Gruber P. Convex and Discrete Geometry

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1 Convex Functions of One Variable 17 The characterization of the gamma function by Bohr and Mollerup [136] is also a result of this type. It will be presented below, together with Artin’s [39] elegant proof. For more information on functional equations and convex functions the reader may consult the books of Kuczma [620], Castillo and Ruiz Cobo [196] and Czerwik [234], to which we add the nice little treatise of Smítal [944]. The Gamma Function Ɣ is defined by Ɣ(x) = � +∞ 0 t x−1 e −t dt for x > 0 and then extended, by analytic continuation, to the whole complex plane C, except the points 0, −1, −2,..., where it has poles of first-order. There are other ways to define Ɣ. See, e.g. formula (6) at the end of this section (Fig. 1.6). We first collect some properties of Ɣ. Theorem 1.10. Ɣ has the following properties: (i) Ɣ(1) = 1. (ii) Ɣ(x + 1) = xƔ(x) for x > 0, i.e. Ɣ satisfies Euler’s functional equation. (iii) Ɣis logarithmic convex, i.e. log Ɣ is convex for x > 0. Proof. (i) Ɣ(1) = � +∞ 0 e −t dt = lim �s s→+∞ 0 1 −1 0 1 e −t � −t dt = lim − e s→+∞ � �s � = 1. 0 Fig. 1.6. Gamma and log-gamma function Ɣ log Ɣ
18 Convex Functions (ii) Let x > 0. Then Ɣ(x + 1) = � +∞ 0 t x e −t dt = lim �s � x −t = lim − t e s→+∞ � �s + x 0 = x lim �s s→+∞ 0 t s→+∞ 0 x e −t dt �s t x−1 e −t dt � t x−1 e −t dt = xƔ(x). (iii) Let x, y > 0 and 0 0, are precisely the functions of the form g(x) = Ɣ(x)h(x) for x > 0, where h : R + → R is any function with period 1 and h(1) = 1. Among this large family of functions, Ɣ is singled out by the property of logarithmic convexity, as shown by Bohr and Mollerup [136]: Theorem 1.11. Let g : R + → R + be a function having the Properties (i)–(iii) of Theorem 1.10. Then g = Ɣ on R + . Proof. Properties (i) and (ii) imply that
Page 1 and 2: Grundlehren der mathematischen Wiss
Page 3 and 4: Peter M. Gruber Institute of Discre
Page 5 and 6: VI Preface theory of finite groups
Page 7 and 8: Contents Preface ..................
Page 9 and 10: Contents XI 12 Special Convex Bodie
Page 11 and 12: Contents XIII 29 Packing of Balls a
Page 13 and 14: 2 Convex Functions 1 Convex Functio
Page 15 and 16: 4 Convex Functions x epi f f C y Fi
Page 17 and 18: 6 Convex Functions Together these i
Page 19 and 20: 8 Convex Functions Theorem 1.4. Let
Page 21 and 22: 10 Convex Functions z = f (x) + f
Page 23 and 24: 12 Convex Functions 1.3 Convexity C
Page 25 and 26: 14 Convex Functions Proof (by affin
Page 27: 16 Convex Functions Minkowski’s I
Page 31 and 32: 20 Convex Functions 2 Convex Functi
Page 33 and 34: 22 Convex Functions | f (z) − f (
Page 35 and 36: 24 Convex Functions First-Order Dif
Page 37 and 38: 26 Convex Functions Remark. More pr
Page 39 and 40: 28 Convex Functions even more is tr
Page 41 and 42: 30 Convex Functions G(x). The proof
Page 43 and 44: 32 Convex Functions by (15), unifor
Page 45 and 46: 34 Convex Functions 2.4 A Stone-Wei
Page 47 and 48: 36 Convex Functions x x Fig. 2.1. S
Page 49 and 50: 38 Convex Functions F is convex. Us
Page 51 and 52: 40 Convex Bodies results, character
Page 53 and 54: 42 Convex Bodies Convex Hulls Given
Page 55 and 56: 44 Convex Bodies The next result is
Page 57 and 58: 46 Convex Bodies C ∩ L ⊥ clearl
Page 59 and 60: 48 Convex Bodies Suppose not. Then,
Page 61 and 62: 50 Convex Bodies The Centrepoint of
Page 63 and 64: 52 Convex Bodies Since G is open, w
Page 65 and 66: 54 Convex Bodies in one of the two
Page 67 and 68: 56 Convex Bodies or geometric infor
Page 69 and 70: 58 Convex Bodies v HC (u, h(u)) (v,
Page 71 and 72: 60 Convex Bodies C D Fig. 4.3. Sepa
Page 73 and 74: 62 Convex Bodies For the proof of t
Page 75 and 76: 64 Convex Bodies in contradiction t
Page 77 and 78: 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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30 Packing of Convex Bodies 441 Nex
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Packing and Central Symmetrization
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Existence of Densest Lattice Packin
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30 Packing of Convex Bodies 447 Rem
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A Lower Estimate for the Maximum La
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Lattice Packing and Packing of Tran
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a f b o e 2D c Fig. 30.3. Disc and
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31 Covering with Convex Bodies 455
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32 Tiling with Convex Polytopes 463
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Define 32 Tiling with Convex Polyto
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33.1 Fejes Tóth’s Inequality for
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Noting that 2h 2 v − hhvv = 2π 2
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33 Optimum Quantization 485 The con
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(7) � (x, y) : x ∈ K, 0 ≤ y
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Next, we prove that (18) lim inf n
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Generalizations 33 Optimum Quantiza
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33 Optimum Quantization 493 set wit
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33 Optimum Quantization 495 In (4)
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33 Optimum Quantization 497 encoder
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34 Koebe’s Representation Theorem
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G 34 Koebe’s Representation Theor
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Di+1 34 Koebe’s Representation Th
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References 1. Achatz, H., Kleinschm
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References 515 36. Arias de Reyna,
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References 517 88. Beer, G., Topolo
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References 519 136. Bohr, H., Molle
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References 521 190. Carathéodory,
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References 523 237. Dantzig, G.B.,
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References 525 286. Edmonds, A.L.,
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References 527 337. Florian, A., Ex
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References 529 385. Goodman, J.E.,
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References 531 435. Gruber, P.M., C
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References 533 487. Heil, E., Über
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References 535 534. Hyuga, T., An e
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References 537 582. Khovanskiĭ (Ho
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References 539 632. Lazutkin, V.F.,
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References 541 684. Mani-Levitska,
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References 543 736. Minkowski, H.,
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References 545 783. Pach, J., Agarw
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References 547 835. Rickert, N.W.,
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References 549 891. Schmidt, E., Di
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References 551 941. Skubenko, B.F.,
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References 553 992. Teissier, B., V
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References 555 1042. Zassenhaus, H.
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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
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578 List of Symbols sch, schL Schwa
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289. Manin: Gauge Field Theory and
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Gruber P. Convex and Discrete Geometry

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