  We introduce LRT-NG, a set of techniques and an associated toolset that
computes a reachtube (an over-approximation of the set of reachable states over
a given time horizon) of a nonlinear dynamical system. LRT-NG significantly
advances the state-of-the-art Langrangian Reachability and its associated tool
LRT. From a theoretical perspective, LRT-NG is superior to LRT in three ways.
First, it uses for the first time an analytically computed metric for the
propagated ball which is proven to minimize the ball's volume. We emphasize
that the metric computation is the centerpiece of all bloating-based
techniques. Secondly, it computes the next reachset as the intersection of two
balls: one based on the Cartesian metric and the other on the new metric. While
the two metrics were previously considered opposing approaches, their joint use
considerably tightens the reachtubes. Thirdly, it avoids the "wrapping effect"
associated with the validated integration of the center of the reachset, by
optimally absorbing the interval approximation in the radius of the next ball.
From a tool-development perspective, LRT-NG is superior to LRT in two ways.
First, it is a standalone tool that no longer relies on CAPD. This required the
implementation of the Lohner method and a Runge-Kutta time-propagation method.
Secondly, it has an improved interface, allowing the input model and initial
conditions to be provided as external input files. Our experiments on a
comprehensive set of benchmarks, including two Neural ODEs, demonstrates
LRT-NG's superior performance compared to LRT, CAPD, and Flow*.
