690 research outputs found
Enhancing quantum entropy in vacuum-based quantum random number generator
Information-theoretically provable unique true random numbers, which cannot
be correlated or controlled by an attacker, can be generated based on quantum
measurement of vacuum state and universal-hashing randomness extraction.
Quantum entropy in the measurements decides the quality and security of the
random number generator. At the same time, it directly determine the extraction
ratio of true randomness from the raw data, in other words, it affects quantum
random numbers generating rate obviously. In this work, considering the effects
of classical noise, the best way to enhance quantum entropy in the vacuum-based
quantum random number generator is explored in the optimum dynamical
analog-digital converter (ADC) range scenario. The influence of classical noise
excursion, which may be intrinsic to a system or deliberately induced by an
eavesdropper, on the quantum entropy is derived. We propose enhancing local
oscillator intensity rather than electrical gain for noise-independent
amplification of quadrature fluctuation of vacuum state. Abundant quantum
entropy is extractable from the raw data even when classical noise excursion is
large. Experimentally, an extraction ratio of true randomness of 85.3% is
achieved by finite enhancement of the local oscillator power when classical
noise excursions of the raw data is obvious.Comment: 12 pages,8 figure
Noise-induced dynamics and photon statistics in bimodal quantum-dot micropillar lasers
Emission characteristics of quantum-dot micropillar lasers (QDMLs) are
located at the intersection of nanophotonics and nonlinear dynamics, which
provides an ideal platform for studying the optical interface between classical
and quantum systems. In this work, a noise-induced bimodal QDML with orthogonal
dual-mode outputs is modeled, and nonlinear dynamics, stochastic mode jumping
and quantum statistics with the variation of stochastic noise intensity are
investigated. Noise-induced effects lead to the emergence of two intensity
bifurcation points for the strong and the weak mode, and the maximum output
power of the strong mode becomes larger as the noise intensity increases. The
anti-correlation of the two modes reaches the maximum at the second intensity
bifurcation point. The dual-mode stochastic jumping frequency and effective
bandwidth can exceed 100 GHz and 30 GHz under the noise-induced effect.
Moreover, the noise-induced photon correlations of both modes simultaneously
exhibit super-thermal bunching effects () in the low injection
current region. The -value of the strong mode can reach over 6 in
the high injection current region. Photon bunching () of both
modes is observed over a wide range of noise intensities and injection
currents. In the presence of the noise-induced effect, the photon number
distribution of the strong or the weak mode is a mixture of Bose-Einstein and
Poisson distributions. As the noise intensity increases, the photon number
distribution of the strong mode is dominated by the Bose-Einstein distribution,
and the proportion of the Poisson distribution is increased in the high
injection current region, while that of the weak mode is reduced. Our results
contribute to the development preparation of super-bunching quantum integrated
light sources for improving the spatiotemporal resolution of quantum sensing
measurements.Comment: 17 pages, 9 figure
High-speed photon correlation monitoring of amplified quantum noise by chaos using deep-learning balanced homodyne detection
Precision experimental determination of photon correlation requires the
massive amounts of data and extensive measurement time. We present a technique
to monitor second-order photon correlation of amplified quantum
noise based on wideband balanced homodyne detection and deep-learning
acceleration. The quantum noise is effectively amplified by an injection of
weak chaotic laser and the of the amplified quantum noise is
measured with a real-time sample rate of 1.4 GHz. We also exploit a photon
correlation convolutional neural network accelerating correlation data using a
few quadrature fluctuations to perform a parallel processing of the
for various chaos injection intensities and effective bandwidths.
The deep-learning method accelerates the experimental acquisition
with a high accuracy, estimating 6107 sets of photon correlation data with a
mean square error of 0.002 in 22 seconds and achieving a three orders of
magnitude acceleration in data acquisition time. This technique contributes to
a high-speed and precision coherence evaluation of entropy source in secure
communication and quantum imaging.Comment: 6 pages, 6 figure
Research methods on the role of financial inclusion, energy efficiency and energy R&D: Evidence from G7 economies
Countries around the globe are rapidly targeting energy efficiency
goal achievement due to the unproductive and inefficient use of
traditional energy sources. Several factors are discovered that are
critical for energy efficiency in the region. Still, there are many economic,
financial, energy, and research and development factors that
could influence energy efficiency and remained ignored in the scholarly
research, which is important from economic growth as well as
environmental sustainability perspective. This research contributes to
the existing literature by providing novel factors affecting energy
efficiency in the developed nations. Specifically, the current study
investigates the influence of financial inclusion, energy R&D, political-
economic-financial risk index, and the energy-related inflation on
the energy efficiency of G7 economies covering the period from
2004 to 2020. This study employed the slope heterogeneity and
cross-section dependence test, which led to using the second-generation
unit root test. For empirical estimations, the current study utilizes
the panel Quantile regression, and the outcomes reveal that all
the considered variables positively influence the energy efficiency in
the region. However, the influence of these variables increases
except for the energy-related inflation when moving from lower
quantile Q0.25 to medium Q0.50 to higher quantile Q0.75, respectively.
The estimated results are found robust, confirmed by the FMOLS
estimator. Based on the empirical findings, it is recommended that
financial inclusion and energy-related research and development be
enhanced to achieve the region’s energy efficiency
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