Comparison of the multi-layer multi-configuration time-dependent Hartree (ML-MCTDH) method and the density matrix renormalization group (DMRG) for ground state properties of linear rotor chains
We demonstrate the applicability of the Multi-Layer Multi-Configuration Time-Dependent Hartree (ML-MCTDH) method to the problem of computing ground states of one-dimensional chains of linear rotors with dipolar interactions. Specifically, we successfully obtain energies, entanglement entropies, and...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
19 April 2021
|
| In: |
The journal of chemical physics
Year: 2021, Jahrgang: 154, Heft: 17, Pages: 1-11 |
| ISSN: | 1089-7690 |
| DOI: | 10.1063/5.0047090 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1063/5.0047090 Verlag, lizenzpflichtig, Volltext: https://aip.scitation.org/doi/10.1063/5.0047090 
|
| Verfasserangaben: | Samrit Mainali, Fabien Gatti, Dmitri Iouchtchenko, Pierre-Nicholas Roy, and Hans-Dieter Meyer |
| Zusammenfassung: | We demonstrate the applicability of the Multi-Layer Multi-Configuration Time-Dependent Hartree (ML-MCTDH) method to the problem of computing ground states of one-dimensional chains of linear rotors with dipolar interactions. Specifically, we successfully obtain energies, entanglement entropies, and orientational correlations that are in agreement with the Density Matrix Renormalization Group (DMRG), which has been previously used for this system. We find that the entropies calculated by ML-MCTDH for larger system sizes contain nonmonotonicity, as expected in the vicinity of a second-order quantum phase transition between ordered and disordered rotor states. We observe that this effect remains when all couplings besides nearest-neighbor are omitted from the Hamiltonian, which suggests that it is not sensitive to the rate of decay of the interactions. In contrast to DMRG, which is tailored to the one-dimensional case, ML-MCTDH (as implemented in the Heidelberg MCTDH package) requires more computational time and memory, although the requirements are still within reach of commodity hardware. The numerical convergence and computational demand of two practical implementations of ML-MCTDH and DMRG are presented in detail for various combinations of system parameters. |
|---|---|
| Beschreibung: | Gesehen am 18.10.2021 |
| Beschreibung: | Online Resource |
| ISSN: | 1089-7690 |
| DOI: | 10.1063/5.0047090 |