edaphos 0.9.0 — Pillar 6 meets real hardware and real chemistry

Summary

Promotes Pillar 6 (Quantum ML) from a statevector-only demonstration
to a NISQ-honest, chemistry-grounded pipeline. Three strictly
additive capabilities land together because each one only becomes
meaningful in the presence of the other two.

Shot-based execution

quantum_vqe_fit(backend = "aer_shots", shots = ...) wires
qiskit_aer.primitives.EstimatorV2 through the VQE loop. The
EfficientSU2 ansatz is transpiled to the standard
{id, rz, sx, x, cx, u} basis gate set so Aer can dispatch it, and
each energy evaluation is reconstructed from shots Monte-Carlo
samples with the expected 1/sqrt(shots) noise floor. SPSA
(Spall 1998) becomes the recommended optimiser under a stochastic
cost function.

Full IBM Quantum Runtime dispatch

backend = "ibmq" routes the VQE through
qiskit_ibm_runtime.EstimatorV2 inside a managed Session. The
ansatz is ISA-transpiled against the target backend's coupling map
via the preset pass manager (level 1), and the observable is
re-indexed with SparsePauliOp.apply_layout(). The new
mitigation argument maps {"none", "m3", "zne"} to IBM
resilience_level ∈ {0, 1, 2} (Kim et al. 2023, Nature 618,
500–505):

mitigation	Technique
"m3"	TREX + Matrix-free Measurement Mitigation for readout errors
"zne"	Zero-Noise Extrapolation over gate-folding scales

Plumbing additions:

• quantum_ibmq_submit() — low-level single-PUB primitive for
  custom hybrid loops that do not want quantum_vqe_fit()'s
  COBYLA/SPSA wrapper.
• quantum_ibmq_least_busy() — automatic backend selection.
• quantum_ibmq_backends(operational_only, simulator) — richer
  filtering.

qiskit-nature bridge

quantum_hamiltonian_from_pyscf() turns a molecular XYZ geometry
into a qubit Hamiltonian through the four-stage pipeline

XYZ → PySCF RHF → FreezeCore → ActiveSpace(n_e, n_o) → ParityMapper

and returns an edaphos_quantum_hamiltonian_nature that carries
the nuclear-repulsion, frozen-core and active-space energy shifts
as attributes so that quantum_nature_total_energy() can
reconstruct the full molecular energy from a VQE active-space fit.

Three curated organo-mineral presets ship via
quantum_hamiltonian_organo_mineral_nature():

Variant	Pedological role	Active space	Qubits
"formic_acid"	carboxylate –COOH — dominant humic functional group	(2e, 2o)	2
"methanediol"	ortho-diol — catechol-style Fe(III) chelator	(2e, 2o)	2
"ferric_formate"	monodentate Fe(III)–OOCH — minimum viable organo-mineral	(4e, 4o)	4

On formic acid the (2e, 2o) active-space VQE recovers ~34
milli-Hartree of correlation energy below the Hartree–Fock
reference — the canonical signature that the quantum circuit is
genuinely beating the mean-field baseline.

Documentation

• Vignette pilar6-quantum gains three new sections deriving the
  shot-based execution (§8), IBMQ + M3/ZNE mitigation (§9) and
  qiskit-nature organo-mineral Hamiltonians (§10) from first
  principles, and updates the roadmap to reflect v0.9.0 delivering
  the three items that were open at v0.8.0.
• README Pillar 6 section gains a VQE-to-hardware walk-through and
  a first-principles organo-mineral subsection.

Quality

• 20 new tests land in test-quantum-v09.R covering the shot-based
  VQE on H₂, the qiskit-nature formic-acid pipeline (both the
  Hamiltonian construction and total-energy reconstruction), the
  IBMQ preflight logic, and the mitigation ↔ resilience_level
  mapping.
• Full quantum test suite: 89/89 green.
• R CMD check --as-cran: 0 errors / 0 warnings / 2 harmless NOTEs
  (network timestamp + PySCF's own tempdir).

Install notes

New optional Python dependencies for the new features:

reticulate::py_install(
  c("qiskit-nature", "pyscf", "qiskit-ibm-runtime"),
  pip = TRUE
)
Sys.setenv(IBMQ_TOKEN = "<your-ibm-quantum-api-token>")  # only for backend = "ibmq"

All three packages are optional at load time; each public entry
point emits a targeted install-hint if its stack is missing.