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Explore the application of gausslets for discretizing molecular Hamiltonians in quantum chemistry through this 13-minute conference talk from JuliaCon Global 2025. Learn about gausslets, which are constructed from wavelet transformations on Gaussian functions and offer high localization compared to traditional atomic basis sets. Discover how their locality increases the sparsity of molecular Hamiltonians, improving computational scalability of tensor network methods by diagonalizing two-body interactions and reducing non-zero terms from O(N^4) to O(N^2). Understand the trade-offs involved, as gausslets may require more basis functions to achieve accuracy comparable to atomic basis sets. See how Quiqbox.jl can construct gausslets and augment them with atomic basis sets to reduce overall basis set size while maintaining accuracy and two-body diagonalization. Examine the integration of Quiqbox.jl's analytical integral engine with gausslets since they're built from Gaussian functions. Witness a demonstration of combining Quiqbox.jl and iTensor.jl to create pathways for exploring novel molecular Hamiltonian discretization methods alongside tensor network approaches for electronic structure problems in computational quantum chemistry.
