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We present how to compute vibrational eigenstates with tree tensor networkstates (TTNSs), the underlying ansatz behind the multilayer multiconfigurationtime-dependent Hartree (ML-MCTDH) method. The eigenstates are computed with analgorithm that is based on the density matrix renormalization group (DMRG). Weapply this to compute the vibrational spectrum of acetonitrile (CH$_3$CN) tohigh accuracy and compare TTNSs with matrix product states (MPSs), the ansatzbehind the DMRG. The presented optimization scheme converges much faster thanML-MCTDH-based optimization. For this particular system, we found no majoradvantage of the more general TTNS over MPS. We highlight that for both TTNSand MPS, the usage of an adaptive bond dimension significantly reduces theamount of required parameters. We furthermore propose a procedure to find goodtrees.

Computing vibrational eigenstates with tree tensor network states (TTNS)