# Properties of the energy Laplacian on the Sierpinski Gasket Konstantinos Tsougkas

U.U.D.M. Project Report 2014:4 Properties of the energy Laplacian on the Sierpinski Gasket Konstantinos Tsougkas Examensarbete i matematik, 30 hp Handledare och examinator: Anders Öberg Januari 2014 Department of Mathematics Uppsala University Properties of the energy Laplacian on the Sierpinski Gasket Konstantinos Tsougkas January 27, 2014 Abstract In this paper we study the recent topic of analysis on fractals, taking as our primary focus the Sierpinski Gasket. We examine how a Laplacian is created on it in regards to different measures and we study its properties. Then we extend some results of the standard Laplacian to the Kusuoka one. 1 Acknowledgements I would like to express my gratitude to my advisor Anders Öberg for his valuable guidance every step along the way of this work. He introduced me to this fascinating topic and then had the patience to help me wherever I needed and provide me constant encouragement, comments and suggestions. I also thank immensely my family whose constant support and love gave me motivation. Without them this work would not have been possible and thus, this is dedicated to them. Contents 1 Introduction 4 2 Energy measures and the Kusuoka measure 16 3 Local behavior of functions in dom∆µ 20 4 Local Solvability of Differential equations for the energy Laplacian 28 5 Approximation by functions vanishing in a neighborhood of the boundary 32 3 1 Introduction Let us define the Sierpinski gasket, SG. Take an equilateral triangle in R2 with vertices {qi } and define maps Fi : R2 → R2 with Fi = 12 (x − qi ) + qi for i = 0, 1, 2. Then, the Sieprinski Gasket is the unique compact set satisfying SG = 2 [ Fi SG. i=0 Also, as a convention we may refer to the Sierpinski Gasket as SG or K. If w = (w1 , . . . , wm ) is a finite word, we can also define the mapping Fw = Fw1 ◦ · · · ◦ Fwm . We call Fw K a cell of level m. The Sierpinski Gasket may be viewed as an approximation of a sequence of graphs Γm with vertices Vm and adjacency relations x ∼m y. That means, that for x, y ∈ Vm we have that x ∼m y ⇐⇒ x, y ∈ Fw (V0 ) for some word w of length m. S∞We want the vertices to be nested V0 ⊆ V1 ⊆ V2 . . . with the union V∗ = m=0 Vm , a dense set of the fractal. In the case of the Sierpinski Gasket, we take V0 = {qi }2i=0 as the vertices of an original equilateral triangle and define Vm = 2 [ Fi (Vm−1 ). i=0 4 We call V0 the boundary of the Sierpinski Gasket and every point in V∗ a junction point. We will be concerned with functions u : K → R. Now, we create a measure on the Sierpinski Gasket. In this thesis we will focus on two measures, namely the standard measure and the Kusuoka measure. The standard measure is a special case of a self-similar measure created in the following way: Assign probability weights µi with 2 X µi = 1 ,with each µi > 0 and then set i=0 µ(Fw K) = 2 Y µwi for |w| = m. i=0 Then, for the standard measure we just set all µi = 1/3. On the Sierpinski Gasket the standard invariant measure µ satisfies 1 µ(Fw Fi SG) = µ(Fw SG), 3 i = 0, 1, 2, for any word w. We also have the self-similar identity X µ(A) = µi µ(Fi−1 A). i Now, after having defined a measure we can define integrals and create and enrich our theory. This is standard as in usual calculus, and since we have uniform continuity due to the compact set K it suffices to define it as Z X f dµ = lim f (xw )µ(Fw K). K m→∞ |w|=m A key concept in the theory of analysis on fractals plays the concept of energy. On each graph G we construct an energy E(u, v) for two functions u and v with: X EG (u, v) = (u(x) − u(y)) (v(x) − v(y)) x∼y where the sum extends over all the edges of the graph. For u = v we simply denote EG (u). This is a bilinear form. If we have a graph G and G0 with vertices V and V 0 respectively, and V ⊂ V 0 and we also have a function u 5 defined on V , then we can extend it on V 0 in many possible ways. However, there is at least one way to do it so that it minimizes EG0 (u). Such an energyminimizing extension will be called a harmonic extension and write it ũ. In the Sierpinski Gasket, it turns out that EG0 (ũ) = 53 EG (u). This leads us to define the so called renormalized graph energies, Em (u) = (r−m Em (u)). In our case, it turns out r = 35 . There exists a simple extension algorithm in order to obtain a harmonic extension of a function defined on Vm to Vm+1 . This algorithm is called the “ 15 − 25 rule” and it goes as follows: If on a given cell Vm we have that the function takes boundary values a, b, c and the junctions points of the next level sub-cell, directly opposite of these points respectively take values x, y, z then we have that 1 2 x = (b + c) + a 5 5 2 1 y = (a + c) + b 5 5 2 1 z = (a + b) + c 5 5 This equations are obtained easily by using calculus. By computing the value of the energy, and taking the derivatives of x, y, z equal to zero to minimize it, and then solving accordingly. If ũ is the harmonic extension of u then it holds that Em+1 (ũ) = Em (u) and in general we have that Em (u) ≤ Em+1 (u). We define a harmonic function h to be one that minimizes Em (h) at all levels for the given boundary values on V0 . This can be done by following the “ 15 − 52 ” rule and thus by this rule, it is obvious that a harmonic function is defined completely by its boundary values. Thus, we have a space of harmonic functions called H0 which is three-dimensional with a basis {h0 , h1 , h2 } with hi (qj ) = δi,j . Thus we have that for harmonic extension functions at each point x ∈ Vm+1 \ Vm , ũ(x) is the average of the values at the four neighboring points in Vm+1 . In a similar fashion as standard analysis, we have a maximum principle for harmonic functions too, and thus they take their maximum value at the boundary. We also have the following key lemma. Lemma 1.1. Let u, v be defined on Vm , let ũ be the harmonic extension of u and let v 0 be any extension of v to Vm+1 . Then Em+1 (ũ, v 0 ) = Em (u, v). 6 We define then the energy of u as E(u) = lim Em (u) or similarly m→∞ E(u, v) = lim Em (u, v) m→∞ This energy plays a central role in our theory and we call functions u such that E(u) < ∞ as functions with finite energy and we denote u ∈ domE. A very important property of functions of finite energy is that they are continuous. In fact, they are Hölder continuous. Moreover, domE is dense in C(K, R) and also domE forms an algebra. This energy E(u, v) is also a bilinear form and forms an inner product on the space of domE modulo constants. In fact, domE/constants forms a Hilbert space with that inner product. We are now ready to define the main object of our study, the Laplacian. Definition 1.2. Let u ∈ domE. Then, u ∈ dom∆µ and ∆µ u = f if Z E(u, v) = − f vdµ for all v ∈ dom0 E K where dom0 E denotes the functions of finite energy that vanish on the boundary. If we mean the standard Laplacian, that is the Laplacian with the standard measure, then we can simply write ∆u instead of ∆µ u without any confusion. We have that dom∆µ is a real vector space. However just by the definition it is not so clear that there are any nontrivial functions in dom∆µ . But a bit later on we will see a theorem which shows that it is a very rich space because for every continuous function f there exists u ∈ dom∆µ such that ∆µ u = f . Initially, a very important fact is that the space contains harmonic functions and they have Laplacian zero, which also is an equivalent way of defining harmonic functions. This fact holds true for all measures µ. Theorem 1.3. If h ∈ H0 , we have that h ∈ dom∆µ and ∆µ h = 0. Conversely, if u ∈ dom∆µ and ∆µ u = 0 then u is harmonic. Proof. We know that harmonic functions h have the property that Em (h, v) is independent of m, so E(h, v) = E0 (h, v) = 0 since v vanishes on the boundary. Thus ∆µ h = 0. For the opposite direction we will use some very specific functions v. Let (m) m and a point x ∈ Vm ∈ / V0 . Define ψx as the piecewise harmonic function 7 (m) at level m that satisfies ψx (y) = δxy for all x, y ∈ Vm . Then we have that ψxm ∈ dom0 E since x ∈ / V0 . Then, by using the fact that ∆µ u = 0 we get (m) that E(u, ψx ) = 0. But then by reversing the roles of u and v we have that (m) (m) (m) E(u, ψx ) = Em (u, ψx ). But then, this condition that Em (u, ψx ) = 0 means that X (u(x) − u(y)) = 0 y∼m x and that u|Vm is harmonic. But this is true for all m, and thus u is harmonic. A very big drawback of dom∆µ is that it is not closed under multiplication. If u ∈ dom∆µ then u2 ∈ / dom∆µ . This will be explored later, and this fact is completely dependent on the measure µ. This major disadvantage however can be lifted if we create a different Laplacian with a different measure. Namely, Kusuoka created a measure called the Kusuoka measure and with that measure we have that the domain of its Laplacian is closed under multiplication. The major scope of this thesis is investigating the properties and the differences between the two Laplacians, with the Kusuoka and the standard measure. The definition we used above for the Laplacian is called a weak definition and there is an equivalent pointwise formula. First, we define a graph Laplacian ∆m u(x) = X (u(y) − u(x)) for all x ∈ Vm V0 . y∼m x Then our pointwise formula would be the following: Z −1 −m (m) ∆µ u(x) = lim r ψx dµ ∆m (x). m→∞ K In the case of the standard Laplacian, we simply get ∆u(x) = 3 lim 5m ∆m u(x) 2 m→∞ The reason for this, is that we already have that r = need to estimate Z ψx(m) dµ. K 8 3 5 and thus we only (m) To do this, let x ∈ K. Then the function ψx has support in the two m-cells meeting at x. If Fw K is one of these cells with vertices x, y, z then we get that ψx(m) + ψy(m) + ψz(m) = 1 and this holds as an identity. Thus m Z 1 (m) (m) (m) (ψx + ψy + ψz )dµ = µ(Fw K) = . 3 Fw K But due to symmetry all the summands have the same integral, so Z ψx(m) dµ = Fw K 1 3m+1 . Along with the other m-cell, we get finally that Z ψx(m) dµ = Fw K 2 . 3m+1 We can also create normal derivatives at the boundary points {qi }. Definition 1.4. Let x a boundary point and u a continuous function on K. We say ∂n u(x) exists if the right hand side limit exists and X ∂n u(x) = lim r−m (u(x) − u(y)). m→∞ y∼m x This is called the normal derivative at the point x. For the case of the Sierpinski Gasket this can be viewed as m 5 (2u(qi ) − u(Fim qi+1 ) − u(Fim qi−1 )) . ∂n u(x) = lim m→∞ 3 We can also localize the definition of the normal derivative. If we have a cell Fw K and x = Fw qi be a boundary point of that cell, then we can say that ∂n u(x) with respect to the cell Fw K is the same formula with the y in the formula lie inside Fw K. We can also view this as a scaling property for the normal derivative, namely ∂n u(Fw qi ) = r−|w| ∂n (u ◦ Fw )(qi ). 9 However at this point it is important to note that a junction point has two addresses Fw qi and Fw0 qi0 and thus there is another local derivative on that point x with respect to the other cell. Thus a normal derivative is not only with respect to any junction point but also viewed according to the cell of that junction point. However we have an important connection to these two derivatives, and that is that they sum to zero. This is called the matching condition for normal derivatives at x. Proposition 1.5. Suppose u ∈ dom∆µ . Then at each junction point x = Fw qi = Fw0 qi0 , the local derivatives exist and ∂n u(Fw qi ) + ∂n u(Fw0 qi0 ) = 0 Proof. The existence follows from the scaling property. Now, we have that X ∂n u(Fw qi ) + ∂n u(Fw0 qi0 ) = lim r−m (u(x) − u(y)) m→∞ y∼m x since the neighbors y of x lie in either Fw K or Fw0 K. However since we have that u ∈ dom∆µ we know that Z −1 lim r−m ψx(m) dµ ∆m u(x) m→∞ exists and since is also zero. K (m) R K ψx dµ → 0 we see that the above right hand side limit In a similar fashion, we also define the tangential derivatives: Definition 1.6. Let qi be a boundary point. The tangential derivative at the point qi is the limit ∂T u(qi ) = lim 5m (u(Fim (qi+1 ) − Fim (qi−1 )) m→∞ if the limit exists. Note, that the tangential derivative may not always exist. However, later on, we will have a theorem confirming its existence under suitable conditions. One of the most important equations which is a very powerful tool for our theory is that of the Gauss-Green formula. 10 Theorem 1.7. Suppose u and v are in dom∆µ . Then Z Z X (∆µ v)udµ = (u∂n v − v∂n u). (∆µ u)vdµ − K K V0 If we choose v = 1 in the above formula, then we get that Z X (∆µ u)dµ = ∂n u. K V0 Another version of the formula is also Z X (∆µ u)vdµ + E(u, v) = − v∂n u. K V0 We also note a consequence of the formula. If u ∈ dom∆µ and ∂n u(x) = 0 for every x ∈ V? then u is constant.R To see this, by Pchoosing v = 1 in the Gauss-Green formula we have that Fw K ∆µ udµ = v0 ∂n u = 0 for all cells Fw K which imples ∆µ = 0 and thus u is harmonic. But we know how to compute the normal derivatives of harmonic functions, and we don’t get all zeros unless the function is constant. A big scope of the theory is to provide solutions to the “differential equation” ∆µ u = f for a continuous f . To derive a solution we create a special function called Green’s function. Definition 1.8. Green’s function is defined by G(x, y) = lim GM (x, y) M →∞ with GM (x, y) defined by GM (x, y) = M X m=0 (m+1) X z 0 ∈V g(z, z 0 )ψz(m+1) (x)ψz 0 (y) m+1 \Vm where g(z, z 0 ) = 0 when z and z 0 are not in the same cell of level m + 1, g(z, z) = and 9 3 m 50 5 for z ∈ Vm+1 \ Vm 3 3 m g(z, z ) = 50 5 0 for z 6= z 0 , z and z 0 in the same level m + 1 cell. 11 Then, now that we have defined Green’s function, we arrive at this very important result that gives us existence of a huge class of functions in dom∆µ . Using the Green’s function is also the main tool we use for solving differential equations on fractals. Theorem 1.9. On the Sierpinski Gasket, the Dirichlet problem −∆µ u = f , u|V0 = 0 has a unique solution in dom∆µ for any continuous f , given by Z u(x) = G(x, y)f (y)dµ(y) K where G(x, y) is the Green’s function. If we don’t have Dirichlet boundary conditions then the solution is given by Z u(x) = G(x, y)f (y)dµ(y) + h(x) K where h(x) is a harmonic function with the same boundary values as u. We have already seen that a function h such that ∆µ h = 0 is called harmonic and the space of those functions is H0 . We can also define spaces of multiharmonic functions in the same way by defining Hk = {u | ∆k+1 µ u = 0} for k = 0, 1, 2, ... Then this space has dimension 3k + 3 and we are interested in creating a basis. There have been many different construction of basis but one way of doing it that is particularly interesting is creating “monomials” that are j the analogue of the functions { xj! } on the real line. These monomials are also centred around a specific boundary point with the ulterior motive of creating Taylor series. Definition 1.10. We define the monomials {Pki ∈ Hk } to have the k-jet consisting of all 0’s except for one 1: ∆j Pki (q0 ) = δjk δi1 ∂n ∆j Pki (q0 ) = δjk δi2 ∂T ∆j Pki (q0 ) = δjk δi3 for j 6 k. 12 From that we can observe that this means ∆Pki = P(k−1)i and thus we can recursively find Pki by Z Pki (x) = − G(x, y)P(k−1)i (y)dµ(y) + h(x) K for a harmonic function h(x) defined by the j = 0 case. Definition 1.11. Define as follows αj = Pj1 (q1 ), βj = Pj2 (q1 ), γj = Pj3 (q1 )nj = ∂n Pj1 (q1 ), tj = ∂T Pj2 (q1 ). Note that by symmetry we have Pj1 (q2 ) = αj , Pj2 (q2 ) = βj and Pj3 (q2 ) = −γj , so that all values of monomials at boundary points are expressible in terms of α’s, β’s and γ’s. Then, in order to obtain some decay rates for the monomials, we use the following relations Lemma 1.12. The following recursion relations hold: j−1 αj = 4 X αj−` α` j 5 −5 for j≥2 `=1 γj = j−1 X 4 5j+1 − 5 αj−` γ` for j≥1 `=0 j−1 1 X 2 j−` 2 4 βj = j 5 αj−` β` − αj−` 5` β` + αj−` β` 5 −1 5 3 5 for j ≥ 1, `=0 with initial data α0 = 1, α1 = 1/6, β0 = −1/2, γ0 = 1/2. In particular, γj = 3αj+1 . Lemma 1.13. There exists a constant c such that 0 < aj < c(j!)−log5/log2 for all j. Then by using the above two lemmas we get the following main theorem. 13 Theorem 1.14. (i) For any r < ∞ there exists cr such that kPj1 k∞ 6 cr r−j or more precisely 1 kPj1 k∞ = −∞. j→∞ j (ii) There exists c such that lim kPj2 k∞ 6 cλ2 −j and lim −λ2 j Pj2 = φ j→∞ where φ is a λ2 -Neumann eigenfunction of ∆ which is R0 -symmetric and vanishes ok F0 K, the limit existing uniformly and in energy. The proofs of the above lemmas and theorem are quite lengthy and detailed and can be found at [3]. Having found these rates for the monomials, a theory of Taylor series can be created. It should also be noted, that the polynomials, i.e the sum of the monomials Pij , or equivalently solutions of ∆nµ P = 0, behave differently from the standard polynomials we are used to in analysis, and many key results that are true in standard analysis, do not hold here. A key example is the Stone-Weierstrass theorem. Polynomials cannot uniformly approximate all continuous functions. To see this, first we must note a very interesting and curious fact about the Laplacian on SG. As usual in analysis we define eigenfunctions and eigenfunction in the natural way as solutions of ∆u = λu and the Dirichlet boundary conditions if the boundary vanishes, while the Neumann boundary conditions if the normal derivatives vanish at the boundary. A striking difference however between standard analysis and analysis on fractals is that in standard analysis we cannot have joint Dirichlet-Neumann eigenfunctions. However, surprisingly, in this theory of Laplacian on fractals we can have certain eigenfunctions also seen as “localized eigenfunctions” that satisfy both Dirichlet and Neumann conditions. Then, let u be a joint Dirichlet-Neumann eigenfunction. Thus if P (x) is a polynomial we have that Z P (x)u(x)dµ = 0 K 14 since by the definition of the monomials we have that ∆Pki = P(k−1)i and thus we can use repeatedly the Gauss-Green formula to reduce the order of the polynomial since due to the joint D − N conditions we have that all the terms u(qi )=0 and ∂n u(qi ) = 0. 15 2 Energy measures and the Kusuoka measure While with the standard measure we know many results concerning the behavior of functions on the Sierpinski gasket, we see that the standard measure has also many drawbacks. Namely, the domain of its Laplacian is not an algebra. To overcome this we create a different measure called the Kusuoka measure. Many results that are known about the standard measure still remain open if we use the Kusuoka measure instead. To define the Kusuoka measure we need to define first the energy measures. Define a measure νu by νu (Fw K) = r−|w| E(u ◦ Fw ). This is called the energy measure νu . For energy measures and u, v ∈ domE we have the important carré du champs formula Z 1 1 1 f dνu,v = E(f u, v) + E(u, f v) − E(f, uv). 2 2 2 K Definition 2.1. Let {h1 , h2 } be an orthonormal basis for the space of harmonic functions modulo constants with respect to the energy inner product. Then the Kusuoka measure is defined as ν = νh1 + νh2 Proposition 2.2. The Kusuoka measure is independent on the choice of the orthonormal basis. Proof. Let {h, h0 } be an orthonormal basis for the Kusuoka measure and let {h1 , h2 } be a different one such that ν 0 = νh1 + νh2 . Then there exist a, b, c, d such that h1 = ah + bh0 and h2 = ch + dh0 . Because of the change of basis we have that the matrix a b M= c d is a rotation matrix and thus we have the properties a2 + c2 = 1, b2 + d2 = 1, ab + cd = 0. Then, we see that 16 ν 0 (Fw K) = r−|w| (E(h1 ◦ Fw ) + E(h2 ◦ Fw ) = r−|w| (a2 E(h ◦ Fw ) + b2 E(h0 ◦ Fw ) +c2 E(h ◦ Fw ) + d2 E(h0 ◦ Fw ) +abE(h ◦ Fw , h0 ◦ Fw ) + cdE(h ◦ Fw , h0 ◦ Fw )) = νh (Fw K) + νh0 (Fw K) We can take as basis h1 = √12 (0, 1, 1) and h2 = √16 (0, 1, −1) to be the orthogonal harmonic functions defining the Kusuoka measure. An equivalent definition for the Kusuoka measure would be to define it as ν 0 = νh0 + νh1 + νh2 but in this case we get that ν 0 = 3ν with respect to the previous definition. Now, with this new measure, by exactly the same definition as before we create a different Laplacian, the Kusuoka Laplacian ∆ν which has different properties. A very important result is that every energy measure is absolutely continuous with respect to the Kusuoka measure. In fact the Kusuoka measure is also singular with respect to the standard measure. Now, in [7], a pointwise formula is obtained for the Kusuoka Laplacian. Proposition 2.3. Let u ∈ dom∆ν . Then for all x ∈ V∗ V0 the following pointwise formula holds with uniform limit across V∗ V0 ∆ν u(x) = 2 lim m→∞ ∆m u(x) ∆m (h1 2 + h2 2 )(x) Proof. First of all, we have already mentioned before that the pointwise formula for any measure is Z −1 −m (m) ∆µ u(x) = lim r ψx dµ ∆µ u(x). m→∞ K R −1 (m) To compute the K ψx dµ where µ is now the Kusuoka measure, we use the carré du champs formula and thus we have Z 1 1 ψx(m) dν = E(ψx(m) h1 , h1 )+E(ψx(m) h2 , h2 )− E(ψx(m) , h1 2 )− E(ψx(m) , h2 2 ). 2 2 K 17 But we have that E(ψx(m) h1 , h1 ) = E0 (ψx(m) h1 , h1 ) = 0 E(ψx(m) h2 , h2 ) = E0 (ψx(m) h2 , h2 ) = 0. And thus we have that Z 1 ψx(m) dν = − E(ψx(m) , h1 2 + h2 2 ) = r−m ∆m (h1 2 + h2 2 ). 2 K Concluding, we get that ∆ν u(x) = lim r m→∞ −m Z ψx(m) dµ −1 ∆m u(x) = 2 lim m→∞ K ∆m u(x) ∆m (h1 2 + h2 2 )(x) It would be interesting to try to see how similar dom∆ and dom∆ν are. The following theorem shows us that they are quite different and in fact they only coincide on the space of harmonic functions. Theorem 2.4. dom∆ ∩ dom∆ν = H0 Similarly as before with the standard measure, we can create polynomials Pij that are the basis for multiharmonic functions for the Kusuoka measure. However, while the decay rates kPij k∞ are known for the polynomials of the standard measure, it remains an open problem to find estimates for the Kusuoka polynomials. In fact, numerical estimation shows that the decay rates are different. As for a self-similar identity, the Kusuoka measure is not self-similar in the way the standard measure is. However, we have the following result. Proposition 2.5. The Kusuoka measure satisfies the variable self-similar identity 2 X 1 12 + Ri ν ◦ Fi −1 15 15 i=0 where Ri = dνi dν the Radon-Nikodym derivative of νi . 18 Using this relation a scaling identity for the Kusuoka Laplacian can be derived. We will introduce the scaling identity in section 4, where we will also make extensive use of it. Perhaps the single most important advantage of the Kusuoka Laplacian over the standard one is that the domain of the Kusuoka Laplacian forms an algebra. This is a key fact that is not true for the standard Laplacian. A proof will be given for that in the next section by evaluating the properties of the decay rates of functions. Thus, for example if u ∈ dom∆ then u2 ∈ / dom∆. However if u ∈ dom∆ν then u2 ∈ dom∆ν and dνu ∆ν u2 = 2u∆ν u + 2 . dν This advantage makes it clear that the Kusuoka Laplacian is one that is worth studying and perhaps despite its apparent disadvantages due to the lack of self-similarity, in some sense is better behaved than the standard one. However, we have also have the following theorem which shows us that the Radon-Nikodym derivative is not continuous. Theorem 2.6. Let h be harmonic function with νh = aν0 + bν1 + cν2 and h0 be a harmonic function orthonormal to h under the energy inner product. Then, if C is a cell on K: i) inf x∈C ii) sup x∈C dνh =0 dν dνh 2 = (a + b + c) dν 3 However we have some form of limited continuity, if we restrict the derivative to the set of vertices V? then it is continuous on the edges of every triangle. 19 3 Local behavior of functions in dom∆µ Now, in this section, we would like to turn our attention to some results concerning the local behavior of functions and namely their rate of convergence to junction points. Let qi any boundary point and define εim (u) = sup |u(x) − u(qi )|. Fim K We would like to get some results about how fast it is decaying to zero. We will split our analysis into two parts. First with the standard measure and next with the Kusuoka measure. For the standard measure, we have the following: Lemma 3.1. Let u ∈ dom∆ and consider any (m-1)-cell with boundary vertices y0 , y1 , y2 and let x0 , x1 , x2 ∈ Vm Vm−1 be the vertex in that cell with xj opposite yj . Then 2 1 2 1 6 2 2 u(x2 ) = (u(y0 )+u(y1 ))+ u(y2 )+ m ( ∆u(x2 )+ ∆u(x1 )+ ∆u(x0 ))+Rm 5 5 35 5 5 5 and so on with Rm = o(5−m ) Theorem 3.2. Let u ∈ dom∆. If ∂n u(q0 ) 6= 0 then m m 3 3 6 εm 6 c2 c1 5 5 while if ∂u(q0 ) = 0 then εm 6 cm5−m Proof. Without loss of generality assume that u(q0 ) = 0. First, we will prove estimates for u(F0m q1 ) and u(F0m q2 ) and then show that these estimates transfer to the entire cell. Formula (2.4.9) in [4] gives us that m m 1 3 m m 2u(q0 ) − u(F0 q1 ) − u(F0 q2 ) = ∂n u(q0 ) + O . 5 5 Now, in our case this gives u(F0m q1 ) + u(F0m q2 ) m m 3 1 ∂n u(q0 ) + O . =− 5 5 20 Now, by using the lemma above, and subtracting at the points F0m (q1 ) and F0m (q2 ) we obtain that 1 u(F0m q1 ) − u(F0m q2 ) = (u(F0m−1 q1 ) − u(F0m−1 q2 )) + O(5−m ). 5 This is a recursion relation for the difference, and it is easy to see that this implies |u(F0m q1 ) − u(F0m q2 )| 6 cm5−m . Then, if ∂n u(q0 ) 6= 0 we get that m m 3 3 m 6 |u(F0 qj )| 6 c2 c1 5 5 while if ∂n u(q0 ) = 0 we get that |u(F0m qj )| 6 cm5−m Now, to see that these estimates transfer to the entire cell. We will use a generic argument here. We recall first the scaling identity for the Laplacian ∆(u ◦ Fw ) = 5−m f ◦ Fw . Then, if u ∈ dom∆ and ∆u = f and Fw K is an m-cell, |w| = m, and we also have that |u(Fw qi )| 6 a for i = 0, 1, 2 then we can write u ◦ Fw = h + g where h is the harmonic function taking the same boundary values as u ◦ Fw and Z −m G(x, y)f (Fw y)dµ(y). g(x) = −5 Then by the maximum principle for harmonic functions we have that |h| 6 a and we also have that |g(x)| 6 c0 kf k∞ 5−m R where c0 = sup G(x, y)dµ(y) So we obtain y∈K |u| 6 a + c0 kf k∞ 5−m on Fw K. We know that the normal derivatives always exist. However while it is not true in general for the tangential ones, we have the following sufficient condition. 21 Theorem 3.3. Assume u ∈ dom∆ and ∆u satisfies a Hölder condition of some order. Then ∂T u(q0 ) exists. Using the above decay rates, we can also prove the very important result which is the main weakness of the standard Laplacian, and that is the domain of the Laplacian does not form an algebra. Corollary 3.4. Let u be any nonconstant function in dom∆. Then u2 is not in dom∆. Proof. Let x0 be a junction point such that ∂n u(x0 ) 6= 0. We can always find such a point since we assumed u is non constant. Then we can write u(x0 ) = y. Thus u = (u − y) + y and thus u2 = (u − y)2 + 2y(u − y) + y 2 . Obviously 2y(u − y) + y 2 ∈ dom∆ and thus we must show that (u − y)2 ∈ / dom∆. By localizing the decay rates we have that ∂n (u − y)(x0 ) 6= 0 and thus by squaring the decay rates we have 2m 2m 2 3 2 3 (c1 ) 6 ε̃m 6 (c2 ) 5 5 where ε̃m = sup |u − y| in the m-cells containing x0 . Then by assuming that (u − y)2 is in dom∆ we have a contradiction since these decay rates are impossible to be also compatible with the decay rates 3 m of Θ 5 . Now, we would like to prove similar results for the Kusuoka measure. We would like to have an estimate of how the Kusuoka measure changes as we are zooming in on individual cells. A simple first result is to study how it changes by zooming in one direction. Lemma 3.5. For the Kusuoka measure we have that: m m 3 1 m + ν(F0 K) = 5 15 Proof. It is easy to see by the definition of the energy measures that m 3 νh1 (F0m K) = 5 and that νh2 (F0m K) = 22 1 15 m . Then, since ν = νh1 + νh2 we get the result. However this result has been significantly strengthened in [2] to have that for an arbitrary junction point, and thus we have the following lemma. Lemma 3.6. For the sequence {Fw Fim K} which converges to the point Fw (qi ) we have that m 3 m ν(Fw Fi K) = Θ 5 To obtain some results about the decay rates, we will need some results about the Green’s function. The following theorem gives us the necessary tools. The proof of the theorem can be found in [5] R Theorem 3.7. If φ(x) = K |G(x, y) − G(Rx, y)|dν(y) where R is the reflection about q0 . Then, 2m 3 m φ(F0 q1 ) = Θ . 5 If ξ(x) = supy∈K |G(x, y)|, then ξ(F0m q1 ) = Θ m 3 5 Now we are ready to prove important results for the decay rates of functions. Theorem 3.8. If u is skew-symmetric, u ∈ dom∆ν , then 2m 3 εm (u) = O 5 Proof. Write Z u(x) = G(x, y)f (y)dν(y) + h1 (x) = ũ(x) + h1 (x) K where f = ∆ν (u) is a continuous function and h1 is a harmonic function taking the same boundary values as u. Note that u is skew-symmetric implies h1 is skew-symmetric and hence m 1 . h1 = Θ 5 23 On the other hand, Z ũ(x) = | G(x, y)f (y)dν(y)| K Z 1 = | (G(x, y) − G(Rx, y)f (y)dν(y)| 2 K Z 1 |(G(x, y) − G(Rx, y)|dν(y). 6 kf k∞ 2 K 2m By the theorem above we have sup∂(F0m K) ũ = O 35 . To extend the m m estimate to the entire cell, we fix F0 K and write ũ ◦ F0 = g̃ + h2 , where h2 is the harmonic function taking the same boundary values as ũ ◦ F0m . Then, we have m m Z m Z 3 3 1 m m g̃(x) = − G(x, y)f (F0 y)dνh (y) + G(x, y)f (F0 y)dνh0 (y) 5 5 15 K K where h and h0 are the harmonic functions used in the definition of the Kusuoka measure. Since f is continuous, we can regard the integrals as O(1) so, 2m 3 g̃(x) = O . 5 m 2m Together with the fact that h2 = Θ 51 = O 35 we are done. Theorem 3.9. Let u ∈ dom∆ν , u(q0 ) = 0, then m 3 εm (u) = O 5 Proof. Similar as before, we can extend the results to the entire cell, so we will estimate only on the boundary. We have that Z u(x) = G(x, y)∆ν u(y)dν(y) + h1 (x) = ũ(x) + h1 (x) K and h1 is harmonic taking the same boundary values as u. Then we have that since h1 (q0 ) = 0 it must be a linear combination of the orthonormal m basis of harmonic functions for the Kusuoka measure, so h1 = O 35 . Also, m and thus we are done. by the theorem above we have that |ũ| = O 35 24 In the same way that we have a sufficient condition for the existence of the tangential derivative for the standard Laplacian, we have a slightly different one also for the Kusuoka one. Proposition 3.10. If u is skew-symmetric and u ∈ dom∆ν 2 then εm (u) = 1 m O 5 and ∂T u(q0 ) exists. Using the following lemma, we can also obtain results about more general functions. Lemma 3.11. If u is symmetric, u ∈ dom∆ν and u(q0 ) = 0 then m m Z 3 3 2u(q0 ) = − ∂n u(q0 ) + ψq(m) ∆ν udν 0 5 5 F0 K Theorem 3.12. Let u be symmetric and u(q0 ) = 0 and u ∈ dom∆ν k+1 for k = 1, 2, 3... with ∂n ∆ν j u(q0 ) = 0 and ∆ν j+1 u(q0 ) = 0 for j < k. Then (2k+1)m 3 εm (u) = O 5 Proof. The estimate will be done similarly as before only on the boundary. The proof is one of induction. For k = 1 we have that ∂n u(q0 ) = 0 and ∆ν u ∈ dom|∆ν and that ∆ν u(q0 ) = 0. Then by the above lemma we have that m 1 3 m |u(F0 q1 )| 6 εm (∆ν u) ν(F0m K). 2 5 By using then the decay rates above to estimate εm (∆ν u) we are done. The induction is based on the above lemma. Now, we will generalize the results in [5] to any random junction point. We will see that the convergence bounds obtained for the boundary points are exactly the same for all junction points of the Sierpinski Gasket. Lemma 3.13. Let y be a junction point such that y = Fw (qi ). For any u in the domain of the Laplacian, we have that sup |u(x) − u(y)| = sup |u ◦ Fw (x) − u ◦ Fw (qi )| Fw Fim K Fim K for any word w and m ∈ N. 25 Proof. Let w be a word and u be in the domain of the Laplacian. Then we know that u is continuous. We have that Fi are continuous functions, then Fw are also continuous, and since K is a compact set, then u ◦ Fw has a maximum and minimum value on u ◦ Fw (K) which is also compact. Then, we have that there exists a y1 ∈ Fw Fim K such that: sup |u(x) − u(y)| = |u(y1 ) − u(y)|. Fw Fim K But then, since y1 ∈ Fw Fim K it must be that there exists a y2 ∈ K such that y1 = Fw Fim (y2 ) So, |u(y1 ) − u(y)| = |u(Fw Fim (y2 )) − u(y)| = |(u ◦ Fw )(Fim (y2 )) − u(y)| 6 sup |(u ◦ Fw )(K) − u(y)|. Fim K Using the exact same argument, we obtain the other inequality as well. Lemma 3.14. Define εim (u) = supFim K |u(x) − u(qi )|, for i=0,1,2. Then, m εim (u) 6 O 35 Proof. Let R be the clockwise rotation around the center point of the Sierpinski gasket by 90 degrees. Namely, if (x0 , y0 ) is the center of the Sierpinski gasket, then R(x, y) = (x0 + (y − y0 ), y0 − (x − x0 )). Then, obviously R is a continuous function, and (R ◦ F1 )(K) = F0 K. Now, let u ∈ dom∆. We have that sup |u(x)| = sup |u ◦ R−1 ◦ R(x)| = sup |(u ◦ R−1 ) ◦ R(x)|. F1m K F1m K F1m K But if we call g = u ◦ R−1 then we have that g is continuous, F1m K is compact, and thus we have sup |g(R(x))| F1m K is actually attained by say, y1 ∈ F1m K and thus sup |g(R(x))| = |g(R(y1 ))|. F1m K 26 But then, R(y1 ) ∈ F0m K so sup |g(R(x))| = |g(R(y1 ))| 6 sup |g(x)|. F1m K F0m K But since g ∈ dom∆ we have that supF0m K |g(x)| 6 O m 3 . sup |u(x)| 6 O 5 F1m K 3 m . 5 So, In an exact similar way, but instead with rotation anticlockwise, we obtain that m 3 sup |u(x)| 6 O 5 F2m K Proposition 3.15. The rate of convergence of a function in thedomain of m the Laplacian to an arbitrary junction point, is bounded by O 35 Proof. Define εim (u) = sup |u(x) − u(qi )|. Fim K Now, let y be any junction point that is not in V0 . Then, it is known that y has two addresses, namely y = Fw (qi ) and y = Fw0 (qi0 ) with w 6= w0 and i 6= i0 . Then, let {Am }m be a sequence of cells with {Am }m → y. Define, ε̃m (u) = supAm |u(x) − u(y)|. Then, it is clear that ε̃m (u) 6 sup |u(x) − u(y)| + sup |u(x) − u(y)| Fw0 Fim 0 K Fw Fim K (Since, it is true that {Fw Fim K} → y and {Fw0 Fim 0 K} → y). Then, using the Lemma above, we have that ε̃m (u) 6 sup |(u ◦ Fw (x)) − u ◦ Fw (qi )| + sup |(u ◦ Fw0 (x)) − u ◦ Fw0 (qi0 )|. Fim K Fim 0 K But, if we call now u ◦ Fw (x) = g(x) and u ◦ Fw0 (x) = h(x) then it is clear that both g and h belong in the domain of the Laplacian. Thus, ε̃m (u) 6 εim (g) + 0 εim (h) 27 m 3 6O . 5 4 Local Solvability of Differential equations for the energy Laplacian In this section we are interested in studying the solvability of differential equations of the form ∆µ u = f. We have already seen that due to the existence of the Green’s function we have solutions. However what is of particular interest is that we have solvability for other certain subsets of K. Theorem 4.1. Let Ω be an open subset of K not containing any points of V0 . Then the equation −∆µ u = f on Ω has a solution for any continuous f on Ω. This result is independent of the measure µ and the proof can be found in [8]. Of course the solution is not unique since we can always add an harmonic function on Ω. Now, we are interested in the analogue of Picard existence and uniqueness theorem for the local solvability of −∆ν u(x) = F (x, u(x)). We already have results for the standard Laplacian in [8]. We are interested in extending them for the Kusuoka Laplacian as well. We will follow the proof of [8] in section 2 “Local Solvability” making the appropriate changes that are required by using ∆ν instead of ∆. Let F (x, u) denote a continuous function from K × R to R which satisfies also a Local Lipschitz condition in the u-variables: for every T > 0, there exists MT < ∞ such that |F (x, u) − F (x, u0 )| 6 MT |u − u0 |, provided |u|, |u0 | 6 T. Theorem 4.2. Given F satisfying the Lipschitz condition above, for every A there exists m such that for all choices of {aj } with |aj | 6 A, the equation −∆ν u(x) = F (x, u(x)) on Fw K for any |w| = m and boundary conditions u(Fw qj ) = aj with V0 = {q1 , q2 , q3 } has a unique solution. 28 First of all, before we begin the proof, we note that there is a typo in [2]. At Theorem 2.3 the expression Qj = 1 12 dνj + 15 25 dν Qj = 12 dνj 1 + . 25 25 dν should be replaced with Then, we have the following scaling property for the energy Laplacian. 3 ∆ν (u ◦ Fj ) = Qj (∆ν u) ◦ Fj 5 for Qj = 1 15 + 12 dνj 15 dν . And using this, on page 8 of [2] we get that m 3 ∆ν (u ◦ Fw ) = Qw (∆ν u) ◦ Fw 5 for w = (w1 , ..., wm ) a finite word of length m and Fw = Fw1 ◦ Fw2 ◦ · · · ◦ Fwm and Qw = Qwm · (Qwm−1 ◦ Fwm ) · (Qw−2 ◦ Fw−1 ◦ Fwm ) · · · (Qw1 ◦ Fw2 ◦ · · · ◦ Fwm ). In the following, we will use the estimate from [2] ν(Fim K) m 3 =Θ 5 from which it is obvious that ν(Fim K) = O m 3 . 5 Now we are ready to prove the theorem. Proof. First, we study the case in which all aj = 0. By changing the variable x → Fw x where w is a word of length m, the original equation becomes −∆ν (u ◦ Fw )(x) = m 3 Qw (x)F (Fw x, u ◦ Fw (x)) 5 29 for x ∈ K. Let v = u ◦ Fw . Then, the equation along with the boundary conditions above becomes m 3 −∆ν v(x) = Qw (x)F (Fw x, v(x)) on K 5 v|V0 = 0 which we can write in an equivalent way to v(x) = m Z 3 G(x, y)Qw (y)F (Fw y, v(y))dν(y). 5 K Let Gv(x) to be m Z 3 Gv(x) = G(x, y)Qw (y)F (Fw y, v(y))dν(y). 5 K The space of continuous functions v is a Banach space and thus to obtain our result it suffices to show that G satisfies the hypotheses of the contractive mapping principle on a suitable ball (kvk∞ 6 T ) . Since G(x, y) is continuous and bounded (let G0 be an upper bound), we have that m 3 |Gv(x)| 6 kQw (y)k∞ G0 FT 5 where FT is an upper bound for |F (x, u)| for x ∈ K and |u| 6 T First, to bound kQw (y)k∞ we have that kQw (y)k∞ = kQwm (y)·(Qwm−1 ◦Fwm y)·(Qw−2 ◦Fw−1 ◦Fwm y) · · · (Qw1 ◦Fw2 ◦· · ·◦Fwm y)k∞ 6 kQwm · Qwm−1 · · · Qw1 k∞ 6 kQwm k∞ · kQwm−1 k∞ · · · kQw1 k∞ . However, we have that for any j = 0, 1, 2 that kQj k∞ = k 12 dνj 1 12 dνj 1 + k∞ 6 + k k∞ . 15 15 dν 15 15 dν Here, we will use the key result from [2], Theorem 3.5 page 10. This theorem proves not only the discontinuity of the Radon-Nikodym derivative but also gives us bounds on its values with respect to the energy measure taken. In our case we see that the Radon-Nikodym derivative is bounded by 23 . Then 30 kQj k∞ 6 1 12 2 3 + · = . 15 15 3 5 2m G0 FT so we And thus, we have that kQw k∞ 6 ( 35 )m . Then, |G(x)| 6 35 3 2m G0 FT 6 T to conclude just have to take m large enough such that 5 0 that G maps the ball to itself. For v and v in this ball, we have that 2m 3 |Gv(x) − Gv (x)| 6 G0 MT kv − v 0 k∞ 5 2m so we get the contractive mapping estimate as long as 35 G0 MT < 1. 0 Now, to modify the proof for the case of general {aj }. Let h(x) denote the harmonic function which satisfies the same boundary conditions as u. Then (w = u − h)|Fw V0 = 0 and solves the equation −∆ν w = F (x, h(x) + w(x)) so it is the same as in the initial special case with F being changed to F 0 (x, u) = F (x, h(x) + u). Note that |h(x)| 6 A, so by taking T = 2A, we have |F 0 (x, u)| 6 FT if kuk∞ 6 A, and we can apply the same argument as before. 31 5 Approximation by functions vanishing in a neighborhood of the boundary Now, we will generalize some results found in [6] in section 7 “Spline cut-offs” from the standard Laplacian to the Kusuoka Laplacian. It is proven in [10] that we have a “weak=strong” property for the Laplacian, as long as certain conditions are satisfied for the test functions, namely that v(qi ) = 0 and ∂n v(qi ) = 0. These conditions have been weakened in [6] to the smaller class of functions v such that they vanish on a neighborhood of the boundary. Our goal in this section is to obtain a similar result for the Kusuoka Laplacian as well. Lemma 5.1. For any u ∈ H1 we have that k∆ν u|Fw K k∞ ! 2m m 5 5 6c sup |u| + sup |∂n u| . 3 3 ∂Fw K ∂Fw K Proof. Since ∆ν u is harmonic, we simply have to bound its values on ∂Fw K = Fw ∂K. Now, for w equal to the empty word, the above estimate is an immediate consequence of the basis for H1 defined in [6]. The general case then follows from the scaling m property for the Kusuoka Laplacian, where we substitute kQw k∞ = 53 and the scaling property for the normal derivatives as well. Lemma 5.2. Let ∆ν be the Kusuoka Laplacian and f ∈ dom∆ν such that it vanishes along with its normal derivatives on the boundary. Then f|∂Fim K 2m 3 =O 5 and ∂n f |∂Fim K m 3 =O . 5 Proof. For the first part: First, let i = 0, 1, 2. Then, 1 1 u(x) = (u(x) + u(Ri x)) + (u(x) − u(Ri x)) 2 2 32 where Ri is the reflection around the point qi . For shorter notation let’s call the symmetric part u+ and the skew symmetric part u− . Then, ∂n u− (qi ) = 0 since always for a skew-symmetric function the normal derivatives are zero. But then, this implies that also ∂u+ (qi ) = 0 since we assumed that u has its normal derivatives zero on the boundary. Then we have that 2m 3 sup |u| 6 sup |u− | + sup |u+ | 6 O 5 ∂Fim K ∂Fim K ∂Fim K by using theorem 3.1 and 3.6 from [5]. For the second part: We use the Gauss-Green formula localized to Fim K with the functions u = f and v = h where h is the harmonic function taking the values 1,-1,0 on the boundary points of Fim K (the value 1 at the point qi ) Then, this gives us Z − h∆f dν = Fim K X f (Fim x)∂n h(Fim x) − h(Fim x)∂n f (Fim x). x∈V0 By assumption, ∂n f (Fim qi ) = 0 so the only term in the right hand side of the form −h(Fim x)∂n f (Fim x) that occurs is the single value at the mvertex where h assumes the value -1. The integral on the left side is O 53 since 3 m h and f are uniformly bounded and the measure is O and the terms of 5 3 m 5 m m m m the form f (Fi x)∂n h(Fi x) are O 5 since ∂n h(Fi x) = O 3 and f (Fim x) 2m 3 =O 5 by the first part of this lemma. Using these two lemmas, we are ready to prove the following theorem. Theorem 5.3. For the Kusuoka Laplacian on SG, suppose that f ∈ dom∆ν and f vanishes together with its normal derivatives on the boundary. Then there exists a sequence of functions {fm } with each fm ∈ domE vanishing in a neighborhood of the boundary with fm → f uniformly, E(fm − f ) → 0 and ∆ν fm → ∆ν f in Lp (dν) for any p < ∞. 33 Proof. As in the proof of theorem 7.1 on [6], we choose fm so that fm = f on Ωm with support in Ωm+1 . On each of the sets Fim K we take fm to be the spline locally in S(H1 , Vm+1 ) so that fm = f and ∂n fm = ∂n f at the two boundary points of Fim K not equal in qi and fm = 0 and ∂n fm = 0 in the other 4 vertices in Vm+1 ∩ Fim K. Because we have matched the values of the functions and the normal derivatives, the functions fm will be in dom∆ν . We will show that Z Fim K |∆ν fm |p dν → 0 as m → ∞ for every p < ∞. After this, the proof is identical to the standard Laplacian case since no other differences between the standard and the energy Laplacian arise. We will use the previous lemma. We have then that: k∆ν fm |Fim K k∞ 2m m 5 5 6 c[ sup |f | + sup |∂n f |] 3 3 ∂Fim K ∂Fim K and by using the lemmas above, we have that k∆ν fm |Fim K k∞ 6 C and thus m we get that since ν(Fim K) = O 35 Z |∆ν fm |p dν → 0 Fim K Then, the proof for the following interesting Corollary on [6] is exactly identical to the standard Laplacian case by using the above theorem and can be found at [6]. Corollary 5.4. Let ∆ be the Kusuoka Laplacian on SG. If u ∈ L2 (dν) and f ∈ L2 (dν) (respectively, f is continuous), and Z Z u∆vdν = f vdν K K for all v ∈ domC (∆ν ) vanishing on a neighborhood of the boundary, then u ∈ domL2 (∆ν ) (respectively domC (∆ν ) and ∆ν = f . 34 References [1] J. Azzam, M.A. Hall and R.S. Strichartz, Conformal energy, conformal Laplacian, and energy measures on the Sierpinski gasket, Trans. Amer. Math. Soc. 360 (2008), 2089–2131. [2] R. Bell, C.-W. Ho and R.S. Strichartz, Energy measures of harmonic functions on the Sierpinski gasket, preprint, arXiv [3] J. Needleman, R.S. Strichartz, A. Teplyaev, P.-L. Yung, Calculus on the Sierpinski gasket. I. Polynomials, exponentials and power series, J. Funct. Anal. 215 (2004), no. 2, 290–340. [4] R.S. Strichartz, Differential Equations on Fractals, Princeton University Press, Princeton 2006. [5] R.S. Strichartz and S.T. Tse, Local behavior of smooth functions for the energy Laplacian on the Sierpinski gasket, Analysis 30 (2010), 285–299. [6] R.S. Strichartz and Michael Usher, Splines on Fractals, Mathematical Proceedings of the Cambridge Philosophical society 129 (2000), 331– 360. [7] Eric D. Mbakop, Analysis on Fractals, Worcester Polytechnique Institute (2009) [8] R.S. Strichartz, Solvability for differential equations on Fractals, Journal d’Analyse Mathmatique, 96 (2005), 247–267. [9] Oren Ben-Bassat, R.S. Strichartz, Alexander Teplyaev, What Is Not in the Domain of the Laplacian on Sierpinski Gasket Type Fractals, Journal of Functional Analysis 166 (1999), 197–217. [10] R.S. Strichartz, Some Properties of Laplacians on Fractals, Journal of Functional Analysis, 164,Issue 2 (1999), 191–208. [11] Alexander Teplyaev, Energy and Laplacian on the Sierpinski Gasket, Fractal Geometry and Applications: A Jubilee of Benoit Mandelbrot, Part 1. Proceedings of Symposia in Pure Mathematics, 72, Amer. Math. Soc., (2004), 131–154. [12] J. Kigami, Harmonic calculus on p.c.f. self-similar sets, Trans. Amer. Math. Soc. 335(2) (1993), 721–755. 35 [13] J. Kigami, Analysis on fractals, Cambridge Tracts in Mathematics 143, Cambridge, 2001. [14] A. Pelander,Solvability of differential equations on open subsets of the Sierpinski Gasket, Journal d’Analyse Mathématique, 102, Issue 1 (2007), 359–369 36

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