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Related Concept Videos

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
Sampling Theorem01:15

Sampling Theorem

In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Upsampling01:22

Upsampling

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...
Bandpass Sampling01:17

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2. The spectrum...

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Updated: May 12, 2026

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

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Published on: May 30, 2014

Wideband frequency-hopping measurement based on quantum compressed sensing.

Wei Li, Jianyong Hu, Yanhua Zang

    Optics Express
    |February 20, 2026
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    Summary

    This study introduces quantum compressed sensing for wideband frequency-hopping signal measurement, overcoming traditional bandwidth limitations. The novel method achieves dynamic capture and accurate reconstruction of complex signals.

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    06:42

    Generation and Coherent Control of Pulsed Quantum Frequency Combs

    Published on: June 8, 2018

    Area of Science:

    • Quantum Information Science
    • Signal Processing
    • Telecommunications Engineering

    Background:

    • Stable operation of frequency-hopping communication systems relies on wideband frequency-hopping measurement.
    • Traditional digital signal processing methods are bandwidth-limited by the Nyquist-Shannon sampling theorem.
    • Compressed sensing, while reducing sampling rates, faces practical limitations due to high-speed pseudo-random sequence requirements.

    Purpose of the Study:

    • To propose and demonstrate a novel wideband frequency-hopping measurement method.
    • To enable dynamic capture and reconstruction of wideband frequency-hopping signals.
    • To overcome the limitations of traditional and existing compressed sensing techniques in this domain.

    Main Methods:

    • Development of a wideband frequency-hopping measurement method based on quantum compressed sensing.
    • Utilization of coherent states as quantum resources.
    • Mapping frequency-hopping signals onto photonic wave functions using an electro-optical modulator.
    • Construction of a compressive measurement system leveraging quantum measurement collapse randomness.
    • Integration of time-frequency analysis with Bayesian optimization for parameter estimation.

    Main Results:

    • Successful measurement and reconstruction of a frequency-hopping signal with 5 GHz bandwidth and 100 kHop/s hopping rate.
    • Achieved a high data compression ratio of 2.1 × 10^3 at a 1 kHop/s hopping rate.
    • Attained a time estimation accuracy of 1 μs for frequency-hopping parameters.

    Conclusions:

    • The proposed quantum compressed sensing method offers a new solution for wideband frequency-hopping measurement.
    • The technique enables dynamic capture and accurate reconstruction of frequency-hopping signals.
    • Potential applications extend to radar and cognitive radio systems.