limit_mmbb1=ymmbb1[i]


    mintanbeta=0.1
    maxtanbeta=5
    n=100
    step=(maxtanbeta-mintanbeta)/n
    BRmm=1
    BRtt=1
    BRbb=1
    a_ymmbb=[]
    a_x=[]
    a_ymmtt=[]
    for i in range(0,100):
       tanbeta=mintanbeta+step*i
       width=get_total_width(args.model,float(args.ma),tanbeta)
       BRmm=gamma_mu(tanbeta,float(args.ma),args.model)/width
       BRtt=gamma_tau(tanbeta,args.ma,args.model)/width
       BRbb=gamma_quarks(tanbeta,args.ma,args.model,6)/width
       a_ymmbb.append(limit_mmbb1*0.00017/(2*BRbb*BRmm))
       a_ymmtt.append(limit_mmtt1/(BRtt*BRtt))
       #print limit_mmbb1,limit_mmtt1
       #print BRbb,BRmm,BRtt
       #print limit_mmbb1*0.00017/(2*BRbb*BRmm),limit_mmtt1/(BRtt*BRtt)
       a_x.append(tanbeta)

    x = array("d", a_x)
    ymmbb = array("d", a_ymmbb)
    ymmtt = array("d", a_ymmtt)

    gmmtt = ROOT.TGraph(len(x),x,ymmtt)
Exemplo n.º 2
0
    parser = argparse.ArgumentParser()
    parser.add_argument('--model', type=int, default='1', help="Which type of 2HDM?")
    parser.add_argument('--tanbeta', type=float, default='1', help="Which tan beta?")

    args = parser.parse_args()

    style1=GetStyleHtt()
    style1.cd()

    #### h->aa->mmtt ####
    x_mmtt1, y_mmtt1 = np.loadtxt('mmtt.txt', unpack=True)
    x_mmtt=array("d",x_mmtt1)
    y_mmtt=array("d",y_mmtt1)
    for i in range(0,len(x_mmtt)):
        width=get_total_width(args.model,float(x_mmtt[i]),args.tanbeta)
        BRtt=gamma_tau(args.tanbeta,float(x_mmtt[i]),args.model)/width
        y_mmtt[i]=y_mmtt[i]/(BRtt*BRtt)
    gmmtt = ROOT.TGraph(len(x_mmtt), x_mmtt,y_mmtt)

    #### h->aa->mmbb ####
    x_mmbb, y_mmbb = np.loadtxt('mmbb.txt', unpack=True)
    for i in range(0,len(x_mmbb)):
        width=get_total_width(args.model,float(x_mmbb[i]),args.tanbeta)
        BRmm=gamma_mu(args.tanbeta,float(x_mmbb[i]),args.model)/width
        BRbb=gamma_quarks(args.tanbeta,float(x_mmbb[i]),args.model,6)/width
	y_mmbb[i]=y_mmbb[i]*0.00017
        y_mmbb[i]=y_mmbb[i]/(2*BRmm*BRbb)
    gmmbb = ROOT.TGraph(len(x_mmbb), x_mmbb.flatten('C'),y_mmbb.flatten('C'))

    #### h->aa->tttt (HIG-14-019) ####
    mintanbeta=0.1
    maxtanbeta=5
    n=100
    step=(maxtanbeta-mintanbeta)/n
    BRmm=1
    BRtt=1
    BRbb=1
    a_y1=[]
    a_y2=[]
    a_y3=[]
    a_y4=[]
    a_x=[]
    for i in range(0,100):
       tanbeta=mintanbeta+step*i
       width1=get_total_width(1,float(args.ma),tanbeta)
       width2=get_total_width(2,float(args.ma),tanbeta)
       width3=get_total_width(3,float(args.ma),tanbeta)
       width4=get_total_width(4,float(args.ma),tanbeta)
       BRmm1=gamma_mu(tanbeta,float(args.ma),1)/width1
       BRtt1=gamma_tau(tanbeta,args.ma,1)/width1
       BRbb1=gamma_quarks(tanbeta,args.ma,1,6)/width1
       BRmm2=gamma_mu(tanbeta,float(args.ma),2)/width2
       BRtt2=gamma_tau(tanbeta,args.ma,2)/width2
       BRbb2=gamma_quarks(tanbeta,args.ma,2,6)/width2
       BRmm3=gamma_mu(tanbeta,float(args.ma),3)/width3
       BRtt3=gamma_tau(tanbeta,args.ma,3)/width3
       BRbb3=gamma_quarks(tanbeta,args.ma,3,6)/width3
       BRmm4=gamma_mu(tanbeta,float(args.ma),4)/width4
       BRtt4=gamma_tau(tanbeta,args.ma,4)/width4
       BRbb4=gamma_quarks(tanbeta,args.ma,4,6)/width4
    minbeta=1.45
    maxbeta=5
    if (args.model==4):
       minbeta=0.28
       maxbeta=0.9

    x_mmtt1, y_mmtt1 = np.loadtxt('mmtt.txt', unpack=True)
    x_mmtt=array("d",x_mmtt1)
    y_mmtt=array("d",y_mmtt1)
    hist=ROOT.TH2F("hist","hist",len(x_mmtt)-1,x_mmtt[0],x_mmtt[len(x_mmtt)-1],binbeta,minbeta,maxbeta)
    for b in range(0,binbeta+1):
	tanbeta=0.001+minbeta+1.0*b*(maxbeta-minbeta)/(binbeta)
        for i in range(0,len(x_mmtt)):
	   #for b in range(0,binbeta):
	   #tanbeta=minbeta+1.0*b*(maxbeta-minbeta)/binbeta
           width=get_total_width(args.model,float(x_mmtt[i]),tanbeta)
           BRtt=gamma_tau(tanbeta,float(x_mmtt[i]),args.model)/width
	   y=y_mmtt[i]/(BRtt*BRtt)
	   print x_mmtt[i],tanbeta,y
           hist.Fill(x_mmtt[i],1.0*tanbeta,y)
    #hist.SetContour(500)

    canvas = MakeCanvas("asdf","asdf",800,800)
    canvas.SetRightMargin(0.2)
    canvas.SetLeftMargin(0.15)
    canvas.cd()
    canvas.SetLogz()
    hist.GetXaxis().SetTitle("m_{a} (GeV)")
    hist.GetYaxis().SetTitle("tan#beta")
    hist.GetZaxis().SetTitle("#frac{#sigma(h)}{#sigma_{SM}} #times B(h#rightarrowaa)")
    if (args.model==3):