What does this research mean for the field?

A unified lattice paradigm utilizing spontaneous ground-state entanglement and quantum vacuum information density enables the modeling of spatial distance as a rendered quantum substrate. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to propose a unified lattice approach to quantum manifold mapping and understand spatial impedance.

June 29, 2026Open Access

A Unified Lattice Paradigm for Quantum Manifold Mapping and Spatial Impedance

Key Points

This research aims to propose a unified lattice approach to quantum manifold mapping and understand spatial impedance.
Conducted two main experiments: Zero Phase Experiment and Field Sweep Experiment.
Collected around 890,000 qubit state-readouts and correlation logs from IBM QPU backends.
Used Python scripts for data processing, Shannon Entropy calculations, and visualization of results.
Raw datasets allowed for replication of figures and metrics detailed in the manuscript.
Shannon Entropy calculations provided new insights into ground-state fluctuations.
Demonstrated effective correlation logs revealing spontaneous ground-state entanglement.

Abstract

Description / Abstract Title: Unified Lattice Paradigm for Quantum Manifold Mapping and Spatial Impedance This dataset archive contains the complete raw experimental datasets, hardware configuration files, and Python analytics code corresponding to Phase II of Project Strata, supporting the research paper "Redefining Distance as a Rendered Substrate". ### Contents of experimentdata. zip: 1. **ZeroPhaseExperiment (Spontaneous Ground-State Entanglement) **: - CSV datasets containing raw qubit state-readouts and correlation logs (~890, 000 snapshots total) from IBM QPU backends ('ibmfez', 'ibmₘarrakesh', and 'ibmₖingston'). - Python code scripts for circuit submission, data processing, and visualization. 2. **FieldSweepExperiment (Quantum Vacuum Information Density) **: - CSV datasets containing raw frequency fluctuation sweeps, manifold calculations, and hybrid study logs. - Python analytics scripts used to calculate the Shannon Entropy of ground-state fluctuations. All data is structured to allow full replication of the figures, metrics, and models presented in the manuscript.

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