Computing Quantum Number in Quantum Computer
What you'll learn
- Python in Google Colab, Qiskit in Jupyter Notebook and IBM Q Experience.
- Stereographic projection between '2-D point (x, y)' & '3-D point (u, v, w)' and Riemann sphere.
- Development of a qubit state: |qubit> in term of the input complex number Z(x, y) = x+iy, i.e. |qubit(x, y)>. And, representation on Bloch sphere.
- Development of a qubit state as function over input function f(x, y), i.e. dancing qubit.
- Coding for the encoded qubit state |qubit(x, y)> in Google Colab, i.e. for the complex encoded stereographic based qubit state.
- Coding for state preparation and quantum gates using qiskit in Jupyter Notebook.
- Development of arithmetic operations using stereographic qubit state.
- Development of 'non-stereographic qubit state' for input number.
- Development of arithmetic operations using non-stereographic qubit state.
- Coding for non-stereographic qubit state with qiskit in Jupyter Notebook.
- Coding for arithmetic operations using non-stereographic qubit state with qiskit in Jupyter Notebook.
- Coding of quantum gates in IBM Q Experience.
- High school mathematical knowledge.
- Beginner in python.
Welcome to the PROJECT BASED course on Computing Quantum Number in Quantum Computer!
To count, measure etc in our day to day life, we need, certain object. Number is that object. When the matter comes to print the number in conventional computing machine, we can do so in very simplified way by command: Num = 0; print('Number=', Num). But, when it is about to print it in quantum machine that means by using quantum gates we have to do it by other ways. One of the way to represent a number is by state of qubit which means the transformation of ordinary number to let say quantum number.
In this R&D based project course we will start from scratch and understand the underlying mathematical formulations and code them in quantum computer. We will use Google Colab, Jupyter Notebook and IBM Q Experience. In Google Colab, we will compute the transformation without using gates. In Jupyter notebook, we will compute the same using unitary gates, whereas in IBM Q Experience we will see the implementation of gates in brief.
If you have high school level of mathematical knowledge, you can take this course.
This course apart of video lectures contain several notes. The GitHub links are also provided. Additionally the installation kit is there.
Who this course is for:
- Interested in Quantum Computing.
My name is Vineet Kumar and doing PhD in ultracold plasma. I am also working as an educator. As an instructor I have more than 5 years of experience in Govt. University as Assist. Professor and as others in the Dept. of Electrical Engineering. Along with academics I have an industrial exposure in the domain of quantum engineering and technology as well on the project entitled 'development of quantum random number generator (QRNG)' experimentally. Theoretically in my master's I worked on the generation of spin squeezed state adiabatically in Python. Additionally, I involved in the different R & D projects as well. Total I have more than 8 years of experience.