6. Output Files Format

RANK means the rank of process (replica) (0, 1, ...).

6.1. RANK/structure.XXX.vasp

The atomic coordinates for each step are saved in the POSCAR file format of VASP. XXX in the filename corresponds to the index of the step.

Example:

Mg8 Al16 O32
1.0
8.113600 0.000000 0.000000
0.000000 8.113600 0.000000
0.000000 0.000000 8.113600
Al Mg O
16 8 32
direct
0.011208 0.995214 0.998158 Al
0.758187 0.240787 0.499981 Al
... skipped ...
0.746308 0.744706 0.233021 O
0.257199 0.255424 0.771040 O

6.2. RANK/minE.vasp

The lowest-energy structure among the samples in this replica.

6.3. RANK/obs.dat

The temperature and the total energy for each step in units of eV.

Example:

0      0.1034076       -41690.28269769395
1      0.1034076       -41692.06763035158
2      0.1034076       -41692.06763035158
3      0.1034076       -41691.98205990787
4      0.1034076       -41692.74143710456

6.4. RANK/obs_save.npy

The total energy for each step in units of eV in the Numpy binary format. Users can load it as darray by using numpy.load('obs_save.npy').

Example:

$ python -c "import numpy; print(numpy.load('obs_save.npy'))"
[[-41690.28269769]
 [-41692.06763035]
 [-41692.06763035]
 [-41691.98205991]
 [-41692.7414371 ]]

6.5. RANK/kT_hist.npy

The temperature for each step in units of eV in the Numpy binary format. Users can load it as darray by using numpy.load('kT_hist.npy').

Example:

$ python -c "import numpy; print(numpy.load('kT_hist.npy'))"
[0.1034076 0.1034076 0.1034076 0.1034076 0.1034076]

6.6. RANK/Trank_hist.npy

(ONLY for RXMC) The rank (index) of the temperature for each step in the Numpy binary format. Users can load it as darray by using numpy.load('Trank_hist.npy').

Example:

$ python -c "import numpy; print(numpy.load('Trank_hist.npy'))"
[1 1 1 1 1]

6.7. RANK/logweight_hist.npy

(ONLY for PAMC) The logarithm of the Neal-Jarzynski weight for each step in the Numpy binary format.

Example:

$ python -c "import numpy; print(numpy.load('logweight_hist.npy'))"
[0 0 0 0 0]

6.8. RANK/acceptance_ratio.dat

Acceptance ratio of Monte Carlo steps for each temperature. The first column is temperature and the second column is acceptance ratio (number of accepted / number of trials).

6.9. logZ.dat

The logarithm of the partition function, \(\log Z_i/Z_0\) where \(i\) is the index of temperature.

  • The 1st column is temperature \(T_i\).

  • The 2nd and 3rd columns are \(\log Z_i/Z_0\) and its error.

  • The 4th and 5th columms are \(\log Z_i/Z_{i-1}\) and its error.

6.10. <name>.dat

Canonical expectation value \(\langle O \rangle\) and statistical error \(\sigma[O]\) of an observable \(O\) for each temperature. <name> is the name of the observable which is specified by name keyword in [[observer.solver]] section of the input file.

  • The 1st column is temperature \(T_i\).

  • The 2nd and 3rd columns are \(\langle O \rangle\) and its error.

  • The 4th and 5th columns are \(\langle O^2 \rangle\) and its error.

  • The 6th and 7th columns are fluctuation, \(\langle O^2 \rangle - \langle O \rangle^2\) and its error.

    • Note that the heat capacity \(C\) is related to the fluctuation of energy as \(k_B T^2 C = \left[ \langle E^2 \rangle - \langle E \rangle^2 \right]\).