Generalized Eulerian Sums

Size: px
Start display at page:

Download "Generalized Eulerian Sums"

Transcription

1 Generalzed Eleran Sms Fan hng Ron Graham Dedcated to Adrano Garsa on the occason of hs 84 th brthday Abstract In ths note, we dere a nmber of symmetrcal sms nolng Eleran nmbers and some of ther generalzatons These extend earler denttes of Don Knth and the athors, and also nclde seeral -nomal sms nspred by recent wor of Shareshan and Wachs on the jont dstrbton of aros permtaton statstcs, sch as the nmber of excedances, the major ndex and the nmber of fxed ponts of a permtaton We also prodce symmetrcal sms nolng restrcted Eleran nmbers whch cont permtatons π on {1, 2,, n} wth a gen nmber of descents and whch, n addton, hae the ale of π 1 (n specfed 1 Introdcton The classcal Eleran nmbers, whch we wll denote by n, occr n a arety of contexts n combnatorcs, nmber theory and compter scence (see [4] These nmbers were ntrodced by Eler [3] n 1736 and hae many nterestng propertes We lst some small ales n Table n Some Eleran nmbers n Table 1 In partclar, n enmerates the nmber of permtatons π on [n] : {1, 2,, n} whch hae descents (e, n1 wth π( > π(+1 as well as the nmber Unersty of alforna, San Dego 1

2 of permtatons π on [n] whch hae excedances (e, < n wth π( > Eleran nmbers satsfy the reflecton property n n, n > 0, (1 n 1 and the recrrence n n 1 n 1 ( (n 1 They also hae the explct representaton E n (t n ( n + 1 (1 ( + 1 n 0 and hae the followng generatng fncton (see [4]: n E(t, x t, n > 0, (2 (1 tex e tx te x 1 + n>0, 0 n t xn n! 1 + E n (t xn n! (3 n>0 Eleran nmbers grow rapdly n sze wth ncreasng n, and one doesn t expect as many combnatoral denttes to exst for them compared wth other seences sch as bnomal coeffcents or Strlng nmbers Neertheless, t was shown n [1] that the followng symmetrcal dentty holds: ( ( a + b a + b 0 a 1 0 b 1 for a, b > 0 (where nless stated otherwse, we se the conenton that In Secton 2, we proe seeral natral generalzatons of ths dentty In Secton 3, we consder a arant of the sal Eleran nmbers n whch we cont the nmber of permtatons π on [n] hang a gen nmber of descents wth the addtonal constrant that π(n 1 s specfed In Sectons 4 and 5, we deal wth -coeffcents arsng n the jont dstrbton of seeral permtaton statstcs stded by Shareshan and Wachs [7, 8] Fnally, n Secton 7, we close wth a nmber of open problems 2 An alternatng Eleran sm dentty Theorem 1 ( a + b (1 a for a, b > 0 0 ( a + b (1 0 b (4 2

3 Proof The generatng fncton for or modfed Eleran nmbers (e, wth s obtaned by sbtractng 1 from (1te x n (3 Ths ges Ths, ( 1 e x e x e tx e tx te x t e tx n, n t xn n! n, 0 e tx te x n t xn n! (5 ( 1 e x t ( e x e tx e tx e tx te x 1 e tx 1 e x Expressng the exponentals as sms mples (1 x! t (1 t x n t x n! n! 0 0 n, n t (1 x n+!n!,n, n (1,n, Shftng the ndces of smmaton yelds (1 n tn x n (1 n xn n! n!, t ++1 x n+!n! (1 n (tn 1x n n! ( n n t (1 x n n!,n, ( n n t (1 x n 1 n!,n, (1 n (tn 1x n n! (6 Identfyng the coeffcents of x n ges ( n n (1 t n (1 1,, ( n t (1 n (t n 1 Assmng 0, n and dentfyng the coeffcents of t ges ( n n (1 ( n n (

4 Fnally, sng the reflecton propertes of the Eleran nmbers n (1, replacng by n, and sng the reflecton propertes of the bnomal coeffcents, we obtan ( n (1 (1 ( n, n for 0 < < n Therefore, f we set n a + b, a, then we hae ( a + b (1 ( a + b (1 a b 0 0 (7 for a, b > 0 Ths proes the theorem Note that (7 can be consdered as a companon to (4 We can rewrte (4 n the form ( n n ( n n, (8 1 for 0 < < n As ponted ot n [1], ths s the frst n an nfnte seence of (ncreasngly complex sms of ths type The next two are: ( n n 2 ( n n 2 2 ( ( n n, for 1 < < n (9 1 ( n n 3 ( n n 3 3 ( ( n n n+1 1 ( ( n n n for 2 < < n (10 The companon sm (7 s also the frst of an nfnte seence of smlar sms, 4

5 the next few beng: ( n (1 2 n ( n (1 3 n ( n (1 2 n n + 1 ( ( n n, for 1 n (11 1 ( n (1 3 n n + 2 ( ( n n 2 n 2 n ( n ( n 2 for 1 n (12 The proofs of these follow the same lnes as that of (7 and are omtted 3 Generalzed Eleran denttes for restrcted descent polynomals In ths secton we consder a restrcted erson of Eleran nmbers We defne the restrcted Eleran nmber b(n,,, for 1 n, 0 < n, to be the nmber of π S n wth des(π and wth π( n Ths restrcton s smlar to one sed by the athors for nestgatng the jont statstcs of permtatons hang a gen nmber of descents and a gen bond on drop sze [2] (A permtaton π has a drop at f π( < and the drop sze s π( From the defnton of b(n,,, t follows that n b(n,,, 1 b(,,, b(n,, 0, f n < or n or < 0 The anttes b(n,, satsfy the followng reflecton property whch wll be needed later Lemma 1 For 1 < < n,, we hae b(n,, b(n,, n 1 (13 Proof The proof follows by consderng the bjecton whch maps π S n wth π( n to π S n wth π ( n defned by π (π( 1,, π(1, n, π(n,, π( + 1 5

6 We consder the followng descent polynomal B n, (t defned by: B n, (t 0 b(n,, t We wll need the generatng fncton for ths polynomal Lemma 2 The descent polynomal B n, (t has the followng generatng fncton: B (t, x n B n, (t xn1 (n 1! E x 1 (e tx te tx 1(t ( 1!(e tx te x (14 Proof We frst consder B n, (t for the case that < n Let S m,l denote the set of permtatons π S m whch hae l descents For a fxed ( 1-sbset of {1,, n}, there s a straghtforward bjecton from the set of permtatons π S n wth π( n and hang descents to the followng set: ( S1,j S n,j1 Ths, for < n, we hae 0 j< B,n (t b(n,, t ( n 1 1 n t t j1 t j2 1 By mltplyng both sdes by fxed, b(n,, t x n1 (n 1! n> j 1 j 1 j 2 xn1 (n1! and smmng oer all n >, we hae for t ( 1! E 1(t E n (tx n1 (n! n> tx1 E 1 (t E n (tx n ( 1! (n! n> ( tx1 E 1 (t (1 te x ( 1! e tx te x 1 ( e x e tx tx1 E 1 (t ( 1! j 2 e tx te x 6

7 Addng to ths sm a term for the case n, we obtan B (t, x b(n,, t x n1 (n 1! n ( tx1 E 1 (t e x e tx ( 1! e tx te x ( tx1 E 1 (t e x e tx ( 1! e tx te x x1 E 1 (t ( 1! x1 E 1 (t ( 1! ( t(e x e tx e tx te x + 1 ( e tx te tx e tx te x + + x1 E 1 (t ( 1! x 1 b(,, t ( 1! Now we are ready to proe the followng generalzed ealty for or restrcted descent polynomals Theorem 2 For > 1, r, s > 0, the restrcted Eleran nmbers b(n,, satsfy ( r + s + 1 b(,, r ( r + s + 1 b(,, s ( Proof We start wth the generatng fncton gen n Lemma 2 By crossmltplyng, we hae b(n,, t x n1 (e tx te x x1 E 1 (t (e tx te tx (n 1! ( 1! n, Expandng the exponental fnctons, we hae n,,j b(n,, t+j x n+j1 j!(n 1! n,,j b(n,, t+1 x n+j1 j!(n 1! x1 E 1 (t ( 1! (1 tt n x n n! Identfyng the coeffcent of x n1 ges t +j b(n j,, j!(n j 1!,j,j E 1(t ( 1! t +1 b(n j,, j!(n j 1! ( t n (n! tn+1 (n! 7

8 We frther dentfy the coeffcents of t l to get b(n l +,, (l!(n l + 1! j b(n j,, l 1 j!(n j 1! ( 1 l + n ( 1 n l 2 1 ( 1!(n! 1 ( 1!(n! 1 l n n l 1 Mltplyng both sdes by (n 1!, we obtan ( n 1 b(n l +,, ( n 1 b(n j,, l 1 l j j ( ( n n l 2 n l 1 (16 We wll deal wth each term n (16 separately For the frst sm on the left sde of (16, we frst change arables by settng l and then n as follows: ( n 1 b(n l +,, ( n 1 b(n,, l l ( n 1 b(,, l n + n Now, sng the reflecton property n Lemma 1, we hae ( n 1 b(,, l n + n ( ( n 1 1 n 1 b(,, n l l n + 1 ( ( n 1 1 n 1 b(,, n l n l 2 1 ( ( r + s n 1 b(,, r + 1 r 1 1 (17 by settng l s + 1 and n r + s + 2 8

9 The second sm of the left sde of (16 can be treated as follows: ( n 1 b(n j,, l 1 ( n 1 b(,, l 1 j n j ( n 1 b(,, l 1 1 ( r + s + 1 b(,, s (18 1 The rght sde of (16 ges ( ( 1 1 n 1 n l 2 n l 1 1 ( ( 1 1 n 1 r 1 r 1 ( ( 1 n 1 n 1 b(,, r (19 r Sbstttng (17, (18 and (19 nto (16, we hae ( r + s + 1 b(,, r ( r + s + 1 b(,, s 1 1 as clamed The proof of Theorem 2 s complete The only case that s left ot n Theorem 2 s the case of 1 Howeer, for ths case, b(n, 1, n1 1, and ths case redces to the orgnal Eleran ealty (4 4 Some -nomal generalzatons Recently, Shareshan and Wachs [7, 8] fond an elegant expresson for the jont dstrbton of the excedance and the major ndex of a permtaton n S n Frst, we ge some standard defntons (see [8] For π S n, defne Also set EX(π { : π( > }, exc(π EX(π, DES(π { : π( > π( + 1}, des(π DES(π, maj(π DES(π A maj,exc n (, t maj(π t exc(π π S n a n (, j t j (20,j 0 9

10 We wll defne the polynomal n (j n (j( by n (j : a n (, j j (21 so that we can wrte An maj,exc (, t j n (j(t j As sal, defne n n1, n! [n] [n 1] [1], a [a]! b [b]![a b]! Theorem 3 ([7, 8] An maj,exc (, t zn [n]! (1 t exp (z exp (tz t exp (z (22 where An maj,exc (, 0 1 and exp (z z n [n]! From ths reslt, we wll show how to dere -nomal generalzatons of (4 and (7 Theorem 4 For a, b > 0, the polynomals defned n (21 and (20 satsfy: a + b (a 1 a + b (b 1 (23 Note that (21 generalzes (4 snce n (j 1 0 a n (, j n j Proof We wll se the conenton that A maj,exc 0 (, t 0 (rather than 1 In ths case, sbtractng 1 from the expresson on (22, we hae exp (z exp (tz exp (tz t exp (z n,j 0 zn n (j(t j [n]! (24 10

11 Mltplyng by exp (tgz t exp (z and expandng, we obtan (tz t z n (j(t j zn []! []! [n]! z n [n]! 0 0 n,j 0 Ths,,n,j 0 n (j(t j+ z n+ []![n]!,n,j 0 Shftng the smmaton ndex n ges n (j(t j+ n z n [n],n,j 0 n (j(t j+1 z n+ []![n]!,n,j 0 (tz n [n]! (25 (1 (t n z n [n]! n (j(t j+1 [ n Identfyng the coeffcents of z n ges n (j(t j+ n n (j(t j+1 n,j 0,j 0 Now, shftng the smmaton ndex j, we hae n (j (t j n n (j 1(t j n,j 0,j 0 Identfyng coeffcents of t j then ges [ n n (j ] [ n n (j 1 ] ] z n [n] (1 (t n z n (26 [n]! 1 (t n 1 (t n 1 f j 0, 1 f j n, 0 f 0 < j < n It was shown n [8] that the n (j enjoy the symmetry property: Hence, we can rewrte (27 as [ n n (n 1 j + ] [ n (n 1 j ] (27 n (r n (n 1 r (28 [ n n (j 1 ] [ n (j 1 ] 1 f j 0, 1 f j n, 0 f 0 < j < n 11

12 Settng n a + b and j b yelds a + b (a 1 a + b (b 1, for a, b > 0 Ths proes the theorem The same technes can be sed to proe the followng companon sm for (22 Theorem 5 For a, b > 0, (1 a + b (a+b 2 (a Ths s a -nomal generalzaton of (7 5 Frther -nomal generalzatons (1 a + b (a+b 2 (b (29 In [7, 8], Shareshan and Wachs proe the followng more general erson of (22: Theorem 6 ([7, 8] A maj,exc,fx n (, t, r zn [n]! (1 t exp (rz exp (tz t exp (z (30 where A maj,exc,fx n (, 0, 0 1 and fx(π denotes the nmber of fxed ponts of π S n, e, the nmber of sch that π( Let s wrte (1 t exp (rz exp (zt t exp (z n,,j, and defne the polynomals n (j, n (j, ( by zn a n (, j, t j r [n]! n (j, a n (, j, j Theorem 7 For a, b, 0, the polynomals ( as defned n (31 satsfy a + b (a, a + b (b, (31 Proof ross-mltplyng, sbstttng and expandng the exponentals n (30, we obtan (tz n (j, (t j r zn []! [n]! t z n (, j, (t j r zn []! [n]! 0 n,j, 0 n,j, (rz n [n]! (1 t 12

13 Now, shftng ndces and dentfyng the coeffcents of z n (as before yelds n (j, (t j r n n (j 1, (t j r n (1 tr n j,, j,, Hence, for < n, we can dentfy the coeffcents of r and t and obtan n n (j, n n (j 1, (32 We next note the followng nce symmetry property of the n (j, Fact for n, j, 0 n (j, n (n j, (33 Proof Frst, a straghtforward comptaton from (30 erfes that A maj,exc,fx n (, t, r zn [n]! ( A maj,exc,fx 1 n, 2 t, r (tz n t [n]! (34 Ths mples a n (, j, t j r zn [n]! a n (, j, 2j+n t j+n r zn [n]! (35 n,,j, n,,j, Identfyng coeffcents of z n and r then ges a n (, j, t j a n (, j, 2j+n t j+n (36,j,j Shftng the ndces of smmaton n the second sm by 2j + n and j j + n yelds a n (, j, t j a n ( 2j + n, j + n, t j (37,j,j Now, dentfyng the coeffcents of and t j ges s a n (, j, a n (n + 2j, n j, (38 for, j,, n 0 Fnally, smmng oer ges a n (, j, j a n (n + 2j, n j, j a n (n + 2j, n j, (n+2j(nj a n (, n j, n+j+ 13

14 e, n (j, n (n j,, and the Fact s proed Now, contnng the proof of (31, we wll apply eaton (33 to (32 Ths, [ n n (j, ] [ n n (n j, ] [ n (j 1, ] Fnally, lettng n a + b + + 1, j b + 1, we get a + b (a, a + b (b, as rered Obsere that settng 1 n Theorem 6 ges s symmetrcal sms for the anttes c n (j, n (j, 1, whch cont the nmber of π n S n wth exc(π j and fx(π These sms can be wrtten as follows: Theorem 8 For a, b, > 0, the c defned aboe satsfy ( a + b c (a, ( a + b c (b, (39 6 oncldng remars In general, we wold le to fnd symmetrcal denttes smlar n form to (4, (15, or (23 whch depend on coeffcents arsng n the enmeraton of aros jont statstcs on permtatons For example, we cold try to proe denttes of the form a + b P (, a 1 a + b P (, b 1 (40 for some approprate polynomals P (, j( A natral place to loo s at the polynomals S(n, j s(n,, j where s(n,, j s defned to be the nmber of π S n sch that n(π and des(π j Unfortnately, we ddn t fnd any araton of (40 whch was ald We fnd ths to be slghtly srprsng snce a classc reslt of Stanley [6], namely, n A n(π,des(π (, t zn [n]! 1 t exp (tz t n zn S(n, jt j [n]!, wold seem to be n the approprate form for or analyss Howeer, we sspect that sch symmetrcal sms do exst 14

15 In another drecton, the precedng technes can be appled to a arety of other expressons whch hae an approprate generatng fncton For example, for π S n, we can defne D n (, t : maj(π t des(π d(n,, j t j, π S n,j Dn(, t : d(n,,, j t j π S n,π(n maj(π t des(π,j We can then apply the precedng argments to obtan sms smlar to (15 and (29 for those coeffcents It wold be nterestng to fnd bjecte proofs for some of these denttes sch as (7, (9, (10, (11, (15, (23 or (31 A beatfl (and non-tral bjecte proof of (4 was dscoered by Don Knth [1] bt no one has yet fond a correspondng bjecte proof for ts companon (7 7 Acnowledgements The athors wsh to than Adrano Garsa, Jeff Remmel and an anonymos referee for ther helpfl comments whle we were preparng ths note References [1] F hng, R Graham and D Knth, A symmetrcal Eleran dentty, Jornal of ombnatorcs, 1 (2010, [2] F hng and R Graham, Restrcted Eleran nmbers and descent polynomals, preprnt [3] L Eler, Methods nersals seres smmand lters promota, ommentar academae scentarm mperals Petropoltanae, 8 (1736, Reprnted n hs Pera Omna, seres 1, olme 14, [4] R Graham, D Knth and O Patashn, oncrete Mathematcs, A Fondaton for ompter Scence, Addson-Wesley, Boston, 1994, x, 657p [5] Jeff Remmel, (personal commncaton [6] R P Stanley, Bnomal posets, Möbs nerson, and permtaton enmeraton, J ombnatoral Theory Ser A 20 (1976, [7] J Shareshan and M Wachs, -Eleran polynomals, excedance nmber and major ndex, Electronc Res Annonc, Amer Math Soc 13 (2007, [8] J Shareshan and M Wachs, Ecleran assymmetrc fnctons, Ad n Math, 225 (2010,

Complex Numbers Practice 0708 & SP 1. The complex number z is defined by

Complex Numbers Practice 0708 & SP 1. The complex number z is defined by IB Math Hgh Leel: Complex Nmbers Practce 0708 & SP Complex Nmbers Practce 0708 & SP. The complex nmber z s defned by π π π π z = sn sn. 6 6 Ale - Desert Academy (a) Express z n the form re, where r and

More information

Inversion-descent polynomials for restricted permutations

Inversion-descent polynomials for restricted permutations Inverson-descent polynomals for restrcted permutatons Fan Chung Ron Graham August 25, 2012 Abstract We derve generatng functons for a varety of dstrbutons of jont permutaton statstcs all of whch nvolve

More information

AE/ME 339. K. M. Isaac. 8/31/2004 topic4: Implicit method, Stability, ADI method. Computational Fluid Dynamics (AE/ME 339) MAEEM Dept.

AE/ME 339. K. M. Isaac. 8/31/2004 topic4: Implicit method, Stability, ADI method. Computational Fluid Dynamics (AE/ME 339) MAEEM Dept. AE/ME 339 Comptatonal Fld Dynamcs (CFD) Comptatonal Fld Dynamcs (AE/ME 339) Implct form of dfference eqaton In the prevos explct method, the solton at tme level n,,n, depended only on the known vales of,

More information

An (almost) unbiased estimator for the S-Gini index

An (almost) unbiased estimator for the S-Gini index An (almost unbased estmator for the S-Gn ndex Thomas Demuynck February 25, 2009 Abstract Ths note provdes an unbased estmator for the absolute S-Gn and an almost unbased estmator for the relatve S-Gn for

More information

Combinatorial Identities for Incomplete Tribonacci Polynomials

Combinatorial Identities for Incomplete Tribonacci Polynomials Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015, pp. 40 49 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM Combnatoral Identtes for Incomplete

More information

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0 Bezer curves Mchael S. Floater August 25, 211 These notes provde an ntroducton to Bezer curves. 1 Bernsten polynomals Recall that a real polynomal of a real varable x R, wth degree n, s a functon of the

More information

h-analogue of Fibonacci Numbers

h-analogue of Fibonacci Numbers h-analogue of Fbonacc Numbers arxv:090.0038v [math-ph 30 Sep 009 H.B. Benaoum Prnce Mohammad Unversty, Al-Khobar 395, Saud Araba Abstract In ths paper, we ntroduce the h-analogue of Fbonacc numbers for

More information

Hyper-Sums of Powers of Integers and the Akiyama-Tanigawa Matrix

Hyper-Sums of Powers of Integers and the Akiyama-Tanigawa Matrix 6 Journal of Integer Sequences, Vol 8 (00), Artcle 0 Hyper-Sums of Powers of Integers and the Ayama-Tangawa Matrx Yoshnar Inaba Toba Senor Hgh School Nshujo, Mnam-u Kyoto 60-89 Japan nava@yoto-benejp Abstract

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

arxiv:math/ v2 [math.co] 30 May 2007

arxiv:math/ v2 [math.co] 30 May 2007 COUNTING DESCENTS, RISES, AND LEVELS, WITH PRESCRIBED FIRST ELEMENT, IN WORDS arxv:math/070032v2 [mathco] 30 May 2007 Sergey Ktaev Insttute of Mathematcs, Reykjavk Unversty, IS-03 Reykjavk, Iceland sergey@rus

More information

Beyond Zudilin s Conjectured q-analog of Schmidt s problem

Beyond Zudilin s Conjectured q-analog of Schmidt s problem Beyond Zudln s Conectured q-analog of Schmdt s problem Thotsaporn Ae Thanatpanonda thotsaporn@gmalcom Mathematcs Subect Classfcaton: 11B65 33B99 Abstract Usng the methodology of (rgorous expermental mathematcs

More information

between standard Gibbs free energies of formation for products and reactants, ΔG! R = ν i ΔG f,i, we

between standard Gibbs free energies of formation for products and reactants, ΔG! R = ν i ΔG f,i, we hermodynamcs, Statstcal hermodynamcs, and Knetcs 4 th Edton,. Engel & P. ed Ch. 6 Part Answers to Selected Problems Q6.. Q6.4. If ξ =0. mole at equlbrum, the reacton s not ery far along. hus, there would

More information

The Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices

The Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices Internatonal Mathematcal Forum, Vol 11, 2016, no 11, 513-520 HIKARI Ltd, wwwm-hkarcom http://dxdoorg/1012988/mf20166442 The Jacobsthal and Jacobsthal-Lucas Numbers va Square Roots of Matrces Saadet Arslan

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

Descent polynomials for permutations with bounded drop size

Descent polynomials for permutations with bounded drop size FPSAC 2010, San Francsco, USA DMTCS proc. AN, 2010, 115 126 Descent polynomals for permutatons wth bounded drop sze Fan Chung 1, Anders Claesson 2, Mark Dukes 3 and Ronald Graham 1 1 Unversty of Calforna

More information

7. Products and matrix elements

7. Products and matrix elements 7. Products and matrx elements 1 7. Products and matrx elements Based on the propertes of group representatons, a number of useful results can be derved. Consder a vector space V wth an nner product ψ

More information

Binomial transforms of the modified k-fibonacci-like sequence

Binomial transforms of the modified k-fibonacci-like sequence Internatonal Journal of Mathematcs and Computer Scence, 14(2019, no. 1, 47 59 M CS Bnomal transforms of the modfed k-fbonacc-lke sequence Youngwoo Kwon Department of mathematcs Korea Unversty Seoul, Republc

More information

DESCENT POLYNOMIALS FOR PERMUTATIONS WITH BOUNDED DROP SIZE

DESCENT POLYNOMIALS FOR PERMUTATIONS WITH BOUNDED DROP SIZE DESCENT POLYNOMIALS FOR PERMUTATIONS WITH BOUNDED DROP SIZE FAN CHUNG, ANDERS CLAESSON, MARK DUKES, AND RONALD GRAHAM Abstract. Motvated by ugglng sequences and bubble sort, we examne permutatons on the

More information

An efficient algorithm for multivariate Maclaurin Newton transformation

An efficient algorithm for multivariate Maclaurin Newton transformation Annales UMCS Informatca AI VIII, 2 2008) 5 14 DOI: 10.2478/v10065-008-0020-6 An effcent algorthm for multvarate Maclaurn Newton transformaton Joanna Kapusta Insttute of Mathematcs and Computer Scence,

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

= z 20 z n. (k 20) + 4 z k = 4

= z 20 z n. (k 20) + 4 z k = 4 Problem Set #7 solutons 7.2.. (a Fnd the coeffcent of z k n (z + z 5 + z 6 + z 7 + 5, k 20. We use the known seres expanson ( n+l ( z l l z n below: (z + z 5 + z 6 + z 7 + 5 (z 5 ( + z + z 2 + z + 5 5

More information

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1 C/CS/Phy9 Problem Set 3 Solutons Out: Oct, 8 Suppose you have two qubts n some arbtrary entangled state ψ You apply the teleportaton protocol to each of the qubts separately What s the resultng state obtaned

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

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

Evaluation of a family of binomial determinants

Evaluation of a family of binomial determinants Electronc Journal of Lnear Algebra Volume 30 Volume 30 2015 Artcle 22 2015 Evaluaton of a famly of bnomal determnants Charles Helou Pennsylvana State Unversty, cxh22@psuedu James A Sellers Pennsylvana

More information

Bézier curves. Michael S. Floater. September 10, These notes provide an introduction to Bézier curves. i=0

Bézier curves. Michael S. Floater. September 10, These notes provide an introduction to Bézier curves. i=0 Bézer curves Mchael S. Floater September 1, 215 These notes provde an ntroducton to Bézer curves. 1 Bernsten polynomals Recall that a real polynomal of a real varable x R, wth degree n, s a functon of

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

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

C PLANE ELASTICITY PROBLEM FORMULATIONS

C PLANE ELASTICITY PROBLEM FORMULATIONS C M.. Tamn, CSMLab, UTM Corse Content: A ITRODUCTIO AD OVERVIEW mercal method and Compter-Aded Engneerng; Phscal problems; Mathematcal models; Fnte element method. B REVIEW OF -D FORMULATIOS Elements and

More information

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS Journal of Mathematcal Scences: Advances and Applcatons Volume 25, 2014, Pages 1-12 A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS JIA JI, WEN ZHANG and XIAOFEI QI Department of Mathematcs

More information

Digital Signal Processing

Digital Signal Processing Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over

More information

Determinants Containing Powers of Generalized Fibonacci Numbers

Determinants Containing Powers of Generalized Fibonacci Numbers 1 2 3 47 6 23 11 Journal of Integer Sequences, Vol 19 (2016), Artcle 1671 Determnants Contanng Powers of Generalzed Fbonacc Numbers Aram Tangboonduangjt and Thotsaporn Thanatpanonda Mahdol Unversty Internatonal

More information

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

Self-complementing permutations of k-uniform hypergraphs

Self-complementing permutations of k-uniform hypergraphs Dscrete Mathematcs Theoretcal Computer Scence DMTCS vol. 11:1, 2009, 117 124 Self-complementng permutatons of k-unform hypergraphs Artur Szymańsk A. Paweł Wojda Faculty of Appled Mathematcs, AGH Unversty

More information

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family IOSR Journal of Mathematcs IOSR-JM) ISSN: 2278-5728. Volume 3, Issue 3 Sep-Oct. 202), PP 44-48 www.osrjournals.org Usng T.O.M to Estmate Parameter of dstrbutons that have not Sngle Exponental Famly Jubran

More information

Zhi-Wei Sun (Nanjing)

Zhi-Wei Sun (Nanjing) Acta Arth. 1262007, no. 4, 387 398. COMBINATORIAL CONGRUENCES AND STIRLING NUMBERS Zh-We Sun Nanng Abstract. In ths paper we obtan some sophstcated combnatoral congruences nvolvng bnomal coeffcents and

More information

A combinatorial proof of multiple angle formulas involving Fibonacci and Lucas numbers

A combinatorial proof of multiple angle formulas involving Fibonacci and Lucas numbers Notes on Number Theory and Dscrete Mathematcs ISSN 1310 5132 Vol. 20, 2014, No. 5, 35 39 A combnatoral proof of multple angle formulas nvolvng Fbonacc and Lucas numbers Fernando Córes 1 and Dego Marques

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

GELFAND-TSETLIN BASIS FOR THE REPRESENTATIONS OF gl n

GELFAND-TSETLIN BASIS FOR THE REPRESENTATIONS OF gl n GELFAND-TSETLIN BASIS FOR THE REPRESENTATIONS OF gl n KANG LU FINITE DIMENSIONAL REPRESENTATIONS OF gl n Let e j,, j =,, n denote the standard bass of the general lnear Le algebra gl n over the feld of

More information

arxiv: v1 [math.co] 12 Sep 2014

arxiv: v1 [math.co] 12 Sep 2014 arxv:1409.3707v1 [math.co] 12 Sep 2014 On the bnomal sums of Horadam sequence Nazmye Ylmaz and Necat Taskara Department of Mathematcs, Scence Faculty, Selcuk Unversty, 42075, Campus, Konya, Turkey March

More information

Math 217 Fall 2013 Homework 2 Solutions

Math 217 Fall 2013 Homework 2 Solutions Math 17 Fall 013 Homework Solutons Due Thursday Sept. 6, 013 5pm Ths homework conssts of 6 problems of 5 ponts each. The total s 30. You need to fully justfy your answer prove that your functon ndeed has

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

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

DONALD M. DAVIS. 1. Main result

DONALD M. DAVIS. 1. Main result v 1 -PERIODIC 2-EXPONENTS OF SU(2 e ) AND SU(2 e + 1) DONALD M. DAVIS Abstract. We determne precsely the largest v 1 -perodc homotopy groups of SU(2 e ) and SU(2 e +1). Ths gves new results about the largest

More information

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

Exact Solutions for Nonlinear D-S Equation by Two Known Sub-ODE Methods

Exact Solutions for Nonlinear D-S Equation by Two Known Sub-ODE Methods Internatonal Conference on Compter Technology and Scence (ICCTS ) IPCSIT vol. 47 () () IACSIT Press, Sngapore DOI:.7763/IPCSIT..V47.64 Exact Soltons for Nonlnear D-S Eqaton by Two Known Sb-ODE Methods

More information

MA 323 Geometric Modelling Course Notes: Day 13 Bezier Curves & Bernstein Polynomials

MA 323 Geometric Modelling Course Notes: Day 13 Bezier Curves & Bernstein Polynomials MA 323 Geometrc Modellng Course Notes: Day 13 Bezer Curves & Bernsten Polynomals Davd L. Fnn Over the past few days, we have looked at de Casteljau s algorthm for generatng a polynomal curve, and we have

More information

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence Remarks on the Propertes of a Quas-Fbonacc-lke Polynomal Sequence Brce Merwne LIU Brooklyn Ilan Wenschelbaum Wesleyan Unversty Abstract Consder the Quas-Fbonacc-lke Polynomal Sequence gven by F 0 = 1,

More information

# c i. INFERENCE FOR CONTRASTS (Chapter 4) It's unbiased: Recall: A contrast is a linear combination of effects with coefficients summing to zero:

# c i. INFERENCE FOR CONTRASTS (Chapter 4) It's unbiased: Recall: A contrast is a linear combination of effects with coefficients summing to zero: 1 INFERENCE FOR CONTRASTS (Chapter 4 Recall: A contrast s a lnear combnaton of effects wth coeffcents summng to zero: " where " = 0. Specfc types of contrasts of nterest nclude: Dfferences n effects Dfferences

More information

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur Module Random Processes Lesson 6 Functons of Random Varables After readng ths lesson, ou wll learn about cdf of functon of a random varable. Formula for determnng the pdf of a random varable. Let, X be

More information

SUMMARY OF STOICHIOMETRIC RELATIONS AND MEASURE OF REACTIONS' PROGRESS AND COMPOSITION FOR MULTIPLE REACTIONS

SUMMARY OF STOICHIOMETRIC RELATIONS AND MEASURE OF REACTIONS' PROGRESS AND COMPOSITION FOR MULTIPLE REACTIONS UMMAY OF TOICHIOMETIC ELATION AND MEAUE OF EACTION' POGE AND COMPOITION FO MULTIPLE EACTION UPDATED 0/4/03 - AW APPENDIX A. In case of multple reactons t s mportant to fnd the number of ndependent reactons.

More information

Problem Do any of the following determine homomorphisms from GL n (C) to GL n (C)?

Problem Do any of the following determine homomorphisms from GL n (C) to GL n (C)? Homework 8 solutons. Problem 16.1. Whch of the followng defne homomomorphsms from C\{0} to C\{0}? Answer. a) f 1 : z z Yes, f 1 s a homomorphsm. We have that z s the complex conjugate of z. If z 1,z 2

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

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

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

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 705: Classical Mechanics. Calculus of Variations II 1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary

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

Assortment Optimization under MNL

Assortment Optimization under MNL Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.

More information

Maximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models

Maximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models ECO 452 -- OE 4: Probt and Logt Models ECO 452 -- OE 4 Maxmum Lkelhood Estmaton of Bnary Dependent Varables Models: Probt and Logt hs note demonstrates how to formulate bnary dependent varables models

More information

Centre for Efficiency and Productivity Analysis

Centre for Efficiency and Productivity Analysis Centre for Effcency and Prodctty Analyss Workng Paper Seres No. WP/7 Ttle On The Dstrbton of Estmated Techncal Effcency n Stochastc Fronter Models Athors We Sang Wang & Peter Schmdt Date: May, 7 School

More information

Two Enumerative Results on Cycles of Permutations 1

Two Enumerative Results on Cycles of Permutations 1 Two Enumeratve Results on Cycles of Permutatons Rchard P. Stanley Department of Mathematcs Massachusetts Insttute of Technology Cambrdge, MA 039, USA rstan@math.mt.edu In memory of Tom Brylawsk verson

More information

CHAPTER 14 GENERAL PERTURBATION THEORY

CHAPTER 14 GENERAL PERTURBATION THEORY CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves

More information

ESS 265 Spring Quarter 2005 Time Series Analysis: Error Analysis

ESS 265 Spring Quarter 2005 Time Series Analysis: Error Analysis ESS 65 Sprng Qarter 005 Tme Seres Analyss: Error Analyss Lectre 9 May 3, 005 Some omenclatre Systematc errors Reprodcbly errors that reslt from calbraton errors or bas on the part of the obserer. Sometmes

More information

ENUMERATING (2+2)-FREE POSETS BY THE NUMBER OF MINIMAL ELEMENTS AND OTHER STATISTICS

ENUMERATING (2+2)-FREE POSETS BY THE NUMBER OF MINIMAL ELEMENTS AND OTHER STATISTICS ENUMERATING 2+2)-FREE POSETS BY THE NUMBER OF MINIMAL ELEMENTS AND OTHER STATISTICS SERGEY KITAEV AND JEFFREY REMMEL Abstract. A poset s sad to be 2 + 2)-free f t does not contan an nduced subposet that

More information

Reading Assignment. Panel Data Cross-Sectional Time-Series Data. Chapter 16. Kennedy: Chapter 18. AREC-ECON 535 Lec H 1

Reading Assignment. Panel Data Cross-Sectional Time-Series Data. Chapter 16. Kennedy: Chapter 18. AREC-ECON 535 Lec H 1 Readng Assgnment Panel Data Cross-Sectonal me-seres Data Chapter 6 Kennedy: Chapter 8 AREC-ECO 535 Lec H Generally, a mxtre of cross-sectonal and tme seres data y t = β + β x t + β x t + + β k x kt + e

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

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have

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

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

1 Generating functions, continued

1 Generating functions, continued Generatng functons, contnued. Generatng functons and parttons We can make use of generatng functons to answer some questons a bt more restrctve than we ve done so far: Queston : Fnd a generatng functon

More information

arxiv: v1 [math.co] 4 May 2012

arxiv: v1 [math.co] 4 May 2012 DESCENT POLYNOMIALS FOR k BUBBLE-SORTABLE PERMUTATIONS OF TYPE B arxv:1205.1014v1 [math.co] 4 May 2012 MATTHEW HYATT Abstract. Motvated by the work of Chung, Claesson, Dukes, and Graham n [5], we defne

More information

A summation on Bernoulli numbers

A summation on Bernoulli numbers Journal of Number Theory 111 (005 37 391 www.elsever.com/locate/jnt A summaton on Bernoull numbers Kwang-Wu Chen Department of Mathematcs and Computer Scence Educaton, Tape Muncpal Teachers College, No.

More information

The binomial transforms of the generalized (s, t )-Jacobsthal matrix sequence

The binomial transforms of the generalized (s, t )-Jacobsthal matrix sequence Int. J. Adv. Appl. Math. and Mech. 6(3 (2019 14 20 (ISSN: 2347-2529 Journal homepage: www.jaamm.com IJAAMM Internatonal Journal of Advances n Appled Mathematcs and Mechancs The bnomal transforms of the

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

Learning Theory: Lecture Notes

Learning Theory: Lecture Notes Learnng Theory: Lecture Notes Lecturer: Kamalka Chaudhur Scrbe: Qush Wang October 27, 2012 1 The Agnostc PAC Model Recall that one of the constrants of the PAC model s that the data dstrbuton has to be

More information

Linear Algebra and its Applications

Linear Algebra and its Applications Lnear Algebra and ts Applcatons 4 (00) 5 56 Contents lsts avalable at ScenceDrect Lnear Algebra and ts Applcatons journal homepage: wwwelsevercom/locate/laa Notes on Hlbert and Cauchy matrces Mroslav Fedler

More information

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2 Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to

More information

763622S ADVANCED QUANTUM MECHANICS Solution Set 1 Spring c n a n. c n 2 = 1.

763622S ADVANCED QUANTUM MECHANICS Solution Set 1 Spring c n a n. c n 2 = 1. 7636S ADVANCED QUANTUM MECHANICS Soluton Set 1 Sprng 013 1 Warm-up Show that the egenvalues of a Hermtan operator  are real and that the egenkets correspondng to dfferent egenvalues are orthogonal (b)

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

Least squares cubic splines without B-splines S.K. Lucas

Least squares cubic splines without B-splines S.K. Lucas Least squares cubc splnes wthout B-splnes S.K. Lucas School of Mathematcs and Statstcs, Unversty of South Australa, Mawson Lakes SA 595 e-mal: stephen.lucas@unsa.edu.au Submtted to the Gazette of the Australan

More information

PHASED TILINGS AND GENERALIZED FIBONACCI IDENTITIES

PHASED TILINGS AND GENERALIZED FIBONACCI IDENTITIES appeared n: Fbonacc Quarterly 38(2000), pp. 282-288. PHASED TILINGS AND GENERALIZED FIBONACCI IDENTITIES Arthur T. Benjamn Dept. of Mathematcs, Harvey Mudd College, Claremont, CA 91711 benjamn@hmc.edu

More information

G = G 1 + G 2 + G 3 G 2 +G 3 G1 G2 G3. Network (a) Network (b) Network (c) Network (d)

G = G 1 + G 2 + G 3 G 2 +G 3 G1 G2 G3. Network (a) Network (b) Network (c) Network (d) Massachusetts Insttute of Technology Department of Electrcal Engneerng and Computer Scence 6.002 í Electronc Crcuts Homework 2 Soluton Handout F98023 Exercse 21: Determne the conductance of each network

More information

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

More information

The Number of Ways to Write n as a Sum of ` Regular Figurate Numbers

The Number of Ways to Write n as a Sum of ` Regular Figurate Numbers Syracuse Unversty SURFACE Syracuse Unversty Honors Program Capstone Projects Syracuse Unversty Honors Program Capstone Projects Sprng 5-1-01 The Number of Ways to Wrte n as a Sum of ` Regular Fgurate Numbers

More information

Notes on Frequency Estimation in Data Streams

Notes on Frequency Estimation in Data Streams Notes on Frequency Estmaton n Data Streams In (one of) the data streamng model(s), the data s a sequence of arrvals a 1, a 2,..., a m of the form a j = (, v) where s the dentty of the tem and belongs to

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

PHYS 705: Classical Mechanics. Canonical Transformation II

PHYS 705: Classical Mechanics. Canonical Transformation II 1 PHYS 705: Classcal Mechancs Canoncal Transformaton II Example: Harmonc Oscllator f ( x) x m 0 x U( x) x mx x LT U m Defne or L p p mx x x m mx x H px L px p m p x m m H p 1 x m p m 1 m H x p m x m m

More information

Short running title: A generating function approach A GENERATING FUNCTION APPROACH TO COUNTING THEOREMS FOR SQUARE-FREE POLYNOMIALS AND MAXIMAL TORI

Short running title: A generating function approach A GENERATING FUNCTION APPROACH TO COUNTING THEOREMS FOR SQUARE-FREE POLYNOMIALS AND MAXIMAL TORI Short runnng ttle: A generatng functon approach A GENERATING FUNCTION APPROACH TO COUNTING THEOREMS FOR SQUARE-FREE POLYNOMIALS AND MAXIMAL TORI JASON FULMAN Abstract. A recent paper of Church, Ellenberg,

More information

2 More examples with details

2 More examples with details Physcs 129b Lecture 3 Caltech, 01/15/19 2 More examples wth detals 2.3 The permutaton group n = 4 S 4 contans 4! = 24 elements. One s the dentty e. Sx of them are exchange of two objects (, j) ( to j and

More information

Appendix for Causal Interaction in Factorial Experiments: Application to Conjoint Analysis

Appendix for Causal Interaction in Factorial Experiments: Application to Conjoint Analysis A Appendx for Causal Interacton n Factoral Experments: Applcaton to Conjont Analyss Mathematcal Appendx: Proofs of Theorems A. Lemmas Below, we descrbe all the lemmas, whch are used to prove the man theorems

More information

Homework Math 180: Introduction to GR Temple-Winter (3) Summarize the article:

Homework Math 180: Introduction to GR Temple-Winter (3) Summarize the article: Homework Math 80: Introduton to GR Temple-Wnter 208 (3) Summarze the artle: https://www.udas.edu/news/dongwthout-dark-energy/ (4) Assume only the transformaton laws for etors. Let X P = a = a α y = Y α

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

More information

Parametric Useful Information Measure of Order Some Coding Theorem

Parametric Useful Information Measure of Order Some Coding Theorem Avalable onlne wwwejaetcom Eroean Jornal of Advances n Engneerng and Technoy, 207, 4(8): 603-607 Research Artcle ISS: 2394-658X Parametrc Usefl Informaton Measre of Order Some Codng Theorem egree and hanesh

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

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

VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES

VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES BÂRZĂ, Slvu Faculty of Mathematcs-Informatcs Spru Haret Unversty barza_slvu@yahoo.com Abstract Ths paper wants to contnue

More information

CHAPTER 13. Exercises. E13.1 The emitter current is given by the Shockley equation:

CHAPTER 13. Exercises. E13.1 The emitter current is given by the Shockley equation: HPT 3 xercses 3. The emtter current s gen by the Shockley equaton: S exp VT For operaton wth, we hae exp >> S >>, and we can wrte VT S exp VT Solng for, we hae 3. 0 6ln 78.4 mv 0 0.784 5 4.86 V VT ln 4

More information

Statistical Inference. 2.3 Summary Statistics Measures of Center and Spread. parameters ( population characteristics )

Statistical Inference. 2.3 Summary Statistics Measures of Center and Spread. parameters ( population characteristics ) Ismor Fscher, 8//008 Stat 54 / -8.3 Summary Statstcs Measures of Center and Spread Dstrbuton of dscrete contnuous POPULATION Random Varable, numercal True center =??? True spread =???? parameters ( populaton

More information

Solutions for Tutorial 1

Solutions for Tutorial 1 Toc 1: Sem-drect roducts Solutons for Tutoral 1 1. Show that the tetrahedral grou s somorhc to the sem-drect roduct of the Klen four grou and a cyclc grou of order three: T = K 4 (Z/3Z). 2. Show further

More information

THE SUMMATION NOTATION Ʃ

THE SUMMATION NOTATION Ʃ Sngle Subscrpt otaton THE SUMMATIO OTATIO Ʃ Most of the calculatons we perform n statstcs are repettve operatons on lsts of numbers. For example, we compute the sum of a set of numbers, or the sum of the

More information