The PIAA-ZWFS, optimized with differentiable modeling and Bayesian design, closes the gap to the fundamental wavefront sensing limit by a factor of 10 versus conventional ZWFS in photon-limited simulations.
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11 Pith papers cite this work. Polarity classification is still indexing.
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astro-ph.IM 2 cs.AI 2 cs.RO 2 astro-ph.CO 1 cond-mat.mtrl-sci 1 cs.LG 1 gr-qc 1 physics.comp-ph 1roles
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RAM is a morphology-conditioned implicit neural representation trained on 3e10 forward-kinematics samples that serves as a fast, differentiable surrogate for pose reachability and generalizes to unseen morphologies while accounting for self-collisions.
AMIGO is an end-to-end differentiable forward model of JWST AMI that corrects detector systematics to recover high-precision astrometry and detect close high-contrast companions.
Numerical polology framework samples coupling space to discover ghost-free tensor field theories up to rank three for cosmology, then applies resulting priors to black hole superradiance, dynamical dark energy, and GW data.
Relaxation techniques applied after each time step to IMEX Runge-Kutta schemes ensure that fully discrete Schrödinger-Poisson systems conserve mass and satisfy energy balance equations up to rounding errors.
AFSAT realizes FastFourierSAT as a production GPU solver for heterogeneous symmetric pseudo-Boolean SAT via JAX-compiled continuous local search, with tailored DFT for stability and near-linear multi-accelerator scaling.
Source-consistent warp shells fail energy conditions at the source-vacuum boundary in all examined constructions and parameter scans.
A nonlinear latent encoder plus linear latent decoder learns cross-coupled, history-dependent, and nonstationary residual dynamics for aerial manipulators, supporting online Bayesian adaptation and improved real-time MPC tracking.
Empirical study of parallel continuous local search for SAT finds redundant constraints can slow convergence, CLS works as a hybrid sub-solver, and search stabilizes quickly due to saddle-dense objectives.
Curvature-aware optimizers such as natural gradient and self-scaling BFGS/Broyden accelerate PINN convergence and accuracy on PDEs including Helmholtz, Stokes, Burgers, and Euler equations plus stiff ODEs, with new model formulations and batched scaling.
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Efficient High-order Mass-conserving and Energy-balancing Schemes for Schr\"odinger-Poisson Equations
Relaxation techniques applied after each time step to IMEX Runge-Kutta schemes ensure that fully discrete Schrödinger-Poisson systems conserve mass and satisfy energy balance equations up to rounding errors.