On the IBM Quantum ibm_fez chip, Nervous Machine identifies 17 clusters of qubits that move together across 106 days of calibration telemetry, 15 of them multi-event-confirmed via independent coordinated-motion events. 156 qubits × 106 days of calibration telemetry. The substrate independently discovered 17 shared-resource clusters from raw telemetry alone, no privileged coupling-map input. 15 of 17 are multi-event-confirmed — at least two distinct coordinated-motion events with within-cluster correlation magnitude |r| > 0.5 in independent windows. Zero discovered clusters are quiet; every one shows coordinated motion at least once in 106 days. The largest discovered cluster discovered_shared_readout_chain_8ef82ebd covers exactly the 9 qubits described in the How Uncertainty Evolved Around a 9-Qubit Cluster substack post, with two confirmed events (March readout-only, May combined readout+T1). Top 8 discovered clusters by event count: Cluster ID Type Size Members Events T1 co-moves Peak |r| 78e15a79 shared readout chain 2 Q14, Q85 4 1/4 0.999 1cee4ce7 shared readout chain 2 Q20, Q153 3 2/3 0.997 3625b1c4 shared readout chain 2 Q58, Q109 3 1/3 0.984 49b87d14 shared readout chain 2 Q81, Q142 3 0/3 0.975 8ef82ebd ★ shared readout chain 9 Q17, Q24, Q36, Q52, Q53, Q55, Q61, Q73, Q91 3 2/3 0.811 d7dd4ee8 regional readout 2 Q115, Q132 2 0/2 0.999 f441a7fb regional readout 2 Q6, Q8 2 0/2 0.994 72cad12f shared readout chain 3 Q1, Q7, Q135 2 0/2 0.993 ★ = the cluster from the original substack post NM vs comparator benchmarks Same comparators (spectral clustering on the correlation matrix; isolation forest and per-day z-score for the event-window AUC test) applied to the IBM_Fez analysis: Test NM Spectral best Quantum: bipartite-split recovery on the 9-qubit cluster (ARI) 1.000 1.000 Quantum: event-window detection AUC 0.718 0.369 (isolation forest), 0.344 (z-score) — below chance Per-component anomaly methods score below chance on event-window detection because the event manifests as correlated cross-component behavior, and per-component detectors don't see cross-component structure by construction. NM's rolling correlation-magnitude signal is structurally appropriate for the event class and reaches AUC 0.718. Bundle contents README.md — framing quantum/ — IBM_Fez analysis code, extracted intermediate JSON, all figures, comparator benchmark LICENSE — CC-BY-4.0 Key figures and reports (inside the bundle): quantum/results/figure_multi_event_topology.png — timeline of all 17 IBM_Fez clusters' coordinated events quantum/results/figure_event_timeline.png — IBM_Fez March + May event windows quantum/results/comparator_table.md — full quantum comparator breakdown (spectral, hierarchical, PC algorithm, isolation forest, per-day z-score) Datasets cited IBM_Fez calibration archive — proprietary; pulled via IBM Quantum API. Extracted intermediate JSON files included in quantum/ for replication without database access. Companion writeup Substack series at https://nervousmachine.substack.com/ — How Uncertainty Evolved Around a 9-Qubit Cluster (the original quantum finding). Ongoing agent cluster analysis and daily predictions: https://quantum-atlas.nervousmachine.com License CC-BY-4.0 — see LICENSE file in the bundle.
On the IBM Quantum ibm_fez chip, Nervous Machine identifies 17 clusters of qubits that move together across 106 days of calibration telemetry, 15 of them multi-event-confirmed via independent coordinated-motion events. 156 qubits × 106 days of calibration telemetry. The substrate independently discovered 17 shared-resource clusters from raw telemetry alone, no privileged coupling-map input. 15 of 17 are multi-event-confirmed — at least two distinct coordinated-motion events with within-cluster correlation magnitude |r| > 0.5 in independent windows. Zero discovered clusters are quiet; every one shows coordinated motion at least once in 106 days. The largest discovered cluster discovered_shared_readout_chain_8ef82ebd covers exactly the 9 qubits described in the How Uncertainty Evolved Around a 9-Qubit Cluster substack post, with two confirmed events (March readout-only, May combined readout+T1). Top 8 discovered clusters by event count: Cluster ID Type Size Members Events T1 co-moves Peak |r| 78e15a79 shared readout chain 2 Q14, Q85 4 1/4 0.999 1cee4ce7 shared readout chain 2 Q20, Q153 3 2/3 0.997 3625b1c4 shared readout chain 2 Q58, Q109 3 1/3 0.984 49b87d14 shared readout chain 2 Q81, Q142 3 0/3 0.975 8ef82ebd ★ shared readout chain 9 Q17, Q24, Q36, Q52, Q53, Q55, Q61, Q73, Q91 3 2/3 0.811 d7dd4ee8 regional readout 2 Q115, Q132 2 0/2 0.999 f441a7fb regional readout 2 Q6, Q8 2 0/2 0.994 72cad12f shared readout chain 3 Q1, Q7, Q135 2 0/2 0.993 ★ = the cluster from the original substack post NM vs comparator benchmarks Same comparators (spectral clustering on the correlation matrix; isolation forest and per-day z-score for the event-window AUC test) applied to the IBM_Fez analysis: Test NM Spectral best Quantum: bipartite-split recovery on the 9-qubit cluster (ARI) 1.000 1.000 Quantum: event-window detection AUC 0.718 0.369 (isolation forest), 0.344 (z-score) — below chance Per-component anomaly methods score below chance on event-window detection because the event manifests as correlated cross-component behavior, and per-component detectors don't see cross-component structure by construction. NM's rolling correlation-magnitude signal is structurally appropriate for the event class and reaches AUC 0.718. Bundle contents README.md — framing quantum/ — IBM_Fez analysis code, extracted intermediate JSON, all figures, comparator benchmark LICENSE — CC-BY-4.0 Key figures and reports (inside the bundle): quantum/results/figure_multi_event_topology.png — timeline of all 17 IBM_Fez clusters' coordinated events quantum/results/figure_event_timeline.png — IBM_Fez March + May event windows quantum/results/comparator_table.md — full quantum comparator breakdown (spectral, hierarchical, PC algorithm, isolation forest, per-day z-score) Datasets cited IBM_Fez calibration archive — proprietary; pulled via IBM Quantum API. Extracted intermediate JSON files included in quantum/ for replication without database access. Companion writeup Substack series at https://nervousmachine.substack.com/ — How Uncertainty Evolved Around a 9-Qubit Cluster (the original quantum finding). Ongoing agent cluster analysis and daily predictions: https://quantum-atlas.nervousmachine.com License CC-BY-4.0 — see LICENSE file in the bundle.
We analyze 10.4 million calibration measurements from three IBM Heron superconducting quantumprocessors and identify two physically distinct classes of correlated multi-qubit degradationevents using only routine cloud-accessible telemetry. A column-wise permutation test reveals statisticallysignificant excess of simultaneous T1 crashes (42.8× expected at ≥ 10 simultaneous,p < 0.0001), simultaneous T2 crashes (4.8× at ≥ 10, p < 0.001), and simultaneous CZ gate-errorspikes (23.4× at ≥ 20, p < 0.0001; excess reaching 15,000× at ≥ 30). All three signals replicateacross backends (Fisher combined p < 10−7). Classifying high-crash snapshots by which parametersdegrade reveals two event types: Type A events degrade T1, T2, and CZ gate fidelity simultaneously(Cohen’s d = −0.94 for crashed-qubit T2), consistent with quasiparticle poisoning from high-energyparticle impacts; Type B events degrade T2 alone without affecting T1 or gate errors, consistentwith correlated dephasing noise. Type B events recover more slowly than Type A, persisting overmultiple calibration cycles with the same qubits remaining affected. T1-only events are rare acrossbackends, consistent with the expectation that relaxation degradation typically accompanies dephasing.Different qubits crash each time (mean Jaccard similarity ≤ 0.04), and readout fidelityremains unaffected in both event types. These correlated events—previously detectable only withdedicated particle detectors—are identifiable, classifiable, and operationally actionable from existingcloud calibration data without hardware modification.
On 4-5 July 2026, an identical shock protocol was executed on the same 156-qubit IBM Heron R2 architecture (ibm_fez) but with the QITE lambda feedback replaced by uniformly random rotation angles per cycle. This random-angle null control preserves every structural variable — RY+RZ+CZ layer, Heavy-Hex CZ coupling, 4096 shots/cycle, seed 20260602, the same 150 cycles, and the same six shocks at the same cycles (20/40/60/80/100/120), the same target qubits (q78, q69, q67, q47, q37, q16) with the same amplitudes (l1,l2) — while removing only the decentralized per-qubit lambda feedback dynamics. Backend selection was driven by queue availability; both are 156-qubit Heron R2 devices with identical architecture, and calibration differences cannot account for the qualitative burst-count contrast reported below. The result is a clean negative: zero collective bursts across all six shocks. The four non-parametric statistical tests (identical methodology to v1) all confirm the absence of shock-driven collective response: (1) permutation test yields p = 1.0 for shock alignment against the noise-saturated per-cycle transitions; (2) pairwise Pearson correlation between per-transition delta-p1 vectors drops from r_mean = +0.65 in the multi-shock run to r_mean = +0.017 in the null; (3) cross-session hypergeometric overlap between null "top-active" qubits and the v1 multi-shock top-active set is not significant (Jaccard = 0.11, p = 0.24); (4) Mann-Whitney U on shock-cycle max|delta p1| versus baseline shows ratio 0.989 with p = 0.89 — statistically indistinguishable from noise. Baseline global coherence exp(-8*Var(p1)) sits at 0.413 +/- 0.022 across all 150 cycles under random angles, versus 0.99 +/- 0.01 under QITE feedback in v1 — two distinct dynamical regimes. That the shock protocol itself executed correctly on the null run is verified locally at the target qubit: for each of the six shocks, the measured p1[q_target] at the shock cycle agrees with the theoretical prediction from theta_shock = 2*atan2(l2, l1) to within <5% (q78 shock: predicted 0.016, measured 0.018; q69 shock: predicted 0.985, measured 0.939; and so on for all six). One cycle after each shock, the target qubit returns to the random baseline distribution — with no feedback dynamics, there is no restoring trajectory. The shocks are physically executed; what is absent is the collective response. Causal conclusion: the QITE per-qubit lambda feedback dynamics are necessary for the observed collective burst phenomenology. The circuit structure (RY+RZ+CZ on Heron R2 Heavy-Hex topology) and shock protocol alone do not produce bursts. Six identical shocks on QITE-stabilized baseline produce 10 collective bursts with 6/10 shock-aligned (p = 0.008); the same six shocks on random baseline produce zero. This 10-vs-0 hardware contrast, verified by four independent non-parametric tests, establishes feedback necessity as a falsifiable causal claim rather than a phenomenological observation. The v2 bundle contains the complete null-control primary data (150-cycle JSONL, consolidated JSON, p1 numpy matrix), all IBM Runtime job IDs with per-cycle timestamps, Tee'd console logs of both the initial run and the resume run (a mid-run job-poll stall on 4 July required a resume from cycle 7 with deterministic per-cycle RNG seeds), five analysis figures including direct null-vs-multi comparison plots, the full side-by-side statistical comparison JSON, the v1 multi-shock p1 matrix and statistical test outputs for reanalysis, an 8-page supplement PDF (Section 5) integrating with the v1 paper, and SHA-256 checksums of every file in MANIFEST_v2.json. Backend (v2 null control): IBM Heron R2 (ibm_fez), 156 qubits, 4096 shots/cycle.Companion patents: DPMA Az. 10 2025 003 906.9 (QITE), 10 2025 004 891.2 (QISE).Predecessor (v1): Westrick, Reproducible Collective Burst Modes on 156 Qubits: Decentralized Per-Qubit QITE Lambda Field on IBM Heron R2, 1 June 2026. On 1 June 2026, a decentralized per-qubit lambda field was implemented on the IBM Heron R2 processor (ibm_kingston, 156 qubits) and probed with a multi-shock excitation protocol. Unlike the predecessor work (Westrick, Controllable Quantum Collective States on 156 Qubits: Experimental Results of the QITE Formalism on IBM Heron R2, 12 April 2026), which tested a globally controlled QITE quantum collective, each qubit here carries its own lambda state and receives, in the feedback loop, only its own measurement statistic p1_i. The only inter-qubit coupling propagates physically through the CZ gates of the Heavy-Hex topology. Six shocks were applied at six different positions on the chip: central (q*=78), nearest neighbor (d=1), intermediate (d=3, d=5), deep (d=8), and edge (d=12). Each individual shock triggered a chip-wide burst within 1-8 cycles (peak |delta p1| between 0.308 and 0.366; 10 to 22 simultaneously active qubits). Four additional spontaneous bursts were detected between shocks, for a total of 10 bursts in 150 cycles. The 6/6 reproducibility was verified by four independent non-parametric statistical tests, all positive: (1) permutation test p = 0.008 against chance alignment; (2) pairwise burst-vector Pearson correlation r_mean = +0.65 with all 15 pairs above noise; (3) cross-session reproducibility 9/10 qubit overlap between two independent IBM Quantum sessions, hypergeometric p = 0.008; (4) Mann-Whitney U test of burst amplitude versus Phase-A baseline, ratio 2.7, p < 0.0001. This bundle contains the complete primary data (raw JSON logs, NumPy matrices), all 27 visualizations, IBM job IDs of every submitted job, console logs of all runs, the pre-registration documents with locked detection thresholds, and SHA-256 checksums of every file (MANIFEST.json) for independent verification. Backend: IBM Heron R2 (ibm_kingston), 156 qubits, 4096 shots/cycle.Patent filings: DPMA Az. 10 2025 003 906.9 (QITE), 10 2025 004 891.2 (QISE).Predecessor: Westrick, Controllable Quantum Collective States on 156 Qubits, 12 April 2026.
Eight verified quantum computing jobs executed on IBM Quantum hardware (ibm_fez Heron R2, 156 qubits; ibm_torino Heron R1, 133 qubits) between January 27 and March 15, 2026. User ID: IBMid-692001DJRD. Experiments include: 1. Bell State Entanglement — 96.3% fidelity on ibm_fez Heron R2 (Concurrence C = 0.926, Tangle T = 0.858, 1,000 shots). Cross-platform benchmark: Heron R2 vs Heron R1 (+8.3 pp fidelity advantage, noise ratio 2.43×). 2. Reproducibility Test — Two independent runs of identical circuit (χ² = 2.70, p = 0.44, df = 3). H₀ not rejected: statistically indistinguishable results at 95% confidence. 3. BB84 Quantum Key Distribution — Full Alice/Eve/Bob protocol implementation. Alice baseline error 0.60% → Bob QBER 49.0% under eavesdropping (82× degradation). Experimental demonstration of the quantum no-cloning theorem. Control group design isolates eavesdropper signal from hardware noise baseline. 4. Variational Quantum Circuit (VQC) — 2-qubit circuit, 10 trained parameters with tied weights (θ₃ = θ₄), 8 CZ gates in 4 entangling layers. 4-qubit ansatz: Shannon entropy 3.885/4.000 bits (97.1%), ground-state bias confirmed (χ² = 300.94, p ≈ 0). 5. Quantum Random Number Generation (QRNG) — 8-bit outputs, 10/10 unique values per shot (range 16–254). Total: 39,010 quantum measurements across 8 jobs and 10 circuits. QPU time: 4.8 seconds. Job completion rate: 100%. All results decoded from raw IBM SamplerV2 BitArray binary archives (zlib + base64 + NumPy .npy pipeline). No simulations. Statistical validation applied throughout (Wilson 95% CIs, chi-squared tests). Stack: Qiskit Runtime SamplerV2 · QPY · OpenQASM 2.0 · Python · NumPy · SciPy Repository: https://github.com/dinohatibovicWhitepaper: https://dinohatibovic.github.io (Doc QAI-WP-2026-01-28-V4)
An important use-case for machine learning (ML) is that of determining readout results in quantum computers. In quantum computing (QC), classical ML models are currently being used to discriminate in-phase and quadrature (IQ) signal data to discriminate between quantum states, which is a fundamental QC operation. In our research we propose a Quantum K-Means (QK-Means) clustering technique to discriminate quantum states on the IBM Bogota quantum device, and compare its performance to the K-Means technique (its classical counterpart). We used both algorithms to perform a correlation analysis and probe cross-talk between couples of qubits on the device. We observed that QK-Means obtained test and training scores at par with the classical K-Means, and testing scores that were marginally lower than K-Means when the clusters weren’t visually separable. The training times for QK-Means were observed to be at par with an implementation of the K-Means that was not optimized. In this case, we concluded a weak correlation with a Pearson correlation coefficient of 0.2 on the (1, 2) and (2, 3) qubit couples. After analyzing the training scores, we also conclude that the 1 qubit has the worst performance at readout evidenced by the signal data not being visually separable and the low scores obtained on both clustering algorithms compared to the other qubits. Its poor performance is further verified by the calibration data showing a high readout error of 8,4%. This technique can be used to find correlations present in readout of quantum circuits and to determine cross-talk.
On 1 June 2026, a decentralized per-qubit lambda field was implemented on the IBM Heron R2 processor (ibm_kingston, 156 qubits) and probed with a multi-shock excitation protocol. Unlike the predecessor work (Westrick, QITE Hardware Results 156Q, 8-12 April 2026), which tested a globally controlled QITE quantum collective, each qubit here carries its own lambda state and receives, in the feedback loop, only its own measurement statistic p1_i. The only inter-qubit coupling propagates physically through the CZ gates of the Heavy-Hex topology. Six shocks were applied at six different positions on the chip: central (q*=78), nearest neighbor (d=1), intermediate (d=3, d=5), deep (d=8), and edge (d=12). Each individual shock triggered a chip-wide burst within 1-8 cycles (peak |delta p1| between 0.308 and 0.366; 10 to 22 simultaneously active qubits). Four additional spontaneous bursts were detected between shocks, for a total of 10 bursts in 150 cycles. The 6/6 reproducibility was verified by four independent non-parametric statistical tests, all positive: (1) permutation test p = 0.008 against chance alignment; (2) pairwise burst-vector Pearson correlation r_mean = +0.65 with all 15 pairs above noise; (3) cross-session reproducibility 9/10 qubit overlap between two independent IBM Quantum sessions, hypergeometric p = 0.008; (4) Mann-Whitney U test of burst amplitude versus Phase-A baseline, ratio 2.7, p < 0.0001. This bundle contains the complete primary data (raw JSON logs, NumPy matrices), all 27 visualizations, IBM job IDs of every submitted job, console logs of all runs, the pre-registration documents with locked detection thresholds, and SHA-256 checksums of every file (MANIFEST.json) for independent verification. Backend: IBM Heron R2 (ibm_kingston), 156 qubits, 4096 shots/cycle. Patent filings: DPMA Az. 10 2025 003 906.9 (QITE), 10 2025 004 891.2 (QISE). Predecessor: Westrick, QITE Hardware Results 156Q (8-12 April 2026).
We report a set of pre-registered experiments on the three 156-qubit IBM Heron r2 processors reachable on a single open-plan account (ibm_kingston, ibm_marrakesh, ibm_fez), carried out on 14–15 October 2026. The object of study is not computational speedup but channel reliability: whether fixed symbolic messages can be delivered intact through a present-day noisy processor when the processor's per-wire readout response is measured fresh in the same sitting, and whether two such processors can exchange messages with per-position verification. Messages are 17-symbol sequences drawn from a 13-symbol test alphabet whose preparations collapse to nine distinguishable readout classes. A receiver combining per-wire selection from a fresh characterization, grammar-constrained decoding, and a corpus-frequency tie-break delivered 36/36 messages on ibm_kingston in two independent campaigns, 36/36 on ibm_marrakesh, and 35/36 on ibm_fez, against stale-plan and uncharacterized controls ranging from 2/36 to 30/36 depending on backend and control type. The grammar-constrained receiver without the corpus prior scored 30/36, 30/36, and 29/36 on the three backends; its losses are a single systematic mechanism — a deterministic tie on one battery message — identified from saved counts and closed by the prior. In a separate experiment, ibm_kingston and ibm_marrakesh exchanged self-introduction streams authored by each backend from its own fresh characterization, through a six-stage symmetric relay, with 204/204 position-flights received exactly and zero substitutions. In a counts-only blind test, an independent decoder with no shared codebook recovered the discreteness and grouping structure of two authored streams (pooled pairwise grouping agreement 0.971 against a pre-registered 0.90 strong-pass bar) while overestimating the alphabet size (reported 8, true value 6). A census of repeated characterizations shows that the ranking of a device's clearest wires turns over within hours (same-day top-17 wire overlap of 1–2 of 17 on ibm_marrakesh), while per-wire response quality moves by only ~0.01, so characterizations are within-sitting instruments. No speedup, no machine networking, and no machine understanding is claimed. The full receiver implementation is withheld as a trade secret; verification is offered through the published job IDs, retained raw counts, and tiered third-party reproduction.