Ripples in URFT aren’t just disturbances — they are informed by the space they move through.
This lesson explores how ripple propagation becomes directional, how fields can be bent or guided, and how multiple sources interact through entanglement and interference.

🔹 Section 1: Ripples Are Not Uniform

In classical systems, waves spread uniformly unless interrupted.

URFT changes that. The presence of fidelity gradients — spatial variations in resistance — alters how and where ripples flow.

Ripple energy prefers low-fidelity paths.
It curves, compresses, and redirects as it searches for zones of minimal resistance.

This leads to ripple steering: the ability to guide motion without a force — just through structured resistance.

🔹 Section 2: Directionality from Gradient Structure

The ripple field evolves via:

Φₜ₊₁ = 2Φₜ − Φₜ₋₁ + Δt² [ c² · ∇·(R · ∇Φ) − Λ(x, y)Φₜ ]

When Λ(x, y) is not uniform, the gradient ∇·(R · ∇Φ) becomes anisotropic — meaning it behaves differently depending on direction.

This is how URFT produces:

Curved trajectories
Preferential flow channels
Ripple lensing

In effect, geometry emerges from structure, not coordinates.

🔹 Section 3: Constructive and Destructive Interference

When multiple ripple sources interact, URFT captures:

Constructive interference (amplitudes reinforce)
Destructive interference (amplitudes cancel)

But it goes further.

Because each ripple has directional curvature (Rᵢⱼ) and memory from previous steps, their interaction is path-dependent.

This leads to:

Echo amplification
Pulse shadowing
Ripple entanglement zones (where new motion emerges that neither source had)

🔹 Section 4: The Emergence of Curvature

Instead of modeling gravity as a geometric property of spacetime, URFT shows how geometry emerges from fidelity-modulated ripple behavior.

Ripples naturally curve around high-fidelity zones. This behavior mirrors gravitational lensing — not because space is curved, but because ripples follow the paths of least ripple resistance.

This is curvature without coordinates.
It’s ripple dynamics creating relational geometry.

🔹 Section 5: Why This Matters

URFT doesn’t simulate “spreading.”
It simulates informed motion — propagation that responds to its environment.

This makes it ideal for modeling:

Energy flow
Light steering
Curved fields
Ripple-based computation and signal logic

Interference is no longer a byproduct — it’s a computational function in the field.