Area distortion of quasiconformal mappings

Size: px
Start display at page:

Download "Area distortion of quasiconformal mappings"

Transcription

1 Area dstorton of quasconformal mappngs K. Astala 1 Introducton A homeomorphsm f : Ω Ω between planar domans Ω and Ω s called K-quasconformal f t s contaned n the Sobolev class W2,loc 1 (Ω) and ts drectonal dervatves satsfy max α α f(x) Kmn α α f(x) a.e. x Ω. In recent years quasconformal mappngs have been an effcent tool n the study of dynamcal systems of the complex plane. We show here that, n turn, methods or deas from dynamcal systems can be used to solve a number of open questons n the theory of planar quasconformal mappngs. It has been known snce the work of Ahlfors [A] and Mor [Mo] that K-quasconformal mappngs are locally Hölder contnuous wth exponent 1/K. The functon f 0 (z) = z z 1 K 1 (1) shows that ths exponent s the best possble. In addton to dstance, quasconformal mappngs dstort also the area by a power dependng only on K, as shown frst by ojarsk [j]. Snce f 0 (r) = π 1 1 K (r) 1 K, where (r) = {z C : z < r}, t s natural to expect that the optmal exponent n area dstorton s smlarly 1/K. In ths paper we gve a postve answer to ths problem and prove the followng result whch was conjectured and formulated n ths precse form by Gehrng and Rech [GR]. We shall denote by the open unt dsk and by E the area of the planar set E. Theorem 1.1 Suppose f : s a K-quasconformal mappng wth f(0) = 0. Then we have fe M E 1/K (2) for all orel measurable sets E. Moreover, the constant M = M(K) depends only on K wth M(K) = 1 + O(K 1). For the proof of (2) we consder famles { } n 1 of dsjont dsks = (λ) whch depend holomorphcally on the parameter λ (n a sense to be defned later). After an approxmaton (2) now becomes equvalent to ( n ) 1 λ (λ) C (0) 1+ λ, (3) 1

2 where C depends only on λ. Furthermore, teratng the confguraton one s led to measures on Cantor sets and there we shall apply the Ruelle-owen thermodynamc formalsm [w]; f we wrte (3) n terms of the topologcal pressure, then the proof comes out n a transparent way. The functon f 0 s extremal n the dstorton of area as well as dstance, and therefore t s natural to ask [I, 9.2] f for quasconformal mappngs the Hölder contnuty alone, rather than the dlataton, mples the nequalty (2). However, ths turns out to be false, as shown recently by P.Koskela [K]. As s well known the optmal control of area dstorton answers several questons n ths feld. For example, n general domans Ω one can nterpret (2) n terms of the local ntegrablty of the Jacoban J f of the quasconformal mappng f. Ths leads to a soluton of the well known problem [LV], [Ge] on the value of the constant p(k) = sup{p : J f L p loc (Ω) for each K quasconformal f on Ω}. Corollary 1.2 In every planar doman Ω, p(k) = K K 1. In other words, for each K-quasconformal f : Ω Ω, f W 1 p,loc(ω), p < 2K K 1. The example (1) shows that ths s false for p 2K K 1. Theorem 1.1 governs also the dstorton of the Hausdorff dmenson dm(e) of a subset E. Corollary 1.3 Let f : Ω Ω be K-quasconformal and suppose E Ω s compact. Then 2 K dm(e) dm(fe) 2 + (K 1) dm(e). (4) Ths nequalty, as well, s the best possble. Theorem 1.4 For each 0 < t < 2 and K 1 there s a set E C wth dm(e) = t and a K-quasconformal mappng f of C such that dm(fe) = 2 K dm(e) 2 + (K 1) dm(e). The estmate (4) was suggested by Gehrng and Väsälä [GV]. It can also be formulated [IM2] n the symmetrc form 1 ( 1 K dm(e) 1 ) 1 2 dm(fe) 1 ( 2 K 1 dm(e) 1 ). (5) 2 The results 1.3 and 1.4 are closely related to the removablty propertes of quasregular mappngs, snce n plane domans these can be represented as compostons of analytc functons and quasconformal mappngs. The strongest removablty conjecture, due to Iwanec and Martn [IM1], suggest that sets of Hausdorff d measure zero, d = n K+1, are removable for bounded quasregular mappngs n Rn. Here we obtan the followng. 2

3 Corollary 1.5 In planar domans sets E of Hausdorff dmenson dm(e) < 2 K + 1 are removable for bounded quasregular mappngs. Conversely, for each K 1 and t > 2/(K + 1) there s a t dmensonal set E C whch s not removable for some bounded K quasregular mappngs. In addton to [IM1] removablty questons have recently been studed for nstance n [JV], [KM] and [R]. Fnally, we menton the applcatons to the regularty results of quasregular mappngs. Recall that a mappng f W 1 q,loc(ω), 1 < q < 2, s sad to be weakly quasregular, f J f 0 almost everywhere and max Df(x)h K mn Df(x)h a.e. x Ω. h =1 h =1 Then f s K quasregular n the usual sense f f W2,loc 1 (Ω),.e. f J f s locally ntegrable. We can now consder the number q(k), the nfmum of the q s such that every weakly K quasregular mappng f Wq,loc 1 (Ω) s actually K quasregular. Corollary 1.6 q(k) = K 2K + 1. Indeed, Lehto and Vrtanen [LV] have proven that the precse estmate on the L p ntegrablty, Corollary 1.2, mples that q(k) 2K 2K K+1. The opposte nequalty q(k) K+1 was shown by Iwanec and Martn n [IM1]. Quasconformal mappngs are also the homeomorphc solutons of the ellptc dfferental equatons f(z) = µ(z) f(z); here µ s the complex dlataton or the eltram coeffcent of f wth µ = K 1 K+1 < 1. Hence there are close connectons to the sngular ntegral operators and especally to the eurlng-ahlfors operator Sω(z) = 1 π C ω(ζ) dm(ζ) (ζ z) 2, see [I],[IM1],[IK] for example. In fact, ths operator was the man tool n the work of ojarsk [j] and Gehrng-Rech [GR], c.f. also [IM2]. elow we shall use mostly dfferent approaches and the role of the S operator remans mplct. Stll the area dstorton nequalty has a number of mplcatons on the propertes of S. In partcular, we have Corollary 1.7 There s a constant α 1 such that for any measurable set E, Sχ E dm E log α E. (6) It s for ths consequence that we must show the asymptotc estmate M(K) = 1 + O(K 1) and then, actually, Theorem 1.1 s equvalent to 1.7, cf. [GR]. 1 1 Davd Hamlton and Tadeusz Iwanec have ponted out that now (6) holds wth α = eπ. 3

4 If we consder general functons ω L ( ) then the nequalty (6) mples the correct exponental decay for {z : R Sω > t} when t. As a consequence, for each δ > 1 there s a constant M δ < such that Sv dm δ v log(1 + M δ v v ) dm, v L log L( ). (7) Here v = 1 π v dm s the ntegral mean of v. It s a natural queston whether (7) holds at δ = 1 as n (6) wth characterstc functons. Ths would also mply the Iwanec-Martn removablty conjecture n the planar case. However, n the last secton we show, agan by consderng the nequaltes arsng from the thermodynamc formalsm, that n fact (7) fals when δ = 1. Further results equvalent to the Gehrng-Rech conjecture have been gven by Iwanec and Koseck [IK]. These nclude applcatons to the L 1 theory of analytc functons, quadratc dfferentals and crtcal values of harmonc functons. Moreover, by results of Lavrentev, ers and others the solutons to the ellptc dfferental equatons A(x) u = 0 can be nterpreted n terms of quasregular mappngs f. Therefore Corollary 1.2 yelds sharp exponents of ntegrablty on the gradent u; note that the dlataton of f and so necessarly the optmal ntegrablty exponent depends n a complcated manner on all the entres of the matrx A rather than just on ts ellptcty coeffcent. Acknowledgements Durng the preparaton of ths manuscrpt a number of people found smplfcatons n the frst prelmnary notes. Especally I would lke to thank Alexander Eremenko and Jose Fernandez who both ponted out Corollary 2.4. Also, I would thank Tadeusz Iwanec and Mchel Znsmester for mportant dscussons and comments on the topcs n ths paper and many people, ncludng Alexander Eremenko, Fred Gehrng, Seppo Rckman, Juha Henonen and Pekka Koskela for readng and makng correctons to the frst draft. 2 Holomorphc deformatons of Cantor sets Let us frst consder a famly { } n of nonntersectng subdsks of. We shall study the quasconformal deformaton of such famles and, n partcular, estmate sums r( ) t, t R, (8) where r( ) denotes the radus of. Lookng for the extremal phenomena we can terate the confguraton { } n and are thus led to Cantor sets. There one needs measures µ whch reflect n a natural manner the propertes of the sums (8). It turns out that such measures can, ndeed, be found by usng the thermodynamc formalsm ntroduced by Ruelle and owen, c.f. [w], [W]. To descrbe ths n more detal suppose hence that we are gven smlartes γ, 1 n, for whch = γ. Snce the γ are contractons, there s a unque compact 4

5 subset J of the unt dsk for whch n γ (J) = J. Thus J s self-smlar n the termnology of Hutchnson [H]. We can also reverse ths pcture and defne the mappng g : by g = γ 1. Now J = g k, k=0 and g s a n-to-1 expandng mappng wth J completely nvarant, J = gj = g 1 J. Furthermore, g represents the shft on J; n a natural manner we can dentfy the pont x J wth the sequence (j k ) k=0 {1,..., n}n by defnng j k = f g k (x). Then, n ths dentfcaton, g : (j k ) k=0 (j k+1) k=0. In the sequel we use the notaton J = J(g) for our Cantor set and say also that t s generated by the smlartes γ. Next, let s = dm(j(g)), the Hausdorff dmenson of J(g). Then the Hausdorff s measure s nonzero and fnte on J(g) and after a normalzaton t defnes a probablty measure µ s whch s nvarant under the shft g,.e. µ s (g 1 E) = µ s (E) for all borelan E J(g). A general and systematc way to produce further nvarant measures s provded by the Ruelle-owen formalsm: Gven a Hölder contnuous and real valued functon ψ on J(g) there s a unque shft-nvarant probablty measure µ = µ ψ, called the Gbbs measure of ψ, for whch the supremum P (ψ) = sup { h µ (g) + J(g) ψ dµ : µ s g nvarant} (9) s attaned, see [w] or [W]. Here h µ (g) denotes the entropy of µ and the quantty P (ψ) s called the topologcal pressure of ψ. Let us then look for the Gbbs measures that are related to the sums (8). Recall that s = dm(j(g)) s the unque soluton of P ( s log g ) = 0, and ths suggest the choces ψ t = t log g. It then readly follows from [w, Lemma I.1.20], that ( P ( t log g n ) = log γ t) ( n = log r( ) t). (10) 5

6 In fact, the functons ψ = ψ t are n our stuaton locally constant and therefore t can be shown that the system g : (J(g), µ ψ ) (J(g), µ ψ ) s ernoull. In other words, the numbers p = µ ψ (J ) satsfy n p = 1 and on J(g) = {1,..., n} N µ ψ s the product measure determned by the probablty dstrbuton {p } n of {1,..., n}. Ths enables one to make the dynamcal approach more elementary, as ponted to us by Alexander Eremenko. We are grateful to hm for lettng us to nclude ths smplfcaton here. For the readers convenence let us recall the proof of the varatonal prncple, the counterpart of (9), n the elementary settng of product measures. Then also the entropy of µ = µ ψ attans the smple form h µ (g) = p log p. 1 Lemma 2.1 Let ν be a product measure on J(g) determned by the probablty dstrbuton {q } n. Then for each t R, wth equalty f and only f h ν (g) t log g dν log( r( ) t ) J(g) q = r( ) t n r( ) t, 1 n. Proof: Snce the logarthm s concave on R +, h ν (g) t J(g) log g dν = q log γ t q = q log r( ) t q log( r( ) t ) where the equalty holds f and only f q r( ) t 1 n. has the same value for each Remark. In the elementary settng, one can use (10) as the defnton of the pressure P ( t log g ). Note also that f s = dm(j(g)), then n r( ) s = 1, or P ( s log g ) = 0, and the extremal measure n Lemma 2.1 s agan the normalzed Hausdorff s measure. We shall next consder holomorphc famles of Cantor sets or pars (g λ, J(g λ )), λ. y ths we mean that each set J(g λ ) s generated as above by smlartes γ,λ (z) = a (λ)z + b (λ), 1 n, where the coeffcents a (λ) 0, b (λ) now depend holomorphcally on the parameter λ. On the other hand, we can also consder the (λ) = γ,λ and say that { (λ)} n 1 s a holomorphc famly of dsjont dsks n. oth of these confguratons can be descrbed as holomorphc motons; recall that a functon Φ : A C s called a holomorphc moton of a set A C f 6

7 () for any fxed a A, the map λ Φ(λ, a) s holomorphc n () for any fxed λ, the map a Φ λ (a) = Φ(λ, a) s an njecton, and () the mappng Φ 0 s the dentty on A. In fact, (global) quasconformal mappngs and holomorphc motons are just dfferent expressons of the same geometrc quantty. For nstance, accordng to Slodkowsk s generalzed λ lemma ([Sl], see also [AM], 3.3) the correspondence γ,0 (z) γ,λ (z) for z and 1 n, extends to a quasconformal mappng Φ λ : C C wth K(Φ λ ) 1+ λ 1 λ. Therefore the estmate ( n ) 1 λ 1+ λ (λ) C (0) (11) s a specal case of the Gehrng-Rech conjecture. ut after smplfyng arguments, gven later n Lemmas 3.1 and 3.3, we wll see that the conjecture s n fact equvalent to (11). Expressng ths nequalty now n terms of the topologcal pressure (10) we end up wth the followng formulaton. Theorem 2.2 Suppose that (g λ, J(g λ )) depends holomorphcally on the parameter λ. Then 1 + λ 1 λ P ( 2 log g 0 ) P ( 2 log g λ ) 1 λ 1 + λ P ( 2 log g 0 ). Proof: y the varatonal nequalty 2.1 for each λ there s a unque (product) measure µ λ such that P ( 2 log g λ ) = h µλ (g λ ) 2 log g λ (z) dµ λ (z) (12) and clearly log g λ (z) s harmonc n λ. To use Harnack s nequalty we freeze the measure µ λ. In other words, gven a probablty dstrbuton {p } n 1 on {1,..., n}, defne for each λ a product measure µ λ on J(g λ ) by the condton µ λ (J(g λ ) (λ)) = p ; ths s possble snce the dsks (λ) reman dsjont. y the constructon, h µλ (g λ ) s also constant n λ. Moreover, we have that P ( 2 log g λ ) < 0, snce P ( s log g λ ) s strctly decreasng n s and t vanshes for s = dm(j(g)) < 2. Alternatvely, we may also use here the dentty (10) to P ( 2 log g λ ) = log( n r( (λ)) 2 ) < 0. If now the numbers {p } are so chosen that µ 0 = µ 0 (the maxmzng measure n (12) when the parameter λ = 0), then Harnack s nequalty wth 2.1 mples that J(g λ ) 1 + λ 1 λ P ( 2 log g 0 ) = 1 + λ ( h µ0 (g 0 ) 2 1 λ h µλ (g λ ) 2 J(g λ ) J(g 0 ) log g λ dµ λ P ( 2 log g λ ) 7 log g 0 dµ 0 )

8 whch proves the frst of the requred nequaltes. symmetry n λ and 0. The second follows smlarly by When t > 2 the same nequaltes hold for P ( t log g λ ) as well. However, smaller exponents must change wth λ and we shall later see how ths reflects n the precse dstorton of Hausdorff dmenson under quasconformal mappngs. Corollary 2.3 If (g λ, J(g λ )) s as above and 0 < t 2, set t(λ) = Then 1 t(λ) P ( t(λ) log g λ ) 1 λ λ t P ( t log g 0 ). t(1 + λ ) (1 λ + t λ ). Proof: If {µ λ } λ s a famly of product measures on J(g λ ), all defned by a fxed probablty dstrbuton {p } n 1 lke n the prevous theorem, then by t(λ) h µ λ (g λ ) log g λ dµ λ = h µλ (g λ )( 1 t(λ) 1 2 ) h µ λ (g λ ) log g λ dµ λ J(g λ ) 1 λ ( h µ0 (g 0 )( λ t 1 2 ) h µ 0 (g 0 ) 1 λ λ t P ( t log g 0 ) J(g 0 ) J(g λ ) log g 0 dµ 0 ) and takng the supremum over the product measures on J(g λ ) proves the clam. The above estmates for the topologcal pressure hold actually n a much greater generalty. We can consder, for nstance, polynomal-lke mappngs of Douady and Hubbard [DH]. More precsely, suppose we have a famly of holomorphc functons f λ defned on the open sets U λ, λ, such that U λ f λ U λ. We need to assume that J(f λ ) = f n λ U λ n=0 s a mxng repeller for f λ. That s, f λ 0 for z J(f λ) and J(f λ ) s compact n C wth no proper f λ nvarant relatvely open subsets. Then the f λ are expandng on J(f λ ) and the thermodynamc formalsm extends to f λ : J(f λ ) J(f λ ), see [w] or [Ru]. To consder the dependence on the parameter, let U λ depend contnuously on λ and let (λ, a) f λ (a) be holomorphc whenever defned. ecause the functons are expandng, we have a holomorphc moton of the perodc ponts ([MSS], p.198). Snce these are dense n the repeller J(f λ ), by the λ lemma of Mañé, Sad and Sullvan we obtan a holomorphc moton Φ of J(f 0 ) such that J(f λ ) = Φ λ J(f 0 ) and f λ Φ λ = Φ λ f 0. Combnng these facts we conclude that 1 t(λ) P ( t(λ) log f λ ) 1 λ λ t P ( t log f 0 ). (13) 8

9 Namely, snce the varatonal prncple generalzes to ths settng, the proof of (13) s as n Lemma 2.3. In ths case to show that P ( t(λ) log f λ ) < 0 we may use Mannng s formula [M] h µ (f λ ) dm(µ) = log f λ dµ J(f λ ) and the fact [Su] that dm(µ) nf{dm(e) : µ(e) = 1} dm(j(f λ )) < 2. These hold for any ergodc f λ nvarant measure on J(f λ ). Especally, startng from a measure µ on J(f 0 ) we can take the mages µ λ = Φ λ µ under the holomorphc moton, and snce the entropy s an somorphsm nvarant, (13) follows. On the other hand, f one looks for the mnmal approach to the quasconformal area dstorton, then the above leads also to a proof for (11) that avods the thermodynamc formalsm. In fact, ths was shown to us by A. Eremenko and J.Fernandez, who ndependently ponted out the followng result on the (nonharmonc!) functon log f(z). Corollary 2.4 Let n = {z C n : z < 1}. If f : n s a holomorphc mappng such that all of ts coordnate functons f are everywhere nonzero, then 1 + z 1 z log f(0) log f(z) log f(0). 1 z 1 + z Proof: If f = (f 1,..., f n ), consder numbers p > 0 wth n 1 p = 1 and set p u(z) = p log f (z) 2. Then u(z) s harmonc and by Jensen s nequalty, e u(z) n f 1 p (z) 2 p < 1, u s also postve. Hence usng the concavty of the logarthm and the Harnack s nequalty we may deduce log f(z) 2 p log f (z) 2 p 1 + z 1 z p log f (0) 2 p. proves the frst nequalty. The second follows by symme- Choosng fnally p = f (0) 2 f(0) 2 try. 3 Dstorton of area We shall reduce the proof of the area dstorton estmate fe M E 1/K nto two dstnct specal cases. In the frst, where we use the nequaltes of the prevous secton, let us assume that E s a fnte unon of nonntersectng dsks = (z, r ), 1 n. 9

10 Lemma 3.1 Suppose that f : s K quasconformal wth f(0) = 0. If f s conformal n E = n 1, then ( n ) 1 f C(K) K, where the constant C(K) depends only on K. Moreover, C(K) = 1 + O(K 1). Proof: Extend f frst to C by a reflecton across S 1 and assume wthout loss of generalty that f(1) = 1. Then we can embed f to a holomorphc famly of quasconformal mappngs of C. However, n order to control the dstorton as K we need to modfy f near. Thus, f µ s the eltram coeffcent of (the extended) f, defne new dlatatons by { λ K+1 µ λ (z) = K 1 µ(z), z 2, 0, z > 2. y the measurable Remann mappng theorem there are unque µ λ quasconformal mappngs f λ : C C normalzed by the condton f λ (z) z = O( 1 ) as z. z Then f λ s conformal n E, f λ (z) and ts dervatves (when z E) depend holomorphcally on λ [A, Theorem 3], f 0 (z) z and f λ 0 = K 1 K+1, then f λ0 = Φ f, (14) where Φ s conformal n f(0, 2). To apply Theorem 2.2 note that by Koebe s 1/4 theorem ( D (λ) f λ (z ), r ) 4 f λ(z ) f λ (z, r ) and smlarly f λ (0, 2) (0, 8). Also D (λ) = ψ λ, D (0), where ψ,λ (z) = f λ(z ) (z z ) + f λ (z ), and thus {D (λ)} n 1 s a holomorphc famly of dsjont dsks contaned n (0, 8). Therefore we need only choose extra smlartes φ : (0, 8) D (0), 1 n, set γ,λ = ψ,λ φ and note that these generate a holomorphc famly of Cantor sets J(g λ ) (0, 8). y Theorem 2.2 P ( 2 log g λ 1 λ ) 1+ λ P ( 2 log g 0 ) or, n other words, by (11) 4 λ ( f λ(z ) 2 r 2 1+ λ n ) 1 λ 1+ λ 32. r 2 The Lemma wll then be completed by smple approxmaton arguments. Snce the mages of crcles under global quasconformal mappngs have bounded dstorton, f λ π max z f λ (z) f λ (z ) 2 πc 0 ( λ ) mn z f λ (z) f λ (z ) 2 10

11 πc 0 ( λ ) f λ(z ) 2 r 2, where the last estmate follows from the Schwarz lemma. Moreover, the correct expresson for the constant C 0 ( λ ), see [L, p.16], shows that C 0 ( λ ) = 1+O( λ ). If we choose λ 0 = K 1 K+1, t then follows that f λ 0 E C 1 (K) E 1 K wth C 1 (K) = 1 + O(K 1). It remans to show that the functon Φ n (14) satsfes Φ (z) C 2 (K) = (1 + O(K 1)) 1 for all z. Frst, snce the dameter of f λ0 (0, 2) s at least four [P, 11.1], the basc bounds on the crcular dstorton, see [L, I.2.5], mply that (f λ0 (0), ρ(k)) f λ0 = Φ for a ρ(k) > 0 dependng only on K. As above, Φ (0) ρ(k) by the Schwarz lemma. Yet another applcaton of the Schwarz lemma, ths tme to the functon λ f λ (z) z, gves f λ (z) z 10 λ, z (0, 2). Ths shows that we may choose ρ(k) = (1 + O(K 1)) 1. Furthermore, as fs 1 = S 1 and f 1 s unformly Hölder contnuous wth constants dependng only on K, f (0, 2) (0, R) for an R = R(K) > 1. Then Koebe s dstorton theorem combned wth Lehto s majorant prncple [L, II.3.5] proves that and the requred estmates follow. ( Φ (z) Φ (1 z R (0) )3 ) K 1 K z R, z, Remark 3.2 The above proof gves us the followng varatonal prncple for planar quasconformal mappngs: Suppose we are gven numbers p > 0 wth n p = 1 and dsjont dsks. Then for each K quasconformal mappng f : for whch f(0) = 0 and we have the nequalty f n 1 s conformal, (15) p log f p 1 K p log p + C(K) (16) where C(K) = O(K 1) depends only on K. n ) In fact, choosng p = f /( f shows that (16) generalzes Lemma 3.1. Somewhat curously, the varatonal nequalty (16) s not true for general quasconformal mappngs, for mappngs whch do not satsfy (15). We shall return to ths n Secton 5 where t wll have mplcatons on the estmates of the L log L norm of the eurlng-ahlfors operator. To prove the complementary case n the area dstorton nequalty we use therefore a dfferent method. We shall apply here the approach due to Gehrng and Rech [GR] based on a parametrc representaton. 11

12 Lemma 3.3 Let f : be K quasconformal wth f(0) = 0. If E s closed and f s conformal outsde E, then fe b(k) E where b(k) = 1 + O(K 1) depends only on K. Proof: As n [GR] defne the eltram coeffcents ν t (z) = sgn(µ(z)) tanh( t T arctanh µ(z) ), t R +, where µ s the complex dlataton of f, T = log K and sgn(w) = w w f w 0 wth sgn(0) = 0. y the measurable Remann mappng theorem we can fnd ν t quasconformal h t : wth h t (0) = 0. If A(t) = h t E, then Gehrng and Rech show that d dt A(t) = φs(χ ) dxdy + c(t) h ht E te (17) where S s the eurlng-ahlfors operator and c(t) s unformly bounded. The functon φ depends only on the famly {h t }, not on E, and from [GR, (2.6) and (3.6)] we conclude that φ 1 and that φ(w) = 0 whenever µ(h 1 t (w)) = 0. Suppose now that f s conformal outsde the compact subset E. Then µ 0 n \E and, n partcular, we obtan φ(z) χ ht E (z). ut S : L 2 L 2 s an sometry and therefore for any set F C, ( ) Sχ F dxdy F 1 2 Sχ F 2 1 dxdy 2 = F. (18) Thus F C d dt A(t) C 0A(t), 0 < t <, and an ntegraton gves h t E = A(t) e C 0t A(0) = e C 0t E. Takng t = log K shows that fe e C 0 log K E = b(k) E, where b(k) = 1 + O(K 1). Remark. On the other hand, as kndly ponted out by the referee, f one consders n C the normal solutons f λ (z) = z + O( z 1 ) of the eltram equaton f z = µf z wth µ supported on E, then n that stuaton the followng argument gves a drect proof for a very precse estmate f(e) K E. Namely, for ω = f z we have f z = 1 + Sω wth ω = µ(1 + Sµ + SµSµ +...). In vew of S 2 = 1 we obtan f(e) = 1 + Sω 2 ω 2 E + 2R Sω, E E 12

13 where for the k th terate E SµSµ... Sµ µ k E as n (18). Thus f(e) E + 2 µ E + 2 µ 2 E +... = E ( µ ) = K E. The area dstorton nequalty s now an mmedate corollary of the two prevous lemmas 3.1 and 3.3. Proof of Theorem 1.1: Suppose that f : s K quasconformal and f(0) = 0. In provng the estmate fe M E 1/K t suffces to study sets of the type E = n 1, where the are subdsks of wth parwse dsjont closures. The general case follows then from Vtal s coverng theorem. To factor f we fnd by the measurable Remann mappng theorem a K quasconformal mappng g :, g(0) = 0, wth complex dlataton µ g = χ \E µ f. Then g s conformal n E and f = h g, where h : s also K quasconformal, h(0) = 0, but now h s conformal outsde ge. Snce quasconformal mappngs preserve sets of zero area, h( ge) = ge = 0, and then Lemmas 3.1 and 3.3 mply fe = h(ge) b(k) ge b(k)c(k) E 1 K, where M(K) b(k)c(k) = 1 + O(K 1) as requred. 2 One of the equvalent formulatons of Theorem 1.1 s the statement that for a K quasconformal f the Jacoban J f belongs to the class weak-l p ( ), p = K K 1. Corollary 3.4 If f : s K quasconformal, f(0) = 0, then for all s > 0, ( M {z : J f (z) s} s ) K K 1, where M depends only on K. Moreover the exponent p = K K 1 Proof: If E s = {z : J f (z) s}, then by Theorem 1.1 s E s J f dm = fe s M(K) E s E s No p larger than 1 K. s the best possble. K K 1 wll do, snce E s = π(ks) K 1 K 1 for f(z) = z z K 1. Proof of Corollary 1.2: If D s a compact dsk n the doman Ω and f : Ω Ω s K quasconformal, choose conformal ψ, φ whch map negbourhoods of D and f D, respectvely, onto the unt dsk. As ψ D and φ fd are blpschtz, applyng Corollary 3.4 to φ f ψ 1 proves that J f L p K loc (Ω) for all p < K 1. 2 Davd Hamlton has nformed us that the same methods can also be used to obtan good bounds for the constant M n fe M E 1/K f one consders nstead of the case f : those mappngs f whch are conformal outsde wth f(z) z = O(1/ z ). 13

14 4 Dstorton of dmenson In the prevous secton we determned the quasconformal area dstorton from the propertes of the pressure P ( 2 log g λ ). Smlarly Corollary 2.3, or the varatonal nequalty (16) wth a sutable choce of the probabltes p, also admts a geometrc nterpretaton: If f : s K quasconformal wth f(0) = 0 and f, n addton, f s conformal n the unon of the dsks, 1 n, then f tk 1+t(K 1) ( C(K) t) 1 1+t(K 1), 0 < t 1, where the constant C(K) depends only on K. Snce the complementary lemma 3.3 fals for exponents t < 2, n the general case we content wth slghtly weaker nequaltes. Lemma 4.1 If 0 < t < 1, f : s K quasconformal, f(0) = 0 and { } n 1 are parwse dsjont sets n, then whenever (1 + t(k 1)) 1 tk < p 1. ( f p C K (t, p) t) 1 1+t(K 1) Proof: We use the ntegrablty of the Jacoban J f as n [GV]. Snce p(1 + t(k 1)) > tk we can choose an exponent 1 < p 0 < K K 1 such that 1 K q 1 + t(k 1) 0 < p, (19) tk where q 0 = p 0 s the conjugate exponent. Then usng Hölder s nequalty twce one p 0 1 obtans f p = ( ) p ( ) p p J f dm p J 0 p q f dm 0 0 ( ) p p J 0 f dm p 0 ( p p 0 ) q 0 p 0 p p 0 p p 0 ( ) p p J 0 f dm p 0 ( p p 0 ) q 0 p 0 p p 0 p p 0. K 1 On the other hand, as p 0 K < 1 < p 1+t(K 1) tk, t follows that > 1 + t(k 1). Combnng ths wth Corollary 3.4 (or 1.2) yelds ( f p M p q 0 (1+t(K 1))) 1 1+t(K 1), p 0 p 0 p where M depends only on p 0 and K. Snce by (19) also t < p q 0 (1 + t(k 1)), the clam follows. 14

15 Proof of Corollary 1.3: If f : Ω Ω s K quasconformal, let E Ω be a compact subset wth dm(e) < 2. Choose also a number 1 2dm(E) < t 1 and cover E by squares wth parwse dsjont nterors. Accordng to [LV], Theorems III.8.1 and III.9.1, da(f ) 2 C 0 f, where the constant C 0 depends only on K, E and Ω. Hence we conclude from Lemma 4.1 that ( da(f ) δ C 1 da( ) 2t) 1 1+t(K 1), δ > 2tK 1 + t(k 1). Wth a proper choce of the coverng { } the sum on the rght hand sde can be made arbtrarly small and thus dm(f E) δ. Consequently, dm(fe) 2 K dm(e) 2 + (K 1) dm(e) (20) whch proves the corollary. In the specal case of K quascrcles Γ, the mages of S 1 under global K quasconformal mappngs, Corollary 1.3 reads as dm(γ) 1 + ( K 1 ) = 2 2 K + 1 K + 1. Ths sharpens recent results due to Jones-Makarov [JM] and ecker-pommerenke [P]. On the other hand, ecker and Pommerenke showed that f the dlataton K 1, then ) 2 ( ( K 1 K+1 dm(γ) K 1 2. K+1) These results suggest the followng Queston 4.2 If Γ s a K quascrcle, s t true that dm(γ) 1 + In the postve case, s the bound sharp? ( K 1 ) 2. K + 1 Let us next show that the equalty can occur n (20) for any value of K and dm(e). Note frst that n terms of the holomorphc motons Corollary 1.3 obtans the followng form. Corollary 4.3. Let Φ : E C be a holomorphc moton of a set E C and wrte d(λ) = dm(φ λ (E)). Then d(λ) 2d(0) (2 d(0)) 1 λ (21) 1+ λ + d(0). Proof: y Slodkowsk s extended λ lemma Φ λ s a restrcton of a K quasconformal mappng of C, K 1+ λ 1 λ, and hence the clam follows from 1.3. For the converse, we start by constructng holomorphc motons of Cantor sets such that the equalty holds n (21) up to a gven ε > 0. Thus for each, say, n 10 fnd 15

16 dsjont dsks (z, r) all of the same radus r = r n, such that 1 2 nr2 1. If 0 < t < 2, let also β(t) = log(n 1/t r). (22) For n large enough, β(t) > 0 and t 2 log r log r β(t) t + ɛ. (23) 2 Set then a t (λ) = exp( β(t) 1 λ 1+λ ). Clearly a t s holomorphc n wth a t ( ) = \{0}. Therefore we can consder the holomorphc famly of smlartes γ,λ (z) = ra t (λ)z + z. Snce the dsks γ,λ (z, r) are dsjont, the smlartes γ,λ generate Cantor sets (g λ, J(g λ )) as n Secton 2. Furthermore, the dervatves γ,λ do not depend on and so the dmenson d(λ) = dm(j(g λ )) s determned from the equaton n(r a t (λ) ) d(λ) = 1. y (22) n(r a t (0) ) t = 1 and therefore d(0) = t. Smlarly, f 0 < λ < 1, t follows from (23) that d(0) d(λ) = log(r a t(λ) ) log(r a t (0) ) d(0) 2 + ( 1 d(0) 2 = log r β(t) 1 λ 1+λ log r β(t) ) 1 λ + ε. (24) 1 + λ Proof of Theorem 1.4: Choose a countable collecton { k } 1 of parwse dsjont subdsks of and defne, usng the argument above, n each dsk k a holomorphc moton Φ of a Cantor set J k wth Φ λ (J k ) k. If d(λ) = dm(φ λ (J k )), we may assume that d(0) = t and that for each k (24) holds wth ε = 1 k. Clearly ths constructon determnes a holomorphc moton Ψ of the unon J = k J k. Wrtng stll d(λ) = dm(ψ λ (J)) we have d(λ) = 2d(0) (2 d(0)) 1 λ 0 λ < 1. 1+λ + d(0), Now Slodkowsk s generalzed λ lemma apples and Ψ extends to a K quasconformal mappng f of C, where K = 1+λ 1 λ, 0 λ < 1. In other words, f E = J, then dm(e) = t and dm(fe) = (2Kdm(E))/(2 + (K 1)dm(E)). Fnally, Corollary 1.5 s an mmedate consequence of 1.3 and 1.4 snce K quasregular mappngs f can be factored as f = φ g, where φ s holomorphc and g K quasconformal; for holomorphc φ sets E wth dm(e) < 1 are removable by Panlevé s theorem whle those wth dm(e) > 1 are never removable [Ga, III. 4.5]. 16

17 Therefore n consderng the removablty questons for K quasregular mappngs, the dmenson d K = 2 K+1 s the border-lne case and there we have the Iwanec-Martn conjecture that all sets of zero Hausdorff d K measure are removable. More generally, t s natural to ask whether the precse bound on the dmenson dm(fe) 2 K dm(e) 2+(K 1) dm(e) gven by Corollary 1.3 s stll correct on the level of measures. 2Kτ 2+τ(K 1). If f s a planar K quas- Queston 4.4 Let 0 < τ < 2 and δ = δ K (τ) = conformal mappng, s t true that H τ (E) = 0 H δ (fe) = 0. If not, what s the optmal Hausdorff measure H h or measure functon h such that f H h H τ? 5 Estmates for the eurlng-ahlfors operator As we saw earler quasconformal mappngs have mportant connectons to the sngular ntegrals and n partcular to the eurlng-ahlfors operator, the complex Hlbert transform Sω(z) = 1 ω(ζ) dm(ζ) π (ζ z) 2. C There are even hgher dmensonal counterparts, see [IM1] and the references there. In fact, many propertes of the S operator can be reduced to the dstorton results of quasconformal mappngs. We shall here consder only the operaton of S on the functon space L log L and refer to the work of Iwanec and Koseck [IK] for further results. In case of the characterstc functons ω = χ E we have then by Corollary 1.7 that Sχ E dm E log α E for all orel subsets E of a dsk C; the constant α does not depend on E or. Ths translates also to the L settng: Corollary 5.1 Let C be a dsk. If ω s a measurable functon such that ω(z) χ (z) a.e. then {z : R Sω(z) > t} 2α e t. (26) Proof: Let E + = {z : R Sω > t}. Snce S has a symmetrc kernel, t E + R Sω dm = R ωsχ E+ E + dm E + log α E + by (25). Thus E + α e t and snce by the same argument E = {z : R Sω < t} satsfes E α e t, the nequalty (26) follows. (25) 17

18 The estmate (26) s sharp snce for ω = (z/z)χ (z) we have Sω = (1 + 2 log z )χ (z). For the modulus Sω Iwanec and Koseck [IK, proposton 12] have shown that (25) mples {z : Sω(z) > t} α(1 + 19t) e t. (27) It remans open f the lnear term 19t can be replaced by a constant. Corollary 5.2 For each δ > 1 there s a constant M(δ) < such that Sv dm δ whenever the rght hand sde s fnte. v(z) log (1 + M(δ) v(z) ) dm(z) v Proof: Let ω be a functon, unmodular n and vanshng n C\, such that Sv dm = ωsv dm = v Sω v dm. v We apply then the elementary nequalty ab a log(1+a)+exp(b) 1. Snce accordng to (27) e Sω /δ α 19δ 1 dm (1 + δ 1 δ 1 ) = M 1(δ), t follows that Sv dm M 1 (δ) v dm + δ v log (1 + δ v ) dm. v Defne now E 0 = {z : v(z) < 1 e v }. As t t log 1 t s ncreasng on (0, 1 e ), e E 0 v log( v v ) dm v E 0 v dm, where we use the conventon 0 log 0 = 0. Thus ( v ) v log (1 + δ v ) dm v \E 0 v log v (e + δ) dm + where M 2 = e 2 + eδ. In concluson, f M = M 2 exp(m 1 (δ)), Sv dm δ whch completes the estmaton. E 0 v log(1 + δ e ) dm v ) v log (M 2 dm, (28) v v log (M v ) dm δ v v log (1 + M v ) dm, v 18

19 Snce the varatonal nequalty (16), p log f p 1 K p log p + C(K) wth C(K) = O(K 1) and f conformal, was the key n the area dstorton Theorem 1.1 t s of nterest to know whether the nequalty s vald wthout any conformalty assumptons. Another natural queston s whether Corollary 5.2 stll holds at δ = 1; for characterstc functons ths s true and (25) wth [IK, proposton 19] mples that for nonnegatve functons v, \E Sv dm E v(z) log (1 + α v(z) ) dm(z), f supp(v) E. v Indeed, t can be shown that these two questons are equvalent (f v 0 n Corollary 5.2). However, t turns out that the answer to them s the negatve. We omt here the proof of the equvalence; nstead we gve frst a smple counterexample to the general varatonal nequalty and then show how ths reflects n the L log L estmates of the complex Hlbert transform. Example 5.3 Choose 0 < ρ < 1 and for 1 n consder the dsjont dsks = (ρ, aρ ) where 0 < a < 1 ρ 1+ρ. Let also p = 1 n and f 0(z) = z z 1 K 1. Then whle p log p = (n + 1) log ρ + log n + log πa 2 p log f 0 n + 1 p K log ρ + log n + C 0 = 1 K p log p + K 1 K log n + C 1, where C 0, C 1 depend only on K and a. Lettng n shows that the varatonal nequalty fals for f 0. Proposton 5.4 For each M < there s an ε > 0 and a nonnegatve functon v L log L( ) such that Sv dm > (1 + ε) v(z) log (1 + M v(z) ) dm(z). v Proof: y nequalty (28) t suffces to show that for no M < does Sv dm hold for all nonnegatve functons v L log L( ). v(z) log (M v(z) ) dm(z) (29) v 19

20 We argue by contradcton. Hence consder frst the mappng f(z) = z z K 1 and mbedd t to a one parameter famly of quasconformal mappngs h t :, as n the proof of Lemma 3.3. Thus for t = log K, h t = f. Suppose next that we have dsjont open sets {D } n 1 and numbers p > 0 wth n1 p = 1. Set then p v t (z) = h t D χ h t D (z). Clearly v t dm = 1 and f ψ(t) = v t log(mv t ) dm then by Jensen s nequalty ψ(t) 0 for M π. Furthermore, we can deduce from the Gehrng-Rech dentty (17) that ψ p d (t) = h t D dt h td = φsv dm c(t) where c(t) s unformly bounded. Thus f (29) holds, then ψ (t) ψ(t) c(t) and after ntegraton ψ(t) e t ψ(0) e t t 0 c(s)e s ds = e t ψ(0) + c 1 (t). Takng t = log K we obtan ( p ) ( p ) p log K p log + C(K), fd D where C(K) = (K 1) log M + c 1 (log K). Fnally, f, p are as n the prevous example wth f 1 (z) = f 0 (z) = z z 1 K 1, we can choose D = f 0. ut ths would mean that p log f 0 p 1 K p log p C(K) K, contradctng Example 5.3. Therefore (29) cannot hold and so the estmate of Corollary 5.2 s sharp. REFERENCES [A] Ahlfors, L., On quasconformal mappngs. J. Analyse Math., 3 (1954), [A] Ahlfors, L. & ers L., Remann s mappng theorem for varable metrcs. Ann. Math., 72 (1960), [AM] Astala, K. & Martn, G., Holomorphc Motons. Preprnt, [P] ecker, J. & Pommerenke Chr., On the Hausdorff Dmenson of Quascrcles. Ann. Acad. Sc. Fenn. Ser. A I Math., 12 (1987), [j] ojarsk,., Generalzed solutons of a system of dfferental equatons of frst order and ellptc type wth dscontnuous coeffcents. Math. Sb., 85 (1957), [w] owen, R., Equlbrum States and the Ergodc Theory of Anosov Dffeomorphsms. Lecture Notes n Math., 470. Sprnger-Verlag, New York-Hedelberg, [DH] Douady, A. & Hubbard J., On the dynamcs of polynomal-lke mappngs. Ann. Sc. Ec. Norm. Sup., 18 (1985),

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

Luby s Alg. for Maximal Independent Sets using Pairwise Independence Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent

More information

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by 6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng

More information

v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

v a 1 b 1 i, a 2 b 2 i,..., a n b n i. SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 455 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces we have studed thus far n the text are real vector spaces snce the scalars are

More information

Support Vector Machines

Support Vector Machines Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.

More information

1 Example 1: Axis-aligned rectangles

1 Example 1: Axis-aligned rectangles COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture # 6 Scrbe: Aaron Schld February 21, 2013 Last class, we dscussed an analogue for Occam s Razor for nfnte hypothess spaces that, n conjuncton

More information

REGULAR MULTILINEAR OPERATORS ON C(K) SPACES

REGULAR MULTILINEAR OPERATORS ON C(K) SPACES REGULAR MULTILINEAR OPERATORS ON C(K) SPACES FERNANDO BOMBAL AND IGNACIO VILLANUEVA Abstract. The purpose of ths paper s to characterze the class of regular contnuous multlnear operators on a product of

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

We are now ready to answer the question: What are the possible cardinalities for finite fields?

We are now ready to answer the question: What are the possible cardinalities for finite fields? Chapter 3 Fnte felds We have seen, n the prevous chapters, some examples of fnte felds. For example, the resdue class rng Z/pZ (when p s a prme) forms a feld wth p elements whch may be dentfed wth the

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

A Probabilistic Theory of Coherence

A Probabilistic Theory of Coherence A Probablstc Theory of Coherence BRANDEN FITELSON. The Coherence Measure C Let E be a set of n propostons E,..., E n. We seek a probablstc measure C(E) of the degree of coherence of E. Intutvely, we want

More information

n + d + q = 24 and.05n +.1d +.25q = 2 { n + d + q = 24 (3) n + 2d + 5q = 40 (2)

n + d + q = 24 and.05n +.1d +.25q = 2 { n + d + q = 24 (3) n + 2d + 5q = 40 (2) MATH 16T Exam 1 : Part I (In-Class) Solutons 1. (0 pts) A pggy bank contans 4 cons, all of whch are nckels (5 ), dmes (10 ) or quarters (5 ). The pggy bank also contans a con of each denomnaton. The total

More information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

On Lockett pairs and Lockett conjecture for π-soluble Fitting classes

On Lockett pairs and Lockett conjecture for π-soluble Fitting classes On Lockett pars and Lockett conjecture for π-soluble Fttng classes Lujn Zhu Department of Mathematcs, Yangzhou Unversty, Yangzhou 225002, P.R. Chna E-mal: ljzhu@yzu.edu.cn Nanyng Yang School of Mathematcs

More information

How Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence

How Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence 1 st Internatonal Symposum on Imprecse Probabltes and Ther Applcatons, Ghent, Belgum, 29 June 2 July 1999 How Sets of Coherent Probabltes May Serve as Models for Degrees of Incoherence Mar J. Schervsh

More information

Extending Probabilistic Dynamic Epistemic Logic

Extending Probabilistic Dynamic Epistemic Logic Extendng Probablstc Dynamc Epstemc Logc Joshua Sack May 29, 2008 Probablty Space Defnton A probablty space s a tuple (S, A, µ), where 1 S s a set called the sample space. 2 A P(S) s a σ-algebra: a set

More information

+ + + - - This circuit than can be reduced to a planar circuit

+ + + - - This circuit than can be reduced to a planar circuit MeshCurrent Method The meshcurrent s analog of the nodeoltage method. We sole for a new set of arables, mesh currents, that automatcally satsfy KCLs. As such, meshcurrent method reduces crcut soluton to

More information

Ring structure of splines on triangulations

Ring structure of splines on triangulations www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAM-Report 2014-48 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon

More information

Loop Parallelization

Loop Parallelization - - Loop Parallelzaton C-52 Complaton steps: nested loops operatng on arrays, sequentell executon of teraton space DECLARE B[..,..+] FOR I :=.. FOR J :=.. I B[I,J] := B[I-,J]+B[I-,J-] ED FOR ED FOR analyze

More information

8 Algorithm for Binary Searching in Trees

8 Algorithm for Binary Searching in Trees 8 Algorthm for Bnary Searchng n Trees In ths secton we present our algorthm for bnary searchng n trees. A crucal observaton employed by the algorthm s that ths problem can be effcently solved when the

More information

NON-CONSTANT SUM RED-AND-BLACK GAMES WITH BET-DEPENDENT WIN PROBABILITY FUNCTION LAURA PONTIGGIA, University of the Sciences in Philadelphia

NON-CONSTANT SUM RED-AND-BLACK GAMES WITH BET-DEPENDENT WIN PROBABILITY FUNCTION LAURA PONTIGGIA, University of the Sciences in Philadelphia To appear n Journal o Appled Probablty June 2007 O-COSTAT SUM RED-AD-BLACK GAMES WITH BET-DEPEDET WI PROBABILITY FUCTIO LAURA POTIGGIA, Unversty o the Scences n Phladelpha Abstract In ths paper we nvestgate

More information

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

More information

Embedding lattices in the Kleene degrees

Embedding lattices in the Kleene degrees F U N D A M E N T A MATHEMATICAE 62 (999) Embeddng lattces n the Kleene degrees by Hsato M u r a k (Nagoya) Abstract. Under ZFC+CH, we prove that some lattces whose cardnaltes do not exceed ℵ can be embedded

More information

Product-Form Stationary Distributions for Deficiency Zero Chemical Reaction Networks

Product-Form Stationary Distributions for Deficiency Zero Chemical Reaction Networks Bulletn of Mathematcal Bology (21 DOI 1.17/s11538-1-9517-4 ORIGINAL ARTICLE Product-Form Statonary Dstrbutons for Defcency Zero Chemcal Reacton Networks Davd F. Anderson, Gheorghe Cracun, Thomas G. Kurtz

More information

where the coordinates are related to those in the old frame as follows.

where the coordinates are related to those in the old frame as follows. Chapter 2 - Cartesan Vectors and Tensors: Ther Algebra Defnton of a vector Examples of vectors Scalar multplcaton Addton of vectors coplanar vectors Unt vectors A bass of non-coplanar vectors Scalar product

More information

How To Assemble The Tangent Spaces Of A Manfold Nto A Coherent Whole

How To Assemble The Tangent Spaces Of A Manfold Nto A Coherent Whole CHAPTER 7 VECTOR BUNDLES We next begn addressng the queston: how do we assemble the tangent spaces at varous ponts of a manfold nto a coherent whole? In order to gude the decson, consder the case of U

More information

Pricing Overage and Underage Penalties for Inventory with Continuous Replenishment and Compound Renewal Demand via Martingale Methods

Pricing Overage and Underage Penalties for Inventory with Continuous Replenishment and Compound Renewal Demand via Martingale Methods Prcng Overage and Underage Penaltes for Inventory wth Contnuous Replenshment and Compound Renewal emand va Martngale Methods RAF -Jun-3 - comments welcome, do not cte or dstrbute wthout permsson Junmn

More information

Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification

Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification Lecture 4: More classfers and classes C4B Machne Learnng Hlary 20 A. Zsserman Logstc regresson Loss functons revsted Adaboost Loss functons revsted Optmzaton Multple class classfcaton Logstc Regresson

More information

COLLOQUIUM MATHEMATICUM

COLLOQUIUM MATHEMATICUM COLLOQUIUM MATHEMATICUM VOL. 74 997 NO. TRANSFERENCE THEORY ON HARDY AND SOBOLEV SPACES BY MARIA J. CARRO AND JAVIER SORIA (BARCELONA) We show that the transference method of Cofman and Wess can be extended

More information

PERRON FROBENIUS THEOREM

PERRON FROBENIUS THEOREM PERRON FROBENIUS THEOREM R. CLARK ROBINSON Defnton. A n n matrx M wth real entres m, s called a stochastc matrx provded () all the entres m satsfy 0 m, () each of the columns sum to one, m = for all, ()

More information

OPTIMAL INVESTMENT POLICIES FOR THE HORSE RACE MODEL. Thomas S. Ferguson and C. Zachary Gilstein UCLA and Bell Communications May 1985, revised 2004

OPTIMAL INVESTMENT POLICIES FOR THE HORSE RACE MODEL. Thomas S. Ferguson and C. Zachary Gilstein UCLA and Bell Communications May 1985, revised 2004 OPTIMAL INVESTMENT POLICIES FOR THE HORSE RACE MODEL Thomas S. Ferguson and C. Zachary Glsten UCLA and Bell Communcatons May 985, revsed 2004 Abstract. Optmal nvestment polces for maxmzng the expected

More information

How To Calculate The Accountng Perod Of Nequalty

How To Calculate The Accountng Perod Of Nequalty Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.

More information

Section 2 Introduction to Statistical Mechanics

Section 2 Introduction to Statistical Mechanics Secton 2 Introducton to Statstcal Mechancs 2.1 Introducng entropy 2.1.1 Boltzmann s formula A very mportant thermodynamc concept s that of entropy S. Entropy s a functon of state, lke the nternal energy.

More information

A Lyapunov Optimization Approach to Repeated Stochastic Games

A Lyapunov Optimization Approach to Repeated Stochastic Games PROC. ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, OCT. 2013 1 A Lyapunov Optmzaton Approach to Repeated Stochastc Games Mchael J. Neely Unversty of Southern Calforna http://www-bcf.usc.edu/

More information

Fisher Markets and Convex Programs

Fisher Markets and Convex Programs Fsher Markets and Convex Programs Nkhl R. Devanur 1 Introducton Convex programmng dualty s usually stated n ts most general form, wth convex objectve functons and convex constrants. (The book by Boyd and

More information

The descriptive complexity of the family of Banach spaces with the π-property

The descriptive complexity of the family of Banach spaces with the π-property Arab. J. Math. (2015) 4:35 39 DOI 10.1007/s40065-014-0116-3 Araban Journal of Mathematcs Ghadeer Ghawadrah The descrptve complexty of the famly of Banach spaces wth the π-property Receved: 25 March 2014

More information

Realistic Image Synthesis

Realistic Image Synthesis Realstc Image Synthess - Combned Samplng and Path Tracng - Phlpp Slusallek Karol Myszkowsk Vncent Pegoraro Overvew: Today Combned Samplng (Multple Importance Samplng) Renderng and Measurng Equaton Random

More information

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy 4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

More information

Finite Math Chapter 10: Study Guide and Solution to Problems

Finite Math Chapter 10: Study Guide and Solution to Problems Fnte Math Chapter 10: Study Gude and Soluton to Problems Basc Formulas and Concepts 10.1 Interest Basc Concepts Interest A fee a bank pays you for money you depost nto a savngs account. Prncpal P The amount

More information

On the Interaction between Load Balancing and Speed Scaling

On the Interaction between Load Balancing and Speed Scaling On the Interacton between Load Balancng and Speed Scalng Ljun Chen, Na L and Steven H. Low Engneerng & Appled Scence Dvson, Calforna Insttute of Technology, USA Abstract Speed scalng has been wdely adopted

More information

Calculation of Sampling Weights

Calculation of Sampling Weights Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

Lecture 3: Force of Interest, Real Interest Rate, Annuity

Lecture 3: Force of Interest, Real Interest Rate, Annuity Lecture 3: Force of Interest, Real Interest Rate, Annuty Goals: Study contnuous compoundng and force of nterest Dscuss real nterest rate Learn annuty-mmedate, and ts present value Study annuty-due, and

More information

Generalizing the degree sequence problem

Generalizing the degree sequence problem Mddlebury College March 2009 Arzona State Unversty Dscrete Mathematcs Semnar The degree sequence problem Problem: Gven an nteger sequence d = (d 1,...,d n ) determne f there exsts a graph G wth d as ts

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fttng of Data Davd Eberly Geoetrc Tools, LLC http://www.geoetrctools.co/ Copyrght c 1998-2016. All Rghts Reserved. Created: July 15, 1999 Last Modfed: January 5, 2015 Contents 1 Lnear Fttng

More information

Cautiousness and Measuring An Investor s Tendency to Buy Options

Cautiousness and Measuring An Investor s Tendency to Buy Options Cautousness and Measurng An Investor s Tendency to Buy Optons James Huang October 18, 2005 Abstract As s well known, Arrow-Pratt measure of rsk averson explans a ratonal nvestor s behavor n stock markets

More information

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem. Producer Theory Producton ASSUMPTION 2.1 Propertes of the Producton Set The producton set Y satsfes the followng propertes 1. Y s non-empty If Y s empty, we have nothng to talk about 2. Y s closed A set

More information

Using Series to Analyze Financial Situations: Present Value

Using Series to Analyze Financial Situations: Present Value 2.8 Usng Seres to Analyze Fnancal Stuatons: Present Value In the prevous secton, you learned how to calculate the amount, or future value, of an ordnary smple annuty. The amount s the sum of the accumulated

More information

Lecture 3: Annuity. Study annuities whose payments form a geometric progression or a arithmetic progression.

Lecture 3: Annuity. Study annuities whose payments form a geometric progression or a arithmetic progression. Lecture 3: Annuty Goals: Learn contnuous annuty and perpetuty. Study annutes whose payments form a geometrc progresson or a arthmetc progresson. Dscuss yeld rates. Introduce Amortzaton Suggested Textbook

More information

NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582

NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582 NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582 7. Root Dynamcs 7.2 Intro to Root Dynamcs We now look at the forces requred to cause moton of the root.e. dynamcs!!

More information

Equlbra Exst and Trade S effcent proportionally

Equlbra Exst and Trade S effcent proportionally On Compettve Nonlnear Prcng Andrea Attar Thomas Marott Franços Salané February 27, 2013 Abstract A buyer of a dvsble good faces several dentcal sellers. The buyer s preferences are her prvate nformaton,

More information

The Greedy Method. Introduction. 0/1 Knapsack Problem

The Greedy Method. Introduction. 0/1 Knapsack Problem The Greedy Method Introducton We have completed data structures. We now are gong to look at algorthm desgn methods. Often we are lookng at optmzaton problems whose performance s exponental. For an optmzaton

More information

Project Networks With Mixed-Time Constraints

Project Networks With Mixed-Time Constraints Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa

More information

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits Lnear Crcuts Analyss. Superposton, Theenn /Norton Equalent crcuts So far we hae explored tmendependent (resste) elements that are also lnear. A tmendependent elements s one for whch we can plot an / cure.

More information

Solution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt.

Solution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt. Chapter 9 Revew problems 9.1 Interest rate measurement Example 9.1. Fund A accumulates at a smple nterest rate of 10%. Fund B accumulates at a smple dscount rate of 5%. Fnd the pont n tme at whch the forces

More information

Do Hidden Variables. Improve Quantum Mechanics?

Do Hidden Variables. Improve Quantum Mechanics? Radboud Unverstet Njmegen Do Hdden Varables Improve Quantum Mechancs? Bachelor Thess Author: Denns Hendrkx Begeleder: Prof. dr. Klaas Landsman Abstract Snce the dawn of quantum mechancs physcst have contemplated

More information

L10: Linear discriminants analysis

L10: Linear discriminants analysis L0: Lnear dscrmnants analyss Lnear dscrmnant analyss, two classes Lnear dscrmnant analyss, C classes LDA vs. PCA Lmtatons of LDA Varants of LDA Other dmensonalty reducton methods CSCE 666 Pattern Analyss

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP) 6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes

More information

INTERPRETING TRUE ARITHMETIC IN THE LOCAL STRUCTURE OF THE ENUMERATION DEGREES.

INTERPRETING TRUE ARITHMETIC IN THE LOCAL STRUCTURE OF THE ENUMERATION DEGREES. INTERPRETING TRUE ARITHMETIC IN THE LOCAL STRUCTURE OF THE ENUMERATION DEGREES. HRISTO GANCHEV AND MARIYA SOSKOVA 1. Introducton Degree theory studes mathematcal structures, whch arse from a formal noton

More information

Bandwdth Packng E. G. Coman, Jr. and A. L. Stolyar Bell Labs, Lucent Technologes Murray Hll, NJ 07974 fegc,stolyarg@research.bell-labs.com Abstract We model a server that allocates varyng amounts of bandwdth

More information

Stability, observer design and control of networks using Lyapunov methods

Stability, observer design and control of networks using Lyapunov methods Stablty, observer desgn and control of networks usng Lyapunov methods von Lars Naujok Dssertaton zur Erlangung des Grades enes Doktors der Naturwssenschaften - Dr. rer. nat. - Vorgelegt m Fachberech 3

More information

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

The Noether Theorems: from Noether to Ševera

The Noether Theorems: from Noether to Ševera 14th Internatonal Summer School n Global Analyss and Mathematcal Physcs Satellte Meetng of the XVI Internatonal Congress on Mathematcal Physcs *** Lectures of Yvette Kosmann-Schwarzbach Centre de Mathématques

More information

) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance

) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance Calbraton Method Instances of the Cell class (one nstance for each FMS cell) contan ADC raw data and methods assocated wth each partcular FMS cell. The calbraton method ncludes event selecton (Class Cell

More information

Efficient Project Portfolio as a tool for Enterprise Risk Management

Efficient Project Portfolio as a tool for Enterprise Risk Management Effcent Proect Portfolo as a tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company January 5, 27 Effcent Proect Portfolo as a tool for Enterprse

More information

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,

More information

On the Solution of Indefinite Systems Arising in Nonlinear Optimization

On the Solution of Indefinite Systems Arising in Nonlinear Optimization On the Soluton of Indefnte Systems Arsng n Nonlnear Optmzaton Slva Bonettn, Valera Ruggero and Federca Tnt Dpartmento d Matematca, Unverstà d Ferrara Abstract We consder the applcaton of the precondtoned

More information

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao

More information

General Auction Mechanism for Search Advertising

General Auction Mechanism for Search Advertising General Aucton Mechansm for Search Advertsng Gagan Aggarwal S. Muthukrshnan Dávd Pál Martn Pál Keywords game theory, onlne auctons, stable matchngs ABSTRACT Internet search advertsng s often sold by an

More information

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,

More information

Uniform topologies on types

Uniform topologies on types Theoretcal Economcs 5 (00), 445 478 555-756/000445 Unform topologes on types Y-Chun Chen Department of Economcs, Natonal Unversty of Sngapore Alfredo D Tllo IGIER and Department of Economcs, Unverstà Lug

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information

Hedging Interest-Rate Risk with Duration

Hedging Interest-Rate Risk with Duration FIXED-INCOME SECURITIES Chapter 5 Hedgng Interest-Rate Rsk wth Duraton Outlne Prcng and Hedgng Prcng certan cash-flows Interest rate rsk Hedgng prncples Duraton-Based Hedgng Technques Defnton of duraton

More information

On Leonid Gurvits s proof for permanents

On Leonid Gurvits s proof for permanents On Leond Gurvts s proof for permanents Monque Laurent and Alexander Schrver Abstract We gve a concse exposton of the elegant proof gven recently by Leond Gurvts for several lower bounds on permanents.

More information

Quantization Effects in Digital Filters

Quantization Effects in Digital Filters Quantzaton Effects n Dgtal Flters Dstrbuton of Truncaton Errors In two's complement representaton an exact number would have nfntely many bts (n general). When we lmt the number of bts to some fnte value

More information

Natural hp-bem for the electric field integral equation with singular solutions

Natural hp-bem for the electric field integral equation with singular solutions Natural hp-bem for the electrc feld ntegral equaton wth sngular solutons Alexe Bespalov Norbert Heuer Abstract We apply the hp-verson of the boundary element method (BEM) for the numercal soluton of the

More information

Politecnico di Torino. Porto Institutional Repository

Politecnico di Torino. Porto Institutional Repository Poltecnco d orno Porto Insttutonal Repostory [Proceedng] rbt dynamcs and knematcs wth full quaternons rgnal Ctaton: Andres D; Canuto E. (5). rbt dynamcs and knematcs wth full quaternons. In: 16th IFAC

More information

FINITE HILBERT STABILITY OF (BI)CANONICAL CURVES

FINITE HILBERT STABILITY OF (BI)CANONICAL CURVES FINITE HILBERT STABILITY OF (BICANONICAL CURVES JAROD ALPER, MAKSYM FEDORCHUK, AND DAVID ISHII SMYTH* To Joe Harrs on hs sxteth brthday Abstract. We prove that a generc canoncally or bcanoncally embedded

More information

Section C2: BJT Structure and Operational Modes

Section C2: BJT Structure and Operational Modes Secton 2: JT Structure and Operatonal Modes Recall that the semconductor dode s smply a pn juncton. Dependng on how the juncton s based, current may easly flow between the dode termnals (forward bas, v

More information

On the Interaction between Load Balancing and Speed Scaling

On the Interaction between Load Balancing and Speed Scaling On the Interacton between Load Balancng and Speed Scalng Ljun Chen and Na L Abstract Speed scalng has been wdely adopted n computer and communcaton systems, n partcular, to reduce energy consumpton. An

More information

Section 5.4 Annuities, Present Value, and Amortization

Section 5.4 Annuities, Present Value, and Amortization Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today

More information

On some special nonlevel annuities and yield rates for annuities

On some special nonlevel annuities and yield rates for annuities On some specal nonlevel annutes and yeld rates for annutes 1 Annutes wth payments n geometrc progresson 2 Annutes wth payments n Arthmetc Progresson 1 Annutes wth payments n geometrc progresson 2 Annutes

More information

How To Calculate An Approxmaton Factor Of 1 1/E

How To Calculate An Approxmaton Factor Of 1 1/E Approxmaton algorthms for allocaton problems: Improvng the factor of 1 1/e Urel Fege Mcrosoft Research Redmond, WA 98052 urfege@mcrosoft.com Jan Vondrák Prnceton Unversty Prnceton, NJ 08540 jvondrak@gmal.com

More information

Face Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching)

Face Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching) Face Recognton Problem Face Verfcaton Problem Face Verfcaton (1:1 matchng) Querymage face query Face Recognton (1:N matchng) database Applcaton: Access Control www.vsage.com www.vsoncs.com Bometrc Authentcaton

More information

Faraday's Law of Induction

Faraday's Law of Induction Introducton Faraday's Law o Inducton In ths lab, you wll study Faraday's Law o nducton usng a wand wth col whch swngs through a magnetc eld. You wll also examne converson o mechanc energy nto electrc energy

More information

When Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services

When Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services When Network Effect Meets Congeston Effect: Leveragng Socal Servces for Wreless Servces aowen Gong School of Electrcal, Computer and Energy Engeerng Arzona State Unversty Tempe, AZ 8587, USA xgong9@asuedu

More information

7.5. Present Value of an Annuity. Investigate

7.5. Present Value of an Annuity. Investigate 7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on

More information

Upper Bounds on the Cross-Sectional Volumes of Cubes and Other Problems

Upper Bounds on the Cross-Sectional Volumes of Cubes and Other Problems Upper Bounds on the Cross-Sectonal Volumes of Cubes and Other Problems Ben Pooley March 01 1 Contents 1 Prelmnares 1 11 Introducton 1 1 Basc Concepts and Notaton Cross-Sectonal Volumes of Cubes (Hyperplane

More information

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

More information

HÜCKEL MOLECULAR ORBITAL THEORY

HÜCKEL MOLECULAR ORBITAL THEORY 1 HÜCKEL MOLECULAR ORBITAL THEORY In general, the vast maorty polyatomc molecules can be thought of as consstng of a collecton of two electron bonds between pars of atoms. So the qualtatve pcture of σ

More information

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS Chrs Deeley* Last revsed: September 22, 200 * Chrs Deeley s a Senor Lecturer n the School of Accountng, Charles Sturt Unversty,

More information

Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures

Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures Mnmal Codng Network Wth Combnatoral Structure For Instantaneous Recovery From Edge Falures Ashly Joseph 1, Mr.M.Sadsh Sendl 2, Dr.S.Karthk 3 1 Fnal Year ME CSE Student Department of Computer Scence Engneerng

More information

On Robust Network Planning

On Robust Network Planning On Robust Network Plannng Al Tzghadam School of Electrcal and Computer Engneerng Unversty of Toronto, Toronto, Canada Emal: al.tzghadam@utoronto.ca Alberto Leon-Garca School of Electrcal and Computer Engneerng

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

I. INTRODUCTION. 1 IRCCyN: UMR CNRS 6596, Ecole Centrale de Nantes, Université de Nantes, Ecole des Mines de Nantes

I. INTRODUCTION. 1 IRCCyN: UMR CNRS 6596, Ecole Centrale de Nantes, Université de Nantes, Ecole des Mines de Nantes he Knematc Analyss of a Symmetrcal hree-degree-of-freedom lanar arallel Manpulator Damen Chablat and hlppe Wenger Insttut de Recherche en Communcatons et Cybernétque de Nantes, rue de la Noë, 442 Nantes,

More information

Simple Interest Loans (Section 5.1) :

Simple Interest Loans (Section 5.1) : Chapter 5 Fnance The frst part of ths revew wll explan the dfferent nterest and nvestment equatons you learned n secton 5.1 through 5.4 of your textbook and go through several examples. The second part

More information

Support vector domain description

Support vector domain description Pattern Recognton Letters 20 (1999) 1191±1199 www.elsever.nl/locate/patrec Support vector doman descrpton Davd M.J. Tax *,1, Robert P.W. Dun Pattern Recognton Group, Faculty of Appled Scence, Delft Unversty

More information