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

Ampere-Maxwell's Law: Problem-Solving

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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...
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Maxwell-Boltzmann Distribution: Problem Solving01:20

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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
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Heat Capacity: Problem-Solving01:17

Heat Capacity: Problem-Solving

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The heat capacity of a gas is the amount of heat energy required to raise the temperature of a unit mass of gas by one degree Celsius. It is an important thermodynamic property of gases, and its determination is essential in many industrial and scientific applications. Here are the steps to solve problems related to the heat capacities of gases:
Determine the type of gas: The heat capacity of a gas depends on its molecular structure and the degree of freedom of its molecules. Different types of...
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Ampere's Law: Problem-Solving01:31

Ampere's Law: Problem-Solving

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Ampere's law states that for any closed looped path, the line integral of the magnetic field along the path equals the vacuum permeability times the current enclosed in the loop. If the fingers of the right hand curl along the direction of the integration path, the current in the direction of the thumb is considered positive. The current opposite to the thumb direction is considered negative.
Specific steps need to be considered while calculating the symmetric magnetic field distribution...
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Thermal expansion and Thermal stress: Problem Solving01:27

Thermal expansion and Thermal stress: Problem Solving

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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...
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Heating and Cooling Curves02:44

Heating and Cooling Curves

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When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
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Related Experiment Video

Updated: Feb 22, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Temperature Scaling Law for Quantum Annealing Optimizers.

Tameem Albash1,2, Victor Martin-Mayor3,4, Itay Hen1,2

  • 1Information Sciences Institute, University of Southern California, Marina del Rey, California 90292, USA.

Physical Review Letters
|September 27, 2017
PubMed
Summary
This summary is machine-generated.

Finite temperature quantum annealers face scalability limits. To function as competitive optimizers, annealer temperatures must decrease with problem size, following a logarithmic or power-law scaling. This research impacts practical quantum annealer design.

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Area of Science:

  • Quantum computing
  • Computational physics
  • Optimization algorithms

Background:

  • Physical quantum annealers operate at unavoidable finite temperatures.
  • Fixed finite temperature limits the scalability and competitiveness of quantum annealers as optimizers.

Purpose of the Study:

  • To identify a fundamental limitation in fixed finite temperature quantum annealers.
  • To establish a temperature scaling law for quantum annealers to function as scalable optimizers.

Main Methods:

  • Theoretical derivation of a temperature scaling law.
  • Experimental validation of the derived scaling law.
  • Computational simulations to corroborate findings.

Main Results:

  • Demonstrated a fundamental limitation of fixed finite temperature quantum annealers.
  • Derived a temperature scaling law requiring temperature reduction with problem size (logarithmic or power-law).
  • Experimental and simulation results confirmed the derived scaling law.

Conclusions:

  • Quantum annealer performance as scalable optimizers is fundamentally limited by fixed finite temperatures.
  • Annealer temperature must be scaled down with problem size for competitive optimization.
  • Findings have significant implications for the design and application of practical quantum annealers.