The approximationerror in some data is the discrepancy between an exact value and some approximation to it. An approximationerror can occur because the measurement of the data is not precise due to the instruments ... below. nowiki reflist External links MathWorld PercentageError Percentage error Mathapplied stub algebra stub Category Numerical analysis ar bg ca Error d aproximaci de Fehlerschranke es Error de aproximaci n eo Ekarto fr Erreur d approximation ko it Errore ... of an algorithm in numerical analysis indicates how the error is propagated by the algorithm. Overview One commonly distinguishes between the relative error and the absolute error . The absolute error is the absolute value magnitude of the difference between the exact value and the approximation. The relative error is the absolute error divided by the magnitude of the exact value. The percent error is the relative error expressed in terms of per 100. As an example, if the exact value is 50 and the approximation is 49.9, then the absolute error is 0.1 and the relative error is 0.1 50 0.002. The relative error is often used to compare approximations of numbers of widely differing size for example, approximating the number 1,000 with an absolute error of 3 is, in most applications, much worse than approximating the number 1,000,000 with an absolute error of 3 in the first case the relative error is 0.003 and in the second it is only 0.000003. Another example would be if you measured a beaker and read, 5mL. The correct reading would have been 6mL. This means that your error Approximate error would be 16.66666.. error. Definitions Given some value v and its approximation v sub approx sub , the absolute error is math epsilon v v text approx , math where the vertical bars denote the absolute value . If math v ne 0. math the relative error is math eta frac v v text approx v left frac v v text approx v right , math and the percent error is math delta frac v v text approx v times ... more details
. See also col begin col break Approximationerror Congruence relation Estimation Fitness approximation Fermi estimate Linear approximation Newton s method col break Numerical analysis Orders of approximation Runge Kutta methods Successive Approximation ADC Taylor series Least squares col break Wiktionarypar approximation col end Category Approximations Category Numerical analysis bg br Tostadur cs Aproximace da Approksimation de Approximation es Aproximaci n eo Proksimuma kalkulado fr Approximation ko hi is N mundun it Approssimazione he kk nl Benadering ja nn Approksimasjon pl Aproksymacja pt Aproxima o ru simple Approximation ...Unreferenced date September 2007 Certainty An approximation is a representation of something that is not exact, but still close enough to be useful. Although approximation is most often applied to number ..., an approximation may yield a sufficiently accurate solution while reducing the complexity of the problem ... rate of evolutionary algorithms, fitness approximation that leads to build model of the fitness function to choose smart search steps is a good solution. The type of approximation used depends ..., and the savings usually in time and effort that can be achieved by approximation. Science ... measurement s, which are constantly compared to one another. The approximation also refers ... physical laws alone incorporates an inherent source of error, which should be corrected by approximating ... wikitable align right Symbols representing approximation style font size xx large & 8784 general approximation style font size xx large asymptotic analysis Approximation usually occurs when an exact ... number of Significant figures significant digits . Approximation theory is a branch of mathematics, a quantitative part of functional analysis . Diophantine approximation deals with approximations of real number s by rational number s. Related to approximation of functions is the Asymptotic analysis ... more details
is called the approximationerror . Cybernetics The word cybernetics stems from the Ancient Greek Greek ... at Gare Montparnasse Montparnasse , France , 1895 The word error entails different meanings and usages relative to how it is conceptually applied. The concrete meaning of the Latin word error is wandering or straying . Unlike an illusion , an error or a mistake can sometimes be dispelled through knowledge ... moscow.jpg right thumbnail One error and its catastrophic results Napoleon s invasion of Russia Retreat ... between error and mistake as follows quote An error is a deviation from accuracy or correctness. A mistake is an error caused by a fault the fault being misjudgment, carelessness, or forgetfulness ... be an error. The first time it would be an error. The second time it would be a mistake since I should ... norms . See deviance . Gaffes and faux pas can be labels for certain instances of this kind of error ... class value judgments about what linguistic forms should and should not be used. See also Error analysis ... the gaffe in a developmental process that can culminate in stuttering. Medicine See medical error for a description of error in medicine. Science and engineering Image TrafficSignIsraelError.JPG .... In statistics , an errors and residuals in statistics error or residual is not a mistake but rather ... correct value. See also Observational error . In science and engineering in general an error is defined as a difference between the desired and actual performance or behavior of a system ... system s, in which error is defined as the difference between a set point and the process value. An example ... is controlled by the difference the error between the thermostat setting and the sensed air temperature ... avoid the effects of error, whether Hanlon s Razor unintentional or not . Such errors in a system ... error , which includes cognitive bias . Human factors engineering is often applied to designs in an attempt to minimize this type of error by making systems more forgiving or error tolerant . In computational ... more details
unreferenced date March 2008 In science , engineering , and other quantitative disciplines, orders of approximation refer to formal or informal terms for how precise an approximation is, and to indicate progressively more refined approximations in increasing order of precision, a zeroth order approximation, a first order approximation, a second order approximation, and so forth. Formally, an n th order approximation is one where the order of magnitude of the error is at most math x n math , or in terms of big O notation , the error is math O x n . math In suitable circumstances, approximating a function by a Taylor polynomial of degree n yields an n th order approximation, by Taylor s theorem a first order approximation is a linear approximation , and so forth. The term is also used more loosely, as detailed below. Usage in science and engineering Zeroth order approximation also 0th order ... 3,914 people in actuality. This is also sometimes referred to as an order of magnitude approximation. A zeroth order approximation of a function mathematics function that is, mathematics mathematically ... math y 3,3,5 , math math y sim f x 3.67 , math is an approximate fit to the data. First order approximation ... is often given the town has 4 10 sup 3 sup or four thousand residents . A first order approximation ... approximation , straight line with a slope a polynomial of degree 1. For example, math x 0,1,2 ... by simply averaging the y values. Other methods for selecting a constant approximation can be used. Second order approximation also 2nd order is the term scientists use for a decent quality answer ... approximation of a function that is, mathematically determining a formula to fit multiple data ... referred to by number. A third order approximation would be required to fit four data ..., the ordinality of the approximation is not exact, but is used to emphasize its insignificance ... theory Taylor approximation Category Perturbation theory Category Numerical analysis ... more details
Rational approximation may refer to Diophantine approximation , the approximation of real numbers by rational numbers. Pad approximation , the approximation of functions by rational functions. See also Simple rational approximation Mathdab ... more details
scheme . An term may appear when an approximation algorithm introduces a multiplicative error ...In computer science and operations research , approximation algorithms are algorithm s used to find approximate solutions to optimization problem s. Approximation algorithms are often associated with NP ... wants provable solution quality and provable run time bounds. Ideally, the approximation is optimal up to a small constant factor for instance within 5 of the optimal solution . Approximation algorithms ... expensive due to the input size. A typical example for an approximation algorithm is the one ... twice as large as the optimal one. This is a constant factor approximation algorithm with a factor ... be approximated within any factor greater than 1 such a family of approximation algorithms is often called a polynomial time approximation scheme or PTAS . Others are impossible to approximate within ... approximation algorithms emerge from the linear programming relaxation of the integer program. Not all approximation algorithms are suitable for all practical applications. They often use IP LP semidefinite ... which lead to difficult implementation problems. Also, some approximation algorithms have ..., it has now been shown that Johnson s 1974 approximation algorithms for Max SAT, Set Cover, Independent Set and Coloring all achieve the optimal approximation ratio, assuming P NP. Performance guarantees For some approximation algorithms it is possible to prove certain properties about the approximation of the optimum result. For example, in the case of a approximation algorithm A it has been ... the relative performance guarantee . An approximation algorithm has an absolute performance guarantee or bounded error c , if it has been proven for every instance x that math mathrm OPT c leq ... to return solutions with a performance guarantee of at most r n , then A is said to be an r n approximation algorithm and has an approximation ratio of r n . Likewise, a problem with an r n approximation ... more details
In mathematics , Spouge s approximation is a formula for the gamma function due to John L. Spouge. The formula is a modification of Stirling s approximation , and has the form math Gamma z 1 z a z 1 2 e z a left c 0 sum k 1 a 1 frac c k z k varepsilon a z right math where a is an arbitrary positive integer and the coefficients are given by math c 0 sqrt 2 pi , math math c k frac 1 k 1 k 1 k a k 1 2 e k a quad k in 1,2, dots, a 1 . math Spouge has proved that, if Re z 0 and a 2, the relative error in discarding &epsilon sub a sub z is bounded by math ,a 1 2 2 pi a 1 2 . math The formula is similar to the Lanczos approximation , but has some distinct features. Whereas the Lanczos formula exhibits faster convergence, Spouge s coefficients are much easier to calculate and the error can be set arbitrarily low. The formula is therefore feasible for arbitrary precision arithmetic arbitrary precision evaluation of the gamma function. However, special care must be taken to use sufficient precision when computing the sum due to the large size of the coefficients c k, as well as their alternating sign. For example, for a 49, you must compute the sum using about 65 decimal digits of precision in order to obtain the promised 40 decimal digits of accuracy. See also Stirling s approximation Lanczos approximation References Citation last Spouge first John L. year 1994 title Computation of the gamma, digamma, and trigamma functions journal SIAM Journal on Numerical Analysis volume 31 issue 3 pages 931 944 doi 10.1137 0731050 External links http en.literateprograms.org Gamma function with Spouge s formula Mathematica Gamma function with Spouge s formula Mathematica implementation at LiteratePrograms Category Gamma and related functions Category Arbitrary precision algorithms hu Spouge formula numtheory stub ... more details
In mathematics , approximation theory is concerned with how function mathematics function s can best be approximation approximated with simpler function mathematics functions , and with Quantitative property quantitative ly characterization mathematics characterizing the approximationerror errors introduced ... Image Logerror.png thumb 300px Error between optimal polynomial and log x red , and Chebyshev approximation and log x blue over the interval 2, 4 . Vertical divisions are 10 sup 5 sup . Maximum error for the optimal polynomial is 6.07 x 10 sup 5 sup . Image Experror.png thumb 300px Error between optimal polynomial and exp x red , and Chebyshev approximation and exp x blue over the interval 1, 1 . Vertical divisions are 10 sup 4 sup . Maximum error for the optimal polynomial is 5.47 x 10 sup ... related topic is the approximation of functions by generalized Fourier series , that is, approximations ... or Rational function rational ratio of polynomials approximations. The objective is to make the approximation ... itself is chosen in such a way as to minimize the worst case error. That is, the goal is to minimize ... th span degree polynomial that will lead to an error curve that oscillates back and forth between math epsilon math and math epsilon math a total of N 2 times, giving a worst case error of math epsilon ... shown to the right show the error in approximating log x and exp x for N 4. The red ... Impossibleerror.png thumb right 300px Error P x &minus f x for level polynomial red ... of degree N having the property described, that is, it gives rise to an error function that has ... what this error function might look like for N 4. Suppose Q x whose error function is shown in blue to the right is another N degree polynomial that is a better approximation to f than P ... N . Chebyshev approximation One can obtain polynomials very close to the optimal one by expanding ... with rapidly converging power series, if the series is cut off after some term, the total error arising ... more details
In number theory , the field of Diophantine approximation , named after Diophantus of Alexandria , deals with the approximation of real number s by rational number s. The absolute value of the difference ... measure of how good the approximation is. However, since the rational numbers are dense in the real .... So this measure tells us nothing about the quality of the approximation. A better measure of the quality of the approximation is by comparison of the difference to the size of the denominator ... approximation because its denominator is smaller. Approximation to algebraic numbers The theory ... of transcendental numbers. This link between diophantine approximation and transcendental number ... M. Schmidt generalised this to the case of simultaneous approximation. The proofs were difficult ... ref R. J. Duffin and A. C. Schaeffer, Khintchine s problem in metric Diophantine approximation , Duke .... This showed that Diophantine approximation results were closely related to the general problem ... of error terms. Related to uniform distribution is the topic of irregularities of distribution , which ... problems remaining in Diophantine approximation, for example the Littlewood conjecture . Recent ... approach to classical problems in Diophantine approximation. Among its notable successes are the proof ... Khinchin in metric Diophantine approximation have also been obtained within this framework ... J.W.S. Cassels authorlink J. W. S. Cassels title An introduction to Diophantine approximation series ... title Flows on homogeneous spaces and Diophantine approximation on manifolds journal Ann. Math. volume ... year 1995 isbn 0 387 94456 7 Grigory Margulis , Diophantine approximation, lattices and flows on homogeneous ... approximation . Lecture Notes in Mathematics 785. Springer. 1980 1996 with minor corrections ... http people.math.jussieu.fr miw articles pdf HCMUNS10.pdf Diophantine Approximation historical ... Approximation Category Number theory Category Diophantine approximation de Diophantische Approximation ... more details
The eikonal approximation is a method of approximation useful in wave scattering equations within the realms of quantum mechanics , optics , quantum electrodynamics , and partial wave expansion Informal description The main advantage the eikonal approximation offers is that the equations reduce to a differential equation in a single variable. This reduction into a single variable is the result of the straight line approximation or the eikonal approximation which allows us to choose the straight line as a special direction. Relation to the WKB approximation The early steps involved in the eikonal approximation in quantum mechanics are very closely related to the WKB approximation . It, like the eikonal approximation, reduces the equations into a differential equation in a single variable. But the difficulty with the WKB approximation is that this variable is described by the trajectory of the particle which, in general, is complicated. Formal description Empty section date July 2010 See also Eikonal equation References http www.nhn.ou.edu shajesh eikonal sp.pdf Eikonal Approximation K. V. Shajesh Department of Physics and Astronomy, University of Oklahoma Category Mathematical analysis Math stub Quantum stub ... more details
Boussinesq approximation may refer to several modelling concepts as introduced by Joseph Valentin Boussinesq 1842 1929 , a French mathematician and physicist known for advances in fluid dynamics Boussinesq approximation buoyancy for buoyancy driven flows for small density differences in the fluid Boussinesq approximation water waves for long waves propagating on the surface of a fluid layer under the action of gravity Turbulence modeling and Viscosity Eddy viscosity eddy viscosity for the Boussinesq approximation resulting in the use of an eddy viscosity to model the turbulence Reynolds stresses disambig ... more details
the approximation by the trapezoid rule of the integral math int 1 n ln x , rm d x n ln n n 1, math and the error in this approximation is given by the Euler Maclaurin formula math begin align ln n frac ... &minus n approaches unity as n increases. In mathematics , Stirling s approximation or Stirling s formula is an approximation for large factorial s. It is named after James Stirling mathematician ... written math n sim sqrt 2 pi n left frac n e right n. math If we want the approximation for natural ... ln n n . math Derivation The formula, together with precise estimates of its error, can be derived ... the equations above yields the approximation formula in its logarithmic form math ln n n ... int 1 n ln x , rm d x n ln n n 1. math Speed of convergence and error estimates Image StirlingErrorGraphBB.svg right thumb The relative error in a truncated Stirling series vs. n, for 1 to 5 terms ... n frac 1 12n . math Stirling s formula is in fact the first approximation to the following series ... cdots right . math The first graph in this section shows the relative error vs. n , for 1 through all 5 terms listed above. Image StirlingError1.svg right thumb The relative error in a truncated Stirling series vs. the number of terms used. As math n to infty math , the error in the truncated series ... graph, which shows the relative error vs. the number of terms in the series. More precisely, let ... ln S n, t n right math , which, when small, is essentially the relative error. The asymptotic expansion ... cdot5 1 cdot7 1 n 7 cdots. math In this case, it is known that the error in truncating the series is always ..., with an error term of math O z m 1 2 math when the first m terms are used. The corresponding approximation may now be written math Gamma z sqrt frac 2 pi z left frac z e right z left 1 O left ... 4 cdots end align math which converges when math Re z 0 math . A version suitable for calculators The approximation ... sine function. This approximation is good to more than 8 decimal digits for z with a real ... more details
in the primed quantities, lead to the derivation of Oseen s approximation math U math math partial v ... of Oseen s approximation it showed that the resultant hydrodynamic force drag is given by math ... of math left 3 over 8 right N R math . Error in Stokes Solution Navier Stokes equations read math triangledown ... r 2 right math The error is then given by the ratio math U math math partial v over partial z 1 over ... unphysical and is known as Stokes paradox. Modifications to Oseen s Approximation One may ... U and the Oseen s approximation is more accurate. ref Fung, Yuan cheng. Biomechanics Circulation ... more details
Refimprove date December 2009 In particle physics , the quenched approximation is an approximation often used in lattice gauge theory in which the quantum loops of fermion s in Feynman diagram s are neglected. Equivalently, the corresponding one loop determinants are set to one. This approximation is often forced upon the physicists because the calculation with the Grassmann number s is computationally very difficult in lattice gauge theory. Recent calculations ref name urlRev. Mod. Phys. 82, 1349 2010 Nonperturbative QCD simulations with 2 1 flavors of improved staggered quarks cite web url http link.aps.org doi 10.1103 RevModPhys.82.1349 author A. Bazavov et. al title Rev. Mod. Phys. 82, 1349 2010 Nonperturbative QCD simulations with 2 1 flavors of improved staggered quarks format work accessdate doi 10.1103 RevModPhys.82.1349 ref typically avoid the quenched approximation. References Reflist DEFAULTSORT Quenched Approximation Category Lattice models Quantum stub pt Aproxima o temperada ... more details
In geometric optics , the paraxial approximation is a small angle approximation used in Gaussian optics and Ray tracing physics ray tracing of light through an optical system such as a lens optics lens . ref name Greivenkamp cite book first John E. last Greivenkamp year 2004 title Field Guide to Geometrical Optics publisher SPIE others SPIE Field Guides vol. FG01 isbn 0 8194 5294 7 pages 19 20 ref A paraxial ray is a Ray optics ray which makes a small angle to the optical axis of the system, and lies close to the axis throughout the system. ref name Greivenkamp Generally, this allows three important approximations for in radian s for calculation of the ray s path ref name Greivenkamp math begin align sin theta & approx theta tan theta & approx theta end align math and math cos theta approx 1 math The paraxial approximation is used in Gaussian optics and first order raytracing. ref name Greivenkamp Ray transfer matrix analysis is one method that uses the approximation. In some cases, the second order approximation is also called paraxial . To second order, the approximations above for sine and tangent do not change the next term in their Taylor series expansion is zero , while for cosine the second order approximation is math cos theta approx 1 theta 2 over 2 . math The paraxial approximation is accurate within 0.5 for angles under about 10 Citation needed date May 2011 but its inaccuracy grows significantly for larger angles. For larger angles it is often necessary to distinguish between meridional ray s, which lie in a plane containing the optical axis , and sagittal ray s, which do not. References reflist External links http demonstrations.wolfram.com ParaxialApproximationAndTheMirror Paraxial Approximation and the Mirror by David Schurig, The Wolfram Demonstrations Project . Category Geometrical optics ca Aproximaci paraxial de Paraxiale Optik es Aproximaci n paraxial fr Approximation de Gauss it Approssimazione parassiale hu Paraxi lis k zel t s nl Paraxiale ... more details
In mathematics , an approximation to the identity refers to a sequence or net that converges to the identity in some algebra. Specifically, it can mean Nascent delta function , most commonly Mollifier , more narrowly Approximate identity , more abstractly disambig ... more details
In computer science , hardness of approximation is a field that studies the algorithmic complexity of finding near optimal solutions to optimization problem s. It complements the study of approximation algorithm s by proving, for certain problems, a limit on the factors with which their solution can be efficiently approximated. Typically such limits show a factor of approximation beyond which a problem becomes NP hard , implying that finding a polynomial time approximation for the problem is impossible unless NP P . Some hardness of approximation results, however, are based on other hypotheses, a notable one among which is the unique games conjecture . Since the early 1970s it was known that many optimization problems could not be solved in polynomial time unless NP P , but in many of these problems the optimal solution could be efficiently approximated to a certain degree. In the early 1990s, with the development of PCP complexity PCP theory, it became clear that there is a limit to the approximability of many of these optimization problems for many optimization problems there is a threshold beyond which they are NP hard to approximate. Hardness of approximation theory deals with studying the approximation threshold of such problems. Examples For an example of an NP hard optimization problem that is hard to approximate, see set cover . See also PCP theorem Further reading http www.cs.berkeley.edu luca pubs inapprox.ps Survey, a good starter by Luca Trevisan External links http www.cs.washington.edu education courses 533 05au CSE 533 The PCP Theorem and Hardness of Approximation, Autumn 2005 , syllabus from the University of Washington , Venkatesan Guruswami and Ryan O Donnell Category Computational complexity theory Category Mathematical optimization comp sci theory stub ... more details
Sparse approximation also referred to as sparse decomposition is the problem of estimating a Sparsity sparse multi dimensional vector, satisfying a System of linear equations linear system of equations given high dimensional observed data and a Design matrix design matrix . Sparse approximation techniques have found wide use in applications such as image processing, audio processing, biology, and document analysis. Sparse decomposition Noiseless observations Consider a System of linear equations linear system of equations math x D alpha math , where math D math is an math m times p math matrix mathematics matrix math m ll p math and math x in mathbb R m, alpha in mathbb R p math . math D math , called as the dictionary or the design matrix, is given. The problem is to estimate the signal math alpha math , subject to the constraint that it is sparse. The underlying motivation for sparse decomposition problems is that even though the observed values are in high dimensional math m math space, the actual signal is organized in some lower dimensional subspace math k ll m math . Sparsity implies that only a few components of math x math are non zero and the rest are zero. This implies that math x math can be decomposed as a linear combination of only a few math m times 1 math vectors in math D math , called atoms. math D math itself is over complete math m ll p . math Such vectors are called as the Basis vectors basis of math x math . However, unlike other Dimensionality reduction dimensionality reducing decomposition techniques such as Principal component analysis Principal Component Analysis , the basis vectors are not required to be orthogonal. The sparse decomposition problem ... to the basic sparse approximation problem. Structured sparsity In the original version of the problem ... point is available. Hence, the data fitting error is defined as the sum of the math l 2 math ... approximation problem. Matching pursuit Matching Pursuit is a greedy iterative algorithm for approximatively ... more details
Infobox Journal cover discipline mathematics abbreviation Constr. Approx. publisher Springer Science Business Media Springer country United States U.S. ISSN 0176 4276 eISSN 1432 0940 CODEN CONSA? history 1985 to present website http www.math.vanderbilt.edu ca Constructive Approximation is an international mathematics journal dedicated to Approximations and Expansions and related research in computation, function theory, functional analysis, interpolation spaces and interpolation of operators, numerical analysis, space of functions, special functions, and applications. ref cite web url http www.springer.com west home?SGWID 4 102 70 1056700 detailsPage journal description&changeHeader true&SHORTCUT www.springer.com journal 00365 about title Constructive Approximation Numerical Analysis Journals, Books & Online Media ¦ Springer accessdate 2007 04 30 ref References references External links http www.math.vanderbilt.edu ca Constructive Approximation web site Category Mathematics journals Category Approximation theory Category English language journals Category Publications established in 1985 Category Springer academic journals Category Bimonthly journals math journal stub sci journal stub ... more details
Orphan date December 2008 Cleanup rewrite date May 2009 A fundamental principle in the field of acoustics , the acoustic approximation states that an acoustic wave is created by a small, adiabatic, pressure ripple riding on a comparatively large equilibrium bias pressure . Typically, the acoustic pressure is on the order of a few ppm of the equilibrium pressure. By extension, the acoustic approximation also guarantees that an acoustic wave travels at a speed exactly equal to the local speed of sound , such that the Mach number math M 1 math See also Sound References reflist External links Category Acoustics physics stub ... more details
The need for function approximations arises in many branches of applied mathematics , and computer science in particular. In general, a function approximation problem asks us to select a function mathematics function among a well defined class that closely matches approximates a target function in a task specific way. One can distinguish two major classes of function approximation problems First, for known target functions approximation theory is the branch of numerical analysis that investigates how certain known functions for example, special function s can be approximated by a specific class of functions for example, polynomial s or rational function s that often have desirable properties inexpensive computation, continuity, integral and limit values, etc. . Second, the target function, call it g , may be unknown instead of an explicit formula, only a set of points of the form x , g x is provided. Depending on the structure of the domain mathematics domain and codomain of g , several techniques for approximating g may be applicable. For example, if g is an operation on the real number s, techniques of interpolation , extrapolation , regression analysis , and curve fitting can be used. If the codomain range or target set of g is a finite set, one is dealing with a statistical classification classification problem instead. To some extent the different problems regression, classification, fitness approximation have received a unified treatment in statistical learning theory , where they are viewed as supervised learning problems. See also Radial basis function network Fitness approximation DEFAULTSORT Function Approximation Category Statistical models Category Statistical approximations mathanalysis stub statistics stub hr Aproksimacija funkcija sr ... more details
Otheruses WKB disambiguation In mathematical physics , the WKB approximation or WKB method is a method for finding approximate solutions to linear partial differential equations with spatially varying coefficients. It is typically used for a semiclassical calculation in quantum mechanics in which the wavefunction is recast as an exponential function, semiclassically expanded, and then either the amplitude or the phase is taken to be slowly changing. The name is an acronym for Wentzel Kramers Brillouin . It is also known as the LG or Liouville Green method. Other often used acronyms for the method include JWKB and WKBJ , where the J stands for Jeffreys. Brief history This method is named after physicists Gregor Wentzel Wentzel , Hendrik Anthony Kramers Kramers , and L on Brillouin Brillouin , who all developed it in 1926. In 1923, mathematician Harold Jeffreys had developed a general method of approximating solutions to linear, second order differential equations, which includes the Schr dinger ... chapter A Survey on the Liouville Green WKB approximation for linear difference equations of the second ... parameter . The method of approximation is as follows For a differential equation math epsilon ... can take two signs the first order WKB approximation will be a linear combination of the two math y ... the smallest error achieved by the WKB method is at best of the order of the last included term ... n max math will be large, and the minimum error of the asymptotic series will be exponentially small ... right , math math B x 2 A x B x 0. math Next, the semiclassical approximation is invoked. This means ... tunneling Slowly varying envelope approximation References Reflist Modern references cite book author ... url http farside.ph.utexas.edu teaching jk1 lectures node70.html title The W.K.B. Approximation year 2002 An application of the WKB approximation to the scattering of radio waves from the ionosphere ... de WKB N herung es Aproximaci n WKB fr Approximation BKW ko WKB it Approssimazione WKB nl Wentzel ... more details
Unreferenced stub auto yes date December 2009 Orphan date December 2009 The Coopmans Approximation is a method for approximating a fractional order integrator in a continuous process with constant space complexity . The most correct and accurate methods for calculating the fractional integral require a record of all previous history, and therefore would require a constant space complexity solution O n , where n is the number of samples measured for the complete history. The fractor is an analog component useful in control systems . In order to model the components behavior in a digital simulation, or replace the fractor in a digital controller, a linear solution is untenable. In order to reduce the space complexity however, it is necessary to lose information in some way. The Coopmans Approximation is a robust, simple method that uses a simple convolution to compute the fractional integral, then recycles old data back through the convolution. The convolution sets up a weighting table as described by the fractional calculus , which varies based on the size of the table, the sampling rate of the system, and the order of the integral. Once computed the weighting table remains static. The data table is initialized as all zeros, which represents a lack of activity for all previous time. New data is added to the data buffer in the fashion of a ring buffer, so that the newest point is written over the oldest data point. The convolution is solved by multiplying corresponding elements from the weight and data tables, and summing the resulting products. As described, the loss of the old data by overwriting with new data will cause echoes in a continuous system as disturbances that were ... Approximation, where the old data point, multiplied by its corresponding weight term, as added to the newest ... history. This approximation has the desirable effect of removing the echo, while preserving the space complexity of the solution. The negative effect of the approximation is that the phase ... more details
Image MazurGes.jpg thumb right The construction of a Banach space without the approximation property earned Per Enflo a live goose in 1972, which had been promised by Stanislaw Mazur in 1936. In mathematics , a Banach space is said to have the approximation property AP , if every compact operator is a limit of finite rank operator s. The converse is always true. Every Hilbert space has this property. There are, however, Banach space s which do not Per Enflo published the first counterexample in a 1973 article. However, a lot of work in this area was done by Grothendieck 1955 . Later many other counterexamples were found. The space of bounded operator s on math ell 2 math does not have the approximation property Szankowski . The spaces math ell p math for math p neq 2 math and math c 0 math see Sequence space have closed subspaces that do not have the approximation property. Definition A Banach space math X math is said to have the approximation property, if, for every compact set math K subset X math and every math varepsilon 0 math , there is an operator mathematics operator math T colon X to X math of finite rank so that math Tx x leq varepsilon math , for every math x in K math . Some other flavours of the AP are studied Let math X math be a Banach space and let math 1 leq lambda infty math . We say that math X math has the math lambda math approximation property math lambda ... bounded approximation property BAP , if it has the math lambda math AP for some math lambda math . A Banach space is said to have metric approximation property MAP , if it is 1 AP. A Banach space is said to have compact approximation property CAP , if in the definition of AP an operator of finite ... G. Bartle title MR0402468 53 6288 Review of Per Enflo s A counterexample to the approximation problem ... 402468 Per Enflo Enflo, P. A counterexample to the approximation property in Banach spaces. Acta Math ... Association of America. Kwapie , S. On Enflo s example of a Banach space without the approximation ... more details
distinguish2 the Born Oppenheimer approximation In scattering theory and, in particular in quantum mechanics , the Born approximation consists of taking the incident field in place of the total field as the driving field at each point in the scatterer. Born approximation is named after Max Born , winner of the 1954 Nobel Prize for physics. It is the perturbation theory perturbation method applied to scattering by an extended body. It is accurate if the scattered field is small, compared to the incident field, in the scatterer. For example, the radar scattering of radio waves by a light styrofoam column can be approximated by assuming that each part of the plastic is polarized by the same electric field that would be present at that point without the column, and then calculating the scattering as a radiation integral over that polarization distribution. Born approximation to the Lippmann Schwinger equation The Lippmann Schwinger equation for the scattering state math vert Psi mathbf p pm rangle math with a momentum p and out going or in going &minus boundary condition s is math vert Psi mathbf p pm rangle vert Psi mathbf p circ rangle G circ E p pm i0 V vert Psi mathbf p pm rangle math where math G circ math is the free particle Green s function , 0 is a positive infinitesimal quantity ... approximation math vert Psi mathbf p pm rangle vert Psi mathbf p circ rangle G circ E p pm i0 V vert ... point of the Born series. Applications The Born approximation is used in quite different physical contexts. In neutron scattering , the first order Born approximation is almost always adequate ... , or grazing incidence small angle scattering . Distorted wave Born approximation DWBA The Born approximation is simplest when the incident waves math vert Psi mathbf p circ rangle math are plane .... In the distorted wave Born approximation DWBA , the incident waves are solutions math vert Psi mathbf ... i0 V 1 vert Psi mathbf p 1 pm rangle math and the Born approximation math vert Psi mathbf p pm rangle ... more details
Encyclopedia
top
