Computing vibrational eigenstates with tree tensor network states (TTNS)
- Creators
- Larsson, Henrik R.
Abstract
We present how to compute vibrational eigenstates with tree tensor network states (TTNSs), the underlying ansatz behind the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) method. The eigenstates are computed with an algorithm that is based on the density matrix renormalization group (DMRG). We apply this to compute the vibrational spectrum of acetonitrile (CH₃CN) to high accuracy and compare TTNSs with matrix product states (MPSs), the ansatz behind the DMRG. The presented optimization scheme converges much faster than ML-MCTDH-based optimization. For this particular system, we found no major advantage of the more general TTNS over MPS. We highlight that for both TTNS and MPS, the usage of an adaptive bond dimension significantly reduces the amount of required parameters. We furthermore propose a procedure to find good trees.
Additional Information
© 2019 Published under license by AIP Publishing. Submitted: 3 October 2019; Accepted: 1 November 2019; Published Online: 25 November 2019. The author is thankful to G. K. Chan, K. Gunst, and R. Haghshenas for helpful discussions. He acknowledges support from the German Research Foundation (DFG) via Grant No. LA 4442/1-1.Attached Files
Published - 1.5130390.pdf
Submitted - 1909.13831.pdf
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Additional details
- Eprint ID
- 100044
- Resolver ID
- CaltechAUTHORS:20191125-143618654
- LA 4442/1-1
- Deutsche Forschungsgemeinschaft (DFG)
- Created
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2019-11-25Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field