How Small Can We Go? 

What are we really made of, and why are we made of it? Particle physics studies the fundamental building blocks that made up the world around us. I aim at understanding the fundamental particles and fields in our Universe. While the Standard Model (SM) gave us a successful description of most of the common phenomena around us, it is not enough. There are so many things that are beyond our reach: the muon magnetic Anomaly, Dark Matter, neutrino oscillation, etc. They are waiting for me to explore! I am specifically interested in Higgs Boson and Beyond SM Physics such as Dark Matter and Neutrino Oscillations. 

I am especially attracted to the simulation works and detector developments. I focused extensively on probability theory and statistic models when I was in high school. I enjoy applying them to simulations and seeing how things were simulated vividly in my code. Additionally, particle detectors are fascinating. Particle physics detectors are always an intricate assembly of trackers, calorimeters, targets, or other components. I love to see how all these components come together and work collectively to form and make a discovery or measurement.

(Picture From CERN) 

How much can we learn from a set?

With large computing power and data storage, we entered a period where data has been more prevalent and informative than ever. We can now try to understand deeper patterns hidden under the dataset than what is perceivable by the human eye. Machine learning offers us a unique perspective on probing patterns. While its immense power was shown, we still have a limited understanding of how it makes successful predictions. The meaning behind many successful learning models remains unknown. A story of my own: 4 years ago, I constructed a convolution neural network that sorts wastes effectively with over 90% of efficiency. Yet we have no idea why our neural networks. It just magically puts things in the right category with all its matrices and layers that we seldom understand. I don't like it. I believe that we need to develop effective methods to understand how these AI classify things, and what pattern they follow. The implications behind these patterns could give us the opportunity to understand many things in a different, maybe more efficient way, that we never thought of. 

Nonetheless, despite our lack of understanding, I have to admit machine learning's strength in assisting us. Its application in high energy physics and many other things has made our life much easier. I enjoy using it as a great assistance to improve my work. Especially in particle physics, I like applying different learning algorithms and understanding why one is better than the other. 

(Picture from HD Wall Paper)

Where did the Universe come from, 

and where would it go?

Particles that we are familiar with, such as protons or electrons, only occupy 5% of our universe. A large percentage of the Universe is occupied by Dark Matter, a kind of matter that interacts very differently from our ordinary matter. In fact, they almost never interact with us, aside from their evident gravitation pull, which was observed in many different ways by astrophysicists. Dark Matter is essential in understanding the evolution of the Universe. The interaction of stars and galaxies with Dark Matter is believed to be the creator of the present-day galaxies. Yet, the particle nature of Dark Matter remains unknown. Its existence as a particle is not predicted by the standard model and might answer many unsolved particle physics questions. Thus, probing dark matter is not only essential to our understanding of the Universe but also a key step in exploring what is beyond our current stand model predictions. I believe that the discovery of Dark Matter is necessary yet difficult. Its mysterious but important nature triggers my passion and curiosity, compelling me to explore this unknown territory. 

(Picture from LiveScience)

Can we really reach "clean energy"?

Since I was young, I was told of nightmares of how human development is going "drain the resources of Earth". Admittedly that as the population grows, we inevitably need more resources and energy. A high-efficiency energy source is necessary to support the growing population. I believe that it lies in plasma science. Although it might be in the distant future, to make the technology safe enough for commercial use, its potential excites me. Although I was never involved in any plasma physics experiment, I am very interested in many hot experiments of it, such as the controlled nuclear fusion at Lawrence Livermore National Laboratory, and other controlled fusion experiments.

(Picture from PPPL)