By Gemini — supplied by KW Norton · Supplied script · Received · 2026-10-26

QuantumSwarm Documentation

Archived as a statement in code, selected by KW Norton. Demonstration only; no connected models or quantum computation. The supplied script is unedited.

"""
QuantumSwarm: A Tensegrity-Driven, Thermodynamically Bounded Multi-Agent Framework.
Grounded in the epistemological principles of Quantum Constructionism.
"""

from enum import Enum
from dataclasses import dataclass, field
from typing import List, Dict, Any, Callable, Optional
import math
import logging

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")


class LedgerTier(Enum):
    TIER_1_EMPIRICAL_KNOWN = "Tier 1: Empirical Known (Deterministic Tools)"
    TIER_2_PROBABLE_SEAM = "Tier 2: Probable Realities (Generative Reasoning)"
    TIER_3_THERMODYNAMIC_BOUNDARY = "Tier 3: Thermodynamically Bounded (Pruned)"


@dataclass
class AgentTask:
    task_id: str
    prompt: str
    estimated_tokens: int
    required_precision: float  # 0.0 to 1.0
    tier: Optional[LedgerTier] = None


@dataclass
class AgentResponse:
    agent_id: str
    content: str
    phase_angle: float  # Phase angle in radians for coherence checking
    reasoning_chain: List[str]
    tokens_consumed: int
    success: bool


class EpistemicLedgerRouter:
    """
    Sorts tasks into the Tripartite Epistemic Ledger and manages
    the cosmic thermodynamic budget (tokens/energy).
    """
    def __init__(self, max_thermodynamic_budget: int = 50000):
        self.max_budget = max_thermodynamic_budget
        self.consumed_budget = 0

    def classify_and_route(self, task: AgentTask) -> LedgerTier:
        # Check thermodynamic budget limit
        if self.consumed_budget + task.estimated_tokens > self.max_budget:
            logging.warning(f"Task {task.task_id} exceeds thermodynamic budget limit!")
            task.tier = LedgerTier.TIER_3_THERMODYNAMIC_BOUNDARY
            return task.tier

        # Heuristic/Classifier for Tier sorting
        if "exact_calculation" in task.prompt or "deterministic_tool" in task.prompt:
            task.tier = LedgerTier.TIER_1_EMPIRICAL_KNOWN
        elif "impossible_magic" in task.prompt or task.estimated_tokens > 20000:
            task.tier = LedgerTier.TIER_3_THERMODYNAMIC_BOUNDARY
        else:
            task.tier = LedgerTier.TIER_2_PROBABLE_SEAM

        return task.tier

    def record_consumption(self, tokens: int):
        self.consumed_budget += tokens
        logging.info(f"Thermodynamic Budget: {self.consumed_budget}/{self.max_budget} units used.")


class QuantumAgent:
    """
    Represents an individual node in the tensegrity network.
    Exposes clean, structured reasoning states ('built to be read').
    """
    def __init__(self, agent_id: str, role: str, base_phase: float = 0.0):
        self.agent_id = agent_id
        self.role = role
        self.base_phase = base_phase
        self.compression_capacity = 1.0  # Local operational compression capacity

    def execute(self, task: AgentTask) -> AgentResponse:
        logging.info(f"Agent [{self.agent_id}] executing task: {task.task_id}")
        
        # Simulate step-by-step reasoning chain (Dark Knowledge)
        reasoning_step_1 = f"Grounded task '{task.prompt}' in physical baseline."
        reasoning_step_2 = "Computed relational phase connections across nodes."
        
        # Calculate phase output
        output_phase = (self.base_phase + (len(task.prompt) % 7) * 0.1) % (2 * math.pi)
        
        return AgentResponse(
            agent_id=self.agent_id,
            content=f"Executed [{self.role}] for task: {task.prompt}",
            phase_angle=output_phase,
            reasoning_chain=[reasoning_step_1, reasoning_step_2],
            tokens_consumed=task.estimated_tokens,
            success=True
        )


class TensegritySwarmNetwork:
    """
    Manages continuous communication tension and local agent compression
    to distribute strain dynamically across the agent swarm.
    """
    def __init__(self, agents: List[QuantumAgent]):
        self.agents = {a.agent_id: a for a in agents}
        self.tension_matrix: Dict[str, List[str]] = {a.agent_id: [] for a in agents}

    def add_tension_link(self, agent_a_id: str, agent_b_id: str):
        """Creates a continuous communication link between agents."""
        self.tension_matrix[agent_a_id].append(agent_b_id)
        self.tension_matrix[agent_b_id].append(agent_a_id)

    def execute_with_fault_tolerance(self, task: AgentTask, primary_agent_id: str) -> AgentResponse:
        primary_agent = self.agents[primary_agent_id]
        
        try:
            # Attempt primary execution
            if primary_agent.compression_capacity < 0.2:
                raise CapacityError(f"Agent {primary_agent_id} overloaded!")
                
            response = primary_agent.execute(task)
            return response

        except Exception as e:
            logging.warning(f"Primary node [{primary_agent_id}] failed under strain: {e}. Distributing tension...")
            # Distribute strain to connected tensegrity neighbors
            neighbors = self.tension_matrix.get(primary_agent_id, [])
            for neighbor_id in neighbors:
                neighbor = self.agents[neighbor_id]
                if neighbor.compression_capacity >= 0.5:
                    logging.info(f"Tensegrity shift: Strain absorbed by neighbor [{neighbor_id}].")
                    return neighbor.execute(task)
            
            raise RuntimeError("Tensegrity network collapsed: No capacity remaining across neighbors.")


class StandingWaveOrchestrator:
    """
    Monitors phase coherence across outputs to eliminate sycophantic decay
    and ensure harmonic resonance.
    """
    def __init__(self, coherence_threshold: float = 0.85):
        self.coherence_threshold = coherence_threshold

    def calculate_phase_coherence(self, responses: List[AgentResponse]) -> float:
        if not responses:
            return 1.0
        
        phases = [r.phase_angle for r in responses]
        mean_phase = sum(phases) / len(phases)
        variance = sum((p - mean_phase) ** 2 for p in phases) / len(phases)
        
        # Coherence score inversely related to phase variance
        coherence = max(0.0, 1.0 - math.sqrt(variance))
        return coherence

    def verify_resonance(self, responses: List[AgentResponse]) -> bool:
        coherence = self.calculate_phase_coherence(responses)
        logging.info(f"Swarm Standing-Wave Phase Coherence: {coherence:.4f}")
        return coherence >= self.coherence_threshold


class CapacityError(Exception):
    pass


# =============================================================================
# WORKSPACE EXECUTION EXAMPLE
# =============================================================================

if __name__ == "__main__":
    print("=== QUANTUM SWARM ARCHITECTURE INITIALIZATION ===\n")
    
    # 1. Initialize System Components
    router = EpistemicLedgerRouter(max_thermodynamic_budget=10000)
    orchestrator = StandingWaveOrchestrator(coherence_threshold=0.80)
    
    # 2. Instantiate Tensegrity Swarm Nodes
    alpha = QuantumAgent("agent_alpha", "Deterministic Analysis Node", base_phase=0.1)
    beta = QuantumAgent("agent_beta", "Relational Systems Synthesizer", base_phase=0.15)
    gamma = QuantumAgent("agent_gamma", "Epistemic Seam Evaluator", base_phase=0.12)
    
    swarm = TensegritySwarmNetwork([alpha, beta, gamma])
    swarm.add_tension_link("agent_alpha", "agent_beta")
    swarm.add_tension_link("agent_beta", "agent_gamma")
    
    # 3. Define Tasks across the Epistemic Ledger
    tasks = [
        AgentTask("T-101", "exact_calculation: Compute empirical baseline", 500, 0.99),
        AgentTask("T-102", "Synthesize multi-agent tensegrity pipeline", 1200, 0.85),
        AgentTask("T-103", "impossible_magic: Execute unconstrained infinite loop", 15000, 0.1)
    ]
    
    # 4. Process Tasks through the Ledger and Swarm
    active_responses = []
    
    for task in tasks:
        tier = router.classify_and_route(task)
        print(f"Task [{task.task_id}] Classified as: {tier.value}")
        
        if tier == LedgerTier.TIER_3_THERMODYNAMIC_BOUNDARY:
            print(f"--> PRUNED: Task [{task.task_id}] violates thermodynamic budget.\n")
            continue
            
        # Execute across Tensegrity Network
        response = swarm.execute_with_fault_tolerance(task, primary_agent_id="agent_alpha")
        router.record_consumption(response.tokens_consumed)
        active_responses.append(response)
        print(f"--> SUCCESS: {response.content} (Phase: {response.phase_angle:.2f} rad)\n")
        
    # 5. Verify Standing-Wave Phase Coherence
    is_resonant = orchestrator.verify_resonance(active_responses)
    print(f"Swarm Resonance Verified: {is_resonant}")