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Journal ArticleDOI

Feedback for physicists: A tutorial essay on control

John Bechhoefer
- 31 Aug 2005 - 
- Vol. 77, Iss: 3, pp 783-836
TLDR
In this paper, a tutorial essay aims to give enough of the formal elements of control theory to satisfy the experimentalist designing or running a typical physics experiment and enough to satisfy a theorist wishing to understand its broader intellectual context.
Abstract
Feedback and control theory are important ideas that should form part of the education of a physicist but rarely do. This tutorial essay aims to give enough of the formal elements of control theory to satisfy the experimentalist designing or running a typical physics experiment and enough to satisfy the theorist wishing to understand its broader intellectual context. The level is generally simple, although more advanced methods are also introduced. Several types of applications are discussed, as the practical uses of feedback extend far beyond the simple regulation problems where it is most often employed. Sketches are then provided of some of the broader implications and applications of control theory, especially in biology, which are topics of active research.

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Citations
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The Ensemble Kalman Filter: Theoretical formulation and practical implementation

TL;DR: The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it as mentioned in this paper, and also presents new ideas and alternative interpretations which further explain the success of the EnkF.
Book

Feedback Systems: An Introduction for Scientists and Engineers

TL;DR: Feedback Systems develops transfer functions through the exponential response of a system, and is accessible across a range of disciplines that utilize feedback in physical, biological, information, and economic systems.
Journal ArticleDOI

Optical magnetometry - eScholarship

Dmitry Budker, +1 more
- 01 Apr 2007 - 
TL;DR: In this article, the basic principles of modern optical magnetometers, discuss fundamental limitations on their performance, and describe recently explored applications for dynamical measurements of biomagnetic fields, detecting signals in NMR and MRI, inertial rotation sensing, magnetic microscopy with cold atoms, and tests of fundamental symmetries of nature.
Journal ArticleDOI

Controlling Complex Networks: How Much Energy Is Needed?

TL;DR: This work addresses the physically important issue of the energy required for achieving control by deriving and validating scaling laws for the lower and upper energy bounds.
References
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Journal ArticleDOI

Engineering Aspects of Enzymatic Signal Transduction: Photoreceptors in the Retina

TL;DR: With the example of vertebrate phototransduction cascade, it is demonstrated that all of the relevant engineering parameters are controlled by enzyme concentrations and, from functional considerations, derive bounds on the required protein numbers.
Journal ArticleDOI

Electrostatic ion beam trap for electron collision studies

TL;DR: In this paper, a system combining an ion beam trap and a low energy electron target is described, in which the interaction between electrons and vibrationally cold molecular ions and clusters can be studied.
Journal ArticleDOI

Vibration compensation for high speed scanning tunneling microscopy

TL;DR: In this paper, an inversion-based approach that compensates for the structural vibrations in the scanner and thus, allows STM imaging at high scanning speeds (relative to the smallest resonant vibrational frequency) is presented.
Journal ArticleDOI

Piconewton regime dynamic force microscopy in liquid

TL;DR: In this article, a cantilever in a fluid is driven by a mixed signal composed of a standard driving signal and a feedback signal consisting of the amplified and phase shifted oscillation signal.
Journal ArticleDOI

Bayesian feedback versus Markovian feedback in a two-level atom

TL;DR: In this paper, the authors compare two different approaches to the control of the dynamics of a continuously monitored open quantum system and show that Bayesian feedback is usually superior to Markovian feedback.
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