Speaker
Description
Quantum computing has arisen as a transformative approach capable of addressing complex computational challenges beyond the reach of classical systems. In recent years, significant attention has turned to leveraging quantum algorithms across diverse domains, particularly High Energy Physics (HEP). This presentation offers a comprehensive survey of quantum machine learning techniques and their relevance to HEP investigations. We will outline the core concepts of quantum computation, such as superposition, entanglement, and quantum logic operations. Subsequently, we will examine specialised quantum algorithms, including quantum-enhanced support vector machines and otghers, emphasizing their prospective role in tackling demanding computational tasks in HEP research.
