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

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

393
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
393
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

424
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
424
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

481
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
481
Frequency-Domain Interpretation of PD Control01:24

Frequency-Domain Interpretation of PD Control

394
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...
394
Aliasing01:18

Aliasing

671
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...
671
Determination of Expected Frequency01:08

Determination of Expected Frequency

2.6K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.6K

You might also read

Related Articles

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

Sort by
Same author

Search for a Dark-Matter-Induced Cosmic Axion Background with ADMX.

Physical review letters·2023
Same author

Phononic bath engineering of a superconducting qubit.

Nature communications·2023
Same author

Energetics of a Single Qubit Gate.

Physical review letters·2022
Same author

Search for Invisible Axion Dark Matter in the 3.3-4.2  μeV Mass Range.

Physical review letters·2022
Same author

Axion Dark Matter Experiment: Detailed design and operations.

The Review of scientific instruments·2022
Same author

Quantifying the quantum heat contribution from a driven superconducting circuit.

Physical review. E·2020

Related Experiment Video

Updated: Feb 17, 2026

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

9.8K

Achieving Optimal Quantum Acceleration of Frequency Estimation Using Adaptive Coherent Control.

M Naghiloo1, A N Jordan2,3,4, K W Murch1,5

  • 1Department of Physics, Washington University, St. Louis, Missouri 63130, USA.

Physical Review Letters
|December 9, 2017
PubMed
Summary

Scientists achieved a quantum advantage in frequency estimation using superconducting circuits. This quantum acceleration in precision, utilizing time-dependent Hamiltonians, offers a 1/T² scaling for oscillation frequency uncertainty.

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

15.1K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

13.3K

Related Experiment Videos

Last Updated: Feb 17, 2026

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

9.8K
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

15.1K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

13.3K

Area of Science:

  • Quantum physics
  • Quantum metrology
  • Superconducting circuits

Background:

  • Precision frequency measurements are vital for timekeeping but are limited by quantum uncertainties.
  • Standard quantum limits for time-independent systems scale as 1/T.
  • Theoretical work predicted enhanced precision (1/T² scaling) using time-dependent quantum Hamiltonians.

Purpose of the Study:

  • To experimentally demonstrate the predicted quantum acceleration in frequency sensitivity.
  • To validate the 1/T² uncertainty scaling for oscillation frequency using time-dependent Hamiltonians.
  • To explore the role of coherent and adaptive control in achieving quantum precision.

Main Methods:

  • Utilized a single transmon qubit in a superconducting circuit.
  • Implemented optimal control pulses for coherent manipulation.
  • Experimentally realized adaptive control strategies for frequency estimation.

Main Results:

  • Achieved the theoretically ideal 1/T² scaling for frequency precision.
  • Demonstrated this quantum improvement for experimental durations shorter than the decoherence time.
  • Confirmed a fundamental quantum advantage in frequency estimation.

Conclusions:

  • Experimental realization of quantum-accelerated frequency estimation is feasible.
  • Superconducting circuits provide a viable platform for quantum metrology advancements.
  • This work highlights a significant quantum advantage for precise frequency measurements.