Gruber P. Convex and Discrete Geometry

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492 Geometry of Numbers Let Dni be the Dirichlet–Voronoĭ cell of xni in K with respect to the set {xn1,..., xnn}. Then Dni ⊆ ρn Bd + xni and the cells Dni form a tiling of the unit cube K . This yields the following rough estimate: n α d I (K,α,n) ≤ n α � d min{�x − xni� xni K α } dx � � �x − xni� α dx ≤ n α � d V (Dni)ρ α n = n α d ρ α n . Thus, = n α d i Dni (27) n α d I (K,α,n) ≤ (2d log d) α d V (B d ) α d . Since V (B d ) = π d 2 /Ɣ(1 + d 2 ), Stirling’s formula for the gamma function and the inequalities (26) and (27) yield the asymptotic formula for δα,d, as required. ⊓⊔ 33.3 Structure of Minimizing Configurations, and a Heuristic Principle While it is out of reach to give a precise description of the configurations Sn which minimize the expressions (24) and (25) for all n, information is available as n →∞. For d = 2 the minimizing configurations Sn are asymptotically regular hexagonal and for d ≥ 3, they are still distributed rather regularly over J. Without giving details, we roughly outline what is known. For precise information, see the author [439, 442, 443]. In addition, a conjecture of Gersho [371] on the distribution of Sn over J will be discussed. The Case d = 2 For a wide class of strictly increasing functions f :[0, +∞) →[0, +∞) a weak stability result of Gruber [439] says the following: For J in E 2 or on a Riemannian 2-manifold 〈M,ρM,ωM〉 and w = const the minimizing configurations Sn for the expressions in (24) for the Euclidean norm and for (25) are asymptotically regular hexagonal patterns in J as n →∞.Ifw is not constant then a result of this type still holds, but its formulation is slightly more complicated. A related weak stability result for the Euclidean norm for a wider class of functions f is due to Fejes Tóth [321]. The Case d ≥ 2 A rather precise description of the minimizing sets Sn is indicated by the following conjecture of Gersho [371] which we state without giving precise definitions. Conjecture 33.1. There is a convex polytope P with V (P) = 1 which tiles E d with congruent copies such that the following holds: Let J ⊆ E d be a Jordan measurable i
33 Optimum Quantization 493 set with V (J) >0 and let Sn ={sn1,...,snn} ⊆J, n = 1, 2,...,be minimizing configurations for I (J, 2, n). Then the corresponding Dirichlet–Voronoĭ cells Dni ={x :�x − sni� ≤�x − snj� for j = 1,...,n} are asymptotically congruent to � V (J)/n � 1/d Pasn→∞. This conjecture has so far been proved only for d = 2, where it is an immediate consequence of the weak stability result mentioned earlier. The convex polytope P then is a regular hexagon. The conjecture also follows from the result of Fejes Tóth [321]. Assertions in the literature that it is a consequence of earlier results are not justified. While for dimensions d > 2 Gersho’s conjecture is open, weaker results on what Sn looks like have been proved by Gruber [443]: Let J, f,wbe as earlier, such that f is from a certain class of non-decreasing functions, the boundary of J is not too fuzzy and w has a positive lower bound. Let Sn, n = 1, 2,..., be minimizing configurations for the expression in (24) for the Euclidean norm or in (25). Then: (i) There is a β>1 such that Sn is a � 1/βn 1/d ,β/n 1/d� -Delone set in J. (ii) Sn is uniformly distributed in J. For the definition of a Delone set in J, compare Sect. 32.1. The sequence of sets (Sn) is uniformly distributed in J, if #(K ∩ Sn) ∼ V (K ) n as n →∞for each Jordan measurable set K ⊆ J. V (J) That is, each K contains the appropriate share of points of Sn if n is sufficiently large. For more on uniform distribution see Hlawka [515]. Heuristic Observations If a convex body is optimal or almost optimal with respect to an inequality, then, in many cases, it is particularly regular or symmetric in a certain sense. See Groemer’s survey [403] on geometric stability results. The weak stability result for point configurations and its applications are also examples of this phenomenon, see the surveys [439, 442, 443]. Results on packing and covering of circular discs with maximum, respectively, minimum density and Gersho’s conjecture are further examples of this, see [436, 438] and Sects. 30.4 and 31.4. In all these cases the extremal configurations are point configurations which are distributed over subsets of E d or Riemannian manifolds in a rather regular way. More generally, we express this as follows: Heuristic Principle. In many simple situations, for example in low dimensions or depending on few parameters, the extremal configurations are rather regular, possibly in an asymptotic sense.
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Grundlehren der mathematischen Wiss
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Peter M. Gruber Institute of Discre
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VI Preface theory of finite groups
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Contents Preface ..................
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Contents XI 12 Special Convex Bodie
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Contents XIII 29 Packing of Balls a
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2 Convex Functions 1 Convex Functio
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4 Convex Functions x epi f f C y Fi
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6 Convex Functions Together these i
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8 Convex Functions Theorem 1.4. Let
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10 Convex Functions z = f (x) + f
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12 Convex Functions 1.3 Convexity C
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14 Convex Functions Proof (by affin
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16 Convex Functions Minkowski’s I
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18 Convex Functions (ii) Let x > 0.
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20 Convex Functions 2 Convex Functi
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22 Convex Functions | f (z) − f (
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24 Convex Functions First-Order Dif
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26 Convex Functions Remark. More pr
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28 Convex Functions even more is tr
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30 Convex Functions G(x). The proof
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32 Convex Functions by (15), unifor
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34 Convex Functions 2.4 A Stone-Wei
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36 Convex Functions x x Fig. 2.1. S
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38 Convex Functions F is convex. Us
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40 Convex Bodies results, character
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42 Convex Bodies Convex Hulls Given
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44 Convex Bodies The next result is
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46 Convex Bodies C ∩ L ⊥ clearl
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48 Convex Bodies Suppose not. Then,
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50 Convex Bodies The Centrepoint of
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52 Convex Bodies Since G is open, w
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54 Convex Bodies in one of the two
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56 Convex Bodies or geometric infor
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58 Convex Bodies v HC (u, h(u)) (v,
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60 Convex Bodies C D Fig. 4.3. Sepa
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62 Convex Bodies For the proof of t
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64 Convex Bodies in contradiction t
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66 Convex Bodies (6) R(t) ⊆ E d i
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68 Convex Bodies 5 The Boundary of
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70 Convex Bodies for all y ∈ C an
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72 Convex Bodies the existence of s
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74 Convex Bodies where r(·) is a s
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76 Convex Bodies Hence x ∈ conv e
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78 Convex Bodies N = � � X, O Y
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80 Convex Bodies Further topics of
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82 Convex Bodies We are now ready t
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84 Convex Bodies similarly, D j is
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86 Convex Bodies For the proof of t
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88 Convex Bodies The definition of
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90 Convex Bodies If ei ∈ Pi is no
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92 Convex Bodies Let v(·) denote (
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94 Convex Bodies The present sectio
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96 Convex Bodies Proposition 6.5. L
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98 Convex Bodies Thus Second, Minko
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100 Convex Bodies The Valuation Pro
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102 Convex Bodies Minkowski’s the
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104 Convex Bodies To remedy the sit
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106 Convex Bodies Proof. Applying S
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108 Convex Bodies Third, let C be a
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110 Convex Bodies A Problem of Sant
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112 Convex Bodies sets of S. Ifφ c
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114 Convex Bodies = � (−1) |J|
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116 Convex Bodies If P has dimensio
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118 Convex Bodies Since, by Volland
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120 Convex Bodies that is, V is sim
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122 Convex Bodies Let C, D ∈ C su
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124 Convex Bodies P Q . . . . Fig.
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126 Convex Bodies 7.3 Characterizat
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128 Convex Bodies and the Bi have p
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130 Convex Bodies Since the Riemann
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132 Convex Bodies Seventh, o v3 v2
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134 Convex Bodies Mean Width and th
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136 Convex Bodies � χ(C ∩ mD)
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138 Convex Bodies In the following,
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140 Convex Bodies 7.5 Hadwiger’s
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142 Convex Bodies 8.1 The Classical
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144 Convex Bodies C ∩ H(tC ) C D
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146 Convex Bodies Theorem 8.4. Let
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148 Convex Bodies In the following
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150 Convex Bodies Integration impli
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152 Convex Bodies As a consequence
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154 Convex Bodies Proof. � 1 2 w(
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156 Convex Bodies Let ϱ>0 be the m
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158 Convex Bodies Wulff’s Theorem
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160 Convex Bodies Third, by (8) and
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162 Convex Bodies Since the measure
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164 Convex Bodies An application of
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166 Convex Bodies Since f has Lipsc
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168 Convex Bodies Clearly, the inte
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170 Convex Bodies Note that �st :
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172 Convex Bodies Proposition 9.2.
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174 Convex Bodies Proof. Let ε>0.
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176 Convex Bodies The Brunn-Minkows
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178 Convex Bodies 9.3 Schwarz Symme
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180 Convex Bodies Torsional Rigidit
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182 Convex Bodies The proof of (3)
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184 Convex Bodies � �� 2 2
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188 Convex Bodies Both problems inf
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190 Convex Bodies The Area Measure
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192 Convex Bodies halfspace {z : un
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194 Convex Bodies Let σm be the di
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196 Convex Bodies Thus Minkowski’
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198 Convex Bodies Suppose now that
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200 Convex Bodies vector of St at x
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202 Convex Bodies Outer Billiards F
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204 Convex Bodies For more informat
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206 Convex Bodies with P. Thus, it
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208 Convex Bodies Note that ui ∈
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212 Convex Bodies the maximum of th
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214 Convex Bodies (20) mni ≥ 1 λ
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216 Convex Bodies Prove analogous r
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218 Convex Bodies Heuristic Princip
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220 Convex Bodies λC + x νC + z
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222 Convex Bodies To show that (K +
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224 Convex Bodies The integral here
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226 Convex Bodies In the following
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228 Convex Bodies The first such re
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230 Convex Bodies v o Fig. 12.3. Sy
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232 Convex Bodies What Does the Bou
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234 Convex Bodies Corollary 13.1. L
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236 Convex Bodies Hence ν = 0 and
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238 Convex Bodies geometry, see Sei
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240 Convex Bodies We distinguish th
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242 Convex Bodies by Proposition 13
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244 Convex Polytopes The material i
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246 Convex Polytopes V-Polytopes an
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248 Convex Polytopes Convex cones w
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250 Convex Polytopes Generalized Co
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252 Convex Polytopes d 2 inequaliti
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254 Convex Polytopes The Face Latti
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256 Convex Polytopes Then (6) impli
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258 Convex Polytopes P in F. For an
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260 Convex Polytopes Euler’s Poly
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262 Convex Polytopes bijection betw
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264 Convex Polytopes The Converse o
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266 Convex Polytopes (geometric) fa
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268 Convex Polytopes consists preci
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270 Convex Polytopes The Lower and
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272 Convex Polytopes A problem of S
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274 Convex Polytopes The first cond
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276 Convex Polytopes The existence
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278 Convex Polytopes For d = 3 it f
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280 Convex Polytopes 16 Volume of P
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282 Convex Polytopes by (2). Hence
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284 Convex Polytopes (12) The volum
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286 Convex Polytopes T ∩ Z, respe
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288 Convex Polytopes An Alternative
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290 Convex Polytopes P clearly can
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292 Convex Polytopes 17 Rigidity Ri
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294 Convex Polytopes Fig. 17.2. Cau
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296 Convex Polytopes Call the index
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298 Convex Polytopes of V. Fori ∈
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300 Convex Polytopes Thus (3) impli
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302 Convex Polytopes Proof. (i)⇒(
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304 Convex Polytopes For other pert
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306 Convex Polytopes where λ is a
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308 Convex Polytopes 18.3 The Isope
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310 Convex Polytopes 19 Lattice Pol
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312 Convex Polytopes Embed E d into
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314 Convex Polytopes To see this, n
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316 Convex Polytopes The Coefficien
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318 Convex Polytopes If the triangl
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320 Convex Polytopes � qP(t) = No
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322 Convex Polytopes Now, take into
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324 Convex Polytopes L � P + (n +
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326 Convex Polytopes V (S) = V .Let
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328 Convex Polytopes (7) ψ|H d = 0
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330 Convex Polytopes Theorem 19.6.
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332 Convex Polytopes (15) L(nP) = L
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334 Convex Polytopes have to be sin
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336 Convex Polytopes economics, von
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338 Convex Polytopes Existence of S
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340 Convex Polytopes Description of
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342 Convex Polytopes (6) u piai xq
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344 Convex Polytopes For x ∈ Bd
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346 Convex Polytopes Rational Polyh
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348 Convex Polytopes Totally Dual I
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350 Convex Polytopes of the vectors
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Geometry of Numbers and Aspects of
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Extension to Crystallographic Group
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Relations Between Different Bases 2
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21 Lattices 359 triangle conv{o,(u,
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By definition of bi+1, Thus (6) yie
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21 Lattices 363 A similar, slightly
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21.4 Polar Lattices 21 Lattices 365
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The First Fundamental Theorem 22 Mi
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22 Minkowski’s First Fundamental
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If 22 Minkowski’s First Fundament
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22 Minkowski’s First Fundamental
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Proof. Consider the linear forms l1
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Proof. It is sufficient to consider
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Thus V (C) ≥ V (O) = 2d � �
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Given C and L, the problem arises t
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23 Successive Minima 383 as require
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24 The Minkowski-Hlawka Theorem 24
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(6) (V (J) ≈) � n�= 0 (7) J
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24 The Minkowski-Hlawka Theorem 389
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The Variance Theorem of Rogers and
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The Selection Theorem of Mahler [68
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26 The Torus Group E d /L 395 where
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Proposition 26.2. E d /L is a compa
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26 The Torus Group E d /L 399 theor
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26 The Torus Group E d /L 401 The m
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The formula to calculate the Jordan
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27 Special Problems in the Geometry
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Asymptotic Estimates 27 Special Pro
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27 Special Problems in the Geometry
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28 Basis Reduction and Polynomial A
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(ii) �b1� ≤2 1 2 (d−1) min
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28 Basis Reduction and Polynomial A
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and so 28 Basis Reduction and Polyn
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Shortest Lattice Vector Problem 28
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and therefore �x − m� 2 = �
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29 Packing of Balls and Positive Qu
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29.3 Error Correcting Codes and Bal
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30 Packing of Convex Bodies 439 The
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Page 453 and 454: Packing and Central Symmetrization
Page 455 and 456: Existence of Densest Lattice Packin
Page 457 and 458: 30 Packing of Convex Bodies 447 Rem
Page 459 and 460: A Lower Estimate for the Maximum La
Page 461 and 462: Lattice Packing and Packing of Tran
Page 463 and 464: a f b o e 2D c Fig. 30.3. Disc and
Page 465 and 466: 31 Covering with Convex Bodies 455
Page 473 and 474: 32 Tiling with Convex Polytopes 463
Page 485 and 486: Define 32 Tiling with Convex Polyto
Page 491 and 492: 33.1 Fejes Tóth’s Inequality for
Page 493 and 494: Noting that 2h 2 v − hhvv = 2π 2
Page 495 and 496: 33 Optimum Quantization 485 The con
Page 497 and 498: (7) � (x, y) : x ∈ K, 0 ≤ y
Page 499 and 500: Next, we prove that (18) lim inf n
Page 501: Generalizations 33 Optimum Quantiza
Page 505 and 506: 33 Optimum Quantization 495 In (4)
Page 507 and 508: 33 Optimum Quantization 497 encoder
Page 509 and 510: 34 Koebe’s Representation Theorem
Page 511 and 512: G 34 Koebe’s Representation Theor
Page 513 and 514: Di+1 34 Koebe’s Representation Th
Page 523 and 524: References 1. Achatz, H., Kleinschm
Page 525 and 526: References 515 36. Arias de Reyna,
Page 527 and 528: References 517 88. Beer, G., Topolo
Page 529 and 530: References 519 136. Bohr, H., Molle
Page 531 and 532: References 521 190. Carathéodory,
Page 533 and 534: References 523 237. Dantzig, G.B.,
Page 535 and 536: References 525 286. Edmonds, A.L.,
Page 537 and 538: References 527 337. Florian, A., Ex
Page 539 and 540: References 529 385. Goodman, J.E.,
Page 541 and 542: References 531 435. Gruber, P.M., C
Page 543 and 544: References 533 487. Heil, E., Über
Page 545 and 546: References 535 534. Hyuga, T., An e
Page 547 and 548: References 537 582. Khovanskiĭ (Ho
Page 549 and 550: References 539 632. Lazutkin, V.F.,
Page 551 and 552: References 541 684. Mani-Levitska,
Page 553 and 554:
References 543 736. Minkowski, H.,
Page 555 and 556:
References 545 783. Pach, J., Agarw
Page 557 and 558:
References 547 835. Rickert, N.W.,
Page 559 and 560:
References 549 891. Schmidt, E., Di
Page 561 and 562:
References 551 941. Skubenko, B.F.,
Page 563 and 564:
References 553 992. Teissier, B., V
Page 565 and 566:
References 555 1042. Zassenhaus, H.
Page 567 and 568:
558 INDEX Bravais classification of
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560 INDEX existence of elementary v
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562 INDEX Kneser-Macbeath theorem,
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564 INDEX rational lattice, 414 rat
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566 INDEX transference theorem of K
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568 AUTHOR INDEX Björner, 265 Blas
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570 AUTHOR INDEX Giles, J., 1 Giles
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572 AUTHOR INDEX Kuczma, 13, 17 Kü
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574 AUTHOR INDEX Pick, 316 Pisier,
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576 AUTHOR INDEX Tanemura, 464 Tarj
Page 587 and 588:
578 List of Symbols sch, schL Schwa
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289. Manin: Gauge Field Theory and
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