@conference {508,
	title = {Qubit Reset and Refresh: A Gamechanger for Random Number Generation},
	booktitle = {Twelveth ACM Conference on Data and Application Security and Privacy (CODASPY )},
	year = {2022},
	abstract = {<p>Generation of random binary numbers for cryptographic use is often addressed using pseudorandom number generating functions in compilers and specialized cryptographic packages. Using the IBM{\textquoteright}s Qiskit reset functionality, we were able to implement a straight-forward in-line Python function that returns a list of quantum-generated random numbers, by creating and executing a circuit on IBM quantum systems. We successfully created a list of 1000 1024-bit binary random numbers as well as a list of 40,000 25-bit binary random numbers for randomness testing, using the NIST Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications. The quantum-generated random data we tested showed very strong randomness, according to the NIST suite. Previously, IBM{\textquoteright}s quantum implementation required a single qubit for each bit of data generated in a circuit, making generation of large random numbers impractical. IBM{\textquoteright}s addition of the reset instruction eliminates this restriction and allows for the creation of functions that can generate a larger quantity of data-bit output, using only a small number of qubits.</p>
},
	keywords = {Qiskit, QRNG, Quantum Computing, Random Number Generator},
	doi = {10.1145/3508398.3519364},
	url = {https://dl.acm.org/doi/abs/10.1145/3508398.3519364},
	author = {Germain, Julie and Dantu, Ram and Thompson, Mark}
}
