Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

$Interference and Diffraction$ 02:18

Interference and Diffraction

Interference is a characteristic phenomenon exhibited by waves. When two electromagnetic waves interact with their peaks and troughs coinciding, a resulting wave with enhanced amplitude is produced. This is known as constructive interference. In this case, the two waves interacting are in phase with each other.

Discrete-Time Fourier Series

Discrete-Time Fourier Series

The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...

Discrete-time Fourier transform

Discrete-time Fourier transform

The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...

Properties of DTFT I

Properties of DTFT I

In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...

You might also read

Related Articles

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

Sort by

Same author

Automated HER2 Scoring with Uncertainty Quantification Using Lensfree Holography and Deep Learning.

BME frontiers·2026

Same author

Snapshot 3D image projection using a diffractive decoder.

Light, science & applications·2026

Same author

Autonomous Uncertainty Quantification for Computational Point-of-Care Sensors.

ACS nano·2026

Same author

Universal and transferable attacks on pathology foundation models using microscopic perturbations.

Light, science & applications·2026

Same author

Super-resolution image projection over an extended depth of field using a diffractive decoder.

Light, science & applications·2026

Same author

Terahertz generation and detection through gain-enhanced interband photomixing in quantum well structures.

Nature communications·2026

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

Search research articles

Related Experiment Video

Updated: Nov 23, 2025

Design, Fabrication, and Experimental Characterization of Plasmonic Photoconductive Terahertz Emitters

Design, Fabrication, and Experimental Characterization of Plasmonic Photoconductive Terahertz Emitters

Published on: July 8, 2013

Terahertz pulse shaping using diffractive surfaces.

Muhammed Veli^1,2,3, Deniz Mengu^1,2,3, Nezih T Yardimci^1,2,3

¹Department of Electrical and Computer Engineering, University of California Los Angeles (UCLA), Los Angeles, CA, 90095, USA.

Nature Communications

|January 5, 2021

Summary

This summary is machine-generated.

Researchers developed a novel diffractive network to precisely control terahertz (THz) pulses, enabling compact and passive pulse engineering for advanced optical applications.

More Related Videos

Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces

Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces

Published on: June 7, 2019

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Related Experiment Videos

Last Updated: Nov 23, 2025

Design, Fabrication, and Experimental Characterization of Plasmonic Photoconductive Terahertz Emitters

Design, Fabrication, and Experimental Characterization of Plasmonic Photoconductive Terahertz Emitters

Published on: July 8, 2013

Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces

Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces

Published on: June 7, 2019

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Area of Science:

Optics and Photonics
Machine Learning
Wave Optics

Background:

Deep learning offers novel solutions for inverse problems in optics.
Diffractive networks integrate wave optics and machine learning for optical tasks.
Existing methods for pulse shaping can be complex and require external pumps.

Purpose of the Study:

To present a diffractive network for arbitrary broadband pulse shaping.
To demonstrate a compact and passive pulse engineering system.
To enable independent control of amplitude and phase in the terahertz spectrum.

Main Methods:

Designing diffractive layers to collectively engineer the temporal waveform of terahertz pulses.
Utilizing a learning-based framework for diffractive pulse engineering.
Implementing a physical transfer learning approach for pulse-width tunability.

Main Results:

Demonstrated direct pulse shaping in the terahertz spectrum.
Achieved independent control over amplitude and phase of terahertz wavelengths.
Showcased modularity and pulse-width tunability through transfer learning.

Conclusions:

The developed diffractive network provides a passive and compact solution for pulse engineering.
This framework enables precise control over optical waveforms.
Potential applications include communications, ultra-fast imaging, and spectroscopy.