A neural-network surrogate for null geodesics enables faster black hole rendering with gravitational lensing, roughly 15x faster than an Euler-method baseline, but accuracy is measured against that same baseline.
What does a binary black hole merger look like? Classical and Quantum Gravity , 32(6):065002,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
gr-qc 1years
2025 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
Learning Null Geodesics for Gravitational Lensing Rendering in General Relativity
A neural-network surrogate for null geodesics enables faster black hole rendering with gravitational lensing, roughly 15x faster than an Euler-method baseline, but accuracy is measured against that same baseline.