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Multi-configuration time-dependent Hartree

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Multi-configuration time-dependent Hartree (MCTDH) is a general algorithm to solve the time-dependent Schrödinger equation for multidimensional dynamical systems consisting of distinguishable particles.

MCTDH can thus determine the quantal motion of the nuclei of a molecular system evolving on one or several coupled electronic potential energy surfaces. It is an approximate method whose numerical efficiency decreases with growing accuracy [1].

MCTDH is suited for multi-dimensional problems, in particular for problems that are difficult or even impossible to solve in conventional ways [citation needed].

Methods

MCTDH

Ansatz

Where the number of configurations is given by the product . The single particle functions (SPFs), , are expressed in a time-independent basis set:

Where is a primative basis function, in general a Discrete Variable Representation (DVR) that is dependent on coordinate [2]. If , one returns to the Time Dependent Hartree (TDH) approach[3]. In MCTDH, both the coefficients and the basis function are time-dependent and optimized using the variational principle.

Equations of Motion

Lagrangian Variational Principle

Where:

Which is subject to the boundary conditions . After integration, one obtains:

McLachlan Variational Principle

Where only the time derivative is to be varied. We can rewrite this norm squared term as a scalar product, and vary the bra and ket side of the product:

Dirac-Frenkel Variational Principle

If each variation of is an allowed variation, then both the the Lagrangian and the McLanchlan Variational Principal turn into the Dirac-Frenkel Variational Principle:

Which simplest and thus preferred method of deriving the equations of motion[2].

ML-MCTDH

Motivation

The original ansatz of MCTDH generates a single layer tensor tree; however, there is a limit to the size and complexity this single layer can handle. This prompted the development of a multilayer (ML)-MCTDH ansatz by Manthe[4] which was then generalized by Vendrell and Meyer[5].

Tensor Tree Formalism

Multiple layers are generated through the creation of a tensor tree of nodes linking the modes (DOFs). Solving the tree layout is an NP-hard problem, but strides have been taken to automate this process through mode correlations by Mendive-Tapia[6].

Example MCTDH tree with l representing layers and q1-6 being the modes.

Ansatz

The generalized ML expansion of Meyer[5] can be written as follows:

Where the coordinates are combined as

Equations of motion

Where the equations of motion are now represented as follows:

The SPF EOMs are formally defined the same for all layers:

Where is a Hermitian gauge operator defined as follows:

Examples of Uses in Literature

NOCl

The first verification of the MCTDH method was with the NOCl molecule. It's size and asymmetry makes it a perfect test bed for MCTDH: it is small and simple enough for its numerics to be manually verified, yet complicated enough for it to already squeeze advantages against conventional product-basis methods.[7]


Water Clusters

The solvation of the hydronium ion is a topic of continued research. Researchers have been able to successfully use MCTDH to model the Zundel [8] and Eigen[9] ions in close agreement with experiment.



Limitations

Approximate Degree of Freedom Allowance for Each Computational Method
Method Degrees of Freedom Possible
Conventional Methods (e.g. TDH) 6
MCTDH 12 [1]
ML-MCTDH 24+ [5]
ML-MCTDH with the Spin-Boson Model 1000+[10]

For a typical input in ML-MCTDH to be run, a node tree, potential energy surface, and equations of motion must be generated by the user [11]. These prerequisites—along with total compute time—soft-cap the size of systems able to be studied with ML-MCTDH; however, advances in neural networks have been shown to address the difficulty of the generation of potential energy surfaces [12]. These issues can also by circumvented by using the spin-boson or other similar bath models that do not pose the same assignment challenges [10].

Software Packages Implementing the MCTDH Method

Package Name Group University Link
Heidelberg MCTDH TC Group Heidelberg University Link
QUANTICS Worth UCL Link
MCTDH-X N/A ETH Zurich Link

Example Usage of the Heidelberg Package for NOCl

Input and Operator File

nocl0.inp nocl0.op
 
RUN-SECTION
relaxation
tfinal= 50.0
tout=   10.0
name = nocl0
overwrite
output    psi=double  timing
end-run-section

OPERATOR-SECTION
opname = nocl0
end-operator-section

SBASIS-SECTION
    rd     =   5
    rv     =   5
    theta  =   5
end-sbasis-section

pbasis-section
#Label    DVR      N         Parameter
    rd    sin     36   3.800    5.600
    rv    HO      24   2.136    0.272,ev  13615.5
    theta Leg     60     0      0
end-pbasis-section

INTEGRATOR-SECTION
 CMF/var =  0.50 , 1.0d-5
 BS/spf =   10 , 1.0d-7
 SIL/A  =   12 , 1.0d-7
end-integrator-section

INIT_WF-SECTION
build
 rd    gauss  4.315  0.0   0.0794
 rv    HO     2.151  0.0    0.218,eV    13615.5
 theta gauss  2.22   0.0   0.0745
end-build
end-init_wf-section

ALLOC-SECTION
   maxkoe=160
   maxhtm=220
   maxhop=220
   maxsub=60
   maxLMR=1
   maxdef=85
   maxedim=1
   maxfac=25
   maxmuld=1
   maxnhtmshift=1
end-alloc-section


end-input

OP_DEFINE-SECTION
title
NOCl S0 surface
end-title
end-op_define-section

PARAMETER-SECTION
mass_rd = 16.1538, AMU
mass_rv =  7.4667, AMU
end-parameter-section


HAMILTONIAN-SECTION
---------------------------------------------------------
modes         |  rd           |  rv           | theta
---------------------------------------------------------
0.5/mass_rd   |  q^-2         |  1            | j^2
0.5/mass_rv   |  1            | q^-2          | j^2
1.0           |  KE           |  1            |  1
1.0           |  1            |  KE           |  1
1.0           |1&2&3  V
---------------------------------------------------------
end-hamiltonian-section

LABELS-SECTION
V = srffile {nocl0um, default}
end-labels-section

end-operator

Output Absorption Spectrum

The absorption spectrum for the NOCl molecule on excitation to the S1 state

Further Reading

  • Meyer, H.-D.; Manthe, U.; Cederbaum, L.S. (1990). "The multi-configurational time-dependent Hartree approach". Chemical Physics Letters. 165 (1). Elsevier BV: 73–78. Bibcode:1990CPL...165...73M. doi:10.1016/0009-2614(90)87014-i. ISSN 0009-2614.
  • Manthe, U.; Meyer, H.‐D.; Cederbaum, L. S. (1992). "Wave‐packet dynamics within the multiconfiguration Hartree framework: General aspects and application to NOCl". The Journal of Chemical Physics. 97 (5). AIP Publishing: 3199–3213. Bibcode:1992JChPh..97.3199M. doi:10.1063/1.463007. ISSN 0021-9606.
  • Beck, M. H.; Jäckle, A.; Worth, G. A.; Meyer, H.-D. (2000). "The multiconfiguration time-dependent Hartree (MCTDH) method: a highly efficient algorithm for propagating wavepackets". Physics Reports. 324 (1). Elsevier BV: 1–105. Bibcode:2000PhR...324....1B. doi:10.1016/s0370-1573(99)00047-2. ISSN 0370-1573.


  1. ^ a b Meyer, Hans-Dieter. "Multi-Configurarion time-dependent Hartree". Theoretical Chemistry Group Heidelberg. Heidelberg University. Retrieved 25 October 2025.
  2. ^ a b Meyer, Hans-Dieter. "Introduction to MCTDH" (PDF). Theoretical Chemistry Group. Heidelberg University. Retrieved 25 October 2025.
  3. ^ McLachlan, A. D.; Ball, M. A. (1964). "Time-Dependent Hartree—Fock Theory for Molecules". Reviews of Modern Physics. 36 (3): 844–855. doi:10.1103/RevModPhys.36.844. Retrieved 25 October 2025.
  4. ^ Manthe, Uwe (2008). "A multilayer multiconfigurational time-dependent Hartree approach for quantum dynamics on general potential energy surfaces". The Journal of Chemical Physics. 128 (16): 164116. doi:10.1063/1.2902982. Retrieved 25 October 2025.
  5. ^ a b c Vendrell, Oriol; Meyer, Hans-Dieter (2011). "Multilayer multiconfiguration time-dependent Hartree method: Implementation and applications to a Henon–Heiles Hamiltonian and to pyrazine". The Journal of Chemical Physics. 134 (4): 044135. doi:10.1063/1.3535541. Retrieved 25 October 2025.
  6. ^ Mendive-Tapia, David; Meyer, Hans-Dieter; Vendrell, Oriol (2023). "Optimal Mode Combination in the Multiconfiguration Time-Dependent Hartree Method through Multivariate Statistics: Factor Analysis and Hierarchical Clustering". Journal of Chemical Theory and Computation. 19 (4): 1144–1156. doi:10.1021/acs.jctc.2c01089.
  7. ^ Manthe, Uwe; Meyer, Hans-Dieter; Cederbaum, Lorenz (1992). "Wave‐packet dynamics within the multiconfiguration Hartree framework: General aspects and application to NOCl". The Journal of Chemical Physics. 97 (5): 3199–3213. doi:10.1063/1.463007. Retrieved 27 October 2025.
  8. ^ Vendrell, Oriol; Gatti, Fabien; Meyer, Hans-Dieter (2007). "Full dimensional (15-dimensional) quantum-dynamical simulation of the protonated water dimer. II. Infrared spectrum and vibrational dynamics". The Journal of Chemical Physics. 127 (18): 184303. doi:10.1063/1.2787596. Retrieved 25 October 2025.
  9. ^ Schröder, Markus; Gatti, Fabien; Lauvergnat, David; Meyer, Hans-Dieter; Vendrell, Oriol (2022). "The coupling of the hydrated proton to its first solvation shell". Nature Communications. 13: 6170. doi:10.1038/s41467-022-33650-w. Retrieved 25 October 2025.
  10. ^ a b Wang, Haobin (2019). "Quantum Phase Transition in the Spin-Boson Model: A Multilayer Multiconfiguration Time-Dependent Hartree Study". The Journal of Physical Chemistry A. 123 (9): 1882–1893. doi:10.1021/acs.jpca.8b11136. Retrieved 25 October 2025.
  11. ^ Meyer, Hans-Dieter. "The Heidelberg MCTDH Package: A set of programs for multi-dimensional quantum dynamics" (PDF). User’s Guide. Heidelberg University. Retrieved 25 October 2025.
  12. ^ Marx, Dominik. "RubNNet4MD". Center for Theoretical Chemistry. Ruhr-Universität Bochum. Retrieved 25 October 2025.