Refactor to Qiskit 1.x, add alternative ansatze#1
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- Migrate all code from deprecated Qiskit 0.x API (execute, Aer, IBMQ) to Qiskit 1.x (qiskit_aer, qiskit_ibm_runtime, Statevector) - Extract shared circuits and cost functions into sqgen.py module - Add 3 alternative variational ansatze (hardware_efficient, strongly_entangling, circular) alongside original MCMT - Fix mutable default arguments, remove globals, clean up imports - Replace readme.txt with README.md, add .gitignore, requirements.txt - Add test suite (test_sqgen.py) and benchmarking scripts - Include benchmark_results.csv: 1500-eval budget, n=1..5, 5 seeds Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- sqgen_fast.py: JIT-compiled statevector simulator (2652x faster than Qiskit Statevector path) with pre-allocated work arrays and split real/imaginary representation - Direct fidelity cost J = 1-F eliminates discriminator circuit overhead - L-BFGS-B with maxiter=5 replaces BFGS maxiter=1 - Achieves F=1.000 for n=1..5 with hardware_efficient and circular ansatze at budget=1500 evals (vs F=0.235/0.160 previously at n=5) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The direct fidelity cost J = 1 - F is the exact synergic regime
of the full SQGEN objective when θ_{z_D} = 0 (Remark after Def. 3.2
in sqgen_proof_revised.tex), not an approximation.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
qiskit_aer,qiskit_ibm_runtime,Statevector)sqgen.pymodule (removes code duplication between script and notebook)hardware_efficient,strongly_entangling,circular) alongside originalmcmt.gitignore,requirements.txt,README.mdBenchmark highlights (mean fidelity at 1500 evals)
Test plan
python test_sqgen.py— all 8 tests pass (param counts, circuit build, cost functions, QGAN loop, SQGEN loop)qiskit-ibm-runtimefake backend🤖 Generated with Claude Code