Energy Versus Ecut Plot Plugin

The energy_versus_ecut_plot plugin provides a specialized tool to examine the relationship between the Ecut parameter and energy values reported for a number of simulation datasets. This plugin expects the user to specify a list of UR XML documents by their UUID. These documents can be partitioned into one or more datasets of equal size which will be grouped in the resulting tables and plot. For example, if the comma separated list of UUIDs contains 20 documents and the user specifies 2 datasets then each group of 10 simulations form a dataset. Each dataset is ordered by the value of the Ecut parameter independently and the value of the energy component specified by the user (default total energy) is read. The values of Ecut and the energy component are tabulated in rows corresponding to the UR XML document mapped to a numerical index. Each dataset is tabled individually in the columns of a container table. The same datasets are plotted as different series in the same figure. The plugin gives the user the option to automatically shift the energy values by the minimum of each dataset such that the lowest energy will be zero and all other energies higher relative to that one. This option filters out arbitrary shifts in energy that skew the comparison between otherwise very similar energy sequences.

One example of validation using this plugin is given in the frame below. Two datasets are presented of oxygen dimer simulations with a bond distance of do-o of 1.234A with Ecut values ranging from 20 to 200 in increments of 20 Rydberg. The parameters of each of the 10 simulations in each dataset are equivalent except that one set is run with Abinit and the other with Quantum Espresso. Furthermore, the oxygen pseudopotential originally used with Abinit that is 8o.6.hgh has been translated into the UPF format and used with Quantum Espresso. By comparing these two datasets formed by the sequence of Ecut versus total energy values we can validate that the translation of pseudopotential formats is correct.

By shifting the energies of the two datasets; we can see that the agreement between the two data sequences agree very well for high values of Ecut and diverge slightly for the lower cutoffs. Since the minimum energy value is shifted to zero in both cases; this data point cannot be counted in agreement.