Fractional Geometric Calculus: Toward A Unified Mathematical Language for Physics and Engineering

Size: px
Start display at page:

Download "Fractional Geometric Calculus: Toward A Unified Mathematical Language for Physics and Engineering"

Transcription

1 Fractional Geometric Calculus: Towar A Unifie Mathematical Language for Physics an Engineering Xiong Wang Center of Chaos an Complex Network, Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR, China. ( wangxiong8686@gmail.com). Abstract: This paper iscuss the longstaning problems of fractional calculus such as too many efinitions while lacking physical or geometrical meanings, an try to exten fractional calculus to any imension. First, some ifferent efinitions of fractional erivatives, such as the Riemann-Liouville erivative, the Caputo erivative, Kolwankar s local erivative an Jumarie s moifie Riemann-Liouville erivative, are iscusse an conclue that the very reason for introucing fractional erivative is to stuy nonifferentiable functions. Then, a concise an essentially local efinition of fractional erivative for one imension function is introuce an its geometrical interpretation is given. Base on this simple efinition, the fractional calculus is extene to any imension an the Fractional Geometric Calculus is propose. Geometric algebra provie an powerful mathematical framework in which the most avance concepts moern physic, such as quantum mechanics, relativity, electromagnetism, etc., can be expresse in this framework graciously. At the other han, recent evelopments in nonlinear science an complex system suggest that scaling, fractal structures, an nonifferentiable functions occur much more naturally an abunantly in formulations of physical theories. In this paper, the extene framework namely the Fractional Geometric Calculus is propose naturally, which aims to give a unifying language for mathematics, physics an science of complexity of the 21st century. Keywors: geometric algebra, geometric calculus, fractional calculus, nonifferentiable function 1. INTRODUCTION It seems a general pattern of our unerstaning of nature to evolve from integer to fraction. In number theory, we iscovery integer number firstly, then we introuce fractional number in orer to o ivision an finally we introuce real number to form a soli base for analysis. In geometry, for a long time we only know the typical geometry objects like point, line, surface an volume with integer number imensions. But recent iscovery of fractal geometry has completely change an enlarge people s unerstaning about the geometry. Fractal is even consiere as the true geometry of nature, see Manelbrot (1983). In calculus, it also follow this path. At the beginning, the motivation of this extension from integer to fractional ifferential operator is just formal, but lack of substantial physical meaning. From the beauty of the mathematical formality, we hope that the semigroup of powers D α will form a continuous semigroup with parameter α, insie which the original iscrete semigroup of D n for integer n can be recovere as a subgroup, see Samko et al. (1993); Miller an Ross (1993). Moreover, for centuries we can only o calculus to a relatively rare an special kin of sufficiently well-behave functions, i.e. the ifferentiable function or even smooth function. But later we come to realize that the typical an prevalent continuous functions are nowhere-ifferentiable functions like the Weierstrass function. The classical calculus with integer orer is just powerless on this type of function. In this paper, First, some ifferent efinitions of fractional erivatives, such as the Riemann-Liouville, the Caputo erivative, Kolwankar s local erivative Kolwankar an Gangal (1997); Kolwankar et al. (1996)an Jumarie s moifie Riemann-Liouville erivative Jumarie (26), are iscusse. Then it s argue that the very reason for introucing fractional erivative is to stuy nonifferentiable functions. A concise an essentially local efinition of fractional erivative for one imension function is introuce an its geometrical interpretation is given. Base on this simple efinition, the fractional calculus is extene to any imension an the Fractional Geometric Calculus is propose. the paper is submitte for consieration of the best stuent paper awar.

2 2. REVIEW AND REMARKS OF SOME DEFINITIONS 2.1 The Riemann-Liouville approach Fractional integration Accoring to the Riemann-Liouville approach to fractional calculus, the notion of fractional integral of orer α (α > ) for a function f(x), is a natural generalization of the well known Cauchy formula for repeate integration, which reuces the calculation of the n fol primitive of a function f(x) to a single integral of convolution type. In our notation the Cauchy formula reas I n f(x) := f ( n) (x) = 1 (n 1)! x where N is the set of positive integers. Taking avantage of the Gamma function Γ(z) := which has the property (x t) n 1 f(t) t, n N (2.1) e u u z 1 u, Re {z} > (2.2) Γ(z + 1) = z Γ(z), (n 1)! = Γ(n), it s very natural to exten the above formula from positive integer values of the inex to any positive real values an efines the Fractional Integral of orer α > : Definition 1. I α f(x) := f ( α) (x) = 1 x (x t) α 1 f(t) t. (2.3) Γ(α) where α is in the set of positive real numbers. Fractional ifferentiation The efinition of fractional ifferentiation is somehow more subtle than the fractional integration. A straightforwar way to efine fractional ifferentiation is to o enough fractional integration firstly, then take integer ifferentiation (of course, one can o in another orer, just as the Caputo approach). That is to introuce a positive integer m such that m 1 < α m, then efine the fractional erivative of orer α > : Definition 2. D α f(t) := D m I m α f(t), namely f (α) (x) := α x α I α α f (2.4) where enotes the Ceiling function which map a real number to the smallest following integer. For complementation, ifferentiation of any real number orer α coul be efine as, α f (α) (x) := x α I α α f(x) α > f(x) α = I α f(x) α <. (2.5) (1) The funamental relations hol x Iα+1 f(x) = I α f(x), I α (I β f) = I β (I α f) = I α+β f, (2.6) the latter of which is a semigroup property fractional for integration operator. But unfortunately the erivative operator D α is quite ifferent an significantly more complex, for D α is neither commutative nor aitive in general. (2) Take a constant function f(x) = 1 for example: x (I 1 2 f)(x) = x x x ( 1 x ) Γ( 1 2 ) (x t) 1 2.1t ( x ) (x t) 1 2 t x (2 x) x ([ 2(x t) 1 2 The fractional ifferentiation of constant functions is not necessary zero from this efinition, which somehow obscures the physical meaning of these fractional erivatives as some kin of velocity. (3) The omain an bounary conitions of the functions must be explicitly chosen. Information about the omain an bounary conition of the functions is neee for calculation, so the fractional erivative is not a local property of the function. Therefore, unlike the integral orer erivative, the fractional orer erivative at a point x is not etermine by an arbitrarily small neighborhoo of x. This obscures the geometric meaning of these fractional erivatives. (4) To partially solve the above problem, many people use as the base point, instea of : I α f(x) := f ( α) (x) = 1 x (x t) α 1 f(t) t. Γ(α) (2.7) 2.2 The Caputo approach Alternatively, we can take integer ifferentiation firstly, then o fractional integration. The Caputo fractional erivative: Definition 3. ( f (α) (x) := I α α α ) f x α ] x ) (2.8) (1) This Caputo fractional erivative prouces zero from constant functions. (2) But it is easy to see that the Caputo efinition for the fractional erivative is in a sense, more restrictive than the Riemann-Liouville efinition because it require the function to have higher orer ifferentiability, but it is often the case that f (α) (x) may exist whilst f (x) oes not. These troublesome features greatly reuce its scope of application.

3 2.3 The Jumarie approach Moifie Riemann Liouville Jumarie s moifie Riemann Liouville fractional erivative is efine by Definition 4. f (α) 1 x (x) := (x t) α (f(t) f()) t, (2.9) Γ(1 α) x where α a real number on the interval (, 1). (1) If f() =, then f (α) is equal to the Riemann Liouville fractional erivative of f of orer α. (2) has the avantages of both the stanar Riemann Liouville an Caputo fractional erivatives. The fractional erivative of a constant is zero, as esire. (3) It is efine for arbitrary continuous (nonifferentiable) functions. (4) But this efinition is still an nonlocal efinition. Information about the omain an bounary conition of the functions is still neee, thus has no goo geometric interpretation. (3) It shoul be applicable to a large class of functions (i.e. continuous but nonifferentiable, or even generalize function) which are not ifferentiable in the classical sense. (4) It shoul have reasonable geometric interpretation, like the classical one. (5) The calculation shoul be easy. 3. THE VERY REASON FOR INTRODUCING FRACTIONAL DERIVATIVE 3.1 Discussion on semigroup property It is generally believe that the motivation for introucing fractional calculus is that we want the semigroup of powers D a to form a continuous semigroup with parameter a, insie which the original iscrete semigroup of D n for integer n can be recovere as a subgroup. But we argue that this is ue to we limit our scope of iscussion in the very special smooth function. Of course, we can calculate the fractional erivative of the common smooth function, like the following: 2.4 Kolwankar-Gangal approach Kolwankar-Gangal local fractional erivative Kolwankar an Gangal (henceforth K-G) has propose a local fractional erivative by introucing Definition 5. If, for a function f : [, 1] IR, the limit ID q q (f(x) f(y)) f(y) = lim x y (x y) q (2.1) exists an is finite, then we say that the local fractional erivative (LFD) of orer q ( < q < 1), at x = y, exists. (1) The operator in the RHS is the Riemann-Liouville erivative, so the K-G local fractional erivative can be equivalently expresse as f (α) (x) x=x := 1 Γ(1 α) lim x x x x f(t) f(x ) x (x t) α t, (2.11) where α a real number on the interval (, 1). (2) The fractional erivative of a constant is zero because the subtraction of f(x ). (3) The erivative is efine by the limiting process x x, so only local information near x is neee. (4) Although this efinition in local in nature, the geometric interpretation is still vague. One can harly have any geometric intuition irectly from this abstract efinition. 2.5 Final remarks We have reviewe several ifferent efinitions about fractional erivative, an each has some avantages an isavantages. But we still hope to have a efinition which can have all the following merits: (1) It shoul be local in nature, thus oes not rely on information of omain an bounary conitions. (2) The erivative of constant function shoul be zero. 1 2 x 1 2 ( 1 2 x) = 1 2 2π 1 1 x 1 2 x 1 2 x 2 2 = 2π Γ( ) Γ( )x1 = 2π 1 2 Γ( 3 2 ) Γ(1) x = 2 πx 2 π! = 1, It s simple an elegant from the pure mathematical point of view, but the semigroup property is not always satisfie for erivative operator. Moreover, it s har to give any geometrical interpretation of this kin 1 2 erivative. 3.2 Differentiability class of function The most basic functions x n, e x, sin x are smooth function. For smooth function we can use power series to approximate an express any smooth function. In mathematical analysis, a ifferentiability class is a classification of functions accoring to the properties of their erivatives. Higher orer ifferentiability classes correspon to the existence of more erivatives. Functions that have erivatives of all orers are calle smooth. Definition 6. The function f is sai to be of class C k if the erivatives f, f,..., f (k) exist an are continuous (except for a finite number of points or a measure zero set of points). The function f is sai to be of class C, or smooth, if it has erivatives of all orers. Uner the above efinition, the class C consists of all continuous functions. The class C 1 consists of all ifferentiable functions whose erivative is continuous; such functions are calle continuously ifferentiable. Thus, a C 1 function is exactly a function whose erivative exists an is of class C. The relation hol: C... C n... C 2 C 1 C G, where G enote the generalize function. In

4 particular, C k is containe in C k 1 for every k, an there are examples to show that this containment is strict. One interesting property is if f C m an g C n, then f + g C min(m,n). 3.3 Non-ifferentiable fuction It s interesting that, in the above relation C k+1 is always a proper (in fact, a measure zero) subset of C k. So coul there be some non-trivial examples which are C but not C 1 almost everywhere? The answer is yes, Weierstrass type of functions are typical such examples, see Berry an Lewis (198). What s more, the Weierstrass function is far from being an isolate or special example. In fact, it is the ominant an typical continuous functions, in the math sense. In physics sense, it s also very important to stuy this kin of fractal curve. Observe path of a quantum mechanical particle are known to be fractals an are continuous but non-ifferentiable, see Abbott an Wise (1981); Sornette (199); Cannata an Ferrari (1988). A simple example of such a parametrization is the well known Weierstrass function given by Wλ(t) s = λ (D 2)k sin λ k t k=1 where λ > 1 an 1 < D < 2. The graph of Wλ s (t) is known to be a fractal curve with box-imension D. (1) C is the set of all continuous functions. (2) C α for < α < 1 is the set functions which the α erivatives exist an are continuous. (3) C k for any positive integer k is the set of all ifferentiable functions whose 1 erivative is in C k 1 (4) C a for any positive real number a = k + α is the set of all functions whose α erivative is in C k (5) C is the intersection of the sets C k So we argue that, the semigroup property may not be a necessary an essential conition when introucing fractional calculus. The classical calculus is enough to eal with smooth function an the geometrical interpretation is natural an intuitive. So why o we nee to introuce some other erivative but has no intuitive interpretation for smooth function? For smooth function, there is no nee for something more. For nonifferentiable functions, things are quite ifferent an classical calculus is not enough. One of the main reason to introuce something new in math is when we want to enlarge our scope of iscussion an fin the ol tool is not applicable. We argue that he very reason for introucing fractional erivative is to stuy nonifferentiable functions. 4. GEOMETRICAL MEANING OF FRACTIONAL DERIVATIVE 4.1 Geometrical meaning of orinary erivative The geometrical meaning of orinary erivative is simple an intuitive: For smooth function f which is ifferentiable at x, the local behavior of f aroun point x can be approximate by using the orinary erivative: f(x + h) f(x) + f (x)h (4.1) Fig. 1. Example of Weierstrass function with D = 1.8 The orinary erivative gives the linear approximation of smooth function. Using Taylor series an higher orer erivative, we have f(x+h) f(x)+f (x)h+ f (x) 2! h 2 + f (3) (x) h (4.2) 3! 3.4 Fractional ifferentiability class of function So like the question of introucing fractional erivative, here we ask the following questions: (1) Coul there be fractional ifferentiability class of function? (2) What s the structure of the space C 1 2, or generally the space of C a? (3) What s the representation of these kin of fractional ifferentiability function space? (4) What s the relation between fractional ifferentiability function space an fractional erivative. In general, the classes C a for any non-negative real number a can be efine recursively as following: Fig. 2. The orinary erivative gives the linear approximation. Here we expect the fractional erivative to have the similar geometrical meaning. We hope for non-ifferentiable

5 functions, the fractional erivative coul give some kin approximation of its local behavior. 5. A SIMPLE DEFINITION DIRECTLY FROM GEOMETRICAL MEANING We expect that the fractional erivative coul give nonlinear (power law) approximation of the local behavior of non-ifferentiable functions: f(x + h) f(x) + f (α) (x) Γ(1 + α) hα (5.1) in which the function f is not ifferentiable because f (x) α so the classical erivative f/x will iverge. Note that the purpose of aing the coefficient Γ(1 + α) is just to make the formal consistency with the Taylor series. We can give a very simple efinition irectly from the above meaning: Definition 7. For function f C α, < α < 1, the fractional erivative is efine as f (α) (x) := Γ(1 + α) lim h + f(t + h) f(t) h α (5.2) Also the fractional integral can formally efine as: Definition 8. For function f, the fractional integral of orer < α < 1 is a function f ( α) (x) := g(x) which satisfy g (α) (x) = Γ(1 + α) lim h + g(t + h) g(t) h α = f(x) (5.3) (1) The erivative of constant function is zero. (2) It coul be applicable to a large class of functions C α < α < 1 which are not ifferentiable in the classical sense. (3) It o have reasonable geometric interpretation, similar to the classical one. The fractional erivative coul give nonlinear (power law) approximation of the local behavior of non-ifferentiable functions. (4) The calculation of erivative is easy. (5) Last but not least, this efinition is local by nature. This property facilitate the generalization of one variable fractional erivative to vector erivative, which is very har if the nonlocal omain an bounary conition of the function is neee for calculation. 6. GEOMETRIC CALCULUS In orer to generalize the one variable fractional erivative to vector erivative, we make use of the language of geometric calculus (GC) instea of Gibbs vector calculus. Geometric algebra provie an powerful mathematical framework in which the most avance concepts moern physic, such as quantum mechanics, relativity, electromagnetism, etc., can be expresse in this framework graciously. There are many great avantages of the GC formalism. For example, the cross prouct only applies in three imensional space, because in four imensions there is an infinity of perpenicular vectors. But in GC formalism, the inner prouct an outer prouct are unifie an both have perfect generalization. Gibbs vector calculus is able to reuce Maxwell s twelve equations own to four, but in GC formalism Maxwell equation can be written in one single elegant equation with a spacetime operator which is reversible. Please see Hestenes an Sobczyk (1984); Hestenes (1966, 1999); Hestenes et al. (21); Gull et al. (1993); Doran et al. (1993, 1996); Lasenby et al. (1998)for further information about geometric calculus. The funamental ifferential operator is the erivative with respect to the position vector x (any imension). This is given the symbol, an is efine in terms of its irectional erivatives, with the erivative in the a irection of a general multivector M efine by M(x + ɛa) M(x) a M(x) = lim. (6.1) ɛ + ɛ Similarly we can efine the Fractional Geometric Calculus(FGC) as following: Definition 9. The Fractional Geometric Calculus is given the symbol α, an is efine in terms of its fractional irectional erivatives, with the fractional erivative in the a irection of a general multivector M efine by a α M(x) = lim ɛ + M(x + ɛa) M(x) ɛ α. (6.2) The α acts algebraically as a vector, as well as inheriting a calculus from its irectional erivatives. As an explicit example, consier the {γ µ } frame introuce above. In terms of this frame we can write the position vector x as x µ γ µ, with x = t, x 1 = x etc. an {x, y, z} a usual set of Cartesian components for the restframe of the γ vector. From the efinition it is clear that γ µ α = α x µ (6.3) which we abbreviate to α µ. From the efinition we can now write α = γ µ α µ = γ α t + γ 1 α x + γ 2 α y + γ 3 α z. (6.4) 7. CONCLUSION In this paper, some ifferent efinitions of fractional erivatives are iscusse an conclue that the very reason for introucing fractional erivative is to stuy nonifferentiable functions. Then, a concise an essentially local efinition of fractional erivative for one imension function is introuce an its geometrical interpretation is given. Base on this simple efinition, the fractional calculus is extene to any imension an the Fractional Geometric Calculus is propose. There are still many open questions: (1) Is it possible to give an explicit expression of f ( α) (t) through f(t) an α. That means a efinition of some kin integration operator corresponing to the new kin of fractional ifferential operator. (2) For Weierstrass function like the above, it has a fixe s, thus coul o α erivative with a fixe α. How to eal with nowhere ifferentiable function which has variable α(t)? (3) For what kin of f(t), there coul be non-trivial f (α) (t) an f ( α) (t)?

6 Fig. 3. Family tree for Fractional Geometric Calculus, extene from figure in (4) Weierstrass function are C but not C 1 almost everywhere. An interesting question is how to give explicit expression of all the continuous everywhere but nowhere ifferentiable functions, just like we can use power series to approximate an express any smooth function. (5) Can we express some basic nowhere ifferentiable functions, an fin the fractional erivative of these basic functions? Is it possible to give a fractional calculus table for nowhere ifferentiable functions, just like the classical calculus? (6) Is it possible to give an example function f C 1 but not C 2 almost everywhere? Does the integral of Weierstrass function belong to this class? There shoul be such functions, but it s har to image it. How it looks like? Finally, we summarize the history of Fractional Geometric Calculus in the following figure 3. Doran, C., Lasenby, A., Gull, S., Somaroo, S., an Challinor, A. (1996). Spacetime algebra an electron physics. Avances in imaging an electron physics, 95, Gull, S., Lasenby, A., an Doran, C. (1993). Imaginary numbers are not realthe geometric algebra of spacetime. Founations of Physics, 23(9), Hestenes, D. (1966). Space-time algebra, volume 1. Goron an Breach Lonon. Hestenes, D. (1999). New founations for classical mechanics, volume 99. Springer. Hestenes, D., Li, H., an Rockwoo, A. (21). New algebraic tools for classical geometry. Geometric computing with Cliffor algebras, 4, Hestenes, D. an Sobczyk, G. (1984). Cliffor algebra to geometric calculus: a unifie language for mathematics an physics, volume 5. Springer. Jumarie, G. (26). Moifie riemann-liouville erivative an fractional taylor series of nonifferentiable functions further results. Computers & Mathematics with Applications, 51(9-1), Kolwankar, K. an Gangal, A. (1997). Höler exponents of irregular signals an local fractional erivatives. Pramana, 48(1), Kolwankar, K., Gangal, A., et al. (1996). Fractional ifferentiability of nowhere ifferentiable functions an imensions. Chaos An Interisciplinary Journal of Nonlinear Science, 6(4), 55. Lasenby, A., Doran, C., an Gull, S. (1998). Gravity, gauge theories an geometric algebra. Philosophical Transactions of the Royal Society of Lonon. Series A: Mathematical, Physical an Engineering Sciences, 356(1737), Manelbrot, B. (1983). The fractal geometry of nature. Wh Freeman. Miller, K. an Ross, B. (1993). An introuction to the fractional calculus an fractional ifferential equations. Samko, S., Kilbas, A., an Marichev, O. (1993). Fractional integrals an erivatives: theory an applications. Sornette, D. (199). Brownian representation of fractal quantum paths. European Journal of Physics, 11, 334. ACKNOWLEDGEMENTS Thanks my supervisor for his selfless support! REFERENCES Abbott, L. an Wise, M. (1981). Dimension of a quantum mechanical path. Am. J. Phys, 49(1), Berry, M. an Lewis, Z. (198). On the weierstrassmanelbrot fractal function. Proceeings of the Royal Society of Lonon. A. Mathematical an Physical Sciences, 37(1743), Cannata, F. an Ferrari, L. (1988). Dimensions of relativistic quantum mechanical paths. Am. J. Phys, 56(8), Doran, C., Lasenby, A., an Gull, S. (1993). States an operators in the spacetime algebra. Founations of physics, 23(9),

Schrödinger s equation.

Schrödinger s equation. Physics 342 Lecture 5 Schröinger s Equation Lecture 5 Physics 342 Quantum Mechanics I Wenesay, February 3r, 2010 Toay we iscuss Schröinger s equation an show that it supports the basic interpretation of

More information

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x) Y. D. Chong (2016) MH2801: Complex Methos for the Sciences 1. Derivatives The erivative of a function f(x) is another function, efine in terms of a limiting expression: f (x) f (x) lim x δx 0 f(x + δx)

More information

II. First variation of functionals

II. First variation of functionals II. First variation of functionals The erivative of a function being zero is a necessary conition for the etremum of that function in orinary calculus. Let us now tackle the question of the equivalent

More information

6 General properties of an autonomous system of two first order ODE

6 General properties of an autonomous system of two first order ODE 6 General properties of an autonomous system of two first orer ODE Here we embark on stuying the autonomous system of two first orer ifferential equations of the form ẋ 1 = f 1 (, x 2 ), ẋ 2 = f 2 (, x

More information

Linear First-Order Equations

Linear First-Order Equations 5 Linear First-Orer Equations Linear first-orer ifferential equations make up another important class of ifferential equations that commonly arise in applications an are relatively easy to solve (in theory)

More information

Lagrangian and Hamiltonian Mechanics

Lagrangian and Hamiltonian Mechanics Lagrangian an Hamiltonian Mechanics.G. Simpson, Ph.. epartment of Physical Sciences an Engineering Prince George s Community College ecember 5, 007 Introuction In this course we have been stuying classical

More information

A Note on Exact Solutions to Linear Differential Equations by the Matrix Exponential

A Note on Exact Solutions to Linear Differential Equations by the Matrix Exponential Avances in Applie Mathematics an Mechanics Av. Appl. Math. Mech. Vol. 1 No. 4 pp. 573-580 DOI: 10.4208/aamm.09-m0946 August 2009 A Note on Exact Solutions to Linear Differential Equations by the Matrix

More information

Table of Common Derivatives By David Abraham

Table of Common Derivatives By David Abraham Prouct an Quotient Rules: Table of Common Derivatives By Davi Abraham [ f ( g( ] = [ f ( ] g( + f ( [ g( ] f ( = g( [ f ( ] g( g( f ( [ g( ] Trigonometric Functions: sin( = cos( cos( = sin( tan( = sec

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson JUST THE MATHS UNIT NUMBER 10.2 DIFFERENTIATION 2 (Rates of change) by A.J.Hobson 10.2.1 Introuction 10.2.2 Average rates of change 10.2.3 Instantaneous rates of change 10.2.4 Derivatives 10.2.5 Exercises

More information

Lecture 2 Lagrangian formulation of classical mechanics Mechanics

Lecture 2 Lagrangian formulation of classical mechanics Mechanics Lecture Lagrangian formulation of classical mechanics 70.00 Mechanics Principle of stationary action MATH-GA To specify a motion uniquely in classical mechanics, it suffices to give, at some time t 0,

More information

On The Leibniz Rule And Fractional Derivative For Differentiable And Non-Differentiable Functions

On The Leibniz Rule And Fractional Derivative For Differentiable And Non-Differentiable Functions On The Leibniz Rule And Fractional Derivative For Differentiable And Non-Differentiable Functions Xiong Wang Center of Chaos and Complex Network, Department of Electronic Engineering, City University of

More information

Quantum Mechanics in Three Dimensions

Quantum Mechanics in Three Dimensions Physics 342 Lecture 20 Quantum Mechanics in Three Dimensions Lecture 20 Physics 342 Quantum Mechanics I Monay, March 24th, 2008 We begin our spherical solutions with the simplest possible case zero potential.

More information

The Exact Form and General Integrating Factors

The Exact Form and General Integrating Factors 7 The Exact Form an General Integrating Factors In the previous chapters, we ve seen how separable an linear ifferential equations can be solve using methos for converting them to forms that can be easily

More information

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold CHAPTER 1 : DIFFERENTIABLE MANIFOLDS 1.1 The efinition of a ifferentiable manifol Let M be a topological space. This means that we have a family Ω of open sets efine on M. These satisfy (1), M Ω (2) the

More information

Calculus of Variations

Calculus of Variations Calculus of Variations Lagrangian formalism is the main tool of theoretical classical mechanics. Calculus of Variations is a part of Mathematics which Lagrangian formalism is base on. In this section,

More information

PDE Notes, Lecture #11

PDE Notes, Lecture #11 PDE Notes, Lecture # from Professor Jalal Shatah s Lectures Febuary 9th, 2009 Sobolev Spaces Recall that for u L loc we can efine the weak erivative Du by Du, φ := udφ φ C0 If v L loc such that Du, φ =

More information

Lecture 6: Calculus. In Song Kim. September 7, 2011

Lecture 6: Calculus. In Song Kim. September 7, 2011 Lecture 6: Calculus In Song Kim September 7, 20 Introuction to Differential Calculus In our previous lecture we came up with several ways to analyze functions. We saw previously that the slope of a linear

More information

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs Lectures - Week 10 Introuction to Orinary Differential Equations (ODES) First Orer Linear ODEs When stuying ODEs we are consiering functions of one inepenent variable, e.g., f(x), where x is the inepenent

More information

Math 1271 Solutions for Fall 2005 Final Exam

Math 1271 Solutions for Fall 2005 Final Exam Math 7 Solutions for Fall 5 Final Eam ) Since the equation + y = e y cannot be rearrange algebraically in orer to write y as an eplicit function of, we must instea ifferentiate this relation implicitly

More information

Euler equations for multiple integrals

Euler equations for multiple integrals Euler equations for multiple integrals January 22, 2013 Contents 1 Reminer of multivariable calculus 2 1.1 Vector ifferentiation......................... 2 1.2 Matrix ifferentiation........................

More information

Switching Time Optimization in Discretized Hybrid Dynamical Systems

Switching Time Optimization in Discretized Hybrid Dynamical Systems Switching Time Optimization in Discretize Hybri Dynamical Systems Kathrin Flaßkamp, To Murphey, an Sina Ober-Blöbaum Abstract Switching time optimization (STO) arises in systems that have a finite set

More information

UNDERSTANDING INTEGRATION

UNDERSTANDING INTEGRATION UNDERSTANDING INTEGRATION Dear Reaer The concept of Integration, mathematically speaking, is the "Inverse" of the concept of result, the integration of, woul give us back the function f(). This, in a way,

More information

Many problems in physics, engineering, and chemistry fall in a general class of equations of the form. d dx. d dx

Many problems in physics, engineering, and chemistry fall in a general class of equations of the form. d dx. d dx Math 53 Notes on turm-liouville equations Many problems in physics, engineering, an chemistry fall in a general class of equations of the form w(x)p(x) u ] + (q(x) λ) u = w(x) on an interval a, b], plus

More information

Sturm-Liouville Theory

Sturm-Liouville Theory LECTURE 5 Sturm-Liouville Theory In the three preceing lectures I emonstrate the utility of Fourier series in solving PDE/BVPs. As we ll now see, Fourier series are just the tip of the iceberg of the theory

More information

Lie symmetry and Mei conservation law of continuum system

Lie symmetry and Mei conservation law of continuum system Chin. Phys. B Vol. 20, No. 2 20 020 Lie symmetry an Mei conservation law of continuum system Shi Shen-Yang an Fu Jing-Li Department of Physics, Zhejiang Sci-Tech University, Hangzhou 3008, China Receive

More information

Agmon Kolmogorov Inequalities on l 2 (Z d )

Agmon Kolmogorov Inequalities on l 2 (Z d ) Journal of Mathematics Research; Vol. 6, No. ; 04 ISSN 96-9795 E-ISSN 96-9809 Publishe by Canaian Center of Science an Eucation Agmon Kolmogorov Inequalities on l (Z ) Arman Sahovic Mathematics Department,

More information

Least-Squares Regression on Sparse Spaces

Least-Squares Regression on Sparse Spaces Least-Squares Regression on Sparse Spaces Yuri Grinberg, Mahi Milani Far, Joelle Pineau School of Computer Science McGill University Montreal, Canaa {ygrinb,mmilan1,jpineau}@cs.mcgill.ca 1 Introuction

More information

Separation of Variables

Separation of Variables Physics 342 Lecture 1 Separation of Variables Lecture 1 Physics 342 Quantum Mechanics I Monay, January 25th, 2010 There are three basic mathematical tools we nee, an then we can begin working on the physical

More information

MATH2231-Differentiation (2)

MATH2231-Differentiation (2) -Differentiation () The Beginnings of Calculus The prime occasion from which arose my iscovery of the metho of the Characteristic Triangle, an other things of the same sort, happene at a time when I ha

More information

Introduction to Markov Processes

Introduction to Markov Processes Introuction to Markov Processes Connexions moule m44014 Zzis law Gustav) Meglicki, Jr Office of the VP for Information Technology Iniana University RCS: Section-2.tex,v 1.24 2012/12/21 18:03:08 gustav

More information

On the number of isolated eigenvalues of a pair of particles in a quantum wire

On the number of isolated eigenvalues of a pair of particles in a quantum wire On the number of isolate eigenvalues of a pair of particles in a quantum wire arxiv:1812.11804v1 [math-ph] 31 Dec 2018 Joachim Kerner 1 Department of Mathematics an Computer Science FernUniversität in

More information

Section 7.1: Integration by Parts

Section 7.1: Integration by Parts Section 7.1: Integration by Parts 1. Introuction to Integration Techniques Unlike ifferentiation where there are a large number of rules which allow you (in principle) to ifferentiate any function, the

More information

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions Working Paper 2013:5 Department of Statistics Computing Exact Confience Coefficients of Simultaneous Confience Intervals for Multinomial Proportions an their Functions Shaobo Jin Working Paper 2013:5

More information

Math 115 Section 018 Course Note

Math 115 Section 018 Course Note Course Note 1 General Functions Definition 1.1. A function is a rule that takes certain numbers as inputs an assigns to each a efinite output number. The set of all input numbers is calle the omain of

More information

ELEC3114 Control Systems 1

ELEC3114 Control Systems 1 ELEC34 Control Systems Linear Systems - Moelling - Some Issues Session 2, 2007 Introuction Linear systems may be represente in a number of ifferent ways. Figure shows the relationship between various representations.

More information

Math Notes on differentials, the Chain Rule, gradients, directional derivative, and normal vectors

Math Notes on differentials, the Chain Rule, gradients, directional derivative, and normal vectors Math 18.02 Notes on ifferentials, the Chain Rule, graients, irectional erivative, an normal vectors Tangent plane an linear approximation We efine the partial erivatives of f( xy, ) as follows: f f( x+

More information

The Principle of Least Action

The Principle of Least Action Chapter 7. The Principle of Least Action 7.1 Force Methos vs. Energy Methos We have so far stuie two istinct ways of analyzing physics problems: force methos, basically consisting of the application of

More information

Math 342 Partial Differential Equations «Viktor Grigoryan

Math 342 Partial Differential Equations «Viktor Grigoryan Math 342 Partial Differential Equations «Viktor Grigoryan 6 Wave equation: solution In this lecture we will solve the wave equation on the entire real line x R. This correspons to a string of infinite

More information

Calculus in the AP Physics C Course The Derivative

Calculus in the AP Physics C Course The Derivative Limits an Derivatives Calculus in the AP Physics C Course The Derivative In physics, the ieas of the rate change of a quantity (along with the slope of a tangent line) an the area uner a curve are essential.

More information

Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling.

Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling. Chapter 8 Analytic Functions Stuents nee encouragement. So if a stuent gets an answer right, tell them it was a lucky guess. That way, they evelop a goo, lucky feeling. 1 8.1 Complex Derivatives -Jack

More information

Global Optimization for Algebraic Geometry Computing Runge Kutta Methods

Global Optimization for Algebraic Geometry Computing Runge Kutta Methods Global Optimization for Algebraic Geometry Computing Runge Kutta Methos Ivan Martino 1 an Giuseppe Nicosia 2 1 Department of Mathematics, Stockholm University, Sween martino@math.su.se 2 Department of

More information

Math 11 Fall 2016 Section 1 Monday, September 19, Definition: A vector parametric equation for the line parallel to vector v = x v, y v, z v

Math 11 Fall 2016 Section 1 Monday, September 19, Definition: A vector parametric equation for the line parallel to vector v = x v, y v, z v Math Fall 06 Section Monay, September 9, 06 First, some important points from the last class: Definition: A vector parametric equation for the line parallel to vector v = x v, y v, z v passing through

More information

Section 7.2. The Calculus of Complex Functions

Section 7.2. The Calculus of Complex Functions Section 7.2 The Calculus of Complex Functions In this section we will iscuss limits, continuity, ifferentiation, Taylor series in the context of functions which take on complex values. Moreover, we will

More information

Differentiation Rules Derivatives of Polynomials and Exponential Functions

Differentiation Rules Derivatives of Polynomials and Exponential Functions Derivatives of Polynomials an Exponential Functions Differentiation Rules Derivatives of Polynomials an Exponential Functions Let s start with the simplest of all functions, the constant function f(x)

More information

Lecture Introduction. 2 Examples of Measure Concentration. 3 The Johnson-Lindenstrauss Lemma. CS-621 Theory Gems November 28, 2012

Lecture Introduction. 2 Examples of Measure Concentration. 3 The Johnson-Lindenstrauss Lemma. CS-621 Theory Gems November 28, 2012 CS-6 Theory Gems November 8, 0 Lecture Lecturer: Alesaner Mąry Scribes: Alhussein Fawzi, Dorina Thanou Introuction Toay, we will briefly iscuss an important technique in probability theory measure concentration

More information

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim QF101: Quantitative Finance September 5, 2017 Week 3: Derivatives Facilitator: Christopher Ting AY 2017/2018 I recoil with ismay an horror at this lamentable plague of functions which o not have erivatives.

More information

4. Important theorems in quantum mechanics

4. Important theorems in quantum mechanics TFY4215 Kjemisk fysikk og kvantemekanikk - Tillegg 4 1 TILLEGG 4 4. Important theorems in quantum mechanics Before attacking three-imensional potentials in the next chapter, we shall in chapter 4 of this

More information

Define each term or concept.

Define each term or concept. Chapter Differentiation Course Number Section.1 The Derivative an the Tangent Line Problem Objective: In this lesson you learne how to fin the erivative of a function using the limit efinition an unerstan

More information

Topic 7: Convergence of Random Variables

Topic 7: Convergence of Random Variables Topic 7: Convergence of Ranom Variables Course 003, 2016 Page 0 The Inference Problem So far, our starting point has been a given probability space (S, F, P). We now look at how to generate information

More information

Optimization Notes. Note: Any material in red you will need to have memorized verbatim (more or less) for tests, quizzes, and the final exam.

Optimization Notes. Note: Any material in red you will need to have memorized verbatim (more or less) for tests, quizzes, and the final exam. MATH 2250 Calculus I Date: October 5, 2017 Eric Perkerson Optimization Notes 1 Chapter 4 Note: Any material in re you will nee to have memorize verbatim (more or less) for tests, quizzes, an the final

More information

Vectors in two dimensions

Vectors in two dimensions Vectors in two imensions Until now, we have been working in one imension only The main reason for this is to become familiar with the main physical ieas like Newton s secon law, without the aitional complication

More information

Laplace s Equation in Cylindrical Coordinates and Bessel s Equation (II)

Laplace s Equation in Cylindrical Coordinates and Bessel s Equation (II) Laplace s Equation in Cylinrical Coorinates an Bessel s Equation (II Qualitative properties of Bessel functions of first an secon kin In the last lecture we foun the expression for the general solution

More information

Math 210 Midterm #1 Review

Math 210 Midterm #1 Review Math 20 Miterm # Review This ocument is intene to be a rough outline of what you are expecte to have learne an retaine from this course to be prepare for the first miterm. : Functions Definition: A function

More information

Geometric Algebra Approach to Fluid Dynamics

Geometric Algebra Approach to Fluid Dynamics Geometric Algebra Approach to Flui Dynamics Carsten Cibura an Dietmar Hilenbran Abstract In this work we will use geometric algebra to prove a number of well known theorems central to the fiel of flui

More information

MATHEMATICS BONUS FILES for faculty and students

MATHEMATICS BONUS FILES for faculty and students MATHMATI BONU FIL for faculty an stuents http://www.onu.eu/~mcaragiu1/bonus_files.html RIVD: May 15, 9 PUBLIHD: May 5, 9 toffel 1 Maxwell s quations through the Major Vector Theorems Joshua toffel Department

More information

A. Incorrect! The letter t does not appear in the expression of the given integral

A. Incorrect! The letter t does not appear in the expression of the given integral AP Physics C - Problem Drill 1: The Funamental Theorem of Calculus Question No. 1 of 1 Instruction: (1) Rea the problem statement an answer choices carefully () Work the problems on paper as neee (3) Question

More information

5.4 Fundamental Theorem of Calculus Calculus. Do you remember the Fundamental Theorem of Algebra? Just thought I'd ask

5.4 Fundamental Theorem of Calculus Calculus. Do you remember the Fundamental Theorem of Algebra? Just thought I'd ask 5.4 FUNDAMENTAL THEOREM OF CALCULUS Do you remember the Funamental Theorem of Algebra? Just thought I' ask The Funamental Theorem of Calculus has two parts. These two parts tie together the concept of

More information

Calculus of Variations

Calculus of Variations 16.323 Lecture 5 Calculus of Variations Calculus of Variations Most books cover this material well, but Kirk Chapter 4 oes a particularly nice job. x(t) x* x*+ αδx (1) x*- αδx (1) αδx (1) αδx (1) t f t

More information

Calculus and optimization

Calculus and optimization Calculus an optimization These notes essentially correspon to mathematical appenix 2 in the text. 1 Functions of a single variable Now that we have e ne functions we turn our attention to calculus. A function

More information

Chapter 2 Lagrangian Modeling

Chapter 2 Lagrangian Modeling Chapter 2 Lagrangian Moeling The basic laws of physics are use to moel every system whether it is electrical, mechanical, hyraulic, or any other energy omain. In mechanics, Newton s laws of motion provie

More information

Differentiation ( , 9.5)

Differentiation ( , 9.5) Chapter 2 Differentiation (8.1 8.3, 9.5) 2.1 Rate of Change (8.2.1 5) Recall that the equation of a straight line can be written as y = mx + c, where m is the slope or graient of the line, an c is the

More information

Conservation laws a simple application to the telegraph equation

Conservation laws a simple application to the telegraph equation J Comput Electron 2008 7: 47 51 DOI 10.1007/s10825-008-0250-2 Conservation laws a simple application to the telegraph equation Uwe Norbrock Reinhol Kienzler Publishe online: 1 May 2008 Springer Scienceusiness

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Thus far, the functions we have been concerne with have been efine explicitly. A function is efine explicitly if the output is given irectly in terms of the input. For instance,

More information

13.1: Vector-Valued Functions and Motion in Space, 14.1: Functions of Several Variables, and 14.2: Limits and Continuity in Higher Dimensions

13.1: Vector-Valued Functions and Motion in Space, 14.1: Functions of Several Variables, and 14.2: Limits and Continuity in Higher Dimensions 13.1: Vector-Value Functions an Motion in Space, 14.1: Functions of Several Variables, an 14.2: Limits an Continuity in Higher Dimensions TA: Sam Fleischer November 3 Section 13.1: Vector-Value Functions

More information

Chapter 2. Exponential and Log functions. Contents

Chapter 2. Exponential and Log functions. Contents Chapter. Exponential an Log functions This material is in Chapter 6 of Anton Calculus. The basic iea here is mainly to a to the list of functions we know about (for calculus) an the ones we will stu all

More information

Differentiability, Computing Derivatives, Trig Review

Differentiability, Computing Derivatives, Trig Review Unit #3 : Differentiability, Computing Derivatives, Trig Review Goals: Determine when a function is ifferentiable at a point Relate the erivative graph to the the graph of an original function Compute

More information

Exam 2 Review Solutions

Exam 2 Review Solutions Exam Review Solutions 1. True or False, an explain: (a) There exists a function f with continuous secon partial erivatives such that f x (x, y) = x + y f y = x y False. If the function has continuous secon

More information

Make graph of g by adding c to the y-values. on the graph of f by c. multiplying the y-values. even-degree polynomial. graph goes up on both sides

Make graph of g by adding c to the y-values. on the graph of f by c. multiplying the y-values. even-degree polynomial. graph goes up on both sides Reference 1: Transformations of Graphs an En Behavior of Polynomial Graphs Transformations of graphs aitive constant constant on the outsie g(x) = + c Make graph of g by aing c to the y-values on the graph

More information

Derivatives and the Product Rule

Derivatives and the Product Rule Derivatives an the Prouct Rule James K. Peterson Department of Biological Sciences an Department of Mathematical Sciences Clemson University January 28, 2014 Outline Differentiability Simple Derivatives

More information

Discrete Operators in Canonical Domains

Discrete Operators in Canonical Domains Discrete Operators in Canonical Domains VLADIMIR VASILYEV Belgoro National Research University Chair of Differential Equations Stuencheskaya 14/1, 308007 Belgoro RUSSIA vlaimir.b.vasilyev@gmail.com Abstract:

More information

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control 19 Eigenvalues, Eigenvectors, Orinary Differential Equations, an Control This section introuces eigenvalues an eigenvectors of a matrix, an iscusses the role of the eigenvalues in etermining the behavior

More information

On the Concept of Local Fractional Differentiation

On the Concept of Local Fractional Differentiation On the Concept of Local Fractional Differentiation Xiaorang Li, Matt Davison, and Chris Essex Department of Applied Mathematics, The University of Western Ontario, London, Canada, N6A 5B7 {xli5,essex,mdavison}@uwo.ca

More information

Fall 2016: Calculus I Final

Fall 2016: Calculus I Final Answer the questions in the spaces provie on the question sheets. If you run out of room for an answer, continue on the back of the page. NO calculators or other electronic evices, books or notes are allowe

More information

Partial Differential Equations

Partial Differential Equations Chapter Partial Differential Equations. Introuction Have solve orinary ifferential equations, i.e. ones where there is one inepenent an one epenent variable. Only orinary ifferentiation is therefore involve.

More information

Problem Sheet 2: Eigenvalues and eigenvectors and their use in solving linear ODEs

Problem Sheet 2: Eigenvalues and eigenvectors and their use in solving linear ODEs Problem Sheet 2: Eigenvalues an eigenvectors an their use in solving linear ODEs If you fin any typos/errors in this problem sheet please email jk28@icacuk The material in this problem sheet is not examinable

More information

Differentiability, Computing Derivatives, Trig Review. Goals:

Differentiability, Computing Derivatives, Trig Review. Goals: Secants vs. Derivatives - Unit #3 : Goals: Differentiability, Computing Derivatives, Trig Review Determine when a function is ifferentiable at a point Relate the erivative graph to the the graph of an

More information

The Natural Logarithm

The Natural Logarithm The Natural Logarithm -28-208 In earlier courses, you may have seen logarithms efine in terms of raising bases to powers. For eample, log 2 8 = 3 because 2 3 = 8. In those terms, the natural logarithm

More information

Lecture XII. where Φ is called the potential function. Let us introduce spherical coordinates defined through the relations

Lecture XII. where Φ is called the potential function. Let us introduce spherical coordinates defined through the relations Lecture XII Abstract We introuce the Laplace equation in spherical coorinates an apply the metho of separation of variables to solve it. This will generate three linear orinary secon orer ifferential equations:

More information

Final Exam Study Guide and Practice Problems Solutions

Final Exam Study Guide and Practice Problems Solutions Final Exam Stuy Guie an Practice Problems Solutions Note: These problems are just some of the types of problems that might appear on the exam. However, to fully prepare for the exam, in aition to making

More information

Calculus Class Notes for the Combined Calculus and Physics Course Semester I

Calculus Class Notes for the Combined Calculus and Physics Course Semester I Calculus Class Notes for the Combine Calculus an Physics Course Semester I Kelly Black December 14, 2001 Support provie by the National Science Founation - NSF-DUE-9752485 1 Section 0 2 Contents 1 Average

More information

MA 2232 Lecture 08 - Review of Log and Exponential Functions and Exponential Growth

MA 2232 Lecture 08 - Review of Log and Exponential Functions and Exponential Growth MA 2232 Lecture 08 - Review of Log an Exponential Functions an Exponential Growth Friay, February 2, 2018. Objectives: Review log an exponential functions, their erivative an integration formulas. Exponential

More information

12.11 Laplace s Equation in Cylindrical and

12.11 Laplace s Equation in Cylindrical and SEC. 2. Laplace s Equation in Cylinrical an Spherical Coorinates. Potential 593 2. Laplace s Equation in Cylinrical an Spherical Coorinates. Potential One of the most important PDEs in physics an engineering

More information

Thermal conductivity of graded composites: Numerical simulations and an effective medium approximation

Thermal conductivity of graded composites: Numerical simulations and an effective medium approximation JOURNAL OF MATERIALS SCIENCE 34 (999)5497 5503 Thermal conuctivity of grae composites: Numerical simulations an an effective meium approximation P. M. HUI Department of Physics, The Chinese University

More information

d dx But have you ever seen a derivation of these results? We ll prove the first result below. cos h 1

d dx But have you ever seen a derivation of these results? We ll prove the first result below. cos h 1 Lecture 5 Some ifferentiation rules Trigonometric functions (Relevant section from Stewart, Seventh Eition: Section 3.3) You all know that sin = cos cos = sin. () But have you ever seen a erivation of

More information

1 Definition of the derivative

1 Definition of the derivative Math 20A - Calculus by Jon Rogawski Chapter 3 - Differentiation Prepare by Jason Gais Definition of the erivative Remark.. Recall our iscussion of tangent lines from way back. We now rephrase this in terms

More information

05 The Continuum Limit and the Wave Equation

05 The Continuum Limit and the Wave Equation Utah State University DigitalCommons@USU Founations of Wave Phenomena Physics, Department of 1-1-2004 05 The Continuum Limit an the Wave Equation Charles G. Torre Department of Physics, Utah State University,

More information

1 Second Facts About Spaces of Modular Forms

1 Second Facts About Spaces of Modular Forms April 30, :00 pm 1 Secon Facts About Spaces of Moular Forms We have repeately use facts about the imensions of the space of moular forms, mostly to give specific examples of an relations between moular

More information

Equations of lines in

Equations of lines in Roberto s Notes on Linear Algebra Chapter 6: Lines, planes an other straight objects Section 1 Equations of lines in What ou nee to know alrea: The ot prouct. The corresponence between equations an graphs.

More information

Delocalization of boundary states in disordered topological insulators

Delocalization of boundary states in disordered topological insulators Journal of Physics A: Mathematical an Theoretical J. Phys. A: Math. Theor. 48 (05) FT0 (pp) oi:0.088/75-83/48//ft0 Fast Track Communication Delocalization of bounary states in isorere topological insulators

More information

Chapter 6: Energy-Momentum Tensors

Chapter 6: Energy-Momentum Tensors 49 Chapter 6: Energy-Momentum Tensors This chapter outlines the general theory of energy an momentum conservation in terms of energy-momentum tensors, then applies these ieas to the case of Bohm's moel.

More information

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013 Survey Sampling Kosuke Imai Department of Politics, Princeton University February 19, 2013 Survey sampling is one of the most commonly use ata collection methos for social scientists. We begin by escribing

More information

FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS. 1. Introduction

FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS. 1. Introduction FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS ALINA BUCUR, CHANTAL DAVID, BROOKE FEIGON, MATILDE LALÍN 1 Introuction In this note, we stuy the fluctuations in the number

More information

Introduction to variational calculus: Lecture notes 1

Introduction to variational calculus: Lecture notes 1 October 10, 2006 Introuction to variational calculus: Lecture notes 1 Ewin Langmann Mathematical Physics, KTH Physics, AlbaNova, SE-106 91 Stockholm, Sween Abstract I give an informal summary of variational

More information

ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS

ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS MARK SCHACHNER Abstract. When consiere as an algebraic space, the set of arithmetic functions equippe with the operations of pointwise aition an

More information

Integration Review. May 11, 2013

Integration Review. May 11, 2013 Integration Review May 11, 2013 Goals: Review the funamental theorem of calculus. Review u-substitution. Review integration by parts. Do lots of integration eamples. 1 Funamental Theorem of Calculus In

More information

θ x = f ( x,t) could be written as

θ x = f ( x,t) could be written as 9. Higher orer PDEs as systems of first-orer PDEs. Hyperbolic systems. For PDEs, as for ODEs, we may reuce the orer by efining new epenent variables. For example, in the case of the wave equation, (1)

More information

APPROXIMATE SOLUTION FOR TRANSIENT HEAT TRANSFER IN STATIC TURBULENT HE II. B. Baudouy. CEA/Saclay, DSM/DAPNIA/STCM Gif-sur-Yvette Cedex, France

APPROXIMATE SOLUTION FOR TRANSIENT HEAT TRANSFER IN STATIC TURBULENT HE II. B. Baudouy. CEA/Saclay, DSM/DAPNIA/STCM Gif-sur-Yvette Cedex, France APPROXIMAE SOLUION FOR RANSIEN HEA RANSFER IN SAIC URBULEN HE II B. Bauouy CEA/Saclay, DSM/DAPNIA/SCM 91191 Gif-sur-Yvette Ceex, France ABSRAC Analytical solution in one imension of the heat iffusion equation

More information

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION The Annals of Statistics 1997, Vol. 25, No. 6, 2313 2327 LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION By Eva Riccomagno, 1 Rainer Schwabe 2 an Henry P. Wynn 1 University of Warwick, Technische

More information

A simple and compact approach to hydrodynamic using geometric algebra. Abstract

A simple and compact approach to hydrodynamic using geometric algebra. Abstract A simple and compact approach to hydrodynamic using geometric algebra Xiong Wang (a) Center for Chaos and Complex Networks (b) Department of Electronic Engineering, City University of Hong Kong, Hong Kong

More information

By writing (1) as y (x 5 1). (x 5 1), we can find the derivative using the Product Rule: y (x 5 1) 2. we know this from (2)

By writing (1) as y (x 5 1). (x 5 1), we can find the derivative using the Product Rule: y (x 5 1) 2. we know this from (2) 3.5 Chain Rule 149 3.5 Chain Rule Introuction As iscusse in Section 3.2, the Power Rule is vali for all real number exponents n. In this section we see that a similar rule hols for the erivative of a power

More information