Subrelativistic Alternating Phase Focusing Dielectric Laser Accelerators

Kavli Affiliate: Robert L. Byer | First 5 Authors: Payton Broaddus, Thilo Egenolf, Dylan S. Black, Melanie Murillo, Clarisse Woodahl | Summary: We demonstrate a silicon-based electron accelerator that uses laser optical near fields to both accelerate and confine electrons over extended distances. Two dielectric laser accelerator (DLA) designs were tested, each consisting of two […]


Continue.. Subrelativistic Alternating Phase Focusing Dielectric Laser Accelerators

Sub-relativistic Alternating Phase Focusing Dielectric Laser Accelerators

Kavli Affiliate: Robert L. Byer | First 5 Authors: Payton Broaddus, Thilo Egenolf, Dylan S. Black, Melanie Murillo, Clarisse Woodahl | Summary: We demonstrate a silicon-based electron accelerator that uses laser optical near fields to both accelerate and confine electrons over extended distances. Two dielectric laser accelerators (DLA) designs were tested, each consisting of two […]


Continue.. Sub-relativistic Alternating Phase Focusing Dielectric Laser Accelerators

Primordial non-Gaussianities with weak lensing: Information on non-linear scales in the Ulagam full-sky simulations

Kavli Affiliate: Chihway Chang | First 5 Authors: Dhayaa Anbajagane, Chihway Chang, Hayden Lee, Marco Gatti, | Summary: Primordial non-Gaussianities (PNGs) are signatures in the density field that encode particle physics processes from the inflationary epoch. Such signatures have been extensively studied using the Cosmic Microwave Background, through constraining the amplitudes, $f^{X}_{rm NL}$, with future […]


Continue.. Primordial non-Gaussianities with weak lensing: Information on non-linear scales in the Ulagam full-sky simulations

A Neural Scaling Law from Lottery Ticket Ensembling

Kavli Affiliate: Max Tegmark | First 5 Authors: Ziming Liu, Max Tegmark, , , | Summary: Neural scaling laws (NSL) refer to the phenomenon where model performance improves with scale. Sharma & Kaplan analyzed NSL using approximation theory and predict that MSE losses decay as $N^{-alpha}$, $alpha=4/d$, where $N$ is the number of model parameters, […]


Continue.. A Neural Scaling Law from Lottery Ticket Ensembling

A Neural Scaling Law from Lottery Ticket Ensembling

Kavli Affiliate: Max Tegmark | First 5 Authors: Ziming Liu, Max Tegmark, , , | Summary: Neural scaling laws (NSL) refer to the phenomenon where model performance improves with scale. Sharma & Kaplan analyzed NSL using approximation theory and predict that MSE losses decay as $N^{-alpha}$, $alpha=4/d$, where $N$ is the number of model parameters, […]


Continue.. A Neural Scaling Law from Lottery Ticket Ensembling

View-Independent Adjoint Light Tracing for Lighting Design Optimization

Kavli Affiliate: Michael Wimmer | First 5 Authors: Lukas Lipp, David Hahn, Pierre Ecormier-Nocca, Florian Rist, Michael Wimmer | Summary: Differentiable rendering methods promise the ability to optimize various parameters of 3d scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this paper, we introduce […]


Continue.. View-Independent Adjoint Light Tracing for Lighting Design Optimization