MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 514.99 MB | Duration: 1h 12m
Quantum Computing with Python-Qiskit; Project on 'Qubit State Encode-Decode for Complex Number' & Arithmetic Operations.
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.
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.
Section 1: Installations, Quantum Number, Quantum Function & Python Coding in Google Colab
Lecture 1 Lecture-1.1
Lecture 2 Lecture-1.2.1
Lecture 3 Lecture-1.2.2
Lecture 4 Lecture-1.2.3
Lecture 5 Lecture-2.1.1
Lecture 6 Lecture-2.1.2
Lecture 7 Lecture-2.1.3
Lecture 8 Lecture-2.1.4
Lecture 9 Lecture-2.2
Lecture 10 Lecture-2.3.1
Lecture 11 Lecture-2.3.2
Lecture 12 Complex_Number -> Qubit_State-GitHub_Link
Lecture 13 Bloch_Sphere-GitHub_Link
Lecture 14 Lecture-3.1
Lecture 15 Lecture-3.2
Section 2: Intermediate Note & Test-1
Lecture 16 Intermediate Note
Section 3: Quantum Gates, Qubit based Arithmetic Operations & Qiskit Coding in Jupyter Note
Lecture 17 Lecture-4.1
Lecture 18 Lecture-4.2
Lecture 19 Lecture-4.3
Lecture 20 Quantum Gates (Single-qubit)-GitHub_Link
Lecture 21 Lecture-5.1
Lecture 22 Lecture-5.2
Lecture 23 Non-Stereographic_Qubit-State[Addition] Code-GitHub Link.
Lecture 24 Lecture-5.3
Lecture 25 Non-Stereographic_Qubit-State[Multiplication] Code-GitHub Link.
Lecture 26 IBM Quantum Experience
Section 4: Closing Note & Test-2
Lecture 27 Closing Note
Interested in Quantum Computing.
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