Spectral Reach
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Related Articles from SNS
Spectral Reach: Understanding Neural Scaling as Progress into the Spectral Tail
Announce Type: new Abstract: Neural scaling laws describe predictable power-law relationships between model size, dataset size, compute, and performance. While these laws guide the development of modern foundation models, the mechanisms underpinning them remain poorly understood, in part due to the absence of scalable analysis tools. To close this gap, we introduce "spectral position": a scalable measure of which eigenvalues of the empirical neural tangent kernel (eNTK) currently drive loss...
Spectral Reach: Understanding Neural Scaling as Progress into the Spectral Tail
Announce Type: cross Abstract: Neural scaling laws describe predictable power-law relationships between model size, dataset size, compute, and performance. While these laws guide the development of modern foundation models, the mechanisms underpinning them remain poorly understood, in part due to the absence of scalable analysis tools. To close this gap, we introduce "spectral position": a scalable measure of which eigenvalues of the empirical neural tangent kernel (eNTK) currently drive...
Echo Enhanced Strong Focusing for Coherent Short-Wavelength Radiation
arXiv:2606.08622v1 Announce Type: new Abstract: Storage-ring-based fully coherent light sources, including steady-state microbunching (SSMB), as well as compact seeded FELs driven by laser plasma accelerators, typically have relatively large intrinsic energy spreads. Extending the spectral reach of these facilities toward the X-ray regime represents a major challenge, as existing seeded schemes require rather extreme parameters to generate appreciable microbunching at high harmonics. In this...
Multilayer Babinet metamaterial to initiate nonreciprocal topological phenomena and generalized Faraday rotation
new Abstract: Multilayers of Babinet complementary periodic structures constructed with miniarrays of spherical plasmonic nanoresonators were optimized to ensure Generalized Faraday Rotation. Nonreciprocal rotation and asymmetric transmission were achieved in spectrally overlapping regions due to the reach physics involving (i) symmetry breaking via coupled localized modes, (ii) Brillouin zone-folding stemmed from constituent sub-lattices forming in-plane twisted coupled loops, (iii)...
Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations
arXiv:2606.03936v1 Announce Type: new Abstract: Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequency content is systematically attenuated, limiting reliability where fine-scale structure matters. Sparse sensor measurements of the field are often available too, offering pointwise accuracy without spectral distortion but covering only a small fraction of the domain. We address this by treating...
Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations
arXiv:2606.03936v1 Announce Type: cross Abstract: Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequency content is systematically attenuated, limiting reliability where fine-scale structure matters. Sparse sensor measurements of the field are often available too, offering pointwise accuracy without spectral distortion but covering only a small fraction of the domain. We address this by...
Neural Spectral Element Methods for stiff multiphysics PDEs with electrochemical transport benchmarks
arXiv:2606.02335v1 Announce Type: cross Abstract: The Neural Spectral Element Method (NSEM) evaluates each network only at fixed Legendre-Gauss-Lobatto quadrature nodes and replaces all derivative calls with precomputed spectral differentiation matrices. The resulting deterministic loss enables limited-memory BFGS (L-BFGS) to reach residuals of 10^-9 to 10^-10. A Kosloff-Tal-Ezer coordinate map resolves electrochemical boundary layers, while a mesh-free neural mortar framework couples...
End-to-End Optimization of Incoherent Imaging for Classification Under Detector-Limited Readout
Announce Type: new Abstract: End-to-end co-optimization of optical front-ends (e.g. metasurfaces) and neural network back-ends has been widely applied to imaging tasks, yet a formalism characterizing when and why such systems outperform conventional lens-based imaging is largely lacking. This paper focuses on object classification, a central imaging task, and asks when end-to-end optimization of a phase mask for incoherent imaging improves performance over a conventional focusing lens. We...
Coincidence-pumping upconversion detector based on passively synchronized fiber laser system
arXiv:2606.04333v1 Announce Type: new Abstract: We experimentally demonstrated a high-performance frequency upconversion detector for telecom-band photons based on a passively synchronized fiber laser system. The involved coincidence pumping technique enabled to spectrally convert the pulsed infrared photons into the visible regime with a conversion efficiency of 72\%. The overall detection efficiency of the upconversion detector reached to 30\% with a low noise equivalent power of...
JA-SIREN: Deterministic Initialization for Sinusoidal Networks via Spectral Matching
Announce Type: new Abstract: Existing implicit neural representation (INR) approaches suffer from stochastic initialization that does not guarantee consistent or high-quality performance across runs, with variations reaching more than 2.5 dB (78%) in image regression. This variation is problematic for scientific computing and simulation, where result reproducibility is crucial. To address this problem, we present Jacobi-Anger Sinusoidal Representation Network (JA-SIREN), a deterministic...