EDM
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Initial results of the TRIUMF ultracold advanced neutron source
arXiv:2509.02916v4 Announce Type: replace-cross Abstract: We report the first results on ultracold neutron production from a new spallation-driven superfluid $^4$He (He-II) source at TRIUMF, which is being prepared for a new, precise measurement of the neutron electric dipole moment. A total of $(9.3 \pm 0.8)\times 10^{5}$ ultracold neutrons were observed at a proton beam current of \SI{37}{\uA}, when the target was irradiated for a period of \SI{60}{\s}.
Few-step Cofolding with All-Atom Flow Maps
Announce Type: new Abstract: All-atom generative modeling of 3D biomolecular complexes has emerged as the dominant paradigm for predicting the structure of proteins and protein-ligand systems. Generating structures at the atomic level of fidelity, however, typically requires expensive iterative diffusion rollouts, making both conventional deployment and inference-time search techniques computationally costly. In this paper, we introduce the Denoiser Cofolding All-Atom Flowmap (DeCAF)...
Physics-Informed Modeling and Control of Emergent Behaviors in Robot Swarms
arXiv:2606.01597v1 Announce Type: new Abstract: Robot swarms can exhibit coherent collective behaviors through local perception, limited communication and decentralized decision-making, yet modeling and controlling such emergence remains challenging when behaviors unfold over multiple phases. Here we introduce PhySwarm, a physics-informed micro--macro framework that represents multi-stage swarm emergence as physically constrained density-field evolution coupled to executable robot motion. At...
Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
Announce Type: new Abstract: A fundamental tension exists in the large-step inference of diffusion models via their deterministic probability flow ordinary differential equation (PF-ODE) trajectories, which we identify as the contractivity trap: efficient inference favors large step sizes, while aggressive steps and highly expressive denoisers can undermine contraction-based stability certificates for error suppression. To address this, we propose SteinDiff, a step-wise inference-time...
TabSODA: Tabular Diffusion based Imputation with Skip Pattern Detection and Ordinal Awareness
arXiv:2606.05361v1 Announce Type: cross Abstract: Missing data imputation in large-scale surveys faces two challenges that are not well handled by current tabular diffusion methods. First, \emph{structural skips}, cells made inapplicable by questionnaire design, should not be imputed but are often conflated with item nonresponse. Second, \emph{ordinal} responses encode ordered categories, yet most pipelines treat them as nominal levels through one-hot or analog-bit encodings.