
Introduction.
Google Colab.
Jupyter Notebook.
IBM Quantum Experience.
Stereographic projection.
Qubit state.
|qubit > = alpha |0> + beta |1>
Bloch sphere.
Riemann sphere.
Quantum number formulation.
Coding-1.
Coding-2.
Python code GitHub link.
Python code GitHub link.
Quantum function.
Quantum function examples.
Brief recall.
Unitary operations.
U(theta, phi, lambda) = U(x, y, lambda) for input complex Z(x ,y) = x + i*y.
Quantum gates.
Coding-3.
Qiskit code in Jupyter Notebook GitHub link.
Arithmetic operations based on 'stereographic based developed qubit state'.
(Stereographic Qubit State)
Introduction of non-stereographic based qubit state. (Non-Stereographic Qubit State)
Addition/ subtraction using non-stereographic qubit state.
Qiskit code in Jupyter Notebook GitHub link.
Multiplication/ division using non-stereographic qubit state.
Qiskit code in Jupyter Notebook GitHub link.
Good bye and welcoming for new course.
Hi Qurious,
Good Day.
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.
MATERIALS
This course apart of video lectures contain several notes. The GitHub links are also provided. Additionally the installation kit is there.