Patterns in Quantum Randomness Research

By driving a quantum processor with laser pulses arranged according to the Fibonacci sequence, physicists observed the emergence of an entirely new phase of matter—one that displays extraordinary stability in a domain where fragility is the norm. Quantum computers operate using qubits, which differ radically from classical bits. A qubit can exist in superposition, occupying multiple states at once, and can become entangled with others across space. These properties enable immense computational power, but they come with a cost: quantum states are notoriously short-lived. Environmental noise, microscopic imperfections, and edge effects rapidly degrade coherence, limiting how long quantum information can survive. Seeking a new way to protect fragile quantum states, scientists at the Flatiron Institute, instead of applying laser pulses at regular intervals, they used a rhythm governed by the Fibonacci sequence—an ordered but non-repeating pattern long known to appear in biological growth, crystal structures, and wave interference. The experiment was carried out on a chain of ten trapped-ion qubits, driven by precisely timed laser pulses. The result was the formation of what is described as a time quasicrystal. Unlike ordinary crystals, which repeat periodically in space, a time quasicrystal exhibits structure in time without repeating in a simple cycle. The Fibonacci-based driving created a temporal order that resisted disruption, allowing the quantum system to remain coherent far longer than expected. The improvement was significant. Under standard conditions, the quantum state persisted for roughly 1.5 seconds. When driven by the Fibonacci pulse sequence, coherence times stretched to approximately 5.5 seconds—more than a threefold increase. Even more intriguing was the system’s temporal behavior. Measurements indicated that the quantum dynamics unfolded as if time itself possessed two independent structural directions. This does not imply time flowing backward, but rather that the system’s evolution followed two intertwined temporal pathways—an emergent property arising purely from the Fibonacci drive. The researchers propose that the non-repeating structure of the Fibonacci sequence suppresses errors that typically accumulate at the boundaries of quantum systems. By distributing disturbances in a highly ordered yet aperiodic way, the sequence stabilizes the collective behavior of the qubits. In effect, a mathematical pattern found throughout nature acts as a self-organizing error-management protocol. The findings suggest a powerful new strategy for quantum control. Rather than fighting noise solely with complex correction algorithms, future quantum technologies may harness structured patterns—drawn from mathematics and natural order—to achieve resilience at a fundamental level. https://lnkd.in/dVxp7R8J https://lnkd.in/dDVNRsPk

What are they claiming? Problem with classical random number generators: Pseudo-random number generators (PRNGs) are predictable and not secure enough for cryptography. True random number generators (TRNGs) based on hardware also have trust and degradation issues. Quantum approach: They propose generating certified random numbers using noisy intermediate-scale quantum (NISQ) computers, specifically IBMQ backends. Key method: Instead of using Bell’s inequality (which requires spatial separation), they use Leggett–Garg Inequality (LGI) violations with No-Signaling-in-Time (NSIT) conditions to certify randomness. Implementation: Built low-depth circuits with only single-qubit gates (RZ, SX). Applied the protocol on IBM Quantum devices (Brussels, Perth, Lagos, Kyoto). Verified LGI violation while NSIT was satisfied. Randomness certification: The violation of LGI ensures that the output cannot be explained by classical deterministic processes → hence the random bits are certified quantum random numbers. Noise mitigation: Used circuit transpilation, optimal qubit layout (mapomatic), and IBM’s Mthree error mitigation to reduce readout errors and bring results closer to theory. Scale of results: Each experiment used ~50,000 shots across 5 circuits. Generated large sequences of certified random bits. Randomness values closely matched theoretical bounds (slightly lower due to noise). Advantages vs. Bell-based certification: No need for multiple spatially separated devices. Works on a single quantum processor. Loopholes like clumsiness, detection efficiency, or coincidence are closed. Practicality: The method is semi-device-independent (assumes 2D qubit state and projective measurements). Still, it’s a simpler and hardware-efficient approach for NISQ-era devices. Applications: Cryptographic key generation. Benchmarking quantum devices. Potential deployment on commercial quantum processors for secure randomness. Urbasi Sinha

Is this the first real-world use case for quantum computers? True randomness is hard to come by. And in a world where cryptography and fairness rely on it, “close enough” just doesn’t cut it. A new paper in Nature claims to present a demonstrated, certified application of quantum computing, not in theory or simulation, but in the real world. Led by Quantinuum, JPMorganChase, Argonne National Laboratory, Oak Ridge National Laboratory, and The University of Texas at Austin, the team successfully ran a certified randomness expansion protocol on Quantinuum’s 56-qubit H2 quantum computer, and validated the results using over 1.1 exaflops of classical computing power. TL;DR is certified randomness--the kind of true, verifiable unpredictability that’s essential to cryptography and security--was generated by a quantum computer and validated by the world’s fastest supercomputers. Here’s why that matters: True randomness is anything but trivial. Classical systems can simulate randomness, but they’re still deterministic at the core. And for high-stakes environments such as finance, national security, or fairness in elections, you don’t want pseudo-anything. You want cold, hard entropy that no adversary can predict or reproduce. Quantum mechanics is probabilistic by nature. But just generating randomness with a quantum system isn’t enough; you need to certify that it’s truly random and not spoofed. That’s where this experiment comes in. Using a method called random circuit sampling, the team: ⚇ sent quantum circuits to Quantinuum’s 56-qubit H2 processor, ⚇ had it return outputs fast enough to make classical simulation infeasible, ⚇ verified the randomness mathematically using the Frontier supercomputer ⚇ while the quantum device accessed remotely, proving a future where secure, certifiable entropy doesn’t require trusting the hardware in front of you The result? Over 71,000 certifiably random bits generated in a way that proves they couldn’t have come from a classical machine. And it’s commercially viable. Certified randomness may sound niche—but it’s highly relevant to modern cryptography. This could be the start of the earliest true “quantum advantage” that actually matters in practice. And later this year, Quantinuum plans to make it a product. It’s a shift— from demos to deployment from supremacy claims to measurable utility from the theoretical to the trustworthy read more from Matt Swayne at The Quantum Insider here --> https://lnkd.in/gdkGMVRb peer-reviewed paper --> https://lnkd.in/g96FK7ip #QuantumComputing #CertifiedRandomness #Cryptography

2D DIPOLAR SPIN ENSEMBLE OR LEVY FLIGHTS WHEN QUANTUM PARTICLES FLYING LIKE BEES Identifying universal properties of non-equilibrium quantum states is a major challenge in modern physics. A fascinating connection between many-body dynamics in a two-dimensional dipolar spin ensemble and Lévy flights lies in the statistical behavior and transport properties of the system. Lévy flights are a type of random walk characterized by step lengths that follow a heavy-tailed probability distribution, allowing for occasional long jumps. This behavior contrasts with classical Brownian motion, where step lengths are normally distributed. In 2D dipolar spin ensemble, the interactions between spins can lead to complex many-body dynamics, including anomalous transport phenomena. These dynamics can exhibit characteristics similar to Lévy flights, where the system's evolution involves non-local interactions or long-range correlations. Such behavior is often observed in systems with strong disorder or long-range interactions, where the transport deviates from classical diffusion and instead follows a pattern resembling Lévy flights. By studying these dynamics, researchers can gain insights into the fundamental properties of quantum systems. Quantum systems are incredibly complex, capable of assuming over two quadrillion states. Researchers from the Munich Quantum Valley and the University of Innsbruck have made a progress in addressing the quantum dynamics of 51 individually controlled ions by a long-range quantum magnet, realizing a long-range interacting spin chain. They demonstrated that the long-term behavior of such systems might be approximated using equations developed by the Bernoulli brothers in the 18th century to model fluid dynamics. Research team developed a protocol to measure space- and time-resolved spin correlations within an engineered infinite temperature state. This approach allows to experimentally demonstrate the emergence of hydrodynamics in a non-equilibrium quantum state. By measuring space- and time-resolved correlation functions in an infinite temperature state, study uncovered a diverse spectrum of hydrodynamic universality classes, spanning from normal diffusion to anomalous superdiffusion, characterized by Lévy flights. The transport coefficients from the hydrodynamic theory were extracted, which capture the microscopic properties of the system. The relaxation dynamics unfold in distinct stages. Initially, a local equilibrium is quickly established after just a few collisions with the abundant excitations in the infinite temperature state. This leads to a rapidly damped oscillation in the auto-correlation at short times. As time progresses, the system transitions into the hydrodynamic regime and ultimately moves toward global equilibrium, driven by the gradual rearrangement of spin excitations, which are restricted by the conserved magnetization. # DOI: 10.1126/science.abk2400

Random Numbers, Quantum Computing and Cybersecurity. Let's try to understand what is Quantum Random Number Generation (QRNG)... In an era where randomness powers security, simulations, and cryptographic protocols, Quantum Random Number Generation (QRNG) emerges as a groundbreaking technology. Unlike classical random number generators, QRNG leverages the intrinsic unpredictability of quantum mechanics to produce truly random numbers, revolutionizing applications across various domains. (This might sound too much but keep reading it will all make sense...) Generally, QRNG can be divided into the following subdomains 🔹 Theoretical Foundations The science behind QRNG includes: - Quantum Mechanics Principles: Studying superposition, entanglement, and uncertainty. - Randomness Generation Limits: Investigating the theoretical boundaries of QRNG. - Quantum Information Theory: Applying concepts like entropy and quantum state evolution. 🔹 Hardware Development through QNRG - Chip-based QRNGs: Compact solutions for mobile and IoT devices. - High-Speed QRNGs: Generating random numbers at gigabit rates. - Quantum Photonics Hardware: Laser-based systems with beam splitters and detectors. - Embedded Quantum Devices: Integrating QRNG into consumer electronics and security systems. 🔹 Cryptographic Applications - Quantum Key Distribution (QKD): Generating encryption keys immune to eavesdropping. - Secure Random Key Generation: Providing unpredictable keys for cryptographic algorithms. - Zero-Knowledge Proofs: Enabling secure, private cryptographic protocols. 🔹 Statistical Analysis - Randomness Testing Frameworks: Standards like NIST and Diehard tests. - Certifiable Randomness: Verifying randomness through quantum principles. - Standards and Compliance: Adhering to industry regulations. 🔹 Security Challenges and Advancements - Noise and Environmental Effects: Reducing external interference in randomness generation. - Tamper Resistance: Protecting devices from manipulation. - Scalability and Integration: Expanding QRNG applications to large-scale systems. 🔹 Entropy Extraction and Post-Processing - Entropy Amplification: Enhancing the purity of randomness extracted from raw data. - Hashing and Compression: Using cryptographic hashing to eliminate biases. - Error Correction: Mitigating noise and imperfections in measurements. 🔹 Emerging Trends and Innovations - Hybrid Systems: Combining QRNG with classical methods for enhanced performance. - AI-Augmented QRNG: Using AI to optimize hardware and processes. - Space-Based QRNG: Exploring QRNG applications in satellite systems. Quantum Random Number Generation represents a paradigm shift in randomness technology. But don't get, "Fooled by this Randomness", explore this field with caution and you might build a Technology which integrates cryptography, AI, and Quantum Computing. #quantumcomputing #quantumtechnology #cybersecurity #datascience #ai #cryptography