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With this GitHub repository, delving into the core concepts of Quantum Computing, from superposition to qubits. Explore quantum algorithms like Quantum Fourier Transform and Amplitude Amplification, while leveraging Microsoft Q# for practical quantum programming. Uncover the intricacies of complex numbers and linear algebra in the quantum realm.

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Quantum Computing Explained

Overview

Welcome to the Quantum Computing Explained repository! This comprehensive guide introduces key concepts, characteristics, and applications of quantum computing. Explore from basic principles to advanced quantum algorithms and programming using Microsoft Q#.

Table of Contents

  1. Quantum Computing Basics
  • Definition
  • Applications
  1. Characteristics of a Computational System
  • Superposition
  • Entanglement
  • Interference
  1. Complex Numbers in Quantum Computing
  • Importance and Usage
  • Properties
  1. Linear Algebra in Quantum Computing
  • Linear Combination
  • Linear Dependence
  • Linear Independence
  • Span and Basis
  • Matrix
  • Projection
  1. Introduction to Qubits
  • Qubit Creation
  • Utility of Qubits
  • Building a Qubit
  • Basic Math Behind Qubits
  1. Quantum Computing Algorithms
  • Quantum Fourier Transform
  • Amplitude Amplification
  • Quantum Walk
  • Microsoft Q#

Quantum Computing Basics

Definition of Quantum Computing

  • Quantum computers are controllable quantum mechanical devices that exploit the properties of quantum physics to perform computations. For some computational tasks, quantum computing provides exponential speedups.

  • Qubits (quantum bits) are the fundamental object of information in quantum computing.

  • Quantum computing leverages the principles of superposition, entanglement, and interference to process information in ways classical computers cannot.

Why use Quantum Computing?

  • Quantum theory can be interpreted as saying that matter, at a quantum level, is in a multitude of possible configurations (known as states).

  • These many configurations of the quantum state, may interfere with each other, and this interference prevents the use of statistical sampling to obtain the quantum state configurations.

  • The foundational core of quantum computing to store Information in quantum states of matter and to use quantum gate operations to compute on that information. by harnessing and learning to 'program' quantum interference.

  • Quantum computers harness the unique behavior of quantum physics—such as superposition, entanglement, and quantum interference—and apply it to computing. This introduces new concepts to traditional programming methods.

  • With Azure Quantum, you can make use of the advantages of quantum computing today, in a full-stack open cloud ecosystem with access to software, hardware, and pre-built solutions. Azure Quantum offers two types of solutions: quantum computing and optimization.

Applications of Quantum Computing

Unlock the potential of quantum computing in cryptography, artificial intelligence, finance, and particle physics.

Characteristics of a Computational System

  1. Superposition

Definition: Existence of one element in many states or places simultaneously.

Example: A basic water molecule exhibiting superposition.

  1. Entanglement

Definition: Quantum mechanical phenomenon where the states of two or more objects are interconnected.

Example: Two spinning electrons demonstrating entanglement.

  1. Interference

Definition: Control the probability of a qubit system collapsing into measurement states.

Example:

Complex Numbers

Importance and Usage

Explore the role of complex numbers in quantum computing and understand why they are crucial for quantum operations.

Properties of Complex Numbers

  1. Commutative
  2. Associative
  3. Distributive

Linear Algebra

  1. Linear Combination

Definition: Combination of vectors through scalar multiplication and addition.

Example:

  1. Linear Dependence

Definition: Vectors are linearly dependent if one vector can be expressed as a combination of others.

Example:

  1. Linear Independence

Definition: Vectors are linearly independent if no vector can be expressed as a combination of others.

Example:

  1. Span and Basis

Explore the concepts of span and basis in linear algebra and understand their significance.

  1. Matrix

Definition: Mathematical representation used in various real-life applications. Mainly we are used two kind of matricies.

- Unitary Matricies: U^t * U = I, inverse of U is U^T means when acting on a vector, unitary matricies rotate/flip the vector, keeping the magnitude of the vector the same
- Hermitian Matricies: H = H^t
  • Eigenvectors and Eigenvalues:

    image image

Where matrices are used:

  1. Projection

Definition: The process of projecting a vector onto a subspace.

Real-life applications:

Introduction to Qubits

  • Classical Computers use 0's and 1's bits in different times. In Quantum Computers also follow same scenerio but it can be use 0 and 1 at the samw time.

  • The fundamental difference between Classical Computers and Quantum Computers is that programs in Quantum Computers are intrinsically probabilistic, whereas Classical Computers are usually deterministic.

Qubit Creation
  • Physically, a qubit can be amde from any quantum particle that has 2 distinct states. A Qubit is in a Superposition, if it is both 0 and 1 at same time.
Utility of Qubits

Learn how qubits enhance computational power in quantum computing compared to classical bits.

Building a Qubit at Home

Delve into the possibility and challenges of building a qubit at home.

Basic Math Behind Qubits

Understand the mathematical concepts behind qubits, including working with multiple qubits and their various states.

Quantum Computing Algorithms

  1. Quantum Fourier Transform Algorithms

Definition: Linear transformation on qubits, analogous to the inverse discrete Fourier transform.

Associated algorithms: Shor's and Simon's algorithms.

  1. Amplitude Amplification Algorithms

Definition: Generalization of Grover's search algorithm, applicable to counting and probability tasks.

Algorithms: Grover's and quantum counting algorithms.

  1. Quantum Walk Algorithms

Definition: Quantum version of the classic random walk, formulated in continuous and discrete time.

Problem: Element distinctness problem.

Microsoft Q#

Explore Microsoft Q#, an open-source programming language designed for developing and running quantum algorithms. It is part of the Quantum Development Kit, allowing you to create quantum programs and simulations.

Feel free to customize and expand upon this template to suit the specific content and structure of your GitHub repository.

About

With this GitHub repository, delving into the core concepts of Quantum Computing, from superposition to qubits. Explore quantum algorithms like Quantum Fourier Transform and Amplitude Amplification, while leveraging Microsoft Q# for practical quantum programming. Uncover the intricacies of complex numbers and linear algebra in the quantum realm.

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