  Molecular Dynamics (MD) simulations are ubiquitous in cutting-edge
physio-chemical research. They provide critical insights into how a physical
system evolves over time given a model of interatomic interactions.
Understanding a system's evolution is key to selecting the best candidates for
new drugs, materials for manufacturing, and countless other practical
applications. With today's technology, these simulations can encompass millions
of unit transitions between discrete molecular structures, spanning up to
several milliseconds of real time. Attempting to perform a brute-force analysis
with data-sets of this size is not only computationally impractical, but would
not shed light on the physically-relevant features of the data. Moreover, there
is a need to analyze simulation ensembles in order to compare similar processes
in differing environments. These problems call for an approach that is
analytically transparent, computationally efficient, and flexible enough to
handle the variety found in materials based research. In order to address these
problems, we introduce MolSieve, a progressive visual analytics system that
enables the comparison of multiple long-duration simulations. Using MolSieve,
analysts are able to quickly identify and compare regions of interest within
immense simulations through its combination of control charts, data-reduction
techniques, and highly informative visual components. A simple programming
interface is provided which allows experts to fit MolSieve to their needs. To
demonstrate the efficacy of our approach, we present two case studies of
MolSieve and report on findings from domain collaborators.
