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We present an atomic cluster expansion for carbon that increases over existing classical and machine learning capabilities. We show the predictive power of ACE on three fronts, brittle crack propagation in diamond, design of amorphous carbon structures at different densities and temperatures, nucleation and expansion of fullerene clusters under demanding pressure and temperature conditions.
The increasing number of applications that necessitate the resolution of large scale singular value problems has reignited interest in iterative approaches for the SVD. Some promising new ad-vances in large scale iterative technologies are also plagued by slow convergence and precision limits for computing smallest single triplets. PRIMME SVDS is a standalone package that solves a need in production-level software for computing the partial SVD, particularly with preconditioning.
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