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@DavidMStraub
Created October 13, 2016 18:14
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import flavio\n",
"import flavio.statistics.fits\n",
"import flavio.plots\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from numpy import cos, sin\n",
"%matplotlib inline\n",
"plt.rc('text', usetex=True)\n",
"plt.rcParams['savefig.dpi'] = 100\n",
"plt.rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(-5.8997126213669525e-12-5.6117423595563851e-12j)"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"CSM = flavio.physics.mesonmixing.wilsoncoefficient.cvll_d(\n",
" par=flavio.default_parameters.get_central_all(),\n",
" meson='B0',\n",
" scale = 4.2)[0]\n",
"CSM"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def wc_fct(Cr, Ci):\n",
" return { 'CVLL_bdbd': (Cr + 1j*Ci) * CSM }"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"observables = ['DeltaM_d', 'S_psiK']"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"par_future = flavio.default_parameters.copy()\n",
"par_future.set_constraint('bag_B0_1', '0.9130(45)')\n",
"par_future.set_constraint('bag_Bs_1', '0.9520(47)')\n",
"par_future.set_constraint('f_B0', '0.1920(10)')\n",
"par_future.set_constraint('f_Bs', '0.2284(11)')\n",
"par_future.set_constraint('Vub', '3.62(3)e-3')\n",
"par_future.set_constraint('Vcb', '4.221(42)e-2')\n",
"par_future.set_constraint('gamma', '1.270(15)') # 0.5°"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"m = flavio.Measurement('future phi_s')\n",
"m.set_constraint('S_psiphi', '0.033+-0.008')\n",
"m.set_constraint('S_psiK', '0.679 ± 0.008')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def my_fit(name, observables):\n",
" return flavio.statistics.fits.FastFit(name,\n",
" par_obj = par_future,\n",
" fit_parameters = [],\n",
" nuisance_parameters = flavio.default_parameters.all_parameters,\n",
" observables = observables,\n",
" fit_wc_names = wc_fct.__code__.co_varnames,\n",
" fit_wc_function = wc_fct,\n",
" input_scale = 4.2,\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"fit={}\n",
"for obs in observables:\n",
" fit[obs] = my_fit('CVLL ' + obs + ' future', [obs] )\n",
"fit['global'] = my_fit('CVLL Bd mixing future', observables)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 2min 39s, sys: 196 ms, total: 2min 39s\n",
"Wall time: 3min 15s\n"
]
}
],
"source": [
"%%time\n",
"for f in fit.values():\n",
" f.make_measurement(N=200)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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HD3P06NFpX2NwO8yZlE33qEWWMJsMls9387Us4hG3ipJwOH8t96lFEm3dunVUEObl5bFx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\n/z98Bw0hAHdEOAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f7dba41d358>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(5,5))\n",
"xmax=0.12\n",
"x0=-0.1\n",
"ymax=0.05\n",
"flavio.plots.band_plot(fit['DeltaM_d'].log_likelihood, x0-xmax, x0+xmax, -xmax, xmax, n_sigma=1, col=1,\n",
" contourf_args={'alpha':0.5}, label=r'$\\Delta M_d$ ($1\\sigma$)')\n",
"flavio.plots.band_plot(fit['S_psiK'].log_likelihood, x0-xmax, x0+xmax, -ymax, ymax, n_sigma=1, col=2,\n",
" contourf_args={'alpha':0.5}, label=r'$S_{\\psi K_S}$ ($1\\sigma$)')\n",
"flavio.plots.band_plot(fit['global'].log_likelihood, x0-xmax, x0+xmax, -ymax, ymax, n_sigma=1, col=0,\n",
" label='global')\n",
"flavio.plots.band_plot(fit['global'].log_likelihood, x0-xmax, x0+xmax, -ymax, ymax, n_sigma=(2,3), \n",
" contourf_args={'alpha':0.1}, contour_args={'alpha':0.4}, col=0)\n",
"flavio.plots.flavio_branding(x=0.77, y=0.09)\n",
"plt.legend()\n",
"plt.xlim([x0-xmax,x0+xmax])\n",
"plt.ylim([-xmax,xmax])\n",
"plt.axhline(0, c='k', lw=0.2)\n",
"plt.axvline(0, c='k', lw=0.2)\n",
"plt.xlabel(r'$\\text{Re} ( C_{VLL}/C_{VLL}^\\text{SM} ) $')\n",
"plt.ylabel(r'$\\text{Im} ( C_{VLL}/C_{VLL}^\\text{SM} ) $')\n",
"plt.tight_layout()\n",
"plt.savefig('CVLL-Bd-future.pdf')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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