Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2212.09773

Quantum random number generation based on a perovskite light emitting diode

Joakim Argillander·Alvaro Alarcón·Chunxiong Bao·Chaoyang Kuang·Gustavo Lima·Feng Gao·Guilherme B. Xavier
View original source ↗Read source document ↗Export metadata ↓

Abstract

The recent development of perovskite light emitting diodes (PeLEDs) has the potential to revolutionize the fields of optical communication and lighting devices, due to their simplicity of fabrication and outstanding optical properties. Here we demonstrate, for the first time, that PeLEDs can also be used in the field of quantum technologies by demonstrating a highly-secure quantum random number generator (QRNG). Modern QRNGs that certify their privacy are posed to replace widely adopted pseudo and true classical random number generators in applications such as encryption and gambling, and therefore, need to be cheap, fast and with integration capabilities. Using a compact metal-halide PeLED source, we generate random numbers, which are certified to be secure against an eavesdropper, following the quantum measurement-device-independent scenario. The obtained random number generation rate of more than 10 Mbit s$^{-1}$, which is already comparable to actual commercial devices, shows that PeLEDs can work as high-quality light sources for quantum information tasks, thus paving the way for future developments of quantum technologies. Lastly, we argue that the simpler PeLED manufacturing process, when comparing to solid-state devices, may have large environmental impacts when quantum technology systems become more mass produced, due to the possible lower carbon footprint.

Explore related subjects

quant-phcond-mat.mtrl-sciphysics.app-ph

Keep this discovery

BibTeXRIS

Joakim Argillander, Alvaro Alarcón, Chunxiong Bao, Chaoyang Kuang, Gustavo Lima, Feng Gao, Guilherme B. Xavier. 2022-12-19. Quantum random number generation based on a perovskite light emitting diode. https://arxiv.org/abs/2212.09773

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Probing the Error-Mitigation Threshold with Matrix Product States

Quantum error mitigation relies on accurate noise characterization, but mismatches between the actual and characterized noise can be amplified and drive a sharp threshold between successful and failed mitigation. In random circuits, this threshold maps onto a random-field Ising transition, but previous exact numerics were limited to small one-dimensional and all-to-all systems, leaving explicit two-dimensional architectures unresolved. We develop a fixed-bond-dimension matrix-product-state method for the replicated transfer dynamics that extends threshold calculations beyond exact propagation while retaining the finite-size signatures of the transition. At system sizes beyond previous exact studies, we recover the predicted absence of a threshold for quenched disorder in 1D, obtain a sharper annealed all-to-all critical point, and resolve architecture-dependent finite-depth thresholds in 2D square and heavy-hex circuits. These results establish replicated tensor-network dynamics as a practical tool for probing error-mitigation thresholds in large and higher-dimensional noisy circuits.

quant-ph↗
arXiv2026

Low-cost algorithm-to-execution framework for surface-code quantum computing

The execution of useful quantum algorithms on fault-tolerant processors requires more than a mapping from logical gates to encoded operations: the spatial organization, non-Clifford resource supply, and execution schedule must also be determined while keeping physical overhead within practical limits. Although the theoretical hierarchy from logical circuits to fault-tolerant operations is well established, these implementation choices are often specified and optimized separately. Here we develop a low-cost algorithm-to-execution framework for surface-code quantum computing. From hierarchical algorithm descriptions, it constructs dependency-preserving logical schedules and an executable workload capturing logical interactions, operation parallelism, and time-resolved non-Clifford demand, thereby linking logical computation to surface-code organization, resource-state preparation, and fault-tolerant execution in a traceable workflow. We apply the framework to twenty benchmark circuits across seven algorithm families and a hierarchically composed application-scale elliptic-curve discrete-logarithm workload. Physical costs vary substantially even for circuits with similar logical resource counts. Under our direct-rotation calibration, non-Clifford implementation selection reduces space-time volume by up to 241.5 times versus an all-synthesis baseline for the QAOA amplitude-amplification workload. Circuit-specific surface-code layouts reduce routed-latency estimates for all twenty benchmarks; thirteen also reduce space-time volume because communication savings outweigh added spatial overhead. These results show that low-cost fault-tolerant execution depends on computation scheduling and organization, not aggregate logical resource counts alone.

quant-ph↗
arXiv2026

Sample-optimal learning of stabilizer states

It is well-known that learning a pure $n$-qubit stabilizer state $|\psi\rangle$ both requires, and can be accomplished with, access to a number of copies of $|\psi\rangle$ linear in $n$. However, the precise constant coefficient of this scaling does not appear to have been determined. Here we prove that $L_\delta(n)$, the smallest number of copies from which a quantum procedure can identify any stabilizer state with failure probability at most $0<\delta<1/8$, satisfies $n+\lceil\log_2(1/\delta)\rceil-3\leq L_\delta(n)\leq n+\left\lceil\log_2(1/\delta)\right\rceil+4$. We present a polynomial-time quantum learning algorithm that saturates this bound, achieving a constant factor improvement in sample-complexity over previously known approaches. As an immediate corollary, we obtain via the Choi-Jamiolkowski isomorphism an algorithm for learning an unknown $n$-qubit Clifford unitary from $2n+\left\lceil\log_2(1/\delta)\right\rceil+4$ queries, the $n$-dependence of which we show to be optimal. Our proof technique, which involves Fourier analysis on the abelian group $\mathbb{Z}_4^n \times \mathbb{F}_2^{n(n-1)/2}$, seems to be qualitatively different to previous approaches to stabilizer state learning, and may be of some independent interest; in particular, it admits natural generalisations to further problems in quantum learning theory.

quant-ph↗