Source code for master_thesis_code.datamodels.parameter_space

from collections.abc import Callable
from dataclasses import dataclass, field

import numpy as np

from master_thesis_code.exceptions import ParameterOutOfBoundsError
from master_thesis_code.galaxy_catalogue.handler import HostGalaxy
from master_thesis_code.physical_relations import dist, redshifted_mass


[docs] def uniform(lower_limit: float, upper_limit: float, rng: np.random.Generator) -> float: return float(rng.uniform(lower_limit, upper_limit))
[docs] def log_uniform(lower_limit: float, upper_limit: float, rng: np.random.Generator) -> float: lower_limit = np.log10(lower_limit) upper_limit = np.log10(upper_limit) uniform_log = uniform(lower_limit, upper_limit, rng) return float(10**uniform_log)
[docs] def polar_angle_distribution( lower_limit: float, upper_limit: float, rng: np.random.Generator ) -> float: return float(np.arccos(rng.uniform(-1.0, 1.0)))
[docs] @dataclass class Parameter: """Main class for parameters.""" symbol: str unit: str lower_limit: float upper_limit: float value: float = 0.0 derivative_epsilon: float = 1e-6 is_fixed: bool = False randomize_by_distribution: Callable[[float, float, np.random.Generator], float] = uniform
[docs] @dataclass class ParameterSpace: """ Dataclass to manage the parameter space of a simulation. """ # Per-parameter derivative_epsilon: Vallisneri (2008) arXiv:gr-qc/0703086 Eq. (A11) # Optimal step size for 5-point stencil (p=4): h* ≈ ε_machine^(1/4) × |x| ≈ 3.3e-4 × |x| # Each epsilon is chosen to be ~3e-4 × (representative parameter value). # Vallisneri (2008) arXiv:gr-qc/0703086 Eq. (A11) — per-param epsilon M: Parameter = field( default_factory=lambda: Parameter( symbol="M", unit="solar masses", lower_limit=1e4, upper_limit=1e7, randomize_by_distribution=log_uniform, # A tiny ABSOLUTE step (1 M_sun) on a ~1e5-1e6 M_sun mass: the EMRI phase is # extremely M-sensitive, so the finite-difference step must keep ∂Φ/∂M·(2ε) # well under a radian — the Vallisneri ε_mach^(1/4)·|x| heuristic (~60-100 # M_sun here) assumes f varies on scale |x|, which is false for an # oscillatory waveform. (Prior comment mis-stated the log-uniform midpoint # as ~3e3 M_sun; the [1e4,1e7] geometric midpoint is 10^5.5 ≈ 3e5. Any change # to this value needs a Fisher step-halving convergence study + /physics-change # — review PHY-09.) derivative_epsilon=1.0, ) ) # mass of the MBH (massive black hole) in solar masses mu: Parameter = field( default_factory=lambda: Parameter( symbol="mu", unit="solar masses", lower_limit=1, upper_limit=1e2, derivative_epsilon=0.01, # ~3e-4 × 30 SM (midpoint ~30 SM) ) ) # mass of the CO (compact object) in solar masses a: Parameter = field( default_factory=lambda: Parameter( symbol="a", unit="dimensionless", lower_limit=0.0, upper_limit=1, derivative_epsilon=1e-3, # ~3e-4 × 0.5 (dimensionless [0, 1]) ) ) # dimensionless spin of the MBH p0: Parameter = field( default_factory=lambda: Parameter( symbol="p0", unit="meters", lower_limit=10.0, upper_limit=16.0, derivative_epsilon=1e-3, # ~3e-4 × 13 (midpoint; dimensionless semi-latus rectum) ) ) # Kepler-orbit parameter: separation e0: Parameter = field( default_factory=lambda: Parameter( symbol="e0", unit="dimensionless", lower_limit=0.05, upper_limit=0.7, derivative_epsilon=1e-4, # ~3e-4 × 0.35 ≈ 1e-4 (dimensionless [0.05, 0.7]) ) ) # Kepler-orbit parameter: eccentricity x0: Parameter = field( default_factory=lambda: Parameter( symbol="x0", unit="dimensionless", lower_limit=-1.0, upper_limit=1.0, derivative_epsilon=1e-4, # symmetric around 0; use half-range scale 1e-4 ) ) # Kepler-orbit parameter: x_I0=cosI (I is the inclination) luminosity_distance: Parameter = field( default_factory=lambda: Parameter( symbol="luminosity_distance", unit="Gpc", lower_limit=0.0, # dist(HOST_DRAW_Z_MAX=1.5, h=H_MIN/100=0.60) = 13.0015 Gpc — the # campaign population reach at the lowest grid h. Model1CrossCheck # recomputes this exactly; the literal here protects bare # ParameterSpace() constructions from a sub-horizon cap (the old # 7 Gpc default silently rejected z >~ 0.9 events). upper_limit=13.1, derivative_epsilon=1e-4, # ~3e-4 × 1 Gpc ≈ 3e-4; use 1e-4 Gpc (= 0.1 Mpc) ) ) # luminosity distance qS: Parameter = field( default_factory=lambda: Parameter( symbol="qS", unit="radian", lower_limit=0.0, upper_limit=np.pi, randomize_by_distribution=polar_angle_distribution, derivative_epsilon=1e-4, # ~3e-4 × π/2 ≈ 5e-4; use 1e-4 rad ) ) # Sky location polar angle in ecliptic coordinates. phiS: Parameter = field( default_factory=lambda: Parameter( symbol="phiS", unit="radian", lower_limit=0.0, upper_limit=2 * np.pi, derivative_epsilon=1e-4, # ~3e-4 × π ≈ 1e-3; use 1e-4 rad ) ) # Sky location azimuthal angle in ecliptic coordinates. qK: Parameter = field( default_factory=lambda: Parameter( symbol="qK", unit="radian", lower_limit=0.0, upper_limit=np.pi, randomize_by_distribution=polar_angle_distribution, derivative_epsilon=1e-4, # same as qS ) ) # Initial BH spin polar angle in ecliptic coordinates. phiK: Parameter = field( default_factory=lambda: Parameter( symbol="phiK", unit="radian", lower_limit=0.0, upper_limit=2 * np.pi, derivative_epsilon=1e-4, # same as phiS ) ) # Initial BH spin azimuthal angle in ecliptic coordinates. Phi_phi0: Parameter = field( default_factory=lambda: Parameter( symbol="Phi_phi0", unit="radian", lower_limit=0.0, upper_limit=2 * np.pi, derivative_epsilon=1e-4, # ~3e-4 × π ≈ 1e-3; use 1e-4 rad ) ) # initial azimuthal phase Phi_theta0: Parameter = field( default_factory=lambda: Parameter( symbol="Phi_theta0", unit="radian", lower_limit=0.0, upper_limit=2 * np.pi, derivative_epsilon=1e-4, # same as Phi_phi0 ) ) # initial polar phase Phi_r0: Parameter = field( default_factory=lambda: Parameter( symbol="Phi_r0", unit="radian", lower_limit=0.0, upper_limit=2 * np.pi, derivative_epsilon=1e-4, # same as Phi_phi0 ) ) # initial radial phase
[docs] def randomize_parameter(self, parameter: Parameter, rng: np.random.Generator) -> None: parameter.value = parameter.randomize_by_distribution( parameter.lower_limit, parameter.upper_limit, rng ) setattr(self, parameter.symbol, parameter)
[docs] def randomize_parameters(self, rng: np.random.Generator | None = None) -> None: if rng is None: rng = np.random.default_rng() for parameter in vars(self).values(): if isinstance(parameter, Parameter) and not parameter.is_fixed: self.randomize_parameter(parameter=parameter, rng=rng) self._check_separatrix_guard()
def _check_separatrix_guard(self) -> None: """Reject draws too close to the plunge separatrix (G9 gate guard). The Schwarzschild separatrix is p_sep(e) = 6 + 2e (conservative for prograde Kerr, where p_sep is smaller); FEW waveforms are unphysical for p0 near/below it. Current bounds (p0 >= 10, e0 <= 0.7) satisfy this with margin >= 2.6, so this never fires today -- it protects against future bound changes silently entering the plunge regime. Stein & Warburton (2020), arXiv:1912.07609 (separatrix). """ p_sep = 6.0 + 2.0 * self.e0.value if self.p0.value < p_sep + 0.5: raise ParameterOutOfBoundsError( f"p0={self.p0.value:.3f} within 0.5 of the separatrix " f"p_sep(e0={self.e0.value:.3f})={p_sep:.3f}; adjust parameter bounds." )
[docs] def set_host_galaxy_parameters(self, host_galaxy: HostGalaxy, h: float) -> None: # FEW (Pn5AAKWaveform) expects the DETECTOR-FRAME (redshifted) mass # M_z = M_source·(1+z) in the M slot; redshift enters the mass, luminosity # distance enters the amplitude. The GLADE-derived catalog mass # host_galaxy.M is source-frame, so it must be lifted by (1+z) before the # waveform call so the stored CRB "M" column genuinely holds M_z (which the # Bayesian inference assumes: det.M = M_z, bayesian_statistics.py:1335). # Maggiore (2008) GW Vol. 1 §4.1.4; Babak et al. (2017) arXiv:1703.09722. self.M.value = redshifted_mass(host_galaxy.M, host_galaxy.z) # M_z = M·(1+z) self.phiS.value = host_galaxy.phiS self.qS.value = host_galaxy.qS # h_inj threaded explicitly per PE-01 (Phase 37); dark siren PE self-consistency at h_inj # (Gray et al. 2020, Laghi et al. 2021). h has no default — calling without h raises TypeError (SC-2). self.luminosity_distance.value = dist(host_galaxy.z, h=h) # SC-1: h_inj threaded
def _parameters_to_dict(self) -> dict: return { "M": self.M.value, "mu": self.mu.value, "a": self.a.value, "p0": self.p0.value, "e0": self.e0.value, "x0": self.x0.value, "luminosity_distance": self.luminosity_distance.value, "qS": self.qS.value, "phiS": self.phiS.value, "qK": self.qK.value, "phiK": self.phiK.value, "Phi_phi0": self.Phi_phi0.value, "Phi_theta0": self.Phi_theta0.value, "Phi_r0": self.Phi_r0.value, }