Related Experiment Video
Updated: Aug 25, 2025

07:56
A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
Published on: September 5, 2019
8.6K
Imperfection-insensitivity quantum random number generator with untrusted daily illumination
Optics Express
|October 14, 2022
Summary
This study introduces a unified model for quantum random number generators (QRNGs) that accounts for imperfect measurements, enhancing security. The research demonstrates high-speed, secure randomness generation even with flawed devices.
Area of Science:
- Quantum Information Science
- Quantum Cryptography
- Device-Independent Quantum Technologies
Background:
- Quantum random number generators (QRNGs) offer theoretically secure randomness but face security risks due to device imperfections.
- Existing security proofs for source-independent QRNGs (SI-QRNGs) are often fragmented and sensitive to deviations from ideal models.
Purpose of the Study:
- To develop a unified model for analyzing imperfect measurements in SI-QRNGs.
- To provide a robust security proof and randomness rate bound for SI-QRNGs under realistic conditions.
Main Methods:
- Established a unified mathematical model for imperfect measurements in SI-QRNGs.
- Derived a tight randomness rate bound using the uncertainty relation for smooth entropies.
- Experimentally demonstrated the proposed SI-QRNG scheme using standard, imperfect devices.
Main Results:
- The unified model accurately quantifies security with significant device imperfections.
- The derived randomness rate approaches theoretical upper bounds seen in common QRNGs.
- Experimental validation achieved randomness generation rates in the Mbps range.
Conclusions:
- The developed unified model enhances the security and practicality of SI-QRNGs.
- This approach enables secure randomness generation even with highly imperfect, real-world devices.
- The findings pave the way for robust, high-speed quantum random number generation.
Related Concept Videos
Propagation of Uncertainty from Random Error
936
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
936
Random Error
1.4K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
1.4K
Random and Systematic Errors
11.9K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
11.9K
Propagation of Uncertainty from Systematic Error
750
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
750
Uncertainty in Measurement: Accuracy and Precision
75.0K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
75.0K
Wald-Wolfowitz Runs Test II
302
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
302

