Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE International Conference on Nanotechnology (IEEE-NANO)

Randomness Enhancement in a Quantum Dot-Based Quantum Random Number Generator by Correctors

Anvadya Khare, C. A. Jothishwaran, Yash Tiwari, Sugata Gangopadhyay, Vishvendra Singh Poonia

Published Jul 2, 2023• 0 citations
Publisher

Abstract

In this work, we analyze the randomness of a bit stream generated by a quantum dot-based quantum random number generator (QRNG) implemented by a noisy Hadamard gate. We observe that the decoherence of the physical system affects the randomness of the bit stream. Further, to enhance the randomness, we employ various linear corrector functions, which (in theory) act on an input string of bits to give an output string of bits with improved randomness. We use certain tests recommended by NIST to characterize the randomness of the generated and the corrected bit strings. A comparison of these test results shows that linear correctors with high$t$values (around 16) can enhance the randomness of the bit strings generated by a noisy quantum random number generator (QRNG). Therefore, even a noisy QRNG, when combined with an appropriate corrector, will make such devices feasible for true random number generators. This randomness enhancement comes at the cost of reduced bit rates and potential computation time overheads for the QRNG.

DOI
10.1109/nano58406.2023.10231225

Related papers

Hybrid Hadamard and controlled-Hadamard based quantum random number generators in IBM QX

Ramin Salehi, Mohammad Razaghi, Bashir Fotouhi

Abstract Designing novel circuits and models for generating truly random numbers is of great importance. Recent attention has been focused on the idea of using real quantum computers to generate random numbers. In order to generate purely random bits and numbers, one method relies on the natural superposition of quantum gates. Here, we design a Quantum Random Number Generator (QRNG) exploiting combinations of Hadamard and controlled-Hadamard gates in IBM Quantum Experience (QX). In order to verify that the generated bit sequences were truly random, the proposed circuit’s outputs were subjected to the National Institute of Standards and Technology (NIST) test suite. In comparison to previous works, we found that not only had the total number of passed tests increased, but the P-values had also improved in many cases. For example, in the simulation style of the IBM QX, the number of passed tests is 14 out of 15 standard NIST tests. For the experimental mood of the IBM 16Q Melbourne, the number of passed tests is six without using any extractions. Furthermore, one more test is passed by adding Barrier operations to the circuits, and the P-values have increased. As a result, we found that the proposed method had more passed tests than previous works. The average of P-values for the six passed tests in former research for the mood of using a combination of extractors is about 0.43 . However, the best result we can get with our circuits is around 0.60 (the average of P-values for 14 passed tests), which is an improvement of 0.17 compared to former works . Because of this, our circuits are getting ever closer to being a true QRNG.

Physica Scripta•Apr 22, 2022•15 citations

Quantum Random Number Generation for Secure Communications Using Hybrid Hadamard Controlled-NOT Gates with XOR Bitmask

Lutfiatul Mar’Ah, Rahmat Mulyawan, Andriyan Bayu Suksmono

The reliability and security of telecommunication systems depend on the quality of random number generators (RNGs). Quantum Random Number Generators (QRNGs) enhance randomness over classical methods, improving cryptographic strength. This paper evaluates three QRNG implementations using IBM quantum computers, analyzing their methodologies, performance, and limitations. We introduce a new QRNG algorithm on the IBM Quantum Experience (IBMQ) platform, using real quantum computers instead of simulators, and incorporating post-processing with XOR bit masking. Our algorithm achieves entropy 0.86458 and passes more NIST 800-90B and NIST 800–22 randomness tests, demonstrating its effectiveness and reliability. This research supports secure telecommunication technologies by providing a reliable source of true randomness.

IEEE International Conference on Advanced Telecommunication and Networking Technologies (ATNT)•Sep 9, 2024•2 citations

Modulator-free, self-testing quantum random number generator

Ana Blázquez, Fadri Grünenfelder, Anthony Martin +3 more

Quantum random number generators (QRNGs) use the inherent unpredictability of quantum mechanics to generate true randomness, as opposed to classical random number generators. However, ensuring the authenticity of this randomness still requires robust verification. Self-testing QRNGs address this need by enabling the validation of the randomness produced based on the observed data from the experiment while requiring few assumptions. In this work, we present a practical, self-testing QRNG designed to operate with an untrusted measurement device and a partially characterized source, allowing the user to check the adequate functioning of the setup in real time. Our experiment yields a rate of certified random bits of 450 kbps.

arXiv:2507.12346•EPJ Quantum Technology•Mar 24, 2026•0 citations

Implement quantum random number generation on the IBM quantum computer platform

Nhu-Quynh Luc, Le Van Anh

Random numbers are a crucial component of any encryption activity in modern cryptography. Quantum Random Number Generators (QRNGs) produce truly random output strings to replace pseudo-random ones. The principle of QRNG relies on measuring qubit states, which excel in quantum computing applications, particularly on IBM's quantum computing platform. To construct a random number generator, the authors utilized IBM Q Experience's Qiskit quantum development toolkit. We developed QRNG applications on IBM quantum computers (7-qubit, 16-qubit, and 127-qubit) and tested the program's functionality on these quantum computing platforms. The quality assessment of the random strings was conducted according to NIST and AIS-31 standards. For NIST standards, to achieve good quality, the output string must reach a minimum of 1,593,088 bits to pass 16 tests per SP800-22 standard. According to AIS-31 standards, to achieve good quality, the output string must reach a minimum of 8,000,000 bits to pass 8 tests of the standard

The Transport and Communications Science Journal•May 15, 2024•2 citations

Construction of a Quantum Random Number Generator

Kashish Karera, Ayan Khan, Humanyou Tariq +4 more

Quantum random number generators (QRNG) are the prime source of randomness, by exploiting the unpredictable nature of Quantum mechanics QRNG aims to provide a string of completely random utterly unpredictable numbers. QRNGs are crucial for cryptography, scientific calculation, simulation, and many more real-world applications. Our Optical Quantum Random Number Generator (OQRNG) utilizes a high-speed pulsating laser, a Polarizing beam splitter (PBS), photodetectors, and advanced signal processing units that capture and digitize random photon intensity forming the raw random bit stream. This technique is famously known as Branching Path Technique. After that, we implement rigorous testing that encompasses the statistical randomness tests developed by National Institute of Standards and Technology (NIST) to ensure the guaranteed ran-domness meets security standards. A user-friendly Graphic user interface (GUI) simplifies interaction with the QRNG allowing the user to configure device settings, monitor system performance, and securely extract random numbers. Our findings help us demonstrate the superiority of QRNGs over classical random number generators, and highlight the potential of photon-based QRNGs and their environmentally friendly and efficient random number generation.

International Conference on Innovations in Computer Science & Software Engineering (ICONICS)•Nov 13, 2024•0 citations

Improving bit generation rates for quantum random number generators

Walter O. Krawec

Quantum Random Number Generators (QRNG) are quantum cryptographic protocols that distill secure random bit strings from quantum sources. One of the main research challenges in this area is to improve their random bit generation rates. Here we investigate several possible post processing strategies for QRNG protocols, showing when they help and when they hinder. We also look at the trade-offs to using these methods as some require a larger amount of initial randomness. Finally, we comment on some interesting future problems that remain open.

•Jun 13, 2023•0 citations
In this work, we analyze the randomness of a bit stream generated by a quantum dot-based quantum random number generator (QRNG) implemented by a noisy Hadamard gate. We observe that the decoherence of the physical system affects the randomness of the bit stream. Further, to enhance the randomness, we employ various linear corrector functions, which (in theory) act on an input string of bits to give an output string of bits with improved randomness. We use certain tests recommended by NIST to characterize the randomness of the generated and the corrected bit strings. A comparison of these test results shows that linear correctors with hightttvalues (around 16) can enhance the randomness of the bit strings generated by a noisy quantum random number generator (QRNG). Therefore, even a noisy QRNG, when combined with an appropriate corrector, will make such devices feasible for true random number generators. This randomness enhancement comes at the cost of reduced bit rates and potential computation time overheads for the QRNG.
Abstract Designing novel circuits and models for generating truly random numbers is of great importance. Recent attention has been focused on the idea of using real quantum computers to generate random numbers. In order to generate purely random bits and numbers, one method relies on the natural superposition of quantum gates. Here, we design a Quantum Random Number Generator (QRNG) exploiting combinations of Hadamard and controlled-Hadamard gates in IBM Quantum Experience (QX). In order to verify that the generated bit sequences were truly random, the proposed circuit’s outputs were subjected to the National Institute of Standards and Technology (NIST) test suite. In comparison to previous works, we found that not only had the total number of passed tests increased, but the P-values had also improved in many cases. For example, in the simulation style of the IBM QX, the number of passed tests is 14 out of 15 standard NIST tests. For the experimental mood of the IBM 16Q Melbourne, the number of passed tests is six without using any extractions. Furthermore, one more test is passed by adding Barrier operations to the circuits, and the P-values have increased. As a result, we found that the proposed method had more passed tests than previous works. The average of P-values for the six passed tests in former research for the mood of using a combination of extractors is about 0.43 . However, the best result we can get with our circuits is around 0.60 (the average of P-values for 14 passed tests), which is an improvement of 0.17 compared to former works . Because of this, our circuits are getting ever closer to being a true QRNG.
The reliability and security of telecommunication systems depend on the quality of random number generators (RNGs). Quantum Random Number Generators (QRNGs) enhance randomness over classical methods, improving cryptographic strength. This paper evaluates three QRNG implementations using IBM quantum computers, analyzing their methodologies, performance, and limitations. We introduce a new QRNG algorithm on the IBM Quantum Experience (IBMQ) platform, using real quantum computers instead of simulators, and incorporating post-processing with XOR bit masking. Our algorithm achieves entropy 0.86458 and passes more NIST 800-90B and NIST 800–22 randomness tests, demonstrating its effectiveness and reliability. This research supports secure telecommunication technologies by providing a reliable source of true randomness.
Quantum random number generators (QRNGs) use the inherent unpredictability of quantum mechanics to generate true randomness, as opposed to classical random number generators. However, ensuring the authenticity of this randomness still requires robust verification. Self-testing QRNGs address this need by enabling the validation of the randomness produced based on the observed data from the experiment while requiring few assumptions. In this work, we present a practical, self-testing QRNG designed to operate with an untrusted measurement device and a partially characterized source, allowing the user to check the adequate functioning of the setup in real time. Our experiment yields a rate of certified random bits of 450 kbps.
Random numbers are a crucial component of any encryption activity in modern cryptography. Quantum Random Number Generators (QRNGs) produce truly random output strings to replace pseudo-random ones. The principle of QRNG relies on measuring qubit states, which excel in quantum computing applications, particularly on IBM's quantum computing platform. To construct a random number generator, the authors utilized IBM Q Experience's Qiskit quantum development toolkit. We developed QRNG applications on IBM quantum computers (7-qubit, 16-qubit, and 127-qubit) and tested the program's functionality on these quantum computing platforms. The quality assessment of the random strings was conducted according to NIST and AIS-31 standards. For NIST standards, to achieve good quality, the output string must reach a minimum of 1,593,088 bits to pass 16 tests per SP800-22 standard. According to AIS-31 standards, to achieve good quality, the output string must reach a minimum of 8,000,000 bits to pass 8 tests of the standard
Quantum random number generators (QRNG) are the prime source of randomness, by exploiting the unpredictable nature of Quantum mechanics QRNG aims to provide a string of completely random utterly unpredictable numbers. QRNGs are crucial for cryptography, scientific calculation, simulation, and many more real-world applications. Our Optical Quantum Random Number Generator (OQRNG) utilizes a high-speed pulsating laser, a Polarizing beam splitter (PBS), photodetectors, and advanced signal processing units that capture and digitize random photon intensity forming the raw random bit stream. This technique is famously known as Branching Path Technique. After that, we implement rigorous testing that encompasses the statistical randomness tests developed by National Institute of Standards and Technology (NIST) to ensure the guaranteed ran-domness meets security standards. A user-friendly Graphic user interface (GUI) simplifies interaction with the QRNG allowing the user to configure device settings, monitor system performance, and securely extract random numbers. Our findings help us demonstrate the superiority of QRNGs over classical random number generators, and highlight the potential of photon-based QRNGs and their environmentally friendly and efficient random number generation.
Quantum Random Number Generators (QRNG) are quantum cryptographic protocols that distill secure random bit strings from quantum sources. One of the main research challenges in this area is to improve their random bit generation rates. Here we investigate several possible post processing strategies for QRNG protocols, showing when they help and when they hinder. We also look at the trade-offs to using these methods as some require a larger amount of initial randomness. Finally, we comment on some interesting future problems that remain open.