arXiv subjects

Andreas Erbs Hillers-Bendtsen

Publications and source records attributed to Andreas Erbs Hillers-Bendtsen.

3 recordsLinked to original sources

arXiv2026

libterachem.py: Modular development of electronic structure methods with graphical processing units

We present libterachem.py, a Python interface and method framework that facilitates development and prototyping of electronic structure methods while leveraging TeraChem's optimized graphical processing unit (GPU) operations. Direct access to these building blocks and their intermediate quantities allows users to assemble and modify methods within Python while reusing the underlying GPU implementations. A layered architecture, programmable at both the operation level and the method level, supports numerical experimentation, composition of complete electronic structure methods with interchangeable components, and integration with external scientific libraries. We illustrate operation-level use with grid pruning for least-squares tensor hypercontraction and with exchange--correlation functionals supplied through LibXC and by the machine-learned Skala functional. We illustrate method-level use with dispersion corrections, periodic calculations, and geometry optimization with an external optimizer. Python-driven self-consistent-field calculations using libterachem.py incur no significant computational overhead compared to native TeraChem and preserve its multi-GPU scaling. A photoactive yellow protein QM/MM molecular dynamics application further demonstrates throughput comparable to native TeraChem in a workflow composed with external simulation libraries. These results establish libterachem.py as a platform for method development and interoperable molecular simulation that retains the performance of TeraChem's GPU operations.

physics.chem-ph↗

arXiv2026

Non-Negative Least Squares Reweighting and Pruning of Quadrature Grids for Tensor Hypercontraction

Tensor hypercontraction provides an attractive four-center two-electron repulsion integral format that can lower the scaling of many electronic structure methods while only requiring O(N^2) memory. However, in its grid-based least-squares incarnation, tensor hypercontraction requires the tedious design of compact spatial quadrature grids to achieve efficiency and accuracy, representing a bottleneck for widespread application. To simplify grid generation, we devise a reweighting scheme in which the grid weights are optimized to ensure accurate reproduction of the atomic orbital overlap matrix by numerical integration. By casting this fitting task as a non-negative least-squares problem, we obtain a black-box methodology that not only yields robust grids for tensor hypercontraction as well as numerical integration of other integrals but also prunes the grids by zeroing quadrature weights for insignificant points.

physics.chem-ph↗

arXiv2025

Accelerating Hartree-Fock and Density Functional Theory Calculations using Tensor Hypercontraction

With the widespread use of self-consistent field methods, including Hartree-Fock and Density Functional Theory, the implications of accelerating these methods are immense. To this end, we develop a tensor hypercontraction construction with $O(N^3)$ formal scaling that can accelerate self-consistent field calculations. Using tensor hypercontraction, we implement an empirically $O(N^2)$ scaling Fock matrix construction that is 2-4$\times$ faster than existing integral-direct methods, as it avoids the repeated recalculation of two-electron repulsion integrals. In combination with a density-difference ansatz, our tensor hypercontraction self-consistent field implementation tests show errors below $7.0 x 10^{-3} E_h$ for relative energies on protein systems containing up to 3000 basis functions.

physics.chem-ph↗