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Transition state optimisation
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There are two algorithms available in DL-FIND to search for transition states:
partitioned rational function optimisation (P-RFO) and the dimer method.

P-RFO
=====

P-RFO is a traditional transition state optimisation algorithm which involves 
a full Hessian calculation to find the transition state mode to follow. It is 
therefore only suitable for the optimisation of small molecules.

The directory ``samples/transition_states/`` contains an example optimisation 
of the transition state for ammonia inversion (``prfo_nh3.nwchem.py``). This
follows a similar pattern to 
the minimisation example, except it searches for a maximum in one dimension 
(i.e. a transition state).

First, we read in the ammonia molecule from disk, and set up the QM calculation
as in previous examples::

 # Read in NH3 geometry from disk
 my_mol = Fragment(coords="nh3.xyz")

 # Set up the QM calculation
 my_theory = NWChem(frag=my_mol, method="dft", functional="blyp", basis="3-21g")

We then call DL-FIND with the option ``algorithm=prfo`` to specify a P-RFO
transition state optimisation::

 # Request an optimisation using DL-FIND
 opt = Opt(theory=my_theory, coordinates="dlc", algorithm="prfo", tolerance=0.0003)
 opt.run()

Here we are using delocalised internal coordinates (``coordinates="dlc"``) rather
than cartesian coordinates for efficiency. The advantages and disadvantages
of the various coordinate systems available in DL-FIND will be discussed in a 
later tutorial.

The dimer method
================

The dimer method defines two connected geometry images which are rotated to
determine the direction to the transition state. This avoids the need to 
calculate a Hessian and is therefore recommended for optimising systems with 
many degrees of freedom.

The dimer method can be chosen by specifying ``dimer=True`` as in the example 
``dimer_nh3.nwchem.py``. The recommended optimisation algorithm for use with 
the dimer method is lbfgs::

 # Request an optimisation using DL-FIND
 opt = Opt(theory=my_theory, dimer=True, coordinates="dlc", algorithm="lbfgs",
           delta=0.01, tolerance=0.0003, trustradius="const")
 opt.run()

You should find that the dimer method converges to the same result as P-RFO,
with very similar final energies and structures (check ``prfo_opt.xyz`` and 
``dimer_opt.xyz``). Due to the approximations made by the dimer method
you may find it takes a few more cycles to converge than P-RFO,
but this is usually outweighed by the cost of calculating the Hessian 
in P-RFO, especially for large systems.

Both the P-RFO and dimer methods require a reasonable initial guess at the 
transition state structure in order to converge efficiently. In the next 
tutorial we will look at a method which only requires knowledge of the reactant 
and product states.