Quantum compilation tested on physical hardware.
Compiler research, physical-QPU experiments and frozen evidence across quantum search, hardware-aware compilation, qubit reuse and quantum-assisted data generation.
Discrete State Mapping to Quantum Processing Units
E(x) = sum_i Q_{ii} x_i + sum_{i<j} Q_{ij} x_i x_jQuadratic Unconstrained Binary Optimization form with penalty weight multipliers.
Lead Empirical Findings on IBM Heron
Five primary research programs evaluated on physical quantum processors under pre-registered hypotheses.
Compiler-Enabled Quantum Query Advantage
Q-Psi demonstrated compiler-enabled physical quantum query advantage on structured candidate-state search problems on IBM Heron hardware under an opaque black-box verifier model. Query reduction factors of 2.43x (N=4), 1.73x (N=8), and 1.19x (N=16) were verified across 9/9 individual cases and 3/3 tested problem sizes.
Dynamic Bernstein–Vazirani Scaling Advantage
Demonstrated bounded physical query-complexity and scaling advantage under single-shot Pokharel-Lidar-style sampling across N=4..16 qubits on ibm_marrakesh. Quantum scaling slope α_Q = 0.1532 proved statistically superior to the classical exhaustive bound α_C = 0.6963 (t = -30.65, p < 10-6).
Compiler-Driven MCM Qubit Reuse
Compiler-driven liveness and mid-circuit reuse reduced physical register width by a median 78.1% (up to 87.5% on 16 logical qubits mapped to 2 physical slots) across the frozen streaming benchmark while all six tested cases remained within the predeclared observable-quality criterion (6/6 non-inferior cases).
Quantum-Assisted Data Foundry V2
Q-Psi demonstrated a physical-QPU-assisted coding-data pipeline in which QPU measurement samples causally selected repository mutation states that were converted by executable software verifiers into 93 unique verified repair records (127.58s runtime, 332,768 shots, 100% QPU provenance). Current bottleneck is classical verification. Downstream LLM fine-tuning was not evaluated.
External MQT Bench Comparison Against Qiskit O3 and TKET
Q-Psi compiled all 18 frozen benchmark cases from the standard MQT suite. Physical execution on IBM Heron demonstrated that competitiveness was workload-dependent:
- Vs. Qiskit O3: Qiskit held a small aggregate physical fidelity advantage (mean delta -0.0067, 95% CI: [-0.0123, -0.0010]).
- Vs. TKET: Q-Psi held an apparent aggregate advantage (+0.0398 delta), but this was heavily driven by TKET's mapping failure on
vqe_su2_n8(+0.2696 delta). - Sensitivity Audit: When
vqe_su2_n8is omitted, Q-Psi vs. TKET mean delta shifts to -0.0062.
Universal compiler superiority is explicitly disclaimed.
da1ul7e3kjvs73877tagHardware-Aware Compiler Studies & Baselines
Dynamic Routing Crossover Study
Dynamic ancilla routing compressed 2Q depth from 73 to 2 on 13 hops, but reset and measurement noise prevented physical Bell fidelity crossover on Heron r2.
QUBO/Ising Hardware Parity
QAOA-based compiler optimization on IBM Marrakesh achieved 4/4 exact optimum hits on small compiler graphs (N≤10), degrading on N=18..25 due to hardware noise.
V1 Proof-of-Concept Baseline
Initial feasibility demonstration of physical QPU selector on M=1024 space yielding 14 verified unique code repair records (superseded by V2 120-Qsec campaign).
Preserving Falsifying Evidence & Inconclusive Studies
Scientific credibility requires publishing where ideas failed or where hardware noise prevented conclusive advantage.
Calibration-Aware Layout
Against Qiskit O3 best-of-8 seeds, Q-Psi layout achieved 1 win, 2 losses, 3 inconclusive (mean delta -0.0106). Preserved as a negative comparator.
Fractional Gate Lowering
Pulse duration compression yielded 2 physical wins and 4 inconclusive cases on IBM Heron, supporting mixed physical signal.
Selective Pauli Twirling
Reduced twirling overhead by 58.9% on beta hardware; selective-vs-full non-inferiority was inconclusive.
56-Slot Simon Circuits
Polynomial query reduction on 6/12 instances, but noise-induced degradation on larger N prevented asymptotic speedup.
Cryptographic Evidence & IBM Quantum Execution Provenance
Q-Psi Research Support Fund
General research fund supporting open physical QPU execution on superconducting quantum processors, compute infrastructure, datasets, reproducibility engineering, and open science publication.
General research support is voluntary. It directly funds physical QPU runtime, open dataset generation, compute infrastructure, and scientific publication. It does not constitute an investment, purchase of securities, commercial license entitlement, or guarantee of commercial quantum advantage.
Support Independent Quantum Research
Contributions fund physical-QPU compute hours on IBM Quantum processors, evidence archiving, and open-access scientific publication.