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

Open and closed-loop control systems01:17

Open and closed-loop control systems

1.1K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.1K
Feedback control systems01:26

Feedback control systems

462
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
462
Effects of feedback01:24

Effects of feedback

725
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
725
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

552
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....
552
Root Loci for Positive-Feedback Systems01:23

Root Loci for Positive-Feedback Systems

164
The Hartley oscillator is a positive feedback system that sustains oscillations by feeding the output back to the input in phase, thereby reinforcing the signal. Positive feedback systems can be viewed as negative feedback systems with inverted feedback signals. In these systems, the root locus encompasses all points on the s-plane where the angle of the system transfer function equals 360 degrees.
The construction rules for the root locus in positive feedback systems are similar to those in...
164
Positive and Negative Feedback Loops01:18

Positive and Negative Feedback Loops

20.4K
Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
20.4K

You might also read

Related Articles

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

Sort by
Same author

Probing Sensitivity Near a Quantum Exceptional Point Using Waveguide Quantum Electrodynamics.

Physical review letters·2026
Same author

Challenges and opportunities for quantum information hardware.

Science (New York, N.Y.)·2025
Same author

Visualising accelerometer-based 24/7 human movement behaviour data: an umbrella review and framework development from the LABDA project.

Journal of activity, sedentary and sleep behaviors·2025
Same author

Attention to quantum complexity.

Science advances·2025
Same author

Synchronous detection of cosmic rays and correlated errors in superconducting qubit arrays.

Nature communications·2025
Same author

Visualizing dynamics of charges and strings in (2 + 1)D lattice gauge theories.

Nature·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: Sep 27, 2025

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

9.1K

Improving qubit coherence using closed-loop feedback.

Antti Vepsäläinen1, Roni Winik2, Amir H Karamlou2,3

  • 1Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. apvepsala@gmail.com.

Nature Communications
|April 12, 2022
PubMed
Summary
This summary is machine-generated.

Stabilizing superconducting transmon qubit frequency fluctuations with closed-loop feedback significantly improves coherence times and reduces single-qubit errors. This enhances quantum processor viability by enabling high-fidelity operations across a wider frequency range.

More Related Videos

Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

12.9K
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

14.7K

Related Experiment Videos

Last Updated: Sep 27, 2025

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

9.1K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

12.9K
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

14.7K

Area of Science:

  • Quantum computing
  • Superconducting circuits
  • Quantum information science

Background:

  • Superconducting qubits are essential for building scalable quantum processors.
  • Achieving practical quantum computation requires suppressing gate errors and enhancing qubit stability.
  • Qubit coherence times currently limit gate fidelities in advanced quantum systems.

Purpose of the Study:

  • To experimentally stabilize superconducting transmon qubit frequency fluctuations.
  • To improve qubit coherence times and reduce single-qubit error rates.
  • To enhance the operational frequency bandwidth for high-fidelity qubit control.

Main Methods:

  • Employed closed-loop feedback control to actively stabilize qubit frequency.
  • Utilized superconducting transmon qubit architecture.
  • Measured coherence times and single-qubit error rates before and after feedback implementation.

Main Results:

  • Increased qubit coherence time by 26%.
  • Reduced single-qubit error rate from 8.5 ± 2.1 × 10⁻⁴ to 5.9 ± 0.7 × 10⁻⁴.
  • Enabled high-fidelity operations over a significantly increased frequency bandwidth, even off the flux-noise insensitive point.

Conclusions:

  • Closed-loop feedback is an effective method for stabilizing superconducting qubits.
  • This technique enhances quantum processor performance by improving coherence and reducing errors.
  • The approach offers a pathway to overcome limitations in large-scale qubit grids caused by frequency crowding.