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If present, the file modifier.py must contain a function


with er=\(E_R\), eprime=\(E^{\prime}\), exp an object belonging to the experiment class, n_element and n_isotope two integers that specify the element in the exp.target.element array and the isotope, respectively and n_bin an integer identifying the energy bin (among those defined in data.tab). The default for the function is unity.

At the time of calculating the integrated response functions the differential response functions are multiplied times the modifier. Its purpose is to implement specific cases where the expected rate is not in a standard form, allowing, in principle, a different modifier for each target or energy bin.

For instance, droplet detectors and bubble chambers such as COUPP, PICO60 or PICASSO are threshold detectors (i.e. a signal is detected only above some value of the deposited energy, which is fixed by changing the running parameters such as the temperature or the pressure). In this case the expected number of events is given by: \[R=N_T MT\int_0^{\infty} P(E_R) \frac{dR}{dE_R} dE_R\] where \(P(E_R)\) is the probability that the energy \(E_R\) will produce a signal if the energy threshold is fixed to \(E_{th}\). The response function for such class of detectors requires that no energy resolution is provided while the \(P(E_R)\) function is implemented through the file modifier.py.