This page answers in plain language: Did the test fail or succeed? How does it relate to holographic work? What can we safely tell customers and researchers?
Three simple boxes. This is a judgment for non-experts; details follow.
The hardware runs completed; numbers are above random guessing for grouping. We did not get “no signal” or broken science.
Structure is visible in measurement statistics on IBM Fez—enough to be meaningful, not enough to call “problem solved.” This is the honest middle: real evidence, NISQ-limited.
We do not claim near-perfect recovery of hidden links or clusters. That would need shallower circuits, more shots, better decoders, and/or better devices—next steps, not shame.
Random baseline to remember: for 3 groups, blind guessing labels hits about 33% on a fair cluster score. Our cluster scores are usually in the ~42–59% range → clearly better than luck.
Same experiment family: hide a relational pattern (who is linked to whom, in groups) in a quantum circuit, run many shots, then try to see that pattern again in the data—without reading a single “secret bitstring” as the main goal.
| Run | Setup | Typical cluster score* | Typical link (edge) F1* | Transpiled depth (contexts 0–2) |
|---|---|---|---|---|
| A | 32 qubits, 8192 shots per context, 3 separate Fez jobs | ~53% / 59% / 50% | ~0.23 / 0.22 / 0.19 | ~282 / 235 / 334 |
| B (tuned) | 24 qubits, 16384 shots per context, shallower circuits | ~50% / 42% / 54% | ~0.31 / 0.21 / 0.25 | ~155 / 236 / 222 |
| C (confirmation batch) | 24 qubits, 8192 shots, observed fraction 0.6, 7 seeds (independent jobs) | mean 52.04% (95% CI 48.04–56.04%) | n/a (partial-observation mode) | ~389–461 |
* Cluster score = match of recovered groups to hidden groups (after fair label alignment). Edge F1 = balance of finding true links vs falsely claiming links (median threshold on correlations).
Takeaway: Run C is the most important quality check: 7/7 seeds above chance (chance = 33.33% for 3 groups), with moderate but repeatable structure signal. This supports an honest claim of reproducible above-chance recovery, while staying below a high-strength breakthrough threshold.
Artifacts: qpc_swr_v1_results.json (run A), qpc_swr_v1_24q_16384.json (run B), qpc_csi_campaign/*.json and qpc_csi_opt_sweep/fez_n24_obs06_opt0_seed*.json (run C). Scripts: qpc_swr_v1_fez.py, qpc_csi_v2_fez.py.
Other Fez hardware runs. A Kochen–Specker (Mermin–Peres) contextuality test also ran on Fez: 18 circuits, 2 qubits. With QPC reducer: row +1, col −1 (ideal). Raw: col3 −0.72. Task framing: Quantum contextuality task. Noise Reducer.
They belong to the same QPC “family” (information in how the circuit is built and what you measure), but they ask different questions:
| Holographic memory line | QPC-SWR v1 (this test) |
|---|---|
| Can we store a pattern in a spread-out way and still reconstruct it from partial or redundant readout? | Can we hide a relationship map (groups + links) and see it again in pairwise statistics from many samples? |
| Success read as reconstruction accuracy, majority vs single-qubit, etc. | Success read as structure recovery (clusters + edges), not “did we get every bit right.” |
Does SWR “go beyond” holography? In one direction, yes: it targets relational / many-body style structure in correlations, which is a different—and scientifically serious—lens than “read out the pattern.” It does not replace holographic demos; it adds a complementary story.
Site-wide statement (all QPC tests on hardware). The main practical limit on our hardware demonstrations is universal NISQ noise and circuit depth—not a defect specific to QPC. We report both ideal / in-principle behavior where available and realistic processor outcomes. When results are only partly satisfying compared to the full QPC story, that reflects today’s machine limits, not proof that the quantum computation concept is wrong. Fuller expression of QPC capabilities on chip tracks better devices, mitigation, and eventually error correction—the same path as the rest of the quantum industry. See also the Holographic Memory report and Quantum-native task pages.
Investor / business version. On IBM Fez, QPC structure-recovery tests now show a repeatable hardware signal: in the latest confirmation batch, all 7/7 runs were above chance, with mean recovery 52.04% (95% CI 48.04–56.04%). This indicates real traction on current chips while keeping expectations realistic under NISQ limits.
Research-safe version. We encoded hidden relational structure and decoded it from repeated measurement statistics (not full tomography). Results are consistently above chance across seeds, supporting recoverable structure under noise, but remain in a moderate-signal regime; we do not claim full structure recovery or quantum advantage from this dataset alone.