DP: There is a person out there "Jason Padgett" who presents a lot of nice information on "quantum state vector". Can you locate his work, analyze it then compare it to SVP/scalar-kinetic?
ChatGPT: Got it. I looked up Padgett’s recent “Quantum State Vector” material and pulled the core through-lines, then mapped them to SVP / scalar-kinetic.
What Padgett is claiming (in plain English)
Reality is built from spinning quantum state vectors (QSVs). He frames each qubit as a little sphere with a state vector; stacked/entangled vectors render geometry, fractals, and “the real matrix.” Motion is discrete—frame-by-frame—rather than truly continuous. Facebook
A “Quantum State Vector Tensor Field.” He proposes promoting the state vector to a field/tensor that could encode both information and curvature (an attempted bridge to gravity). Most of this appears in videos, Medium write-ups, and unpublished manuscripts. YouTube
Holographic/fractal story. He leans on “quantum information holography”: geometry and fractals are rendered from entangled spin/angle relations. YouTube
Public footprint & rigor. Talks (TEDx), social posts, Medium features (often via Maureen Seaberg), and some drafts on Academia.edu; not much in peer-reviewed venues. Academia.edu
How this lines up with SVP / Scalar–Kinetic
Strong resonances with SVP:
Discrete updates vs. continuous flow → Your “oscillation as kinetic effect” emerging from disturbances of a deeper scalar stillness. Padgett’s “quantum frames” rhyme with effect steps rather than cause. Facebook
Spin/angle encodes form → SVP’s interval/angle-of-incidence and dominance/sub-dominance mapping; “stacked slopes” → your harmonic stacking and toroidal field architecture. Facebook
Holographic/fractal rendering → Your “bubble in an ultra-dense medium” and nested shells; he’s describing geometry precipitating from information relations (sympathy) rather than billiard-ball mechanics. YouTube
Where it diverges / needs tightening:
Math + validation. His QSV-tensor unification is more proposal than derivation; I don’t see a worked pipeline from state-vector dynamics to the Einstein tensor or testable gravitational predictions. (Mostly talks, Medium, and self-hosted PDFs.)
Academia.edu
Terminology drift. He uses quantum-info terms (qubits, state vectors) somewhat metaphorically. For SVP alignment, we’d want explicit mappings to your subdivisions (Interetheric/Etheric ↔ information domain; Interatomic/Atomic ↔ rendered kinetics).
Medium
Evidence base. Popular coverage is abundant; peer commentary is mixed and sometimes skeptical. Treat the physics as exploratory, not settled. Wikipedia
A clean SVP translation of his core ideas
Padgett: “Spinning QSVs (information) render geometry and motion in discrete frames.”
SVP: Sympathetic field (scalar cause) organizes oscillation (kinetic effect); frames are the measurable steps of a deeper, continuous sympathetic coherence.
Padgett: “Vector-tensor field could encode gravity.”
SVP: Neutral Center + rhythmic balanced interchange produces centripetal syntropy (what you call inward etheric curl) and centrifugal entropy, appearing as “gravity/radiation” pairs. QSV orientation ↔ dominant phase; entanglement ↔ sympathy.
Padgett: “Holographic fractal universe.”
SVP: Nested etheric shells / chord of mass / toroidal heart—self-similar structure across subdivisions.
Practical next steps (if you want to build a bridge)
Define a dictionary:
QSV orientation (θ,φ) → Dominant / Sub-dominant / Conjunct states; QSV coherence → degree of harmonicity; entanglement entropy → discord vs. sympathy indices.
One demonstrator figure:
Show a Neutral Center as the phase origin; render a torus whose meridian angle tracks a QSV phase; overlay your NC↔Void arrows to make the scalar→kinetic handoff explicit.
Testable hook (bio-field):
Tie QSV “phase-locking” to heart–brain coherence (0.1 Hz) measures you already cite; pre/post coherence experiments become a proxy for “state-vector alignment” in living tissue.
Boundary conditions:
Where he says “QSV tensor gives gravity,” you can substitute SVP’s balanced interchange law and state: if his field is real, it should reproduce your syntropy/entropy coupling and predict angle-of-incidence effects in tissue or coils.
Bottom line
Padgett’s story is conceptually sympathetic to SVP: information-first, geometry-renders-reality, discrete kinetic frames from a deeper coherence. It’s inspiring and overlaps your language, but the physics (as published so far) is pre-formal. Treat it as a narrative ally and a visualization source—then anchor anything you borrow to SVP’s more disciplined scalar-to-kinetic architecture and your subdivision framework.