Simultaneous approximation of polynomials

Size: px
Start display at page:

Download "Simultaneous approximation of polynomials"

Transcription

1 Smultaneous approxmaton of polynomals Anre Kupavsk * János Pach Abstract Let P enote the famly of all polynomals of egree at most n one varable x, wth real coeffcents. A sequence of postve numbers x 1 x 2... s calle P -controllng f there exst y 1, y 2,... R such that for every polynomal p P there exsts an nex wth p(x ) y 1. We settle an problem of Maka an Pach (1983) by showng that x 1 x 2... s P -controllng f an only f =1 1 x s vergent. The proof s base on a statement about coverng the Euclean space wth translates of slabs, whch s relate to Tarsk s plank problem. 1 Introucton Let F be a class of real functons R R. We say that a sequence of postve numbers x 1, x 2,... s F-controllng f there exst reals y 1, y 2,... wth the property that for every f F, one can fn an wth f(x ) y 1. In other wors, a sequence x 1, x 2,... s F-controllng f we can fn y 1, y 2,... R such that the ponts p 1 = (x 1, y 1 ), p 2 = (x 2, y 2 ),... R 2 smultaneously approxmate all functons n F, n the sense that the graph of every member f F gets (vertcally) closer than 1 to at least one pont p. In ths paper, we aress the followng queston rase n [11]. Gven a class of functons F, how sparse a F-controllng sequence can be? A smlar queston, motvate by a problem of László Fejes Tóth [5], was stue n [4]. Let P enote the class of polynomals R R of egree at most. It was shown by Maka an Pach [11] that f a sequence of postve numbers x 1 x 2... s P -controllng, then the nfnte seres s vergent. They conjecture that ths conton s also x 1 x 2 suffcent for a sequence x 1 x 2... to be P -controllng (see Conjecture 3.2.B n [11]). The am of ths note s to prove ths statement. * EPFL, Lausanne an MIPT, Moscow. Supporte n part by the grant N of the Russan Founaton for Basc Research. E-mal: kupavsk@ya.ru. EPFL, Lausanne an Rény Insttute, Buapest. Supporte by Hungaran Scence Founaton EuroGIGA Grant OTKA NN , by Swss Natonal Scence Founaton Grants an E-mal: pach@cms.nyu.eu. 1

2 Theorem 1. Let be a postve nteger an x 1 x 2... be a monotone ncreasng nfnte sequence of postve numbers. The sequence x 1, x 2,... s P -controllng f an only 1 f =. x 1 x 2 x 3 We also generalze ths result to other fntely generate functon classes. Gven + 1 real functons, f 0, f 1,..., f : R + R +, let L = L(f 0,..., f ) enote the set of all functons that can be obtane as lnear combnatons of them wth real coeffcents. That s, Here R + stans for the set of postve reals. L = {a 0 f a f : a 0,..., a R}. Theorem 2. Let 1 be an nteger, x 0 > 0, ε > 0, an let f 0, f 1,..., f : R + R + be real functons that are monotone ncreasng for x x 0 an boune over every boune subnterval of R +. Assume that the functons F j (x) = f j (x)/(f (x)) 1 ε (j = 0,..., 1) are monotone ecreasng for x x 0 an ten to 0 as x. An ncreasng sequence of postve numbers x 1 x 2... s L(f 0,..., f )-controllng f an only f =1 1 =. f (x ) Obvously, the functons f (x) = x ( = 0, 1,..., )) meet the above requrements, so that Theorem 2 mples Theorem 1. For the proof of Theorem 1, we wll rephrase the queston as a coverng problem for slabs. A slab (sometmes calle plank or strp) s the set of ponts S lyng between two parallel hyperplanes n R. The stance w between these two hyperplanes s calle the wth of the slab. We can wrte S as S = {x R : b w 2 v, x b + w 2 }, for some unt vector v an real number b. We say that a sequence of slabs S 1, S 2,... permts a translatve coverng of a subset R f there are sutable translates S of S ( = 1, 2,...) such that =1S = R. As t was shown n [11], Theorem 1 (an, n fact, Theorem 2, too) woul easly follow from Conjecture 1. ([11], [3]) Let be a postve nteger. A sequence of slabs n R wth wths w 1, w 2,... permts a translatve coverng of R f an only f =1 w =. The fact that ths conton s necessary follows, for example, from Tarsk s result [12] whch states that the total wth of any system of slabs the unon of whch covers a sk of unt ameter s at least 1. Tarsk s plank problem, whether ths statement remans true n hgher mensons, remane open for almost twenty years. In 1950, Bang [1, 2] answere ths queston n the affrmatve. For = 2, Conjecture 1 was prove by Maka an Pach [11] an, accorng to [6], nepenently, by Erős an Straus (unpublshe). (See [7, 8] for 2

3 some refnements.) For 3, the problem s open. Groemer [6] prove that any sequence of slabs n R wth wths w 1, w 2,... satsfyng =1 w +1 2 = permts a translatve coverng of R. Recently, the authors of the present note [9] have come close to settlng Conjecture 1 by replacng Groemer s suffcent conton wth the weaker assumpton lm sup n w 1 + w w n log(1/w n ) In partcular, any sequence of slabs of wths 1, 1, 1,... permts a translatve coverng of 2 3 space. To establsh Theorem 1, t s enough to verfy Conjecture 1 for specal sequences of slabs, whose normal vectors le on a moment curve. We wll o precsely ths n Secton 2, by explorng the natural orerng of these vectors. In Secton 3, we generalze our arguments to establsh Theorem 2. The last secton contans a few conclung remarks. > 0. Fgure 1: Controllng polynomals of egree at most. 2 Proof of Theorem 1 We only have to prove the f part of the theorem. 3

4 Let x 1 x 2... be a monotone ncreasng sequence of postve numbers wth 1 = x. We have to fn a sequence of reals y 1, y 2,... such that for any polynomal p(x) = j=0 a jx j wth real coeffcents a j, there exsts a postve nteger wth p(x ) y 1. Wrte p(x) n the form p(x) = x, a, where x = (1, x,..., x ), a = (a 0, a 1,..., a ) R +1, an. stans for the scalar prouct. Usng ths notaton, we have x = (1, x,..., x ) an the nequalty p(x ) y 1 can be rewrtten as y 1 x, a y + 1. For a fxe, the locus of ponts a R +1 satsfyng ths ouble nequalty s a slab S R +1 of wth w = 2 = 2 x (, wth normal vector x. See Fg. 1. The sequence x 1, x 2,... j=0 x2j )1/2 s P -controllng f an only f the sequence of slabs S 1, S 2,... permts a translatve coverng of R +1. If x 3 for nfntely many (an, hence, for all) postve ntegers, then for the wths of the corresponng slabs S we have w > 1. Thus, these slabs permt a translatve coverng 3 of R +1, because each of them can be translate to cover any ball of ameter 1. 3 Therefore, we can assume that x > 3 for all m. In fact, we can assume wthout loss of generalty that x > 3 for all 1, otherwse we smply scar the frst m 1 members of the sequence, an prove the theorem for the resultng sequence x m x m We are gong to explot the fact that the normal vectors x = (1, x,..., x ) of the slabs S le on the moment curve (1, x, x 2,..., x ). Frst, we nee an auxlary lemma. Lemma 1. Let be a postve nteger, let 3 x 1 x 2... be a fnte or nfnte sequence of reals, an let x = (1, x, x 2,..., x ) for every. Then there exst +1 lnearly nepenent vectors u 1,..., u +1 R +1 such that for every ( = 1, 2,...) an j (j = 1, 2,..., + 1), we have () x +1, u 1 x, u 1 x +1, u j x, u j, () x, u j 1 3 x u j. Proof. Take the stanar bass e 1,..., e +1 n R +1,.e., let e enote the all-zero vector wth a sngle 1 at the -th poston. Set u j := e +1 j +e +1 for j = 1,..., an u +1 := e +1. Conton () trvally hols for j = 1 an very easy to check for j = +1. For j = 2,...,, t reuces to x x x +1 whch s equvalent to x 1 + x x j x j + x (x x +1)(x j + x ) (x j +1 + x +1)(x 1 + x ). 4,

5 The last nequalty can be rewrtten as x j +1 x j j 1 (x +1 x )( or, vng both ses by x j j 1 +1 x j j 2 x k +1x j 1 k + (x +1 x ), as j 2 x k +1x j 1 k + x k +1x j 2 k x k +1x j 2 k x j 1 +1 xj 1 0. x j 1 +1 xj 1 ) 0, Usng the fact x +1 x, an bounng from above each sum by ts largest term multple by the number of terms, we obtan that the left-han se of the last nequalty s at most jx j (j 1)xj 2 +1 xj 1 +1 xj 1 < x j 1 +1 (2j 1 xj 1 ). As x 3, the rght-han se of ths nequalty s always negatve an () hols. It remans to verfy conton (). Takng nto account that x 3, we have x, u +1 = x 1 2 x = 1 2 x u +1. On the other han, for j = 1,...,, we obtan x, u j = x j Ths completes the proof of Lemma 1. + x 1 2 x 1 3 x u j. In orer to establsh Theorem 1, t s enough to prove that there s a constant c = c(+1) such that any system of slabs S ( = 1,..., n) n R +1 whose normal vectors are (1, x,..., x ) for some 3 x 1 x 2... x n an whose total wth s at least c, permts a translatve coverng of a ball of unt ameter. Ths s an mmeate corollary of Lemma 1 an the followng asserton. Lemma 2. For every postve nteger, for any system of + 1 lnearly nepenent vectors u 1,..., u +1 n R +1, an for any γ > 0, there s a constant c wth the followng property. Gven any system of slabs S ( = 1,..., n) n R +1, whose normal vectors x satsfy the contons () x +1, u 1 x, u 1 x +1, u j x, u j, () x, u j γ x u j for every an j, an whose total wth n =1 w s at least c, the slabs S permt a translatve coverng of a ( + 1)-mensonal ball of unt ameter. 5

6 Fgure 2: We place the slabs one by one. Proof. Instea of coverng a ball of unt ameter, t wll be more convenent to cover the smplex Δ wth one vertex n the orgn 0 an the others at the ponts (vectors) u j (j = 1,..., + 1). By properly scalng these vectors, f necessary, we can assume that Δ contans a ball of unt ameter. We place the slabs one by one. See Fg. 2. We place S 1, a translate of S 1, so that one of ts bounary hyperplanes passes through 0 an the other one cuts a smplex Δ 1 out of the cone Γ of all lnear combnatons of the vectors u 1,..., u +1 wth postve coeffcents. Accorng to our assumptons, we have x 1, u j > 0 for every j. Therefore, S 1 oes not separate Γ nto two cones: S 1 Γ s nee a smplex Δ 1. Suppose that we have alreay place S 1,..., S, the translates of S 1,..., S, so that ther unon covers a smplex Δ wth one vertex at the orgn, an the others along the + 1 half-lnes that span the cone Γ. We also assume that the facet of Δ opposte to the orgn s a bounary hyperplane of S. Let p (j) enote the vertex of Δ that belongs to the open half-lne parallel to u j emanatng from 0 (j = 1,..., + 1). Next, we place a translate S +1 of S +1 so that one of ts bounary hyperplanes, enote by π, passes through p (1), an the other one, π, cuts the half-lne parallel to u 1 at a pont p +1 (1) wth p +1 (1) > p (1). That s, p +1 (1) s further away from the orgn than p (1) s. Let p +1 (2),..., p +1 ( + 1) enote the ntersecton ponts of π wth the half-lnes parallel to u 2,..., u +1, respectvely, an let Δ +1 be the smplex nuce by the vertces 0, p +1 (1),..., p +1 ( + 1). We have to verfy that Δ +1 s entrely covere by the slabs S 1,..., S +1. By the nucton hypothess, Δ was covere by the slabs S 1,..., S. Thus, t s suffcent to check that the 6

7 hyperplane π ntersects every ege 0p (j) of Δ, for j = 1,..., + 1. Let α j u j be the ntersecton pont of π wth the half-lne parallel to u j, an let p (j) = β j u j. We have to prove that α j β j. By efnton, we have x +1, p (1) α j u j = 0 an x, p (1) β j u j = 0. From here, we get α j = x +1, p (1) x, p (1) β j x +1, u j x, u j = x +1, p (1) x+1, u j x, p (1) x, u j = x +1, u 1 x+1, u j x, u 1 x, u j. In vew of assumpton () of the lemma, the rght-han se of the above chan of equatons s at most 1, as requre. Observe that urng the whole proceure the uncovere part of the cone Γ always remans convex an, hence, connecte. In the nth step, n =1S Δ n. By the constructon, p (1) les at least w farther away from the orgn along the half-lne parallel to u 1 than p 1 (1) oes. Thus, we have n p n (1) w c. Usng the fact that x n, p n (j) p n (1) = 0 for every j 2, an takng nto account assumpton (), we obtan p n (j) x n, p n (j) x n =1 = x n, p n (1) x n γ p n (1) γc. Thus, f c s suffcently large, we have p n (j) u j. Ths means that Δ n contans the smplex Δ efne n the frst paragraph of ths proof. Hence, t also contans a ball of unt ameter, as requre. 3 Proof of Theorem 2 In ths secton, we exten the technque use n the proof of Theorem 1 to establsh Theorem 2. As n the proof Theorem 1, we can wrte any functon l = a kf k L(f 0,..., f ) as l(x) = x, a, where x = (f 0 (x), f 1 (x),..., f (x)) an a = (a 0, a 1,..., a ) R +1. As before, we only have to prove the f part of the theorem, whch s equvalent to the fact that the slabs S R +1 wth normal vector x = (f 0 (x ),..., f (x )) an wth w = 2 x = 2 ( f k 2(x )) 2 1/2 f (x ), for = 1, 2,..., permt a translatve coverng of R +1. Agan, t s enough to conser the case when lm x =, otherwse each slab S contans a ball of ameter at least 2 f (lm x ) > 0. 7

8 We follow the scheme of the proof of Theorem 1. Accorng to Lemma 2, t s enough to show that there exst + 1 lnearly nepenent vectors u 1,..., u +1 that satsfy contons () an () wth x = (f 0 (x ),..., f (x )) an wth a sutable constant γ > 0. We can assume wthout loss of generalty that x 1, an hence all x s, are so large that they satsfy x 1 x 0 an the nequaltes f j (x) f (x) f j(x 1 ) f (x 1 ) 1, (1) for every x x 1 an j = 0,..., 1. To see ths, observe that f j (x)/f (x) = F j (x)/f ε(x) s monotone ecreasng n x, because F j s monotone ecreasng, whle f s monotone ncreasng. Let e 1,..., e +1 be the stanar bass n R +1. For 1 j + 1, set +1 u j := e k 1 2 e +2 j. k=1 In other wors, all coornates of u j are 1, wth the excepton of the (+2 j)-th coornate, whch s 1 2. By efnton, we have x, u j 1f 2 (x ) an u j < + 1. It follows from (1) that for j, so that f j (x ) f (x ) 1 Hence, for every an j, ( 1/2 x fk 2 (x )) 2f (x ). x, u j 1 2 f (x ) x 1 2 2( + 1) x u j. Therefore, conton () n Lemma 2 s satsfe wth γ = 1 2 2(+1). It remans to verfy conton (). For the rest of the argument, fx j (1 j + 1). We have to show that for every ( = 1, 2,...), the nequalty x +1, u 1 x, u 1 x +1, u j x, u j hols. For j = 1, the statement s trval. Therefore, we may suppose that j > 1. Next, we want to get r of f (x) n the left han se, keepng both the numerator an enomnator postve. The above nequalty equvalent to the followng: x +1, u x +1, u j x, u x, u j x +1, u j x, u j. 8

9 Usng the notaton φ(x) = 1 1 f k (x) f 1 +1 j(x), ψ(x) = f k (x) 1 2 f +1 j(x), the above nequalty may be rewrtten as φ(x +1 ) φ(x ) f (x +1 ) + ψ(x +1 ). (2) f (x ) + ψ(x ) Before checkng that (2) s true, let us summarze the propertes of the functons φ an ψ we nee: 1. φ(x +1 )/φ(x ) f 1 ε (x +1 )/f 1 ε (x ) for the constant ε > 0 from Theorem 2, 2. ψ(x +1 ) cf 1 ε (x +1 ) for a constant c > 0, an 3. ψ(x +1 ) ψ(x ). By the monotoncty of F k, we have f k (x +1 )/f k (x ) f 1 ε (x +1 )/f 1 ε (x ), for k = 0,..., 1. Now property 1 follows from the fact that, f a 0,..., a 1, b 0,..., b 1, t are postve numbers satsfyng a 0 /b 0 t,..., a 1 /b 1 t, then (a a 1 )/(b b 1 ) t. Usng that lm x F k (x) = 0 for k = 0,..., 1, we get property 2. Property 3 s a rect consequence of our assumpton that each f k (k = 0, 1,...) s monotone ncreasng for x x 0. We have to verfy (2). In vew of property 1, t s suffcent to show f 1 ε (x +1 ) f 1 ε (x ) f (x +1 ) + ψ(x +1 ), f (x ) + ψ(x ) whch s equvalent to ( ( f ψ(x )f 1 ε (x +1 ) ψ(x +1 )f 1 ε (x ) f (x )f 1 ε (x +1 ) ) ) ε (x +1 ) 1, f (x ) or, n a slghtly fferent form, ψ(x )f 1 ε (x +1 ) ψ(x +1 )f 1 ε (x ) f (x )f 1 ε ( ( (x +1 ) ε f (x +1 ) f 1 ε f 1 ε (x ) (x ) ) ) ε 1 ε 1. Replacng the left-han se by a larger quantty (takng property 3 nto account) an the rght-han se by a smaller one (applyng the nequalty (1 + x) α 1 + αx, val for all α, x 0), we obtan the stronger nequalty ψ(x +1 )(f 1 ε ( (x +1 ) f 1 ε (x )) f (x )f 1 ε (x +1 ) 9 ε 1 ε f 1 ε (x +1 ) f 1 ε f 1 ε (x ) (x ) ). (3)

10 Thus, t s suffcent to prove (3). Rearrangng the terms, we obtan ψ(x +1 ) ε 1 ε f ε (x )f 1 ε (x +1 ). By property 2, we have ψ(x +1 ) cf 1 ε (x +1 ), so that t s enough to check that cf 1 ε (x +1 ) ε 1 ε f (x ε )f 1 ε (x +1 ), that s, c ε f ε 1 ε (x ). As f (x) s an ncreasng functon for x x 0, the last nequalty s satsfe f we choose x 1 (an, hence, all other x ) suffcently large. Ths completes the proof of (3), (2), an so the proof of Theorem 2. 4 Conclung remarks 1. As was mentone n the Introucton, Conjecture 1 s known to be true n the plane. Moreover, n [11] a stronger statement was prove: there exsts a constant c such that every collecton of strps wth total wth at least c permts a translatve coverng of a sk of ameter 1. In vew of ths, one can make the followng even boler conjecture. Conjecture 2. For any postve nteger, there exsts a constant c = c() such that every collecton of slabs n R of total wth at least c permts a translatve coverng of a unt ameter -mensonal ball. Suppose Conjecture 1 s true for a postve nteger. Answerng a queston n [11], Imre Z. Ruzsa [10] prove that then, for the same value of, Conjecture 2 also hols. Thus, the two conjectures are equvalent. 2. Gven a class F of functons R R, we say that a sequence of postve numbers x 1 x 2... s strongly F-controllng f there exst reals y 1, y 2,... wth the property that, for every ε > 0 an every f F, one can fn an wth f(x ) y ε. It s easy to see that the conton n Theorem 1 s suffcent to guarantee that the sequence x 1, x 2,... s strongly P -controllng. Theorem 2 can also be strengthene analogously. 3. The am of ths paper was to fn necessary an suffcent contons for a sequence of numbers to be L-controllng, where L = L(f 1,..., f ) s the class of functons that can be obtane as lnear combnatons of f 1,..., f. We reuce ths problem to a queston about coverng R wth translates of certan slabs. However, the two problems are not necessarly equvalent. For example, we have notce that the slabs obtane at ths reucton ha some specal propertes: apart from ther wths, ther normal vectors were also prescrbe. Ths enable us to cover R wth ther translates, even f we o not know whether such a coverng exsts for every system of slabs wth the same wths. Nevertheless, n a more complcate sense, the two problems are equvalent. 10

11 Theorem 3. Gven a postve nteger, an a sequence of postve numbers x 1, x 2,..., efne a famly F = F(, x 1, x 2,...) of -tuples of functons f 1,..., f : R R as F = {(f 1,..., f ) : fj 2 (x ) = x 2 j=1 for all }. Then a sequence of slabs wth wths x 1, x 2,... permts a translatve coverng of R f an only f x 1, x 2,... s L(f 1,..., f )-controllng for every -tuple (f 1,..., f ) F, where L(f 1,..., f ) = {a 1 f a f : a 1,..., a R}. References [1] Th. Bang, On coverng by parallel-strps, Mat. Tsskr. B (1950), [2] Th. Bang, A soluton of the plank problem, Proc. Amer. Math. Soc. 2 (1951), [3] P. Brass, W. Moser, an J. Pach, Research Problems n Dscrete Geometry, Sprnger, Heelberg, [4] P. Erős an J. Pach, On a problem of L. Fejes Tóth, Dscrete Math. 30 (1980), no. 2, [5] L. Fejes Tóth, Remarks on the ual of Tarsk s plank problem n Hungaran), Matematka Lapok 25 (1974), [6] H. Groemer, On coverngs of convex sets by translates of slabs, Proc. Amer. Math. Soc. 82 (1981), no. 2, [7] H. Groemer, Coverng an packng propertes of boune sequences of convex sets, Mathematka 29 (1982), [8] H. Groemer, Some remarks on translatve coverngs of convex omans by strps, Cana. Math. Bull. 27 (1984), no. 2, [9] A. Kupavsk an J. Pach, Translatve coverng of the space wth slabs, manuscrpt. [10] I. Z. Ruzsa, personal communcaton. [11] E. Maka Jr. an J. Pach, Controllng functon classes an coverng Euclean space, Stu. Scent. Math. Hungarca 18 (1983), [12] A. Tarsk, Uwag o stopnu równoważnośc welok atów (n Polsh), Parametr 2 (1932),

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space.

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space. Lnear, affne, and convex sets and hulls In the sequel, unless otherwse specfed, X wll denote a real vector space. Lnes and segments. Gven two ponts x, y X, we defne xy = {x + t(y x) : t R} = {(1 t)x +

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

A GENERALIZATION OF JUNG S THEOREM. M. Henk

A GENERALIZATION OF JUNG S THEOREM. M. Henk A GENERALIZATION OF JUNG S THEOREM M. Henk Abstract. The theorem of Jung establshes a relaton between crcumraus an ameter of a convex boy. The half of the ameter can be nterprete as the maxmum of crcumra

More information

Affine transformations and convexity

Affine transformations and convexity Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/

More information

A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON

A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON PIOTR NAYAR AND TOMASZ TKOCZ Abstract We prove a menson-free tal comparson between the Euclean norms of sums of nepenent ranom vectors

More information

arxiv: v1 [math.co] 1 Mar 2014

arxiv: v1 [math.co] 1 Mar 2014 Unon-ntersectng set systems Gyula O.H. Katona and Dánel T. Nagy March 4, 014 arxv:1403.0088v1 [math.co] 1 Mar 014 Abstract Three ntersecton theorems are proved. Frst, we determne the sze of the largest

More information

Chapter 2 Transformations and Expectations. , and define f

Chapter 2 Transformations and Expectations. , and define f Revew for the prevous lecture Defnton: support set of a ranom varable, the monotone functon; Theorem: How to obtan a cf, pf (or pmf) of functons of a ranom varable; Eamples: several eamples Chapter Transformatons

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

Exercise Solutions to Real Analysis

Exercise Solutions to Real Analysis xercse Solutons to Real Analyss Note: References refer to H. L. Royden, Real Analyss xersze 1. Gven any set A any ɛ > 0, there s an open set O such that A O m O m A + ɛ. Soluton 1. If m A =, then there

More information

Math 702 Midterm Exam Solutions

Math 702 Midterm Exam Solutions Math 702 Mdterm xam Solutons The terms measurable, measure, ntegrable, and almost everywhere (a.e.) n a ucldean space always refer to Lebesgue measure m. Problem. [6 pts] In each case, prove the statement

More information

Non-negative Matrices and Distributed Control

Non-negative Matrices and Distributed Control Non-negatve Matrces an Dstrbute Control Yln Mo July 2, 2015 We moel a network compose of m agents as a graph G = {V, E}. V = {1, 2,..., m} s the set of vertces representng the agents. E V V s the set of

More information

REAL ANALYSIS I HOMEWORK 1

REAL ANALYSIS I HOMEWORK 1 REAL ANALYSIS I HOMEWORK CİHAN BAHRAN The questons are from Tao s text. Exercse 0.0.. If (x α ) α A s a collecton of numbers x α [0, + ] such that x α

More information

GENERIC CONTINUOUS SPECTRUM FOR MULTI-DIMENSIONAL QUASIPERIODIC SCHRÖDINGER OPERATORS WITH ROUGH POTENTIALS

GENERIC CONTINUOUS SPECTRUM FOR MULTI-DIMENSIONAL QUASIPERIODIC SCHRÖDINGER OPERATORS WITH ROUGH POTENTIALS GENERIC CONTINUOUS SPECTRUM FOR MULTI-DIMENSIONAL QUASIPERIODIC SCHRÖDINGER OPERATORS WITH ROUGH POTENTIALS YANG FAN AND RUI HAN Abstract. We stuy the mult-mensonal operator (H xu) n = m n = um + f(t n

More information

Maximizing the number of nonnegative subsets

Maximizing the number of nonnegative subsets Maxmzng the number of nonnegatve subsets Noga Alon Hao Huang December 1, 213 Abstract Gven a set of n real numbers, f the sum of elements of every subset of sze larger than k s negatve, what s the maxmum

More information

PHZ 6607 Lecture Notes

PHZ 6607 Lecture Notes NOTE PHZ 6607 Lecture Notes 1. Lecture 2 1.1. Defntons Books: ( Tensor Analyss on Manfols ( The mathematcal theory of black holes ( Carroll (v Schutz Vector: ( In an N-Dmensonal space, a vector s efne

More information

NP-Completeness : Proofs

NP-Completeness : Proofs NP-Completeness : Proofs Proof Methods A method to show a decson problem Π NP-complete s as follows. (1) Show Π NP. (2) Choose an NP-complete problem Π. (3) Show Π Π. A method to show an optmzaton problem

More information

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS BOUNDEDNESS OF THE IESZ TANSFOM WITH MATIX A WEIGHTS Introducton Let L = L ( n, be the functon space wth norm (ˆ f L = f(x C dx d < For a d d matrx valued functon W : wth W (x postve sem-defnte for all

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON

A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON PIOTR NAYAR AND TOMASZ TKOCZ Abstract We prove a menson-free tal comparson between the Euclean norms of sums of nepenent ranom vectors

More information

Bounds for Spectral Radius of Various Matrices Associated With Graphs

Bounds for Spectral Radius of Various Matrices Associated With Graphs 45 5 Vol.45, No.5 016 9 AVANCES IN MATHEMATICS (CHINA) Sep., 016 o: 10.11845/sxjz.015015b Bouns for Spectral Raus of Varous Matrces Assocate Wth Graphs CUI Shuyu 1, TIAN Guxan, (1. Xngzh College, Zhejang

More information

Appendix B. Criterion of Riemann-Stieltjes Integrability

Appendix B. Criterion of Riemann-Stieltjes Integrability Appendx B. Crteron of Remann-Steltes Integrablty Ths note s complementary to [R, Ch. 6] and [T, Sec. 3.5]. The man result of ths note s Theorem B.3, whch provdes the necessary and suffcent condtons for

More information

On a one-parameter family of Riordan arrays and the weight distribution of MDS codes

On a one-parameter family of Riordan arrays and the weight distribution of MDS codes On a one-parameter famly of Roran arrays an the weght strbuton of MDS coes Paul Barry School of Scence Waterfor Insttute of Technology Irelan pbarry@wte Patrck Ftzpatrck Department of Mathematcs Unversty

More information

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg prnceton unv. F 17 cos 521: Advanced Algorthm Desgn Lecture 7: LP Dualty Lecturer: Matt Wenberg Scrbe: LP Dualty s an extremely useful tool for analyzng structural propertes of lnear programs. Whle there

More information

Graph Reconstruction by Permutations

Graph Reconstruction by Permutations Graph Reconstructon by Permutatons Perre Ille and Wllam Kocay* Insttut de Mathémathques de Lumny CNRS UMR 6206 163 avenue de Lumny, Case 907 13288 Marselle Cedex 9, France e-mal: lle@ml.unv-mrs.fr Computer

More information

Some basic inequalities. Definition. Let V be a vector space over the complex numbers. An inner product is given by a function, V V C

Some basic inequalities. Definition. Let V be a vector space over the complex numbers. An inner product is given by a function, V V C Some basc nequaltes Defnton. Let V be a vector space over the complex numbers. An nner product s gven by a functon, V V C (x, y) x, y satsfyng the followng propertes (for all x V, y V and c C) (1) x +

More information

2.3 Nilpotent endomorphisms

2.3 Nilpotent endomorphisms s a block dagonal matrx, wth A Mat dm U (C) In fact, we can assume that B = B 1 B k, wth B an ordered bass of U, and that A = [f U ] B, where f U : U U s the restrcton of f to U 40 23 Nlpotent endomorphsms

More information

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016 U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and

More information

STEINHAUS PROPERTY IN BANACH LATTICES

STEINHAUS PROPERTY IN BANACH LATTICES DEPARTMENT OF MATHEMATICS TECHNICAL REPORT STEINHAUS PROPERTY IN BANACH LATTICES DAMIAN KUBIAK AND DAVID TIDWELL SPRING 2015 No. 2015-1 TENNESSEE TECHNOLOGICAL UNIVERSITY Cookevlle, TN 38505 STEINHAUS

More information

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP C O L L O Q U I U M M A T H E M A T I C U M VOL. 80 1999 NO. 1 FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP BY FLORIAN K A I N R A T H (GRAZ) Abstract. Let H be a Krull monod wth nfnte class

More information

Lecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem.

Lecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem. prnceton u. sp 02 cos 598B: algorthms and complexty Lecture 20: Lft and Project, SDP Dualty Lecturer: Sanjeev Arora Scrbe:Yury Makarychev Today we wll study the Lft and Project method. Then we wll prove

More information

Spectral Graph Theory and its Applications September 16, Lecture 5

Spectral Graph Theory and its Applications September 16, Lecture 5 Spectral Graph Theory and ts Applcatons September 16, 2004 Lecturer: Danel A. Spelman Lecture 5 5.1 Introducton In ths lecture, we wll prove the followng theorem: Theorem 5.1.1. Let G be a planar graph

More information

MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS

MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS These are nformal notes whch cover some of the materal whch s not n the course book. The man purpose s to gve a number of nontrval examples

More information

THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS

THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS Dscussones Mathematcae Graph Theory 27 (2007) 401 407 THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS Guantao Chen Department of Mathematcs and Statstcs Georga State Unversty,

More information

Large-Scale Data-Dependent Kernel Approximation Appendix

Large-Scale Data-Dependent Kernel Approximation Appendix Large-Scale Data-Depenent Kernel Approxmaton Appenx Ths appenx presents the atonal etal an proofs assocate wth the man paper [1]. 1 Introucton Let k : R p R p R be a postve efnte translaton nvarant functon

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

Explicit bounds for the return probability of simple random walk

Explicit bounds for the return probability of simple random walk Explct bouns for the return probablty of smple ranom walk The runnng hea shoul be the same as the ttle.) Karen Ball Jacob Sterbenz Contact nformaton: Karen Ball IMA Unversty of Mnnesota 4 Ln Hall, 7 Church

More information

First day August 1, Problems and Solutions

First day August 1, Problems and Solutions FOURTH INTERNATIONAL COMPETITION FOR UNIVERSITY STUDENTS IN MATHEMATICS July 30 August 4, 997, Plovdv, BULGARIA Frst day August, 997 Problems and Solutons Problem. Let {ε n } n= be a sequence of postve

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

REGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction

REGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction REGULAR POSITIVE TERNARY QUADRATIC FORMS BYEONG-KWEON OH Abstract. A postve defnte quadratc form f s sad to be regular f t globally represents all ntegers that are represented by the genus of f. In 997

More information

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017 U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that

More information

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

COMPLEX NUMBERS AND QUADRATIC EQUATIONS COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not

More information

Field and Wave Electromagnetic. Chapter.4

Field and Wave Electromagnetic. Chapter.4 Fel an Wave Electromagnetc Chapter.4 Soluton of electrostatc Problems Posson s s an Laplace s Equatons D = ρ E = E = V D = ε E : Two funamental equatons for electrostatc problem Where, V s scalar electrc

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

On a theorem of V. Bernik in the metrical theory of Diophantine approximation

On a theorem of V. Bernik in the metrical theory of Diophantine approximation Acta Arthmetca 117, no.1 (2005) 71-80 On a theorem of V. Bern n the metrcal theory of Dophantne approxmaton by V. Beresnevch (Mns) 1 1. Introducton. We begn by ntroducng some notaton: #S wll denote the

More information

Convexity preserving interpolation by splines of arbitrary degree

Convexity preserving interpolation by splines of arbitrary degree Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete

More information

THE WEIGHTED WEAK TYPE INEQUALITY FOR THE STRONG MAXIMAL FUNCTION

THE WEIGHTED WEAK TYPE INEQUALITY FOR THE STRONG MAXIMAL FUNCTION THE WEIGHTED WEAK TYPE INEQUALITY FO THE STONG MAXIMAL FUNCTION THEMIS MITSIS Abstract. We prove the natural Fefferman-Sten weak type nequalty for the strong maxmal functon n the plane, under the assumpton

More information

Complete subgraphs in multipartite graphs

Complete subgraphs in multipartite graphs Complete subgraphs n multpartte graphs FLORIAN PFENDER Unverstät Rostock, Insttut für Mathematk D-18057 Rostock, Germany Floran.Pfender@un-rostock.de Abstract Turán s Theorem states that every graph G

More information

CENTRAL LIMIT THEORY FOR THE NUMBER OF SEEDS IN A GROWTH MODEL IN d WITH INHOMOGENEOUS POISSON ARRIVALS

CENTRAL LIMIT THEORY FOR THE NUMBER OF SEEDS IN A GROWTH MODEL IN d WITH INHOMOGENEOUS POISSON ARRIVALS The Annals of Apple Probablty 1997, Vol. 7, No. 3, 82 814 CENTRAL LIMIT THEORY FOR THE NUMBER OF SEEDS IN A GROWTH MODEL IN WITH INHOMOGENEOUS POISSON ARRIVALS By S. N. Chu 1 an M. P. Qune Hong Kong Baptst

More information

Competitive Experimentation and Private Information

Competitive Experimentation and Private Information Compettve Expermentaton an Prvate Informaton Guseppe Moscarn an Francesco Squntan Omtte Analyss not Submtte for Publcaton Dervatons for te Gamma-Exponental Moel Dervaton of expecte azar rates. By Bayes

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009 College of Computer & Informaton Scence Fall 2009 Northeastern Unversty 20 October 2009 CS7880: Algorthmc Power Tools Scrbe: Jan Wen and Laura Poplawsk Lecture Outlne: Prmal-dual schema Network Desgn:

More information

20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The first idea is connectedness.

20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The first idea is connectedness. 20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The frst dea s connectedness. Essentally, we want to say that a space cannot be decomposed

More information

Bernoulli Numbers and Polynomials

Bernoulli Numbers and Polynomials Bernoull Numbers and Polynomals T. Muthukumar tmk@tk.ac.n 17 Jun 2014 The sum of frst n natural numbers 1, 2, 3,..., n s n n(n + 1 S 1 (n := m = = n2 2 2 + n 2. Ths formula can be derved by notng that

More information

DIFFERENTIAL FORMS BRIAN OSSERMAN

DIFFERENTIAL FORMS BRIAN OSSERMAN DIFFERENTIAL FORMS BRIAN OSSERMAN Dfferentals are an mportant topc n algebrac geometry, allowng the use of some classcal geometrc arguments n the context of varetes over any feld. We wll use them to defne

More information

SELECTED SOLUTIONS, SECTION (Weak duality) Prove that the primal and dual values p and d defined by equations (4.3.2) and (4.3.3) satisfy p d.

SELECTED SOLUTIONS, SECTION (Weak duality) Prove that the primal and dual values p and d defined by equations (4.3.2) and (4.3.3) satisfy p d. SELECTED SOLUTIONS, SECTION 4.3 1. Weak dualty Prove that the prmal and dual values p and d defned by equatons 4.3. and 4.3.3 satsfy p d. We consder an optmzaton problem of the form The Lagrangan for ths

More information

Solutions to the 71st William Lowell Putnam Mathematical Competition Saturday, December 4, 2010

Solutions to the 71st William Lowell Putnam Mathematical Competition Saturday, December 4, 2010 Solutons to the 7st Wllam Lowell Putnam Mathematcal Competton Saturday, December 4, 2 Kran Kedlaya and Lenny Ng A The largest such k s n+ 2 n 2. For n even, ths value s acheved by the partton {,n},{2,n

More information

8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS

8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 493 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces you have studed thus far n the text are real vector spaces because the scalars

More information

Visualization of 2D Data By Rational Quadratic Functions

Visualization of 2D Data By Rational Quadratic Functions 7659 Englan UK Journal of Informaton an Computng cence Vol. No. 007 pp. 7-6 Vsualzaton of D Data By Ratonal Quaratc Functons Malk Zawwar Hussan + Nausheen Ayub Msbah Irsha Department of Mathematcs Unversty

More information

Edge Isoperimetric Inequalities

Edge Isoperimetric Inequalities November 7, 2005 Ross M. Rchardson Edge Isopermetrc Inequaltes 1 Four Questons Recall that n the last lecture we looked at the problem of sopermetrc nequaltes n the hypercube, Q n. Our noton of boundary

More information

Random Walks on Digraphs

Random Walks on Digraphs Random Walks on Dgraphs J. J. P. Veerman October 23, 27 Introducton Let V = {, n} be a vertex set and S a non-negatve row-stochastc matrx (.e. rows sum to ). V and S defne a dgraph G = G(V, S) and a drected

More information

LECTURE 8-9: THE BAKER-CAMPBELL-HAUSDORFF FORMULA

LECTURE 8-9: THE BAKER-CAMPBELL-HAUSDORFF FORMULA LECTURE 8-9: THE BAKER-CAMPBELL-HAUSDORFF FORMULA As we have seen, 1. Taylor s expanson on Le group, Y ] a(y ). So f G s an abelan group, then c(g) : G G s the entty ap for all g G. As a consequence, a()

More information

The Second Eigenvalue of Planar Graphs

The Second Eigenvalue of Planar Graphs Spectral Graph Theory Lecture 20 The Second Egenvalue of Planar Graphs Danel A. Spelman November 11, 2015 Dsclamer These notes are not necessarly an accurate representaton of what happened n class. The

More information

Solutions to exam in SF1811 Optimization, Jan 14, 2015

Solutions to exam in SF1811 Optimization, Jan 14, 2015 Solutons to exam n SF8 Optmzaton, Jan 4, 25 3 3 O------O -4 \ / \ / The network: \/ where all lnks go from left to rght. /\ / \ / \ 6 O------O -5 2 4.(a) Let x = ( x 3, x 4, x 23, x 24 ) T, where the varable

More information

Lecture 3: Probability Distributions

Lecture 3: Probability Distributions Lecture 3: Probablty Dstrbutons Random Varables Let us begn by defnng a sample space as a set of outcomes from an experment. We denote ths by S. A random varable s a functon whch maps outcomes nto the

More information

A note on almost sure behavior of randomly weighted sums of φ-mixing random variables with φ-mixing weights

A note on almost sure behavior of randomly weighted sums of φ-mixing random variables with φ-mixing weights ACTA ET COMMENTATIONES UNIVERSITATIS TARTUENSIS DE MATHEMATICA Volume 7, Number 2, December 203 Avalable onlne at http://acutm.math.ut.ee A note on almost sure behavor of randomly weghted sums of φ-mxng

More information

CALCULUS CLASSROOM CAPSULES

CALCULUS CLASSROOM CAPSULES CALCULUS CLASSROOM CAPSULES SESSION S86 Dr. Sham Alfred Rartan Valley Communty College salfred@rartanval.edu 38th AMATYC Annual Conference Jacksonvlle, Florda November 8-, 202 2 Calculus Classroom Capsules

More information

n ). This is tight for all admissible values of t, k and n. k t + + n t

n ). This is tight for all admissible values of t, k and n. k t + + n t MAXIMIZING THE NUMBER OF NONNEGATIVE SUBSETS NOGA ALON, HAROUT AYDINIAN, AND HAO HUANG Abstract. Gven a set of n real numbers, f the sum of elements of every subset of sze larger than k s negatve, what

More information

Case A. P k = Ni ( 2L i k 1 ) + (# big cells) 10d 2 P k.

Case A. P k = Ni ( 2L i k 1 ) + (# big cells) 10d 2 P k. THE CELLULAR METHOD In ths lecture, we ntroduce the cellular method as an approach to ncdence geometry theorems lke the Szemeréd-Trotter theorem. The method was ntroduced n the paper Combnatoral complexty

More information

Second main theorems and uniqueness problem of meromorphic mappings with moving hypersurfaces

Second main theorems and uniqueness problem of meromorphic mappings with moving hypersurfaces Bull Math Soc Sc Math Roumane Tome 5705 No 3, 04, 79 300 Secon man theorems an unqueness problem of meromorphc mappngs wth movng hypersurfaces by S Duc Quang Abstract In ths artcle, we establsh some new

More information

Ballot Paths Avoiding Depth Zero Patterns

Ballot Paths Avoiding Depth Zero Patterns Ballot Paths Avodng Depth Zero Patterns Henrch Nederhausen and Shaun Sullvan Florda Atlantc Unversty, Boca Raton, Florda nederha@fauedu, ssull21@fauedu 1 Introducton In a paper by Sapounaks, Tasoulas,

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens THE CHINESE REMAINDER THEOREM KEITH CONRAD We should thank the Chnese for ther wonderful remander theorem. Glenn Stevens 1. Introducton The Chnese remander theorem says we can unquely solve any par of

More information

CONJUGACY IN THOMPSON S GROUP F. 1. Introduction

CONJUGACY IN THOMPSON S GROUP F. 1. Introduction CONJUGACY IN THOMPSON S GROUP F NICK GILL AND IAN SHORT Abstract. We complete the program begun by Brn and Squer of charactersng conjugacy n Thompson s group F usng the standard acton of F as a group of

More information

General viscosity iterative method for a sequence of quasi-nonexpansive mappings

General viscosity iterative method for a sequence of quasi-nonexpansive mappings Avalable onlne at www.tjnsa.com J. Nonlnear Sc. Appl. 9 (2016), 5672 5682 Research Artcle General vscosty teratve method for a sequence of quas-nonexpansve mappngs Cuje Zhang, Ynan Wang College of Scence,

More information

MAT 578 Functional Analysis

MAT 578 Functional Analysis MAT 578 Functonal Analyss John Qugg Fall 2008 Locally convex spaces revsed September 6, 2008 Ths secton establshes the fundamental propertes of locally convex spaces. Acknowledgment: although I wrote these

More information

8.1 Arc Length. What is the length of a curve? How can we approximate it? We could do it following the pattern we ve used before

8.1 Arc Length. What is the length of a curve? How can we approximate it? We could do it following the pattern we ve used before .1 Arc Length hat s the length of a curve? How can we approxmate t? e could do t followng the pattern we ve used before Use a sequence of ncreasngly short segments to approxmate the curve: As the segments

More information

Perron Vectors of an Irreducible Nonnegative Interval Matrix

Perron Vectors of an Irreducible Nonnegative Interval Matrix Perron Vectors of an Irreducble Nonnegatve Interval Matrx Jr Rohn August 4 2005 Abstract As s well known an rreducble nonnegatve matrx possesses a unquely determned Perron vector. As the man result of

More information

Perfect Competition and the Nash Bargaining Solution

Perfect Competition and the Nash Bargaining Solution Perfect Competton and the Nash Barganng Soluton Renhard John Department of Economcs Unversty of Bonn Adenauerallee 24-42 53113 Bonn, Germany emal: rohn@un-bonn.de May 2005 Abstract For a lnear exchange

More information

Randić Energy and Randić Estrada Index of a Graph

Randić Energy and Randić Estrada Index of a Graph EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 5, No., 202, 88-96 ISSN 307-5543 www.ejpam.com SPECIAL ISSUE FOR THE INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND ALGEBRA 29 JUNE -02JULY 20, ISTANBUL

More information

European Journal of Combinatorics

European Journal of Combinatorics European Journal of Combnatorcs 0 (009) 480 489 Contents lsts avalable at ScenceDrect European Journal of Combnatorcs journal homepage: www.elsever.com/locate/ejc Tlngs n Lee metrc P. Horak 1 Unversty

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

( 1) i [ d i ]. The claim is that this defines a chain complex. The signs have been inserted into the definition to make this work out.

( 1) i [ d i ]. The claim is that this defines a chain complex. The signs have been inserted into the definition to make this work out. Mon, Apr. 2 We wsh to specfy a homomorphsm @ n : C n ()! C n (). Snce C n () s a free abelan group, the homomorphsm @ n s completely specfed by ts value on each generator, namely each n-smplex. There are

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

Journal of Mathematical Analysis and Applications

Journal of Mathematical Analysis and Applications J Math Anal Appl 388 0) 78 85 Contents lsts avalable at ScVerse ScenceDrect Journal of Mathematcal Analyss an Applcatons wwwelsevercom/locate/jmaa Multvarate nequaltes of Chernoff type for classcal orthogonal

More information

Eigenvalues of Random Graphs

Eigenvalues of Random Graphs Spectral Graph Theory Lecture 2 Egenvalues of Random Graphs Danel A. Spelman November 4, 202 2. Introducton In ths lecture, we consder a random graph on n vertces n whch each edge s chosen to be n the

More information

arxiv:math.nt/ v1 16 Feb 2005

arxiv:math.nt/ v1 16 Feb 2005 A NOTE ON q-bernoulli NUMBERS AND POLYNOMIALS arv:math.nt/0502333 v1 16 Feb 2005 Taekyun Km Insttute of Scence Eucaton, Kongju Natonal Unversty, Kongju 314-701, S. Korea Abstract. By usng q-ntegraton,

More information

Complex Numbers Alpha, Round 1 Test #123

Complex Numbers Alpha, Round 1 Test #123 Complex Numbers Alpha, Round Test #3. Wrte your 6-dgt ID# n the I.D. NUMBER grd, left-justfed, and bubble. Check that each column has only one number darkened.. In the EXAM NO. grd, wrte the 3-dgt Test

More information

On the Operation A in Analysis Situs. by Kazimierz Kuratowski

On the Operation A in Analysis Situs. by Kazimierz Kuratowski v1.3 10/17 On the Operaton A n Analyss Stus by Kazmerz Kuratowsk Author s note. Ths paper s the frst part slghtly modfed of my thess presented May 12, 1920 at the Unversty of Warsaw for the degree of Doctor

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

Problem Solving in Math (Math 43900) Fall 2013

Problem Solving in Math (Math 43900) Fall 2013 Problem Solvng n Math (Math 43900) Fall 2013 Week four (September 17) solutons Instructor: Davd Galvn 1. Let a and b be two nteger for whch a b s dvsble by 3. Prove that a 3 b 3 s dvsble by 9. Soluton:

More information

2. High dimensional data

2. High dimensional data /8/00. Hgh mensons. Hgh mensonal ata Conser representng a ocument by a vector each component of whch correspons to the number of occurrences of a partcular wor n the ocument. The Englsh language has on

More information

Geometry of Müntz Spaces

Geometry of Müntz Spaces WDS'12 Proceedngs of Contrbuted Papers, Part I, 31 35, 212. ISBN 978-8-7378-224-5 MATFYZPRESS Geometry of Müntz Spaces P. Petráček Charles Unversty, Faculty of Mathematcs and Physcs, Prague, Czech Republc.

More information

Economics 101. Lecture 4 - Equilibrium and Efficiency

Economics 101. Lecture 4 - Equilibrium and Efficiency Economcs 0 Lecture 4 - Equlbrum and Effcency Intro As dscussed n the prevous lecture, we wll now move from an envronment where we looed at consumers mang decsons n solaton to analyzng economes full of

More information

arxiv: v1 [math.nt] 8 Nov 2018

arxiv: v1 [math.nt] 8 Nov 2018 ON THE ERDŐS COVERING PROBLEM: THE DENSITY OF THE UNCOVERED SET PAUL BALISTER, BÉLA BOLLOBÁS, ROBERT MORRIS, JULIAN SAHASRABUDHE, AND MARIUS TIBA arxv:8.03547v math.nt] 8 Nov 208 Abstract. Snce ther ntroucton

More information

Differential Polynomials

Differential Polynomials JASS 07 - Polynomals: Ther Power and How to Use Them Dfferental Polynomals Stephan Rtscher March 18, 2007 Abstract Ths artcle gves an bref ntroducton nto dfferental polynomals, deals and manfolds and ther

More information

a b a In case b 0, a being divisible by b is the same as to say that

a b a In case b 0, a being divisible by b is the same as to say that Secton 6.2 Dvsblty among the ntegers An nteger a ε s dvsble by b ε f there s an nteger c ε such that a = bc. Note that s dvsble by any nteger b, snce = b. On the other hand, a s dvsble by only f a = :

More information

The Noether theorem. Elisabet Edvardsson. Analytical mechanics - FYGB08 January, 2016

The Noether theorem. Elisabet Edvardsson. Analytical mechanics - FYGB08 January, 2016 The Noether theorem Elsabet Evarsson Analytcal mechancs - FYGB08 January, 2016 1 1 Introucton The Noether theorem concerns the connecton between a certan kn of symmetres an conservaton laws n physcs. It

More information