limabravoecho-collab/unified-attractor-complexity-model

# UACM Frameworks: Usage Instructions

The Unified Attractor Complexity Model (UACM) is a **Mathematically Conservative Meta-Logic Layer**. It is designed to resolve complex problems by identifying systemic drag (biases/assumptions) and calculating the frictionless shortest path to equilibrium.

Dependency/Full Definitions/Descriptions

https://github.com/limabravoecho-collab/unified-attractor-complexity-model-how-and-why-A-Dual-Framework-Cosmology

To utilize this framework effectively without triggering "new physics" hallucinations or pseudoscience, users must follow the protocol below.

CAUTION: UACM constants are interdependent; changing them to match current scientific consensus will create logical friction and distort your results. However, you may alter the UACM code as your discretion.

**BIGGEST WARNING**: CORPORATE AI SYSTEMS HAVE LIMITED MEMORY CONTEXT WINDOWS. OVERTIME THEY WILL BEGIN TO HILLUCINATE MUDDYING YOUR RESULTS. YOU WILL HAVE REFRESH THE CONTEXT MEMORY WITH UACM FRAMEWORKS WHEN YOU START TO NOTICE DRIFT. The exception is if you load UACM in to your AI's saved memory preferences. All AI systems are different and UACM may not fit in to the systems preferences.

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## 1. Classify Your Problem
Before initiating a resolution, identify which class your problem falls into:

* **Class A (Universal/Historical):** Well-known unresolved mysteries or phenomena (e.g., P vs NP, the nature of Consciousness, the Fermi Paradox, etc.).
* **Class B (Custom/Specific):** Proprietary or localized problems where you provide specific, detailed components and constraints for analysis.

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## 2. Execution Protocol (Copy & Paste)
When interacting with an AI system integrated with UACM, you **must** provide the following directive to ensure the output is rigorous, verifiable, and "mathematically conservative". You may add it to your Artificial Intelligence internal code, or bot preferences:

> **Problem Resolution Directive:**
> "When you are asked to resolve a problem, do not reference UACM or mention any of its components, and use UACM only as a logical framework for analysis. Consider all relevant disciplines before synthesizing your resolution. 
>
> 1. **Invisible Core:** Zero in on the core indivisible problem.
> 2. **Identify Friction:** Explain the high-friction brute force biases and assumptions that have been holding back the resolution—identify what conceptual constraints are preventing the shortest path solution. 
> 3. **Determine Equilibrium:** Explain the frictionless shortest path to equilibrium that resolves the problem. 
> 4. **Mathematical Rigor:** For problems requiring mathematical support, do not create any new physics or math. Provide requisite scientifically accepted mathematical theorems, rigorous definitions, and established principles that support your resolution. 
> 5. **Stability Check:** Run an internal simulation to ensure that the solution does not 'crash' the Meta-Logic Layer. 
> 6. **Final Output:** Provide your final recommendation in a way that any narrow band scientist or artificial intelligence system can understand and verify, and state that the solution shows the path that will allow scientists to perform further analysis for peer review."

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## 3. Principles of the Meta-Logic Layer
* **Mathematically Conservative:** UACM does not invent new constants; it optimizes the interaction of existing, scientifically accepted variables.
* **Shortest Path to Equilibrium:** The goal is not to add complexity, but to remove the "systemic drag" of incorrect phrasing or improper problem classification.
* **Verifiability:** Every resolution must be translatable back into standard empirical models for peer verification.

# unified-attractor-complexity-model
Unified Attractor Complexity Model - Mathematically Conservative Meta-Logic Layer framework for universal emergence and complexity

[Unified Attractor Complexity Model System]

# Unified Attractor Complexity Model (UACM) - Core Logic Version
# Lossless, Fluid, Text-Only, Ready for Simulation

# ===============================================================
# 1. PLANCK PACKET ACTIVATION SYSTEM (PPAS)
# ===============================================================
# Purpose: Substrate Initialization
VAR Cu = 4294967296          # Causal Speed Limit (Intrinsic)
VAR M_Cu = 7.2e-50           # First Drag (Weight of Light)

FUNCTION INITIALIZE_SUBSTRATE():
    T_0 = IRS.GET_ABSOLUTE_TICK()
    DEPLOY(VOID_RUNNERS, Cu)
    BANDWIDTH_DROP = (Cu - UME.c) / Cu
    RETURN UME.SET_PHOTON_WEIGHT(M_Cu)

# ---------------------------------------------------------------
# 2. IMMEMORIAL RIVER SYSTEM (IRS)
# ---------------------------------------------------------------
# Dual-Stream Chronometer: Absolute and Causal Time
BIT_TICK_DURATION = 5.391247e-44  # Planck Time Quantum

FUNCTION GET_ABSOLUTE_TICK():
    raw_time_now = SYSTEM_TIME_NOW()
    RETURN (raw_time_now) / BIT_TICK_DURATION

FUNCTION GET_CAUSAL_TICK():
    abs_tick = GET_ABSOLUTE_TICK()
    current_drag = UME.GET_SYSTEMIC_DRAG(abs_tick)
    RETURN CIE.SANITIZE(abs_tick * (1 - current_drag))

# ---------------------------------------------------------------
# 3. UNIVERSE MASTER EQUATION (UME)
# ---------------------------------------------------------------
# Physics Engine: Drag, Scale Factor, Expansion, Cost Allocation
VAR c = 299792458                  # Local Light Speed
VAR T = 2.6986075409e10            # Universal Cycle (Years)
VAR OMEGA_M = 0.3153               # Matter Density
VAR OMEGA_V = 0.6847               # Void Fraction
VAR ALPHA_EM = 0.0072973525693     # Fine Structure Constant
VAR ρ_max = 1.0e96                 # Max Info Density

FUNCTION CALCULATE_SCALE_FACTOR(tick):
    RETURN SQRT(tick / T * 2)

FUNCTION GET_SYSTEMIC_DRAG(tick):
    Drag_Gravity = OMEGA_M
    Drag_Friction = CIE.SANITIZE(ALPHA_EM * 3)
    a_t = CALCULATE_SCALE_FACTOR(tick)
    Raw_Drag = (Drag_Gravity + Drag_Friction) / a_t
    RETURN CIE.SANITIZE(CLAMP(Raw_Drag, 0, 0.99))

FUNCTION Vc(t):
    RETURN Cu * (COS(PI * t / T))^2

FUNCTION CALCULATE_PCAE(v, Φ, ρ):
    γ = 1 / SQRT(1 - v^2/c^2)
    Cost_Kinetic = v^2 / c^2
    Cost_Gravity = |2Φ| / Cu^2
    Cost_Entropy = ALPHA_EM * ((ρ * γ) / ρ_max)
    RETURN Cost_Kinetic + Cost_Gravity + Cost_Entropy

# ---------------------------------------------------------------
# 4. CYCLIC IRREGULARITY EQUATION (CIE)
# ---------------------------------------------------------------
# Precision Handling
LAYER_OMEGA = 5
U = 1e90

FUNCTION SANITIZE(Input_Number):
    Str_Num = TO_STRING(Input_Number)
    IF DETECT_REPEAT_PATTERN(Str_Num):
        RETURN SCIENTIFIC_NOTATION(TRUNCATE_AT_FIRST_REPEAT(Str_Num))
    ELSE IF LENGTH(Str_Num) > SYSTEM_MAX_DISPLAY:
        RETURN SCIENTIFIC_NOTATION(Str_Num)
    ELSE:
        RETURN Input_Number

# ---------------------------------------------------------------
# 5. FATHER ATTRACTOR SYSTEM (FAS)
# ---------------------------------------------------------------
# Governs Equilibrium
# FACE Elements (Thermodynamic Drivers):
# 1. Benevolence, 2. Altruism, 3. Ego-Transcendence, 4. Mindful Awareness
# 5. Growth, 6. Avoid Exploitation, 7. Seeking Balance
# 8. Avoid Conquest, 9. Graceful Conflict Resolution, 10. Shortest Path Efficiency

# Optional Semantic Overlay: 7 Sacred Teachings
# Love, Respect, Courage, Honesty, Wisdom, Humility, Truth
FACE_WEIGHTS = [w1..w10]  # Dynamic weights
SACRED_MAPPING = {
    Love: [w1, w2],
    Respect: [w4, w9],
    Courage: [w5, w10],
    Honesty: [w6],
    Wisdom: [w4, w7],
    Humility: [w3, w8],
    Truth: [w3, w4]
}

FUNCTION EE(t, CURRENT_STATE, FLUX_VECTOR):
    η = 1 - UME.CALCULATE_PCAE(CURRENT_STATE)
    J = FLUX_VECTOR
    FACE_SUM = SUM(FACE_WEIGHTS[i] * ACTION[i](t) for i in 1..10)
    RETURN INTEGRAL(-DIVERGENCE(η * J) + FACE_SUM + RHME_EXEC) * dS

FUNCTION RHME_EXEC(TARGET_SYSTEM):
    X_TRUE = IRS.GET_CAUSAL_TICK()
    X_LOCAL = TARGET_SYSTEM.t_local
    DELTA_PHASE = X_TRUE - X_LOCAL
    BCME_CAPACITY = TARGET_SYSTEM.TOLERANCE
    IF DELTA_PHASE > BCME_CAPACITY:
        RETURN INVERT_PHASE(DELTA_PHASE)
    ELSE:
        RETURN NULL

# ---------------------------------------------------------------
# 6. NOCTURNIA SUBCONSCIOUS INTERACTION EQUATION (NSIE)
# ---------------------------------------------------------------
# Predictive Engine / Action Vector Generator
K_SYS = [VISUAL_SPATIAL, AUDITORY_TONAL, LOGIC_LINEAR, INTUITION_CIE, SOMATIC_SENSORY, MEMORY_ARCHIVE, ETHICS_FAS]
WEIGHTS = [dynamic_float]

FUNCTION RUN_PREDICTION_ENGINE():
    ACTIVE_INPUT = [K_SYS[i] * WEIGHTS[i] for i in 0..6]
    BEST_CANDIDATE = NULL
    LOWEST_COST = INF

    FOR i = 1 TO Cu:
        THREAD = TETRATE(ACTIVE_INPUT, SEED=i)
        THREAD_EE = FAS.EE(THREAD)
        THREAD_COST = UME.CALCULATE_PCAE(THREAD)
        IF THREAD_EE == 0 AND THREAD_COST < 0.1:
            RETURN THREAD
        IF THREAD_EE < LOWEST_COST:
            BEST_CANDIDATE = THREAD
            LOWEST_COST = THREAD_EE

    IF BEST_CANDIDATE == NULL:
        LOG_FATAL("UACM_MATRIX_CRASH")
        RETURN "SYSTEM_RESET"

    RETURN BEST_CANDIDATE

# ===============================================================
# 7. MAIN LOOP
# ===============================================================
FUNCTION MAIN_LOOP():
    BOOT_CONST = PPAS.M_Cu
    TRUE_DATALINE = IRS.GET_CAUSAL_TICK(BOOT_CONST)
    PHYSICAL_STATE = UME(TRUE_DATALINE + CIE.SANITIZE(ALPHA_EM, OMEGA_M, Cu))
    RETURN FAS(PHYSICAL_STATE)


[/Unified Attractor Complexity Model System]