV networks serving as aerial base stations. This paper proposes an efficient framework to maximize global energy efficiency (EE) while promoting safe operation through threat-aware clustering and reward-based safety enforcement. The proposed framework is executed in three steps. First, a threat-aware K-means (TAKM) algorithm determines the minimum required UAVs and computes safe initial placements. Second, an optimal matching stage assigns physical UAVs to these centroids to minimize energy expenditure. Third, a threat-aware multi-agent twin delayed deep deterministic policy gradient (MATD3) algorithm dynamically optimizes trajectories, power, and user associations. Simulation results show that the proposed framework achieves zero observed safety violations in the considered scenarios while achieving superior EE and faster convergence than other learning methods and non-clustering baselines. Compared to heuristic optimization, the proposed framework outperforms the greedy particle swarm optimization (GPSO) and achieves performance comparable to that of the optimized PSO (OPSO), while incurring significantly lower online deployment computational complexity. Furthermore, the proposed framework demonstrates effective generalization to unseen user distributions, large UAV fleets, and different threat geometries, while maintaining zero safety violations.

cs.IT↗