Lagrangians to Lasers

Note: This session features brief, insightful talks of 25 mins each from early-stage BS-MS students, showcasing their summer projects. [Read More]

Machine learning is a powerful tool for analyzing complex datasets, but its application to quantum systems presents unique challenges. Kernels, which measure the similarity between data points, are a key component of many machine learning algorithms. Quantum kernels offer the... [Read More]

“Two physically different states of a classical system are in principle distinguishable. But that is not always true for quantum mechanical systems. I will discuss why is it not possible to distinguish states of a quantum system which are non-orthogonal,... [Read More]

Note: This session features brief, insightful talks of 15 mins each from early-stage BS-MS students, showcasing their summer projects. It’s an opportunity to gain entry level understanding of various sub-fields of physics from your peer. [Read More]

Over the last decade, machine learning techniques have been widely adopted by various domains in particle physics. I will discuss using such ML algorithms and simulations in particle physics analysis and the challenges they present. Then, I will introduce a... [Read More]