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Related Articles from SNS
Boundary-Layer-Induced Failure of Standard Physics-Informed Neural Networks: A Legendre Wavelet Collocation Benchmark for Singularly Perturbed Transport Problems
Announce Type: new Abstract: Boundary layers provide a demanding test for numerical solvers because the solution may remain almost constant over most of the domain while changing rapidly in a narrow region near the boundary. This paper studies a singularly perturbed one-dimensional transport boundary-value problem with increasing Peclet number $(\mathrm{Pe})$. A local Legendre wavelet collocation method (LWM) is compared with a standard soft-boundary physics-informed neural network (PINN)...
UP Police SI Admit Card 2026 released: Check link and steps to download
The Uttar Pradesh Police Recruitment and Promotion Board (UPPRPB) has released the admit cards for the UP Police Sub-Inspector (SI) Document Verification (DV) and Physical Standard Test (PST) 2026. Candidates who appeared for the written examination held on March 14 and 15, 2026, and were declared successful can now download their admit cards from the official website. The admit card has been made available on the UPPRPB portal.
Creating and Probing Spin-Squeezed States of Molecules
Announce Type: new Abstract: Polar molecules are a promising platform for quantum-enhanced sensing and precision tests of fundamental physics, owing to their strong long-range dipolar interactions, broad sensitivity to electromagnetic fields, and sensitivity to potential physics beyond the Standard Model. However, the creation of metrologically useful entangled states in molecular systems has remained elusive. Here, we report the first observation of a class of metrologically useful...
Measurement of reactor neutrino oscillation with the first JUNO data
Abstract Neutrino oscillations (see refs. 1,2 and references therein), a quantum effect manifesting at macroscopic scales, are governed by lepton flavour mixing angles and neutrino mass-squared differences3 that are fundamental parameters of particle physics, representing phenomena beyond the Standard Model. Precision measurements of these parameters are essential for testing the completeness of the three-flavour framework, determining the mass ordering of neutrinos and probing possible new...
A nuclear clock based on $^{229}$Th
Announce Type: new Abstract: Atomic clocks have made time and frequency the most precisely measured quantities in physics, progressing from microwave standards that realize the SI second to optical clocks that now reach unprecedented levels of precision. A nuclear clock would shift the frequency reference from an electronic transition to the uniquely low-lying, laser-accessible isomeric transition in the $^{229}$Th nucleus, offering a route to compact, robust timekeeping and sensitive tests...
Modeling life beneath our feet: A step towards realistic soil ecology at the landscape scale
Modeling life beneath our feet: A step towards realistic soil ecology at the landscape scale Sadie Harley Scientific Editor Andrew Zinin Lead Editor As soil health becomes a defining goal of the EU Soil Strategy for 2030, researchers at Aarhus University are rethinking how we model what lives beneath our feet. Their new spatially explicit population model for the soil invertebrate Folsomia candida (springtails) marks a significant step beyond standard laboratory testing. For more than 60...
A Geometric Lens on Physics-Aligned Data Compression
arXiv:2606.03279v1 Announce Type: new Abstract: In AI for Science, physics-informed losses are increasingly used to train learned compressors for scientific data, but their rate-distortion implications remain poorly understood. At fixed bitrate, these objectives often improve preservation of a target physical observable while degrading standard reconstruction fidelity. We develop a local geometric theory showing that this tradeoff is governed by the interaction of latent-space sensitivities...
Systematic Gray-Box Identification Methodology for Voltage Source Converters
arXiv:2606.03567v1 Announce Type: new Abstract: This paper introduces a systematic gray-box identification framework for voltage-source converter models based solely on terminal time-series data. The proposed approach combines a physically informed white-box standard model with iterative time-domain calibration to estimate controller parameters that mimic the behavior of the black-box model in electromagnetic transient (EMT) simulations. Unlike conventional frequency-domain identification...
Physics-Informed Machine Learning for Short-Term Flood Prediction
arXiv:2606.04143v1 Announce Type: new Abstract: Accurate flood forecasting is essential for mitigating disaster risks and protecting communities. However, purely data-driven machine learning models often struggle in data-scarce environments and may violate fundamental hydrological principles. Standard Long Short-Term Memory (LSTM) networks can generate physically inconsistent predictions, particularly when extrapolating to extreme weather conditions.
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics
arXiv:2604.01313v2 Announce Type: replace Abstract: High-fidelity simulations and complex inverse problems, such as detector modeling and unfolding, are computationally intensive bottlenecks across subatomic physics, yet essential for accurate physical interpretation. While Conditional Flow Matching (CFM) offers a robust acceleration approach, we demonstrate its standard training loss is fundamentally misleading. Specifically, utilizing a Jefferson Lab Nuclear Physics (NP) kinematic dataset...