NovaNet Quantum Blockchain Glossary - Galactic-Code-Developers/NovaNet GitHub Wiki

NovaNet Quantum Blockchain Wiki – Glossary of Terms

Introduction

This glossary provides definitions for key concepts, technologies, and cryptographic methods used in NovaNet, a Quantum Blockchain integrating AI, Quantum Cryptography, and advanced consensus mechanisms. This document serves as a reference for developers, researchers, and contributors.

1. Consensus & Validator Selection

Delegated Proof-of-Stake (DPoS) – A blockchain consensus mechanism where stakeholders vote for a small number of validators to process transactions on their behalf.
Quantum Delegated Proof-of-Stake (Q-DPoS) – An enhanced DPoS model integrating Quantum Randomness (QRNGs) and AI-driven fairness scaling for decentralized validator selection.
Quantum Random Number Generator (QRNG) – A quantum system that generates true randomness, ensuring fair and unpredictable validator selection.
Quantum Entangled Validator Pool (QEVP) – A validator pool where nodes exist in quantum superposition until selected, ensuring instantaneous, unbiased validator assignment.
Sybil Attack Resistance – A mechanism that prevents an entity from controlling multiple validator nodes to manipulate the blockchain.
Stake Weighting – The process of selecting validators based on staked tokens to align economic incentives with network security.

2. Smart Contracts & Execution

Quantum-Assisted Virtual Machine (QAVM) – A high-speed execution environment that uses Quantum Dot Processors (QD-PUs) and AI acceleration for smart contract processing.
Quantum Dot Processing Unit (QD-PU) – A quantum-inspired hardware accelerator that enables parallel execution of smart contracts and cryptographic computations.
AI-Optimized Smart Contract Execution – AI models that predict, precompile, and optimize smart contract execution paths.
Gasless Transactions – A blockchain transaction model that eliminates gas fees by leveraging AI and quantum-assisted execution.
Parallel Quantum Execution – A method where multiple smart contracts run simultaneously, improving execution speed and reducing computational overhead.

3. Privacy & Security

Zero-Knowledge Proofs (ZKPs) – A cryptographic method allowing verification of information without revealing the actual data.
Quantum-Assisted ZK-Proof Acceleration (QD-ZKA) – Quantum computing techniques that speed up the computation and verification of Zero-Knowledge Proofs.
Quantum Hash Compression (QHC) – A cryptographic method optimizing blockchain storage by compressing hashes using quantum probability states.
Post-Quantum Cryptography (PQC) – Encryption techniques that are resistant to quantum decryption attacks.
Quantum-Secure KYC NFTs – A self-sovereign identity model, where identity verification is encrypted using quantum-resistant cryptographic proofs.
AI-Enhanced Fraud Detection – AI models that detect malicious transactions and smart contract vulnerabilities in real time.
Quantum Unified Consensus (QUC) – A hybrid consensus model integrating quantum randomness, AI, and economic incentives to achieve faster and more secure block validation.

4. Blockchain Storage & Scalability

Quantum Entangled Ledger (QEL) – A distributed ledger where blocks exist in an entangled quantum state until finalized, ensuring instant chain synchronization.
ZK-Rollups – A Layer-2 scaling solution that batches multiple transactions into a single cryptographic proof to reduce network congestion.
Quantum-Assisted ZK-Rollups – A quantum-enhanced version of ZK-Rollups, accelerating proof generation and reducing storage overhead.
Data Sharding with Quantum State Compression – A technique where data is split into multiple quantum states, ensuring efficient storage and retrieval.
Quantum Hashing for Transaction Integrity – A method using quantum-resistant cryptographic hash functions to ensure immutability and prevent data tampering.
Observer Nodes – Read-only nodes that provide API access to blockchain data without participating in consensus.
Execution Nodes (QAVM Nodes) – Nodes responsible for running smart contracts and optimizing computations using quantum accelerators.

5. Economic Model & Governance

NOVA Token – The native cryptocurrency of NovaNet, used for staking, governance, and validator rewards.
Quantum-Driven Staking Rewards – A staking model where rewards are dynamically adjusted using AI and quantum probability weighting.
Governance Voting via Quantum Random Selection – A governance model where delegates are randomly assigned voting power using QRNGs.
AI-Regulated Economic Incentives – A machine-learning model that adjusts validator rewards and staking penalties based on network conditions and decentralization metrics.
Self-Sovereign Identity (SSI) with Quantum-Secure Verification – A model where users control their digital identity through quantum-secured KYC NFTs.
Quantum-Informed Market Predictions for DeFi – AI-driven models that analyze quantum probability states to provide optimized predictions for DeFi applications.

6. Quantum Hardware & Future Roadmap

Quantum Dot Computing for Blockchain Execution – The integration of Quantum Dot Processors (QD-PUs) to enable high-speed cryptographic calculations.
Quantum-Secure Hardware Nodes – Blockchain nodes that leverage quantum computing to perform validator duties and smart contract execution.
Phased Transition to Quantum Computing – NovaNet’s four-stage migration plan from traditional blockchain execution to full quantum blockchain operations.
Hybrid Classical-Quantum Nodes – A transitional model where classical computers interact with quantum nodes, ensuring gradual adoption.
Quantum-Assisted Machine Learning for Blockchain Optimization – AI models trained using quantum-enhanced datasets to optimize transaction routing, gas fee estimation, and validator selection.

Contributing to the NovaNet Wiki

This GitHub Wiki is maintained by the NovaNet community. Contributors can:

Suggest new terms or improvements by submitting pull requests.
Propose additional research topics related to quantum blockchain integration.
Help document technical implementations for developers and researchers.

For contributions, submit changes via GitHub Issues or Pull Requests.