Nhat Anh Nghiem Vu

Ph.D student, C.N.Yang Institute for Theoretical Physics

Department of Physics and Astronomy, Stony Brook University

Office: A-140 Physics Building

Email: nhatanh.nghiemvu@stonybrook.edu


"Happiness Is The Pursuit of Beauty "



About me 


I am currently a 3rd year Ph.D student at C.N.Yang Institute for Theoretical Physics. Before that I obtained B.S degree in Physics from Department of Physics & Astronomy,  Stony Brook University.  During my undergraduate time,  I worked as student researcher at Brookaven National Laboratory and Los Alamos National Laboratory.

I am very honored to receive supervision of Prof. Tzu-Chieh Wei since I was undergraduate student. Along the journey, I have been very fortunate to learn, either directly or indirectly,  from all people with fantastic minds.  Altogether, these experiences have fueled my passion for research, as well as shaped my career path in a very miraculous way. 

I am blessed with amazing friends, colleagues, and teachers in my life ! 

 

Research interest


My research is centered on the fascinating intersection of quantum computation and information theory. I am deeply intrigued by how the principles of quantum physics offer an entirely new paradigm for computing, enabling quantum computers to tackle complex computational challenges that pose significant hurdles for classical computers, including supercomputers.

While I have been dedicated to the field of quantum machine learning for some time, I have recently shifted my focus towards the development of quantum algorithms capable of addressing a diverse range of computational problems spanning topology, geometry, linear algebra, numerical methods, and more. Simultaneously, I am delving into the captivating connection between quantum computation and modern geometry, particularly in areas like differential geometry. This exploration reveals how geometric perspectives can shed light on various facets of quantum computation and information theory, such as quantum complexity and phenomena like black hole formation.

 A few concrete inquiries that are driving my research include: 

Some highlights/descriptions of my past/current researches could be find below. A list of my publications are available on Google Scholar 

Research news

Nonlinear science is fundamental, as nonlinear phenomenon occurs frequently, e.,g, chaos, but usually too hard to solve due to its nonlinear nature. We provide a quantum algorithm that solves nonlinear algebraic equation of arbitrary polynomial types in polylogarithmic time, meanwhile the problem is not practically tractable from a classical devices for  very high degree polynomials.  As some applications, our work suggests a new tool to deal with nonlinear differential equation, and potential usage in algebraic geometry, such as computing intersection of algebraic varieties.

In this work we leverage the block encodings method to dramatically improve two previously known quantum algorithms. What surprised us is that even with elementary operations  within the block encoding framework, highly efficient algorithm could be constructed, eliminating major components from previous methods. 

This is probably one of my most proud and fascinating work ! We use de Rham cohomology and Hodge theory to tackle a very difficult task in topological data analysis, which is estimating Betti numbers of a given triangulated manifold. While the problem has been established as an #P-hard in general case, where connectivity is not known priorly, in the tailored setting, our method is efficient and can be exponentially faster than previously proposed methods

This is one of my favorite work so far!  Unfolding underlying properties of blackbox oracle is one of the leading themes for demonstrating quantum advantage, and only a modest number of examples exist. In this work, we show that even with some oracle usages, an intrinsic topological property of a closed curve  on a triangulated manifold could be revealed, thus suggesting a fruitful domain, e.g, computational topology, might be a 'golden mineral' to invest quantum effort

Other work from my undergraduate research journey ! This project took part when I was a summer fellowship student at Los Alamos National Laboratory. We specifically show that the barren plateaus phenomena still can present and possess detrimental issues in training quantum machine learning model, which arise mainly from the loading of dataset. Our work suggested that the choice of data embedding scheme is a crucial step in training quantum learning model

> It was a great pleasure to work under Prof. Phillip Allen! In this work, I developed a Matlab code that simulate pulse propagation in 1-dimensional atom chain in multiple settings, including anharmonic effect and mass disorder. The numerical result failed to backup theoretical prediction

 > This work marked the beginning of my research journey when I was a third-year undergraduate student ! We introduced a general framework that provides a unified viewpoint for all quantum classifier models, which emphasizes the role of data embedding in quantum supervised learning.  In particular,  I had a chance to run some programs on real quantum hardware provided by IBM, which showed a surprisingly stellar performance in the presence of noise