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Drop the HF initial_occupancies seed; ship a curated H2O counts file (#13)
initial_occupancies was passed unconditionally, which is not the inert "insurance" its comment claimed. qiskit_addon_sqd._prepare_ci_strings branches on it: None -> postselect_by_hamming_right_and_left(): keep only the bitstrings that already have the target Hamming weights. provided -> recover_configurations(): take the full noisy set and bit-flip every string toward the target. So supplying it replaced postselection with configuration recovery in every run, including --counts runs. At iteration 1 the only occupancies available are Hartree-Fock (all virtuals exactly 0.0), so the subspace was largely synthesised by bit-flips against a mean-field prior instead of built from sampled configurations. Published SQD postselects at iteration 1 and uses solver-derived occupancies from iteration 2 on, which is what qiskit-addon-dice-solver's test_n2_sbd.py already does. Changes: - run_sqd_sbd.py: drop the HF occupancy block and the initial_occupancies= argument. - run_sqd_sbd.py: the --samples fallback now uses generate_counts_bipartite_hamming() instead of generate_bit_array_uniform(), so generated bitstrings carry the target Hamming weights. Uniform strings are postselected away except near half filling: the survival rate is C(norb,ne)^2 / 4^norb, i.e. 0 of 3000 for H2O (5 of 24) versus 3000 of 3000 with this generator. - Add python/examples/count_dict_h2o.json: 275 bitstrings in [beta | alpha] layout, from the vendored h2o-1em3-alpha.txt list with each alpha half-determinant reused for both spin sectors. Counts are all 1 -- a curated determinant list, not a shot histogram. - Notebook: load that file instead of generating random bitstrings, and drop initial_occupancies. Previously it reached ~-76.2 only because the HF seed pulled uniform-random strings toward HF. Validated (GB200, --device gpu, notebook's settings: samples_per_batch 300, 1 batch, 2 iterations): -76.2359466308 Ha, matching the -76.23594663 that vendor/sbd-upstream/data/h2o/README.md reports for the 1.0e-3 / 275-bitstring / 7.56e4-determinant subspace. All 275 bitstrings survive postselection, so no occupancy seed is required.
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‎python/examples/count_dict_h2o.json‎

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