Quantum Information Science is a very exciting field that combines physics (Quantum Mechanics, Cryogenics, and Condensed Matter Physics), computer science, electrical engineering, and math.
Quantum computing gives us access to the Hilbert space, which is different from the classical bits of 0/1 discrete space, and has the potential to make computers exponentially more powerful.
I got interested in this field when I first learned about the limitations of classical computing: when our current chip technology reaches the limit, we can't go any further.
But with Quantum Information Science, we could solve many problems that classical computers would never be able to do, and I'm currently learning about it.
I'm very excited to see what I can do in this field in the future.
We are facing many difficulties at the current research stage for quantum computing.
Quantum states are fragile and can be easily disrupted and lose coherence due to the external environment.
One of the biggest changes is storing a quantum state for a long time and manipulating it.
So we need to have error correction methods to overcome this problem and create logical qubits that could detect errors that come from external noise.
So far, I have done a course project in surface code and learned about how it uses stabilizer measurement to detect errors and the pros and cons of this technology.
My lab work with Prof. Krastanov was to develop a GPU-accelerated open-source package that's used to simulate Clifford circuits.
Quantum simulation is one of the major uses of quantum computation. It's the process of using the quantum computation system to study another quantum system, and we can use this technology to study high energy physics, many body physics, and condensed matter physics. Due to the limitations of computation power in classical computers, it could be hard to simulate the behavior of a large quantum system. Instead, we can use quantum simulation as a more efficient way to investigate other quantum systems.