Amplitude model with ampform

Amplitude model with ampform#

Formulate helicity amplitude model for \(p \gamma \to \eta \pi^0 p\) symbolically using AmpForm.

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import logging
import os
import warnings
from collections import defaultdict

import ampform
import graphviz
import ipywidgets as w
import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import numpy as np
import qrules
import sympy as sp
from ampform.dynamics.builder import RelativisticBreitWignerBuilder
from ampform.io import aslatex, improve_latex_rendering
from IPython.display import SVG, Image, Math, display
from qrules.particle import Particle, Spin, create_particle, load_pdg
from tensorwaves.data import (
    SympyDataTransformer,
    TFPhaseSpaceGenerator,
    TFUniformRealNumberGenerator,
)
from tensorwaves.function.sympy import create_parametrized_function

STATIC_PAGE = "EXECUTE_NB" in os.environ

os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
logging.disable(logging.WARNING)
warnings.filterwarnings("ignore")

improve_latex_rendering()
particle_db = load_pdg()

Generate transitions#

pgamma1 = Particle(
    name="pgamma1",
    latex=r"p\gamma (s1/2)",
    spin=0.5,
    mass=4.101931071854584,
    charge=1,
    isospin=Spin(1 / 2, +1 / 2),
    baryon_number=1,
    parity=-1,
    pid=99990,
)
pgamma2 = create_particle(
    template_particle=pgamma1,
    name="pgamma2",
    latex=R"p\gamma (s3/2)",
    spin=1.5,
    pid=pgamma1.pid + 1,
)
particle_db.update([pgamma1, pgamma2])

We keep the relevant information about branching fractions in the previous Branching fraction chapter. For simplicity, after the information about branching fraction, and under the current qrules results, we limit the intermediate resonances to be:

  • \(a(2)\) for \(\eta \pi^0\),

  • \(\Delta(1232)\) for \(\pi p\)”,

  • and “\(N(1535)\)” for both \(\pi^0 p\) and \(\eta p\).

reaction = qrules.generate_transitions(
    initial_state="pgamma1",
    final_state=["eta", "pi0", "p"],
    allowed_intermediate_particles=["a(2)(1320)", "N(1535)", "Delta(1232)"],
    allowed_interaction_types=["strong", "EM"],
    particle_db=particle_db,
    max_angular_momentum=3,
    max_spin_magnitude=3,
    mass_conservation_factor=0,
)
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src = qrules.io.asdot(reaction, collapse_graphs=True)
graphviz.Source(src)
../_images/faf0809dee2c1ed78bc55b7f161a80d9cfc296012665426ad6b1ed8b9f83e2c2.svg

Formulate model#

model_builder = ampform.get_builder(reaction)
model_builder.config.scalar_initial_state_mass = True
model_builder.config.stable_final_state_ids = 0, 1, 2
bw_builder = RelativisticBreitWignerBuilder(
    energy_dependent_width=False,
    form_factor=False,
)
for name in reaction.get_intermediate_particles().names:
    model_builder.dynamics.assign(name, bw_builder)
model = model_builder.formulate()

The first component of the full amplitude is shown below. The other terms are in similar way of formualation and thus not showing explicitly here again.

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(symbol, expr), *_ = model.amplitudes.items()
Math(aslatex({symbol: expr}, terms_per_line=1))
\[\begin{split}\displaystyle \begin{array}{rcl} A^{01}_{- \frac{1}{2}, 0, 0, - \frac{1}{2}} &=& \frac{C_{p\gamma (s1/2) \xrightarrow[S=3/2]{L=1} a_{2}(1320)^{0} p; a_{2}(1320)^{0} \xrightarrow[S=0]{L=2} \eta \pi^{0}} \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} C^{0,0}_{0,0,0,0} C^{\frac{1}{2},- \frac{1}{2}}_{1,0,\frac{3}{2},- \frac{1}{2}} C^{\frac{3}{2},- \frac{1}{2}}_{2,-1,\frac{1}{2},\frac{1}{2}} C^{2,0}_{2,0,0,0} D^{\frac{1}{2}}_{- \frac{1}{2},- \frac{1}{2}}\left(- \phi_{01},\theta_{01},0\right) D^{2}_{-1,0}\left(- \phi^{01}_{0},\theta^{01}_{0},0\right)}{- i \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} - m_{01}^{2} + \left(m_{a_{2}(1320)^{0}}\right)^{2}} \\ &+& \frac{C_{p\gamma (s1/2) \xrightarrow[S=3/2]{L=1} a_{2}(1320)^{0} p; a_{2}(1320)^{0} \xrightarrow[S=0]{L=2} \eta \pi^{0}} \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} C^{0,0}_{0,0,0,0} C^{\frac{1}{2},\frac{1}{2}}_{1,0,\frac{3}{2},\frac{1}{2}} C^{2,0}_{2,0,0,0} C^{\frac{3}{2},\frac{1}{2}}_{2,0,\frac{1}{2},\frac{1}{2}} D^{\frac{1}{2}}_{- \frac{1}{2},\frac{1}{2}}\left(- \phi_{01},\theta_{01},0\right) D^{2}_{0,0}\left(- \phi^{01}_{0},\theta^{01}_{0},0\right)}{- i \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} - m_{01}^{2} + \left(m_{a_{2}(1320)^{0}}\right)^{2}} \\ &+& \frac{C_{p\gamma (s1/2) \xrightarrow[S=5/2]{L=3} a_{2}(1320)^{0} p; a_{2}(1320)^{0} \xrightarrow[S=0]{L=2} \eta \pi^{0}} \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} C^{0,0}_{0,0,0,0} C^{\frac{5}{2},- \frac{1}{2}}_{2,-1,\frac{1}{2},\frac{1}{2}} C^{2,0}_{2,0,0,0} C^{\frac{1}{2},- \frac{1}{2}}_{3,0,\frac{5}{2},- \frac{1}{2}} D^{\frac{1}{2}}_{- \frac{1}{2},- \frac{1}{2}}\left(- \phi_{01},\theta_{01},0\right) D^{2}_{-1,0}\left(- \phi^{01}_{0},\theta^{01}_{0},0\right)}{- i \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} - m_{01}^{2} + \left(m_{a_{2}(1320)^{0}}\right)^{2}} \\ &+& \frac{C_{p\gamma (s1/2) \xrightarrow[S=5/2]{L=3} a_{2}(1320)^{0} p; a_{2}(1320)^{0} \xrightarrow[S=0]{L=2} \eta \pi^{0}} \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} C^{0,0}_{0,0,0,0} C^{2,0}_{2,0,0,0} C^{\frac{5}{2},\frac{1}{2}}_{2,0,\frac{1}{2},\frac{1}{2}} C^{\frac{1}{2},\frac{1}{2}}_{3,0,\frac{5}{2},\frac{1}{2}} D^{\frac{1}{2}}_{- \frac{1}{2},\frac{1}{2}}\left(- \phi_{01},\theta_{01},0\right) D^{2}_{0,0}\left(- \phi^{01}_{0},\theta^{01}_{0},0\right)}{- i \Gamma_{a_{2}(1320)^{0}} m_{a_{2}(1320)^{0}} - m_{01}^{2} + \left(m_{a_{2}(1320)^{0}}\right)^{2}} \\ \end{array}\end{split}\]
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sorted_parameter_defaults = {
    symbol: model.parameter_defaults[symbol]
    for symbol in sorted(model.parameter_defaults, key=str)
}
src = aslatex(sorted_parameter_defaults)
Math(src)
\[\begin{split}\displaystyle \begin{array}{rcl} C_{p\gamma (s1/2) \xrightarrow[S=1/2]{L=1} N(1535)^{+} \eta; N(1535)^{+} \xrightarrow[S=1/2]{L=0} p \pi^{0}} &=& 1+0i \\ C_{p\gamma (s1/2) \xrightarrow[S=1/2]{L=1} N(1535)^{+} \pi^{0}; N(1535)^{+} \xrightarrow[S=1/2]{L=0} \eta p} &=& 1+0i \\ C_{p\gamma (s1/2) \xrightarrow[S=3/2]{L=1} a_{2}(1320)^{0} p; a_{2}(1320)^{0} \xrightarrow[S=0]{L=2} \eta \pi^{0}} &=& 1+0i \\ C_{p\gamma (s1/2) \xrightarrow[S=3/2]{L=2} \Delta(1232)^{+} \eta; \Delta(1232)^{+} \xrightarrow[S=1/2]{L=1} p \pi^{0}} &=& 1+0i \\ C_{p\gamma (s1/2) \xrightarrow[S=5/2]{L=3} a_{2}(1320)^{0} p; a_{2}(1320)^{0} \xrightarrow[S=0]{L=2} \eta \pi^{0}} &=& 1+0i \\ \Gamma_{N(1535)^{+}} &=& 0.15 \\ \Gamma_{\Delta(1232)^{+}} &=& 0.117 \\ \Gamma_{a_{2}(1320)^{0}} &=& 0.107 \\ m_{0} &=& 0.547862 \\ m_{012} &=& 4.101931071854584 \\ m_{1} &=& 0.1349768 \\ m_{2} &=& 0.93827208816 \\ m_{N(1535)^{+}} &=& 1.53 \\ m_{\Delta(1232)^{+}} &=& 1.232 \\ m_{a_{2}(1320)^{0}} &=& 1.3182 \\ \end{array}\end{split}\]
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Math(aslatex(model.kinematic_variables))
\[\begin{split}\displaystyle \begin{array}{rcl} m_{01} &=& m_{{p}_{01}} \\ m_{02} &=& m_{{p}_{02}} \\ m_{12} &=& m_{{p}_{12}} \\ \phi_{0} &=& \phi\left({p}_{12}\right) \\ \phi^{01}_{0} &=& \phi\left(\boldsymbol{B_z}\left(\frac{\left|\vec{{p}_{01}}\right|}{E\left({p}_{01}\right)}\right) \boldsymbol{R_y}\left(- \theta\left({p}_{01}\right)\right) \boldsymbol{R_z}\left(- \phi\left({p}_{01}\right)\right) p_{0}\right) \\ \phi^{02}_{0} &=& \phi\left(\boldsymbol{B_z}\left(\frac{\left|\vec{{p}_{02}}\right|}{E\left({p}_{02}\right)}\right) \boldsymbol{R_y}\left(- \theta\left({p}_{02}\right)\right) \boldsymbol{R_z}\left(- \phi\left({p}_{02}\right)\right) p_{0}\right) \\ \phi_{01} &=& \phi\left({p}_{01}\right) \\ \phi^{12}_{1} &=& \phi\left(\boldsymbol{B_z}\left(\frac{\left|\vec{{p}_{12}}\right|}{E\left({p}_{12}\right)}\right) \boldsymbol{R_y}\left(- \theta\left({p}_{12}\right)\right) \boldsymbol{R_z}\left(- \phi\left({p}_{12}\right)\right) p_{1}\right) \\ \phi_{02} &=& \phi\left({p}_{02}\right) \\ \theta_{0} &=& \theta\left({p}_{12}\right) \\ \theta^{01}_{0} &=& \theta\left(\boldsymbol{B_z}\left(\frac{\left|\vec{{p}_{01}}\right|}{E\left({p}_{01}\right)}\right) \boldsymbol{R_y}\left(- \theta\left({p}_{01}\right)\right) \boldsymbol{R_z}\left(- \phi\left({p}_{01}\right)\right) p_{0}\right) \\ \theta^{02}_{0} &=& \theta\left(\boldsymbol{B_z}\left(\frac{\left|\vec{{p}_{02}}\right|}{E\left({p}_{02}\right)}\right) \boldsymbol{R_y}\left(- \theta\left({p}_{02}\right)\right) \boldsymbol{R_z}\left(- \phi\left({p}_{02}\right)\right) p_{0}\right) \\ \theta_{01} &=& \theta\left({p}_{01}\right) \\ \theta^{12}_{1} &=& \theta\left(\boldsymbol{B_z}\left(\frac{\left|\vec{{p}_{12}}\right|}{E\left({p}_{12}\right)}\right) \boldsymbol{R_y}\left(- \theta\left({p}_{12}\right)\right) \boldsymbol{R_z}\left(- \phi\left({p}_{12}\right)\right) p_{1}\right) \\ \theta_{02} &=& \theta\left({p}_{02}\right) \\ \end{array}\end{split}\]

Visualization#

unfolded_expression = model.expression.doit()
intensity_func = create_parametrized_function(
    expression=unfolded_expression,
    parameters=model.parameter_defaults,
    backend="jax",
)
phsp_event = 500_000
rng = TFUniformRealNumberGenerator(seed=0)
phsp_generator = TFPhaseSpaceGenerator(
    initial_state_mass=reaction.initial_state[-1].mass,
    final_state_masses={i: p.mass for i, p in reaction.final_state.items()},
)
phsp_momenta = phsp_generator.generate(phsp_event, rng)
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WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1730122887.772450    3497 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1730122887.776682    3497 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1730122894.129640    3560 service.cc:148] XLA service 0x7f5db418c780 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
I0000 00:00:1730122894.129685    3560 service.cc:156]   StreamExecutor device (0): Host, Default Version
I0000 00:00:1730122894.150112    3561 device_compiler.h:188] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.
helicity_transformer = SympyDataTransformer.from_sympy(
    model.kinematic_variables,
    backend="jax",
)
phsp = helicity_transformer(phsp_momenta)
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resonances = defaultdict(set)
for transition in reaction.transitions:
    topology = transition.topology
    top_decay_products = topology.get_edge_ids_outgoing_from_node(0)
    (resonance_id, resonance), *_ = transition.intermediate_states.items()
    recoil_id, *_ = top_decay_products - {resonance_id}
    resonances[recoil_id].add(resonance.particle)
resonances = {k: sorted(v, key=lambda p: p.mass) for k, v in resonances.items()}
{k: [p.name for p in v] for k, v in resonances.items()}
{0: ['Delta(1232)+', 'N(1535)+'], 1: ['N(1535)+'], 2: ['a(2)(1320)0']}
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sliders = {}
categorized_sliders_m = defaultdict(list)
categorized_sliders_gamma = defaultdict(list)
categorized_cphi_pair = defaultdict(list)

for symbol, value in model.parameter_defaults.items():
    if symbol.name.startswith(R"\Gamma_{"):
        slider = w.FloatSlider(
            description=Rf"\({sp.latex(symbol)}\)",
            min=0.0,
            max=1.0,
            step=0.01,
            value=value,
            continuous_update=False,
        )
        sliders[symbol.name] = slider
        if symbol.name.startswith(R"\Gamma_{N"):
            categorized_sliders_gamma[0].append(slider)
        elif symbol.name.startswith(R"\Gamma_{\D"):
            categorized_sliders_gamma[1].append(slider)
        elif symbol.name.startswith(R"\Gamma_{a"):
            categorized_sliders_gamma[2].append(slider)

    if symbol.name.startswith("m_{"):
        slider = w.FloatSlider(
            description=Rf"\({sp.latex(symbol)}\)",
            min=0.63,
            max=4,
            step=0.01,
            value=value,
            continuous_update=False,
        )
        sliders[symbol.name] = slider
        if symbol.name.startswith("m_{N"):
            categorized_sliders_m[0].append(slider)
        elif symbol.name.startswith(R"m_{\D"):
            categorized_sliders_m[1].append(slider)
        elif symbol.name.startswith("m_{a"):
            categorized_sliders_m[2].append(slider)

    if symbol.name.startswith("C_{"):
        c_latex = sp.latex(symbol)
        phi_latex = c_latex.replace("C", R"\phi", 1)

        slider_c = w.FloatSlider(
            description=Rf"\({c_latex}\)",
            min=0,
            max=10,
            step=0.01,
            value=abs(value),
            continuous_update=False,
        )
        slider_phi = w.FloatSlider(
            description=Rf"\({phi_latex}\)",
            min=-np.pi,
            max=+np.pi,
            step=0.01,
            value=np.angle(value),
            continuous_update=False,
        )

        sliders[symbol.name] = slider_c
        sliders[symbol.name.replace("C", "phi", 1)] = slider_phi

        cphi_hbox = w.HBox([slider_c, slider_phi])
        if R"\D" in symbol.name:
            categorized_cphi_pair[1].append(cphi_hbox)
        elif "N" in symbol.name:
            categorized_cphi_pair[0].append(cphi_hbox)
        elif "a" in symbol.name:
            categorized_cphi_pair[2].append(cphi_hbox)

tab_contents = []
resonances_name = ["N*", "Δ*", "a₂*"]
for i in range(len(resonances_name)):
    tab_content = w.VBox([
        w.HBox(categorized_sliders_m[i] + categorized_sliders_gamma[i]),
        w.VBox(categorized_cphi_pair[i]),
    ])
    tab_contents.append(tab_content)
UI = w.Tab(tab_contents, titles=resonances_name)
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def insert_phi(parameters: dict) -> dict:
    updated_parameters = {}
    for key, value in parameters.items():
        if key.startswith("phi_"):
            continue
        if key.startswith("C_"):
            phi_key = key.replace("C_", "phi_")
            if phi_key in parameters:
                phi = parameters[phi_key]
                value *= np.exp(1j * phi)  # noqa:PLW2901
        updated_parameters[key] = value
    return updated_parameters
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%matplotlib widget
%config InlineBackend.figure_formats = ['png']
fig_2d, ax_2d = plt.subplots(dpi=200)
ax_2d.set_title("Model-weighted Phase space Dalitz Plot")
ax_2d.set_xlabel(R"$m^2(\eta \pi^0)\;\left[\mathrm{GeV}^2\right]$")
ax_2d.set_ylabel(R"$m^2(\pi^0 p)\;\left[\mathrm{GeV}^2\right]$")

mesh = None


def update_histogram(**parameters):
    global mesh
    parameters = insert_phi(parameters)
    intensity_func.update_parameters(parameters)
    intensity_weights = intensity_func(phsp)
    bin_values, xedges, yedges = jnp.histogram2d(
        phsp["m_01"].real ** 2,
        phsp["m_12"].real ** 2,
        bins=200,
        weights=intensity_weights,
        density=True,
    )
    bin_values = jnp.where(bin_values < 1e-6, jnp.nan, bin_values)
    x, y = jnp.meshgrid(xedges[:-1], yedges[:-1])
    if mesh is None:
        mesh = ax_2d.pcolormesh(x, y, bin_values.T, cmap="jet", vmax=0.15)
    else:
        mesh.set_array(bin_values.T)
    fig_2d.canvas.draw_idle()


interactive_plot = w.interactive_output(update_histogram, sliders)
fig_2d.tight_layout()
fig_2d.colorbar(mesh, ax=ax_2d)

if STATIC_PAGE:
    filename = "dalitz-plot-auto.png"
    fig_2d.savefig(filename)
    plt.close(fig_2d)
    display(UI, Image(filename))
else:
    display(UI, interactive_plot)
../_images/516b161a96bd7db5d975535c0c8fa2f0cd9d3a442d5cb5f64be4769e5b569e56.png
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%matplotlib widget
%config InlineBackend.figure_formats = ['svg']

fig, axes = plt.subplots(figsize=(11, 3.5), ncols=3, sharey=True)
fig.canvas.toolbar_visible = False
fig.canvas.header_visible = False
fig.canvas.footer_visible = False
ax1, ax2, ax3 = axes

for recoil_id, ax in enumerate(axes):
    decay_products = sorted({0, 1, 2} - {recoil_id})
    product_latex = " ".join([reaction.final_state[i].latex for i in decay_products])
    ax.set_xlabel(f"$m({product_latex})$ [GeV]")

LINES = 3 * [None]
RESONANCE_LINES = defaultdict(dict)


def update_plot(**parameters):
    parameters = insert_phi(parameters)
    intensity_func.update_parameters(parameters)
    intensities = intensity_func(phsp)
    max_value = 0
    resonance_colors: dict[Particle, int] = {}
    color_id = 0
    for recoil_id, ax in enumerate(axes):
        decay_products = sorted({0, 1, 2} - {recoil_id})
        key = f"m_{''.join(str(i) for i in decay_products)}"
        bin_values, bin_edges = jax.numpy.histogram(
            phsp[key].real,
            bins=120,
            density=True,
            weights=intensities,
        )
        max_value = max(max_value, bin_values.max())

        if LINES[recoil_id] is None:
            LINES[recoil_id] = ax.step(bin_edges[:-1], bin_values, alpha=0.5)[0]
        else:
            LINES[recoil_id].set_ydata(bin_values)

        for resonance in resonances[recoil_id]:
            key = f"m_{{{resonance.latex}}}"
            val = parameters.get(key, resonance.mass)
            resonance_line = RESONANCE_LINES[recoil_id].get(resonance.name)
            if resonance_line is None:
                RESONANCE_LINES[recoil_id][resonance.name] = ax.axvline(
                    val,
                    c=f"C{resonance_colors.get(resonance, color_id)}",
                    ls="dotted",
                    label=resonance.name,
                )
            else:
                resonance_line.set_xdata([val, val])
            if resonance not in resonance_colors:
                resonance_colors[resonance] = color_id
                color_id += 1

    for ax in axes:
        ax.set_ylim(0, max_value * 1.1)


interactive_plot = w.interactive_output(update_plot, sliders)
for ax in axes:
    ax.legend(fontsize="small")
fig.tight_layout()

if STATIC_PAGE:
    filename = "1d-histograms-auto.svg"
    fig.savefig(filename)
    plt.close(fig)
    display(UI, SVG(filename))
else:
    display(UI, interactive_plot)
../_images/7dd95035884a934cdd48a685f703011745963bd95d7b45228043415cfe5f299d.svg