Quantum Lab | AI-Powered Web3 Quantitative Research Platform

Cutting-Edge Web3 Quantitative Research

Our published papers advance the frontier of decentralized finance and algorithmic trading

Graph Neural Network for Cross-DEX Arbitrage Detection

Novel GNN architecture identifies arbitrage opportunities across 15+ decentralized exchanges with 92.4% accuracy and sub-1-second latency.

Graph Neural Networks Smart Contract Analysis Latency Optimization

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Efficient Pump and Dump Detection on DEXs with Graph Neural Network

GNN-based framework for detecting pump-and-dump schemes on decentralized exchanges by analyzing on-chain transaction graphs in real-time.

Graph Neural Networks DEX EVM Simulation

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Core Technology Stack

Infrastructure built for high-performance Web3 quantitative research

Multi-Chain Node Infrastructure

Optimized full nodes and archive nodes for 15+ blockchains with sub-100ms latency for real-time data processing.

                        const node = new Web3NodeCluster({

                          chains: ['ethereum', 'arbitrum', 'solana'],

                          syncMode: 'fast'

                        });

AI Model Training Platform

Distributed training framework for deep learning models with PB-scale historical blockchain data and synthetic market scenarios.

                        from quantlab.models import ArbGNN

                        model = ArbGNN(

                          num_layers=3,

                          hidden_dim=256

                        )

                        train(model, dataset='dex_triangles')

Execution Simulator

High-fidelity EVM and SVM simulator with gas estimation and slippage modeling for strategy backtesting.

                        const simulator = new EVMSimulator({

                          block: 15867845,

                          strategies: ['arb', 'liquidations']

                        });

                        simulator.run();

Scientific Approach to Web3 Markets

Our research methodology combines rigorous academic standards with practical blockchain expertise

1

Data Collection & Processing

Construct comprehensive datasets from raw blockchain data including mempool transactions, DEX events, and oracle data.

2

Model Development

Design and train machine learning models targeting specific Web3 market inefficiencies.

3

Simulation & Backtesting

Test in high-fidelity environments with historical and synthetic market conditions.

4

Peer Review & Publication

Share findings with academic and industry communities to advance the field.

Research Performance Metrics

Model Accuracy

Arbitrage Detection 92.4%

Latency Benchmarks

0.3s

Opportunity Identification

1.2s

Full Cycle

Data Processing Volume

Daily Transactions 12.8M

Academic & Industry Collaborations

Partnering with leading institutions to advance Web3 quantitative research

W3F

Solana

EAA

IC3

AI-Powered Web3 Quantitative Research