Abstract
Molecular dynamics (MD) and hybrid quantum–classical (QM/MM) methods provide powerful tools for simulating chemical and biological systems, yet their application to long-timescale, strongly coupled processes remains limited by non-integrability, chaotic sensitivity, and extreme time-scale separation. These limitations motivate complementary formalisms that emphasize structure, constraint, and evidence integration over brute-force trajectory resolution. Here we introduce the Gated Quantum Resonator (GQR) framework, a Bayesian circuit–Hamiltonian formalism in which reactive coordinates are modeled as coupled vibronic–electronic resonators with gateable interactions. Linearization around operating points maps the effective Hamiltonian onto electrical network analogues, enabling transparent parameterization and rapid Bayesian updating from spectroscopic and mechanistic evidence. The framework provides a unified language for describing non-Arrhenius kinetics, tunnelling assisted by constrained vibronic coherence, and mode-selective transport in open quantum systems. Without resolving full many-body trajectories, GQR identifies protected dynamical subspaces in which coherent evolution can persist under environmental coupling. This formulation is applicable across enzymatic catalysis, heterogeneous and electrocatalytic systems, and radiative phenomena, offering a tractable complement to conventional simulation approaches for hypothesis generation, model reduction, and mechanistic discrimination.
Supplementary materials
Title
Supplementary Material (V4)
Description
This Supplementary Information (V4) presents the Gated Quantum Resonator (GQR) as a circuit–Hamiltonian framework for catalysis and quantum dynamics, focused on enzymes but portable to heterogeneous/photocatalysis and materials. Part I (S1–S14) builds from LC-resonator pedagogy to bond-level and port–Hamiltonian forms, analytic two-mode models, active-site Hamiltonians, and explicit light–matter couplings. Bayesian gate-update rules link structure, spectroscopy, and control. The “Quantum Shield” gives an open-quantum criterion for sustaining coherence under noise; Landau–Zener–Stückelberg phase accumulation is treated in the same state space. Chiral-induced spin selectivity (CISS) and a nonlinear “Logic Vortex” attractor unify spin filtering with probability reduction and amplitude amplification. Part II (SM1–SM14) details methods: mechanical–electrical mapping, SPICE-class implementations, parameterization strategies, and experiment-facing workflows (polarization-resolved UPE, Stark-modulated 2D-IR, isotope editing, XFEL SFX). Worked protocols translate observables (lineshapes, Q, helicity) into GQR parameters (g, κ, γφ) and model fits. V4 emphasizes reproducibility (code listings) and clear roadmaps for validation.
Actions
Title
figure packet
Description
(NB currently these figures are also named 1-10, they are different to the supplemental figures)
Figure 1: Marcus-type free energy landscape showing ∆G‡ and reorganization λ.
Figure 2. Vibronic gating and multipath interference
Figure 3a. OEC structure (Shang et al., S1)
Figure 3b. Kok-cycle XFEL snapshots
Figure 3c. Multiwave connectivity schematic
Figure 4. Reaction success rate vs temperature (up-
loaded)
Figure 5. Kinetic isotope effect vs temperature (up-
loaded)
Figure 6. TST vs Quantum Tunneling (Python-derived)
Figure 7. Vibrational gating and interference (Python-
derived)
Figure 8. Enzyme promiscuity tuning (Python-derived)
Figure 9: Integrated demonstration of vibrational gating (green dashed) and interference
(magenta total probability).
Figure 10: Toy model of enzyme promiscuity: Product A (cyan) vs Product B (yellow)
tuned by vibrational frequency.
Actions
Title
14.1 quantum tunneling and interference demos
Description
NB all demos are on earlier versions of the model build, new demo data is under construction.
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Title
14.2 GQR v TST Temp/KIE sweep
Description
NB all demos are on earlier versions of the model build, new demo data is under construction.
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Title
14.3 Toy tunneling movie generation code
Description
NB all demos are on earlier versions of the model build, new demo data is under construction.
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Title
S13 Computational Illustrations of the GQR framework of S14
Description
this is a summary of the S14 Python code listings
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