Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

491
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
491
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

335
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
335
Propagation of Uncertainty from Random Error00:59

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
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

116
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
116
Continuous Charge Distributions01:17

Continuous Charge Distributions

7.1K
Imagine a bucket of water. It contains many molecules, of the order of 1026 molecules. Thus, although it contains discrete elements (molecules) at the microscopic level, macroscopically, it can be considered continuous. Small volume elements of water, infinitesimal compared to the bulk of the bucket's volume, still contain many molecules. Under this framework, quantized matter is approximated as continuous for practical purposes.
The electric charge can also be subjected to an analogical...
7.1K
Basic Continuous Time Signals01:22

Basic Continuous Time Signals

292
Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
292

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mechanism of negative supercoil relaxation by Topoisomerase IV.

Nucleic acids research·2026
Same author

Microbial community restructuring and transcriptional responses to acute stress in duckweed enhance lead phytoremediation.

Journal of hazardous materials·2026
Same author

Integrative single-cell and bulk transcriptomics reveal cuproptosis subtypes, prognostic models, and COL5A1 as a key gene in glioblastoma.

Cellular signalling·2026
Same author

Uropathogenic profiles and antibiotic resistance in gynecological cases: a microbial surveillance study from Northeast India.

Scientific reports·2026
Same author

The microbiota-tryptophan-brain axis in neurodegenerative diseases: pathogenic mechanisms, disease-specific roles, and translational therapeutics.

Frontiers in microbiology·2026
Same author

BioMedGraphica: an all-in-one platform for joint textual biomedical prior knowledge and numeric graph generation.

Bioinformatics (Oxford, England)·2026
Same journal

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor.

Optics express·2026
Same journal

Robust 3D topography measurement of large-range high-aspect-ratio structures based on dual-domain statistical filtering in SD-OCT.

Optics express·2026
Same journal

Broadband transmissive terahertz metasurface for simultaneous quad-mode OAM multiplexing.

Optics express·2026
Same journal

Leveraging two-dimensional materials for high-sensitivity optical sensors: quasi-bound states in the continuum within hybrid metasurfaces.

Optics express·2026
Same journal

Resolution investigation for dual-spherical-wave optical scanning holographic microscopy: methods and performance.

Optics express·2026
Same journal

Robustness of parallel subnetwork-filtered diffractive deep neural networks.

Optics express·2026
See all related articles

Related Experiment Video

Updated: Aug 25, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

637

Experimental study on underwater continuous-variable quantum key distribution with discrete modulation.

Xinke Tang, Zhen Chen, Zongyao Zhao

    Optics Express
    |October 15, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study demonstrates a secure underwater quantum communication system. The continuous-variable quantum key distribution (CV-QKD) system achieved a key rate of 22.9 kbits/s and a transmission distance of 148.7 m.

    More Related Videos

    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
    09:23

    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

    Published on: May 30, 2014

    14.6K
    Quasi-light Storage for Optical Data Packets
    07:45

    Quasi-light Storage for Optical Data Packets

    Published on: February 6, 2014

    10.9K

    Related Experiment Videos

    Last Updated: Aug 25, 2025

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
    05:30

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

    Published on: September 8, 2023

    637
    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
    09:23

    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

    Published on: May 30, 2014

    14.6K
    Quasi-light Storage for Optical Data Packets
    07:45

    Quasi-light Storage for Optical Data Packets

    Published on: February 6, 2014

    10.9K

    Area of Science:

    • Quantum Information Science
    • Optical Communication
    • Marine Technology

    Background:

    • Underwater wireless optical communication faces security challenges.
    • Quantum Key Distribution (QKD) offers unconditional security.
    • Continuous-Variable (CV) QKD protocols are suitable for practical implementation.

    Purpose of the Study:

    • To experimentally demonstrate the feasibility of an underwater continuous-variable quantum key distribution (CV-QKD) system.
    • To evaluate the secure key rate and transmission distance of the CV-QKD system in an underwater environment.
    • To investigate the system's performance with different water types.

    Main Methods:

    • Implementation of a four-state protocol for underwater CV-QKD.
    • Transmission of quantum coherent signals through a water tank for parameter estimation.
    • Analysis of secure key rate under collective attack.
    • Performance evaluation across various water conditions.

    Main Results:

    • Demonstrated the feasibility of an underwater CV-QKD system.
    • Estimated secure key rate of 22.9 kbits/s at 12.4 dB channel loss.
    • Estimated maximum underwater transmission distance of 148.7 m in pure seawater.

    Conclusions:

    • The demonstrated CV-QKD system guarantees unconditionally secure underwater wireless optical communication.
    • The system shows promising performance for practical underwater quantum communication applications.
    • The transmission distance is dependent on water type and quality.