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

Adiabatic Processes for an Ideal Gas01:18

Adiabatic Processes for an Ideal Gas

3.1K
When an ideal gas is compressed adiabatically, that is, without adding heat, work is done on it, and its temperature increases. In an adiabatic expansion, the gas does work, and its temperature drops. Adiabatic compressions actually occur in the cylinders of a car, where the compressions of the gas-air mixture take place so quickly that there is no time for the mixture to exchange heat with its environment. Nevertheless, because work is done on the mixture during the compression, its...
3.1K
Work Done in an Adiabatic Process01:20

Work Done in an Adiabatic Process

3.2K
Consider the adiabatic compression of an ideal gas in the cylinder of an automobile diesel engine. The gasoline vapor is injected into the cylinder of an automobile engine when the piston is in its expanded position. The temperature, pressure, and volume of the resulting gas-air mixture are 20 °C, 1.00 x 105 N/m2, and 240 cm3 , respectively. The mixture is then compressed adiabatically to a volume of 40 cm3. Note that, in the actual operation of an automobile engine, the compression is not...
3.2K
Pressure and Volume in an Adiabatic Process01:27

Pressure and Volume in an Adiabatic Process

2.7K
Free expansion of a gas is an adiabatic process. However, there are few differences between free expansion and adiabatic expansion. During free expansion, no work is done, and there is no change in internal energy. But, for an adiabatic expansion, work is done, and there is a change in internal energy. During an adiabatic process, the relation between the pressure and volume is obtained from the condition for the adiabatic process, that is, 
2.7K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.5K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.5K
Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

208
Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
208
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

155
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
155

You might also read

Related Articles

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

Sort by
Same author

Non-classicality and the effect of one photon.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2024
Same author

Non-reciprocity in photon polarization based on direction of polarizer under gravitational fields.

Scientific reports·2024
Same author

A Differential-Geometric Approach to Quantum Ignorance Consistent with Entropic Properties of Statistical Mechanics.

Entropy (Basel, Switzerland)·2023
Same author

Negativity vs. purity and entropy in witnessing entanglement.

Scientific reports·2023
Same author

Gaussian Amplitude Amplification for Quantum Pathfinding.

Entropy (Basel, Switzerland)·2022
Same author

Complexity and efficiency of minimum entropy production probability paths from quantum dynamical evolutions.

Physical review. E·2022
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jul 15, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.2K

Quantum-Walk-Inspired Dynamic Adiabatic Local Search.

Chen-Fu Chiang1, Paul M Alsing2

  • 1Department of Computer Science, State University of New York Polytechnic Institute, Utica, NY 13203, USA.

Entropy (Basel, Switzerland)
|September 28, 2023
PubMed
Summary
This summary is machine-generated.

We resolved the challenge of translating quantum search algorithms between Continuous Time Quantum Walk (CTQW) and Adiabatic Quantum Computing (AQC) frameworks. Our modified approach maintains optimal running time for AQC, matching CTQW efficiency.

Keywords:
adiabatic path schedulingadiabatic quantum computingcatalyst Hamiltonianquantum walk

More Related Videos

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

591
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.6K

Related Experiment Videos

Last Updated: Jul 15, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.2K
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

591
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.6K

Area of Science:

  • Quantum computing
  • Quantum algorithms
  • Computational complexity

Background:

  • Translating search algorithms between Continuous Time Quantum Walk (CTQW) and Adiabatic Quantum Computing (AQC) frameworks presents irreconcilability issues.
  • AQC requires a constant energy gap in the Hamiltonian to follow the CTQW evolution path, posing a significant challenge.

Purpose of the Study:

  • To address the constant energy gap issue in AQC when translating CTQW search algorithms.
  • To maintain the optimal running time of CTQW within the AQC framework.
  • To explore adaptive scheduling for improved local search in Grover-inspired AQC.

Main Methods:

  • Modified the CTQW-inspired AQC catalyst Hamiltonian from an XZ operator to a Z oracle operator.
  • Conducted simulations to validate the proposed approach.
  • Investigated adaptive scheduling for the catalyst Hamiltonian and its coefficient function.

Main Results:

  • The modified catalyst Hamiltonian resolves the constant energy gap issue.
  • Simulations demonstrate that the proposed AQC approach with the modified Hamiltonian achieves optimal running time, equivalent to CTQW.
  • Adaptive scheduling shows potential for enhancing adiabatic local search in Grover-inspired AQC.

Conclusions:

  • The modified Z oracle catalyst Hamiltonian effectively bridges the CTQW and AQC frameworks for search algorithms.
  • The proposed method preserves the computational efficiency of CTQW within AQC.
  • Further research into adaptive scheduling can optimize adiabatic local search performance.