Photon-phonon interaction in photonic crystals

Size: px
Start display at page:

Download "Photon-phonon interaction in photonic crystals"

Transcription

1 IOP Cofr Srs: Mtrls S d Egrg Photo-phoo trto photo rystls To t ths rtl: T Ut IOP Cof. Sr.: Mtr. S. Eg. 3 Vw th rtl ol for updts d hmts. Rltd ott - study o optl proprts of photo rystls osstg of hollow rods G Fuj T Mtsumoto T Tkhsh t l. - Frto of Trhrtz Wv Rsotors wth lum Dmod Photo Crystls for Frquy mplfto Wtr Solvts N Oht T Nk d S Krhr - Squzg of Phoos Photo-Phoo Itrto v t-stoks Lght * Ch Jhu d Guo Gug Ths ott ws dowlodd from IP ddrss o 7 t 3:

2 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 Photo-phoo trto photo rystls T Ut Isttut of Md d Iformto Thology Ch Uvrsty -33 Yyo-ho Ig-ku Ch Jp E-ml: ut@fulty.h-u.jp strt. Photo-phoo trto o th logy of ltro-phoo trto s osdrd o-dmsol photo rystl. Wh ltt vrto s rtflly trodud to th photo rystl govrg quto of ltromgt fld s drvd. smpl modl s umrlly lysd d th followg ovl phom r foud out. Th ltt vrto grts th lght of frquy whh ddd th tgrl multpl of th vrto frquy to tht of th dt wv d lso mplfs th dt wv rsotly. O rso th mplfto ftor rss vry rpdly wth th umr of lyrs rss. Rso frqus hg wth th phss of ltt vrto. Th mplfto phomo s lytlly dsussd for low frquy of th ltt vrto.. Itroduto It s wdly kow tht ltromgt flds prodlly modultd dltr md s ltros rystls form rgy d struturs. Suh phom hv vstgtd rgorously d tsvly for mor th t yrs[-]. O th othr hd th ltro-phoo trto s othr rmrkl phomo of ltro mtl or smodutor. I som ss ltros odutors form polros y trtg wth phoos. Furthrmor ths uss v suprodutvty phomo. Now lt us osdr th logy of th ltro-phoo trto photo rystls. Nw physl phom ptd photo rystls wth ltt vrtos[3-4]. Nmly f th ltt of photo rystl s rtflly oslltd wht would hpp? I th prst study drt trto tw ltromgt flds d ltt vrtos s osdrd o-dmsol photo rystl ostrutd y prodlly rrgd dltr plts.. Formulto W osdr o-dmsol photo rystl mly mult-lyr of dltr plts. Th sptl vrto of th dltr ostt s ssumd s U d whr d s th ltt ostt d w do ot spfy th futo U. Th -th dltrs s ssumd to oslltd hrmolly wth mpltud ξ t. Th th sptl d tm vrto of th dltr ostt s prssd s follows: Pulshd udr l y IOP Pulshg Ltd

3 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 t U d ξ t && ξ t ξ. t I ordr to dsr hvour of th ltromgt fld E t ths systm w g wth th ufd Mwll quto. Th ltromgt fld s ssumd to propgt log th -s d to prlll to th lyrs. Th w hv E t E t whr th rltv prmlty s st to. I ths prolm th tm drvtv of t s sstl d s th org of th photo-phoo trto. ssumg th mpltud ξ t to sufftly smllr th th ltt ostt d tht s ξ t d << t pdd s U η t ξ t. η η d Th frst d sod drvtvs r otd strghtforwrd s t U η & ξ t t η η d η t U. ξ t t η η d y susttutg ths qutos th ufd Mwll quto oms U η t ξ t t η t η d η U η & ξ t. t η d Th vrl t s slr fld s rprsttv of th vtor fld. Suppos w wrt th -th mpltud ξ t s ξ t ξ os t th Fourr trsform of th govrg quto s otd s follows [3]: U η. ξ η η d Hr ξ d r th mpltud frquy d wvumr of th ltt vrto rsptvly. Th vrl s th frquy of th ltromgt fld. Th trms o th rght hd sd prss th fft of th photo-phoo trto. It s proportol to ξ. Ths ms tht ξ dos ot d to lrg f dor r lrg ordr to s th flu of th trto. Th fld s oupld wth ±. Ths quto s dffr quto frquy sp. Thrfor wh ltromgt wv wth frquy omg s dt towrd th photo rystl ltromgt flds wth frqus l wll td whr l s tgr. 3. Numrl Implmtto Hrftr w osdr th s of rtgulr vrto of dltr ostt s show Fg..

4 - Fgur. Illustrto of th umrl modl of o-dmsol photo rystl. Th lyr of th dltr ostt hs thkss of d th ltt ostt s d. Th th futo η U s wrtt y th ut stp futo s { } U η η η so th drvtv ossts of two dlt futos. Howvr th otuty of th fld holds. Th oudry odtos t ± r otd s follows rsptvly; { } { }. ξ ξ Th fld r otuous t y oudrs of lyrs ut th frst drvtv of th fld hs jumps. Th flds wth th -th lyr d th lyr r prssd y lr omto of two dpdt fudmtl solutos wth h lyr for h frquy s p p p p D C whr s th vloty of lght vuum. Th offts dpd ot oly o ut lso o. y ms of th oudry odtos w ot st of quto of th offts s { } { } [ ] { } D C D C ξ WCCMPCOM IOP Pulshg IOP Cof. Srs: Mtrls S d Egrg 3 do: x3 3

5 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 C D { C D } ξ [ { } { }]. Now w osdr ft systm of N lyrs d dt wv of pl wv of frquy p[ ]. If w ssum th frquy of th fld tw l m d l m th trsmsso sptr r otd y solvg st of 4N lm qutos. Th th trsmsso prolty T l of frquy l s dfd y T l l N l for th tgr l stsfyg l >. 4. Numrl Rsults t frst th trsmsso sptr for th lght of frquy of ± d so o for 3 lyrs N 3 r show Fg.. Th prmtrs r st s 8 π ξ. d l m 4. I ths s th whol photo rystl s just oly shk. W s th fld of frquy dffrt from th dt o r grtd. Th tsts rflt th photo d strutur of th systm wthout ltt vrto d grow proporto to th squr of th frquy. Hr w must py ttto splly to th trsmsso sptrum of th dt frquy. W s th dt wv s rsotly mplfd [5]. Th trsmsso sptrum T th s of lyrs N s plottd Fg. 3 whr th vlus of prmtrs rm. Th rsot mplfto s rpdly hd s th umr of lyrs s rsd. Th trvl tw rsot pks s out π. It sms tht th rsot pks r lotd t photo d dgs. Th trsmsso sptrum T for π s plottd Fg.4. Othr prmtrs r ot hgd. Th trvl oms out π 4 d th pks ppr wth th d. Th trsmsso sptrum T for π 3 d s plottd Fg.5. Othr prmtrs r ot hgd. I ths s w s modfto of d strutur.. th ppr of w d gps. Th mplfto ours t th dgs of th w ds. Wh s st to π w srly fd th mplfto for. For π π 3 d π 4 howvr th mplfto s rtly osrvd th hgh frquy rgo. 4

6 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 T ê T μ μ μ -6. μ ê T3.6.4 T-3.5. T T ê ê ê T- T ê ê ê.5 T ê Fgur. Th trsmsso sptr of 3 lyrs. Th prmtrs r st s 8 π d ξ.. 5

7 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 4 3 T ê Fgur 3. Th trsmsso sptrum T of lyrs for. 4 3 T ê Fgur 4. Th trsmsso sptrum T of lyrs for π. 4 3 T ê Fgur 5. Th trsmsso sptrum d. T of lyrs for π 3 6

8 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 5. lytl Trtmt of th mplfto W osdr th s tht th vlu of th rto s smll ough ordr to dv lytl trtmt of th mplfto. Th w pd th flds ± srs so tht w ot U η ξ { } η ξ ξ η U η η U η η d η d η d Ths quto rwrtt s ~ os s. η l ~ U ξ s η η d U d ξ os. Now th dltr ostt hs th mgry prt. Th mgry prt dpds o th proprts of th fld th photo rystl. Wh th mgry prt s gtv th dt fld s mplfd. For th mgry prt vshs so tht w s tht ltt vrto ot shk of whol systm mks photo rystl tv mdum [6]. Th rl prt of th dltr ostt U d ξ os shows tht ths quto s fftvly for dul-prod multlyr strutur [7 8] whh th ltt ostt s modultd lk d ξ s s. Th trsmsso prolty T l ths s rflts th d strutur of dul-prod o-dmsol photo rystl. 6. Summry d Colusos I th prst ppr w hv osdrd photo-phoo trto o th logy of ltro-phoo trto d drvd th govrg quto. Wh ltt vrto s trodud th ltt vrto dos ot oly grt th wvs wth vrous frqus ut lso mplfs th dt wv rsotly. O rso th mplfto ftor rss vry rpdly s th umr of th plts rss. Rso frqus hg wth th phss of vrto of h lyr. Suh mplfto ours pt for th s tht ll lyrs osllt wth th sm phs mly tht of shkg th systm v f th frquy of th ltt vrto s vry smll. Ltt vrto mks photo rystl tv md. Th mplfto s osrvl. 7

9 WCCMPCOM IOP Cof. Srs: Mtrls S d Egrg 3 IOP Pulshg do: x3 Rfrs [] K. Ohtk: Phys. Rv. Vol [] Joh D. Joopoulos Rort D. Md Joshu N. W : Photo Crystls: Moldg th Flow of Lght Prto Uv. Prss 995 [3] T. Ut: Mtg strts of th Physl Soty of Jp Vol. 54 Issu Prt p Jps. [4] Y. Tk t l. Ntur Mtrls Vol [5] T. Ut d K. Ohtk: Mtg strts of th Physl Soty of Jp Vol. 54 Issu Prt p Jps. [6] T. Ut d K. Ohtk: Mtg strts of th Physl Soty of Jp Vol. 55 Issu Prt p.86 Jps. [7] R. Shmd T. Kod T. Ut d K. Ohtk : J. Phys. So. Jp Vol. 67 o. pp [8] R. Shmd T. Kod T. Ut d K. Ohtk : J. ppl. Phys. Vol. 9 o. 8 pp

Section 5.1/5.2: Areas and Distances the Definite Integral

Section 5.1/5.2: Areas and Distances the Definite Integral Scto./.: Ars d Dstcs th Dt Itgrl Sgm Notto Prctc HW rom Stwrt Ttook ot to hd p. #,, 9 p. 6 #,, 9- odd, - odd Th sum o trms,,, s wrtt s, whr th d o summto Empl : Fd th sum. Soluto: Th Dt Itgrl Suppos w

More information

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem Avll t http:pvu.u Appl. Appl. Mth. ISSN: 9-9466 Vol. 0 Issu Dr 05 pp. 007-08 Appltos Appl Mthts: A Itrtol Jourl AAM Etso oruls of Lurll s utos Appltos of Do s Suto Thor Ah Al Atsh Dprtt of Mthts A Uvrst

More information

minimize c'x subject to subject to subject to

minimize c'x subject to subject to subject to z ' sut to ' M ' M N uostrd N z ' sut to ' z ' sut to ' sl vrls vtor of : vrls surplus vtor of : uostrd s s s s s s z sut to whr : ut ost of :out of : out of ( ' gr of h food ( utrt : rqurt for h utrt

More information

Spectral Characteristics of Digitally Modulated Signals

Spectral Characteristics of Digitally Modulated Signals Strl Chrtrt of Dgtlly odultd Sgl 6:33:56 Wrl Couto holog Srg 5 Ltur7&8 Drtt of Eltrl Egrg Rutgr Uvrty Ptwy J 89 ught y Dr. ry dy ry@wl.rutgr.du Doutd y Bozh Yu ozh@d.rutgr.du trt: h ltur frt trodu th tdrd

More information

1. Stefan-Boltzmann law states that the power emitted per unit area of the surface of a black

1. Stefan-Boltzmann law states that the power emitted per unit area of the surface of a black Stf-Boltzm lw stts tht th powr mttd pr ut r of th surfc of blck body s proportol to th fourth powr of th bsolut tmprtur: 4 S T whr T s th bsolut tmprtur d th Stf-Boltzm costt= 5 4 k B 3 5c h ( Clcult 5

More information

Handout 11. Energy Bands in Graphene: Tight Binding and the Nearly Free Electron Approach

Handout 11. Energy Bands in Graphene: Tight Binding and the Nearly Free Electron Approach Hdout rg ds Grh: Tght dg d th Nrl Fr ltro roh I ths ltur ou wll lr: rg Th tght bdg thod (otd ) Th -bds grh FZ C 407 Srg 009 Frh R Corll Uvrst Grh d Crbo Notubs: ss Grh s two dsol sgl to lr o rbo tos rrgd

More information

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca**

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca** ERDO-MARANDACHE NUMBER b Tbrc* Tt Tbrc** *Trslv Uvrsty of Brsov, Computr cc Dprtmt **Uvrsty of Mchstr, Computr cc Dprtmt Th strtg pot of ths rtcl s rprstd by rct work of Fch []. Bsd o two symptotc rsults

More information

Linear Algebra Existence of the determinant. Expansion according to a row.

Linear Algebra Existence of the determinant. Expansion according to a row. Lir Algbr 2270 1 Existc of th dtrmit. Expsio ccordig to row. W dfi th dtrmit for 1 1 mtrics s dt([]) = (1) It is sy chck tht it stisfis D1)-D3). For y othr w dfi th dtrmit s follows. Assumig th dtrmit

More information

Special Curves of 4D Galilean Space

Special Curves of 4D Galilean Space Irol Jourl of Mhml Egrg d S ISSN : 77-698 Volum Issu Mrh hp://www.jms.om/ hps://ss.googl.om/s/jmsjourl/ Spl Curvs of D ll Sp Mhm Bkş Mhmu Ergü Alpr Osm Öğrmş Fır Uvrsy Fuly of S Dprm of Mhms 9 Elzığ Türky

More information

Outline. Outline. Outline. Questions 2010/9/30. Introduction The Multivariate Normal Density and Its Properties

Outline. Outline. Outline. Questions 2010/9/30. Introduction The Multivariate Normal Density and Its Properties 9 Multvrt orml Dstruto Shyh-Kg Jg Drtmt of Eltrl Egrg Grdut Isttut of Commuto Grdut Isttut of tworkg d Multmd Outl Itroduto Th Multvrt orml Dsty d Its Prorts Smlg from Multvrt orml Dstruto d Mmum Lklhood

More information

THE TRANSMUTED GENERALIZED PARETO DISTRIBUTION. STATISTICAL INFERENCE AND SIMULATION RESULTS

THE TRANSMUTED GENERALIZED PARETO DISTRIBUTION. STATISTICAL INFERENCE AND SIMULATION RESULTS Mr l Btr vl Admy Stf Bullt Volum VIII 5 Issu Pulshd y Mr l Btr vl Admy Prss Costt Rom // Th jourl s dd : PROQUST STh Jourls PROQUST grg Jourls PROQUST Illustrt: Thology PROQUST Thology Jourls PROQUST Mltry

More information

Outline. Outline. Outline. Questions. Multivariate Normal Distribution. Multivariate Normal Distribution

Outline. Outline. Outline. Questions. Multivariate Normal Distribution. Multivariate Normal Distribution Multvrt orml Dstruto hyh-kg Jg Drtmt of Eltrl Egrg Grdut sttut of Commuto Grdut sttut of tworg d Multmd Outl troduto Th Multvrt orml Dsty d ts Prorts mlg from Multvrt orml Dstruto d Mmum Llhood Estmto

More information

CBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find

CBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find BSE SMLE ER SOLUTONS LSS-X MTHS SET- BSE SETON Gv tht d W d to fd 7 7 Hc, 7 7 7 Lt, W ow tht Thus, osd th vcto quto of th pl z - + z = - + z = Thus th ts quto of th pl s - + z = Lt d th dstc tw th pot,,

More information

Face Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction

Face Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction F Dtto Roto Lr Alr F Roto C Y I Ursty O solto: tto o l trs s s ys os ot. Dlt to t to ltpl ws. F Roto Aotr ppro: ort y rry s tor o so E.. 56 56 > pot 6556- stol sp A st o s t ps to ollto o pots ts sp. F

More information

Linear Prediction Analysis of

Linear Prediction Analysis of Lr Prdcto Alyss of Sch Souds Brl Ch Drtt of Coutr Scc & Iforto grg Ntol Tw Norl Uvrsty frcs: X Hug t l So Lgug g Procssg Chtrs 5 6 J Dllr t l Dscrt-T Procssg of Sch Sgls Chtrs 4-6 3 J W Pco Sgl odlg tchqus

More information

CHAPTER 4. FREQUENCY ESTIMATION AND TRACKING

CHAPTER 4. FREQUENCY ESTIMATION AND TRACKING CHPTER 4. FREQUENCY ESTITION ND TRCKING 4.. Itroducto Estmtg mult-frquc susodl sgls burd os hs b th focus of rsrch for qut som tm [68] [58] [46] [64]. ost of th publshd rsrch usd costrd ft mpuls rspos

More information

Linear Prediction Analysis of Speech Sounds

Linear Prediction Analysis of Speech Sounds Lr Prdcto Alyss of Sch Souds Brl Ch 4 frcs: X Hug t l So Lgug Procssg Chtrs 5 6 J Dllr t l Dscrt-T Procssg of Sch Sgls Chtrs 4-6 3 J W Pco Sgl odlg tchqus sch rcogto rocdgs of th I Stbr 993 5-47 Lr Prdctv

More information

CBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane.

CBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane. CBSE CBSE SET- SECTION. Gv tht d W d to fd 7 7 Hc, 7 7 7. Lt,. W ow tht.. Thus,. Cosd th vcto quto of th pl.. z. - + z = - + z = Thus th Cts quto of th pl s - + z = Lt d th dstc tw th pot,, - to th pl.

More information

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis Dpartmt of Mathmatcs ad Statstcs Ida Isttut of Tchology Kapur MSOA/MSO Assgmt 3 Solutos Itroducto To omplx Aalyss Th problms markd (T) d a xplct dscusso th tutoral class. Othr problms ar for hacd practc..

More information

FOURIER SERIES. Series expansions are a ubiquitous tool of science and engineering. The kinds of

FOURIER SERIES. Series expansions are a ubiquitous tool of science and engineering. The kinds of Do Bgyoko () FOURIER SERIES I. INTRODUCTION Srs psos r ubqutous too o scc d grg. Th kds o pso to utz dpd o () th proprts o th uctos to b studd d (b) th proprts or chrctrstcs o th systm udr vstgto. Powr

More information

Introduction to Laplace Transforms October 25, 2017

Introduction to Laplace Transforms October 25, 2017 Iroduco o Lplc Trform Ocobr 5, 7 Iroduco o Lplc Trform Lrr ro Mchcl Egrg 5 Smr Egrg l Ocobr 5, 7 Oul Rvw l cl Wh Lplc rform fo of Lplc rform Gg rform b gro Fdg rform d vr rform from bl d horm pplco o dffrl

More information

Chapter 2 Reciprocal Lattice. An important concept for analyzing periodic structures

Chapter 2 Reciprocal Lattice. An important concept for analyzing periodic structures Chpt Rcpocl Lttc A mpott cocpt o lyzg podc stuctus Rsos o toducg cpocl lttc Thoy o cystl dcto o x-ys, utos, d lctos. Wh th dcto mxmum? Wht s th tsty? Abstct study o uctos wth th podcty o Bvs lttc Fou tsomto.

More information

On the Existence and uniqueness for solution of system Fractional Differential Equations

On the Existence and uniqueness for solution of system Fractional Differential Equations OSR Jourl o Mhms OSR-JM SSN: 78-578. Volum 4 ssu 3 Nov. - D. PP -5 www.osrjourls.org O h Es d uquss or soluo o ssm rol Drl Equos Mh Ad Al-Wh Dprm o Appld S Uvrs o holog Bghdd- rq Asr: hs ppr w d horm o

More information

More Statistics tutorial at 1. Introduction to mathematical Statistics

More Statistics tutorial at   1. Introduction to mathematical Statistics Mor Sttstcs tutorl t wwwdumblttldoctorcom Itroducto to mthmtcl Sttstcs Fl Soluto A Gllup survy portrys US trprurs s " th mvrcks, drmrs, d lors whos rough dgs d ucompromsg d to do t thr ow wy st thm shrp

More information

Chapter 3 Fourier Series Representation of Periodic Signals

Chapter 3 Fourier Series Representation of Periodic Signals Chptr Fourir Sris Rprsttio of Priodic Sigls If ritrry sigl x(t or x[] is xprssd s lir comitio of som sic sigls th rspos of LI systm coms th sum of th idividul rsposs of thos sic sigls Such sic sigl must:

More information

IIT JEE MATHS MATRICES AND DETERMINANTS

IIT JEE MATHS MATRICES AND DETERMINANTS IIT JEE MTHS MTRICES ND DETERMINNTS THIRUMURUGN.K PGT Mths IIT Trir 978757 Pg. Lt = 5, th () =, = () = -, = () =, = - (d) = -, = -. Lt sw smmtri mtri of odd th quls () () () - (d) o of ths. Th vlu of th

More information

1 Introduction to Modulo 7 Arithmetic

1 Introduction to Modulo 7 Arithmetic 1 Introution to Moulo 7 Arithmti Bor w try our hn t solvin som hr Moulr KnKns, lt s tk los look t on moulr rithmti, mo 7 rithmti. You ll s in this sminr tht rithmti moulo prim is quit irnt rom th ons w

More information

3.4 Properties of the Stress Tensor

3.4 Properties of the Stress Tensor cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato

More information

SYSTEMS OF LINEAR EQUATIONS

SYSTEMS OF LINEAR EQUATIONS SYSES OF INER EQUIONS Itroducto Emto thods Dcomposto thods tr Ivrs d Dtrmt Errors, Rsdus d Codto Numr Itrto thods Icompt d Rdudt Systms Chptr Systms of r Equtos /. Itroducto h systm of r qutos s formd

More information

A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex.

A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex. Lnr lgr Vctors gnrl -dmnsonl ctor conssts of lus h cn rrngd s column or row nd cn rl or compl Rcll -dmnsonl ctor cn rprsnt poston, loct, or cclrton Lt & k,, unt ctors long,, & rspctl nd lt k h th componnts

More information

Divided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano

Divided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano RIGHT-ANGLE WEAVE Dv mons Mm t look o ts n rlt tt s ptvly p sn y Py Brnkmn Mttlno Dv your mons nto trnls o two or our olors. FCT-SCON0216_BNB66 2012 Klm Pulsn Co. Ts mtrl my not rprou n ny orm wtout prmsson

More information

Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals

Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals Intgrtion Continud Intgrtion y Prts Solving Dinit Intgrls: Ar Undr Curv Impropr Intgrls Intgrtion y Prts Prticulrly usul whn you r trying to tk th intgrl o som unction tht is th product o n lgric prssion

More information

Quantum Mechanics & Spectroscopy Prof. Jason Goodpaster. Problem Set #2 ANSWER KEY (5 questions, 10 points)

Quantum Mechanics & Spectroscopy Prof. Jason Goodpaster. Problem Set #2 ANSWER KEY (5 questions, 10 points) Chm 5 Problm St # ANSWER KEY 5 qustios, poits Qutum Mchics & Spctroscopy Prof. Jso Goodpstr Du ridy, b. 6 S th lst pgs for possibly usful costts, qutios d itgrls. Ths will lso b icludd o our futur ms..

More information

Problem Set 4 Solutions

Problem Set 4 Solutions 4 Eoom Altos of Gme Theory TA: Youg wg /08/0 - Ato se: A A { B, } S Prolem Set 4 Solutos - Tye Se: T { α }, T { β, β} Se Plyer hs o rte formto, we model ths so tht her tye tke oly oe lue Plyer kows tht

More information

Note 7. Device applications 1

Note 7. Device applications 1 ot 7. Dv lto Prt : P- Juto P Juto A P juto h rtyg urrt voltg I or I hrtrt. It ll rtr or o. h P juto th trutur o olr ll, lght-mttg o, o lr, rt ll ty o trtor. A P juto b brt by ovrtg lyr o P-ty moutor to

More information

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS C 24 - COMBINATIONAL BUILDING BLOCKS - INVST 3 DCODS AND NCODS FALL 23 AP FLZ To o "wll" on this invstition you must not only t th riht nswrs ut must lso o nt, omplt n onis writups tht mk ovious wht h

More information

LINEAR 2 nd ORDER DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS

LINEAR 2 nd ORDER DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS Diol Bgyoko (0) I.INTRODUCTION LINEAR d ORDER DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS I. Dfiiio All suh diffril quios s i h sdrd or oil form: y + y + y Q( x) dy d y wih y d y d dx dx whr,, d

More information

A Genetic Algorithm for Fuzzy Shortest Path in a Network with mixed fuzzy arc lengths

A Genetic Algorithm for Fuzzy Shortest Path in a Network with mixed fuzzy arc lengths Prodg of th 0 Itrtol Cofr o Idustrl d Oprtos Mgt Kul pur Mls Jur - 0 A Gt Algorth for Fuzz Shortst Pth Ntwork wth d fuzz r lgths z Hsszdh Irj Mhdv * Al Tjd Dprtt of Idustrl Egrg Mzdr Uvrst of S d Tholog

More information

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely . DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,

More information

Finite Element Approach to Electric Field Distribution Resulting from Phase-sequence Orientation of a Double- Circuit High Voltage Transmission Line

Finite Element Approach to Electric Field Distribution Resulting from Phase-sequence Orientation of a Double- Circuit High Voltage Transmission Line Prodgs of th 8th WSEAS Itrtol Cofr o ELECTRIC POWER SYSTEMS HIGH VOLTAGES ELECTRIC MACHIES (POWER '8) Ft Elt Approh to Eltr Fld Dstruto Rsultg fro Phs-squ Ortto of Doul- Crut Hgh Voltg Trssso L A. ISARAMOGKOLRAK

More information

Model of the multi-level laser

Model of the multi-level laser Modl of th multilvl lsr Trih Dih Chi Fulty of Physis, Collg of turl Sis, oi tiol Uivrsity Tr Mh ug, Dih u Kho Fulty of Physis, Vih Uivrsity Astrt. Th lsr hrtristis dpd o th rgylvl digrm. A rsol rgylvl

More information

Inner Product Spaces INNER PRODUCTS

Inner Product Spaces INNER PRODUCTS MA4Hcdoc Ir Product Spcs INNER PRODCS Dto A r product o vctor spc V s ucto tht ssgs ubr spc V such wy tht th ollowg xos holds: P : w s rl ubr P : P : P 4 : P 5 : v, w = w, v v + w, u = u + w, u rv, w =

More information

Designing A Concrete Arch Bridge

Designing A Concrete Arch Bridge This is th mous Shwnh ri in Switzrln, sin y Rort Millrt in 1933. It spns 37.4 mtrs (122 t) n ws sin usin th sm rphil mths tht will monstrt in this lsson. To pro with this lsson, lik on th Nxt utton hr

More information

Weighted Graphs. Weighted graphs may be either directed or undirected.

Weighted Graphs. Weighted graphs may be either directed or undirected. 1 In mny ppltons, o rp s n ssot numrl vlu, ll wt. Usully, t wts r nonntv ntrs. Wt rps my tr rt or unrt. T wt o n s otn rrr to s t "ost" o t. In ppltons, t wt my msur o t lnt o rout, t pty o ln, t nry rqur

More information

The Z-Transform in DSP Lecture Andreas Spanias

The Z-Transform in DSP Lecture Andreas Spanias The Z-Trsform DSP eture - Adres Ss ss@su.edu 6 Coyrght 6 Adres Ss -- Poles d Zeros of I geerl the trsfer futo s rtol; t hs umertor d deomtor olyoml. The roots of the umertor d deomtor olyomls re lled the

More information

The Theory of Small Reflections

The Theory of Small Reflections Jim Stils Th Univ. of Knss Dt. of EECS 4//9 Th Thory of Smll Rflctions /9 Th Thory of Smll Rflctions Rcll tht w nlyzd qurtr-wv trnsformr usg th multil rflction viw ot. V ( z) = + β ( z + ) V ( z) = = R

More information

a b c cat CAT A B C Aa Bb Cc cat cat Lesson 1 (Part 1) Verbal lesson: Capital Letters Make The Same Sound Lesson 1 (Part 1) continued...

a b c cat CAT A B C Aa Bb Cc cat cat Lesson 1 (Part 1) Verbal lesson: Capital Letters Make The Same Sound Lesson 1 (Part 1) continued... Progrssiv Printing T.M. CPITLS g 4½+ Th sy, fun (n FR!) wy to tch cpitl lttrs. ook : C o - For Kinrgrtn or First Gr (not for pr-school). - Tchs tht cpitl lttrs mk th sm souns s th littl lttrs. - Tchs th

More information

Numerical Method: Finite difference scheme

Numerical Method: Finite difference scheme Numrcal Mthod: Ft dffrc schm Taylor s srs f(x 3 f(x f '(x f ''(x f '''(x...(1! 3! f(x 3 f(x f '(x f ''(x f '''(x...(! 3! whr > 0 from (1, f(x f(x f '(x R Droppg R, f(x f(x f '(x Forward dffrcg O ( x from

More information

Reliability of time dependent stress-strength system for various distributions

Reliability of time dependent stress-strength system for various distributions IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,

More information

Major: All Engineering Majors. Authors: Autar Kaw, Luke Snyder

Major: All Engineering Majors. Authors: Autar Kaw, Luke Snyder Nolr Rgrsso Mjor: All Egrg Mjors Auhors: Aur Kw, Luk Sydr hp://urclhodsgusfdu Trsforg Nurcl Mhods Educo for STEM Udrgrdus 3/9/5 hp://urclhodsgusfdu Nolr Rgrsso hp://urclhodsgusfdu Nolr Rgrsso So populr

More information

Lecture 11 Waves in Periodic Potentials Today: Questions you should be able to address after today s lecture:

Lecture 11 Waves in Periodic Potentials Today: Questions you should be able to address after today s lecture: Lctur 11 Wvs in Priodic Potntils Tody: 1. Invrs lttic dfinition in 1D.. rphicl rprsnttion of priodic nd -priodic functions using th -xis nd invrs lttic vctors. 3. Sris solutions to th priodic potntil Hmiltonin

More information

Gilbert the Green Tree Frog

Gilbert the Green Tree Frog Gbrt th Gr Tr Frog A org Kpr Kd book Wrtt by Stph Jk Iutrtd by T Eor ONCE UPON A TIME thr w frog md Gbrt. Gbrt w Gr Tr Frog. H fmy w gr. H hom w gr. Ad omtm v h food w gr. Gbrt w ck d trd of bg o gr th

More information

Fractions. Mathletics Instant Workbooks. Simplify. Copyright

Fractions. Mathletics Instant Workbooks. Simplify. Copyright Frctons Stunt Book - Srs H- Smplfy + Mthltcs Instnt Workbooks Copyrht Frctons Stunt Book - Srs H Contnts Topcs Topc - Equvlnt frctons Topc - Smplfyn frctons Topc - Propr frctons, mpropr frctons n mx numbrs

More information

CIVL 8/ D Boundary Value Problems - Rectangular Elements 1/7

CIVL 8/ D Boundary Value Problems - Rectangular Elements 1/7 CIVL / -D Boundr Vlu Prolms - Rctngulr Elmnts / RECANGULAR ELEMENS - In som pplictions, it m mor dsirl to us n lmntl rprsnttion of th domin tht hs four sids, ithr rctngulr or qudriltrl in shp. Considr

More information

# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths.

# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths. How os it work? Pl vlu o imls rprsnt prts o whol numr or ojt # 0 000 Tns o thousns # 000 # 00 Thousns Hunrs Tns Ons # 0 Diml point st iml pl: ' 0 # 0 on tnth n iml pl: ' 0 # 00 on hunrth r iml pl: ' 0

More information

Minimum Spanning Trees

Minimum Spanning Trees Minimum Spnning Trs Minimum Spnning Trs Problm A town hs st of houss nd st of rods A rod conncts nd only houss A rod conncting houss u nd v hs rpir cost w(u, v) Gol: Rpir nough (nd no mor) rods such tht:

More information

Improving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e)

Improving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e) POW CSE 36: Dt Struturs Top #10 T Dynm (Equvln) Duo: Unon-y-Sz & Pt Comprsson Wk!! Luk MDowll Summr Qurtr 003 M! ZING Wt s Goo Mz? Mz Construton lortm Gvn: ollton o rooms V Conntons twn t rooms (ntlly

More information

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o

More information

Instructions for Section 1

Instructions for Section 1 Instructions for Sction 1 Choos th rspons tht is corrct for th qustion. A corrct nswr scors 1, n incorrct nswr scors 0. Mrks will not b dductd for incorrct nswrs. You should ttmpt vry qustion. No mrks

More information

Aotomorphic Functions And Fermat s Last Theorem(4)

Aotomorphic Functions And Fermat s Last Theorem(4) otomorphc Fuctos d Frmat s Last Thorm(4) Chu-Xua Jag P. O. Box 94 Bg 00854 P. R. Cha agchuxua@sohu.com bsract 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES DEFINITION OF A COMPLEX NUMBER: A umbr of th form, whr = (, ad & ar ral umbrs s calld a compl umbr Th ral umbr, s calld ral part of whl s calld

More information

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018 CSE 373: Mor on grphs; DFS n BFS Mihl L Wnsy, F 14, 2018 1 Wrmup Wrmup: Disuss with your nighor: Rmin your nighor: wht is simpl grph? Suppos w hv simpl, irt grph with x nos. Wht is th mximum numr of gs

More information

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty 3 Bary Choc LPM logt logstc rgrso probt Multpl Choc Multomal Logt (c Pogsa Porchawssul,

More information

Practice Final Exam. 3.) What is the 61st term of the sequence 7, 11, 15, 19,...?

Practice Final Exam. 3.) What is the 61st term of the sequence 7, 11, 15, 19,...? Discrt mth Prctic Fl Em.) Fd 4 (i ) i=.) Fd i= 6 i.) Wht is th 6st trm th squnc 7,, 5, 9,...? 4.) Wht s th 57th trm, 6,, 4,...? 5.) Wht s th sum th first 60 trms th squnc, 5, 7, 9,...? 6.) Suppos st A

More information

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology! Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik

More information

On Matrices associated with L-Fuzzy Graphs

On Matrices associated with L-Fuzzy Graphs lol Jorl of Pr d Appld Mthmts ISSN 973-768 olm 3 Nmr 6 7 pp 799-8 Rsrh Id Pltos http://wwwrpltoom O Mtrs ssotd wth -Fzzy rphs Prmd Rmhdr P Dprtmt of Mthmts St Pl s Collg Klmssry Koh-683 53 Krl Id K Thoms

More information

Constructive Geometric Constraint Solving

Constructive Geometric Constraint Solving Construtiv Gomtri Constrint Solving Antoni Soto i Rir Dprtmnt Llngutgs i Sistms Inormàtis Univrsitt Politèni Ctluny Brlon, Sptmr 2002 CGCS p.1/37 Prliminris CGCS p.2/37 Gomtri onstrint prolm C 2 D L BC

More information

page 11 equation (1.2-10c), break the bar over the right side in the middle

page 11 equation (1.2-10c), break the bar over the right side in the middle I. Corrctios Lst Updtd: Ju 00 Complx Vrils with Applictios, 3 rd ditio, A. Dvid Wusch First Pritig. A ook ought for My 007 will proly first pritig With Thks to Christi Hos of Swd pg qutio (.-0c), rk th

More information

CSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review

CSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review rmup CSE 7: AVL trs rmup: ht is n invrint? Mihl L Friy, Jn 9, 0 ht r th AVL tr invrints, xtly? Disuss with your nighor. AVL Trs: Invrints Intrlu: Exploring th ln invrint Cor i: xtr invrint to BSTs tht

More information

International Journal of Mathematical Archive-6(5), 2015, Available online through ISSN

International Journal of Mathematical Archive-6(5), 2015, Available online through  ISSN Itratoal Joural of Mathmatal Arhv-6), 0, 07- Avalabl ol through wwwjmafo ISSN 9 06 ON THE LINE-CUT TRANSFORMATION RAPHS B BASAVANAOUD*, VEENA R DESAI Dartmt of Mathmats, Karatak Uvrsty, Dharwad - 80 003,

More information

On the Hubbard-Stratonovich Transformation for Interacting Bosons

On the Hubbard-Stratonovich Transformation for Interacting Bosons O h ubbrd-sroovh Trsformo for Irg osos Mr R Zrbur ff Fbrury 8 8 ubbrd-sroovh for frmos: rmdr osos r dffr! Rdom mrs: hyrbol S rsformo md rgorous osus for rg bosos /8 Wyl grou symmry L : G GL V b rrso of

More information

Chapter 16. 1) is a particular point on the graph of the function. 1. y, where x y 1

Chapter 16. 1) is a particular point on the graph of the function. 1. y, where x y 1 Prctic qustions W now tht th prmtr p is dirctl rltd to th mplitud; thrfor, w cn find tht p. cos d [ sin ] sin sin Not: Evn though ou might not now how to find th prmtr in prt, it is lws dvisl to procd

More information

Data-Depend Hash Algorithm

Data-Depend Hash Algorithm Dt-Dp s Algortm ZJ Xu K Xu uzwz@gml.com ukzp@gml.com Astrct: W stuy som tcologys tt popl vlop lys ttck s lgortm. W wy tt us t-p uc rsst rtl ttck. T w sg s lgortm tt cll Dt-Dp s Algort(DDA. A DDA s smpl

More information

Unbalanced Panel Data Models

Unbalanced Panel Data Models Ubalacd Pal Data odls Chaptr 9 from Baltag: Ecoomtrc Aalyss of Pal Data 5 by Adrás alascs 4448 troducto balacd or complt pals: a pal data st whr data/obsrvatos ar avalabl for all crosssctoal uts th tr

More information

Fundamentals of Continuum Mechanics. Seoul National University Graphics & Media Lab

Fundamentals of Continuum Mechanics. Seoul National University Graphics & Media Lab Fndmntls of Contnm Mchncs Sol Ntonl Unvrsty Grphcs & Md Lb Th Rodmp of Contnm Mchncs Strss Trnsformton Strn Trnsformton Strss Tnsor Strn T + T ++ T Strss-Strn Rltonshp Strn Enrgy FEM Formlton Lt s Stdy

More information

OPTIMAL STEP-STRESS PLANS FOR ACCELERATED LIFE TESTING CONSIDERING RELIABILITY/LIFE PREDICTION

OPTIMAL STEP-STRESS PLANS FOR ACCELERATED LIFE TESTING CONSIDERING RELIABILITY/LIFE PREDICTION OPIM P-R PN FOR CCRD IF ING CONIDRING RIBIIY/IF PRDICION Dssrtto Prstd b Chhu to h Dprtmt of Mhl d Idustrl grg prtl fulfllmt of th rqurmt for th dgr of Dotor of Phlosoph Idustrl grg Northstr Uvrst Bosto

More information

TOPIC 5: INTEGRATION

TOPIC 5: INTEGRATION TOPIC 5: INTEGRATION. Th indfinit intgrl In mny rspcts, th oprtion of intgrtion tht w r studying hr is th invrs oprtion of drivtion. Dfinition.. Th function F is n ntidrivtiv (or primitiv) of th function

More information

Handout 7. Properties of Bloch States and Electron Statistics in Energy Bands

Handout 7. Properties of Bloch States and Electron Statistics in Energy Bands Hdout 7 Popts of Bloch Stts d Elcto Sttstcs Eg Bds I ths lctu ou wll l: Popts of Bloch fuctos Podc boud codtos fo Bloch fuctos Dst of stts -spc Elcto occupto sttstcs g bds ECE 407 Spg 009 Fh R Coll Uvst

More information

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt

More information

Rate of Molecular Exchange Through the Membranes of Ionic Liquid Filled. Polymersomes Dispersed in Water

Rate of Molecular Exchange Through the Membranes of Ionic Liquid Filled. Polymersomes Dispersed in Water Supportng Informton for: Rt of Molculr Exchng hrough th Mmrns of Ionc Lqud Flld olymrsoms Dsprsd n Wtr Soonyong So nd mothy. Lodg *,, Dprtmnt of Chmcl Engnrng & Mtrls Scnc nd Dprtmnt of Chmstry, Unvrsty

More information

Statistical properties and applications of a Weibull- Kumaraswamy distribution

Statistical properties and applications of a Weibull- Kumaraswamy distribution Itrtol Jourl of Sttstcs d Appld Mthmtcs 208; 3(6): 8090 ISSN: 2456452 Mths 208; 3(6): 8090 208 Stts & Mths www.mthsjourl.com Rcvd: 09208 Accptd: 20208 Amu M Dprtmt Mths d Sttstcs, Aukr Ttr Al Polytchc,

More information

Solve Multi Linear Programming Problem By Taylor Polynomial solution

Solve Multi Linear Programming Problem By Taylor Polynomial solution Solv Mult Lr Progrmmg Problm By ylor Polyoml soluto Wld Khld Jbr Collg of Comutr S.& Mthmt Comutr Drtmt h-qr Uvrsty انخالصت تض انبحج حم يسائم انبشيجت انخطيت ان تعذدة باستخذاو يتسهسهت تايه س انحص ل عهى

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

Minimum Spanning Trees

Minimum Spanning Trees Mnmum Spnnng Trs Spnnng Tr A tr (.., connctd, cyclc grph) whch contns ll th vrtcs of th grph Mnmum Spnnng Tr Spnnng tr wth th mnmum sum of wghts 1 1 Spnnng forst If grph s not connctd, thn thr s spnnng

More information

ASSERTION AND REASON

ASSERTION AND REASON ASSERTION AND REASON Som qustios (Assrtio Rso typ) r giv low. Ech qustio cotis Sttmt (Assrtio) d Sttmt (Rso). Ech qustio hs choics (A), (B), (C) d (D) out of which ONLY ONE is corrct. So slct th corrct

More information

ELEG 413 Lecture #6. Mark Mirotznik, Ph.D. Professor The University of Delaware

ELEG 413 Lecture #6. Mark Mirotznik, Ph.D. Professor The University of Delaware LG 43 Lctur #6 Mrk Mirtnik, Ph.D. Prfssr Th Univrsity f Dlwr mil: mirtni@c.udl.du Wv Prpgtin nd Plritin TM: Trnsvrs lctrmgntic Wvs A md is prticulr fild cnfigurtin. Fr givn lctrmgntic bundry vlu prblm,

More information

COMP108 Algorithmic Foundations

COMP108 Algorithmic Foundations Grdy mthods Prudn Wong http://www.s.liv..uk/~pwong/thing/omp108/01617 Coin Chng Prolm Suppos w hv 3 typs of oins 10p 0p 50p Minimum numr of oins to mk 0.8, 1.0, 1.? Grdy mthod Lrning outoms Undrstnd wht

More information

Volumes of Solids of Revolution via Summation Methods

Volumes of Solids of Revolution via Summation Methods olums of Solds of Rvoluto va Summato Mthods Tlak d Alws talws@slu.du Dpartmt of Mathmats Southastr Lousaa Uvrsty Hammod, LA 70403 USA Astrat: I ths papr, w wll show how to alulat volums of rta solds of

More information

ADORO TE DEVOTE (Godhead Here in Hiding) te, stus bat mas, la te. in so non mor Je nunc. la in. tis. ne, su a. tum. tas: tur: tas: or: ni, ne, o:

ADORO TE DEVOTE (Godhead Here in Hiding) te, stus bat mas, la te. in so non mor Je nunc. la in. tis. ne, su a. tum. tas: tur: tas: or: ni, ne, o: R TE EVTE (dhd H Hdg) L / Mld Kbrd gú s v l m sl c m qu gs v nns V n P P rs l mul m d lud 7 súb Fí cón ví f f dó, cru gs,, j l f c r s m l qum t pr qud ct, us: ns,,,, cs, cut r l sns m / m fí hó sn sí

More information

How much air is required by the people in this lecture theatre during this lecture?

How much air is required by the people in this lecture theatre during this lecture? 3 NTEGRATON tgrtio is us to swr qustios rltig to Ar Volum Totl qutity such s: Wht is th wig r of Boig 747? How much will this yr projct cost? How much wtr os this rsrvoir hol? How much ir is rquir y th

More information

Correlation in tree The (ferromagnetic) Ising model

Correlation in tree The (ferromagnetic) Ising model 5/3/00 :\ jh\slf\nots.oc\7 Chaptr 7 Blf propagato corrlato tr Corrlato tr Th (frromagtc) Isg mol Th Isg mol s a graphcal mol or par ws raom Markov fl cosstg of a urct graph wth varabls assocat wth th vrtcs.

More information

b.) v d =? Example 2 l = 50 m, D = 1.0 mm, E = 6 V, " = 1.72 #10 $8 % & m, and r = 0.5 % a.) R =? c.) V ab =? a.) R eq =?

b.) v d =? Example 2 l = 50 m, D = 1.0 mm, E = 6 V,  = 1.72 #10 $8 % & m, and r = 0.5 % a.) R =? c.) V ab =? a.) R eq =? xmpl : An 8-gug oppr wr hs nomnl mtr o. mm. Ths wr rrs onstnt urrnt o.67 A to W lmp. Th nsty o r ltrons s 8.5 x 8 ltrons pr u mtr. Fn th mgntu o. th urrnt nsty. th rt vloty xmpl D. mm,.67 A, n N 8.5" 8

More information

Construction 11: Book I, Proposition 42

Construction 11: Book I, Proposition 42 Th Visul Construtions of Euli Constrution #11 73 Constrution 11: Book I, Proposition 42 To onstrut, in givn rtilinl ngl, prlllogrm qul to givn tringl. Not: Equl hr mns qul in r. 74 Constrution # 11 Th

More information

Handout on. Crystal Symmetries and Energy Bands

Handout on. Crystal Symmetries and Energy Bands dou o Csl s d g Bds I hs lu ou wll l: Th loshp bw ss d g bds h bs of sp-ob ouplg Th loshp bw ss d g bds h ps of sp-ob ouplg C 7 pg 9 Fh Coll Uvs d g Bds gll hs oh Th sl pol ss ddo o h l slo s: Fo pl h

More information

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are Itratoal Joural Of Computatoal Egrg Rsarch (crol.com) Vol. Issu. 5 Total Prm Graph M.Rav (a) Ramasubramaa 1, R.Kala 1 Dpt.of Mathmatcs, Sr Shakth Isttut of Egrg & Tchology, Combator 641 06. Dpt. of Mathmatcs,

More information

Adagba O Henry /International Journal Of Computational Engineering Research / ISSN: OPERATION ON IDEALS

Adagba O Henry /International Journal Of Computational Engineering Research / ISSN: OPERATION ON IDEALS Adagba O Hry /Itratoal Joural Of Computatoal Egrg Rsarh / ISSN 50 3005 OPERATION ON IDEALS Adagba O Hry, Dpt of Idustral Mathmats & Appld Statsts, Eboy Stat Uvrsty, Abakalk Abstrat W provd bas opratos

More information

On Hamiltonian Tetrahedralizations Of Convex Polyhedra

On Hamiltonian Tetrahedralizations Of Convex Polyhedra O Ht Ttrrzts O Cvx Pyr Frs C 1 Q-Hu D 2 C A W 3 1 Dprtt Cputr S T Uvrsty H K, H K, C. E: @s.u. 2 R & TV Trsss Ctr, Hu, C. E: q@163.t 3 Dprtt Cputr S, Mr Uvrsty Nwu St. J s, Nwu, C A1B 35. E: w@r.s.u. Astrt

More information

Ch 1.2: Solutions of Some Differential Equations

Ch 1.2: Solutions of Some Differential Equations Ch 1.2: Solutions of Som Diffrntil Equtions Rcll th fr fll nd owl/mic diffrntil qutions: v 9.8.2v, p.5 p 45 Ths qutions hv th gnrl form y' = y - b W cn us mthods of clculus to solv diffrntil qutions of

More information

Chap 2: Reliability and Availability Models

Chap 2: Reliability and Availability Models Chap : lably ad valably Modls lably = prob{s s fully fucog [,]} Suppos from [,] m prod, w masur ou of N compos, of whch N : # of compos oprag corrcly a m N f : # of compos whch hav fald a m rlably of h

More information

Walk Like a Mathematician Learning Task:

Walk Like a Mathematician Learning Task: Gori Dprtmnt of Euction Wlk Lik Mthmticin Lrnin Tsk: Mtrics llow us to prform mny usful mthmticl tsks which orinrily rquir lr numbr of computtions. Som typs of problms which cn b on fficintly with mtrics

More information