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This page lists examples of magnetic induction B in teslas and gauss produced by various sources, grouped by orders of magnitude. The magnetic flux density does not measure how strong a magnetic field is, but only how strong the magnetic flux is in a given point or at a given distance (usually right above the magnet's surface).
The gauss is the unit of magnetic flux density B in the system of Gaussian units and is equal to Mx/cm 2 or g/Bi/s 2, while the oersted is the unit of H-field. One tesla (T) corresponds to 10 4 gauss, and one ampere (A) per metre corresponds to 4π × 10 −3 oersted .
One difference between the Gaussian and SI systems is in the factor 4π in various formulas that relate the quantities that they define. With SI electromagnetic units, called rationalized, [3] [4] Maxwell's equations have no explicit factors of 4π in the formulae, whereas the inverse-square force laws – Coulomb's law and the Biot–Savart law – do have a factor of 4π attached to the r 2.
The above equations are the microscopic version of Maxwell's equations, expressing the electric and the magnetic fields in terms of the (possibly atomic-level) charges and currents present. This is sometimes called the "general" form, but the macroscopic version below is equally general, the difference being one of bookkeeping.
USB power, used for example to charge a cell phone or a digital camera. [18] Also one of the most common digital circuit supply voltages for both TTL and CMOS technologies. 6 V A common voltage for medium-size electric lanterns. [19] A voltage for older electric systems of automobiles. Deca-10 1: 12 V Typical car battery [20] Hecto-10 2: 100 ...
In physics (specifically electromagnetism), Gauss's law, also known as Gauss's flux theorem (or sometimes Gauss's theorem), is one of Maxwell's equations. It is an application of the divergence theorem , and it relates the distribution of electric charge to the resulting electric field .
Consider e.g. the case where the output of the Gaussian process corresponds to a magnetic field; here, the real magnetic field is bound by Maxwell's equations and a way to incorporate this constraint into the Gaussian process formalism would be desirable as this would likely improve the accuracy of the algorithm.
Output measurements are assumed to be corrupted by Gaussian noise and the initial state, likewise, is assumed to be a Gaussian random vector. Under these assumptions an optimal control scheme within the class of linear control laws can be derived by a completion-of-squares argument. [ 1 ]