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

Parallel Processing01:20

Parallel Processing

631
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
631
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

56.5K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
56.5K
Semiconductors01:22

Semiconductors

1.4K
There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
Metals such as copper (Cu), zinc (Zn), or lead (Pb) have low resistivity and feature conduction bands that are either not fully occupied or overlap with the valence band, making a bandgap non-existent. This allows electrons in the highest energy levels of the valence band to easily transition to the conduction band upon gaining...
1.4K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

1.1K
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
1.1K
Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

721
Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
721
Quantum Numbers02:43

Quantum Numbers

49.1K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
49.1K

You might also read

Related Articles

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

Sort by
Same author

Efficacy and safety of recombinant human thrombopoietin (rhTPO) in critically ill patients with severe thrombocytopenia: A single-center retrospective cohort study.

International immunopharmacology·2026
Same author

High-performance quantum interconnect between bosonic modules beyond transmission loss constraints.

Science bulletin·2026
Same author

Complement C5a/C5aR1 pathway facilitates glioblastoma progression via fostering glioma stem cell-macrophage symbiosis.

Journal of neuroinflammation·2026
Same author

Factors influencing delays in seeking medical care among elderly patients with pulmonary tuberculosis in Ningbo: a study conducted from 2015 to 2023.

Journal of health, population, and nutrition·2026
Same author

High-Fidelity Controlled-Phase Gate for Binomial Codes via Geometric Phase Engineering.

Physical review letters·2026
Same author

Non-equilibrium criticality-enhanced quantum sensing with superconducting qubits.

Science bulletin·2026
Same journal

Neural Regulation of Cardiac Arrhythmias: From the Brain-Heart Axis to Emerging Precision Therapies.

Research (Washington, D.C.)·2026
Same journal

N<sup>6</sup>-Methyladenosine on Key Messenger RNAs Governs Reproductive Development and Metabolic Adaptation in Human Blood Fluke.

Research (Washington, D.C.)·2026
Same journal

Additive-Free Contact-Electro-Catalysis/Vacuum Ultraviolet System for Rapid Mitigation of Antimicrobial-Resistance-Associated Contaminants in Water.

Research (Washington, D.C.)·2026
Same journal

Predicting 1-Year Renal Outcomes in Patients with Diabetic Kidney Disease in CKD Stages 3 to 4: A Multimodal Machine Learning Approach Fusing Clinical Composites and Pathology Images.

Research (Washington, D.C.)·2026
Same journal

Antioxidant Nanozymes: From Rational Design to Biomedical Applications.

Research (Washington, D.C.)·2026
Same journal

Quantum-Inspired Fast Algorithm and Circuit Realization for Constrained Combinatorial Optimization Problem.

Research (Washington, D.C.)·2026
See all related articles

Related Experiment Video

Updated: Jan 14, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

A Resource-Virtualized and Hardware-Aware Quantum Compilation Framework for Real Quantum Computing Processors.

Hong-Ze Xu1,2,3, Xu-Dan Chai1,3, Meng-Jun Hu1,3

  • 1Beijing Academy of Quantum Information Sciences, Beijing 100193, China.

Research (Washington, D.C.)
|October 20, 2025
PubMed
Summary
This summary is machine-generated.

QSteed virtualizes quantum processors, enabling hardware-aware compilation for noisy superconducting systems. This framework optimizes quantum programs for improved performance without altering user code.

More Related Videos

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

10.2K

Related Experiment Videos

Last Updated: Jan 14, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K
Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

10.2K

Area of Science:

  • Quantum Computing
  • Computer Science
  • Quantum Information Science

Background:

  • Scaling quantum computing systems presents challenges in compiling programs for real hardware.
  • Efficient compilation is crucial for achieving high-fidelity quantum computations.

Purpose of the Study:

  • Introduce QSteed, a system-software framework for resource virtualization and hardware-aware compilation.
  • Enable unified management of quantum processors across different superconducting platforms.

Main Methods:

  • QSteed employs a 4-layer abstraction hierarchy (QPU, StdQPU, SubQPU, VQPU) for processor virtualization.
  • A dedicated database stores calibration data, topology, and noise descriptors for fine-grained management.
  • A modular compiler matches circuits to suitable VPQUs, performing localized optimizations.

Main Results:

  • QSteed was deployed on the Quafu superconducting cluster, validating the virtualization model.
  • Experimental runs confirmed the compiler's efficacy without user code modification.
  • The select-then-compile workflow demonstrated robust compilation for noisy superconducting processors.

Conclusions:

  • QSteed offers a promising architecture for efficient compilation on noisy superconducting quantum computers.
  • The framework supports various superconducting quantum computing platforms.
  • This approach addresses compilation needs in the noisy intermediate-scale quantum era.