Classical reinforcement learning (RL) and decision theory rely on Kolmogorovian probability spaces and independent utility metrics. These models fail to capture non-commutative cognitive framing, question order effects, and collective voter gridlocks observed in human surveys and Web3 decentralized autonomous organization (DAO) governance. Here we introduce a Quantum-Cognitive Reinforcement Learning (Q-AI) Policy Agent governed by Penrose Orchestrated Objective Reduction (Orch-OR) statevector collapse (tau = hbar / E_G) under Lindblad open-system thermal dephasing (T = 310 K). We validate our architecture against two empirical datasets:1. Human Survey Cognition: Achieving a 98% coefficient of determination (R² = 0.98) fitting Gallup national survey question order effects and 84% accuracy on the Linda conjunction fallacy.2. Web3 DAO Governance: Validating across 835,000 real Snapshot DAO votes (Uniswap, Arbitrum, Optimism, Gitcoin, Aave), achieving an 86.7% Mean Absolute Error reduction (1.3% MAE vs 9.8% classical linear models) and demonstrating that N-qubit GHZ statevector entanglement doubles public-good proposal consensus approval rates from 40% to 80%. Code, PyPI library (pip install q-ai-governance), and live visualizers are available at: https://github.com/JonathanReiser/quantum-orch-or
This paper explores the application of quantum error correction (QEC) codes to enhance the security and resilience of blockchain technology. Traditional blockchains are vulnerable to attacks that exploit vulnerabilities in their distributed ledger systems. The core challenge lies in the immutable nature of the blockchain, where a single compromised node can potentially disrupt the entire network. This research proposes leveraging the powerful error-correcting capabilities of QEC codes to safeguard blockchain data. Specifically, we examine the encoding and decoding processes using various QEC codes, focusing on their ability to detect and correct errors introduced by malicious actors. The integration of QEC codes into the blockchain architecture can significantly improve its tolerance to attacks, ensuring data integrity and maintaining the trust inherent in the blockchain system. We present a framework for implementing QEC within blockchain transactions and discuss the potential performance implications. The primary goal is to demonstrate that QEC codes offer a viable path towards a more robust and secure blockchain ecosystem.
This paper proposes a novel distributed consensus algorithm inspired by quantum mechanics, termed the Quantum-Inspired Distributed Consensus Algorithm with Measurement-Based Feedback (QIDCA-MBF). The core idea is to utilize the principles of quantum superposition to accelerate the convergence of distributed consensus in challenging network environments, particularly those prone to node failures. Unlike traditional consensus algorithms, QIDCA-MBF employs probabilistic representations of proposed values within each node, mimicking the concept of quantum superposition. A key innovation is the incorporation of measurement-based feedback, modeled after quantum measurement, to collapse these superpositions and guide the nodes towards a shared consensus value. This feedback mechanism dynamically adapts to the network topology and detects node failures, significantly enhancing the algorithm's robustness and convergence speed. The algorithm is formulated based on a modified averaging process, incorporating probabilistic weights derived from the superposition states. Simulation results demonstrate the effectiveness of QIDCA-MBF in achieving consensus rapidly and reliably, outperforming conventional distributed consensus protocols under various failure scenarios. The algorithm's adaptability and resilience make it a promising candidate for applications in decentralized systems, sensor networks, and blockchain technologies.
The paper provides an integrated literature review of recent scientific publications on quantum computing in finance and identifies promising directions for future research on the subject. The review covers seven thematic areas: portfolio optimization, derivative pricing and stochastic volatility, quantum machine learning for fraud detection and credit risk, insurance and actuarial science, mixed-frequency econometrics, fuzzy-quantum approaches for financial explainability, and security of cryptocurrencies. The paper compiles the essential quantum computational methods proposed in the literature, outlines their economic significance and the existing constraints for empirical testing and implementation, and discusses cross-cutting issues of explainability, trustworthy AI, robustness, and governance that arise across these application domains. Drawing on this review, the paper identifies five macro-gaps in the existing literature and proposes seven concrete directions for future research, grounded in European financial data and currently available quantum computing infrastructure. A special focus throughout is the increasingly available quantum infrastructure in Europe and the regulatory emphasis on trustworthy artificial intelligence, both of which create timely opportunities for future applications in financial modelling, risk management, and explainable financial AI.
Mohammad Reehan Nawaz, Mohammad Afaque, Anzer Hussain, Dr. Anand Prakash
The emergence of quantum computing poses a significant threat to classical cryptographic mechanisms such as RSA and Elliptic Curve Cryptography that are widely used to secure email communication. Traditional secure email systems rely on classical public-key infrastructure and therefore lack resilience against quantum attacks. This paper presents QuMail, a quantum-secure email client that integrates BB84-based Quantum Key Distribution (QKD) simulation, CRYSTALS-Kyber post-quantum cryptography (PQC), and blockchain-based audit logging within a unified architecture. The proposed system operates entirely at the application layer and remains compatible with existing email infrastructures using standard SMTP and IMAP protocols without requiring any server-side modification. A modular prototype was implemented using IBM Qiskit for quantum key generation and hybrid cryptographic techniques for secure message transmission. Experimental evaluation demonstrates an average latency of 120–180 ms for QKD key generation and 20–30 ms for Kyber-based encryption while maintaining minimal overhead for email transmission. The results demonstrate the feasibility of integrating quantum-resilient security mechanisms into existing email systems and highlight the potential of hybrid QKD–PQC architectures for next-generation secure communication platforms.