Grover's Algorithm

---

⭐️⭐️⭐️ Please star this repo if you find it helpful, interesting, or useful! ⭐️⭐️⭐️

---

Requirements

• Anaconda OR Miniconda

Tip

If you have trouble deciding between Anaconda and Miniconda, please refer to the table below

Anaconda	Miniconda
New to conda and/or Python	Familiar with conda and/or Python
Not familiar with using terminal and prefer GUI	Comfortable using terminal
Like the convenience of having Python and 1,500+ scientific packages automatically installed at once	Want fast access to Python and the conda commands and plan to sort out the other programs later
Have the time and space (a few minutes and 3 GB)	Don't have the time or space to install 1,500+ packages
Don't want to individually install each package	Don't mind individually installing each package

Typing out entire Conda commands can sometimes be tedious, so I wrote a shell script (conda_shortcuts.sh on GitHub Gist) to define shortcuts for commonly used Conda commands.

Example: Delete/remove a conda environment named test_env

• Shortcut command

  rmenv test_env
  

• Manually typing out the entire command

  conda env remove -n test_env && rm -rf $(conda info --base)/envs/test_env
  

The shortcut has 80.8% less characters!

Installation

1. Verify that conda is installed

   conda --version
   

2. Ensure conda is up to date

   conda update conda
   

3. Enter the directory where you want the repository (grovers-algorithm) to be cloned
   • POSIX

     cd ~/path/to/directory

   • Windows

     cd C:\Users\user\path\to\directory

4. Clone the repository (grovers-algorithm), then enter (i.e. cd command) grovers-algorithm directory

   git clone https://github.com/lynkos/grovers-algorithm.git && cd grovers-algorithm

5. Create a conda virtual environment from environment.yml

   conda env create -f environment.yml
   

6. Activate the virtual environment (grovers_env)

   conda activate grovers_env
   

7. Confirm that the virtual environment (grovers_env) is active
   • If active, the virtual environment's name should be in parentheses () or brackets [] before your command prompt, e.g.

     (grovers_env) $
     

   • If necessary, see which environments are available and/or currently active (active environment denoted with asterisk (*))

     conda info --envs
     

     OR

     conda env list
     

Usage

Tip

If you're unsure about which subsection(s) to follow, please refer to the table below

Visual Studio Code	Command Line
Beginner/User-friendly	Recommended if familiar with using terminals/shells/CLIs
GUI	CLI
Click a button to run program	Execute a command in terminal/shell/CLI to run program

Python Script

Note

Although they both perform the same function, there's a discernable difference between grovers_algorithm.py and grovers_algorithm.ipynb. The former is a Python script, the latter is a Jupyter notebook.

Command Line (Recommended)

Run grovers_algorithm.py

python grovers_algorithm.py

Command Line Arguments

Option	Type	Description	Default
-H, --help		Show help message and exit
-T, --title <title>	str	Window title	"Grover's Algorithm"
-n, --n-qubits <n_qubits>	int	Number of qubits	5
-s, --search <search>	int	Nonnegative integers to search for	11 9 0 3 (i.e., { 11, 9, 0, 3 })
-S, --shots <shots>	int	Number of simulations	1000
-f, --font-size <font_size>	int	Histogram's font size	10
-p, --print	bool	Whether or not to print quantum circuit(s)	False
-c, --combine	bool	Whether to combine all non-winning states into 1 bar labeled "Others" or not	False

Visual Studio Code

1. Open grovers_algorithm.py
2. Run grovers_algorithm.py: Click ▷ (i.e. Play button) in the upper-right corner

Jupyter Notebook

Visual Studio Code (Recommended)

1. Open the Command Palette with the relevant keyboard shortcut
   • Mac

     ⌘ + Shift + P
     

   • Windows

     CTRL + Shift + P
     

2. Search and select Python: Select Interpreter
3. Select the virtual environment (grovers_env)
4. Open grovers_algorithm.ipynb
5. Confirm grovers_env is the selected kernel
6. Run grovers_algorithm.ipynb by clicking Run All

Command Line

1. Install ipykernel in the virtual environment (grovers_env)

   conda install -n grovers_env ipykernel
   

2. Add the virtual environment (grovers_env) as a Jupyter kernel

   python -m ipykernel install --user --name=grovers_env
   

3. Open grovers_algorithm.ipynb in the currently running notebook server, starting one if necessary

   jupyter notebook grovers_algorithm.ipynb
   

4. Select the virtual environment (grovers_env) as the kernel before running grovers_algorithm.ipynb

Cleanup

1. [Optional] Deactivate the virtual environment (grovers_env) to clean up and remove it

   conda deactivate
   

2. Close the terminal

Resources

• Anaconda Documentation
• Conda Documentation
• Getting Started with Conda
• Jupyter Notebook Documentation
• Jupyter Project Documentation [PDF]
• Technical Support - Jupyter Google Group
• Qiskit Documentation
• Documentation for Visual Studio Code
• Using Jupyter Notebooks in Visual Studio Code

Credit

Special thanks to Simanraj Sadana for "Grover's search algorithm for n qubits with optimal number of iterations", which has been a helpful reference and an informative read

License

Distributed under the MIT License, Copyright © 2024 Kiran Brahmatewari