Force-calibrated finite-time coherence bounds for a Diósi–Penrose model
Joint force and coherence constraints are implemented for one specified Gaussian Diósi–Penrose generator in a fixed finite-time protocol. The analysis retains kinetic energy, correlated two-body noise, three-dimensional wave packets, and local decoding followed by tracing out motion. A trusted normalized initial-force bound of 0.995 restricts the common smearing scale from above. Uniformly over the remaining positive scales, the local statistic has Newton mean greater than 0.9965 and DP absolute mean less than 0.4581. An entanglement witness from the same measurement record also has a positive prediction gap greater than 0.03761, but entanglement is not necessary for this model exclusion. The small-smearing argument bounds full coherence blocks by an early completely positive instrument and includes subsequent interacting evolution in the bound. The general force–decoherence principle is known; the contribution is the controlled finite-readout implementation. This is a conditional nonrelativistic theoretical result with trusted ideal preparation, force calibration, and readout, not an empirical exclusion or a general certification of quantum gravity. The companion archive includes the full LaTeX source, standalone Python checks, exact rational certificates, and reproducibility instructions. The work has undergone internal checks, not independent peer review. Generative-AI assistance is disclosed in the paper. Licensing: the manuscript PDF, LaTeX source, documentation and numerical records are licensed under CC BY 4.0. The Python software and its embedded tests are licensed under MIT. These licenses apply to separate file categories, as specified in the companion archive; they are not alternative licenses for every file.
Authors
- Mikhail Petrov
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-04
- DOI
- https://doi.org/10.5281/zenodo.23142965
- Primary Topic
- Quantum Mechanics and Applications
- Type
- preprint