# Hybrid Quantum-Classical Deep Neural Networks Based Smart Contract Vulnerability Detection
## 1 Introduction  
Blockchain technology has established itself as a revolutionary development in recent years, bringing about new paradigms in transaction processing and data management [1]. Among its most impactful innovations is the Ethereum blockchain network--a decentralized platform that extends blockchain capabilities beyond mere transactional operations by assisting in the creation of smart contracts and decentralized apps (DApps) [2]. Recognized as Blockchain 2.0, Ethereum pioneered support for smart contracts with Turing-complete capabilities, establishing itself as the earliest and most extensively adopted platform for this feature [3]. Its design, which enables complex computations and programmable agreements, has solidified Ethereum as a cornerstone in the evolution of blockchain technologies [4]. While Bitcoin focuses on secure and decentralized value transfers, the Ethereum Virtual Machine (EVM) allows developers to create DApps and automated, reliable digital contracts [5]. Additionally, Ethereum's gas mechanism determines the computational costsof smart contracts, ensuring the network operates securely and efficiently [6]. As a result, Ethereum has evolved beyond a simple payment system into a foundational infrastructure for large-scale applications across various industries. The Ethereum Virtual Machine (EVM) serves as the execution environment that enables smart contract processing within the Ethereum blockchain, ensuring deterministic and decentralized computation [5]. While the blockchain functions as a secure and immutable ledger that records transactions, the EVM facilitates the execution of complex programmable logic, allowing for trustless automation through smart contracts [7]. Smart contracts, typically written in Solidity, are compiled into bytecode and executed on the EVM, with each Ethereum node replicating the computations to maintain network consensus [8]. The EVM allows developers to launch applications that execute precisely as intended, ensuring they operate without downtime, censorship, fraud, or interference from third parties [5]. It compiles code into bytecode executable on the blockchain, guaranteeing that every node across the network arrives at the same outcome for computation results [6]. This virtual machine serves as a cornerstone for preserving the Ethereum network's integrity and functionality, offering a robust platform for smart contract execution [7,8]. Smart contracts function as self-enforcing digital agreements, with their conditions seamlessly woven into the code, running on decentralized blockchain networks like Ethereum [9]. These contracts automatically enforce agreements without intermediaries, promising enhanced efficiency and reduced costs across various industries [6]. Because blockchain technology is unchangeable, after a smart contract is put into place, it remains unchangeable and transactions are final, ensuring transparency and trustworthiness. That is, once smart contracts are placed on the blockchain, they are immutable, meaning that their code cannot be changed or removed [10]. However, this immutability also implies that any vulnerabilities in the smart contract code remain permanent, posing significant security risks [10,11]. The rise of smart contracts has been accompanied by considerable security challenges, especially throughout the Ethereum ecosystem. Flaws in smart contract code have facilitated high-profile exploits, causing significant monetary losses and eroding trust in blockchain systems. The complexity of the EVM and the novelty of smart contract programming introduce risks that traditional software development practices may not fully address. For instance, the notorious Decentralized Autonomous Organization (DAO) breach in 2016 leveraged a reentrancy vulnerability, culminating in the theft of around 3.6 million Ether [11,12].