mercurial.params.empirical module

Empirical parameter database for the MERCURIAL framework.

This file contains all literature‑driven and physically justified parameters for neural models (Wilson‑Cowan, Jansen‑Rit, Hopf, Kuramoto, Hebbian), sensory transduction (photoreceptor, hair cell), quantum field propagation, entanglement, and the core Priorities 1‑4 (thermodynamics, pattern formation, impression formation, LADDER coupling, branch decoherence).

class mercurial.params.empirical.DecoherenceParams(gamma_dec0: float = 0.1, kappa_env: float = 0.01, theta_branch: float = 0.7)[source]

Bases: object

Branch decoherence parameters (Priority 4).

gamma_dec0: float = 0.1
kappa_env: float = 0.01
theta_branch: float = 0.7
class mercurial.params.empirical.EntanglementParams(squeezing_r: float = 0.5, squeezing_theta: float = 0.0, thermal_nbar: float = 0.05, coherence_length: float = 1.0)[source]

Bases: object

Quantum optical parameters for entanglement measures.

coherence_length: float = 1.0
squeezing_r: float = 0.5
squeezing_theta: float = 0.0
thermal_nbar: float = 0.05
class mercurial.params.empirical.FDTDParams(tissue_type: str = 'gray_matter', frequency: float = 1000000000.0, eps_r_gray: float = 52.0, sigma_gray: float = 0.98, eps_r_white: float = 38.0, sigma_white: float = 0.6)[source]

Bases: object

Biological tissue dielectric properties for FDTD.

eps_r_gray: float = 52.0
eps_r_white: float = 38.0
frequency: float = 1000000000.0
sigma_gray: float = 0.98
sigma_white: float = 0.6
tissue_type: str = 'gray_matter'
class mercurial.params.empirical.HairCellParams(g_max: float = 5e-09, z: float = 0.2, x0: float = 0.0, tau_fast: float = 0.002, tau_slow: float = 0.05)[source]

Bases: object

Hair cell Boltzmann transduction parameters.

g_max: float = 5e-09
tau_fast: float = 0.002
tau_slow: float = 0.05
x0: float = 0.0
z: float = 0.2
class mercurial.params.empirical.HebbianParams(learning_rate: float = 0.001, decay: float = 0.2, stdp_ltp_rate: float = 0.001, stdp_ltd_rate: float = 0.001, stdp_tau_plus: float = 0.02, stdp_tau_minus: float = 0.02)[source]

Bases: object

Parameters for Hebbian plasticity.

decay: float = 0.2
learning_rate: float = 0.001
stdp_ltd_rate: float = 0.001
stdp_ltp_rate: float = 0.001
stdp_tau_minus: float = 0.02
stdp_tau_plus: float = 0.02
class mercurial.params.empirical.HopfParams(alpha_rest: float = -0.1, alpha_active: float = 0.1, beta: float = 1.0, omega_alpha: float = 62.83185307179586, omega_beta: float = 125.66370614359172, omega_gamma: float = 251.32741228718345, sigma: float = 0.05)[source]

Bases: object

Parameters for Hopf oscillator (frequency bands).

alpha_active: float = 0.1
alpha_rest: float = -0.1
beta: float = 1.0
omega_alpha: float = 62.83185307179586
omega_beta: float = 125.66370614359172
omega_gamma: float = 251.32741228718345
sigma: float = 0.05
class mercurial.params.empirical.ImpressionParams(eta_STP: float = 0.1, eta_LTP: float = 0.02, gamma_forget: float = 0.001, kappa_emo: float = 2.0, beta_rep: float = 0.5)[source]

Bases: object

Memory consolidation and emotional parameters (Priority 3).

beta_rep: float = 0.5
eta_LTP: float = 0.02
eta_STP: float = 0.1
gamma_forget: float = 0.001
kappa_emo: float = 2.0
class mercurial.params.empirical.JansenRitParams(a: float = 100.0, b: float = 50.0, A: float = 3.25, B: float = 22.0, C: float = 135.0, C1: float = 135.0, C2: float = 108.0, C3: float = 33.75, C4: float = 33.75, e0: float = 5.0, v0: float = 6.0, r: float = 0.56)[source]

Bases: object

Literature‑sourced Jansen‑Rit parameters.

A: float = 3.25
B: float = 22.0
C: float = 135.0
C1: float = 135.0
C2: float = 108.0
C3: float = 33.75
C4: float = 33.75
a: float = 100.0
b: float = 50.0
e0: float = 5.0
r: float = 0.56
v0: float = 6.0
class mercurial.params.empirical.KuramotoParams(coupling_weak: float = 0.1, coupling_moderate: float = 0.5, coupling_strong: float = 0.9, phase_noise: float = 0.05)[source]

Bases: object

Parameters for Kuramoto oscillator.

coupling_moderate: float = 0.5
coupling_strong: float = 0.9
coupling_weak: float = 0.1
phase_noise: float = 0.05
class mercurial.params.empirical.LadderCouplingParams(K0: float = 0.1, l_decay: float = 1.0, L_min: int = 7, L_max: int = 10)[source]

Bases: object

Cross‑level coupling (LADDER) parameters (Priority 4).

K0: float = 0.1
L_max: int = 10
L_min: int = 7
l_decay: float = 1.0
class mercurial.params.empirical.NeuralFieldParams(A_e: float = 1.0, sigma_e: float = 0.5, A_i: float = 0.8, sigma_i: float = 1.5, dx: float = 0.5)[source]

Bases: object

2D neural field lateral connectivity parameters.

A_e: float = 1.0
A_i: float = 0.8
dx: float = 0.5
sigma_e: float = 0.5
sigma_i: float = 1.5
class mercurial.params.empirical.PatternCompletionParams(n_glomeruli: int = 8000, n_mitral_cells: int = 40000, n_piriform_neurons: int = 20000000, tau_a: float = 0.02, pattern_sparsity: float = 0.1, learning_rate: float = 0.001)[source]

Bases: object

Olfactory/gustatory network parameters.

learning_rate: float = 0.001
n_glomeruli: int = 8000
n_mitral_cells: int = 40000
n_piriform_neurons: int = 20000000
pattern_sparsity: float = 0.1
tau_a: float = 0.02
class mercurial.params.empirical.PatternFormationParams(diff_ratio: float = 0.1, reaction_rate: float = 0.05, decay_rate: float = 0.01, growth_param: float = 0.5)[source]

Bases: object

Reaction‑diffusion / Turing parameters (Priority 2).

decay_rate: float = 0.01
diff_ratio: float = 0.1
growth_param: float = 0.5
reaction_rate: float = 0.05
class mercurial.params.empirical.PhotoreceptorParams(R_max: float = 100.0, I50: float = 100.0, n: float = 1.0, tau_p: float = 0.02, alpha_adapt: float = 0.1)[source]

Bases: object

Naka‑Rushton photoreceptor model parameters.

I50: float = 100.0
R_max: float = 100.0
alpha_adapt: float = 0.1
n: float = 1.0
tau_p: float = 0.02
class mercurial.params.empirical.QFTParams(mass_scalar: float = 0.5, mass_dirac: float = 0.5, dx: float = 0.05, courant_factor: float = 0.707)[source]

Bases: object

Parameters for Klein‑Gordon and Dirac field solvers.

courant_factor: float = 0.707
dx: float = 0.05
mass_dirac: float = 0.5
mass_scalar: float = 0.5
class mercurial.params.empirical.ThermodynamicParams(T_eff: float = 1.0, k_eff: float = 1.0, eta: float = 0.01, gamma0: float = 0.001)[source]

Bases: object

Parameters for free energy and entropy (Priority 1).

T_eff: float = 1.0
eta: float = 0.01
gamma0: float = 0.001
k_eff: float = 1.0
class mercurial.params.empirical.WilsonCowanParams(tau_e: float = 0.0025, tau_i: float = 0.00375, a_e: float = 1.5, a_i: float = 1.5, mu_e: float = 3.0, mu_i: float = 3.0, w_ee: float = 16.0, w_ie: float = 12.0, w_ei: float = 15.0, w_ii: float = 3.0, sigma_e: float = 5e-05, sigma_i: float = 5e-05)[source]

Bases: object

Literature‑sourced Wilson‑Cowan parameters.

a_e: float = 1.5
a_i: float = 1.5
mu_e: float = 3.0
mu_i: float = 3.0
sigma_e: float = 5e-05
sigma_i: float = 5e-05
tau_e: float = 0.0025
tau_i: float = 0.00375
w_ee: float = 16.0
w_ei: float = 15.0
w_ie: float = 12.0
w_ii: float = 3.0
mercurial.params.empirical.get_all_parameters() Dict[str, Any][source]

Return all empirical parameters as a dictionary.