arXiv preprints from January 1, 2026 through September 21, 2026 — 14:51:37 EST
High-resolution digital surface models (DSMs) play an important role in urban analysis, 3D building reconstruction, and infrastructure monitoring, yet their availability remains limited due to the high cost and complexity of data acquisition. In contrast, coarse DSMs from commercial satellite missions are widely accessible, and...
Zero-cost proxies rank architectures cheaply, but their reliability varies across search spaces. We introduce CoRA-NAS (COarse Ranking + Anchor-residual), a two-stage framework combining a static ranking prior with low-cost learning-curve refinement. CoRA-Rank aggregates capacity and structure-at-initialization proxies through an...
The Signal protocol is a prominent messaging protocol that secures communication for billions of users. It powers WhatsApp, the most widely used messaging application worldwide, and the Signal app, popular among privacy-conscious users. Extensive research in the computational and Dolev-Yao settings provides strong formal security...
Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo (MC) Dropout uncertainty quantification, and temperature-scaled calibration for response-level hallucination...
We compute the energy gained by accretion onto a compact star due to matter falling from the inner edge of a thin accretion disk. We employ a controlled slow-rotation expansion based on the Hartle-Thorne metric and find that in neutron stars in general only leading order rotational corrections to the metric, describing frame dragging,...
EFI pairs (Brakerski, Canetti, and Qian, ITCS 2023) and one-way puzzles (Khurana and Tomer, STOC 2024) are the leading candidates for the minimal assumption of quantum cryptography. The first are efficiently preparable quantum states, statistically far yet computationally indistinguishable; the second are classical puzzles, easy to...
Adding noise can make a random quantum circuit look faster without making its unitary dynamics more random. This distinction is especially relevant in modular processors, where local gates randomize each core and scarce inter-core communication must spread that randomness across the full device. In this paper, we study this problem...
We investigate non-invertible selection rules originating from the discrete $H$-gauging of theories with an underlying discrete global symmetry group $G$. To systematically describe these theories, we formulate a general framework for $H$-gauged models that incorporates generalized field transformations. Our approach naturally...
Primordial Black Holes (PBHs) with masses below $\mathcal{O}(10^9)$g occupy an interesting region of parameter space that is largely inaccessible to conventional observations. Despite evaporating before Big Bang Nucleosynthesis (BBN), these PBHs can naturally generate a period of early matter domination in the early Universe. A...
Accurate calibration of electromagnetic field strength in the terahertz (THz) frequency regime remains challenging due to the limited availability of SI-traceable field sensors. Here we demonstrate SI-traceable calibration and performance benchmarking of a commercial photomixer-based THz transmitter-receiver system operating near 204...
Low-dimensional parametric mass models are standard in gravitational-wave population inference, but their rigidity can bias the recovered distribution and the conclusions drawn from it. We present a pipeline in which the source-frame binary-black-hole population in $(z,m_1,m_2)$ is represented by a normalizing flow trained directly...
Geometrically frustrated triangular-lattice antiferromagnets exhibit a delicate competition between magnetic order and quantum spin liquid (QSL) behavior, with the Yb-based delafossite family $A$Yb$X_2$ providing a structurally clean platform for exploring this physics. Here, we report a comprehensive study of single-crystal TlYbS$_2$...
We present FM-JADES-v1, a self-supervised foundation model for James Webb Space Telescope ({\em JWST}) deep-field science, trained with 482,444 objects from the {\em JWST} Advanced Deep Extragalactic Survey (JADES) Data Release 5 using multi-band imaging and the photometric catalog. The shared embedding space is trained without class...
Laser-plasma accelerators (LPAs) sustain accelerating gradients of order $100\,\mathrm{GV/m}$, but routine operation remains difficult: electron beam metrics drift over an operating shift, and the root physical cause is often invisible to the available diagnostics. We formulate LPA operation as a latent state-space model in which...
Mechanistic corrosion models are routinely fitted with four to six parameters to a few measurements and extrapolated across service lifetimes, yet whether the data determine them is rarely tested. We identify a reduced point defect model for the duplex oxide on Nb-stabilized AISI 347 in simulated boiling-water-reactor water from...
We present Tomography-NMR, an open-source Python package that reconstructs quantum density matrices from spectroscopic measurement data. The package implements a complete analysis pipeline for two-qubit quantum state tomography based on the product operator formalism: raw time-domain signals are Fourier-transformed into...
The discovery of high-temperature ferromagnetism in the metallic van der Waals (vdW) system Fe$_N$GeTe$_2$ has brought two-dimensional (2D) magnets into technologically relevant temperature scales. Specifically at N = 5, dilution of magnetic moments by nickel substitution counterintuitively achieves a record high Curie temperature of...
The k$\cdot$p method can be applied directly to first-principles energies and momentum matrix elements, but the resulting models converge slowly with the number of bands and are inexact wherever the underlying Hamiltonian is nonlocal. We show that both limitations can be largely removed by renormalizing the eigenvalue spectra of the...
We develop Entropic Value-at-Risk (EVaR) parity for tempered stable returns. EVaR-based inverse risk parity (IRP) and equal risk contribution (ERC) portfolios are constructed using multivariate normal tempered stable models and independent component analysis with tempered stable components. We derive the corresponding asset-level EVaR...
Classical market-making strategies based on stochastic control, such as the Avellaneda-Stoikov and the Guéant-Lehalle-Fernandez-Tapia (GLFT) extension, provide closed-form quoting rules, but rest on assumptions that break down at realistic microstructure timescales. One of them is that order flow is stationary, while empirical...
We prove that the skew stickiness ratio converges to two at short maturity under local volatility models. This appears to be the first rigorous proof of this limit for a general time-dependent local volatility function. As a by-product, we strengthen the one-half rule of the implied volatility skew by removing uniform ellipticity and...
Modeling the joint distribution of extreme values in high-dimensional financial time series is challenging because extremes are sparse and locally extreme observations are not necessarily extreme relative to their full marginal distribution. To address this, we introduce a time-dependent network Hüsler-Reiss model in which...
Constructing a confidence interval for the difference between two independent binomial proportions involves a nuisance direction that is not identified by the estimand. The one-sample Wilson score interval inverts a scalar score test, but has no direct bivariate analogue isolating the difference: inverting the joint normal...
The Clifford hierarchy is a nested sequence of sets of quantum gates that can be fault-tolerantly performed using gate teleportation within standard quantum error correction schemes. The importance of these gates has motivated numerous studies of their structure. Zeng-Chen-Chuang conjectured in 2007 that all hierarchy gates are...
We show that the inference problem of constraining the parton distribution functions of the proton from deeply inelastic scattering data can be formulated as a linear tensor reconstruction inverse problem. This means that instead of fitting model parameters to the world data, a reconstructive approach to solve a system of coupled...