def plotMOut(config):
config_section_name = 'M_OUT'
binary_par = {}
binary_par["theta_i_deg"]=float(config[config_section_name]['theta_i_deg'])
binary_par["EOS"]=config[config_section_name]['EOS']
binary_par["chi_ns"]=float(config[config_section_name]['chi_ns'])
binary_par["m_ns"]=float(config[config_section_name]['m_ns'])
q_min=float(config[config_section_name]['q_min'])
q_max=float(config[config_section_name]['q_max'])
q = np.linspace(q_min, q_max, 5*(q_max-q_min+1))
chi_bh_min=float(config[config_section_name]['chi_bh_min'])
chi_bh_max=float(config[config_section_name]['chi_bh_max'])
chi_bh = np.linspace(chi_bh_min, chi_bh_max, 10*(chi_bh_max-chi_bh_min)+1)
binary_par["type"]=config[config_section_name]['type']
plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
plt.rcParams['ytick.right'] = plt.rcParams['ytick.labelright'] = True
for j in range(len(chi_bh)):
m_out_arr = []
binary_par['chi_bh'] = chi_bh[j]
for k in range(len(q)):
binary_par['q'] = q[k]
spin_object = sm.Spin_class(binary_par)
m_out = spin_object.M_out()
m_out_arr.append(m_out)
plt.plot(q, m_out_arr, label=r"$\chi_{BH}:$ %.2f" %chi_bh[j])
plt.legend()
plt.title(r"$M_{NS}$ = %.2f $M_{\odot}$, EOS = %s, $\theta_i$ = %d$^{\circ}$"%(binary_par["m_ns"], binary_par["EOS"], binary_par["theta_i_deg"]), y=1.08)
plt.xlabel(r"$q$")
plt.ylabel(r"$M_{b,out}[M_{\odot}]$")
plt.show()
def plotChiF_VarTheta(config):
config_section_name = 'CHI_F_VARTHETA'
binary_par = {}
binary_par["chi_bh"]=float(config[config_section_name]['chi_bh'])
binary_par["EOS"]=config[config_section_name]['EOS']
binary_par["chi_ns"]=float(config[config_section_name]['chi_ns'])
binary_par["m_ns"]=float(config[config_section_name]['m_ns'])
q_min=float(config[config_section_name]['q_min'])
q_max=float(config[config_section_name]['q_max'])
q = np.linspace(q_min, q_max, 5*(q_max-q_min+1))
theta_i_deg_min=float(config[config_section_name]['theta_i_deg_min'])
theta_i_deg_max=float(config[config_section_name]['theta_i_deg_max'])
theta_i_deg = np.linspace(theta_i_deg_min, theta_i_deg_max, 9)
binary_par["type"]=config[config_section_name]['type']
plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
plt.rcParams['ytick.right'] = plt.rcParams['ytick.labelright'] = True
for j in range(len(theta_i_deg)):
chi_f_arr = []
binary_par['theta_i_deg'] = theta_i_deg[j]
for k in range(len(q)):
binary_par['q'] = q[k]
spin_object = sm.Spin_class(binary_par)
chi_f, theta_f, m_final, m_out = spin_object.FinalPar()
chi_f_arr.append(chi_f)
plt.plot(q, chi_f_arr, label= r'$\theta_i:$ %d$^{\circ}$' %theta_i_deg[j])
plt.legend()
plt.title(r"$M_{NS}$ = %.2f $M_{\odot}$, EOS = %s, $\chi_{BH}$= %.2f "%(binary_par["m_ns"], binary_par["EOS"], binary_par["chi_bh"]), y=1.08)
plt.xlabel(r"$q$")
plt.ylabel(r"$\chi_f$")
plt.show()
def sigmaMF(config):
colors = [
'b', 'g', 'r', 'c', 'm', 'y', 'k', 'hotpink', 'olivedrab', 'gray'
]
sigma_par = {}
config_section_name = 'SIGMA_MF'
sigma_par['m_ns'] = float(config[config_section_name]['m_ns'])
sigma_par['type'] = config[config_section_name]['type']
sigma_par['theta_i_deg'] = float(
config[config_section_name]['theta_i_deg'])
sigma_par['EOS'] = config[config_section_name]['EOS']
snr = float(config[config_section_name]['snr'])
l = float(config[config_section_name]['l'])
m = float(config[config_section_name]['m'])
n = float(config[config_section_name]['n'])
q_min = float(config[config_section_name]['q_min'])
q_max = float(config[config_section_name]['q_max'])
q_arr = np.linspace(q_min, q_max, 30)
chi_bh_min = float(config[config_section_name]['chi_bh_min'])
chi_bh_max = float(config[config_section_name]['chi_bh_max'])
chi_bh = np.linspace(chi_bh_min, chi_bh_max, 10)
qnm = wf.QNM_fit(l, m, n)
plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
plt.rcParams['ytick.right'] = plt.rcParams['ytick.labelright'] = True
for i in range(len(chi_bh)):
sigma_par['chi_bh'] = chi_bh[i]
m_out_arr = []
err_m_f = []
for j in range(len(q_arr)):
sigma_par['q'] = q_arr[j]
spin_object = sm.Spin_class(sigma_par)
chi_f, theta_f, m_f, m_out = spin_object.FinalPar()
f_rd = qnm.f(m_f, chi_f)
tau_rd = qnm.tau(m_f, chi_f)
sigma_m_f = SigmaMF_Fisher(qnm, f_rd, tau_rd, chi_f, m_f, snr)
m_out_arr.append(m_out)
err_m_f.append(sigma_m_f)
plt.plot(q_arr,
err_m_f,
color=colors[i % 10],
label=r"$\sigma_M$, $\chi_{BH}$:%.1f" % chi_bh[i],
linestyle='--')
plt.plot(q_arr,
m_out_arr,
colors[i % 10],
label=r"$M_{OUT}$,$\chi_{BH}:%.1f$" % chi_bh[i],
linestyle='-')
#idx = np.argwhere(np.diff(np.sign(np.array(err_m_f) - np.array(m_out_arr))).flatten()
#plt.plot(q_arr[idx], m_out_arr[idx], 'ro')
plt.title(r"$M_{NS}$=%.2f, EOS= %s, mode = %d%d%d, SNR = %d" %
(sigma_par["m_ns"], sigma_par["EOS"], l, m, n, snr),
y=1.08)
plt.xlabel(r"$q$")
plt.ylabel(r"$[M_{\odot}]$")
plt.legend()
plt.show()
def sigma_freq(snr, mode1, mode2, binary_par):
spin_object = sm.Spin_class(binary_par)
a_f, theta_f, m_f, m_out = spin_object.FinalPar()
if mode1 == mode2:
print("non orthogonal mode")
else:
l1 = int(mode1[0])
m1 = int(mode1[1])
n1 = int(mode1[2])
l2 = int(mode2[0])
m2 = int(mode2[1])
n2 = int(mode2[2])
# Pair of modes
qnm1 = wf.QNM_fit(l1, m1, n1)
qnm2 = wf.QNM_fit(l2, m2, n2)
f1 = qnm1.f(m_f, a_f)
f2 = qnm2.f(m_f, a_f)
tau1 = qnm1.tau(m_f, a_f)
tau2 = qnm2.tau(m_f, a_f)
Q1 = np.pi * f1 * tau1
Q2 = np.pi * f2 * tau2
amplitude_object = am.Amplitude_class(binary_par)
switch = {
"220": amplitude_object.A22220,
"210": amplitude_object.A21210,
}
A1 = switch[mode1](0)
A2 = switch[mode2](0)
#print(f1,f2,tau1,tau2,A1,A2, m_f, a_f)
sigma = 1./(snr*2*2**(1./2))*(f1**3*(3+16*Q1**4)/(A1**2*Q1**7)*\
(A1**2*Q1**3/(f1*(1+4*Q1**2))+\
A2**2*Q2**3/(f2*(1+4*Q2**2))))**(1./2)
sigma = 1. / (2**(1. / 2) * np.pi * tau1 * snr)
return sigma
def sigma_tau(snr, mode1, mode2, binary_par):
spin_object = sm.Spin_class(binary_par)
a_f, theta_f, m_f, m_out = spin_object.FinalPar()
if mode1 == mode2:
print("Error, non orthogonal modes")
else:
l1 = int(mode1[0])
m1 = int(mode1[1])
n1 = int(mode1[2])
l2 = int(mode2[0])
m2 = int(mode2[1])
n2 = int(mode2[2])
qnm1 = wf.QNM_fit(l1, m1, n1)
qnm2 = wf.QNM_fit(l2, m2, n2)
f1 = qnm1.f(m_f, a_f)
f2 = qnm2.f(m_f, a_f)
tau1 = qnm1.tau(m_f, a_f)
tau2 = qnm2.tau(m_f, a_f)
Q1 = np.pi * f1 * tau1
Q2 = np.pi * f2 * tau2
amplitude_object = am.Amplitude_class(binary_par)
switch = {
"220": amplitude_object.A22220,
"210": amplitude_object.A21210,
}
A1 = switch[mode1](0)
A2 = switch[mode2](0)
sigma = 2./(snr*np.pi)*((3+4*Q1**2)/(A1**2*f1*Q1)*\
(A1**2*Q1**3/(f1*(1+4*Q1**2))+\
A2**2*Q2**3/(f2*(1+4*Q2**2))))**(1./2)
sigma = 2. * tau1 / snr
return sigma
def __init__(self, iterate=()):
self.__dict__.update(iterate)
# useful quantities
self.eta = self.q / (1 + self.q)**2
self.m_bh = self.q * self.m_ns
self.M = self.m_ns + self.m_bh
#self.G = 6.67*10**(-8)
self.G = lal.G_SI
#self.c = 3*10**(10)
self.c = lal.C_SI
#self.m_sol = 2*10**33
self.m_sol = lal.MSUN_SI
self.chi_ns = 0
self.winfact = 1. / 2 # ok=1/2, paper=1
# coefficients for PhenomC model
self.gamma = self.xi01[6] * self.chi_bh + self.xi02[
6] * self.chi_bh**2 + self.xi11[
6] * self.eta * self.chi_bh + self.xi10[
6] * self.eta + self.xi20[6] * self.eta**2
self.delta1 = self.xi01[7] * self.chi_bh + self.xi02[
7] * self.chi_bh**2 + self.xi11[
7] * self.eta * self.chi_bh + self.xi10[
7] * self.eta + self.xi20[7] * self.eta**2
self.delta2 = self.xi01[8] * self.chi_bh + self.xi02[
8] * self.chi_bh**2 + self.xi11[
8] * self.eta * self.chi_bh + self.xi10[
8] * self.eta + self.xi20[8] * self.eta**2
# spin section
binary_par = {
"m_ns": self.m_ns,
"q": self.q,
"theta_i_deg": self.theta_i_deg,
"chi_bh": self.chi_bh,
"EOS": self.EOS,
"type": self.type
}
spin_object = sm.Spin_class(binary_par)
chi_f, theta_f, m_f, m_out = spin_object.FinalPar()
self.chi_f = float(chi_f)
self.theta_f = float(theta_f)
self.m_f = float(m_f)
self.m_out = float(m_out)
# Ringdown frequency and damping time
# From Arxiv:gr-qc/0512160v2 eq. E1, E2
self.f_220_ringdown = (1.5251 - 1.1568 * (1 - self.chi_f)**
(0.1292)) / (2 * np.pi * self.m_f * self.m_sol *
self.G / self.c**2) * self.c
self.Q_220_ringdown = 0.7 + 1.4187 * (1 - self.chi_f)**(-0.4990)
self.tau_220_ringdown = self.Q_220_ringdown / self.f_220_ringdown / np.pi
# PhenomC for BBH
if self.type == "BBH":
self.eps_insp = 1
self.k = 1
self.sigma_tid = 0
self.eps_tid = 1
self.f0_pn = 0.98 * self.f_220_ringdown
self.f0_pm = 0.98 * self.f_220_ringdown
self.f0_rd = 0.98 * self.f_220_ringdown
# PhenomMixed
if self.type == "BHNS":
print("Total mass outside BH at late times: %.3f" % m_out)
m_g, m_b, compactness = np.loadtxt("EOS/equil_{}.d".format(
self.EOS),
unpack=True)
C_from_mg = interp1d(m_g, compactness)
self.C = float(C_from_mg(self.m_ns))
mb_from_mg = interp1d(m_g, m_b)
self.m_ns_b = float(mb_from_mg(self.m_ns))
xi_tid = fsolve(spin_object.XiTidal, 10)
r_tid = xi_tid * (self.m_ns * self.m_sol * self.G /
self.c**2) / self.C * (1 - 2 * self.C)
#r_tid = self.eta**(-1./3)*(self.m_ns*self.m_sol*self.G/self.c**2)/self.C*(1-2*self.C)
# frequencies in Hz
self.f_tid = float(
1. /
(np.pi *
(self.chi_f * self.m_f * self.m_sol * self.G / self.c**2 +
(r_tid**3 /
(self.m_f * self.m_sol * self.G / self.c**2))**(1. / 2))) *
self.c)
#print("theta_i_deg", self.theta_i_deg)
#print("chi_bh", self.chi_bh)
#print("chi_f", self.chi_f)
self.f_220_tilde = 0.99 * 0.98 * self.f_220_ringdown
self.k = 1.25
if self.x_var == "f":
plt.axvline(self.f_220_ringdown, 0.9, 1, color="c")
plt.axvline(self.f_tid, 0.9, 1, color="r")
if self.x_var == "fm":
plt.axvline(self.f_220_ringdown * self.G / self.c**3 * self.M *
self.m_sol,
0.9,
1,
color="c")
plt.axvline(self.f_tid * self.G / self.c**3 * self.M *
self.m_sol,
0.9,
1,
color="r")
if self.eta >= 5. / 36:
self.alpha = 1 + self.winfact * self.Windowed_function(
self.eta, 0.146872, 0.0749456, -1)
if self.eta < 5. / 36:
self.alpha = 1 + self.winfact * self.Windowed_function(
5. / 36, 0.146872, 0.0749456, -1)
self.delta2prime = self.alpha * self.delta2
# Non disruptive
if self.f_220_ringdown <= self.f_tid and self.m_out == 0:
print("Case: Non disruptive")
self.x_nd1 = (
(self.f_tid - self.f_220_tilde) / self.f_220_tilde
)**2 - 0.571505 * self.C - 0.00508451 * self.chi_bh
self.x_nd2 = (
(self.f_tid - self.f_220_tilde) / self.f_220_tilde
)**2 - 0.657424 * self.C - 0.0259977 * self.chi_bh
self.eps_tid = self.winfact * 2 * self.Windowed_function(
self.x_nd1, -0.0796251, 0.0801192, 1)
self.sigma_tid = self.winfact * 2 * self.Windowed_function(
self.x_nd2, -0.206465, 0.226844,
-1) / (self.G / self.c**3 * self.M * self.m_sol)
#self.delta2prime = 1.62496*self.winfact*self.Windowed_function((self.f_tid-self.f_220_tilde)/self.f_220_tilde, 0.0188092, 0.338737, -1)
self.f0_pn = self.f_220_tilde
self.f0_pm = self.f_220_tilde
self.f0_rd = self.f_220_tilde
#print("")
#print("f0_pn", self.f0_pn)
#print("f0_pm", self.f0_pm)
#print("f0_rd", self.f0_rd)
#print("eps_tid", self.eps_tid)
#print("sigma_tid", self.sigma_tid)
#print("delta2prime", self.delta2prime)
#print("x_nd", self.x_nd1)
#print("")
# Disruptive
if self.f_tid < self.f_220_ringdown and self.m_out > 0:
print("Case: Disruptive")
self.x_d1 = self.m_out/self.m_ns_b+0.424912*self.C+\
0.363604*(self.eta)**(1./2)-0.0605591*self.chi_bh
self.x_d2 = self.m_out/self.m_ns_b-0.132754*self.C+\
0.576669*(self.eta)**(1./2)-0.0603749*self.chi_bh-\
0.0601185*self.chi_bh**2-0.0729134*self.chi_bh**3
self.esp_tid = 0
self.eps_insp = -1.61724 * self.x_d1 + 1.29971
self.sigma_tid = (-0.293237*self.x_d2+0.1377221)/\
(self.G/self.c**3*self.M*self.m_sol)
self.f0_pn = self.eps_insp * self.f_tid
self.f0_pm = self.f_tid
# Mildly disruptive 1
if self.f_tid < self.f_220_ringdown and self.m_out == 0:
print("Case: Midly disruptive, no ringdown, no M outside BH")
self.x_d1 = self.m_out/self.m_ns_b+0.424912*self.C+\
0.363604*(self.eta)**(1./2)-0.0605591*self.chi_bh
self.x_d2 = self.m_out/self.m_ns_b-0.132754*self.C+\
0.576669*(self.eta)**(1./2)-0.0603749*self.chi_bh-\
0.0601185*self.chi_bh**2-0.0729134*self.chi_bh**3
self.x_nd2 = (
(self.f_tid - self.f_220_tilde) / self.f_220_tilde
)**2 - 0.657424 * self.C - 0.0259977 * self.chi_bh
self.eps_tid = 0
self.eps_insp = -1.61724 * self.x_d1 + 1.29971
self.sigma_tid_d = (-0.293237*self.x_d2+0.1377221)/\
(self.G/self.c**3*self.M*self.m_sol)
self.sigma_tid_nd = self.winfact * 2 * self.Windowed_function(
self.x_nd2, -0.206465, 0.226844,
-1) / (self.G / self.c**3 * self.M * self.m_sol)
self.sigma_tid = (self.sigma_tid_d + self.sigma_tid_nd) / 2.
self.f0_pn = (1-self.q**(-1))*self.f_220_tilde+\
self.q**(-1)*self.eps_insp*self.f_tid
self.f0_pm = (1-self.q**(-1))*self.f_220_tilde+\
self.q**(-1)*self.f_tid
# Mildly disruptive 2
if self.f_220_ringdown <= self.f_tid and self.m_out > 0:
print("Case: Mildly diruptive, ringdown, M outside BH")
self.x_d1 = self.m_out/self.m_ns_b+0.424912*self.C+\
0.363604*(self.eta)**(1./2)-0.0605591*self.chi_bh
self.x_nd1 = (
(self.f_tid - self.f_220_tilde) / self.f_220_tilde
)**2 - 0.571505 * self.C - 0.00508451 * self.chi_bh
self.x_nd2 = (
(self.f_tid - self.f_220_tilde) / self.f_220_tilde
)**2 - 0.657424 * self.C - 0.0259977 * self.chi_bh
self.eps_insp = -1.61724 * self.x_d1 + 1.29971
self.eps_tid = self.winfact * 2 * self.Windowed_function(
self.x_nd1, -0.0796251, 0.0801192, 1)
self.sigma_tid = self.winfact * 2 * self.Windowed_function(
self.x_nd2, -0.206465, 0.226844,
-1) / (self.G / self.c**3 * self.M * self.m_sol)
#self.delta2prime = 1.62496*self.winfact*self.Windowed_function((self.f_tid-self.f_220_tilde)/self.f_220_tilde, 0.0188092, 0.338737, -1)
self.f0_pn = self.eps_insp * self.f_220_tilde
self.f0_pm = self.f_220_tilde
self.f0_rd = self.f_220_tilde
print("Tidal frequency %.2f" % self.f_tid)
print("Ringdown frequency: %.2f" % self.f_220_tilde)
#print("eps_tid", self.eps_tid)
#print("eps_insp", self.eps_insp)
#print("m_out", self.m_out)
#print("f_tidal", self.f_tid)
#print("f_220", self.f_220_tilde)
#print("f_220_ring", self.f_220_ringdown)
self.d_bbh = 0.015 / (self.G / self.c**3 * self.M * self.m_sol)
self.d = self.d_bbh + self.sigma_tid
def ParameterZones(config):
config_section_name = 'PARAMETER_ZONES'
binary_par = {}
binary_par["theta_i_deg"]=float(config[config_section_name]['theta_i_deg'])
binary_par["EOS"]=config[config_section_name]['EOS']
binary_par["chi_ns"]=float(config[config_section_name]['chi_ns'])
m_ns = binary_par["m_ns"]=float(config[config_section_name]['m_ns'])
q_min=float(config[config_section_name]['q_min'])
q_max=float(config[config_section_name]['q_max'])
q = np.linspace(q_min, q_max, 20*(q_max-q_min+1))
chi_bh_min=float(config[config_section_name]['chi_bh_min'])
chi_bh_max=float(config[config_section_name]['chi_bh_max'])
chi_bh = np.linspace(chi_bh_min, chi_bh_max, 15*(chi_bh_max-chi_bh_min)+1)
binary_par["type"]=config[config_section_name]['type']
G = 6.67*10**(-8)
c = 3*10**(10)
m_sol = 2*10**33
plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
plt.rcParams['ytick.right'] = plt.rcParams['ytick.labelright'] = True
m_out_chi = []
m_out_q = []
f_chi = []
f_q = []
qnm_object = wf.QNM_fit(2,2,0)
for j in range(len(chi_bh)):
m_out_arr = []
m_out_first_time = 0
f_tid_maj_f_220 = 0
binary_par['chi_bh'] = chi_bh[j]
for k in range(len(q)):
binary_par['q'] = q[k]
spin_object = sm.Spin_class(binary_par)
chi_f, theta_f, m_f, m_out = spin_object.FinalPar()
m_out_arr.append(m_out)
binary_par['q'] = q[k]
f_220 = qnm_object.f(m_f,chi_f)
xi_tid = fsolve(spin_object.XiTidal,10)
r_tid = xi_tid*(m_ns*m_sol*G/c**2)/spin_object.C*(1-2*spin_object.C)
f_tid = float(1./(np.pi*(chi_f*m_f*m_sol*G/c**2+(r_tid**3/(m_f*m_sol*G/c**2))**(1./2)))*c)
#print("")
#print("m_out",m_out)
#print("chi",chi_bh[j])
#print("q",q[k])
#print("")
if f_tid>=f_220 and f_tid_maj_f_220==0:
f_tid_maj_f_220=1
f_chi.append(chi_bh[j])
f_q.append(q[k])
#print("")
#print("f_220", f_220)
#print("f_tid",f_tid)
#print("chi",chi_bh[j])
#print("q",q[k])
#print("")
if m_out==0 and m_out_first_time==0:
m_out_first_time = 1
m_out_chi.append(chi_bh[j])
#print("")
#print(chi_bh[j])
m_out_q.append(q[k])
#print(q[k])
#print("")
#plt.plot(q, m_out_arr, label=r"$\chi_{BH}:$ %.2f" %chi_bh[j])
#plt.legend()
#plt.title(r"$M_{NS}$ = %.2f $M_{\odot}$, EOS = %s, $\theta_i$ = %d$^{\circ}$" %(binary_par["m_ns"], binary_par["EOS"], binary_par["theta_i_deg"]), y=1.08)
plt.plot(f_chi, f_q,label=r'$f_{tid}=f_{220}$')
plt.plot(m_out_chi, m_out_q, label=r'$M_{OUT}=0$')
plt.xlabel(r'$\chi_{BH}$')
plt.ylabel(r'$q$')
switch={
"2H":[[0.1,9],[0.5,9],[0.4,6.5],[-0.01,6.0],[-0.01,5.8]],
"H": [[0.2,8],[0.65,8],[0.6,4],[-0.05,3.4],[-0.05,3.2]],
"HB":[[0.2,7],[0.6,6],[0.6,3.5],[-0.05,3],[-0.05,2.7]],
"B": [[0.2,6],[0.65,5],[0.65,2.5],[-0.01,2.5],[-0.01,2.3]]
}
position = switch[binary_par["EOS"]]
plt.text(position[0][0],position[0][1], r'$f_{220}<f_{tid}, M_{OUT}=0$')
plt.text(position[1][0],position[1][1], r'$f_{220}<f_{tid}, M_{OUT}>0$')
plt.text(position[2][0],position[2][1], r'$f_{tid}<f_{220}, M_{OUT}>0$')
plt.text(position[3][0],position[3][1], r'$f_{tid}<f_{220}$')
plt.text(position[4][0],position[4][1], r'$M_{OUT}=0$')
plt.title(r"$M_{NS}=%.2f, EOS=%s, \theta_i=%d $"%(m_ns, binary_par["EOS"], binary_par["theta_i_deg"]),y=1.08)
plt.legend()
plt.show()