Benchmarking Vibrational Spectra: 5000 Accurate Eigenstates of Acetonitrile Using Tree Tensor Network States
Year: 2025
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide Accurate vibrational spectra are essential for understanding how molecules behave, yet their computation remains challenging, and benchmark data to reliably compare different methods are sparse. Here, we present high-accuracy eigenstate computations for the six-atom, 12-dimensional acetonitrile molecule, a prototypical, strongly coupled anharmonic system. Using a density matrix renormalization group (DMRG) algorithm with a tree-tensor-network-state (TTNS) ansatz, a refinement using TTNSs as basis set, and reliable procedures to estimate energy errors, we compute up to 5,000 vibrational states with error estimates below 0.0007 cm –1 . Our analysis reveals that previous works underestimated the energy error by up to 2 orders of magnitude. Our data serve as a benchmark for future vibrational spectroscopy methods, and our new method offers a path toward similarly precise computations of large, complex molecular systems.
Author: Henrik R. Larsson
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,500
Awards: G2733463057, G3155042411, State-Resolved Vibrational Spectra of Fluxional Protonated Water Clusters via Tensor Network States, MRI: Acquisition of Pinnacles -- Raising Research Computing to New Heights in California's Central Valley, MRI Acquisition: Multi-Environment Research Computer for Exploration and Discovery (MERCED) Cluster, G7589016773
OpenAlex ID: W4409412813