Microscopic Gating Documentation

A minimal microscopic model for chemically gated bridging.

This package implements a theoretical framework for understanding how chemical binding controls transport through gated structures at the microscopic scale. The model connects molecular adsorption to macroscopic transport properties through a chain of physical mechanisms.

Core Concept 

The model describes how particle binding to receptor sites creates transient “bridges” that can either open or close transport pathways. The key insight is that transport is controlled by the statistics of bridge formation, which depends on:

Adsorption isotherms - How occupancy depends on concentration
Gating functions - How bridge probability depends on occupancy
Bridge statistics - Distribution of bridge counts
Escape dynamics - How bridges affect transport rates

The full chain is:

Langmuir/Hill occupancy → bridging probability → bridge-number distribution → gate open/closed

Quick Start 

from microscopic_gating import MicroscopicGatingModel, LangmuirIsotherm
from microscopic_gating.geometry import ConstantContactProbability
from microscopic_gating.gating import SymmetricGating
from microscopic_gating.types import SitePairCount

# Create isotherm
isotherm = LangmuirIsotherm(K=1.0)

# Create symmetric gating
gating = SymmetricGating(isotherm)

# Create full model
model = MicroscopicGatingModel(
    gating=gating,
    contact=ConstantContactProbability(chi=0.5),
    kappa_B=0.8,
    site_pairs=SitePairCount(M=10, N_acc=5)
)

# Calculate gate probabilities
import numpy as np
phi = np.logspace(-2, 2, 100)
P_open = model.P_open(phi)
P_closed = model.P_closed(phi)