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

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

532
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...
532
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

753
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....
753
Basic Continuous Time Signals01:22

Basic Continuous Time Signals

546
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...
546
Classification of Signals01:30

Classification of Signals

1.1K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.1K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.5K
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...
1.5K
Upsampling01:22

Upsampling

467
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
467

You might also read

Related Articles

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

Sort by
Same author

Structured Educational Tours in Hospital-Based Radiopharmaceutical Production: Balancing Safety and Learning.

Journal of nuclear medicine technology·2026
Same author

Clinical and radiographic outcomes of cannulated cancellous screw osteosynthesis with and without side-plate for nondisplaced femoral neck fractures: a multicenter propensity score-matched study.

International orthopaedics·2026
Same author

Phantom-based optimization of [<sup>18</sup>F]fluciclovine neuro-oncology imaging on a high-resolution dedicated head PET system: dual-pathway reconstruction protocols.

Annals of nuclear medicine·2026
Same author

Environmental and operational factors affecting 17-month routine <sup>18</sup>F-FDG production: Impact of final purification water cooling and process optimization.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2026
Same author

Continuous-variable fault-tolerant quantum computation under general noise.

Nature communications·2026
Same author

Flow of supercooled liquids under dipolar force field.

The Journal of chemical physics·2025
Same journal

Demonstration of a quantum C-NOT gate in a time-multiplexed fully reconfigurable photonic processor.

Nature communications·2026
Same journal

Nonlinear quantum light source with van der Waals ferroelectric NbOX<sub>2</sub> (X = Br, I).

Nature communications·2026
Same journal

Antagonistic histone H2A variants and autonomous heterochromatin formation shape epigenomic patterns in Arabidopsis.

Nature communications·2026
Same journal

The long tail of nitrate pollution in groundwater challenges governance of global water quality.

Nature communications·2026
Same journal

Select microbial metabolites promote tau aggregation in a murine tauopathy model.

Nature communications·2026
Same journal

Warming climate has lengthened global intense tropical cyclone seasons.

Nature communications·2026
See all related articles

Related Experiment Video

Updated: Nov 21, 2025

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

14.8K

Finite-size security of continuous-variable quantum key distribution with digital signal processing.

Takaya Matsuura1, Kento Maeda1, Toshihiko Sasaki1,2

  • 1Department of Applied Physics, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan.

Nature Communications
|January 14, 2021
PubMed
Summary
This summary is machine-generated.

Continuous-variable quantum key distribution (CV-QKD) offers advantages but lacks full security proofs. This study introduces a method for fidelity estimation and a secure CV-QKD protocol, enabling practical applications.

More Related Videos

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.4K
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

945

Related Experiment Videos

Last Updated: Nov 21, 2025

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

14.8K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.4K
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

945

Area of Science:

  • Quantum Information Science
  • Quantum Cryptography
  • Optical Communication

Background:

  • Continuous-variable quantum key distribution (CV-QKD) presents implementation advantages over discrete-variable (DV) QKD, including lower cost and compatibility with wavelength division multiplexing.
  • The continuous nature of CV-QKD poses challenges for practical signal processing and has hindered complete security proofs.
  • Existing CV-QKD protocols often lack rigorous security guarantees in finite-key regimes against sophisticated attacks.

Purpose of the Study:

  • To develop a robust method for estimating the fidelity of optical pulses to coherent states using heterodyne measurements.
  • To construct a secure binary phase-modulated CV-QKD protocol.
  • To provide a complete security proof for the proposed CV-QKD protocol in the finite-key-size regime against general coherent attacks.

Main Methods:

  • Proposal of a novel, tight, and robust method for fidelity estimation of optical pulses via heterodyne measurements.
  • Construction of a binary phase-modulated CV-QKD protocol.
  • Application of DV QKD proof techniques to establish security in the finite-key-size regime.

Main Results:

  • A reliable method for fidelity estimation in CV-QKD systems is presented.
  • A binary phase-modulated CV-QKD protocol with proven security is developed.
  • The security of the protocol is demonstrated against general coherent attacks within the finite-key-size framework.

Conclusions:

  • The developed fidelity estimation method enhances the practicality of CV-QKD.
  • The proposed CV-QKD protocol achieves complete security, addressing a critical gap in the field.
  • This work paves the way for the secure and widespread adoption of CV-QKD, leveraging its inherent advantages.