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

Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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 problem,...
Thermal expansion and Thermal stress: Problem Solving01:27

Thermal expansion and Thermal stress: Problem Solving

San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55 °C.
Thermal Stress01:09

Thermal Stress

If the temperature of an object is changed while it is prevented from expanding or contracting, the object is subjected to stress. The stress is compressive if the object expands in the absence of constraint and tensile if it contracts. This stress resulting from temperature change is known as thermal stress. It can be quite large and can cause damage. To avoid this stress, engineers may design components so they can expand and contract freely. For instance, on highways, gaps are deliberately...
Temperature and Thermal Equilibrium01:11

Temperature and Thermal Equilibrium

Heat and temperature are essential concepts for everyone every day. The study of heat and temperature is part of an area of physics known as thermodynamics. It is not always easy to distinguish heat and temperature.
The concept of temperature has evolved from the common concepts of hot and cold. The scientific definition of temperature explains more than just our sense of hot and cold. Temperature is operationally defined as the quantity measured with a thermometer. Furthermore, temperature is...
Quantifying Heat02:46

Quantifying Heat

Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a higher temperature. When the atoms and...
Thermal Strain01:19

Thermal Strain

Thermal strain is a concept that arises when we consider how temperature changes affect structures. Unlike the conventional assumption that structures remain constant under load, real-world scenarios often involve temperature fluctuations that can significantly impact these structures. Consider a homogeneous rod with a uniform cross-section resting freely on a flat horizontal surface. If the rod's temperature increases, the rod elongates. This elongation is proportional to the temperature...

You might also read

Related Articles

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

Sort by
Same author

Author Correction: EXCRETE workflow enables deep proteomics of the microbial extracellular environment.

Communications biology·2026
Same author

Detecting genuine multipartite entanglement in multi-qubit devices with restricted measurements.

Nature communications·2026
Same author

Advanced Quality and Comparability Assessment of mRNA-Loaded Lipid Nanoparticles: Absolute Size Distribution Profiles and Structure from AF4-Coupled Light and X-ray Scattering Measurements.

Analytical chemistry·2026
Same author

Entropic Costs of Extracting Classical Ticks from a Quantum Clock.

Physical review letters·2025
Same author

Precision is not limited by the second law of thermodynamics.

Nature physics·2025
Same author

Integrating AF4 and Py-GC-MS for Combined Size-Resolved Polymer-Compositional Analysis of Nanoplastics with Application to Wastewater.

Analytical chemistry·2025
Same journal

Bound states in the continuum in plasmonic structures.

Reports on progress in physics. Physical Society (Great Britain)·2026
Same journal

Unlocking complex optical vortices with flat optics.

Reports on progress in physics. Physical Society (Great Britain)·2026
Same journal

Pseudo-Hermitian magnon dynamics.

Reports on progress in physics. Physical Society (Great Britain)·2026
Same journal

Uniaxial-stress-induced magnetic transitions in the triangular-lattice antiferromagnet PdCrO<sub>2</sub>.

Reports on progress in physics. Physical Society (Great Britain)·2026
Same journal

From intuition to optimization: a review of inverse design applied to optical nanotweezers.

Reports on progress in physics. Physical Society (Great Britain)·2026
Same journal

A less-for-more metamaterial paradigm via Laplace-Helmholtz correspondence.

Reports on progress in physics. Physical Society (Great Britain)·2026
See all related articles
  1. Home
  3. Autonomous Quantum Processing Unit: An Autonomous Thermal Computing Machine & Its Physical Limitations.
  1. Home
  3. Autonomous Quantum Processing Unit: An Autonomous Thermal Computing Machine & Its Physical Limitations.

Related Experiment Video

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

Autonomous quantum processing unit: an autonomous thermal computing machine & its physical limitations.

Florian Meier1, Marcus Huber1, Paul Erker1

  • 1Atominstitut, Technische Universität Wien Atominstitut, Atominstitut, Stadionallee 2, 1020 Wien, Vienna, Vienna, 1020, Austria.

Reports on Progress in Physics. Physical Society (Great Britain)
|June 12, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

We introduce the autonomous Quantum Processing Unit (aQPU), a self-contained quantum computation model. This framework integrates thermodynamic resource analysis directly into quantum computing, advancing fundamental research.

Keywords:
Open Quantum SystemsQuantum ComputationQuantum Thermodynamics

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

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping
14:58

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

Published on: June 3, 2015

Related Experiment 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

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

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping
14:58

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

Published on: June 3, 2015

Area of Science:

  • Quantum Computing
  • Thermodynamics
  • Computational Complexity

Background:

  • Quantum computation typically relies on external classical control, obscuring resource requirements.
  • A self-contained model is crucial for understanding fundamental computational and thermodynamic limits.

Purpose of the Study:

  • To develop a fully self-contained quantum computation framework.
  • To model quantum computation within autonomous thermal machines.
  • To investigate the interplay of thermodynamic cost, complexity, speed, and fidelity.

Main Methods:

  • Developed the autonomous Quantum Processing Unit (aQPU) framework.
  • Modeled quantum computation as an autonomous thermal machine.
  • Integrated internal quantum timekeeping, instruction register, and memory systems.

Main Results:

  • The aQPU framework provides a unified model for quantum computation and its resource costs.
  • Enables direct investigation of thermodynamic resource requirements for quantum algorithms.
  • Facilitates analysis of the trade-offs between speed, fidelity, and resource consumption.

Conclusions:

  • The aQPU represents a significant step towards understanding the fundamental limits of quantum computation.
  • This self-contained approach is vital for analyzing the thermodynamic costs inherent in quantum processing.
  • The framework opens new avenues for optimizing quantum algorithms based on resource efficiency.