Three-Mode Solvation Comparison

Compare fixed, hf_corrected, and dynamic solvation modes. Run H2 MC Solvation first. This comparison includes the more expensive dynamic circuit.

Run The Script

uv run python examples/qmmm/h2_three_mode_comparison.py

Modes

Mode	Formula	Role
fixed	E_QPE(H_vac) + E_MM	Fast baseline that ignores solvent changes in correlation
hf_corrected	E_HF(R) + E_MM	HF-level MM embedding with interval QPE diagnostics
dynamic	E_QPE(H_eff) + E_MM	Runtime MM-embedded QPE coefficients

The comparison delegates analysis to q2m3.solvation.analysis.run_mode_comparison().

Compile-Once Idea

        flowchart LR
    accTitle: Three Mode Execution
    accDescr: Fixed and dynamic modes compile reusable QPE structures while the MC loop updates solvent coordinates and energies.

    mc["MC solvent states"]
    fixed["fixed<br/>vacuum Hamiltonian"]
    hf["hf_corrected<br/>HF energy path"]
    dynamic["dynamic<br/>runtime coefficients"]
    analysis["mode comparison<br/>delta_corr-pol"]

    mc --> fixed
    mc --> hf
    mc --> dynamic
    fixed --> analysis
    hf --> analysis
    dynamic --> analysis
    

Dynamic mode uses Hamiltonian coefficients that Catalyst can trace at runtime. Catalyst compiles the circuit structure once. The coefficients change across MC steps.

Reading The Result

The key scientific quantity is delta_corr-pol, the correlation-polarization coupling term. For small H2 runs, it measures whether QPE energy changes materially when MM embedding changes the Hamiltonian as well as the classical correction.

Optional H3O+ Diagnostics

H3O+ workflows use a larger active space and many more Hamiltonian terms. The public H3O+ scripts are useful for ionic-solvation diagnostics, but they are not the default tutorial path. Use a 16 GB+ RAM machine for h3o_mc_solvation.py and a 30 GB+ RAM machine for 8-bit or dynamic Trotter diagnostics.