4. Phase‑3: Resonance‑native core skeleton#

Here we show how a unit could start building the new core alongside legacy systems.

4.1 Resonance‑Time Kernel interface#

// phase3/rtk.ts
export interface RtkObjectState {
  id: string;
  domain: "AIR" | "SPACE" | "NEAR_SPACE";
  position: [number, number, number]; // unified frame
  velocity: [number, number, number];
  meta: Record<string, unknown>;
}
 
export interface RtkFieldSample {
  position: [number, number, number];
  stability: number;
  drift_potential: number;
  coherence_gradient: [number, number, number];
}
 
export class ResonanceTimeKernel {
  ingest(states: RtkObjectState[]): void {
    // Build internal resonance field
  }
 
  sampleField(position: [number, number, number]): RtkFieldSample {
    return {
      position,
      stability: 0.95,
      drift_potential: 0.1,
      coherence_gradient: [0, 0, 0]
    };
  }
 
  propagate(id: string, horizonSec: number): RtkObjectState[] {
    return [];
  }
}

4.2 Global State Fabric façade#

// phase3/globalStateFabric.ts
import { RtkObjectState } from "./rtk";
 
export class GlobalStateFabric {
  private objects = new Map<string, RtkObjectState>();
 
  upsert(state: RtkObjectState) {
    this.objects.set(state.id, state);
  }
 
  getAll(): RtkObjectState[] {
    return [...this.objects.values()];
  }
 
  // In real life: consensus, replication, time sync, etc.
}

4.3 Phase‑3 automation built on RTK#

// phase3/resonanceAutomation.ts
import { ResonanceTimeKernel, RtkObjectState } from "./rtk";
import { GlobalStateFabric } from "./globalStateFabric";
 
export class ResonanceAutomation {
  constructor(
    private rtk: ResonanceTimeKernel,
    private gsf: GlobalStateFabric
  ) {}
 
  updateFromSensors(states: RtkObjectState[]) {
    states.forEach(s => this.gsf.upsert(s));
    this.rtk.ingest(this.gsf.getAll());
  }
 
  computeGlobalCoherence(): number {
    const all = this.gsf.getAll();
    if (!all.length) return 1;
    const samples = all.map(o => this.rtk.sampleField(o.position));
    return samples.reduce((s, f) => s + f.stability, 0) / samples.length;
  }
 
  proposeLaunchWindowCorridor(): unknown {
    // Use RTK field samples to find high-coherence windows/volumes
    return {};
  }
}

Outcome: they can run this in parallel with legacy SDA/ATC systems, compare outputs, and gradually shift trust and authority to the resonance‑native core.


5. Migration pattern for a Space Force unit#

Phase‑1 (3–9 months):

  • Deploy phase1/ middleware + overlays in sim → shadow → limited ops.
  • Train operators on new visuals and language (stability, resonance, coherence).

Phase‑2 (9–24 months):

  • Deploy phase2/ automation adapter.
  • Feed RTT predictions into existing conjunction + launch tools.
  • Run A/B comparisons and refine thresholds.

Phase‑3 (multi‑year, incremental):

  • Stand up phase3/ RTK + GSF in parallel.
  • Gradually route more decisions through resonance‑native automation.
  • Eventually retire legacy prediction/automation, keeping RTT/Inside as the canonical core.