The field of quantum computing is rapidly advancing, with significant developments in optimization and security. Researchers are exploring new approaches to solve complex problems, such as the steelmaking continuous casting scheduling problem, using quantum learning-based methods. Additionally, there is a growing interest in applying quantum computing to real-world problems, including secure data access in cloud environments and satellite communications. Notably, quantum cryptography and noise-based approaches are being investigated for their potential to provide unconditional security. The integration of quantum computing with high-performance computing systems is also an active area of research, with promising results in distributed quantum approximate optimization algorithms. Overall, the field is moving towards more practical applications of quantum computing, with a focus on optimizing performance, security, and scalability. Noteworthy papers include: Secure Data Access in Cloud Environments Using Quantum Cryptography, which demonstrates the application of quantum key distribution and one-time pad for secure data encryption. GPU-Accelerated Distributed QAOA on Large-scale HPC Ecosystems, which achieves significant speedup in distributed quantum approximate optimization algorithm using GPU acceleration.