Difference between revisions of "Simulations of Particle Interactions with Matter"

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<math>P(E=5eV) = e^{-5/0.0258} \approx 10^{-85}</math>
 
<math>P(E=5eV) = e^{-5/0.0258} \approx 10^{-85}</math>
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This approximation breaks down as <math>E \rightarrow 0.0258 eV</math>
  
 
=== The Monte Carlo method ===
 
=== The Monte Carlo method ===

Revision as of 16:08, 31 August 2007

Overview

Particle Detection

A device detects a particle only after the particle transfers energy to the device.

Energy intrinsic to a device depends on the material used in a device

Some device of material with an average atomic number (Z) is at some temperature (T). The materials atoms are in constant thermal motion (unless T = zero degrees Klevin).

Statistical Thermodynamics tells us that the canonical energy distribution of the atoms is given by the Maxwell-Boltzmann statistics such that

P(E)=1kTeEkT

P(E) represents the probability of any atom in the system having an energy E where

k=1.38×1023JmoleK

Note: You may be more familiar with the Maxwell-Boltzmann distribution in the form

N(ν)=4πN(m2πkT)3/2v2emv2/2kT

where N(v)Δv would represent the molesules in the gas sample with speeds between v and v+Δv

Example 1

What is the probability that an atom in a 12.011 gram block of carbon would have and energy of 5 eV?

First lets check that the probability distribution is Normailized; ie: does 0P(E)dE=1?


0P(E)dE=01kTeEkTdE=1kT11kTeEkT0=[ee0]=1

P(E=5eV) is calculated by integrating P(E) over some energy interval ( ie:N(v)dv). I will arbitrarily choose 4.9 eV to 5.1 eV as a starting point.


5.1eV4.9eVP(E)dE=[e5.1eV/kTe4.9eV/kT]

k=(1.38×1023JmoleK)=(1.38×1023JmoleK)(6.42×1018eVJ)=8.614×105eVmoleK

assuming a room empterature of T=300K

thenkT=0.0258eVmole

and

5.1eV4.9eVP(E)dE=[e5.1/0.0258e4.9/0.0258]=4.48×10831.9×10864.48×1083

or inother words the precise mathematical calculation of calculating the probability may be approximated by just using the distribution function alone

P(E=5eV)=e5/0.02581085

This approximation breaks down as E0.0258eV

The Monte Carlo method

A Unix Primer

A Root Primer

Example 1: Create Ntuple and Draw Histogram

Cross Sections

Deginitions

Example : Elastic Scattering

Lab Frame Cross Sections

Stopping Power

Bethe Equation

Classical Energy Loss

Bethe-Bloch Equation

Energy Straggling

Thick Absorber

Thin Absorbers

Range Straggling

Electron Capture and Loss

Multiple Scattering

Interactions of Electrons and Photons with Matter

Bremsstrahlung

Photo-electric effect

Compton Scattering

Pair Production

Hadronic Interactions

Neutron Interactions

Elastic scattering

Inelasstic Scattering