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Related Concept Videos

BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

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.
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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...
Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
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Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

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 particular...
Continuous Charge Distributions01:17

Continuous Charge Distributions

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.
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Distribution Reliability and Automation

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Related Experiment Videos

Security of continuous-variable quantum key distribution against general attacks.

Anthony Leverrier1, Raúl García-Patrón, Renato Renner

  • 1Institute for Theoretical Physics, ETH Zurich, 8093 Zurich, Switzerland.

Physical Review Letters
|February 5, 2013
PubMed
Summary
This summary is machine-generated.

We prove the security of quantum key distribution using Gaussian continuous-variable coherent states. Our method works in the finite-size regime, offering practical security against all attacks.

Related Experiment Videos

Area of Science:

  • Quantum Information Science
  • Quantum Cryptography
  • Continuous-Variable Quantum Key Distribution

Background:

  • Quantum key distribution (QKD) offers information-theoretic security.
  • Continuous-variable (CV) QKD protocols are promising for practical implementation.
  • Security proofs in the finite-size regime are crucial for real-world applications.

Purpose of the Study:

  • To prove the security of Gaussian CV-QKD with coherent states.
  • To extend security guarantees to the finite-size regime.
  • To address limitations of previous proofs based on asymptotic assumptions.

Main Methods:

  • Utilized a novel proof approach exploiting phase-space symmetries.
  • Applied the postselection technique developed by Christandl, Koenig, and Renner.
  • Analyzed security against arbitrary quantum attacks.

Main Results:

  • Established the security of Gaussian CV-QKD with coherent states in the finite-size regime.
  • Demonstrated the applicability of the proof beyond the asymptotic limit.
  • Provided a rigorous security guarantee for practical quantum communication.

Conclusions:

  • The developed proof method enhances the practical security of CV-QKD.
  • This work bridges the gap between theoretical security and real-world deployment.
  • Gaussian CV-QKD with coherent states is a secure protocol even with limited data.