# Preparing the PARAMS file

Here we provide a standard PARAMS file for CT-QMC calculation for two-particle Green’s functions for Nickel at $\beta$=50 (eV$^{-1}$) which should be run on at least 1000 cores for a day to produce high quality data over all energies.

OffDiagonal  real
Sig  Sig.out
Gf  Gf.out
mode GH
SampleVertex 100
nOm 2
Delta  Delta.inp
cix  actqmc.cix
Nmax  3000         # Maximum perturbation order allowed
nom  200          # Number of Matsubara frequency points sampled
exe  ctqmc        # Name of the executable
tsample  50       # How often to record measurements
Ed [ -26.407760, -26.407519, -27.011761, -26.407397, -27.011682, -25.662041, -25.662114, -26.272431, -25.662012, -26.272482] # Ed: Eimp-Edc for PARAMS
M  80000000     # Total number of Monte Carlo steps per core
Ncout  2000000            # How often to print out info
PChangeOrder  0.9         # Ratio between trial steps: add-remove-a-kink / move-a-kink
mu   26.407760 # mu = -Eimp[0] for PARAMS
warmup  5000000           # Warmup number of QMC steps
sderiv  0.02      # Maximum derivative mismatch accepted for tail concatenation
aom  10           # Number of frequency points used to determin the value of sigma at nom
U    4.0
J    0.3
nf0  8.0
beta 50.0

If you have run CTQMC with this PARAMS file, you have in your local directory a new file named tvertex.dat. It has stored the two-particle Green’s functions for Nickel. I shall explain to you the data format now. So now we want to have the local Green’s functions and the non-local Green’s functions. These three quantities are inputs to the BSE. So for that, we want to run lmfdmft in a speecial mode called gprt:mode=3 to produce the loca and non-local Green’s functions.

### Producing local and non-local Green’s functions:

cp Sig.out sig.inp
lmfdmft ni -vnk=12 --rs=1,0 --ldadc=28.95 -job=1 --gprt:mode=3:nom=100 --fullg

This produces two files named gloc.ni and gkloc.ni. Suscept.py, the script that solved the BSE and produces the dynamic momentum resolved Susceptibilities, reads them. It would also look for a file with the k-list and a file with the Q-list. The k-list is the same k-grid information on which gkloc.ni is written. And Q-list file contains the Q-grid on which you want to find the susceptibilities $\chi(Q,\omega)$.

The input files and their paths are identified in the suscept.in. You can have the input files from here this link. The suscept.in file looks like below:

suscept.klist     # filename with k-list
suscept.qlist     # filename with Qlist
rmesh.dat      # real axis mesh
./G_k1r         # file with real axis k-dependent Gren's function
./G_local1r     # file with real axis local Gren's function
./chi0_real.     # name of the Bubble on real axis
gkloc.ni         # imaginary axis k-dependent Green's function
gloc.ni          # imaginary axis local Green's function
./tvertex.dat    # ctqmc local vertex function
50            # inverse temperature for bose function in Sq(omega)

Now, copy all essential files to a directory for Susceptibility calculations and launch Suscept.py to solve BSE:

mkdir suscept
cp *.klist *.qlist tvertex.dat gkloc.ni gloc.ni suscept.in suscept
cd suscept
Suscept.py suscept.in

You can find a good vertex from here and also other input files from this link this link:

mkdir good_vertex
cp ni-sus-inp/* good_vertex
cd good_vertex
cp /home/cseg/scarf705/ni-suscept/tvertex.dat .

Here are our cuprates results published in this paper . You should be able to reproduce the $Nd_{2}CuO_{4}$ results with the input files and the script. You can copy a directory with all converged results for NCO and run the script to see if the results match with what we show in our paper.

cp -r /home/cseg/scarf705/*.tar.gz .