True random number generators (TRNGs) underpin modern cryptography, yet existing implementations face fundamental trade-offs between speed, scalability, and entropy quality. Here, we demonstrate that stochastic switching in the bistable regime of spin-wave dynamics provides a physical entropy source for high-quality random number generation. Our magnonic random number generator (mRNG), based on a lithography-patterned microstrip on yttrium iron garnet (YIG), exploits thermal fluctuations near the nonlinear bistable regime to generate random bitstreams that pass all 15 NIST SP 800-22 statistical tests at rates with 20 Mb/s. We implement a random-bit multiplier using synchronized mRNG units and demonstrate scalability to 200-nm-wide nanoscale waveguides, establishing spin-wave bistability as a viable physical entropy source for integrated random number generation.
True random number generators (TRNGs) underpin modern cryptography, yet existing implementations face fundamental trade-offs between speed, scalability, and entropy quality. Here, we demonstrate that stochastic switching in the bistable regime of spin-wave dynamics provides a physical entropy source for high-quality random number generation. Our magnonic random number generator (mRNG), based on a lithography-patterned microstrip on yttrium iron garnet (YIG), exploits thermal fluctuations near the nonlinear bistable regime to generate random bitstreams that pass all 15 NIST SP 800-22 statistical tests at rates with 20 Mb/s. We implement a random-bit multiplier using synchronized mRNG units and demonstrate scalability to 200-nm-wide nanoscale waveguides, establishing spin-wave bistability as a viable physical entropy source for integrated random number generation.
True random number generation is a critical capability for fault-tolerant quantum computing at millikelvin temperatures. Yet existing Josephson-junction-based TRNGs all rest on a widely accepted but untested assumption: that reliable entropy extraction requires precisely controlled device parameters. Here we show that this assumption does not always hold. We demonstrate a counterintuitive finding: a single current-biased Josephson junction, regardless of its parameter quality, can serve as a cryptographic-grade true random number generator. To establish the universality of this conclusion, we deliberately selected the most extremely deviated devices from fabrication, with critical currents three orders of magnitude away from theoretical predictions and IcR products an order of magnitude above conventional values, as the ultimate stress test. Even under these extreme conditions, the raw Shannon entropy reaches 0.9981~bit (99.8\% of the theoretical maximum), with a min-entropy of 0.9271~bit. Using a square-wave pulsed-bias scheme, we tune the switching probability to P≈0.5. After SHA-256 post-processing, the bitstreams pass all 15 NIST SP 800-22 tests under a conservative m=3 criterion that is more demanding than the standard recommendation, and this certification holds across the entire 100-700~mK operating window of a dilution refrigerator.
Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On the other hand, True Random Number Generation (TRNG) offers true randomness. One way of obtaining such randomness are quantum systems, including quantum computers. As such the use of quantum computers for TRNG has received considerable attention in recent years. However, existing studies almost exclusively consider IBM quantum computers, often stop at using simulations and usually test only a handful of different TRNG quantum circuits. In this paper, we address those issues by presenting a study of TRNG circuits on Odra 5 a real-life quantum computer installed at Wrocław University of Science and Technology. It is also the first study to utilize the IQM superconducting architecture. Since Odra 5 is available on-premises it allows for much more comprehensive study of various TRNG circuits. In particular, we consider 5 types of TRNG circuits with 105 circuit subvariants in total. Each circuit is used to generate 1 million bits. We then perform an analysis of the quality of the obtained random sequences using the NIST SP 800-22 and NIST SP 800-90B test suites. We also provide a comprehensive review of existing literature on quantum computer-based TRNGs.
Multi-junctional magnetic tunneling junction spin dice based on orthogonal spin-transfer devices, a new type of true random number (RN) generator (TRNG) is demonstrated in this paper. Orthogonal spin-transfer devices use a planar polarizer to push the free layer with perpendicular anisotropy to metastable state (high-energy state) when power is on. The stochastic precessional switching behavior in ferromagnetic free layer is utilized as the entropy source of the TRNG. Once the power is turned off, anisotropy field and demagnetization field relax the magnetization of free layer from metastable state to one of the two stable states, producing a random bit whose value is solely determined by the stochastic switching behavior. The generation and detection of random bits were summarized under the macrospin picture. RN sequences with high randomness can be produced steadily in the proposed TRNG with a wide operation range of temperature and applied current density. Furthermore, the RN sequences pass the statistical test of NIST SP-800 with an appropriate pass rate without any need of post-procession of data. Ease of design, ultrafast switching as well as high randomness of the bit sequences make the proposed TRNG a competitive device in information security field.
True random number generators, which output truly random numbers by extracting entropy from physical phenomena such as thermal and electronic noises, are widely used in the field of the cryptographic communication systems. We have been developing a superconductive true random number generator that can generate truly random number sequences, impossible to be predicted, by utilizing the high-speed operation and high-sensitivity of superconductive integrated circuits. In this study, we have calculated the dependences of correlation of output random bits on the generation rate. Statistical tests have been performed on the basis of the NIST statistical test suite in order to evaluate the quality of the randomness of sequences generated by the superconductive true random number generator at high generation rate. We have generated a random number sequence consisting of 3.2 M-bit at the generation rate of 30 Gbit/s using the superconductive true random number generator, fabricated by the ISTEC-SRL 2.5 kA/cm2Nb standard process. The generated random number sequences passed 13 kinds of the statistical tests in the NIST statistical test suit, although the 3 tests were not performed because of the shortage of the generated random numbers. The result sufficiently proves that a superconductive true random number generator can generate a high quality of random numbers that can be used for practical cryptographic applications, at a generation rate of up to 30 Gbit/s.
True random number generators are essential for many applications including security and statistical simulations. A novel superconductive true random number generator is proposed based on inductor-less bistable Josephson junction circuits. The recently proposed design methodology, based on all-Josephson junctions, promises higher area efficiency and simpler circuit design. In this brief, this methodology is extended to a superconductive circuit design that extracts randomness from thermal noise present in electronic circuits. A high throughput of 16 GHz is achieved using the proposed design, with no bias or correlation in the output sequence. The quality of the generated randomness is assessed using NIST SP 800-22 statistical tests. A 100 Mb binary sequence is demonstrated to pass all 15 statistical tests using recommended parameters as per NIST guidelines. The simulation methodology, described in detail, is based on the MIT-LL SFQ5EE 10 kA/cm2 Nb standard process and open source Verilog-A model.
Efficient and reliable Random Number Generator (RNG) are increasingly demanded in cryptographic applications, such as on-the-fly data encription/decription and as a general tool for data protection. Main requirement of RNG is a true randomness, which is achievable by means of physical randomness sources only. A True-RNG based on two independent Stochastic Processes (SP) is presented and discussed. As primary randomness sources, two radioactive decay processes are used. A radioactive source has many advantages over others noise sources, since the decay rate of any nuclide does not depend on temperature, chemical composition, physical state, environmental conditions, and aging. In addition, in U ore for example, the various nuclides are, at very good approximation, at equilibrium in the decay chain, so that many stationary independent SP's with the same statistics can be simply obtained by detecting and selectively routing, e.g. by pulse amplitude sorting, gamma rays of different energy emitted by different nuclides in the decay chain. Simulation is performed by a numerical code. The random bit stream obtained is tested for randomness by the NIST test suite, and results are shown. A hardware implementation of the system is also presented.