This page states what QPC is doing in the holographic line of work—not as a race against classical machines, but as a class of problems whose object is quantum: a distributed state, multiple implicit contexts, readout by measurement.
Quantum-native task: Prepare and probe a polycontextural hologram in Hilbert space—encode distributed structure across many degrees of freedom, then answer a question that is defined by quantum correlations and measurement, not by a classical bit-register story alone.
Failure mode on NISQ hardware: When a run on a real quantum processor does not match the ideal readout, the limiting factor is noise in the readout channel (depth, decoherence, SPAM)—not that the task was “secretly classical” or ill-defined. The definition of the task remains: the computation is the quantum process.
One framing for every QPC demonstration on real processors linked from this holographic family.
Universal restriction. Gate errors, decoherence, and readout noise cap everyone's circuits on current machines—not only QPC. That is why several QPC tests on IBM Quantum show stronger signal in principle (simulator or shallow settings) than full satisfaction on hardware: the limiting factor is NISQ depth and noise, not that polycontextural or holographic tasks are “classical in disguise.”
How we present it. We separate (1) the definition of the quantum-native task, (2) what we ran on device (transparency), and (3) the implementation ceiling imposed by today's chips. Partially satisfying hardware results are honest physics, not a reason to abandon the architecture narrative.
One-line summary. The main practical limit on hardware demonstrations is universal NISQ noise and depth; fuller QPC capability on chip follows better devices and, longer term, error correction—see also the Holographic Memory report and SWR executive results.
We do not anchor this work in “can a supercomputer approximate the same I/O?” Classical logic and classical simulation are a different language for a different object. Here the object under study is the quantum state produced by QPC-style encoding.
A pattern is written into a polycontextural interference field (several layers: phase, spreading, entanglement). Only k of N qubits are measured. Reconstruction from marginals is the operational story—but conceptually, the stored object is the joint quantum state before and at measurement. Ideal simulator vs hardware separates architecture from device noise.
A related line encodes structure into many qubits and uses a parameterized quantum decoder; the answer is intended to appear on a small ancilla register after measurement—again, a quantum readout channel. When depth and noise dominate, the channel fails before the definition of “read the hologram by measurement” loses meaning.
Numbers from the holographic partial-measurement runs (IBM backends) illustrate the split between task definition and hardware limits.
| Layer | What we observe |
|---|---|
| Ideal (simulator) | Reconstruction tracks the intended distributed encoding—task structure is visible. |
| Hardware (e.g. Fez, Torino, Pittsburgh) | Lower fidelity vs ideal: attributed to NISQ noise, not to replacing quantum logic with classical. |
| Gap (e.g. up to ~12.5 pp) | Readout / sampling of the prepared state is degraded; the holographic task remains quantum-native. |
Discussion. We present results this way: (1) In principle, QPC implements the intended prepare → partial probe → infer / read pipeline for a holographic quantum object. (2) On current machines, noise limits how cleanly that readout channel resolves the answer. (3) That is an implementation limitation, not a reclassification of the task as classical. Future work: shallower decoders, error mitigation, or fault-tolerant hardware—still serving the same quantum-native definition.
Clear success criteria without dragging in classical baselines.
Brain microtubules are cited as an example where the relevant picture is many coupled quantum degrees of freedom and distributed information—not a classical register. QPC Holographic Memory targets that class of phenomenon computationally: holographic storage, partial readout, quantum correlations. The full report maps Kenograms, contextures, and partial measurement to that analogy in detail.
→ Full QPC Holographic Memory Report (methods, 3D view, tubulin mapping)
→ QPC-SWR v1 executive results (structure witness on Fez; how it compares to this holographic framing)
→ Quantum contextuality task (Mermin–Peres) (parallel framing for contextuality demos on Fez)