Floating Body, Illumination Body, and Polytopal Approximation

Size: px
Start display at page:

Download "Floating Body, Illumination Body, and Polytopal Approximation"

Transcription

1 Convex Geometric Analysis MSRI Publications Volume 34, 998 Floating Boy, Illumination Boy, an Polytopal Approximation CARSTEN SCHÜTT Abstract. Let K be a convex boy inr an K t its floating boies. There is a polytope that satisfies K t P n K an has at most n vertices, where n e 6 vol (K \ K t t vol (B. Let K t be the illumination boies of K an Q n a polytope that contains K an has at most n ( -imensional faces. Then vol (K t \ K c 4 vol (Q n \ K, where n c t vol (K t \ K.. Introuction We investigate the approximation of a convex boy K in R by a polytope. We measure the approximation by the symmetric ifference metric. The symmetric ifference metric between two convex boies K an C is S (C, K = vol ((C \ K (K \ C. We stuy in particular two questions: How well can a convex boy K be approximate by a polytope P n that is containe in K an has at most n vertices an how well can K be approximate by a polytope Q n that contains K an has at most n ( -imensional faces. Macbeath [Mac] showe that the Eucliean Ball B 2 is an extremal case: The approximation for any other convex boy is better. We have for the Eucliean ball c vol (B 2n 2 S (P n, B 2 c 2 vol (B 2n 2, (. 99 Mathematics Subject Classification. 52A22. This paper was written while the author was visiting MSRI at Berkeley in the spring of

2 204 CARSTEN SCHÜTT provie that n (c 3 ( /2. The right han inequality was first establishe by Bronshtein an Ivanov [BI] an Duley [D,D 2 ]. Goron, Meyer, an Reisner [GMR,GMR 2 ] gave a constructive proof for the same inequality. Müller [Mü] showe that ranom approximation gives the same estimate. Goron, Reisner, an Schütt [GRS] establishe the left han inequality. Gruber [Gr 2 ] obtaine an asymptotic formula. If a convex boy K in R has a C 2 -bounary with everywhere positive curvature, then inf { S (K, P n P n K an P n has at most n vertices} is asymptotically the same as ( + ( 2 2 el κ(x + µ(x, K n where el is a constant that is connecte with Delone triangulations. In this paper we are not concerne with asymptotic estimates, but with uniform. Int(M enotes the interior of a set M. H(x, ξ enotes the hyperplane that contains x an is orthogonal to ξ. H + (x, ξ enotes the halfspace that contains the vector x ξ, an H (x, ξ the halfspace containing x + ξ. e i, i =,..., enotes the unit vector basis in R. [A, B] is the convex hull of the sets A an B. The convex floating boy K t of a convex boy K is the intersection of all halfspaces whose efining hyperplanes cut off a set of volume t from K. The illumination boy K t of a convex boy K is [W] {x R vol ([x, K] \ K t }. K t is a convex boy. It is enough to show this for polytopes. Let F i enote the faces of a polytope P, ξ i the outer normal an x i an element of F i. Then vol ([x, P ] \ P = n max{0, ξ i, x x i } vol (F i. i= The right-han sie is a convex function. 2. The Floating Boy Theorem 2.. Let K be a convex boy in R. Then, for every t satisfying 0 t 4 e 5 vol (K, there exist n N with n e 6 vol (K \ K t t vol (B an a polytope P n that has n vertices an such that K t P n K.

3 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 205 We want to see what kin of asymptotic estimate we get for boies with smooth bounary from Theorem 2.. We have [SW] Since we get Thus we get vol (K \ K t t 2 ( + 2 t vol (B K n 2 ( vol (K \ K t 2 vol (K \ K t + 2 n 2 + κ(x + µ(x. t vol (K \ K t, n vol (K \ K t K 2 + K κ(x + µ(x 2 + K κ(x κ(x + µ(x. ( vol (K \ P n vol (K \ K t 2 n 2 When K is the Eucliean ball we get K vol (B 2 \ P n c 2 n 2 vol (B 2, + µ(x, κ(x + µ(x +. where c is an absolute constant. If one compares this to the optimal result (. one sees that there is an aitional factor. The volume ifference vol (P vol (P t for a polytope P is of a much smaller orer than for a convex boy with smooth bounary. In fact, we have [S] that it is of the orer t ln t. In [S] this has been use to get estimates for approximation of convex boies by polytopes. The same result as in Theorem 2. hols if we fix the number of (-- imensional faces instea of the number of vertices. This follows from the same proof as for Theorem 2. an also from the economic cap covering for floating boies [BL, Theorem 6]. I. Bárány showe us a proof for Theorem 2. using the economic cap covering. The constants are not as goo as in Theorem 2.. The following lemmata are not new. They have usually been formulate for symmetric, convex boies [B,H,MP]. Lemma 2.2 is ue to Grünbaum [Grü]. Lemma 2.2. Let K be a convex boy in R an let H(cg(K, ξ be the hyperplane passing through the center of gravity cg(k of K an being orthogonal to ξ. Then we have, for all ξ B 2: (i ( + vol (K vol (K H + (cg(k, ξ ( ( + vol (K.

4 206 CARSTEN SCHÜTT (ii For all hyperplanes H in R that are parallel to H(cg(K, ξ, ( vol (K H vol (K H(cg(K, ξ. + The sequence ( +, = 2, 3,... is monotonely ecreasing. Inee, by Bernoulli s inequality we have (, or 2 ( 2. Therefore 2 we get ( + (, which implies ( + (. Therefore we get for the inequalities (i e vol (K vol (K H + (cg(k, ξ ( e vol (K. (2. By the preceing calculations, ( + is a monotonely increasing sequence. Thus ( + < e. For (ii we get vol (K H e vol (K H(cg(K, ξ. (2.2 Proof. (i We can reuce the inequality to the case that K is a cone with a Eucliean ball of imension as base. To see this we perform a Schwarz symmetrization parallel to H(cg(K, ξ an enote the symmetrize boy by S(K. The Schwarz symmetrization replaces a section parallel to H(cg(K, ξ by a ( -imensional Eucliean sphere of the same ( -imensional volume. This oes not change the volume of K an K H + (cg(k, ξ an the center of gravity cg(k is still an element of H(cg(K, ξ. Now we consier the cone such that [z, S(K H(cg(K, ξ] vol ([z, S(K H(cg(K, ξ] = vol (K H (cg(k, ξ an such that z lies on the axis of symmetry of S(K an in H (cg(k, ξ. See Figure. The set K = (K H + (cg(k, ξ [z, S(K H(cg(K, ξ] is a convex set such that vol (K = vol ( K an such that the center of gravity cg( K of K is containe in [z, S(K H(cg(K, ξ]. Thus vol ( K H + (cg( K, ξ vol ( K H + (cg(k, ξ = vol (K H + (cg(k, ξ. We apply a similar argument to the set S(K H + (cg(k, ξ an show that we may assume that S(K is a cone with z as its vertex. Thus we may assume that K = [ (0,..., 0,, { (x,..., x, 0 i= x i 2 }] an ξ = (0,..., 0,. Then vol (K = vol (B

5 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 207 H(cg(K, ξ z S(K an x x = vol (K K We obtain 0 Figure. t( t t = vol (K H (cg(k, (0,..., 0, = 0 ( ss s = +. ( vol (K. + (ii Let H be a hyperplane parallel to H(cg(K, ξ an such that vol (K H > vol (K H(cg(K, ξ. Otherwise there is nothing to prove. We apply a Schwarz symmetrization parallel to H(cg(K, ξ to K. The symmetrize boy is enote by S(K. Let z be the element of the axis of symmetry of S(K such that [z, S(K H] H(cg(K, ξ = S(K H(cg(K, ξ. Since vol (K H > vol (K H(cg(K, ξ there is such a z. assume that H + (cg(k, ξ is the half-space containing z. Then We may [z, S(K H] H (cg(k, ξ S(K H (cg(k, ξ, [z, S(K H] H + (cg(k, ξ S(K H + (cg(k, ξ. Therefore cg([z, S(K H] H + (cg(k, ξ.

6 208 CARSTEN SCHÜTT Therefore, if h cg enotes the istance of z to H(cg(K, ξ an h the istance of z to H, we get as in the proof of (i that ( h cg h. + Thus we get vol (K H(cg(K, ξ = vol (S(K H(cg(K, ξ ( + vol (S(K H = ( + vol (K H. Lemma 2.3. Let K be a convex boy in R an let Θ(ξ be the infimum of all positive numbers t such that Then vol (K H(cg(K, ξ e vol (K H(cg(K + tξ, ξ. 2e 3 vol (K Θ(ξ vol (K H(cg(K, ξ e vol (K. Proof. The right han inequality follows from Fubini s theorem an Brunn Minkowski s theorem. Now we verify the left han inequality. We consier first the case in which, for all t such that t > Θ(ξ, Then, by (2. an (2.2, K H(cg(K + tξ, ξ =. e vol (K vol (K H + (cg(k, ξ = Θ(ξ 0 vol (K H(cg(K + tξ, ξ t e Θ(ξ vol (K H(cg(K, ξ. If, for some t such that t > Θ(ξ, we have K H(cg(K + tξ, ξ, then, by continuity, vol (K H(cg(K, ξ = e vol (K H(cg(K + Θ(ξξ, ξ. We perform a Schwarz symmetrization parallel to H(cg(K, ξ. We consier the cone [z, S(K H(cg(K, ξ] such that z is an element of the axis of symmetry of S(K an such that [z, S(K H(cg(K, ξ] H(cg(K + Θ(ξξ, ξ = S(K H(cg(K + Θ(ξξ, ξ.

7 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 209 H(cg(K, ξ z S(K H(cg(K + Θ(ξξ, ξ Figure 2. Let H + (cg(k, ξ an H + (cg(k+θ(ξξ, ξ be the half-spaces that contain z. Then, by convexity, [z, S(K H(cg(K, ξ] H + (cg(k + Θ(ξξ, ξ We get by (2. e vol (K vol (K H + (cg(k, ξ S(K H + (cg(k + Θ(ξξ, ξ. (2.3 = vol (K H + (cg(k, ξ H (cg(k + Θ(ξξ, ξ + vol (K H + (cg(k + Θ(ξξ, ξ = vol (S(K H + (cg(k, ξ H (cg(k + Θ(ξξ, ξ + vol (S(K H + (cg(k + Θ(ξξ, ξ. By the hypothesis of the lemma we have, for all s with 0 s Θ(ξ, vol (K H(cg(K, ξ e vol (K H(cg(K + sξ, ξ. Using this an (2.2 we estimate the first summan. The secon summan is estimate by using (2.3. Thus the above expression is not greater than e 2 vol ([z, S(K H(cg(K, ξ] H (cg(k + Θ(ξξ, ξ + vol ([z, S(K H(cg(K, ξ] H + (cg(k + Θ(ξξ, ξ.

8 20 CARSTEN SCHÜTT This is the volume of a cone with the base S(K H(cg(K, ξ. By an elementary computation for the volume of a cone we get that the latter expression is smaller than 2e 2 vol ([z, S(K H(cg(K, ξ] H (cg(k + Θ(ξξ, ξ. Since in a cone the base has the greatest surface area, the above expression is smaller than 2e 2 Θ(ξ vol (K H(cg(K, ξ. Lemma 2.4. Let K be a convex boy in R. Then there is a linear transform T with et(t = so that, for all ξ B 2, T (K x, ξ 2 x = T (K i= x, e i 2 x. We say that a convex boy is in an isotropic position if the linear transform T in Lemma 2.4 can be chosen to be the ientity. See [B,H]. Proof. We claim that there is a orthogonal transform U such that, for all i, j =,..., with i j, x, e i x, e j x = 0. Clearly, the matrix U(K ( x, e i x, e j x K i,j= is symmetric. Therefore there is an orthogonal -matrix U so that ( U x, e i x, e j x U t K is a iagonal matrix. We have ( U x, e i x, e j x K i,j= U t = = = ( ( ( K i,j= i,j= u l,i x, e i x, e j u k,j x x, U t (e l x, U t (e k x K y, e l y, e k y U(K l,k= l,k= l,k= So the latter matrix is a iagonal matrix. All the iagonal elements are strictly positive. This argument is repeate with a iagonal matrix so that the iagonal.

9 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 2 elements turn out to be equal. Therefore there is a matrix T with et T = such that 0 if i j, x, e i x, e j x = T (K x, e j 2 x if i = j. T (K j= From this the lemma follows. Lemma 2.5. Let K be a convex boy in R that is in an isotropic position an whose center of gravity is at the origin. Then, for all ξ B 2, 24e 0 vol (K 3 vol (K H(cg(K, ξ 2 K 6 e 3 vol (K 3. Proof. By Lemma 2.4 we have, for all ξ B 2, K x, e i 2 x = i= By Fubini s theorem, this equals K x, ξ 2 x. x, e i 2 x i= t 2 vol (K H(tξ, ξ t Θ(ξ t 2 0 vol (K H(tξ, ξ t, where Θ(ξ is as efine in Lemma 2.3. expression is greater than By the efinition of Θ(ξ the above e vol (K H(cg(K, ξ Θ(ξ By Lemma 2.3 this is greater than 0 t 2 t 3e Θ(ξ3 vol (K H(cg(K, ξ. vol (K 3 24e 0 vol (K H(cg(K, ξ 2. Now we show the right han inequality. By Lemma 2.4 we have K x, e i 2 x = i= Θ(ξ = Θ( ξ K x, ξ 2 x = t 2 vol (K H(tξ, ξ t + t 2 vol (K H(tξ, ξ t + t 2 t 2 Θ(ξ Θ( ξ t 2 vol (K H(tξ, ξ t vol (K H(tξ, ξ t vol (K H(tξ, ξ t.

10 22 CARSTEN SCHÜTT By (2.2 this is not greater than e 3 Θ(ξ3 vol (K H(cg(K, ξ + t 2 Θ(ξ + e 3 Θ( ξ3 vol (K H(cg(K, ξ + The integrals can be estimate by vol (K H(tξ, ξ t Θ( ξ t 2 vol (K H(tξ, ξ t. 2 Θ(ξ 3 vol (K H(cg(K, ξ an 2 Θ( ξ 3 vol (K H(cg(K, ξ, respectively. We treat here only the case ξ; the case ξ is treate in the same way. If the integral equals 0, there is nothing to show. If the integral oes not equal 0, we have vol (K H(cg(K, ξ = e vol (K H(cg(K + Θ(ξξ, ξ. We consier the Schwarz symmetrization S(K of K with respect to the plane H(cg(K, ξ. We consier the cone C that is generate by the Eucliean spheres S(K H(cg(K, ξ an S(K H(cg(K + Θ(ξξ, ξ. We an the height of C equals S(K H + (cg(k + Θ(ξξ, ξ C Θ(ξ e Since ( + < e, we have e >. Thus the height of the cone C is less than Θ(ξ. Thus, for all t with Θ(ξ t Θ(ξ, ( vol (K H(cg(K + tξ, ξ t vol (K H(cg(K, ξ. Θ(ξ Now we get Θ(ξ t 2 vol (K H(tξ, ξ t Therefore x, e i 2 x K i= Θ(ξ Θ(ξ t 2 (. t Θ(ξ vol (K H(cg(K, ξ t vol (K H(cg(K, ξ( Θ(ξ 3 s 2 ( s s = vol (K H(cg(K, ξ( Θ(ξ 3 2 ( + ( vol (K H(cg(K, ξθ(ξ 3. ( e 3 + (Θ(ξ 3 + Θ( ξ 3 vol (K H(cg(K, ξ. 0

11 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 23 Now we apply Lemma 2.3 an get 2( e 3 + 2e3 vol (K 3 vol (K H(cg(K, ξ 2. Lemma 2.6. Let K be a convex boy in R such that the origin is an element of K. Then K x, e i 2 x vol ( B2 2 vol (K +2. i= Proof. Let r(ξ be the istance of the origin to the bounary of K in irection ξ. By passing to spherical coorinates we get K x, e i 2 x = i= B 2 r(ξ 0 ρ + ρ ξ = By Höler s inequality, this expression is greater than ( vol ( B2 +2 ( + 2 vol ( B2 r(ξ ξ B 2 r(ξ +2 ξ ( + 2 B2 = vol ( B 2 2 vol (K +2. The following lemma can be foun in [MP]. It is formulate there for the case of symmetric convex boies. Lemma 2.7. Let K be a convex boy in R such that the origin coincies with the center of gravity of K an such that K is in an isotropic position. Then B 2(cg(K, 24e 5 π vol (K K 4e 4 vol (K. An affine transform can put a convex boy into this position. Proof. As in Lemma 2.3, let Θ(ξ be the infimum of all numbers t such that vol (K H(cg(K, ξ e vol (K H(cg(K + tξ, ξ. By Lemma 2.3, Θ(ξ vol (K 2e 3 vol (K H(cg(K, ξ. By Lemma 2.5 we get ( Θ(ξ 2e 3 x, e 6e 3 i 2 x 2 vol (K We have π 2 K i= vol (B2 = Γ( 2 + π( /2 (2e 2 + 2, 2.

12 24 CARSTEN SCHÜTT an thus Therefore, by Lemma 2.6, Θ(ξ 2e 3 6e 3 2 On the other han, ( + 2 vol (B 2 2πe. vol (K vol ( B2 vol (K H (cg(k + 2 Θ(ξξ, ξ Θ(ξ 2e 5 π vol (K. vol (K H(cg(K + tξ, ξ t, 2 Θ(ξ where H (cg(k+ 2Θ(ξξ, ξ is the half-space not containing the origin. By the efinition of Θ(ξ this expression is greater than Θ(ξ 2e vol (K H(cg(K, ξ. By Lemma 2.3 we get that this is greater than 4e 4 vol (K. Therefore, every hyperplane that has istance 24e 5 π vol (K from the center of gravity cuts off a set of volume greater than 4e 4 vol (K. Proof of Theorem 2.. We are choosing the vertices x,..., x n K of the polytope P n. N(x k enotes the normal to K at x k. x is chosen arbitrarily. Having chosen x,..., x k we choose x k such that {x,..., x k } Int(K H (x k k N(x k, N(x k =, where k is etermine by vol (K H (x k k N(x k, N(x k = t. If the normal at x k is not unique it suffices that just one of the normals satisfies the conition. It coul be that the hyperplane H(x k k N(x k, N(x k is not tangential to the floating boy K t, but this oes not affect the computation. We claim that this process terminates for some n with n e 6 vol (K \ K t t vol (B. (2.4 This claim proves the theorem: If we cannot choose another x n+, then there is no cap of volume t that oes not contain an element of the polytope P n = [x,..., x n ]. By the theorem of Hahn Banach we get K t P n. We show now

13 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 25 x k H(x k k N(x k, N(x k K t K Figure 3. the claim. We assume that we manage to choose points x,..., x n where n is to big that (2.4 oes not hol. We put an S k = K ( n i=k+ S n = K H (x n n N(x n, N(x n (2.5 H + (x i N(x i, N(x i for k =,..., n. For k l, we have Let k < l < n. Then ( n S k S l = K K i=k+ ( n vol (S k S l = 0. H + (x i N(x i, N(x i i=l+ H + (x i N(x i, N(x i H + (x l l N(x l, N(x l H (x l l N(x l, N(x l = H(x l l N(x l, N(x l. Thus we have H (x k k N(x k, N(x k H (x k k N(x k, N(x k H (x l l N(x l, N(x l vol (S k S l vol (H(x l l N(x l, N(x l = 0. (2.6

14 26 CARSTEN SCHÜTT The case k < l = n is shown in the same way. We have, for k =,..., n, ( n S k = K H + (x i N(x i, N(x i H (x k k N(x k, N(x k i=k+ [x k, K t ] H (x k k N(x k, N(x k [x k, (K H (x k k N(x k, N(x k t ] H (x k k N(x k, N(x k, where k is etermine by vol (K H (x k k N(x k, N(x k = 4e 4 t. By Lemma 2.7 there is an ellipsoi E containe in (K H (x k k N(x k, N(x k t whose center is cg(k H (x k k N(x k, N(x k an that has volume vol (E = 4e 4 (24e 5 π t vol (B 2 Since (K H (x k k N(x k, N(x k t is containe in K t, E is containe in K t. Thus S k [x k, E] H (x k k N(x k, N(x k. We claim now that [x k, E] H (x k k N(x k, N(x k contains an ellipsoi Ẽ such that vol (Ẽ = 4e 4 (24e 5 π (4e 5 t vol (B2, an consequently vol (S k 4e 4 (24e 5 π (4e 5 t vol (B2 4e 4 = (96e 0 π t vol (B2. (2.7 For this we have to see that k 4e 5 k. By the assumption t 4 e 5 vol (K we get vol (K H (x k k N(x k, N(x k e vol (K. Therefore, by (2., cg(k H + (x k k N(x k, N(x k. We consier two cases. If vol (K H(x k k N(x k, N(x k vol (K H(x k k N(x k, N(x k, the theorem of Brunn Minkowski implies that, for all s in the range k s k, we have vol (K H(cg(K, N(x k vol (K H(x k k N(x k, N(x k vol (K H(x k sn(x k, N(x k. (2.8

15 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 27 We get, by (2.2, By (2.8, k ( k k vol (K H(cg(K, N(x k t e vol (K H(cg(K, N(x k. vol (K H (x k k N(x k, N(x k vol (K H (x k k N(x k, N(x k. This implies Therefore k k k (4e 4 t vol (K H(cg(K, N(x k. (4e 4 t vol (K H(cg(K, N(x k + k 4e 5 k. If vol (K H(x k k N(x k, N(x k vol (K H(x k k N(x k, N(x k, the theorem of Brunn Minkowski implies that, for all u in the range 0 u k, an all s in the range k s k, we have vol (K H(x k un(x k, N(x k vol (K H(x k k N(x k, N(x k We get an Therefore k k k k vol (K H(x k sn(x k, N(x k. t vol (K H(x k k N(x k, N(x k (4e 4 t vol (K H(x k k N(x k, N(x k. (4e 4 t vol (K H(x k k N(x k, N(x k + k 4e 4 k. We have verifie (2.7. From (2.6 an (2.7 we get vol (K \ K t vol ( n S k = k= n 4e 4 vol (S k n (96e 0 π t vol (B2. k= Thus we get the esire equation (2.4: vol (K \ K t e 6 n t vol (B 2.

16 28 CARSTEN SCHÜTT 3. The Illumination Boy Theorem 3.. Let K be a convex boy in R such that c B 2 K c 2 B 2. Let 0 t (5c c vol (K an let n N be such that ( 28 7 π( /2 n 32 et vol (K t \ K. Then we have, for every polytope P n that contains K an has at most n ( - imensional faces, vol (K t \ K (c c 2+ vol (P n \ K. We want to see what this result means for boies with a smooth bounary. We have the asymptotic formula [W] Thus lim t 0 vol (K t vol (K = 2 t 2 + An by the theorem we have vol (K t vol (K t 2 + ( 2 ( + + vol (B2 κ(x + µ(x. K K κ(x + µ(x. Thus or n t vol (K t \ K. ( 2 vol (K t vol (K n vol (K t + \ K κ(x + µ(x, K ( vol (K t \ K + n ( 2 vol (K t \ K n By Theorem 3. we now get vol (P n \ K ( c c ( n 2 + ( K K 2 ( By a theorem of F. John [J] we have c c 2. κ(x + µ(x, κ(x + µ(x +. K κ(x + µ(x +.

17 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 29 The following lemma is ue to Bronshtein an Ivanov [BI] an Duley [D, D 2 ]. It can also be foun in [GRS]. Lemma 3.2. For all imensions, 2, an all natural numbers n, n 2, there is a polytope Q n that has n vertices an is containe in the Eucliean ball B2 such that H (Q n, B2 6 ( vol ( B2 2 7 vol (B2 n 2. We have π 2 vol ( B2 = vol (B2 = Γ( 2 + Since 2 = Γ( 2 + π Γ( 2 + vol (B2 π vol (B2. (3. 4 an ( t t, (3. yiels H (B2, Q n 6 ( π 7 n π n 2. (3.2 Proof of Theorem 3.. We enote the ( -imensional faces of P n by F i, for i =,..., n, an the cones generate by the origin an a face F i by C i, for i =,..., n. Take x i F i an let ξ i, with ξ i 2 =, be orthogonal to F i an pointing to the outsie of P n. Then H(x i, ξ i is the hyperplane containing F i an H + (x i, ξ i the halfspace containing P n. See Figure 4. We may assume that the hyperplanes H(x i, ξ i, i =,..., n, are supporting hyperplanes of K. Otherwise we can choose a polytope of lesser volume. Let be the height of the set K t H (x i, ξ i C i, that is, the smallest number s such that K t H (x i, ξ i C i H + (x i + sξ i, ξ i. Let z i be a point in K t C i where the height is attaine. We may assume that B 2 K cb 2 where c = c c 2. Also we may assume that P n 2cB 2 (3.3 if we allow twice as many faces. This follows from (3.2: There is a polytope Q k such that 2 B 2 Q k B2 an the number of vertices k is smaller than ( 28 7 π( /2. Thus Q k satisfies B 2 Q k 2B 2 an has at most ( 28 7 π( /2 ( -imensional faces. As the new polytope P n we choose the intersection of cq k with the original polytope P n. Since we have by assumption that n is greater than ( 28 7 π( /2 the new polytope has at most 6 et vol (K t \ K. (3.4

18 220 CARSTEN SCHÜTT z i H(x i, ξ i K t P n K C i 0 Figure 4. ( -imensional faces. We show first that for t with 0 t (5c vol (K an all i, i =,..., n we have (3.5 Assume that there is a face F i with >. Consier the smallest infinite cone D i having z i as vertex an containing K. Since H(x i, ξ i is a supporting hyperplane to K an K c B2 we have K D i H + (x i, ξ i H (x i 2cξ i, ξ i an D i H (x i, ξ = [z i, K] H (x i, ξ We have t = vol ([z i, K] \ K vol ([z i, K] H (x i, ξ i = vol (D i H (x i, ξ i = Thus vol (D i H(x i, ξ i 2 vol (D i H(x i, ξ i vol (D i H(x i, ξ i 2 t (3.6

19 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 22 Since (3.5 oes not hol we have vol (D i H(x i 2cξ i, ξ i = ( 2c + vol (D i H(x i, ξ i By (3.6 we get Thus (2c + vol (D i H(x i, ξ i. vol (D i H(x i 2cξ i, ξ i (2c + 2 t (3c 2 t. an we conclue that vol (K vol (D i H + (x i, ξ i H (x i 2cξ i, ξ i 2c(3c 2 t (3c + t, t (3c vol (K. This is a contraiction to the assumption on t in the hypothesis of the theorem. Thus we have shown (3.5. We consier now two cases: All those heights that are smaller than 2t/vol (F i an those that are greater. We may assume that, i =,..., k are smaller than 2t/vol (F i an, i = k +,..., n are strictly greater. We have vol ((K t \ P n C i = Since B 2 K P n we get vol ((K t \ P n C i By (3.5 we get For i =,..., k we get Thus i 0 i 0 vol ((K t \ P n C i H(x i + sξ i, ξ i s. vol (F i ( + s s ( + vol (F i. vol ((K t \ P n C i ( + vol (F i. vol ((K t \ P n C i By (3.4 we get vol ((K t \ P n vol ((K t \ P n ( 2t + vol vol (F i (F i 2et. k C i 2ket 2net. i= k C i 8 vol (K t \ K. (3.7 Now we consier the other faces. For i = k +,..., n, we have i= 2t vol (F i. (3.8

20 222 CARSTEN SCHÜTT We show that, for i = k +,..., n, we have 5c ( 5c vol (F i 2 vol (K. (3.9 Suppose that there is a face F i so that (3.9 oes not hol. Then t = vol ([z i, K] \ K vol ([z i, K] H (x i, ξ i = vol ([z i, K] H(x i, ξ i. Therefore we get, by (3.8, Since K B 2 we have Thus vol ([z i, K] H(x i, ξ i t 2 vol (F i. (3.0 K D i H + (x i, ξ i H (x i 2cξ i, ξ i. vol (K vol (D i H (x i 2cξ i, ξ i. The cone D i H (x i 2cξ i, ξ i has a height equal to 2c +. Therefore vol (K ( 2c + (2c + i i vol (D i H(x i, ξ i. By (3.5 we have. Therefore we get vol (K 3c ( 3c vol (D i H(x i, ξ i = 3c ( 3c vol ([z i, K] H(x i, ξ i. By (3.0 we get vol (K 3c ( 3c vol (F i, 2 which implies (3.9. Let y i be the unique point y i = [0, z i ] H(x i, ξ i. We want to make sure that y i F i [z i, K]. This hols since z i C i H (x i, ξ i an > 0. Since y i F i we have vol (F i = vol (B2 vol 2 ( B2 r i (η µ(η, B 2 where r i (η is the istance of y i to the bounary F i in irection η, η B2, an, since y i F i [z i, K], we have vol (F i [z i, K] = vol (B vol 2 ( B B 2 ρ i (η µ(η,

21 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 223 where ρ i (η is the istance of y i to the bounary (F i [z i, K]. Consier the set A i = {η ( 4 r i(η ρ i (η }. We show that 4 vol (F i vol (B2 vol 2 ( B r i (η ρ i (η µ(η (3. We have vol (B vol 2 ( B Therefore vol (B vol 2 ( B A c i A i r i (η ρ i (η µ(η A c i vol (B vol 2 ( B 4 vol (B vol 2 ( B r i (η ρ i (η µ(η r i (η ( ( 4 µ(η A i A i r i (η µ(η 4 vol (F i. vol (B2 vol 2 ( B2 r i (η ρ i (η µ(η B 2 vol (B2 vol 2 ( B2 r i (η ρ i (η µ(η A i vol (F i vol (F i [z i, K] 4 vol (F i. By (3.0 this is greater than 4 vol (F i. This implies 4 vol (F i vol (B2 vol 2 ( B r i (η ρ i (η µ(η. Thus we have establishe (3.. We shall show that We have A c i vol ((K t \ P n C i 0 6 e 2 c 2+ vol ((P n \ K C i. (3.2 vol (D c i H + (x i, ξ i C i vol ((P n \ K C i. Compare Figure 5. Therefore, if we want to verify (3.2 it is enough to show that vol ((K t \ P n C i 0 6 e 2 c 2+ vol (D c i H + (x i, ξ i C i. We may assume that y i an z i are orthogonal to H(x i, ξ i. This is accomplishe by a linear, volume preserving map: Any vector orthogonal to ξ i is mappe onto itself an y i is mappe to ξ i, y i ξ i. See Figure 6.

22 224 CARSTEN SCHÜTT z i α i F i y i y i + r i (ηη δ i β i 0 Figure 5. z i F i y i y i + ρ(ηη α i β i y i + r i (ηη δ i 0 Figure 6.

23 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 225 Let w i (η D c i H+ (x i, ξ i C i such that w i (η is an element of the 2- imensional subspace containing 0, y i, an y i + η. Let δ i (η be the istance of w i (η to the plane H(x i, ξ i. Then vol (B vol 2 ( B A c i (r i (η ρ i (η δ i (η µ(η Thus, in orer to verify (3.2, it suffices to show that vol ((K t \ P n C i 0 6 e 2 c 2+ vol (B vol 2 ( B A c i vol (D c i H + (x i, ξ i C i. (r i (η ρ i (η δ i (η µ(η. (3.3 In orer to o this we shall show that for all i = k +,..., n an all η A c i there is w i (η such that the istance δ i (η of w i from H(x i, ξ i satisfies { 32c if 0 αi π i 4, δ i if π 4 α i π 2. (3.4 ( 60 c 2 5c vol (F i r i 2 vol (K The angles α i (η an β i (η are given in Figure 6. We have for all η A c i δ i =(r i ρ i sin(α i sin(β i sin(π α i β i, =ρ i tan α i, (3.5 with 0 α i, β i π 2. Thus we get ρ i sin(π α i β i ρ i δ i r i ρ i cos(α i sin(β i (r i ρ i cos(α i sin(β i. By (3. we have ρ i ( 4 r i. Therefore δ i 4 cos(α i sin(β i. Since B2 K P n 2c B2 we have tan β i 4c : Here we have to take into account that we applie a transform to K mapping y i to ξ i, y i ξ i. That leaves the istance of F i to the origin unchange an r i (η is less than 4c. If β i π 4 we have sin β i 2. If β i π 4 then 4c tan β i = sin β i cos β i 2 sin β i. Therefore we get 6 2 c. δ i cos α i Therefore we get, for all 0 α i π 4, δ i 32c.

24 226 CARSTEN SCHÜTT By (3.9 an (3.5 we get δ i ( sin(π α i β i 5c r i ρ i sin(α i sin(β i 5c vol (F i. 2 vol (K We procee as in the estimate above an obtain 6 2 c 5c δ i sin(α i Thus we get for π 4 α i π 2 δ i r i ( 5c vol (F i 2 vol (K ( 32 c 5c vol (F i 5c. r i 2 vol (K. We verify now (3.3. By the efinition of A i we get vol (B2 vol 2 ( B2 (r i (η ρ i (η δ i (η µ(η A c i ( e vol (B 8 vol 2 ( B2 r i (η δ i µ(η. A c i We get by (3.4 that the last expression is greater than 320c vol (B2 i vol 2 ( B2 ( A c i α i π 4 By (3. we get that either or vol (B vol 2 ( B r i µ + ( 2 vol (K 5c 5c vol (F i Ac i α i > π 4 vol (B2 vol 2 ( B2 A c i α i π 4 A c i α i > π 4 r i µ 8 vol (F i r i µ 8 vol (F i. r i µ In the first case we get for the above estimate vol (B2 vol 2 ( B2 (r i (η ρ i (η δ i (η µ(η A c i 2560c vol (F i 2560ec vol ((K t \ P n C i. The last inequality is obtaine by using (3.5: Since B 2 K we have, for all hyperplanes H that are parallel to F i, vol (K t H C i ( + vol (F i..

25 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 227 By (3.5 we get vol (K t H C i e vol (F i. In the secon case we have vol (B2 vol 2 ( B2 A c i ( 2 vol (K 5c 5c vol (F i 5c (r i (η ρ i (η δ i (η µ(η ( 2 vol (K 5c vol (F i ( 2 vol (K 5c 5c vol (F i = ( vol (K 5c 20c vol (B2 ( vol (K 5c 20c vol (B2 Since B 2 K we get 320c 320c vol (B2 vol 2 ( B2 A c i α i > π 4 vol (B2 (vol 2 ( B2 ( r i µ A c i α i > π 4 r i µ 320c vol (B ( 8 vol (F i 2560c vol (F i 2560ec vol ((K t \ P n C i. vol (B2 vol 2 ( B2 (r i (η ρ i (η δ i (η µ(η A c i ( 5c 5c vol (B 2 20c vol (B 2560ec vol ((K t \ P n C i ( 20c 2560ec vol ((K t \ P n C i (0 6 ec 2+ vol ((K t \ P n C i. The secon case gives a weaker estimate. Therefore we get for both cases vol ((K t \ P n C i 0 6 ec 2+ vol (B vol 2 ( B2 (r i (η ρ i (η δ i µ(η. A c i Thus we have verifie (3.3 an thereby also (3.2. By (3.2 we get vol ((K t \P n n i=k+ (( n C i 0 6 e 2 c 2+ vol i=k+ C i (P n \K 0 6 e 2 c 2+ vol ((P n \K. (3.6

26 228 CARSTEN SCHÜTT If the assertion of the theorem oes not hol we have Thus we get vol ((P n \ K vol (K t \ K 0 7 e 2 c 2+ vol ((K t \ P n Together with (3.7 we obtain n i=k+ C i 0 vol (K t \ K.. (3.7 vol (K t \ P n 4 vol (K t \ K 4 {vol (K t \ P n + vol (P n \ K}. (3.8 By (3.7 we have This implies vol (P n \ K vol (K t \ K 0 7 e 2 c 2+ 2 vol (K t \ K 2 vol (K t \ P n + 2 vol (P n \ K. vol (P n \ K vol (K t \ P n. Together with (3.8 we get now the contraiction vol (K t \ P n 2 vol (K t \ P n. References [B] K. Ball, Logarithmically concave functions an sections of convex sets in R n, Stuia Math. 88 (988, [BL] I. Bárány an D. G. Larman, Convex boies, economic cap covering, ranom polytopes, Mathematika 35 (988, [BI] E. M. Bronshtein an L. D. Ivanov, The approximation of convex sets by polyhera, Siberian Math. J. 6 (975, 0 2. [D ] R. Duley, Metric entropy of some classes of sets with ifferentiable bounaries, J. of Approximation Theory 0 (974, [D 2] R. Duley, Correction to Metric entropy of some classes of sets with ifferentiable bounaries, J. of Approximation Theory 26 (979, [F T] L. Fejes Toth, Über zwei Maximumsaufgaben bei Polyeern, Tohoku Math. J. 46 (940, [GMR ] Y. Goron, M. Meyer, an S. Reisner, Volume approximation of convex boies by polytopes a constructive metho, Stuia Math. (994, [GMR 2 ] Y. Goron, M. Meyer an S. Reisner, Constructing a polytope to approximate a convex boy, Geometriae Deicata 57 (995, [GRS] Y. Goron, S. Reisner, an C. Schütt, Umbrellas an polytopal approximation of the Eucliean ball, J. of Approximation Theory 90 (997, [Gr ] P. M. Gruber, Volume approximation of convex boies by inscribe polytopes, Math. Annalen 28 (988,

27 FLOATING BODY, ILLUMINATION BODY, AND APPROXIMATION 229 [Gr 2] P. M. Gruber, Asymptotic estimates for best an stepwise approximation of convex boies II, Forum Mathematicum (993, [GK] P. M. Gruber an P. Kenerov, Approximation of convex boies by polytopes, Ren. Circolo Mat. Palermo 3 (982, [Grü] B. Grünbaum, Partitions of mass-istributions an of convex boies by hyperplanes, Pacific J. Math. 0 (960, [H] D. Hensley, Slicing convex boies-bouns for slice area in terms of the boy s covariance, Proc. Amer. Math. Soc. 79 (980, [J] F. John, Extremum problems with inequalities as subsiiary conitions, R. Courant Anniversary Volume, Interscience, New York, 948, [Mac] A. M. Macbeath, An extremal property of the hypersphere, Proc. Cambrige Phil. Soc. 47 (95, [MP] V. Milman an A. Pajor, Isotropic position an inertia ellipsois an zonois of the unit ball of a norme n-imensional space, Geometric Aspects of Functional Analysis (GAFA , eite by J. Linenstrauss an V. D. Milman, Springer, 989, [Mü] J. S. Müller, Approximation of the ball by ranom polytopes, J. Approximation Theory 63 (990, [R] C. A. Rogers, Packing an covering, Cambrige University Press, 964. [S] C. Schütt, The convex floating boy an polyheral approximation, Israel J. Math. 73 (99, [SW] C. Schütt an E. Werner, The convex floating boy, Math. Scaninavica 66 (990, [W] E. Werner, Illumination boies an the affine surface area, Stuia Math. 0 (994, Carsten Schütt Mathematisches Seminar Christian Albrechts Universität D Kiel Germany CarstenSchuett@compuserve.com

arxiv: v1 [math.mg] 10 Apr 2018

arxiv: v1 [math.mg] 10 Apr 2018 ON THE VOLUME BOUND IN THE DVORETZKY ROGERS LEMMA FERENC FODOR, MÁRTON NASZÓDI, AND TAMÁS ZARNÓCZ arxiv:1804.03444v1 [math.mg] 10 Apr 2018 Abstract. The classical Dvoretzky Rogers lemma provies a eterministic

More information

Acute sets in Euclidean spaces

Acute sets in Euclidean spaces Acute sets in Eucliean spaces Viktor Harangi April, 011 Abstract A finite set H in R is calle an acute set if any angle etermine by three points of H is acute. We examine the maximal carinality α() of

More information

LECTURE NOTES ON DVORETZKY S THEOREM

LECTURE NOTES ON DVORETZKY S THEOREM LECTURE NOTES ON DVORETZKY S THEOREM STEVEN HEILMAN Abstract. We present the first half of the paper [S]. In particular, the results below, unless otherwise state, shoul be attribute to G. Schechtman.

More information

Lower bounds on Locality Sensitive Hashing

Lower bounds on Locality Sensitive Hashing Lower bouns on Locality Sensitive Hashing Rajeev Motwani Assaf Naor Rina Panigrahy Abstract Given a metric space (X, X ), c 1, r > 0, an p, q [0, 1], a istribution over mappings H : X N is calle a (r,

More information

INRADII OF SIMPLICES

INRADII OF SIMPLICES INRADII OF SIMPLICES ULRICH BETKE, MARTIN HENK, AND LYDIA TSINTSIFA Abstract. We stuy the following generalization of the inraius: For a convex boy K in the -imensional Eucliean space an a linear k-plane

More information

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

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

More information

Tractability results for weighted Banach spaces of smooth functions

Tractability results for weighted Banach spaces of smooth functions Tractability results for weighte Banach spaces of smooth functions Markus Weimar Mathematisches Institut, Universität Jena Ernst-Abbe-Platz 2, 07740 Jena, Germany email: markus.weimar@uni-jena.e March

More information

UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics

UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics UC Berkeley Department of Electrical Engineering an Computer Science Department of Statistics EECS 8B / STAT 4B Avance Topics in Statistical Learning Theory Solutions 3 Spring 9 Solution 3. For parti,

More information

A Weak First Digit Law for a Class of Sequences

A Weak First Digit Law for a Class of Sequences International Mathematical Forum, Vol. 11, 2016, no. 15, 67-702 HIKARI Lt, www.m-hikari.com http://x.oi.org/10.1288/imf.2016.6562 A Weak First Digit Law for a Class of Sequences M. A. Nyblom School of

More information

PDE Notes, Lecture #11

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

More information

On John type ellipsoids

On John type ellipsoids On John type ellipsoids B. Klartag Tel Aviv University Abstract Given an arbitrary convex symmetric body K R n, we construct a natural and non-trivial continuous map u K which associates ellipsoids to

More information

SOME RESULTS ON THE GEOMETRY OF MINKOWSKI PLANE. Bing Ye Wu

SOME RESULTS ON THE GEOMETRY OF MINKOWSKI PLANE. Bing Ye Wu ARCHIVUM MATHEMATICUM (BRNO Tomus 46 (21, 177 184 SOME RESULTS ON THE GEOMETRY OF MINKOWSKI PLANE Bing Ye Wu Abstract. In this paper we stuy the geometry of Minkowski plane an obtain some results. We focus

More information

Math 342 Partial Differential Equations «Viktor Grigoryan

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

More information

Agmon Kolmogorov Inequalities on l 2 (Z d )

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

More information

A stability result for mean width of L p -centroid bodies.

A stability result for mean width of L p -centroid bodies. A stability result for mean with of L p -centroi boies. B. Fleury, O. Guéon an G. Paouris Abstract We give a ifferent proof of a recent result of lartag [1] concerning the concentration of the volume of

More information

An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback

An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback Journal of Machine Learning Research 8 07) - Submitte /6; Publishe 5/7 An Optimal Algorithm for Banit an Zero-Orer Convex Optimization with wo-point Feeback Oha Shamir Department of Computer Science an

More information

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

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

More information

Convex Geometry. Carsten Schütt

Convex Geometry. Carsten Schütt Convex Geometry Carsten Schütt November 25, 2006 2 Contents 0.1 Convex sets... 4 0.2 Separation.... 9 0.3 Extreme points..... 15 0.4 Blaschke selection principle... 18 0.5 Polytopes and polyhedra.... 23

More information

Qubit channels that achieve capacity with two states

Qubit channels that achieve capacity with two states Qubit channels that achieve capacity with two states Dominic W. Berry Department of Physics, The University of Queenslan, Brisbane, Queenslan 4072, Australia Receive 22 December 2004; publishe 22 March

More information

Least-Squares Regression on Sparse Spaces

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

More information

McMaster University. Advanced Optimization Laboratory. Title: The Central Path Visits all the Vertices of the Klee-Minty Cube.

McMaster University. Advanced Optimization Laboratory. Title: The Central Path Visits all the Vertices of the Klee-Minty Cube. McMaster University Avance Optimization Laboratory Title: The Central Path Visits all the Vertices of the Klee-Minty Cube Authors: Antoine Deza, Eissa Nematollahi, Reza Peyghami an Tamás Terlaky AvOl-Report

More information

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

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

More information

A new proof of the sharpness of the phase transition for Bernoulli percolation on Z d

A new proof of the sharpness of the phase transition for Bernoulli percolation on Z d A new proof of the sharpness of the phase transition for Bernoulli percolation on Z Hugo Duminil-Copin an Vincent Tassion October 8, 205 Abstract We provie a new proof of the sharpness of the phase transition

More information

Math 1271 Solutions for Fall 2005 Final Exam

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

More information

Problem set 2: Solutions Math 207B, Winter 2016

Problem set 2: Solutions Math 207B, Winter 2016 Problem set : Solutions Math 07B, Winter 016 1. A particle of mass m with position x(t) at time t has potential energy V ( x) an kinetic energy T = 1 m x t. The action of the particle over times t t 1

More information

Table of Common Derivatives By David Abraham

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

More information

Monotonicity of facet numbers of random convex hulls

Monotonicity of facet numbers of random convex hulls Monotonicity of facet numbers of ranom convex hulls Gilles Bonnet, Julian Grote, Daniel Temesvari, Christoph Thäle, Nicola Turchi an Florian Wespi arxiv:173.31v1 [math.mg] 7 Mar 17 Abstract Let X 1,...,

More information

Lecture 1b. Differential operators and orthogonal coordinates. Partial derivatives. Divergence and divergence theorem. Gradient. A y. + A y y dy. 1b.

Lecture 1b. Differential operators and orthogonal coordinates. Partial derivatives. Divergence and divergence theorem. Gradient. A y. + A y y dy. 1b. b. Partial erivatives Lecture b Differential operators an orthogonal coorinates Recall from our calculus courses that the erivative of a function can be efine as f ()=lim 0 or using the central ifference

More information

θ x = f ( x,t) could be written as

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

More information

15.1 Upper bound via Sudakov minorization

15.1 Upper bound via Sudakov minorization ECE598: Information-theoretic methos in high-imensional statistics Spring 206 Lecture 5: Suakov, Maurey, an uality of metric entropy Lecturer: Yihong Wu Scribe: Aolin Xu, Mar 7, 206 [E. Mar 24] In this

More information

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

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

More information

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. ω Q. Pr (y(ω x) < 0) = Pr A k

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. ω Q. Pr (y(ω x) < 0) = Pr A k A Proof of Lemma 2 B Proof of Lemma 3 Proof: Since the support of LL istributions is R, two such istributions are equivalent absolutely continuous with respect to each other an the ivergence is well-efine

More information

Large Cells in Poisson-Delaunay Tessellations

Large Cells in Poisson-Delaunay Tessellations Large Cells in Poisson-Delaunay Tessellations Daniel Hug an Rolf Schneier Mathematisches Institut, Albert-Luwigs-Universität, D-79104 Freiburg i. Br., Germany aniel.hug, rolf.schneier}@math.uni-freiburg.e

More information

1 dx. where is a large constant, i.e., 1, (7.6) and Px is of the order of unity. Indeed, if px is given by (7.5), the inequality (7.

1 dx. where is a large constant, i.e., 1, (7.6) and Px is of the order of unity. Indeed, if px is given by (7.5), the inequality (7. Lectures Nine an Ten The WKB Approximation The WKB metho is a powerful tool to obtain solutions for many physical problems It is generally applicable to problems of wave propagation in which the frequency

More information

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

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

More information

Multi-View Clustering via Canonical Correlation Analysis

Multi-View Clustering via Canonical Correlation Analysis Technical Report TTI-TR-2008-5 Multi-View Clustering via Canonical Correlation Analysis Kamalika Chauhuri UC San Diego Sham M. Kakae Toyota Technological Institute at Chicago ABSTRACT Clustering ata in

More information

Permanent vs. Determinant

Permanent vs. Determinant Permanent vs. Determinant Frank Ban Introuction A major problem in theoretical computer science is the Permanent vs. Determinant problem. It asks: given an n by n matrix of ineterminates A = (a i,j ) an

More information

STABILITY RESULTS INVOLVING SURFACE AREA MEASURES OF CONVEX BODIES DANIEL HUG AND ROLF SCHNEIDER

STABILITY RESULTS INVOLVING SURFACE AREA MEASURES OF CONVEX BODIES DANIEL HUG AND ROLF SCHNEIDER STABILITY RESULTS INVOLVING SURFACE AREA MEASURES OF CONVEX BODIES DANIEL HUG AND ROLF SCHNEIDER Abstract We strengthen some known stability results from the Brunn-Minkowski theory an obtain new results

More information

Physics 505 Electricity and Magnetism Fall 2003 Prof. G. Raithel. Problem Set 3. 2 (x x ) 2 + (y y ) 2 + (z + z ) 2

Physics 505 Electricity and Magnetism Fall 2003 Prof. G. Raithel. Problem Set 3. 2 (x x ) 2 + (y y ) 2 + (z + z ) 2 Physics 505 Electricity an Magnetism Fall 003 Prof. G. Raithel Problem Set 3 Problem.7 5 Points a): Green s function: Using cartesian coorinates x = (x, y, z), it is G(x, x ) = 1 (x x ) + (y y ) + (z z

More information

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

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

More information

MARTIN HENK AND MAKOTO TAGAMI

MARTIN HENK AND MAKOTO TAGAMI LOWER BOUNDS ON THE COEFFICIENTS OF EHRHART POLYNOMIALS MARTIN HENK AND MAKOTO TAGAMI Abstract. We present lower bouns for the coefficients of Ehrhart polynomials of convex lattice polytopes in terms of

More information

On the Orlicz-Brunn-Minkowski theory

On the Orlicz-Brunn-Minkowski theory On the Orlicz-Brunn-Minkowski theory C J Zhao 2 3 4 5 6 7 8 9 0 2 3 4 5 Abstract Recently, Garner, Hug an Weil evelope an Orlicz-Brunn- Minkowski theory Following this, in the paper we further consier

More information

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION

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

More information

Solutions to Math 41 Second Exam November 4, 2010

Solutions to Math 41 Second Exam November 4, 2010 Solutions to Math 41 Secon Exam November 4, 2010 1. (13 points) Differentiate, using the metho of your choice. (a) p(t) = ln(sec t + tan t) + log 2 (2 + t) (4 points) Using the rule for the erivative of

More information

Least Distortion of Fixed-Rate Vector Quantizers. High-Resolution Analysis of. Best Inertial Profile. Zador's Formula Z-1 Z-2

Least Distortion of Fixed-Rate Vector Quantizers. High-Resolution Analysis of. Best Inertial Profile. Zador's Formula Z-1 Z-2 High-Resolution Analysis of Least Distortion of Fixe-Rate Vector Quantizers Begin with Bennett's Integral D 1 M 2/k Fin best inertial profile Zaor's Formula m(x) λ 2/k (x) f X(x) x Fin best point ensity

More information

arxiv: v4 [cs.ds] 7 Mar 2014

arxiv: v4 [cs.ds] 7 Mar 2014 Analysis of Agglomerative Clustering Marcel R. Ackermann Johannes Blömer Daniel Kuntze Christian Sohler arxiv:101.697v [cs.ds] 7 Mar 01 Abstract The iameter k-clustering problem is the problem of partitioning

More information

Discrete Mathematics

Discrete Mathematics Discrete Mathematics 309 (009) 86 869 Contents lists available at ScienceDirect Discrete Mathematics journal homepage: wwwelseviercom/locate/isc Profile vectors in the lattice of subspaces Dániel Gerbner

More information

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

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

More information

Iterated Point-Line Configurations Grow Doubly-Exponentially

Iterated Point-Line Configurations Grow Doubly-Exponentially Iterate Point-Line Configurations Grow Doubly-Exponentially Joshua Cooper an Mark Walters July 9, 008 Abstract Begin with a set of four points in the real plane in general position. A to this collection

More information

Monotonicity for excited random walk in high dimensions

Monotonicity for excited random walk in high dimensions Monotonicity for excite ranom walk in high imensions Remco van er Hofsta Mark Holmes March, 2009 Abstract We prove that the rift θ, β) for excite ranom walk in imension is monotone in the excitement parameter

More information

Linear First-Order Equations

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

More information

Final Exam Study Guide and Practice Problems Solutions

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

More information

Generalized Tractability for Multivariate Problems

Generalized Tractability for Multivariate Problems Generalize Tractability for Multivariate Problems Part II: Linear Tensor Prouct Problems, Linear Information, an Unrestricte Tractability Michael Gnewuch Department of Computer Science, University of Kiel,

More information

A bi-lipschitz continuous, volume preserving map from the unit ball onto a cube

A bi-lipschitz continuous, volume preserving map from the unit ball onto a cube Note i Matematica Note Mat. 8, 77-93 ISSN 3-536, e-issn 59-93 DOI.85/i5993v8np77 Note http://siba.unile.it/notemat i Matematica 8, n., 8, 77 93. A bi-lipschitz continuous, volume preserving map from the

More information

SYSTEMS OF DIFFERENTIAL EQUATIONS, EULER S FORMULA. where L is some constant, usually called the Lipschitz constant. An example is

SYSTEMS OF DIFFERENTIAL EQUATIONS, EULER S FORMULA. where L is some constant, usually called the Lipschitz constant. An example is SYSTEMS OF DIFFERENTIAL EQUATIONS, EULER S FORMULA. Uniqueness for solutions of ifferential equations. We consier the system of ifferential equations given by x = v( x), () t with a given initial conition

More information

Lecture 5. Symmetric Shearer s Lemma

Lecture 5. Symmetric Shearer s Lemma Stanfor University Spring 208 Math 233: Non-constructive methos in combinatorics Instructor: Jan Vonrák Lecture ate: January 23, 208 Original scribe: Erik Bates Lecture 5 Symmetric Shearer s Lemma Here

More information

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

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

More information

On the enumeration of partitions with summands in arithmetic progression

On the enumeration of partitions with summands in arithmetic progression AUSTRALASIAN JOURNAL OF COMBINATORICS Volume 8 (003), Pages 149 159 On the enumeration of partitions with summans in arithmetic progression M. A. Nyblom C. Evans Department of Mathematics an Statistics

More information

arxiv: v1 [math.co] 15 Sep 2015

arxiv: v1 [math.co] 15 Sep 2015 Circular coloring of signe graphs Yingli Kang, Eckhar Steffen arxiv:1509.04488v1 [math.co] 15 Sep 015 Abstract Let k, ( k) be two positive integers. We generalize the well stuie notions of (k, )-colorings

More information

A Unified Theorem on SDP Rank Reduction

A Unified Theorem on SDP Rank Reduction A Unifie heorem on SDP Ran Reuction Anthony Man Cho So, Yinyu Ye, Jiawei Zhang November 9, 006 Abstract We consier the problem of fining a low ran approximate solution to a system of linear equations in

More information

WUCHEN LI AND STANLEY OSHER

WUCHEN LI AND STANLEY OSHER CONSTRAINED DYNAMICAL OPTIMAL TRANSPORT AND ITS LAGRANGIAN FORMULATION WUCHEN LI AND STANLEY OSHER Abstract. We propose ynamical optimal transport (OT) problems constraine in a parameterize probability

More information

Sharp Thresholds. Zachary Hamaker. March 15, 2010

Sharp Thresholds. Zachary Hamaker. March 15, 2010 Sharp Threshols Zachary Hamaker March 15, 2010 Abstract The Kolmogorov Zero-One law states that for tail events on infinite-imensional probability spaces, the probability must be either zero or one. Behavior

More information

Discrete Operators in Canonical Domains

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

More information

Lecture 2 Lagrangian formulation of classical mechanics Mechanics

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

More information

On the cells in a stationary Poisson hyperplane mosaic

On the cells in a stationary Poisson hyperplane mosaic On the cells in a stationary Poisson hyperplane mosaic Matthias Reitzner and Rolf Schneider Abstract Let X be the mosaic generated by a stationary Poisson hyperplane process X in R d. Under some mild conditions

More information

Lecture 10: October 30, 2017

Lecture 10: October 30, 2017 Information an Coing Theory Autumn 2017 Lecturer: Mahur Tulsiani Lecture 10: October 30, 2017 1 I-Projections an applications In this lecture, we will talk more about fining the istribution in a set Π

More information

A FURTHER REFINEMENT OF MORDELL S BOUND ON EXPONENTIAL SUMS

A FURTHER REFINEMENT OF MORDELL S BOUND ON EXPONENTIAL SUMS A FURTHER REFINEMENT OF MORDELL S BOUND ON EXPONENTIAL SUMS TODD COCHRANE, JEREMY COFFELT, AND CHRISTOPHER PINNER 1. Introuction For a prime p, integer Laurent polynomial (1.1) f(x) = a 1 x k 1 + + a r

More information

Some Examples. Uniform motion. Poisson processes on the real line

Some Examples. Uniform motion. Poisson processes on the real line Some Examples Our immeiate goal is to see some examples of Lévy processes, an/or infinitely-ivisible laws on. Uniform motion Choose an fix a nonranom an efine X := for all (1) Then, {X } is a [nonranom]

More information

On the Inclined Curves in Galilean 4-Space

On the Inclined Curves in Galilean 4-Space Applie Mathematical Sciences Vol. 7 2013 no. 44 2193-2199 HIKARI Lt www.m-hikari.com On the Incline Curves in Galilean 4-Space Dae Won Yoon Department of Mathematics Eucation an RINS Gyeongsang National

More information

Another Low-Technology Estimate in Convex Geometry

Another Low-Technology Estimate in Convex Geometry Convex Geometric Analysis MSRI Publications Volume 34, 1998 Another Low-Technology Estimate in Convex Geometry GREG KUPERBERG Abstract. We give a short argument that for some C > 0, every n- dimensional

More information

Calculus of Variations

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

More information

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments 2 Conference on Information Sciences an Systems, The Johns Hopkins University, March 2, 2 Time-of-Arrival Estimation in Non-Line-Of-Sight Environments Sinan Gezici, Hisashi Kobayashi an H. Vincent Poor

More information

MAT 545: Complex Geometry Fall 2008

MAT 545: Complex Geometry Fall 2008 MAT 545: Complex Geometry Fall 2008 Notes on Lefschetz Decomposition 1 Statement Let (M, J, ω) be a Kahler manifol. Since ω is a close 2-form, it inuces a well-efine homomorphism L: H k (M) H k+2 (M),

More information

Lower Bounds for k-distance Approximation

Lower Bounds for k-distance Approximation Lower Bouns for k-distance Approximation Quentin Mérigot March 21, 2013 Abstract Consier a set P of N ranom points on the unit sphere of imension 1, an the symmetrize set S = P ( P). The halving polyheron

More information

SHARP BOUNDS FOR EXPECTATIONS OF SPACINGS FROM DECREASING DENSITY AND FAILURE RATE FAMILIES

SHARP BOUNDS FOR EXPECTATIONS OF SPACINGS FROM DECREASING DENSITY AND FAILURE RATE FAMILIES APPLICATIONES MATHEMATICAE 3,4 (24), pp. 369 395 Katarzyna Danielak (Warszawa) Tomasz Rychlik (Toruń) SHARP BOUNDS FOR EXPECTATIONS OF SPACINGS FROM DECREASING DENSITY AND FAILURE RATE FAMILIES Abstract.

More information

THE DUCK AND THE DEVIL: CANARDS ON THE STAIRCASE

THE DUCK AND THE DEVIL: CANARDS ON THE STAIRCASE MOSCOW MATHEMATICAL JOURNAL Volume 1, Number 1, January March 2001, Pages 27 47 THE DUCK AND THE DEVIL: CANARDS ON THE STAIRCASE J. GUCKENHEIMER AND YU. ILYASHENKO Abstract. Slow-fast systems on the two-torus

More information

Unit vectors with non-negative inner products

Unit vectors with non-negative inner products Unit vectors with non-negative inner proucts Bos, A.; Seiel, J.J. Publishe: 01/01/1980 Document Version Publisher s PDF, also known as Version of Recor (inclues final page, issue an volume numbers) Please

More information

Combinatorica 9(1)(1989) A New Lower Bound for Snake-in-the-Box Codes. Jerzy Wojciechowski. AMS subject classification 1980: 05 C 35, 94 B 25

Combinatorica 9(1)(1989) A New Lower Bound for Snake-in-the-Box Codes. Jerzy Wojciechowski. AMS subject classification 1980: 05 C 35, 94 B 25 Combinatorica 9(1)(1989)91 99 A New Lower Boun for Snake-in-the-Box Coes Jerzy Wojciechowski Department of Pure Mathematics an Mathematical Statistics, University of Cambrige, 16 Mill Lane, Cambrige, CB2

More information

A note on asymptotic formulae for one-dimensional network flow problems Carlos F. Daganzo and Karen R. Smilowitz

A note on asymptotic formulae for one-dimensional network flow problems Carlos F. Daganzo and Karen R. Smilowitz A note on asymptotic formulae for one-imensional network flow problems Carlos F. Daganzo an Karen R. Smilowitz (to appear in Annals of Operations Research) Abstract This note evelops asymptotic formulae

More information

A Sketch of Menshikov s Theorem

A Sketch of Menshikov s Theorem A Sketch of Menshikov s Theorem Thomas Bao March 14, 2010 Abstract Let Λ be an infinite, locally finite oriente multi-graph with C Λ finite an strongly connecte, an let p

More information

Function Spaces. 1 Hilbert Spaces

Function Spaces. 1 Hilbert Spaces Function Spaces A function space is a set of functions F that has some structure. Often a nonparametric regression function or classifier is chosen to lie in some function space, where the assume structure

More information

arxiv: v1 [math.dg] 3 Jun 2016

arxiv: v1 [math.dg] 3 Jun 2016 FOUR-DIMENSIONAL EINSTEIN MANIFOLDS WITH SECTIONAL CURVATURE BOUNDED FROM ABOVE arxiv:606.057v [math.dg] Jun 206 ZHUHONG ZHANG Abstract. Given an Einstein structure with positive scalar curvature on a

More information

Separation of Variables

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

More information

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

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

More information

Lower Bounds for the Smoothed Number of Pareto optimal Solutions

Lower Bounds for the Smoothed Number of Pareto optimal Solutions Lower Bouns for the Smoothe Number of Pareto optimal Solutions Tobias Brunsch an Heiko Röglin Department of Computer Science, University of Bonn, Germany brunsch@cs.uni-bonn.e, heiko@roeglin.org Abstract.

More information

18-660: Numerical Methods for Engineering Design and Optimization

18-660: Numerical Methods for Engineering Design and Optimization 8-66: Nmerical Methos for Engineering Design an Optimization in Li Department of ECE Carnegie Mellon University Pittsbrgh, PA 53 Slie Overview Geometric Problems Maximm inscribe ellipsoi Minimm circmscribe

More information

12.11 Laplace s Equation in Cylindrical and

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

More information

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy,

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy, NOTES ON EULER-BOOLE SUMMATION JONATHAN M BORWEIN, NEIL J CALKIN, AND DANTE MANNA Abstract We stuy a connection between Euler-MacLaurin Summation an Boole Summation suggeste in an AMM note from 196, which

More information

arxiv: v2 [math.dg] 16 Dec 2014

arxiv: v2 [math.dg] 16 Dec 2014 A ONOTONICITY FORULA AND TYPE-II SINGULARITIES FOR THE EAN CURVATURE FLOW arxiv:1312.4775v2 [math.dg] 16 Dec 2014 YONGBING ZHANG Abstract. In this paper, we introuce a monotonicity formula for the mean

More information

The group of isometries of the French rail ways metric

The group of isometries of the French rail ways metric Stu. Univ. Babeş-Bolyai Math. 58(2013), No. 4, 445 450 The group of isometries of the French rail ways metric Vasile Bulgărean To the memory of Professor Mircea-Eugen Craioveanu (1942-2012) Abstract. In

More information

Approximation of convex bodies by polytopes. Viktor Vígh

Approximation of convex bodies by polytopes. Viktor Vígh Approximation of convex bodies by polytopes Outline of Ph.D. thesis Viktor Vígh Supervisor: Ferenc Fodor Doctoral School in Mathematics and Computer Science Bolyai Institute, University of Szeged 2010

More information

x = c of N if the limit of f (x) = L and the right-handed limit lim f ( x)

x = c of N if the limit of f (x) = L and the right-handed limit lim f ( x) Limit We say the limit of f () as approaches c equals L an write, lim L. One-Sie Limits (Left an Right-Hane Limits) Suppose a function f is efine near but not necessarily at We say that f has a left-hane

More information

arxiv: v2 [math.pr] 27 Nov 2018

arxiv: v2 [math.pr] 27 Nov 2018 Range an spee of rotor wals on trees arxiv:15.57v [math.pr] 7 Nov 1 Wilfrie Huss an Ecaterina Sava-Huss November, 1 Abstract We prove a law of large numbers for the range of rotor wals with ranom initial

More information

Hyperbolic Systems of Equations Posed on Erroneous Curved Domains

Hyperbolic Systems of Equations Posed on Erroneous Curved Domains Hyperbolic Systems of Equations Pose on Erroneous Curve Domains Jan Norström a, Samira Nikkar b a Department of Mathematics, Computational Mathematics, Linköping University, SE-58 83 Linköping, Sween (

More information

1. Aufgabenblatt zur Vorlesung Probability Theory

1. Aufgabenblatt zur Vorlesung Probability Theory 24.10.17 1. Aufgabenblatt zur Vorlesung By (Ω, A, P ) we always enote the unerlying probability space, unless state otherwise. 1. Let r > 0, an efine f(x) = 1 [0, [ (x) exp( r x), x R. a) Show that p f

More information

On the Aloha throughput-fairness tradeoff

On the Aloha throughput-fairness tradeoff On the Aloha throughput-fairness traeoff 1 Nan Xie, Member, IEEE, an Steven Weber, Senior Member, IEEE Abstract arxiv:1605.01557v1 [cs.it] 5 May 2016 A well-known inner boun of the stability region of

More information

3 The variational formulation of elliptic PDEs

3 The variational formulation of elliptic PDEs Chapter 3 The variational formulation of elliptic PDEs We now begin the theoretical stuy of elliptic partial ifferential equations an bounary value problems. We will focus on one approach, which is calle

More information

Lecture 6 : Dimensionality Reduction

Lecture 6 : Dimensionality Reduction CPS290: Algorithmic Founations of Data Science February 3, 207 Lecture 6 : Dimensionality Reuction Lecturer: Kamesh Munagala Scribe: Kamesh Munagala In this lecture, we will consier the roblem of maing

More information

Binary Discrimination Methods for High Dimensional Data with a. Geometric Representation

Binary Discrimination Methods for High Dimensional Data with a. Geometric Representation Binary Discrimination Methos for High Dimensional Data with a Geometric Representation Ay Bolivar-Cime, Luis Miguel Corova-Roriguez Universia Juárez Autónoma e Tabasco, División Acaémica e Ciencias Básicas

More information

SINGULAR PERTURBATION AND STATIONARY SOLUTIONS OF PARABOLIC EQUATIONS IN GAUSS-SOBOLEV SPACES

SINGULAR PERTURBATION AND STATIONARY SOLUTIONS OF PARABOLIC EQUATIONS IN GAUSS-SOBOLEV SPACES Communications on Stochastic Analysis Vol. 2, No. 2 (28) 289-36 Serials Publications www.serialspublications.com SINGULAR PERTURBATION AND STATIONARY SOLUTIONS OF PARABOLIC EQUATIONS IN GAUSS-SOBOLEV SPACES

More information