Quantum-Computing
  • Welcome to Quantum-Computing
    • Start with Pennylane
  • The Project
    • Team
    • Discord
    • actual tasks
    • Termine
    • Trello-Planung
  • FAQ
  • Which tools do you use ?
    • Jupyter
    • Ubuntu
    • Visual Studio Code
    • Python virtual Env & Jupyter
      • Update Python Version
      • How to install virtuel Env on Ubuntu
        • Python with PipENV
        • Python with Venv
        • Uninstall Python Version
        • Using Jupyter with virtual Env
    • GitKraken
    • @Python
      • pyGIMLi
      • Qutip
      • scikit-learn
      • seaborn
    • Practical Tool - Circuit Builder
  • Self-study-Guide
    • Pennylane.ai
      • Tutorials
        • Getting Started
          • Basic tutorial: qubit rotation
    • Clean Code
    • Statistik
    • Komplexitätstheorie
      • Quantum Complexity
    • Logik
    • Physik
      • Visuelle Physik
      • Einstieg Quanten-Mechanik
      • Math behind
    • Stochastic & statistic
      • PCA
    • Mathe
      • Geometry
        • Page 1
        • Lie groups & continuous symmetries
        • Euclidean and non-Euclidean geometry
      • numeric linear algebra for Coders
      • Graphen-Theorie
      • Einsteins Summenkonventiom
      • EigenValues
      • Hilbert-Raum
        • Operatoren im Hilbertraum
      • Vector Calculus
      • Basics:
        • Calculus
          • Matrix Calculus
          • Derivative
          • Integral
        • Algebra ( precalculus )
      • Einfach:
        • Vektoren
      • Mittel:
      • Schwer:
      • Symbolbeschreibung
      • Tensor Produkt
      • Inners Produkt vs Kreuzprodukt
      • Vektorprodukt bzw. Kreuzprodukt
      • "inner product" - Skalarprodukt
      • Lineare Algebra
      • Notationen
      • Hilbert-Raum
      • Komplexe Zahlen
      • Die Matrix
      • Tensoren
      • Funktionen n-Ordnung
      • Integralrechnung
      • Rechnen im Kreis
      • Differentia(operator
    • DataScience
      • Practical Deep Learning for Coders
      • Computational Linear Algebra for Coders
      • Maschinen-Theorie
      • Algorithmen & Datenstrukturen
      • ClassicalMachineLearning
        • Supervised Learning
          • Regression
          • Lineare Modelle
          • Lineare und Quadratische Discriminanten Analyse
          • Support Vector Machines
          • Stochastik Gradient Descent
          • Nearest Nighbors
          • DecissionTrees
            • RegressionTree
            • Classification Tree
        • Unsupervised Learning
          • Gaussian Mixture Models
          • Neural Network Models ( unsupervised )
          • Clustering
      • Python
      • Minimal-Cost
      • Tree-Algorithms
      • Complexity
      • Multi-Out Problems
      • Classification
      • Regression
    • offtopic
      • Neuronale Netze
      • LibreOffice Math
        • Symbole
    • Griechisch für Anfänger
  • Course
    • Quantum Capstone
    • Lecture
      • Kapitel 2
      • Kapitel 3
      • Kapitel 4
        • Rechnen mit Zuständen
          • Hilbert-Raum
          • selbstadjunktierter Operator mit Spur N
          • unitärer Operator
      • Kapitel 5
      • DSE meets Quantum
      • Kapitel 1 - Welcome and cold start
    • Coding-Part
      • Kapitel 1
        • Installation der Arbeitsumgebung
          • Install Anaconda
          • Spyder Installation und Start
          • Umgang mit Conda im Terminal
        • Clean Template
      • Kapitel 2
        • First steps /w Python
        • Hello Qiskit
        • Hello Pennylane
      • Kapitel 3
      • Quantum-Gates
      • First own steps
      • Kapitel 6 - Quantum-Code
      • Kapitel 7
      • Kapitel 8
      • Kapitel 9
      • Kapitel 10
      • Special:
        • Saturday II
        • Saturday I
    • Axiome der Quanten-Mechanik
    • Course Kick-Off
  • Literature list
    • Deep Learning
  • Quantum Machine Learning
    • Quantum Projects
      • The Quantum Graph Recurrent Neural Network
      • Quantum circuit structure learning
      • Training and evaluating quantum kernels
      • Kernel-based training of quantum models with scikit-learne 2
      • Qubit_Rotation
      • Variational Quantum Linear Solver
      • Variational classifier
      • Understanding the Haar Measure
        • Unitary Designs
      • Lineare Regression @QML
      • Quantum-Simulation @Kubernetes with QuEST
      • Documentation
    • Reinforcement Learning
      • Konfidenzinterval [ ger. ]
      • Multi Arm Bandits
      • Markov Decision Processes
        • stochastic vs deterministic
        • path dependency
        • Value Function
        • markov probability
        • Bellman equation
        • Hamilton–Jacobi–Bellman (HJB) equation
    • Classification
    • Code Example:
    • Optimizer
    • Regression
  • Research Papers & More
    • Variational quantum Algorithms
    • Quantum Natural Gradient Descent
    • Boolsche Logik
    • Quantum-Logik
    • Bra-Ket
    • Quantum-Mathe
    • Quanten-Mechanik
      • Entanglement
      • Mathematische Grundlagen:
      • Quanten-Theorie
      • Born'sche Wahrscheinlichkeitsinterpretation
      • Quantenmechanische Gleichungen
      • Wellen-Gleichung
      • Wellen-Funktion
      • "The fundamental idea of wave mechanics " Schrödinger
      • Spin
    • Visualisation
    • Quantum-Informatik
      • Gradient Descent
      • UCSM Unit cycle state machine
    • Quanten-Physik
    • Collection[unsorted]
    • Quantum-Hardware
      • Hardware Vergleich
      • Quantum Trapping
    • Spin 1/2 (Fermion)
    • offtopic
    • Physik
      • Ising Model
      • Feynman Lectures
    • Komplexitätstheorie
      • Graph isomorphism problem
      • Quantum Komplexität
    • Quantum-Simulation
      • Hamiltonian simulation
      • QiBo -Simulation
    • Machine Learing
    • Reading Guide:
  • Coders Help
    • Pyhton
    • Anaconda
    • komplexe Zahlen
    • Numpy
    • Jupyter-Notebook
    • Logik
    • Terminal[Linux]
      • Mint
    • Collection-Folder
    • Additional TOOLs:
    • Code Book Quantum
    • Pennylane
  • Documentation-Guide
    • Jupyter Notebook
    • Qiskit
    • Python
      • NetworkX
      • MatPlotLib
    • Anaconda
    • Pennylane
    • Pennylane
    • Quantum-Gates
      • Controlled Z (CZ) Gate
      • Swap Gate
      • Phase ( S,P) Gate
      • Pauli Y Gate
      • Pauli X Gate
      • Hadamard ( H ) Gate
      • Toffoli double controlled-Not CCX Gate
      • Pauli Z Gate
      • CNOT ( CX )Gate
      • density matrix
  • Quantum-Hommage
    • ecosystem Quantum
    • Richard Bellman
    • Wolfgang Pauli
    • Max Planck
    • Andrew Helwer
    • William Rowan Hamilton
    • Bell's Theorie: Das Quanten-Venn-Diagramm-Paradoxon
    • Dirac–von Neumann axioms
    • Schrödingers Gleichung
    • Von Neumann
    • von Neumann Landauer Limit
    • Deutsch-Joza
      • Simon's problem
  • Algorithmen
    • The Basics
    • Graph Algorithms & Data Structures
    • Greedy Algorithms & Dynamic Programming
    • Worst-Case Analysis
    • Basic-Python Algorithms
    • Unsupervised Learning
    • Supervised Learning
    • Reinforcement Learning
    • Quantum
      • Shor-Algorithm
      • Grover's algorithm
      • Deutsch-Josza
      • Shor-Algorithm for Prime Factorization
    • Classification
    • Regression
  • Quantum @ LinuxFoundation
    • QIR
    • aide-qc
    • QCoDeS
  • Github
    • Team-Members
    • This GitBook
  • Quantum-Simulation
    • Quest
      • Publications
    • Cloud
      • Kubernetes
      • Kubernetes Tutorial
      • K8s & JupyterHUB
      • JupyterLAB @ JupyterHUB
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Welcome to Quantum-Computing

Quantum-Computing made in Schleswig-Holstein

NextStart with Pennylane

Last updated 3 years ago

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Author: Tjark Ziehm ( falls nicht anders angegeben )

Welcome and thank you for signing up for the course to get a first insight into the field of quantum computing. My name is Tjark Ziehm from OHIOH e.V. and the working group of the same name at Kiel University of Applied Sciences. As a student like you, I love to get knowledge from different fields. My fields are related to computer science. DataScience, robotics, Bluetooth and quantum computing. I took IBM's internal course for quantum computing and acquired quantum mechanics in addition to my "normal" student life. From the beginning, I was fascinated by the possibilities of the extremely new technology of quantum. In the beginning it was extremely hard for me to understand all this math, physics and everything related to it. About myself I would say that I am not a very good student when it comes to memorizing vocabulary and the like. So I have been thinking a lot about how to explain quantum mechanics for myself, to feel it,see it in my mind's eye and understand this fantastic world of quanta. Most of the quantum world was like magic for me and after some time I realized ... if the content is well explained .... there is no magic in it. It is rather a great tool for the future of data science and humanity. That was the reason to make this course for you guys. Let's demystify quantum! We will learn the basics to get to productivity quickly with our own group project and successfully complete the introduction to quantum computing with a presentation. But now straight to Quantum...

Durch die Aufnahme in den Studiengang erhalten Sie:

  • Zugang zu Quanten-Hardware von IBM Die Fähigkeit

  • Einblick in 2 Quanten-SDKs ( qiskit & pennylane ) zu programmieren

  • das nötige Wissen für Quantenmechanik

  • minimal benötigte mathematische Sicht auf die Quanten

  • Grundkenntnisse in Python (Programmiersprache)

  • die Fähigkeit, euer eigenen Quanten-Code zu programmieren, der eure Basis wird, tiefer in die Quantenwelt einzutauchen und selbst Quanten-Berechnungen an einem "Quanten-Rechner" oder Simulationsumgebung zu ertesten

Quantum-Hardware
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