We report five preregistered experiments on the IQM Garnet 20-qubit square-lattice processor, each with its decision rule committed before any hardware data existed and each reported regardless of outcome. First, the even-over-odd parity-sector leakage asymmetry previously measured on IBM Heron r2 replicates on Garnet at preregistered power (relative asymmetry +0.068, one-sided p = 1.1 × 10−5). Because the noiseless parity leakage of these number-conserving XY-Trotter circuits is exactly zero, this is a statement about device noise. Second, the asymmetry is not stable: over ten execution windows it varies beyond shot noise at fixed depth (Cochran Q = 19.01 on 9 degrees of freedom, p = 0.025), more strongly when windows are pooled by provider calibration set (p = 0.0083), and an isolated sign reversal at depth 10 does not replicate. Third, a confirmatory campaign that takes the calibration epoch as its independent unit — twelve epochs, 688,128 shots — finds the asymmetry larger at depth 8 than at depth 12 (mean contrast +0.0173, one-sided p = 0.026); the lower bound is +0.0030 and three of twelve epochs have the opposite sign. Fourth, a calibration-aware layout optimiser developed on heavy-hex devices fails its frozen transfer rule: it is better than automatic placement at chain lengths 8 and 16 and worse at 12, and a powered follow-up confirms the reversal. All preregistrations, calibration snapshots, job identifiers, raw counts and analysis scripts are public. All quantum-hardware results were obtained on IQM Garnet through IQM Resonance under an extended-access research grant. Preregistrations, raw counts and analysis code: https://github.com/anulum/scpn-quantum-control
We report five preregistered experiments on the IQM Garnet 20-qubit square-lattice processor, each with its decision rule committed before any hardware data existed and each reported regardless of outcome. First, the even-over-odd parity-sector leakage asymmetry previously measured on IBM Heron r2 replicates on Garnet at preregistered power (relative asymmetry +0.068, one-sided p = 1.1 × 10−5). Because the noiseless parity leakage of these number-conserving XY-Trotter circuits is exactly zero, this is a statement about device noise. Second, the asymmetry is not stable: over ten execution windows it varies beyond shot noise at fixed depth (Cochran Q = 19.01 on 9 degrees of freedom, p = 0.025), more strongly when windows are pooled by provider calibration set (p = 0.0083), and an isolated sign reversal at depth 10 does not replicate. Third, a confirmatory campaign that takes the calibration epoch as its independent unit — twelve epochs, 688,128 shots — finds the asymmetry larger at depth 8 than at depth 12 (mean contrast +0.0173, one-sided p = 0.026); the lower bound is +0.0030 and three of twelve epochs have the opposite sign. Fourth, a calibration-aware layout optimiser developed on heavy-hex devices fails its frozen transfer rule: it is better than automatic placement at chain lengths 8 and 16 and worse at 12, and a powered follow-up confirms the reversal. All preregistrations, calibration snapshots, job identifiers, raw counts and analysis scripts are public. All quantum-hardware results were obtained on IQM Garnet through IQM Resonance under an extended-access research grant. Preregistrations, raw counts and analysis code: https://github.com/anulum/scpn-quantum-control
This preprint reports a bounded IBM Heron hardware observation of parity-sector and excitation-number correlated decoherence asymmetry in small XY-Hamiltonian circuits. The dynamical Lie algebra of the XY Hamiltonian decomposes under the parity operator, and the experiment measures parity leakage rates across labelled sectors without promoting the observation as a DLA-only causal effect. The archived study uses a 342-circuit campaign on IBM ibm_kingston (Heron r2, 156 qubits), with n = 4 circuits across eight Trotter depths. It reports an odd-sector leakage excess over the even sector, with seven of eight tested depths individually significant under Welch tests, while explicitly treating shared-qubit and shared-calibration context as a boundary on inference. The record includes the manuscript source and PDF for a reproducible archival preprint. Claims are limited to the named hardware campaign, committed raw-count artefacts, stated reducers, and the open repository at https://github.com/anulum/scpn-quantum-control.
Compilers for today's quantum processors choose a layout by reading the day's calibration. We ask how deep a circuit stays readable when no placement reads a quality number. We place a ring of CZ gates on IBM's heavy-hex devices in three ways that see only the coupling graph, the basis and which elements have failed: a formula that puts the ring on a lattice cycle (the rule), the ring folded onto the same qubits (zipper), and Qiskit's level-2 search without error rates (blind Qiskit). The workload is the kicked Ising ring at J = pi/4; the probes are a weight-2 charge conserved by the circuit, a mirror echo with a longitudinal field that breaks integrability, and the global parity. In declared tests on ibm_marrakesh and ibm_kingston (29-30 October 2026), the rule kept more of the charge than both other placements in all 24 comparisons (readable depth 56-90 steps against 15-26), and in the non-integrable echo it won 71, tied 11 and lost none of 144 comparisons, at sizes up to n = 72. Several declared predictions failed, and we report them with the results. On ibm_kingston the rule's n = 40 ring carried a run of 18 sites whose echo was near random or inverted: the same 18 sites in three runs of the byte-identical circuit over three hours, while the calibration showed nothing there and the same qubits were healthy on the n = 20 ring. Gate twirling, which leaves the ideal circuit unchanged, turned the inverted part random, so the cause is on the device, not in the circuit; a light-cone argument bounds how far one fault reaches. These sites set the readable depth at n >= 40 and erased the parity at n = 40. A map read from the calibration could not have avoided them. All declarations, records and raw counts are public in TOQB.
H. Billah and M.M.H. Sarker contributed equally to this work. Interpreting a fixed quantum circuit's output as evidence of a hardware effect requires ruling out two things usually conflated with it: finite-sample fluctuation, and structure already present in the circuit's own noiseless output. Less commonly checked is a third: whether the reference circuit compared against is the one actually executed, once compiler-level qubit routing is accounted for. We execute a fixed 35-qubit, 243-gate diagnostic circuit on IBM Heron-family hardware (three runs, two backends) and show this third check is essential: the routed circuit submitted to hardware has different noiseless predictions than the logical circuit intended, for several qubits. Against the correct, routed-circuit reference, the aggregate deviation is significant in two of three runs, and four registers (0, 9, 14, 27) show a significant output-probability deviation in every run — though we distinguish a high-confidence subset, {0, 9, 27}, with tightly time-matched calibration, from qubit 14, included only on an exploratory basis given its calibration was retrieved roughly two weeks post-execution. Same-backend replicates correlate more strongly by the Pearson measure, though a rank-based (Spearman) test shows this gap does not survive at the level of register ordering, indicating substantial leverage from a small number of registers rather than a broadly robust pattern; these three executions also share a byte-identical payload and are not independent replications in the strictest sense. The mechanism is only partially resolved: independent single-qubit readout error and raw gate count are ruled out as complete explanations for most of these registers, but the simplest version of the leading hypothesis for the single most-affected register does not reproduce the observed cross-backend pattern even with live, backend-specific timing data. A second, structurally different circuit validated only in simulation calibrates the statistical procedure's behavior under one synthetic noise model; it does not itself establish generality to real hardware, and the specific register set found here should not be expected to generalize beyond this study. Note on scope: this is a methodology and case-study contribution centered on executed-circuit references for fixed-circuit diagnostics, not a characterization of IBM Heron hardware in general or a randomized-benchmarking experiment in the formal sense. Supporting data, the routed OpenQASM circuits, raw measurement counts, and analysis code for this study are available on request from the corresponding author. Affiliation: Sonicium Quantum Lab Ltd., Dhaka, Bangladesh.
This document fixes, before the data exist, the hypothesis, apparatus, observables, cadence, analysis, thresholds, controls, stopping rule and reporting commitment of a one-year search for a modulation of superconducting-qubit energy relaxation (T1) at the sidereal frequency, 1/(23 h 56 m 4.09 s), beyond what the solar day and its seasonal modulation can produce. Data collection began on 17 October 2026 at 16:42 UTC on qubit 9 of the IBM Heron processor ibm_fez: an eight-delay inversion-recovery T1 measurement every six hours (about 3 s of processor time each), with the device's calibration values polled hourly. The analysis is fixed in advance: a least-squares fit of a smooth drift plus sinusoids at the solar, sidereal, anti-sidereal and extended-sidereal frequencies, with the reported amplitude leakage-corrected as sqrt(A_sid^2 - A_anti^2) (Farley and Storey 1954). The pipeline was validated on synthetic data before the first measurement and recovers an injected 0.3% at 2.7-3.4 sigma while returning 0.5 sigma with nothing injected. Detection requires a leakage-corrected amplitude at or above 3 sigma, both control channels below 2 sigma, a phase stable between the two halves of the year, and survival when runs adjacent to calibrations are removed; otherwise the result is the 95% upper limit, expected near 0.3%. The search is declared inconclusive if fewer than 900 of 1460 scheduled runs succeed or the anti-sidereal control exceeds 3 sigma. An amplitude matching the known cosmic-ray anisotropy (~0.1%) is a calibration, not a discovery. Stopping rule: one year, with a six-month interim look at the controls only; a second year is pre-declared as the response to an inconclusive or 2-3 sigma outcome. The result will be reported whether it is a detection, a bound, or a failure of the apparatus. Standard physics predicts a null result at this sensitivity; the alternative hypothesis is from The Cosmic Page (doi:10.5281/zenodo.23287018, Ch. 13) and the research proposal doi:10.5281/zenodo.23201109. Included: the pre-registration (PDF and LaTeX source), the monitor script that runs on the device, the fixed analysis script, the synthetic-data validation script with its results and figure, and the README. First data point: job db9qap9gv2cc73e5tufg, 2026-10-17T16:42:19Z, T1 = 162.9 +/- 7.9 us.
Abstract Calibration summaries are used both to select physical qubits and to parameterize noisy emulators, creating a risk that agreement within a calibration-derived model is mistaken for validation on hardware. We test whether calibration-aware compiler rankings transfer to hardware using weighted-MaxCut instances implemented with the quantum approximate optimization algorithm. The evidence comprises four stages: 3240 historical calibration-derived simulations; a complete 54-pair hardware grid on three IBM Heron r2 processors; exact-circuit repeats 9.3–12.1 d later; and a contemporaneous five-arm refresh experiment. Full-calibration selection improves the median hardware approximation ratio by 0.74 percentage points (pp), with 29 resolved gains and 11 resolved losses. This is a mean-objective effect: its translation to exact-solution probability is instance- and size-dependent, and we do not extrapolate it beyond the tested n ⩽ 10 regime. A Qiskit Aer model constructed from the calibration state available before execution reproduced the direction of the measured full-calibration-versus-topology advantage in 35/54 comparisons, but systematically overestimated its size: the simulated advantage exceeded the subsequently measured hardware advantage by a median 1.35 pp. Regressing the measured hardware advantage on the simulated advantage gave a slope of 0.28 (workload-depth case-cluster 95% interval 0.06–0.52), rather than the unit slope of a calibrated predictor. The emulator identified the exact best of six backend-compiler configurations in only 5/18 cases (95% Wilson interval [0.125, 0.509]). By contrast, identical circuits preserved the compiler-effect sign in 16/18 later repeats ( r = 0.92 ). Refreshing the full-calibration mapping yielded a median +0.72 pp gain, whereas the calibration-score difference agreed in sign with the measured refresh benefit in only 9/18 cases. Calibration data are therefore useful for candidate discovery and timely refresh, but their scalar scores are not calibrated predictors of hardware performance or configuration ranking.
Technical notes and complete deposit (code, synthetic data, preregistrations, decision log, independent audits) for three preregistered synthetic studies of drift-aware decoding of a distance-5 repetition code with one drifting data qubit. QP-02-H7, a kill test at equal information (1850 fresh trajectories): a hard keep/exclude switch beat neither equal-information baseline; verdict NO_SEPARATION. The soft reweighting policy P9 had an 8.6% [95% CI 7.1%, 10.0%] lower logical error rate than the switch, and a change-aware in-epoch estimator P10 3.1% [1.4%, 4.9%]. The hard action is not the source of the advantage measured in earlier runs. QP-02-H8, a preregistered 2x2 decomposition of the P9 versus P10 difference (1225 fresh trajectories): both main-effect labels POSITIVE; under the frozen attribution rule the estimator procedure is attributed to P9's advantage and the protocol regime offsets part of it. QP-02-H9 addendum: with a second qubit co-drifting with the first, the procedure contrast favours the structure-free estimator (run 002, labels NEGATIVE; an outcome-aware validation after run 001, which was INVALID_RUN and is reported beside it, never pooled). All data are simulated; no quantum hardware and no personal data are involved. Code (*.py, *.ps1) is MIT licensed, all other content CC BY 4.0. Start with DEPOSIT_README.md inside the archive.