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https://igit.ific.uv.es/fernando.p.csic.es/sfcf.jl.git
synced 2025-11-30 09:56:53 +01:00
Main script and dirs. Only four correlation functions.
This commit is contained in:
Fernando Pérez Panadero
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commit
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2 changed files with 232 additions and 0 deletions
21
input/sfcf.in
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21
input/sfcf.in
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[Run]
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user = "fperez"
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name = "SFtest_Setup10"
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[Space]
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size = [8,8,8,8]
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blocks = [4,4,4,4]
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phi0 = [-1.047197551196598, 0.0] # Boundary fields for SF
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phiT = [-3.141592653589793, 1.047197551196598]
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cG = 1.0 # Correction for boundaries (SF only)
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[Fermion]
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beta = 6.0 #Used only if cG/csw/ct are not input
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kappa = 0.1
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theta = 0.5
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csw = 1.0
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ct = 0.9
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[Solver]
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tolerance = 1.0e-10
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maxiter = 1000
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211
sfcf.jl
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211
sfcf.jl
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using LatticeGPU
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using TOML
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using TimerOutputs
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using ArgParse
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using CUDA
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function parse_commandline()
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s = ArgParseSettings()
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@add_arg_table s begin
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"-i"
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help = "Input parameters file"
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required = true
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arg_type = String
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"-c"
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help = "Gauge configuration file"
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required = true
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arg_type = String
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end
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return parse_args(s)
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end
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parsed_args = parse_commandline()
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println("--------------------------------------------------")
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println("Reading input file from:", parsed_args["i"], "...")
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params = TOML.parsefile(parsed_args["i"])
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cG = try
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params["Space"]["cG"]
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catch
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try
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println("Using default value for cG")
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1.0 - 0.089*6/params["Fermion"]["beta"]
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catch
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error("Either cG of beta has to be defined in the input file")
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end
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end
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ct = try
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params["Fermion"]["ct"]
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catch
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try
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error("ct not defined")
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println("Using default value for ct")
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catch
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error("Either ct of beta has to be defined in the input file")
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end
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end
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csw = try
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params["Fermion"]["csw"]
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catch
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try
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error("csw not defined")
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println("Using default value for csw")
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catch
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error("Either csw of beta has to be defined in the input file")
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end
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end
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lp = SpaceParm{4}(tuple(params["Space"]["size"]...), tuple(params["Space"]["blocks"]...),BC_SF_ORBI, (0,0,0,0,0,0))
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gp = GaugeParm{Float64}(SU3{Float64},params["Fermion"]["beta"],1.0,(cG,0.0),params["Space"]["phiT"],lp.iL);
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dpar = DiracParam{Float64}(SU3fund,(1/(2*params["Fermion"]["kappa"])) - 4,csw,ntuple(i -> exp((i!=4)*im*params["Fermion"]["theta"]/lp.iL[i]),4),0.0,ct);
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dws = DiracWorkspace(SU3fund,Float64,lp);
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ymws = YMworkspace(SU3,Float64,lp);
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println("Reading gauge field from: ", parsed_args["c"], "...")
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U,_ = read_cnfg(parsed_args["c"])
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Csw!(dws, U, gp, lp)
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println("--------------------------------------------------")
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println("Parameters:")
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println("Lattice size: ", lp.iL)
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println("Phi0 = ", params["Space"]["phi0"])
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println("PhiT = ", params["Space"]["phiT"])
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println("cG = ", gp.cG[1])
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println("kappa = ", params["Fermion"]["kappa"])
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println("theta = ", params["Fermion"]["theta"])
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println("csw = ", dpar.csw)
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println("ct = ", dpar.ct)
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println("tolerance = ", params["Solver"]["tolerance"])
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println("maxiter = ", params["Solver"]["maxiter"])
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println("--------------------------------------------------")
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psi = scalar_field(Spinor{4,SU3fund{Float64}},lp)
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f1 = 0.0
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println("Computing propagators from t=0 to the bulk")
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niter = bndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 1, 1)
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println("CG converged for s=1 and c=1 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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A11 = Array(psi)
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f1 += norm2(bndtobnd(psi, U, dpar, dws, lp))
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niter = bndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 2, 1)
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println("CG converged for c=2 and s=1 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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A21 = Array(psi)
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f1 += norm2(bndtobnd(psi, U, dpar, dws, lp))
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niter = bndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 3, 1)
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println("CG converged for c=3 and s=1 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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A31 = Array(psi)
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f1 += norm2(bndtobnd(psi, U, dpar, dws, lp))
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niter = bndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 1, 2)
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println("CG converged for c=1 and s=2 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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A12 = Array(psi)
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f1 += norm2(bndtobnd(psi, U, dpar, dws, lp))
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niter = bndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 2, 2)
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println("CG converged for c=2 and s=2 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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A22 = Array(psi)
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f1 += norm2(bndtobnd(psi, U, dpar, dws, lp))
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niter = bndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 3, 2)
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println("CG converged for c=3 and s=2 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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A32 = Array(psi)
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f1 += norm2(bndtobnd(psi, U, dpar, dws, lp))
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println("Computing propagators from t=T to the bulk")
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niter = Tbndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 1, 1)
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println("CG converged for s=1 and c=1 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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B11 = Array(psi)
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niter = Tbndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 2, 1)
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println("CG converged for c=2 and s=1 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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B21 = Array(psi)
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niter = Tbndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 3, 1)
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println("CG converged for c=3 and s=1 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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B31 = Array(psi)
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niter = Tbndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 1, 2)
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println("CG converged for c=1 and s=2 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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B12 = Array(psi)
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niter = Tbndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 2, 2)
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println("CG converged for c=2 and s=2 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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B22 = Array(psi)
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niter = Tbndpropagator!(psi, U, dpar, dws, lp, params["Solver"]["maxiter"], params["Solver"]["tolerance"], 3, 2)
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println("CG converged for c=3 and s=2 after ",niter," iterations with absolute residue ", CUDA.mapreduce(x -> norm(x), +, dws.sr))
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B32 = Array(psi)
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println("--------------------------------------------------")
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println("Computing correlators")
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println("Computing fP...")
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file = open(basename(parsed_args["i"])*".fP","w+")
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fP = Vector{Complex{Float64}}(undef,lp.iL[4])
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for t in 1:lp.iL[4]
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fP[t] = 0.0
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for i in 1:lp.iL[1] for j in 1:lp.iL[2] for k in 1:lp.iL[3]
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b,r = point_index(CartesianIndex{lp.ndim}((i,j,k,t)),lp)
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fP[t] += norm2(A11[b,r]) + norm2(A21[b,r]) + norm2(A31[b,r]) + norm2(A12[b,r]) + norm2(A22[b,r]) + norm2(A32[b,r])
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end end end
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println(file,t," ",fP[t])
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end
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flush(file)
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close(file)
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println("Computing fA...")
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file = open(basename(parsed_args["i"])*".fA","w+")
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fA = Vector{Complex{Float64}}(undef,lp.iL[4])
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for t in 1:lp.iL[4]
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fA[t] = 0.0
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for i in 1:lp.iL[1] for j in 1:lp.iL[2] for k in 1:lp.iL[3]
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b,r = point_index(CartesianIndex{lp.ndim}((i,j,k,t)),lp)
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fA[t] += dot(A11[b,r],A13[b,r]) + dot(A21[b,r],A23[b,r]) + dot(A31[b,r],A33[b,r]) + dot(A12[b,r],A14[b,r]) + dot(A22[b,r],A24[b,r]) + dot(A32[b,r],A34[b,r])
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end end end
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println(file,t," ",fA[t])
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end
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flush(file)
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close(file)
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println("Computing gP...")
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file = open(basename(parsed_args["i"])*".gP","w+")
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gP = Vector{Complex{Float64}}(undef,lp.iL[4])
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for t in 1:lp.iL[4]
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gP[t] = 0.0
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for i in 1:lp.iL[1] for j in 1:lp.iL[2] for k in 1:lp.iL[3]
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b,r = point_index(CartesianIndex{lp.ndim}((i,j,k,t)),lp)
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gP[t] += norm2(B11[b,r]) + norm2(B21[b,r]) + norm2(B31[b,r]) + norm2(B12[b,r]) + norm2(B22[b,r]) + norm2(B32[b,r])
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println(file,t," ",gP[t])
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end end end
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end
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flush(file)
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close(file)
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println("Computing gA...")
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file = open(basename(parsed_args["i"])*".gA","w+")
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gA = Vector{Complex{Float64}}(undef,lp.iL[4])
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for t in 1:lp.iL[4]
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gA[t] = 0.0
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for i in 1:lp.iL[1] for j in 1:lp.iL[2] for k in 1:lp.iL[3]
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b,r = point_index(CartesianIndex{lp.ndim}((i,j,k,t)),lp)
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gA[t] += dot(B11[b,r],B13[b,r]) + dot(B21[b,r],B23[b,r]) + dot(B31[b,r],B33[b,r]) + dot(B12[b,r],B14[b,r]) + dot(B22[b,r],B24[b,r]) + dot(B32[b,r],B34[b,r])
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end end end
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println(file,t," ",gA[t])
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end
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flush(file)
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close(file)
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