arXiv preprints from January 1, 2026 through September 23, 2026 — 13:14:09 EST
The CO luminosity-to-H$_2$ mass conversion factor ($α_{CO}$) remains a debated uncertainty in determining molecular gas masses of high-redshift dusty star-forming galaxies (DSFGs). Dynamical mass constraints have often favored $α_{CO}=0.8$~$M_{\odot}~{(K~km~{s}^{-1}~{pc}^{2})}^{-1}$, whereas dust- and radiative-transfer-based methods...
GRB 230812B is a bright long-duration GRB with a luminous, long-lived afterglow and an AstroSat/CZTI polarization measurement during the prompt phase, enabling a joint study of its prompt spectral evolution, polarization, and broadband afterglow. Time-resolved spectroscopy of the prompt emission shows that during the rising phase, the...
Silicon is an attractive host for scalable quantum photonics, but the absence of bright telecom-band emitters with optically addressable spin states has limited its use for spin-photon interfaces. Here we demonstrate the Al1-center, an aluminum--carbon defect in silicon, as a bright waveguide-integrated single-photon emitter with a...
Intelligence appears under different names in different fields: as data compression in statistics and machine learning, as universal computation in dynamical systems, and as adaptive behavior in agents. Each field carries its own objective, and the two most influential drives often fail in mirror image: novelty search, which seeks...
The Astro2020 Decadal recommended the development of a suite of next generation astronomical observatories spanning the X-ray to near-IR spectrum. These programs require fast, extremely low noise detectors to fulfill their science goals. To address this technology gap, Stanford X-ray Astronomy and Observational Cosmology (XOC) group,...
Single polycyclic aromatic hydrocarbon molecules embedded in organic matrices have proven to be an excellent family of narrow-linewidth quantum emitters. Extending this host-guest setting to van der Waals materials offers the opportunity to combine the preeminent properties of molecular emitters with the access to the versatility of...
We investigate the recombination dynamics of localized defect emission in monolayer WSe$_2$ using time-resolved photoluminescence over the temperature range from 4 to 120 K. The defect emission comprises a dominant sub-nanosecond exponential component and two weak, long-lived power-law channels extending from a few nanoseconds to...
Manganese telluride ($\text{MnTe}$) has recently emerged as a prototypical $g$-wave altermagnet, providing an ideal platform to investigate the non-equilibrium excitations of altermagnetic order. Here, we report simultaneous spatial mapping of the local equilibrium orientation of the Néel vector, $\varphi_L(\mathbf{r})$, alongside the...
The characterization of electron transfer through the emitting surface is of crucial importance for optimizing existing and developing new photocathodes. Here we propose and develop a method for the direct determination of the electron escape probability in high-efficiency semiconductor photocathodes. The proposed method is based on...
The Nancy Grace Roman Space Telescope's Wide Field Instrument (WFI) will observe hundreds of thousands of bright stars across its Core Community Surveys, particularly in the dense stellar fields of the Galactic Bulge Time Domain Survey (GBTDS). Sources brighter than ~17th magnitude will saturate WFI detector pixels in typical survey...
AI weather and climate emulators increasingly incorporate physical principles into their formulation. One approach is to apply hard correctors that modify network outputs so that global mass, water, or energy budgets close. Prior work introduced such training-time correctors in the CREDIT framework and reported reduced precipitation...
The Next Generation Virgo Cluster Survey (NGVS) is a deep, high resolution imaging campaign that used the 1 deg$^2$ MegaCam instrument on the Canada-France-Hawaii Telescope to carry out a comprehensive optical survey of the Virgo cluster, from its core to its virial radius. The NGVS covers a contiguous area of 104 deg$^2$ (8.63...
The Plan B Model was proposed by Allanach et al. (2023) and explains some gross features of the fermion mass spectrum. It also affects the predictions of various observables involving the $b \rightarrow s$ quark-flavour transition. The model predicts a new TeV-scale $Z^{\prime}$ which decays into various different final states. We...
Gold-standard phenotype labels are often unavailable at scale in electronic health record (EHR) studies because they require manual chart review. Weakly supervised phenotyping methods instead use silver-standard labels, such as diagnosis-code counts, natural language processing (NLP) mentions, medication indicators, or laboratory...
Overparameterized models often have continuous parameter symmetries, so different parameters define the same predictor. We show that PAC--Bayesian analysis should be performed on the quotient predictor space: pushing a prior and posterior to the quotient preserves the empirical and population Gibbs risks while removing the nonnegative...
We establish a $\widetildeΩ(d^{5/4}\sqrt T)$ lower bound on the minimax expected regret of stochastic bandit convex optimization of $1$-Lipschitz functions on the Euclidean ball. This presents the first nontrivial regret lower bound that grows faster than $d\sqrt{T}$ for this problem, establishing that stochastic bandit convex...
Two families of polytopes underlie the combinatorics of associative operations. Associahedra and multiplihedra respectively capture the information in the operation itself and in the morphisms that respect that operation. The first applications of these polytopes, from Stasheff, were for modeling homotopy associative spaces and their...
Spatial Dataflow Architectures are an emerging hardware pattern in high-performance computing, whose mesh-connected fixed-memory processing elements are tailored for structured grid kernels with two-dimensional neighborhoods. However, practical multiphysics codes are often computed on unstructured grids, which induce indirect memory...
Implicit Neural Representations (INRs) have become the standard for continuous 2D shape modeling, but they suffer from black-box uneditability, vulnerability to noise, and high parameter counts that severely hinder deployment on edge devices. We introduce Fluid-SDF, a highly compressed, differentiable Constructive Solid Geometry (CSG)...
Barry introduced a central transform of integer sequences and proposed four conjectures concerning the Hankel transforms of central transform of four rational families. We prove these four conjectures. The proofs are unified within a common algebraic framework: we interpret the Hankel determinants as Gram determinants and use a basis...
Mined code corpora are abundant but uncontrolled: a snippet's semantics, surface "messiness," and difficulty are whatever the wild contained; there is no known-optimal reference to grade against; and any public sample may already sit in a model's training set. We present Spaghetti Architect, a tool that mints code datasets with the...
Pneumatic artificial muscles have wide applications in robotics and industrial fields. Conventional pneumatic artificial muscles generate extra radial deformation during axial contraction, which severely wastes available working space. Inspired by the widely adopted drawstring principle in textile products, this paper proposes a novel...
Safety interventions on dual-use knowledge typically choose between destroying hazardous content (e.g., unlearning, filtering) and suppressing it at the output layer (e.g., refusal training); both pay a tax in adjacent-domain competence or over-refusal. We argue that the right operation is conditioning, not reduction: we show that...
Purpose: To develop and validate a deep learning ensemble for estimating adult sex, age, height, and weight from coronal digitally reconstructed radiographs (DRRs) generated from diagnostic CT. Materials and Methods: This retrospective study included 128,621 CT examinations from 80,004 adults at nine institutions in Japan. Three...
Generating closed-loop traffic scenarios that are both realistic and controllable is crucial for evaluating autonomous driving systems, especially under rare safety-critical interactions. Existing learning-based methods often struggle to balance controllability and realism, offering either limited fine-grained control over traffic...