Gruber P. Convex and Discrete Geometry

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20 Linear Optimization 349 systems of linear inequalities. An algorithm for geometric Hilbert bases is due to Hirzebruch [507] and Jung [556]. For references and detailed information, compare Schrijver [915] and Bertsimas and Weismantel [104]. Geometric Hilbert Bases A (geometric) Hilbert basis of a polyhedral convex cone C in E d with apex o is a set of vectors {a1,...,am} in C such that each integer vector in C is an integer linear combination of a1,...,am. Of particular interest are integer (geometric) Hilbert bases, that is, Hilbert bases consisting of integer vectors. The Geometric Hilbert Basis Theorem Old results of Gordan [387] and van der Corput [225] on systems of linear equations can be formulated as follows. Theorem 20.4. Let C be a pointed rational polyhedral convex cone in E d with apex o. Then C has an integer Hilbert basis. If C is pointed, it has a unique minimal (with respect to inclusion) integer Hilbert basis. Proof. Existence: Let C = pos{q1,...,qn} where the qi are rational vectors. We may suppose that qi ∈ Z d . We prove the following: (1) Let {a1,...,am} = � λ1q1 + ··· + λnqn : 0 ≤ λi ≤ 1 � ∩ Z d . Then {a1,...,am} is an integer Hilbert basis of C and C = pos{a1,...,am}. Since C = pos{q1,...,qn} and {q1,...,qn} ⊆{a1,...,am} ⊆C, clearly C = pos{a1,...,am}. To see that {a1,...,am} is an integer Hilbert basis of C, let u ∈ C ∩ Z d . Since C = pos{q1,...,qn}, there are µ1,...,µn ≥ 0 such that u = µ1q1 +···+µnqn. Then u −⌊µ1⌋q1 −···−⌊µn⌋qn = (µ1 −⌊µ1⌋)q1 +···+(µn −⌊µn⌋)qn ∈ C ∩ Z d . The vector (µ1 −⌊µ1⌋)q1 +···+(µn −⌊µn⌋)qn thus occurs among a1,...,am. Since the q1,...,qn also occur among the a1,...,am, we see that u is a non-negative integer linear combination of a1,...,am, concluding the proof of (1). Uniqueness: Let C be pointed. We will show that (2) B = � a ∈ C ∩ Z d \{o} :a is not a sum of vectors in C ∩ Z d \{o} � is the unique minimal Hilbert basis of C. Clearly, B is contained in any Hilbert basis of C. Since the Hilbert basis in (1) is finite, B is also finite. B is integer. Thus, to finish the proof of (2), we have to show that B is a Hilbert basis of C. Since C is pointed, o is an extreme point and thus a vertex of C. Thus there is a support hyperplane {x : cx = 0} of C at o which meets C only at o. We may assume that cx > 0 for each x ∈ C \{o}. Suppose that there are vectors in C ∩ Z d \{o}, which are not non-negative integer linear combinations
350 Convex Polytopes of the vectors in B. Letu be such a vector with cu(> 0) as close as possible to 0. Then, in particular, u �∈ B and we may choose vectors v,w ∈ C ∩ Z d \{o}, with u = v + w. Then cu = c v + c w. Since v,w ∈ C \{o} we thus have that 0 < c v,c w < cu which contradicts our choice of u. Thus every vector in C ∩ Z d , including o, is a non-negative integer linear combination of vectors in B. The proof of (2) is complete. ⊓⊔ The notion of geometric Hilbert basis and the geometric Hilbert basis theorem remind one of the Hilbert [500] basis theorem for ideals in polynomial rings over Noetherian rings. There are actually relations between these two topics, see [915], p. 376 for references. Characterization of Totally dual Integral Systems by Hilbert Bases We prove the following result, where a row ai of A is active on F if ai x = βi for each x ∈ F: Theorem 20.5. Let Ax ≤ b be a rational system of linear inequalities. Then the following propositions are equivalent: (i) Ax ≤ b is totally dual integral. (ii) For each face F of the convex polyhedron P ={x : Ax ≤ b} the rows of A which are active on F form a Hilbert basis of the cone generated by these rows. Proof. (i)⇒(ii) Let F be a face of P and let a1,...,ak be the rows of A which are active on F. Then, clearly, the following hold: (3) Let x be a relatively interior point of F. Leta be a row of A and β the corresponding entry of b. Then ax= β if a is one of a1,...,ak and ax
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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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Page 311 and 312: 300 Convex Polytopes Thus (3) impli
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Page 315 and 316: 304 Convex Polytopes For other pert
Page 317 and 318: 306 Convex Polytopes where λ is a
Page 319 and 320: 308 Convex Polytopes 18.3 The Isope
Page 321 and 322: 310 Convex Polytopes 19 Lattice Pol
Page 323 and 324: 312 Convex Polytopes Embed E d into
Page 325 and 326: 314 Convex Polytopes To see this, n
Page 327 and 328: 316 Convex Polytopes The Coefficien
Page 329 and 330: 318 Convex Polytopes If the triangl
Page 331 and 332: 320 Convex Polytopes � qP(t) = No
Page 333 and 334: 322 Convex Polytopes Now, take into
Page 335 and 336: 324 Convex Polytopes L � P + (n +
Page 337 and 338: 326 Convex Polytopes V (S) = V .Let
Page 339 and 340: 328 Convex Polytopes (7) ψ|H d = 0
Page 341 and 342: 330 Convex Polytopes Theorem 19.6.
Page 343 and 344: 332 Convex Polytopes (15) L(nP) = L
Page 345 and 346: 334 Convex Polytopes have to be sin
Page 347 and 348: 336 Convex Polytopes economics, von
Page 349 and 350: 338 Convex Polytopes Existence of S
Page 351 and 352: 340 Convex Polytopes Description of
Page 353 and 354: 342 Convex Polytopes (6) u piai xq
Page 355 and 356: 344 Convex Polytopes For x ∈ Bd
Page 357 and 358: 346 Convex Polytopes Rational Polyh
Page 359: 348 Convex Polytopes Totally Dual I
Page 363 and 364: Geometry of Numbers and Aspects of
Page 365 and 366: Extension to Crystallographic Group
Page 367 and 368: Relations Between Different Bases 2
Page 369 and 370: 21 Lattices 359 triangle conv{o,(u,
Page 371 and 372: By definition of bi+1, Thus (6) yie
Page 373 and 374: 21 Lattices 363 A similar, slightly
Page 375 and 376: 21.4 Polar Lattices 21 Lattices 365
Page 377 and 378: The First Fundamental Theorem 22 Mi
Page 379 and 380: 22 Minkowski’s First Fundamental
Page 381 and 382: If 22 Minkowski’s First Fundament
Page 383 and 384: 22 Minkowski’s First Fundamental
Page 385 and 386: Proof. Consider the linear forms l1
Page 387 and 388: Proof. It is sufficient to consider
Page 389 and 390: Thus V (C) ≥ V (O) = 2d � �
Page 391 and 392: Given C and L, the problem arises t
Page 393 and 394: 23 Successive Minima 383 as require
Page 395 and 396: 24 The Minkowski-Hlawka Theorem 24
Page 397 and 398: (6) (V (J) ≈) � n�= 0 (7) J
Page 399 and 400: 24 The Minkowski-Hlawka Theorem 389
Page 401 and 402: The Variance Theorem of Rogers and
Page 403 and 404: The Selection Theorem of Mahler [68
Page 405 and 406: 26 The Torus Group E d /L 395 where
Page 407 and 408: Proposition 26.2. E d /L is a compa
Page 409 and 410: 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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