Monte Carlo Simulator for Commision Modelling with Quantum Random Number Generator

The project aims to set up a simple monte carlo simutor that models univariate functions with the help of a quantum random generator. The code is set up to allow the user to select between the default numpy RNG or a QRNG using the IBMQ quantum computing network.

Development plan

• Setup simple Monte Carlo Simulator (MCS) on python[DONE]
• Setp simple QRNG[DONE]
• link QRNG to MCS{DONE}
• enable QRNG with probablity distributions<[DONE]
• Study effects of QRNG on montecarlo accuracy and efficieny

Sources

• https://towardsdatascience.com/monte-carlo-simulations-with-python-part-1-f5627b7d60b0
• https://pbpython.com/monte-carlo.html
• https://medium.com/qiskit/programming-a-quantum-computer-generating-true-random-numbers-7dd631ef10a1
• https://quantumcomputinguk.org/tutorials/modelling-probability-distributions-in-qiskit

Instructions for use

1. first time users can use python3 -m pip install -r requirements.txt
2. Enter target function as a function of x in the functions.py in python language
3. call montecarlo.py --h for help on how to use the simulator