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Magnetic Fields

Magnetic Fields

A moving charge or a current creates a magnetic field in the surrounding space, in addition to its electric field. The magnetic field exerts a force on any other moving charge or current that is present in the field. Like an electric field, the magnetic field is also a vector field. At any position, the direction of the magnetic field is defined as the direction in which the north pole of a compass needle points.
A magnetic field is defined by the force that a charged particle experiences...

Carrier Generation and Recombination

Carrier Generation and Recombination

Carrier generation is the process by which electron-hole pairs (EHPs) are created within the semiconductor. In direct-bandgap semiconductors, such as gallium arsenide (GaAs), this occurs efficiently when energy absorption prompts valence electrons to leap into the conduction band, leaving behind holes.
This process is given by the generation rate G and is efficient due to the conservation of momentum between the valence band maximum and conduction band minimum.
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Electromagnetic Fields

Electromagnetic Fields

Electric fields generated by static charges, often referred to as electrostatic fields, are characteristically different from electric fields created by time-varying magnetic fields. While the former is a conservative field, implying that no net work is done on a test charge if it goes around in a complete loop in the field, the latter is, by definition, not a conservative field; net work is done, and it is proportional to the rate of change of magnetic flux.
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An important distinction exists between the electric field induced by a changing magnetic field and the electrostatic field produced by a fixed charge distribution. Specifically, the induced electric field is nonconservative because it does not work in moving a charge over a closed path. In contrast, the electrostatic field is conservative and does no net work over a closed path. Hence, electric potential can be associated with the electrostatic field but not the induced field. The following...

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Once the fields have been calculated using Maxwell's four equations, the Lorentz force equation gives the force that the fields exert on a charged particle moving with a certain velocity. The Lorentz force equation combines the force of the electric field and of the magnetic field on the moving charge. Maxwell's equations and the Lorentz force law together encompass all the laws of electricity and magnetism. The symmetry that Maxwell introduced into his mathematical framework may not be...

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

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

Published on: September 8, 2023

Mean field theory for nonequilibrium network reconstruction.

Yasser Roudi¹, John Hertz

¹NORDITA, Stockholm, Sweden.

Physical Review Letters

|March 17, 2011

Summary

This study presents a new method for inferring network interactions in dynamic, non-equilibrium systems. The approach successfully recovers interactions in a complex model using correlation functions.

Area of Science:

Complex systems
Network science
Statistical physics

Background:

Progress in inferring network structures is limited to equilibrium systems satisfying detailed balance.
Nonequilibrium systems present significant challenges for interaction inference.

Purpose of the Study:

To introduce a novel approach for inferring interaction structures in nonequilibrium complex networks.
To apply and validate the method on an asymmetrically coupled, synchronously updated Sherrington-Kirkpatrick model.

Main Methods:

Derivation of an exact iterative inversion algorithm.
Development of approximations using dynamical mean-field and Thouless-Anderson-Palmer equations.
Utilizing equal-time and one-time-step-delayed correlation functions to express interactions.

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Main Results:

Successfully recovered interactions in the specified nonequilibrium model.
Demonstrated the efficacy of the iterative algorithm and approximations.

Conclusions:

The developed approach provides a viable method for analyzing nonequilibrium systems.
This work opens new avenues for understanding complex network dynamics beyond equilibrium conditions.