# julia并行问题

Running 8 processes
Unhandled Task ERROR: On worker 8:
UndefVarError: #cut_n not defined

``````using ProgressMeter
using Distributed
@everywhere using SharedArrays, LinearAlgebra

@everywhere function annihilation(n_max::Int64
)::Tuple{Matrix{Float64}, Matrix{Float64}}
a = diagm(1 => sqrt.(1:n_max-1))
c = a'
return a, c*a
end

@everywhere function ham(z::Int64, mu::Float64, t::Float64,
phi::Float64, n_max::Int64, u::Float64)::Matrix{Float64}
a, n= annihilation(n_max)
h0 = u/2 .* n * (n - diagm(ones(n_max))) - mu .* n
h1 = -z .* t .* phi .* a
h = h0 + h1 + h1'
return h
end

@everywhere function cut_n(z::Int64, mu::Float64, t::Float64, psi::Float64)::Int64
e_old = 1.0
n_max = 0
for i in 5:50
h = ham(z, mu, t, psi, i, 1.0)
eig, psi_t = eigen(h)
if abs(eig[1] - e_old) < 1e-6
break
end
e_old = eig[1]
n_max = i
end
return n_max
end

function Iteration(z::Int64, mu, t
)::Matrix{Float64}

println("Running ",nprocs()," processes")
n_max = SharedArray(zeros(length(t), length(mu)))
@sync @distributed for j in 1:length(t)
# for j in 1:length(t)
mut = mu[j]
for k in 1:length(mu)
tt = t[k]
n_max[j, k] = cut_n(z, mut, tt, 0.1)
end
end
return n_max
end

z = 1
step = 10
t = range(0, stop=0.2, length=step)
mu = range(0, stop=3, length=step)
x = Iteration(z, mu, t)
println(x)``````