Text: To be done in Python code (beginner).
3. Something old: light [3 marks] Assume that a molecule has n = 5 fluorophores attached. Under illumination, each fluorophore emits photons at a rate T = 100/s. The total emission rate of the molecule is then nT. Each fluorophore also bleaches at a rate of T = 1/s, so the total bleach rate is nT. The total rate of things happening is T = n(T + T). The probability of a bleach happening is pa = T/(T + T), and when this happens there is one less fluorophore n = n - 1. When n = 0 there is no more photon emission or bleaching (the molecule is invisible!).
a) Use Kinetic Monte Carlo to generate a list of photon emission times from a single molecule. Remember that the next event occurs after t = 1/T * RAN01 has elapsed. Use a histogram to get the photons per second, or intensity I(t). Plot this for N = 10 different fluorophores.
b) Average the N signals, i.e. measure < I > (t), and see if it decays with an exponential. What is the best fit timescale T, i.e. < I > = Joet/. You can fit by eye or use your code from the previous question. [Note that you can't fit the data well if you don't average it first. Why not?]
