import WimPyDD as WD import numpy as np import matplotlib.pyplot as pl pl.clf() vmin, delta_eta0=WD.streamed_halo_function() pl.clf() # defines the effective Hamiltonian for spin-independent interaction parameterizing the Wilson coefficients # interms of the effective scale M: c_1^tau=[c_1,c_1^1]=[c_1^p+c_1^n,c_1^p+c_1^n] with c_1^p=c_1^n=1/M^2 SI_M=WD.eft_hamiltonian('SI',{1: lambda M:1./M**2*np.array([2,0])}) # loads response functions for built-in experiment WD.XENON_1T_2018 (j_chi=0.5 defalult spin value) WD.load_response_functions(WD.XENON_1T_2018,SI_M,verbose=False) # calling mchi_vs_exclusion without passing M corresponds to setting M=1 (holds for any parameter without a default value # the rate is proportional to 1/M^4, so the exclusion plot is on the same quantity. mchi,one_over_M4=WD.mchi_vs_exclusion(WD.XENON_1T_2018, SI_M, vmin,delta_eta0) # plots M=(1/M^4)^(-1/4) pl.plot(mchi,one_over_M4**(-1./4.)) pl.xlabel('$m_\chi$ (GeV)') pl.ylabel('$M$ (GeV)') pl.xscale('log') pl.yscale('log') pl.show()