BATATA Tracks

Fiber optics attenuation lenght


In [1]:
using PyPlot
using Distributions
PyPlot.matplotlib[:rc]("text", usetex=true)


INFO: Loading help data...

In [2]:
a₁₁ = 11.993
a₂₂ = 32.749
a₁₂ = a₁₁ + a₂₂ 

a₁ = a₁₁/a₁₂ 
a₂ = a₂₂/a₁₂

λ₁ = 47.13
λ₂ = 1136.19

println("a₁ = ",a₁)
println("a₂ = ",a₂)


a₁ = 0.2680479191810826
a₂ = 0.7319520808189174

In [3]:
x = linspace(10,400,50)

S(S₀,x)= S₀*((a₁*(exp(-x/λ₁))) +  (a₂*(exp(-x/λ₂))))

ylabel(L"$S(1,x)$",fontsize=20,rotation=360, labelpad=20)
xlabel(L"$x$",fontsize=20)
ylim(0.3,1)

plot(x,S(1,x))
grid("on")


Cheking Poisson function


In [4]:
k = linspace(0,20,21)

p₁ = Poisson(2)
p₂ = Poisson(5)
p₃ = Poisson(8)


cpois₁ = cdf(p₁,k)
cpois₂ = cdf(p₂,k)
cpois₃ = cdf(p₃,k)


ylim(0,1.3)

plot(k,cpois₁,"r",label=L"$cpois_1$")
plot(k,cpois₂,"b",label=L"$cpois_2$")
plot(k,cpois₃,"g",label=L"$cpois_3$")
legend(loc=4)

xlabel(L"$k$",fontsize=20)


Out[4]:
PyObject <matplotlib.text.Text object at 0x7f40c1265710>

In [5]:
k = linspace(0,20,21)

p₁ = Poisson(2)
p₂ = Poisson(5)
p₃ = Poisson(8)

dpois₁ = pdf(p₁,k)
dpois₂ = pdf(p₂,k)
dpois₃ = pdf(p₃,k)

plot(k,dpois₁,"r",label=L"$dpois_1$")
plot(k,dpois₂,"b",label=L"$dpois_2$")
plot(k,dpois₃,"g",label=L"$dpois_3$")
legend(loc=4)

xlabel(L"$k$",fontsize=20)


Out[5]:
PyObject <matplotlib.text.Text object at 0x7f40bdfd1be0>

The detector


In [20]:
#Numer of strips
N = 50

#x-direction
i = linspace(1,N,50)

#y-direction
j = linspace(1,N,50)

#Lateral side of the detector
LD = 200

#Optical fiber bending region:
LC = 50

#pixel size
Lpix = LD/N

#Vertical muon deposition in SPEs (2 MeV)
Svm = 7

#Distance from impact point to PMT1 (x-plane)
Ld1(i,j) = LD - Lpix*i
Lc1(i,j) = sqrt(LC^2 + (Lpix*j - LD/2).*(Lpix*j - LD/2))
L1(i,j) = Ld1(i,j) + Lc1(i,j)


#Distance from impact point to PMT2 (y-plane)
Ld2(i,j) = LD - Lpix*j
Lc2(i,j) = sqrt(LC^2 + (Lpix*i - LD/2).*(Lpix*i - LD/2))
L2(i,j) = Ld1(i,j) + Lc1(i,j)

# reshape(L1(i,j),N,N)

matriz1(i,j) = hcat([L1(i,j) for j=1:50]...)
matriz2(i,j) = hcat([L2(i,j) for j=1:50]...)

# println(matriz1(i,j)[1,3])
# println(matriz2(i,j)[1,3])

for i in [1:50]
    for j in [1:50]
        X(i,j) = Ld1(i,j) + Lc1(i,j)
        Y(i,j) = Ld2(i,j) + Lc2(i,j)
        Z(i,j) = X(i,j) - Y(i,j)
    end
end

#Effective angle for propagation of light inside the optical fiber

ζ = 40

c = 3*10^10*cos(ζ) #cm/sec

for i in [1:50]
    for j in [1:50]
        Δt(i,j) = (Z(i,j))/(c*10^(-9.0))
        #print(Δt(i,j))
        end
end

typeof(Δt(i,j))

# for i in [1:50]
#     for j in [1:50]
# matshow(Δt(i,j))
#     end
# end



#Detection probability for each (i,j) pixel

# Pd1(i,j) = 1-cdf(Poisson(1),S(Svm,L1))

# Pd2(i,j) = 1-cdf(Poisson(1),S(Svm,L2))

# PD(i,j) = Pd1 .* Pd2


        






# for i in [1:N]
#     for j in [1:N]
#         #Distance from impact point to PMT1 (x-plane)
#         Ld1(i,j) = LD - Lpix*i
#         Lc1(i,j) = sqrt(LC^2 + (Lpix*j - LD/2).*(Lpix*j - LD/2))
#         L1(i,j) = Ld1(i,j) + Lc1(i,j)

#         #Distance from impact point to PMT2 (y-plane)
#         Ld2(i,j) = LD - Lpix*j
#         Lc2(i,j) = sqrt(LC^2 + (Lpix*i - LD/2).*(Lpix*i - LD/2))
#         L2(i,j) = Ld1(i,j) + Lc1(i,j)

#          #Detection probability for each (i,j) pixel

#          Pd1(i,j) = 1-cdf(Poisson(1),S(Svm,L1))

#          Pd2(i,j) = 1-cdf(Poisson(1),S(Svm,L2))

#          PD(i,j) = Pd1 .* Pd2

#          #Time of flight to PMT1 and PMT2

#          #Effective angle for propagation of light inside the optical fiber

#          ζ = 40

#          c = 3*10^10*cos(ζ) #cm/sec

#          Δt(i,j) = (L1(i,j) - L2(i,j))/(c*10^(-9.0))
#     end
# end
#plot(Δt(i,j))



#THIS MAKES NO SENSE FOR THE MOMENT


Out[20]:
Float64

$\mu$ propagation


In [59]:
#Depth of planes [cm]

z = [30,60,150]


#Particle trayectory

T(z,θ,φ,x₀) = z/(c*cos(θ)*10^-9.0)

X(θ,φ,x₀) = z*tan(θ)*cos(φ) + x₀

Y(θ,φ,y₀) = z*tan(θ)*sin(φ) + y₀

I(θ,φ,x₀) = ceil(X(θ,φ,x₀)/Lpix)

J(θ,φ,y₀) = ceil(Y(θ,φ,y₀)/Lpix)

ζ₁(θ,φ,x₀,y₀) = (0 <= X(θ,φ,x₀) <= 200) & (0 <= X(θ,φ,x₀) <= 200) ? 1 : 0

#Arrival time of signal ar each PMT

Tx(plane,θ,φ,x₀,y₀) = L1(I(θ,φ,x₀),J(θ,φ,y₀))/(c*10^-9.0)

Ty(plane,θ,φ,x₀,y₀) = L2(I(θ,φ,x₀),J(θ,φ,y₀))/(c*10^-9.0)

"""
Layer 1 - plane x - PMT1
Layer 1 - plane y - PMT2
Layer 2 - plane x - PMT3
Layer 2 - plane y - PMT4
Layer 3 - plane x - PMT5
Layer 3 - plane y - PMT6
"""

Tp(θ,φ,x₀,y₀,t₀) = [t₀ +T(z[1],θ,φ,x₀) + Tx(1,θ,φ,x₀,y₀), 
                    t₀ + T(z[1],θ,φ,x₀) + Ty(1,θ,φ,x₀,y₀),
                    t₀ + T(z[2],θ,φ,x₀) + Tx(2,θ,φ,x₀,y₀),
                    t₀ + T(z[2],θ,φ,x₀) + Ty(1,θ,φ,x₀,y₀),
                    t₀ + T(z[3],θ,φ,x₀) + Tx(3,θ,φ,x₀,y₀),
                    t₀ + T(z[3],θ,φ,x₀) + Ty(3,θ,φ,x₀,y₀)]

# Single given μ

# Initial conditions 

# Plane #1

t₀₁  = 0
x₀₁ = 80
y₀₁ = 180
θ₁ = 30
φ₁ = -4

Tp(θ₁,φ₁,x₀₁,y₀₁,t₀₁)

#i = linspace(1,18,18)


#plot(i,Tp(θ₁,φ₁,x₀₁,y₀₁,t₀₁))


Out[59]:
18-element Array{Float64,1}:
 -13.3797
 -13.815 
 -16.4146
 -13.3797
 -13.815 
 -16.4146
 -23.1001
 -23.5354
 -26.135 
 -23.1001
 -23.5354
 -26.135 
 -52.2614
 -52.6967
 -55.2963
 -52.2614
 -52.6967
 -55.2963