lenscape : Fast, High-resolution Δ χ 2 Maps of Microlensing Events

Abstract Planetary microlensing analyses rely on Δ χ 2 maps across the binary-lens separation s and mass ratio q to locate degenerate solutions and bound parameter uncertainties. Because every grid point requires a full light-curve optimization with finite-source magnifications, constructing these maps is often the primary computational bottleneck in event modeling. Here I present lenscape ( https://github.com/hippke/lenscape ), an open-source Python package that accelerates Δ χ 2 mapping and suppresses local-minimum artifacts through multi-stage neighbor propagation and adaptive contour refinement. Applied to the planetary event MOA-2022-BLG-091, lenscape reproduces the published 50 × 50 map in 14 minutes and generates a 400 × 400 map in under two hours on a desktop computer.