MAIB-Class-016: Foundation of Quantum Mechanism

[Tlexander]

https://www.linkedin.com/events/maib-cl ... 703313408/

Title: Foundation of Quantum Mechanism

Background

Quantum computing is a rapidly accelerating field with the power to revolutionize artificial intelligence (AI) and machine learning (ML). Rooted in parallelization and able to manage far more complex algorithms, quantum computers will be the key to unlocking the next generation of AI and ML models. Quantum computing grows very quickly. It is reported that IBM has over 20 quantum systems available on the cloud from their Poughkeepsie and Yorktown locations. In 2024, IBM will add a new cloud data center with 100+ qubit quantum systems in Ehningen, Germany. Quantum computing can significantly accelerate the drug discovery process. Its computational power allows for complex molecular simulations, predicting drug-target interactions, understanding mechanisms of action, and designing more effective drugs. In summary, quantum computing will redefine the drug discovery. The first lecture discuss the basics of quantum computing, how it differs from classical computing, and its potential applications in addressing current challenges.

Bio

Dr. Jun Qi is now a Research Assistant Professor in the Department of Computer Science at Hong Kong Baptist University. Previously, he received a Ph.D. from the School of Electrical and Computer Engineering at Georgia Institute of Technology, advised by Prof. Chin-Hui Lee and Prof. Xiaoli Ma for the Speech, Language, and Signal Processing research. His current study focuses on (1) Quantum Machine Learning Theory, which investigates the interplay of trainability, generalization, and expressive power in quantum machine learning models as we explore paths to practical quantum advantage in Artificial Intelligence; (2) Quantum Optimization Algorithms, which involve the development of quantum-aware optimization techniques tailored for quantum neural networks and the design of quantum approximate algorithms addressing combinatorial optimization problems; (3) Speech Signal and Natural Language Processing, which employs efficient deep learning computing techniques that enable speech and language processing on resource-constrained devices.

Reference

https://sites.google.com/site/uwjunqi/home

[Tlexander]

量子力学与量子计算有着密切的关系。

量子力学是研究物质在微观尺度上的性质和规律的理论基础。它揭示了微观物体(如电子、原子等)存在波粒二象性,以及测量时存在不确定性等量子效应。这些量子效应为量子计算的发展奠定了理论基础。

量子计算利用了量子态的叠加和纠缠等量子效应,实现了比经典计算更强大的计算能力。量子位(qubit)可以代表0和1的叠加态,多个qubit可以形成高度纠缠的量子态。这使得量子计算机可以并行处理大量信息,实现指数级的加速。许多量子算法如量子霍尔算法、量子傅里叶变换等都利用了这一优势。

综上所述,量子力学揭示的量子效应为量子计算的可能性提供了理论依据。量子计算机的功能依赖于这些量子效应的利用。可以说,没有量子力学就没有量子计算。量子力学奠定了量子计算的理论基础,两者有着密不可分的内在联系。