*Code author: Alexander Yu. Sokolov and Andrew C. Simmonett*

*Section author: Alexander Yu. Sokolov*

*Module:* *Keywords*, *PSI Variables*, DCFT

Density cumulant functional theory (DCFT) is a density-based *ab initio* theory
that can compute electronic energies without the use of the wavefunction. The
theory starts by writing the exact energy expression in terms of the one- and
two-particle density matrices (OPDM and TPDM):

Here we used Einstein convention for the summation over the repeated indices,
and are the standard one- and two-electron integrals,
and are the elements of the OPDM and TPDM,
respectively. Naively, one might expect that it is possible to minimize the
energy functional in the equation above and obtain the exact energy. This is,
however, not trivial, as the density matrix elements and
cannot be varied arbitrarily, but must satisfy some
conditions that make sure that the density matrices are N-representable, *i.e.*
correspond to an antisymmetric N-electron wavefunction. Unfortunately, no
simple set of necessary and sufficient N-representability conditions are known,
and some of the known conditions are not easily imposed. In addition, the lack
of separability of the density matrices may result in the loss of
size-consistency and size-extensivity. In DCFT one takes a different route and
replaces the TPDM in favor of its two-particle density cumulant:

The one-particle density matrix is separated into its idempotent part and a correction :

The idempotent part of the OPDM corresponds to a Hartree-Fock-like density of non-interacting electrons, while the non-idempotent correction depends on the density cumulant and describes the electron correlation effects. Inserting the above two equations into the energy expression, we obtain:

where the antisymmetrized two-electron integrals and the generalized Fock operator matrix elements were defined as follows:

Energy functional has several important properties. First, the energy is now a function of two types of independent parameters, the idempotent part of OPDM and the density cumulant . As a result, the energy functional is Hermitian, which is important for the evaluation of the molecular properties. The additive separability of the density cumulant guarantees that all of the DCFT methods are size-extensive and size-consistent. Furthermore, the N-representability problem is now greatly simplified, because the idempotent part of the OPDM is N-representable by construction. One only needs to worry about the N-representability of the density cumulant, which is a relatively small part of the TPDM.

In order to obtain the DCFT energy, two conditions must be satisfied:

1) The energy must be stationary with respect to the variation of the idempotent part of the one-particle density matrix . This is achieved by the self-consistent diagonalization of the generalized Fock operator matrix defined above, which introduces the relaxation of the orbitals.

2) The energy must be stationary with respect to the variation of the density cumulant , constrained to the N-representability conditions.

Making the energy stationary requires the solution of the two sets of coupled
equations for the orbital and cumulant updates, respectively (also known as
residual equations). At the present moment three different algorithms for the
solution of the system of coupled equations are available (see section
*Iterative Algorithms* for details).

Publications resulting from the use of the DCFT code should cite contributions
listed *here*.

Currently two DCFT methods (functionals) are available: DC-06 and DC-12. Both
methods use approximate N-representability conditions derived from the
second-order perturbation theory, but differ in the description of the
correlated (non-idempotent) part of the one-particle density
matrix. While in the DC-06 method is derived from the density cumulant
in an approximate way, the DC-12 method derives this contribution exactly, and
therefore takes full advantage of the N-representability conditions. Both DC-06
and DC-12 methods have similar computational cost. However, the DC-12 method
usually exhibits much better numerical stability and can be significantly
cheaper than the DC-06 in the problematic cases as the result of the improved
convergence. For the comparison of the quality of these methods we refer
user to the *recent publications*.

The DCFT functional can be specified by the *DCFT_FUNCTIONAL* option. The
default choice is the DC-06 functional. In addition to the two methods listed
above, *DCFT_FUNCTIONAL* option can be set to CEPA0 (coupled electron
pair approximation zero, equivalent to linearized coupled cluster doubles
method, LCCD). CEPA0 can be considered as a particular case of the DC-06 and DC-12
methods in the limit of zero non-idempotency of OPDM. This option has a limited
functionality and should only be used for the test purposes.

At the present moment DCFT computations can only be run with the unrestricted
orbitals. If the *REFERENCE* option is not specified in the input file,
the PSI4 Python driver will conveniently set it to UHF for the DCFT
computations.

As explained in the *Theory* section, in order to obtain the DCFT energy one
needs to solve the system of coupled equations for the orbitals and the density
cumulant. At the present moment three iterative algorithms for the solution of the
equations are available. The choice of the algorithm is controlled using the
*ALGORITHM* option.

1) Two-step algorithm (can be invoked by setting *ALGORITHM* option to
TWOSTEP and is currently the default). In two-step algorithm the DCFT equations
are solved in macroiterations. Each macroiteration consists of two sets of
microiterations. In the first set the density cumulant equations are solved
iteratively, while the orbitals are kept fixed. After the density cumulant is
converged, the second set of microiterations is performed for the
self-consistent update of the orbitals with the fixed density cumulant. Each
macroiteration is completed by performing the orbital transformation of the
integrals. The convergence of the two-step algorithm is accelerated using the
DIIS extrapolation technique.

2) Simultaneous algorithm (set *ALGORITHM* to SIMULTANEOUS). In this algorithm
each macroiteration consists of a single iteration of the cumulant update
followed by a single iteration of the orbital update and orbital transformation
of the integrals. The macroiterations are repeated until the simultaneous
convergence of the cumulant and the orbitals is achieved. As in the two-step algorithm, the DIIS
extrapolation is used to accelerate the convergence.

3) Quadratically-convergent algorithm (set *ALGORITHM* to QC). The
orbital and cumulant update equations are solved using the Newton-Raphson
method. Each macroiteration of the quadratically-convergent algorithm consists
of a single Newton-Raphson update followed by the orbital transformation
of the integrals. The solution of the Newton-Raphson equations is performed
iteratively using the preconditioned conjugate gradients method, where only the
product of the electronic Hessian with the step vector is computed for
efficiency. The electronic Hessian is build for both the cumulant and orbital
updates and both updates are performed simultaneously. By default the
electronic Hessian also contains the matrix elements that couple the orbitals
and the density cumulant. The computation of these coupling elements increases
the cost of the macroiteration, but usually leads to faster convergence and is
recommended for open-shell systems. If the computation of the coupling elements
is not desired, it can be turned off by setting *QC_COUPLING* to FALSE.
It is important to note that the quadratically-convergent algorithm is not yet fully
optimized and often converges slowly when the RMS of the cumulant or
the orbital gradient is below .

The choice of the iterative algorithm can significantly affect the cost of the
energy computation. While the two-step algorithm requires a small number of
disk-intensive integral transformations, the simultaneous
algorithm benefits from a smaller number of expensive
cumulant updates. As a result, for the small closed-shell systems the two-step
algorithm is usually preferred, while for the larger systems and the molecules with the
open-shell character it is recommended to use the simultaneous algorithm. The
efficiency of the simultaneous algorithm can be greatly increased by avoiding
the transformation of the four-index virtual two-electron integrals
and computing the terms that involve these integrals in the AO
basis. In order to do that one needs to set the *AO_BASIS* option to
DISK. For more recommendations on the choice of the algorithm see
*Recommendations* section.

Analytic gradients are available for the DC-06 method. Gradients are only
available if the *ALGORITHM* option is set to TWOSTEP or SIMULTANEOUS for
the energy computation. Evaluation of the analytic gradients requires the solution of the
coupled response equations. Two algorithms are available for their iterative
solution: two-step (default) and simultaneous. These algorithms are similar to those
described for the orbital and cumulant updates in the *Iterative Algorithms*
section and usually exhibit the similar efficiency. The choice of the algorithm can
be made using the *RESPONSE_ALGORITHM* option. For the DC-12 method the
analytic gradients are not yet available, one has to use numerical gradients to
perform the geometry optimizations.

Minimal input for the DCFT single-point computation looks like this:

```
molecule {
H
H 1 1.0
}
set basis 3-21G
energy('dcft')
```

The `energy('dcft')` call to `energy()` executes the DCFT module, which will first call the SCF module and perform the SCF computation with UHF reference to obtain the guess for the DCFT orbitals. After the SCF is converged, the program will perform the energy computation using the DC-06 method. By default, the two-step algorithm will be used for the solution of the equations. Note that while the default value for the option *REFERENCE* is RHF, this option is set to UHF before the DCFT module is executed. For the DC-06 method one can also request to perform the geometry optimization following the example below:

```
molecule {
H
H 1 1.0
}
set basis 3-21G
optimize('dcft')
```

The `optimize('dcft')` call will first perform all of the procedures
described above to obtain the DC-06 energy. After that the DC-06 analytic
gradients code will be executed to perform the solution of the DCFT response
equations, compute the analytic gradients of the DCFT energy and perform the
geometry optimization.

Here is the list of the recommendations for the DCFT module:

- For the computations of small systems (less than 150 basis functions and high symmetry) the use of the default parameters is recommended, including the choice of the two-step algorithm.
- For large systems (more than 150 basis functions) the simultaneous algorithm
is preferred and can be significantly faster than two-step, as the result of
smaller number of the expensive steps. In addition,
significant savings can be achieved if one sets
*AO_BASIS*option to DISK together with simultaneous algorithm. - In the case when insufficient memory is available, set
*AO_BASIS*option to DISK. This will significantly reduce the memory requirements. However, when used together with the two-step algorithm, this option can significantly increase the cost of the energy computation. - In the case when the oscillatory convergence is observed before the DIIS
extrapolation is initialized, it is recommended to increase the threshold for
the RMS of the density cumulant or orbital update residual, below which the
DIIS extrapolation starts. This can be done by setting
*DIIS_START_CONVERGENCE*option to the value greater than by one or two orders of magnitude (e.g. or ). - If the oscillatory convergence is observed for atoms or molecules with high symmetry, it is recommended to use quadratically-convergent algorithm.
- When using quadratically-convergent algorithm for closed-shell molecules, it
is recommended to set
*QC_COUPLING*option to FALSE for efficiency reasons.