Quantum physics is old and mature. Quantum computing and algorithms arose 3 decades ago. Quantum programming on real Quantum Computational Devices (QCD) is something new. Less than the last five years, researchers and scientists could apply quantum programming to QCD since several vendors like IBM, Rigetti, Microsoft or Google could provide access to real machines. In this paper, we experiment and investigate the accuracy of a 5-qubits QCD applying a string search algorithm. Simulating environment used also in order to evaluate the technique and the results obtained were very promising. Even if the accuracy of a real device was around 48% since the possibilities of the other outcomes were extremely low proved the reliability of the real machine. The number of existing qubits was the main obstacle that limits their processing power. In addition, a random number generator was implemented which overcomes all the disadvantages of pseudo-random generators.
Quantum physics is old and mature. Quantum computing and algorithms arose 3 decades ago. Quantum programming on real Quantum Computational Devices (QCD) is something new. Less than the last five years, researchers and scientists could apply quantum programming to QCD since several vendors like IBM, Rigetti, Microsoft or Google could provide access to real machines. In this paper, we experiment and investigate the accuracy of a 5-qubits QCD applying a string search algorithm. Simulating environment used also in order to evaluate the technique and the results obtained were very promising. Even if the accuracy of a real device was around 48% since the possibilities of the other outcomes were extremely low proved the reliability of the real machine. The number of existing qubits was the main obstacle that limits their processing power. In addition, a random number generator was implemented which overcomes all the disadvantages of pseudo-random generators.
Creating a true random number generator is a difficult problem that may be solved by leveraging quantum computing. A simple quantum random number generation program involves applying the Hadamard gate to all qubits then measuring each qubit for random data, repeating the program to obtain the desired bitstring length. Implementing this algorithm on IBM’s Manila and Rigetti’s Aspen-9 quantum computers, we obtained a sample of 1,000,000 potentially random bits. In this thesis, we evaluate the quality of random bits generated by using quantum computers as a hardware random number generator with statistical testing and present the implications of those results.
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
Random numbers are the lifeline of any cryptographic operation in modern computing. Quantum True Random Number Generator (QTRNG) can yield real random data to replace random-looking periodic sequences. Here, we present the fastest QTRNG on factual Quantum Computational Devices (QCD) locally on our device to save time. To construct a random number generator, the IBM Q Experience called Qiskit is used. The ease of our source Hadamard gate pooled with its verifiably sole randomness is imperative for attaining quantum random number generators at no cost. The inner matrix product of the square of the Hadamard gate is proved to be identified in the quantum lab. Applying the H gate twice on the quantum register cancelled out the H gate pair. It acted as a single Hadamard gate that was practically visualised using the IMB Q experience. The 24-qubit random number is experimented with and investigated in this work. The min-entropy of such generated random numbers is 0.0007244 with the worst-case entropy value of 0.999507. Besides, subsequent verification of genuine randomness was confirmed by steering restart experimentation, & the statistical properties of TRNG were evaluated over autocorrelation study, National Institute of Standards and Technology (NIST) SP 800-90B & 800-22 tests.
Objectives . The absence of error-resistant quantum computers, coupled with the challenges associated with providing unrestricted and fully operational physical access to cloud quantum computing systems, prompts a critical examination of the necessity to develop universal and independent methods for evaluating and verifying cloud quantum computers. A promising approach involves evaluating the capabilities of a quantum computer in relation to its effectiveness in addressing specific challenges encountered in the assessment of information security systems. A potential test for ascertaining the performance and computational quality of a quantum computing device (QCD) is based on a model designed to generate a random binary sequence. By analyzing this sequence, insights can be obtained into the accuracy and reliability of the quantum register under study. The paper presents a software program developed for simulating the operation of a quantum random number generator. Methods . The software implementation for interacting with cloud quantum computers was performed using the Qiskit open-source software kit. The graphical user interface of the software package was developed using a Qt5 crossplatform set of tools and widgets for creating applications. The analysis of the generated binary sequence was performed using a set of statistical tests NIST STS 2 . Results . The developed software package provides users with a graphical interface for conducting an analysis of a cloud QCD to identify the optimal and most error-resistant set of qubits. The findings from experiments conducted on three cloud quantum computing devices are reported. Conclusions . The proposed approach, which is constrained by limitations of computing power and duration of access to cloud-based QCD, imposes minimal demands on the productive capabilities of the quantum system. It offers clear and unequivocally interpretable insights into the technical characteristics of a cloud quantum computer, while also being reproducible, easily scalable, and universally applicable.
Abstract Quantum realizations have opened a new ways for computer science. The new characteristics and phenomenons allow us to create new algorithms for general proposes. An interesting topic is random number generation. There are two perspectives for this proposes. True random numbers generator (TRN) and pseudo random numbers generator (PRNG). True Random Number Generators has four significant characteristics: randomness, long Period, insensitivity to seeds, repeatability. Additionally, Pseudo Random Number Generators is a fascinating topic that leverages the principles of computer science to craft deterministic algorithms, enabling the creation of a sequence of pseudo-random numbers. A crucial element in this process is the 'seed', which serves as the initial value to generate the entire sequence. This document proposes a algorithm based on a quantum system and the quasi-probability of its possible states to generate a long set of numbers which has pseudo random properties. The quantum system is compound by n qubits, its initial conditions and a small set of rotation gates with a fixed angle. The tests were realized using the battery test called NIST SP800-22, and alpha=0.01 as a threshold to ensures 99\% of precision. The results demonstrate that it is possible generate a long set of pseudo numbers with random characteristics using a quantum simple operation. However, the experiments reveal that a real world implementation require a quantum system with at least 10-9 precision order.
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.