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Computing Quantum Number in Quantum Computer

Vineet Kumar

Hi Qurious,

Good Day.

                   Welcome to the

                   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.

Read more

Hi Qurious,

Good Day.

                   Welcome to the

                   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.

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What's inside

Learning objectives

  • 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.
  • Show more
  • Show less

Syllabus

Jupyter Notebook.

Stereographic projection, Riemann sphere, Qubit state, Bloch sphere, Complex number to qubit state transformation (quantum number), Related python coding in Google colab etc.
Read more

Introduction.

Google Colab.

IBM Quantum Experience.

Qiskit

Stereographic projection.

Qubit state.

|qubit > = alpha |0> + beta |1>

Bloch sphere.

Riemann sphere.

2-Sphere

Quantum number formulation.

Coding-1.

Coding-2.

Python code GitHub link.

Real number to qubit state

Quantum function.

Quantum function examples.

Brief recall and practice test based on lectures 2.1.1 to 2.3.2

Brief recall.

Based on lectures 2.1.1 to 2.3.2

Unitary operations, Single-qubit gates, Qubit state based arithmetic operations, Related qiskit coding in Jupyter notebook etc.

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.

Quantum gates.

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.

Multiplication/ division using non-stereographic qubit state.

IBM Quantum Experience
Closing session and practice test based on lectures 4.1 to 4.3

Good bye and welcoming for new course.

Based on lectures 4.1 to 4.3

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Uses Google Colab, Jupyter Notebook, and IBM Q Experience, which are standard tools and platforms for quantum computing development and experimentation
Requires a high school level of mathematical knowledge, making it accessible to learners without advanced degrees or extensive formal training
Explores the underlying mathematical formulations behind quantum computing, which is essential for a deeper understanding of the field
Focuses on representing numbers using qubit states, which is a fundamental concept in quantum computing and quantum information processing
Covers the implementation of quantum gates, which are the building blocks of quantum circuits and essential for performing quantum computations
Employs Qiskit in Jupyter Notebook, which is a popular open-source quantum computing framework for writing quantum programs and experimenting with quantum algorithms

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computing Quantum Number in Quantum Computer with these activities:
Review Complex Numbers
Reinforce your understanding of complex numbers, which are fundamental to representing qubit states and quantum operations.
Browse courses on Complex Numbers
Show steps
  • Review the definition of complex numbers and their representation on the complex plane.
  • Practice arithmetic operations with complex numbers, including addition, subtraction, multiplication, and division.
  • Solve problems involving complex conjugates and modulus.
Brush up on Python coding
Improve your Python skills, as the course uses Python with Qiskit for quantum computing simulations.
Browse courses on Python
Show steps
  • Review basic Python syntax, data structures (lists, dictionaries), and control flow (loops, conditional statements).
  • Practice writing functions and working with modules.
  • Familiarize yourself with libraries commonly used in scientific computing, such as NumPy.
Read 'Quantum Computing: A Gentle Introduction'
Gain a broader understanding of quantum computing principles to better grasp the specific techniques taught in the course.
View Quantum Computing: A Gentle Introduction... on Amazon
Show steps
  • Read the chapters covering basic quantum mechanics and qubit representation.
  • Study the sections on quantum gates and quantum circuits.
  • Work through the examples and exercises provided in the book.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow Qiskit Tutorials
Learn how to use Qiskit, the quantum computing framework used in the course, through hands-on tutorials.
Show steps
  • Install Qiskit and set up your development environment.
  • Work through the official Qiskit tutorials on qubit manipulation and quantum gate implementation.
  • Experiment with building simple quantum circuits and running them on simulators.
Create a Blog Post on Stereographic Projection
Solidify your understanding of stereographic projection by explaining it in your own words and creating visuals.
Show steps
  • Research stereographic projection and its applications in mathematics and physics.
  • Write a blog post explaining the concept in a clear and concise manner, including diagrams and examples.
  • Publish the blog post on a platform like Medium or your personal website.
Implement Quantum Gates
Practice implementing quantum gates using Qiskit to reinforce your understanding of their mathematical representations.
Show steps
  • Choose a set of common quantum gates (e.g., Hadamard, Pauli-X, CNOT).
  • Write Qiskit code to implement each gate and verify its behavior on a single qubit or entangled qubits.
  • Test the gates by applying them to different qubit states and observing the resulting state vectors.
Build a Quantum Number Visualizer
Develop a tool to visualize the transformation of classical numbers into qubit states, enhancing your understanding of quantum number representation.
Show steps
  • Design a user interface that allows users to input classical numbers.
  • Implement the transformation algorithms to convert the input numbers into qubit states.
  • Visualize the resulting qubit states on a Bloch sphere using a library like Matplotlib.
  • Add features to display the quantum number representation and perform basic arithmetic operations.

Career center

Learners who complete Computing Quantum Number in Quantum Computer will develop knowledge and skills that may be useful to these careers:
Quantum Computing Scientist
A Quantum Computing Scientist explores the development and application of quantum technologies. This often involves designing quantum algorithms, implementing them on quantum hardware, and analyzing the results. The scientist works to translate theoretical concepts into tangible solutions, using tools like Google Colab, Jupyter Notebook, and IBM Q Experience. This course on computing quantum numbers in quantum computers helps to lay a foundation for understanding how numbers are represented and manipulated within quantum systems. The coding experience gained in the course, including the use of Qiskit, helps prepare one for the practical aspects of quantum algorithm development and implementation, which are vital for the quantum computing scientist. The scientist may benefit from this course by building upon their present understanding of quantum systems.
See salaries and explore the career path for Quantum Computing Scientist
Quantum Algorithm Developer
A Quantum Algorithm Developer focuses on creating new algorithms designed to run on quantum computers. It’s a role that requires a deep understanding of quantum mechanics and computer science. The work includes understanding how to leverage quantum phenomena like superposition and entanglement to solve problems more efficiently than classical computers. This course on computing quantum numbers in quantum computers directly relates to the representation and manipulation of data within quantum systems, which is crucial for algorithm design. Through the hands-on coding exercises using Google Colab, Jupyter Notebook, and IBM Q Experience, one can gain practical experience in implementing basic quantum operations and transformations. This experience may contribute to the more sophisticated tasks of quantum algorithm development, where optimized number representation is often essential.
See salaries and explore the career path for Quantum Algorithm Developer
Quantum Software Engineer
A Quantum Software Engineer designs, develops, and tests software for quantum computers. The role involves building tools and libraries that make quantum computers accessible to a wider range of users. This course on computing quantum numbers in quantum computers introduces the fundamental concepts of representing numbers as qubit states and manipulating them using quantum gates. By working through the coding exercises in Google Colab, Jupyter Notebook with Qiskit, and IBM Q Experience, one can gain practical experience in quantum programming. The course's focus on transforming ordinary numbers into quantum numbers and implementing arithmetic operations may be helpful for developing the software infrastructure required to handle the complex calculations performed by quantum computers. The engineer may find that this course helps them with quantum computer software.
See salaries and explore the career path for Quantum Software Engineer
Quantum Research Scientist
A Quantum Research Scientist conducts research to advance the field of quantum computing. This position often requires a strong theoretical background and the ability to design and conduct experiments. The topics covered in this course on computing quantum numbers in quantum computers, such as stereographic projection, Riemann sphere, and Bloch sphere representations, are useful for developing a deeper understanding of qubit states and transformations. The hands-on coding experience with Qiskit and IBM Q Experience may be helpful in implementing and testing new quantum algorithms and protocols. The scientist can translate abstract mathematical concepts into practical implementations. The course also may help build a foundation for conducting more advanced research in quantum information theory and quantum algorithm design, both of which are vital for the Quantum Research Scientist.
See salaries and explore the career path for Quantum Research Scientist
Quantum Data Scientist
A Quantum Data Scientist explores the application of quantum computing to data analysis and machine learning. Data Scientists work on developing quantum algorithms that enhance machine learning models or enable new types of data analysis. The exploration of qubit state representation and manipulation in this course on computing quantum numbers in quantum computers may be helpful for understanding how data can be encoded and processed in quantum systems. Gaining experience with Qiskit and IBM Q Experience, as offered in the course, helps one implement quantum machine learning algorithms and analyze their performance. By understanding how quantum gates can be used to perform arithmetic operations on qubit states, data scientists may find new ways to leverage quantum computing for data analysis tasks.
See salaries and explore the career path for Quantum Data Scientist
Quantum Educator
A Quantum Educator teaches quantum computing concepts to students and professionals. This involves creating educational materials, delivering lectures, and designing hands-on exercises. This course on computing quantum numbers in quantum computers may be useful for Quantum Educators who want to enhance their understanding of fundamental quantum concepts and develop practical coding skills. By working through the course materials, including the Google Colab, Jupyter Notebook, and IBM Q Experience exercises, they can gain experience in explaining complex topics such as stereographic projection, Riemann sphere, and Bloch sphere representations. Also, the educator can translate these concepts into practical coding examples. Quantum Educators may find this course helpful for enriching their teaching materials and providing students with hands-on experience in quantum computing.
See salaries and explore the career path for Quantum Educator
Computational Physicist
A Computational Physicist applies computational methods to solve complex problems in physics. This often involves developing simulations, analyzing data, and writing code to model physical systems. The principles taught in this course on computing quantum numbers in quantum computers, may be useful for simulating quantum systems and developing quantum algorithms for physics applications. The course's coverage of qubit states, Bloch sphere representation, and quantum gates may be helpful for building computational models of quantum phenomena. Furthermore the experience gained using Google Colab, Jupyter Notebook, and IBM Q Experience may be useful for implementing and testing computational physics models. The physicist may find this course useful in supplementing their skills in quantum systems analysis.
See salaries and explore the career path for Computational Physicist
Quantum Cryptographer
A Quantum Cryptographer develops secure communication protocols based on the principles of quantum mechanics. The role involves designing quantum key distribution systems, analyzing the security of quantum cryptographic protocols, and implementing quantum-resistant cryptographic algorithms. This course on computing quantum numbers in quantum computers may be helpful for understanding the fundamental concepts of qubit states and quantum gates, which form the basis of many quantum cryptographic protocols. The course's coverage of quantum number formulation and arithmetic operations on qubit states may be useful for designing quantum-resistant cryptographic algorithms. The crytographer may find this course helpful in enhancing their understanding of security.
See salaries and explore the career path for Quantum Cryptographer
Quantum Hardware Engineer
A Quantum Hardware Engineer designs and builds the physical components of quantum computers. This role involves working with superconducting circuits, trapped ions, or other physical systems used to create qubits. While this course on computing quantum numbers in quantum computers focuses on the software and algorithmic aspects of quantum computing, it may still be useful for hardware engineers who want to gain a better understanding of how qubits are represented and manipulated. The course's coverage of qubit states, Bloch sphere representation, and quantum gates can provide valuable insights into the requirements and limitations of quantum hardware. The insights from this course may help the engineer see things from a different perspective.
See salaries and explore the career path for Quantum Hardware Engineer
Research Engineer
A Research Engineer supports research by designing and developing equipment. They also analyze data, and conduct experiments. This course on computing quantum numbers in quantum computers introduces the underlying mathematical formulations and codes them in quantum computer. The course may provide a foundation for understanding the principles behind quantum computing and the tools used in the field. The engineer may use this course to increase their understanding, benefiting their contribution to the scientific process.
See salaries and explore the career path for Research Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and implements machine learning algorithms and systems. The concepts in this course on computing quantum numbers in quantum computers may be useful for exploring the intersection of quantum computing and machine learning. The course provides experience with quantum computing tools and the fundamental concepts of qubit states and quantum gates. The engineer's understanding of quantum computing concepts may be enhanced, leading to creative solutions.
See salaries and explore the career path for Machine Learning Engineer
Software Developer
A Software Developer might find the quantum number concepts explored in this course on computing quantum numbers in quantum computers to be conceptually interesting. This course helps learn the fundamentals of quantum computing, including representing numbers as qubit states and manipulating them using quantum gates. The developer can leverage this knowledge to improve their programming skill set.
See salaries and explore the career path for Software Developer
Data Analyst
A Data Analyst benefits from being exposed to a wide variety of computational methods. This course on computing quantum numbers in quantum computers introduces data analysis, manipulation, and representation within the context of quantum computing. Although the analyst might not use quantum computing directly, they may be able to translate principles to improve their analysis.
See salaries and explore the career path for Data Analyst
Systems Engineer
The job of Systems Engineer involves the integration and management of complex systems. This course on computing quantum numbers in quantum computers focuses on quantum computing systems. While the Systems Engineer may not use quantum computing directly, they may have a foundation for engaging with and integrating quantum technologies in complex systems.
See salaries and explore the career path for Systems Engineer
Technical Consultant
A Technical Consultant draws upon a broad knowledge of technology in order to best advise stakeholders. This course on computing quantum numbers in quantum computers focuses on quantum computing systems and operations, exposing the consultant with a new technology. This course may expand the consultant's set of technological knowledge, helping them to become a better consultant.
See salaries and explore the career path for Technical Consultant

Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Computing Quantum Number in Quantum Computer.
Cover image
Quantum Computing
Save
Provides a comprehensive introduction to the core concepts of quantum computing. It covers the mathematical foundations and quantum algorithms in a clear and accessible manner. It is particularly useful for understanding the underlying principles behind quantum number computation. This book is often used as a textbook in introductory quantum computing courses.
Quantum Computing: A Gentle Introduction...
Kindle Edition
$$

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Instructor
Vineet Kumar
Language
English
Good to know
Uses Google Colab, Jupyter Notebook, and IBM Q Experience, which are standard tools and platforms for quantum computing development and experimentation
Requires a high school level of mathematical knowledge, making it accessible to learners without advanced degrees or extensive formal training
Explores the underlying mathematical formulations behind quantum computing, which is essential for a deeper understanding of the field
Focuses on representing numbers using qubit states, which is a fundamental concept in quantum computing and quantum information processing
Covers the implementation of quantum gates, which are the building blocks of quantum circuits and essential for performing quantum computations
Employs Qiskit in Jupyter Notebook, which is a popular open-source quantum computing framework for writing quantum programs and experimenting with quantum algorithms
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