BSM-SG/QFG φΨ Engine – Simulation Overview

The purpose of those simulations 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.


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.