🧠 Quantum Memory Module¶

🔐 Licensed Component - Contact: bajpaikrishna715@gmail.com for licensing

Quantum Memory Architecture¶

graph TB
    subgraph "Memory Hierarchy"
        A[Quantum RAM - QRAM]
        B[Entangled Storage]
        C[Coherent Cache]
        D[Classical Buffer]
    end

    subgraph "Access Patterns"
        E[Quantum Addressing]
        F[Superposition Lookup]
        G[Entangled Retrieval]
        H[Parallel Access]
    end

    subgraph "Memory Types"
        I[Short-Term Quantum]
        J[Long-Term Classical]
        K[Working Memory]
        L[Episodic Memory]
    end

    subgraph "Coherence Management"
        M[Decoherence Monitoring]
        N[Error Correction]
        O[State Refreshing]
        P[Fidelity Maintenance]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

    I --> M
    J --> N
    K --> O
    L --> P

🌟 Core Features¶

Quantum Associative Memory¶

graph LR
    subgraph "Input Processing"
        A[Query Encoding]
        B[Quantum State Preparation]
        C[Superposition Creation]
        D[Entanglement Setup]
    end

    subgraph "Memory Search"
        E[Quantum Interference]
        F[Amplitude Amplification]
        G[Pattern Matching]
        H[Similarity Assessment]
    end

    subgraph "Retrieval Process"
        I[State Collapse]
        J[Measurement]
        K[Result Extraction]
        L[Confidence Scoring]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

Memory Consolidation¶

graph TB
    subgraph "Encoding Phase"
        A[Information Input]
        B[Quantum Encoding]
        C[State Preparation]
        D[Initial Storage]
    end

    subgraph "Consolidation Process"
        E[Pattern Recognition]
        F[Connection Strengthening]
        G[Redundancy Creation]
        H[Error Correction]
    end

    subgraph "Long-term Storage"
        I[Stable States]
        J[Classical Backup]
        K[Distributed Storage]
        L[Accessibility Indexing]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

🔧 Implementation¶

Basic Quantum Memory¶

from quantumlangchain.memory import QuantumMemory
import numpy as np

# Initialize quantum memory system
memory = QuantumMemory(
    classical_dim=1024,
    quantum_dim=8,
    decoherence_rate=0.01,
    error_correction=True
)

# Store information with quantum encoding
key = "quantum_computing_basics"
value = "Quantum computing uses quantum mechanical phenomena..."
memory.store(key, value, importance=0.9)

# Retrieve with quantum search
result = memory.retrieve("quantum computing", similarity_threshold=0.8)
print(result)

Advanced Memory Configuration¶

from quantumlangchain.memory import (
    QuantumMemory, 
    EntangledMemory,
    AdaptiveMemory
)

# Multi-layer memory system
class HybridMemorySystem:
    def __init__(self):
        # Fast quantum cache
        self.qcache = QuantumMemory(
            classical_dim=256,
            quantum_dim=4,
            decoherence_rate=0.1,
            refresh_rate="high"
        )

        # Long-term entangled storage
        self.entangled_store = EntangledMemory(
            classical_dim=2048,
            quantum_dim=12,
            entanglement_strength=0.9,
            persistence=True
        )

        # Adaptive working memory
        self.working_memory = AdaptiveMemory(
            base_dim=512,
            max_expansion=4096,
            adaptation_rate=0.05
        )

    async def store_experience(self, experience, context=None):
        """Store experience across memory layers."""
        # Immediate storage in quantum cache
        await self.qcache.store(
            experience["key"], 
            experience["data"],
            tags=experience.get("tags", [])
        )

        # Contextual storage in working memory
        if context:
            await self.working_memory.store_with_context(
                experience, context
            )

        # Long-term consolidation
        if experience.get("importance", 0) > 0.7:
            await self.entangled_store.consolidate(experience)

Quantum Episodic Memory¶

from quantumlangchain.memory import EpisodicMemory
from datetime import datetime

# Episodic memory for experiences
episodic_memory = EpisodicMemory(
    temporal_encoding=True,
    spatial_encoding=True,
    emotional_weighting=True
)

# Store episodic experience
experience = {
    "content": "User asked about quantum entanglement",
    "timestamp": datetime.now(),
    "context": "scientific discussion",
    "emotional_tone": "curious",
    "outcome": "provided detailed explanation"
}

await episodic_memory.store_episode(experience)

# Retrieve similar episodes
similar_episodes = await episodic_memory.retrieve_episodes(
    query="quantum physics questions",
    temporal_window="last_week",
    similarity_threshold=0.75
)

🎯 Memory Types¶

Short-Term Quantum Memory¶

graph TB
    subgraph "Quantum Working Memory"
        A[Active Information]
        B[Quantum Registers]
        C[Superposition States]
        D[Coherent Processing]
    end

    subgraph "Characteristics"
        E[High Speed Access]
        F[Limited Capacity]
        G[Quantum Coherence]
        H[Temporary Storage]
    end

    subgraph "Use Cases"
        I[Real-time Processing]
        J[Quantum Calculations]
        K[Intermediate Results]
        L[Active Reasoning]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

Long-Term Classical Memory¶

graph LR
    subgraph "Classical Storage"
        A[Vector Embeddings]
        B[Relational Data]
        C[Graph Structures]
        D[Hierarchical Trees]
    end

    subgraph "Persistence Layer"
        E[Database Storage]
        F[File Systems]
        G[Distributed Storage]
        H[Cloud Backends]
    end

    subgraph "Access Methods"
        I[Index-based Lookup]
        J[Semantic Search]
        K[Graph Traversal]
        L[Hierarchical Navigation]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

Entangled Memory Networks¶

graph TB
    subgraph "Memory Nodes"
        A[Node 1 - Facts]
        B[Node 2 - Concepts]
        C[Node 3 - Relations]
        D[Node 4 - Experiences]
    end

    subgraph "Entanglement Links"
        E[Fact-Concept Links]
        F[Concept-Relation Links]
        G[Relation-Experience Links]
        H[Cross-Domain Links]
    end

    subgraph "Emergent Properties"
        I[Holistic Understanding]
        J[Non-local Correlations]
        K[Quantum Interference]
        L[Collective Behavior]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

📊 Performance Characteristics¶

Memory Access Patterns¶

graph LR
    subgraph "Classical Access"
        A[Sequential Search]
        B[O log n Lookup]
        C[Cache Miss Penalty]
        D[Linear Scaling]
    end

    subgraph "Quantum Access"
        E[Parallel Search]
        F[O sqrt n Speedup]
        G[Coherent Operations]
        H[Quantum Advantage]
    end

    subgraph "Hybrid Benefits"
        I[Best of Both Worlds]
        J[Adaptive Selection]
        K[Context-Aware Access]
        L[Optimized Performance]
    end

    A --> I
    B --> J
    C --> K
    D --> L

    E --> I
    F --> J
    G --> K
    H --> L

Capacity Scaling¶

graph TB
    subgraph "Quantum Scaling"
        A[Exponential State Space]
        B[n Qubits = 2^n States]
        C[Superposition Storage]
        D[Entanglement Compression]
    end

    subgraph "Classical Scaling"
        E[Linear Growth]
        F[Hardware Limitations]
        G[Storage Costs]
        H[Access Time Growth]
    end

    subgraph "Hybrid Optimization"
        I[Quantum for Hot Data]
        J[Classical for Cold Data]
        K[Dynamic Allocation]
        L[Intelligent Caching]
    end

    A --> I
    B --> J
    C --> K
    D --> L

    E --> I
    F --> J
    G --> K
    H --> L

🛠️ Configuration Options¶

Memory Architecture Configuration¶

# Memory configuration templates
MEMORY_CONFIGS = {
    "basic": {
        "classical_dim": 512,
        "quantum_dim": 4,
        "decoherence_rate": 0.1,
        "error_correction": False,
        "backup_frequency": "hourly"
    },

    "professional": {
        "classical_dim": 1024,
        "quantum_dim": 8,
        "decoherence_rate": 0.01,
        "error_correction": True,
        "distributed": False,
        "compression": True
    },

    "enterprise": {
        "classical_dim": 2048,
        "quantum_dim": 16,
        "decoherence_rate": 0.001,
        "error_correction": True,
        "distributed": True,
        "fault_tolerance": True,
        "encryption": True
    },

    "research": {
        "classical_dim": 4096,
        "quantum_dim": 32,
        "decoherence_rate": 0.0001,
        "error_correction": True,
        "distributed": True,
        "experimental_features": True,
        "custom_protocols": True
    }
}

Coherence Management¶

graph TB
    subgraph "Decoherence Sources"
        A[Environmental Noise]
        B[Thermal Fluctuations]
        C[Electromagnetic Interference]
        D[System Interactions]
    end

    subgraph "Mitigation Strategies"
        E[Error Correction Codes]
        F[Dynamical Decoupling]
        G[Decoherence-Free Subspaces]
        H[Active Feedback Control]
    end

    subgraph "Performance Metrics"
        I[Coherence Time]
        J[Fidelity Measures]
        K[Error Rates]
        L[Success Probability]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

🔒 License Integration¶

Memory Tier Restrictions¶

graph LR
    subgraph "License Tiers"
        A[Basic - 512 MB]
        B[Professional - 2 GB]
        C[Enterprise - 8 GB]
        D[Research - Unlimited]
    end

    subgraph "Quantum Dimensions"
        E[4 Qubits]
        F[8 Qubits]
        G[16 Qubits]
        H[32+ Qubits]
    end

    subgraph "Advanced Features"
        I[Basic Operations]
        J[Error Correction]
        K[Distributed Memory]
        L[Experimental Protocols]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

Memory Access Control¶

from quantumlangchain.licensing import requires_license

class QuantumMemory(LicensedComponent):
    @requires_license(tier="basic")
    def __init__(self, classical_dim=512, quantum_dim=4, **kwargs):
        """Initialize quantum memory with license validation."""
        super().__init__(
            required_features=["quantum_memory"],
            required_tier="basic"
        )

        # Validate memory limits based on license
        max_classical, max_quantum = self._get_memory_limits()

        if classical_dim > max_classical:
            raise LicenseError(
                f"Classical memory limit exceeded. "
                f"License allows {max_classical}MB, requested {classical_dim}MB. "
                f"Contact: bajpaikrishna715@gmail.com"
            )

        if quantum_dim > max_quantum:
            raise LicenseError(
                f"Quantum dimension limit exceeded. "
                f"License allows {max_quantum} qubits, requested {quantum_dim}. "
                f"Contact: bajpaikrishna715@gmail.com"
            )

    @requires_license(tier="professional")
    def enable_error_correction(self):
        """Enable quantum error correction (Professional+ only)."""
        pass

    @requires_license(tier="enterprise")
    def enable_distributed_storage(self):
        """Enable distributed memory storage (Enterprise+ only)."""
        pass

🎯 Advanced Features¶

Quantum Memory Patterns¶

graph TB
    subgraph "Content-Addressable Memory"
        A[Input Pattern]
        B[Quantum Encoding]
        C[Associative Recall]
        D[Pattern Completion]
    end

    subgraph "Temporal Memory"
        E[Sequence Learning]
        F[Temporal Patterns]
        G[Predictive Coding]
        H[Future State Prediction]
    end

    subgraph "Hierarchical Memory"
        I[Multi-level Organization]
        J[Abstraction Layers]
        K[Concept Hierarchies]
        L[Emergent Structure]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

Memory Optimization¶

# Advanced memory optimization
class OptimizedQuantumMemory:
    def __init__(self, **config):
        self.config = config
        self.optimizer = MemoryOptimizer()

    async def optimize_storage(self):
        """Optimize memory storage patterns."""
        # Analyze access patterns
        patterns = await self.analyzer.analyze_access_patterns()

        # Optimize quantum state allocation
        optimal_allocation = self.optimizer.optimize_allocation(
            patterns, self.config
        )

        # Reorganize memory structure
        await self.reorganize_memory(optimal_allocation)

    async def adaptive_compression(self):
        """Adaptive memory compression based on usage."""
        # Identify rarely accessed memories
        cold_memories = await self.identify_cold_memories()

        # Apply quantum compression
        for memory in cold_memories:
            compressed = await self.quantum_compress(memory)
            await self.store_compressed(memory.key, compressed)

    async def predictive_prefetch(self, current_context):
        """Predictive memory prefetching."""
        # Predict likely future access patterns
        predictions = await self.predictor.predict_access(
            current_context
        )

        # Prefetch predicted memories
        for prediction in predictions:
            if prediction.confidence > 0.8:
                await self.prefetch_memory(prediction.key)

📚 API Reference¶

Core Memory Operations¶

class QuantumMemory:
    async def store(self, key: str, value: Any, **metadata) -> bool:
        """Store information in quantum memory."""

    async def retrieve(self, query: str, **params) -> List[MemoryItem]:
        """Retrieve information using quantum search."""

    async def update(self, key: str, value: Any) -> bool:
        """Update existing memory entry."""

    async def delete(self, key: str) -> bool:
        """Delete memory entry."""

    async def search(self, query: str, **params) -> SearchResults:
        """Semantic search across memory."""

    def get_memory_stats(self) -> MemoryStats:
        """Get memory usage statistics."""

    async def optimize(self) -> None:
        """Optimize memory organization."""

    async def backup(self, location: str) -> bool:
        """Backup memory to specified location."""

Specialized Memory Types¶

class EpisodicMemory(QuantumMemory):
    async def store_episode(self, experience: Experience) -> bool:
        """Store episodic experience."""

    async def retrieve_episodes(self, query: str, **filters) -> List[Episode]:
        """Retrieve similar episodes."""

class SemanticMemory(QuantumMemory):
    async def store_concept(self, concept: Concept) -> bool:
        """Store semantic concept."""

    async def retrieve_concepts(self, query: str) -> List[Concept]:
        """Retrieve related concepts."""

class ProceduralMemory(QuantumMemory):
    async def store_procedure(self, procedure: Procedure) -> bool:
        """Store procedural knowledge."""

    async def retrieve_procedures(self, task: str) -> List[Procedure]:
        """Retrieve relevant procedures."""

🔮 Future Enhancements¶

Planned Memory Features¶

graph TB
    subgraph "Near Future"
        A[Improved Error Correction]
        B[Faster Access Times]
        C[Better Compression]
        D[Enhanced Coherence]
    end

    subgraph "Medium Term"
        E[Fault-Tolerant Memory]
        F[Distributed Quantum Memory]
        G[Memory-Memory Entanglement]
        H[Quantum Memory Networks]
    end

    subgraph "Long Term"
        I[Topological Memory]
        J[Quantum Error-Free Memory]
        K[Consciousness-Level Memory]
        L[Universal Memory Protocols]
    end

    A --> E
    B --> F
    C --> G
    D --> H

    E --> I
    F --> J
    G --> K
    H --> L

🔐 License Requirements¶

• Basic Memory: Basic license tier (512MB classical, 4 qubits)
• Professional Memory: Professional license tier (2GB classical, 8 qubits)
• Enterprise Memory: Enterprise license tier (8GB+ classical, 16+ qubits)
• Research Memory: Research license tier (unlimited capacity)

Contact bajpaikrishna715@gmail.com for licensing.

Quantum Memory represents the foundation of quantum-enhanced information storage and retrieval, enabling unprecedented memory capabilities for AI systems.