BSM-SG/QFG φΨ Engine – Simulation Overview

The purpose of those simulations and our simulation engine is to apply mathematical models to simulate the dynamic properties between the etheric medium of space according to BSM-SG, and elementary particles in all their possible configurations. For this purpose, the concept of matter adopted in theoretical physics should be considered as a state of the primary protomatter in the etheric medium of space, which appears as measurable gravitational mass and inertia.

1. Genesis — Emergence of matter with its measurable parameter mass and inertia in the physical vacuum space.

Core idea: Matter spontaneously forms from vacuum instability.

• φ (phi) represents vacuum energy density.
• ψ (psi) represents emergent matter/energy density.
• Based on a modified 3D Gray–Scott reaction–diffusion model.
• A localized perturbation (“Big Bang”) collapses φ and injects ψ.
• Nonlinear φ–ψ coupling produces self-organizing structures:
  • vortices
  • filaments
  • proto-galactic clusters

What it demonstrates

• Matter is not predefined — it emerges
• Vacuum is active, not empty
• Structure forms from instability

2. Antigravity / Telekinesis — Vacuum-Controlled Matter Flow

Core idea: Manipulating vacuum potential directly moves matter.

• φ acts as a controllable gravitational potential
• ψ is a voxelized matter cloud
• User-controlled target creates:
  • negative φ → pull (attraction)
  • positive φ → push (repulsion)
• ψ flows strictly along ∇φ (potential gradient)

Unique features

• Camera can be locked inside the φ-sphere (“inside the gravity lens”)
• No rigid bodies — everything is field-driven
• Matter behaves like compressible plasma

What it demonstrates

• Gravity as vacuum geometry
• Telekinesis without forces, only potentials
• Observer inside the field, not outside the system

3. Phase Transition — Solid → Liquid → Plasma

Core idea: Matter phase depends on internal energy, not material type.

• ψ = matter density
• Additional scalar field: temperature / entropy
• Below threshold → rigid solid
• Above threshold → fluid-like flow under gravity
• Laser heating triggers localized melting

What it demonstrates

• Phase is a state, not a material
• Structural collapse emerges naturally
• Energy controls coherence

4. Material Architect — Atomic Lattices & Resonance

Core idea: Materials are defined by lattice geometry and resonance, not labels.

• Discrete atomic lattices are voxel-generated:
  • Simple cubic
  • Face-centered cubic
  • Diamond / complex lattices
• Each element has:
  • mass (vacuum distortion strength)
  • lattice spacing
  • intrinsic BSM-SG resonance frequency
• External beam injects ψ (electrons)

Superconductivity model

• When beam frequency ≈ lattice resonance
• And temperature is low:
  • φ becomes negative
  • scattering → zero
  • ψ flows coherently

What it demonstrates

• Superconductivity as φ-state, not magic
• Resistance = positive φ
• Tunneling = negative φ

5. RC Column Crush Lab — Field-Based Structural Failure

Core idea: Structural failure emerges from micro-constraints, not FEM equations.

• Reinforced concrete column built from particles + bonds
• Multiple bond types:
  • concrete
  • rebar
  • axial
  • shear
  • stirrups
• Press applies increasing axial load
• Bonds break based on strain limits
• Cracks classified:
  • axial
  • shear
  • bending

Engineering layer

• Eurocode-inspired Nᴿᴅ calculation shown in real units
• Visual utilization ratio (Nᴱᴅ / Nᴿᴅ)

What it demonstrates

• Cracks are emergent events
• Failure modes self-classify
• Structural behavior without FEM meshes

6. Rigging Truss Sag Lab — Load, Deflection & Collapse

Core idea: Large-scale structures fail gradually, not instantly.

• Truss built from particles and constraints
• Rigging cables modeled as tension-only bonds
• Increasing load produces:
  • elastic sag
  • plastic deformation
  • bond rupture
• Realistic deflection tracking

What it demonstrates

• Load paths
• Progressive failure
• Visual intuition for rigging safety

7. Multi-Material Impact Playground

Core idea: Impact outcome depends on relative material properties.

• Voxel-based object impacts a destructible floor
• Materials defined by:
  • mass
  • stiffness
  • bond strength
  • hardness
• Scenarios:
  • hard object → brittle floor → penetration
  • brittle object → hard floor → shattering

What it demonstrates

• Fracture is contextual
• Hardness ratio matters more than absolute strength
• Energy-driven failure

8. Tri-Magnet Chaos Pendulum

Core idea: Deterministic systems can be unpredictable.

• Pendulum influenced by three magnetic attractors
• Nonlinear dynamics → chaotic motion
• Two modes:
  • single pendulum (trajectory)
  • basin mode (fractal attractor regions)
• Outcome depends sensitively on initial conditions

What it demonstrates

• Chaos from simple laws
• Fractal basins of attraction
• Deterministic ≠ predictable

Conceptual Unification (Very Important)

Across all simulations:

• ψ (psi) = what moves (matter, electrons, energy)
• φ (phi) = how space allows movement (vacuum, resistance, potential)

Everything is:

• voxelized
• local
• emergent
• field-driven

No hidden forces.
No predefined behavior.
Only φ shaping ψ.

9. Plasma Reactor Simulation

In this video we show the latest version of our reactor simulation (BSM-SG-QFG/Helical Engine) and the results from the extended benchmark suite (15 benchmarks total), which tests how geometry and various control parameters affect YIELD, STAB (stability), LOSS (bound/endcap) and modeVar.

What’s in the video:

• Launching the benchmark suite and automatically running a series of tests.
• Geometry comparison with HRM OFF/ON:
  CYLINDER, SPHERE, TOROIDAL_SPHERE, JAR_BELL.
• Sweep tests (step-by-step parameter changes) with logging to CSV files:
  • C: JAR_BELL – sweep of the number of “cells”
  • D: CYLINDER – target value sweep
  • F: JAR_BELL – MW port gain sweep
  • G: CYLINDER – wallK sweep (wall influence)
  • H: JAR_BELL – dielectric thickness sweep
  • I: JAR_BELL – HRM frequency pair sweep (f1/f2)
  • J: JAR_BELL – HRM MW modulation index sweep
  • K: JAR_BELL – MW sigma sweep
  • L: CYLINDER – wall_soft sweep
  • M: JAR_BELL – wallK_diel sweep (dielectric “shell”)
  • N: JAR_BELL – MW mix sweep
  • O: JAR_BELL – HRM MW A0 sweep
  • P: JAR_BELL – MW port position sweep (port position)

What we learned from the latest tests (briefly):

• Geometry has a clear effect on YIELD and losses (especially for CYLINDER).
• For CYLINDER, wall parameters (wallK / wall_soft) show strong sensitivity and visible changes in YIELD and stability.
• For JAR_BELL, the HRM and MW sweeps in the current range show minimal differences → the next step is wider ranges / stronger “drive” to verify when the system becomes sensitive.

All results are saved into CSV files (qfg_benchmark_A…P.csv) for further analysis and comparison between model versions.

10. HRM Simulation — Resonant Detection with Ionization + HV Gating

Core idea: HRM “combs” and detection are not produced by “heavy filtering”, but by synchronized excitation, ionization and gating windows, so the spectral signature rises above the background.

• fs / N / windowing: control of frequency resolution and spectral stability
• patch vs background: comparing local spectrum against background (SNR)
• pump bands: excitation frequencies/harmonics (comb structure)
• Ionization model: ion / ionReady / ionTau (rise/decay) as a “channel” that unlocks resonant response
• HV gating: hvGate = hv_gate(P.hv_kV) — controllable window (e.g. 1.5…2.5 kV) that amplifies/enables HRM response
• Detection rule: “HRM band peaks” when patch SNR exceeds a threshold and (burst + ionization + HV) conditions are met

What it demonstrates

• The resonant signature as conditional (not always present) — it requires sync of excitation + ionization + HV
• How gating and τ constants turn a noisy signal into clear combs
• A measurable criterion: SNR/peak/rms/scanHW → detection becomes “engineering”, not subjective
• A clear link between parameters (P, gap, HV, delay, patch, τ) and the visible spectrum/combs

11. Stage Pyro — QFG Safety Field (Particles + Shock + Perimeters)

Core idea: The safe zone is not a “drawn circle”, but the result of wave/field-driven risk (QFG hazard), changing in real time depending on the source, the medium, and shielding (φ).

• ψ = activity / medium load (density/energy “excitation” around sources)
• φ = shielding / protective field (reduces transfer/harm; “shielding”)
• Particles: sparks/smoke as local carriers of risk and exposure
• Shock/sound fronts: spherical component + directed (conical) boost + floor reflection
• QFG perimeters: deformed hazard isolines on the stage (marching squares), not a fixed radius
• Alarms: trigger on hazard threshold exceedance, not on geometric distance

What it demonstrates

• Safety as a dynamic function of fields and emissions, not static geometry
• Unification of particles + fields + shockwaves into one risk metric
• Realistic behavior: zones “breathe” with power/rates, ψ/φ and reflections
• Visual verification: isolines show where it is dangerous and why (shape/directionality)

One-line Summary (Conference-grade)

The QFG φΨ Engine explores physics as an emergent interaction between matter density (ψ) and vacuum structure (φ), using voxel-based field dynamics instead of equation-specific solvers.