130 lines
4.1 KiB
Python
130 lines
4.1 KiB
Python
import pycatima as catima
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import numpy as np, sys
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import matplotlib.pyplot as plt
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# --- 1. Constants ---
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P_TORR = 250
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P_CO2 = 0
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if(len(sys.argv)==3):
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P_TORR=int(sys.argv[1])
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P_CO2 = int(sys.argv[2])
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TEMP_K = 293.15
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R = 8.3144
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MEV2U = 1.0 / 931.494
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# Gas Density Calculations
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p_pa = P_TORR * 133.322
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molar_density = p_pa / (R * TEMP_K)
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m_he, m_c, m_o= 4.0026, 12.0000, 15.9949
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m_mix_avg = ((1 - P_CO2 / 100) * m_he) + (P_CO2 / 100 * (m_c + 2*m_o))
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rho_g_cm3 = (molar_density * m_mix_avg) / 1e6
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print(f"Gas density at {P_TORR} Torr: {rho_g_cm3:.6e} g/cm^3")
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# --- 2. Material & Step Setup ---
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material_def = [(m_he, 2, (1 - P_CO2 / 100)), (m_c, 6, P_CO2 / 100), (m_o, 8, 2*P_CO2 / 100)]
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gas_mix = catima.Material(material_def)
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gas_mix.density(rho_g_cm3)
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# Thickness step settings
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step_mg_cm2 = 0.001
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step_g_cm2 = step_mg_cm2 / 1000.0
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max_steps = 1000000000 # Adjust based on how far you want to track
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coarse_step_cm = 0.2
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fine_step_cm = 0.03
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fine_zone_frac = 0.085
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# Set relative integration tolerance (lower = higher precision, slower calculation)
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catima.Config.epsrel = 1e-6
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# Set absolute integration tolerance
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catima.Config.epsabs = 1e-9
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def generate_lookup(z, mass_u, e_start_mev, label):
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filename = f"Eloss/E_vs_x_{label}.dat"
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header = (
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"Distance_cm\tEnergy_MeV\tSigma_E_MeV\tSigma_x_cm\tSigma_a_cm\t"
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"Thickness_mg_cm2\tEin_MeV\tSigma_r\tCov\tToF\tStoppingPower"
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)
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projectile = catima.Projectile(mass_u, z)
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e_u_init = e_start_mev / mass_u
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# 1. Get exact analytical range directly from CATIMA
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projectile.T(e_u_init)
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total_range_g_cm2 = catima.range(projectile, gas_mix)
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total_range_cm = total_range_g_cm2 / rho_g_cm3
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fine_zone_start_cm = total_range_cm * (1.0 - fine_zone_frac)
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output = []
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current_dist_cm = 0.0
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# 2. Step directly at checkpoint resolution
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while current_dist_cm <= total_range_cm * 1.05: # Track slightly past range
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thickness_g_cm2 = current_dist_cm * rho_g_cm3
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# Configure target thickness for this checkpoint
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gas_mix.density(rho_g_cm3).thickness(thickness_g_cm2)
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projectile.T(e_u_init)
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result = catima.calculate(projectile, gas_mix)
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# Save checkpoint row
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e_total_out = result.Eout * mass_u
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output.append([
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current_dist_cm, e_total_out, result.sigma_E, result.sigma_x,
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result.sigma_a, thickness_g_cm2 * 1000.0, result.Ein,
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result.sigma_r, result.cov, result.tof, result.sp
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])
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if result.Eout == 0:
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break
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# Adaptive spatial step
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step = fine_step_cm if current_dist_cm >= fine_zone_start_cm else coarse_step_cm
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current_dist_cm += step
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data = np.asarray(output)
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data = data[np.argsort(data[:, 1])]
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np.savetxt(
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filename, data, fmt='%.6f', delimiter='\t', header=header, comments=""
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)
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print(f"Lookup table created: {filename} ({len(output)} rows)")
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# Plot in increasing distance order even though the saved table is energy-sorted.
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plot_data = data[::-1]
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dist_cm, energy_mev, sigma_e, tof = (
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plot_data[:, 0], plot_data[:, 1], plot_data[:, 2], plot_data[:, 9]
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)
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fig, (ax_e, ax_sig, ax_tof) = plt.subplots(3, 1, figsize=(8, 12), sharex=True)
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ax_e.plot(dist_cm, energy_mev)
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ax_e.fill_between(dist_cm, energy_mev - sigma_e, energy_mev + sigma_e, alpha=0.3)
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ax_e.set_ylabel("Energy (MeV)")
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ax_e.set_title(f"Energy Loss Curve {label.capitalize()}")
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ax_e.grid(True)
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ax_sig.plot(dist_cm, sigma_e)
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ax_sig.set_ylabel("Energy straggle $\\sigma_E$ (MeV)")
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ax_sig.grid(True)
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ax_tof.plot(dist_cm, tof)
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ax_tof.set_xlabel("Distance (cm)")
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ax_tof.set_ylabel("Time of flight (ns)")
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ax_tof.grid(True)
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plt.tight_layout()
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plt.show()
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# --- 3. Run ---
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# Format: generate_lookup(Z, mass_u, E_start_MeV, label)
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generate_lookup(1, 1.0078, 30, "proton")
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generate_lookup(1, 2.01355, 30, "deuteron")
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generate_lookup(2, 4.0026, 50, "alpha")
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generate_lookup(13,26.9815, 56.1, "aluminum")
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#generate_lookup(9,17.0021, 70, "fluorine")
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#generate_lookup(8,15.9949, 70, "oxygen")
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