Skip to main content
Ctrl+K
NordIQuEst Application Library - Home NordIQuEst Application Library - Home

Application Library

  • NordIQuEst Application Library
  • Hybrid Algorithms
    • Quantum Approximate Optimization Algorithm (QAOA)
      • Comparison of Different Optimizers for QAOA on a Max Cut instance
    • Quantum Chemistry
      • Installation instructions
      • Theory: Quantum Chemistry on Quantum Computers
      • Notebook example: VQE
    • Quantum Walk
      • Classical Random Walk on a Quantum Computer
      • Quantum Random Walk on a Quantum Computer
    • Variational Quantum Eigensolver (VQE) Tutorial
      • Cirq: Variational Quantum Eigensolver for \(H_2\)
      • Qiskit: Variational Quantum Eigensolver for \(H_2\)
    • Quantum Reservoir Computing
      • Quantum Reservoir Computing: Logistic map
  • Real Devices
    • ex3-qal9000 Demo
      • ex3-qal9000 Demo: StateTomography on QAL9000
    • Introduction to Helmi with Qiskit
  • Simulators
    • ex3 Simulators
      • Running Quantum programs on the Qiskit Simulator in eX3
      • QSIM
      • Guide of Running QuEST in eX3
    • LUMI Simulators
      • Qiskit
        • v0.12.0
        • v1.1.1
      • QSim
      • QuEST
  • Training Material Archive
    • Quantum Autumn School 2022
      • Notebooks
        • Quantum programming I
        • Quantum programming II
        • Quantum programming III
        • Use case: Optimization
        • Use case: Quantum chemistry
        • Quantum software testing with Quito
      • Slides
        • The HPC-QC landscape
        • Overview of different QC hardware approaches and QC types
        • Introduction to high-level languages for QC
        • The hybrid HPC-QC approach
        • Overview of the software stack
        • Hybrid classical/quantum algorithms
        • Quantum software testing
    • Quantum Autumn School 2023
      • Notebooks
        • Tutorial - Quantum chemistry
        • Tutorial - Introduction to Helmi with qiskit
        • Tutorial - Quantum Alternating Operator Ansatz
        • Solutions - Tutorial - Quantum Alternating Operator Ansatz
        • Tutorial - Qubit Spectroscopy Analysis
      • Slides
        • HPC-QC integration
        • QC software stack
        • Hybrid Classical/Quantum Algorithms
    • NeIC 2024 Workshop: Quantum Computing 101
      • Setup
      • Workshop: Quantum Computing 101 Part I
      • Workshop: Quantum Computing 101 Part II
    • Quantum Autumn School 2024
      • Notebooks
        • Tutorial - Fault-Tolerant Quantum Computing with CSS codes
        • Tutorial - MAP Decoding Exercise
        • Tutorial - Solving Flight Scheduling Optimization using QAOA
        • Tutorial - Introduction to Helmi
        • Tutorial - Pricing a European call option using quantum computing
        • Tutorial - Pricing a European call option on a quantum computer
        • Tutorial - Variational Quantum Algorithms
        • Tutorial - Estimating the Surface Code Threshold
      • Slides
        • Integration of High Performance Computing and Quantum Computing
        • Quantum Computing for Materials Science
        • Tergite Software Stack
        • Introduction to Helmi
        • Quantum walks on quantum computers
        • Quantum Extreme Learning Machine: Case Studies on Software Testing
        • Option pricing on a quantum computer
        • Quantum Error Correction: Theory and Hands-on
        • Distributed Quantum Computing
        • Quantum Amplitude Estimation
        • Quantum Sweden Innovation Platform
        • Introduction to variational quantum algorithms: VQE and QAOA
        • Icelandic National Competence Center (NCC) for HPC & AI – Quantum Computing Activities
  • Quantum Software Testing Tools
    • Run Software Testing Tools on Jupyter Notebook
    • Welcome to Quito!
    • Welcome to QuSBT!
    • Welcome to QuCAT!

Information

  • Contributors
  • Acknowledgement
  • .rst

Quantum Walk

Contents

  • Setup

Quantum Walk#

This folder contains:

  • Classical Random Walk.ipynb - explains how to simulate classical random walks on a quantum computer

  • Quantum Random Walk.ipynb - explains how to simulate quantum random walks on a quantum computer

Download the requirements.txt

Setup#

Requires Python 3.10–3.12 (qiskit-aer==0.14.2 has no wheels for newer versions; tested with Python 3.12).

python3.12 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Then open the notebooks in Jupyter, e.g. with pip install jupyterlab && jupyter lab.

  • Classical Random Walk on a Quantum Computer
    • In our setting we consider a typical classical 1-D random walk setting, consisting of:
    • Can we use a quantum computer to evolve a lot of these experiments simultaneously?
    • 1) Encode the starting position in a quantum circuit
    • 2) Create a coin-flip circuit
    • 3) Create add and sub gates
    • 4) Apply the gates to the position circuit, conditioned to the coin-flip, for steps number of times
    • 5) Put the circuit together, run experiments and show the final distribution
    • 6) Improving the circuit with QFT
  • Quantum Random Walk on a Quantum Computer
    • Classical -> Quantum walk
    • Run the quantum walk and plot results
    • Compare Classical and Quantum Random Walk results

previous

Notebook example: VQE

next

Classical Random Walk on a Quantum Computer

Contents
  • Setup

By NordIQuEst

© Copyright 2024, NordIQuEst.

https://nordiquest.net

Funding

NordIQuEst is a project of the Nordic e-Infrastructure Collaboration (NeIC).. NeIC is an organisational unit under NordForsk..

Project Manager: Alberto Lanzanova (alberto.lanzanova at csc.fi)