Quantum-Native Sensing Kernels on IBM Hardware

Version update: This record has been updated to remove enabling implementation details pending patent prosecution. Technical implementation is available under NDA. This preprint documents three quantum-native sensing kernels implemented on current IBM superconducting hardware under the Quantum State Command Encoding (QSCE) architecture. Rather than treating a quantum processor as a probabilistic number generator, QSCE treats the device as a command substrate, where quantum state is executable code and collapse is the execution of a control instruction. The work presents three low-qubit, shallow-depth sensing primitives designed to convert small, controlled perturbations into structured, repeatable changes in collapse-band behavior around a deterministic baseline: QMCA — a 1-qubit collapse-response kernel that converts small perturbations into calibrated changes in a non-baseline population while preserving a stable baseline anchor. SQCA — a 1-qubit hybrid-response kernel consistent with superconducting drive behavior, exhibiting a deterministic baseline anchor and a complementary deviation profile under perturbation. EBA — a 2-qubit correlation-based kernel producing a repeatable joint-distribution response signature under perturbation while retaining a deterministic baseline band. All three kernels are validated on real IBM backends (4096 shots per configuration), showing: Deterministic baselines under the null condition, with $>99%$ of counts concentrated in a single “quiet” band, and Monotonic, structured deviations in non-baseline states under small perturbations, consistent with a calibrated response signature. Within QSCE, these sensing kernels are treated as command-native primitives: baseline and deviant collapse bands are assigned explicit operational semantics (“no signal,” “signal present,” “threshold exceeded”), so that collapse functions as a decision event rather than merely a readout step. The note contrasts these primitives with bespoke quantum magnetometers (e.g., NV and vapor-cell platforms) and argues that QSCE kernels trade extreme sensitivity for programmability, integrability, and substrate-level command semantics on today’s NISQ hardware. This preprint also situates the sensing kernels alongside recent QSCE benchmarking on IBM hardware (including RCS-style metrics on 16-qubit circuits), highlighting a unified, control-first approach to quantum sensing and computation. Enabling implementation details are withheld in this public version pending ongoing patent prosecution; technical details are available under NDA.