Genralised Floquet Time Crystal Systems I. INTRODUCTION

Size: px
Start display at page:

Download "Genralised Floquet Time Crystal Systems I. INTRODUCTION"

Transcription

1 Gerlsed Floquet Tme Crystl ystems Gutm Kmlr N Physcs Deprtmet, Id Isttute of Techology (Brs Hdu Uversty), Vrs - 005, Id Ktsur Lbortory, Deprtmet of Physcs, Uversty of Toyo, Hogo, Buyo-u, Toyo , Jp (Dted: 9 August 07) Tme trsltol symmetry breg s possblty eplored oly the recet pst. I ths report, we frst revew pper by Else, Buer d Ny whch defes the oto of tme trsltol symmetry breg qutum systems d gves the lytcl d umercl study of sp ½ model tht shows ths behvor. ecodly we eted ths de to lytclly d umerclly show tht t s possble to hve tme trsltol symmetry breg hgher sp systems. I. INTRODUCTION A. poteous ymmetry Breg (B) poteous symmetry breg s process where symmetrc stte of system spoteously chges to symmetrc stte. Ths occurs whe the uderlyg lws of system obeys cert symmetry but the groud sttes or the low eergy sttes of the system do ot obey the sme symmetry. The smplest emple for ths pheomeo s tht of crystls. A volume of gs uform potetl hs cotuous trsltol symmetry. If ths system cools dow d suppose the gs ow crystlles, the, the system o more hs cotuous trsltol symmetry but ow hs dscrete trsltol symmetry. Cotuous trsltol symmetry s sd to be broe ths cse. Aother emple s tht of the Isg model. The Isg Hmlto (for ch of sp ½ prtcles) H Isg J s symmetrc uder the smulteous flp of ll the sps of the system. I the ferromgetc cse ( J 0 ), there re low eergy sttes wth o-ero mgetto. Uder the cto of the symmetry (.e. uder sp-flp), we obt other low eergy sttes whch hve opposte mgetto. For fte chs, symmetrc d tsymmetrc superpostos of such sttes re the egesttes. These superpostos, lso ow s ct sttes, cot be dstgushed by y locl mesuremets d re etremely sestve to eterl felds. Eve ftesml felds cuse the system to decohere d gve stte wth mgetto log the eterl feld. B ths system my be defed terms of the low eergy egesttes beg ct sttes or to the developmet of mgetto o pplcto of ftesml eterl feld. There re my other emples of B prtcle physcs d codesed mtter physcs - guge symmetry breg, electromgetc guge symmetry breg, chrl symmetry breg d Euclde symmetry breg to me few. My emples we hve for B seems to suggest tht for every symmetry we c th of, we c come up wth system whch bres tht symmetry. I ths report we re terested tme trsltol symmetry breg. B. Tme Trsltol ymmetry Breg (TTB) The cocept of TTB ws frst descrbed by Frc Wlce 0 [] [3]. ystems whch bre tme trsltol symmetry hve bee clled Tme Crystls logy wth ordry crystls whch bre cotuous trsltol symmetry. The defto of TTB s ot strghtforwrd. As dscussed by Else, Buer d Ny (EBN) [], the most obvous defto d ts modfctos, ll bsed o the epectto vlues d correlto

2 fuctos of the therml equlbrum stte e H must be ruled out due to o-go theorems [4]. These theorems show tht t s mpossble to hve TTB equlbrum sttes d hece suggest the eed to eplore the possblty of hvg TTB o-equlbrum sttes. Eve the cse of symmetres other th tht of tme trslto, whe we cosder spoteously broe symmetres, we loo t oequlbrum systems whch show ergodcty breg d hve lfe tmes whch dverge wth the system se. It should be possble to hve systems whch show logous behvor for TTB. Tg these to cosderto the EBN pper gves two equvlet deftos of TTB. Cosderg Hmlto H ( t ) perodc wth perod T wth ts correspodg utry s U ( t, t ) for tme evoluto from tme t to tme t, TTB s defed s: TTB-: TTB occurs f for ech t, d for every stte ( t) wth short-rged correltos, there ests opertor such tht ( t T ) ( t T) ( t ) ( t), where ( t T ) U ( t T, t ) ( t ). TTB-: TTB occurs f the egesttes of the Floquet opertor U U( T, 0) cot be short-rge correlted. Here, stte s sd to hve short rge correltos f, for y locl opertor ( ), ( ) ( ) ( ) ( ) 0 s,.e. f cluster decomposto holds. Notce tht the Hmlto cosdered hs dscrete tme trsltol symmetry d ot cotuous tme trsltol symmetry. f II. MODEL OF TTB A. p ½ system The EBN pper gves my body locled system of oe dmesol sp ½ prtcles wth Floquet utry U ept H ep ept H f 0 j 0 j j j whch hs perod T t0. The utry hs two Hmltos ppled oe fter the other, the frst beg the whch whe ppled for perod effectvely flps ll the sps the ch bout j j the -drecto. The secod s my body locled Hmlto H whch gves Isg tercto coupled wth eterl mgetc feld log the -drecto wth perturbto cosdered log the - drecto,.e. 3 H J h h where J, h d h re uformly chose from J,, h 0, d h 0, h. Oly slghtly perturbed systems wth smll vlues of h re cosdered.

3 For o perturbto (.e. h 0 ), ths system c be lytclly solved to show tht TTB occurs. uppose we cosder tht {s } wth s re the egesttes of the opertors σ so tht { s} s { s}. As H commutes wth whe h 0, sttes {s } re lso egesttes of H wth the egevlues s H { s} E { s} E { s} { s} where we defe E { s } J s s d { } E s h s. Wth these ottos the egesttes of the Floquet opertor c be wrtte s: s ep t0e { s} { s} ep t0e { s} { s} The correspodg Floquet egevlues re ep { } t0e s. Notce tht the egesttes stsfy TTB-. To see tht TTB- s stsfed s well, we study the vrto of epectto vlues of wth tme: d U ep j j j j Let U ep t0 J h Cosderg s the tl stte, we hve U U U U UU tt f f t0, so tht U f UU. s U, 0 d, 0 for s, 0 Ths shows tht the epectto vlues of show osclltory behvor re perodc wth perod T hece verfyg tht TTB- s stsfed. The EBN pper goes o to rgue tht the bove behvor s see eve whe we perturbtos to the Floquet utry such s smll devtos the legth of pplcto of the flppg Hmlto from π d o-ero vlues of h do ot destroy TTB. The behvor of the system uder o ero vlues of h c be studed by smultg the systems. Ths system s smulted by usg tme-evolvg bloc decmto scheme (TEBD) [6] whch s dscussed the pped. Fg.. shows the dsorder verged epectto vlues of d over 00 dsorders for system se of L=0, h=0.3 d t 0 wth the sp flps doe stteously. The TEBD clcultos were doe wth Trotter step of 0.T d bod dmeso of 6. The lfetmes of the TTB observed the perturbed systems c be studed by smultg the system usg ect dgolto (ED). We defe mgetto Z(t) bsolute vlue of t. Fg.b. shows the vrto of the dsorder verged mgetto over 500 dsorders wth tme for system wth

4 h=0.3, t 0 d tl product stte polred log the -drecto for smll system ses. We c see tht the lfetmes dverge epoetlly wth the system ses. Fg.. Tme depedece of dsorder verged d for system of 0 sp ½ stes shows tht the osclltos of the former perssts whle tht of the ltter des dow N=4 N=5 N=6 N= Z(t) ^ 0^ 0^3 0^4 0^5 0^6 0^7 0^8 t/t Fg.b. The decy of dsorder verged mgetto Z(t) sp ½ system wth tme. I ths sp ½ system, we observed tht the epectto vlue of hd perod twce tht of the Hmlto. I ttempt to observe TTB wth the epectto vlue of some opertor hvg perod three tmes tht of the Hmlto, we study sp system.

5 B. p system We cosder oe-dmesol sp system wth Floquet opertor smlr to the oe cosdered the sp ½ system. We use the followg otto for the opertors. The mtr form of the opertors re epressed by cosderg the stdrd bss ep The Floquet utry s 0 0 ep where e 3 U ept H ep ept H f Alogous to the p ½ cse, the Floquet utry hs two Hmltos ppled oe fter the other wth totl perod of T t 0 3. Frst the Hmlto ppled for perod 3 cycles every sp the ch betwee the sttes wth mgetto log the -drecto beg, 0 d - (referred to s cyclg of sps). Ths s wy the log of sp flp sp ½ systems. Ths s followed by the Hmlto H gve by: H J h h where J, h d h re uformly chose from,, d J h 0, h 0, h 3. The frst prt of the Hmlto s the tercto term d the secod prt s tht of the eterl mgetc feld log the -drecto wth perturbto log the -drecto. Ths specfc tercto term s chose out of the my possbltes of the tercto terms sp systems becuse ths tercto term s vrt uder the cyclg of sps whch s vtl for the d of behvor we wsh to hve the system. Just s the sp ½ cse, ths system c be solved lytclly for o perturbtos.e. h=0 d t c be proved tht TTB occurs. Cosder the egesttes of s { } s,0, such tht s wth. For h=0, we hve H { s } E { s } E { s } { s } { s } s { s } where s s { } Re d E { s} h s E s J. We defe the cyclg opertor wth

6 the followg set of equtos: 0, 0, d s s for d. Usg the otto {,,3} d E s E { s } E { s} 3, the Floquet egesttes re s ep t E { s} { s} ep t E { s } { s } ep t E { s } { s } wth the egevlues ep { } epectto vlues of t0e s. These egesttes stsfy TTB-. The vrto of wth tme c be foud s follows: Let U ep t0 J U f d U U U. Cosderg s the tl stte, we hve U U U U UU tt f f t 0 ep 3, so tht s U, 0 d, 0 for s ce, we get the result 3 whch shows tht the epectto vlues of Hece TTB- s stsfed for ths system. Im 3 tt t 0 re perodc wth perod thrce tht of the Hmlto. Whe perturbtos to the system re cosdered, the behvor of the system my be studed by smultos. The system s smulted by usg TEBD. Fg.. shows the dsorder verged epectto vlues of d over 67 dsorders for system se of L=50, h=0.3 d t 0 wth the cyclg of sps doe stteously. The TEBD clcultos were doe wth Trotter step of 0.T d bod dmeso of 0. We see tht the TTB behvor s stll see the system. To study the lfetme of TTB the system, we smulte t usg ED. Here we defe mgetto Z(t) s the mmum vlue of the bsolute vlue of t the tme tervl t to t+t. Fg.b. shows the vrto of the dsorder verged mgetto over 500 dsorders, wth tme for system wth h=0.3, t 0 d tl product stte polred log the -drecto for smll system ses. Notce tht just s the cse of the sp ½ systems, the lfetmes dverge epoetlly wth the system se but the decy of mgetto s ot s steep.

7 Fg.. Tme depedece of dsorder verged d for system of 50 sp stes N=4 N=5 N=6 N=7 Z(t) ^ 0^ 0^3 0^4 0^5 0^6 0^7 0^8 t/t Fg.b. The decy of the dsorder verged mgetto Z(t) sp system wth tme.

8 C. p system The TTB model of sp system proposed c be turlly eteded to sp systems. We use the followg ottos ( ) ( ) d where d d e d The Floquet utry d the my body loclsed Hmlto cosdered re smlr structure to tht cosdered the sp cse. U ep t H f 0 where H J h h To show tht the system s fct model of TTB, we fd the vrto of epectto vlue of tme., b d ( b ) b d d U f U f U U UU t T s t0 wth s U, 0 d, 0 for Hece we hve d b tt d, b ( ) b to

9 Here g we c see tht the epectto vlues of re perodc (by substtutg =d) wth perod d tmes the perod of the Hmlto hece stsfyg TTB-. Fg.. shows the epectto vlues of d for system wth =3/ d = respectvely d hvg system se of L=50, h=0 d t 0 wth the cyclg of sps doe stteously. The TEBD clcultos were doe wth Trotter step of 0.T d bod dmeso of 4 d 5 respectvely. Fg.3. Tme depedece of d (bottom pel) stes wth o perturbtos. for system of 50 sp 3 (top pel) d sp

10 III. ACKNOWLEDGEMENT Frst d foremost I would le to th Professor Hosho Ktsur for gvg me the opportuty to wor hs lb, for hs ptet gudce d hs vluble sght durg dscussos. I would lso le to th hot Tmur for hs support d ssstce wth the project, Yut Ag, Nobuyu Yosho d the other members of the lb for ther hosptlty, fellow UTRIP studet Ze Ross for the my frutful dscussos d for shrg the project, d Tsh Mor for hs commets d suggestos regrdg the project. I would lso le to eted my grttude to Uversty of Toyo's Grdute chool of cece for ther geerous scholrshp d the ILO for orgg d helpg me throughout the progrm. Apped: Tme Evolvg Bloc Decmto (TEBD) TEBD s lgorthm used to effcetly smulte the tme evoluto of qutum systems whch hve low log rge etglemet throughout the perod for whch t s evolved. Geerlly low eergy sttes of qutum systems follow re lw of etglemet etropy (.e. the etglemet etropy scles lerly wth the se of boudry of the system) [7] whle hgher eergy sttes follow the volume lw of etglemet. But my body loclsed systems, eve hgher eergy sttes follow re lw of etglemet whch mples tht ll sttes my body loclsed system hve oly short rge correltos. Ths llows for my body loclsed systems to be effcetly smulted by TEBD. Vdl hs gve comprehesve method of mplemetg TEBD [6]. The tl stte epressed the mtr product stte (MP) form s:......,...,,..., [] [] [] [] [ ], where {,,..., } d... represets the sp orthoorml bss of sp system. For short-rge correlted sttes, the compoets of vectors fll epoetlly [5]. Eplotg ths fct c led to sgfct decrese the storge spce d provde speed up the clcultos requred to smulte these systems. The umber of sgfct vlues of cosdered s te to be. For smultg the system wth ero error, the vlue of tht eeds to be cosdered s the chmdt r of the system. The evoluto of the system hvg Hmltos wth sgle sp tercto or eghborg sp terctos s reltvely smple ths method. gle sp terctos re crred out by updtg just the pproprte tesor. Cosderg U s the utry correspodg to the Hmlto ctg o the lth [ l ] [ l ] sp, the updted tesor s gve by. The computtol cost for the opertos volved s Ø( ) bsc opertos. U j The evoluto of the system wth eghborg sp terctos c be crred out by updtg the correspodg two tesors d the correspodg vector. The computtol cost for crryg out ll 3 the clcultos volved s Ø( ).

11 Hece usg TEBD, computto whose complety would hve scled epoetlly wth the umber of sps f doe covetolly, c be doe wth complety of polyoml of whch tur grows s polyoml of the umber of sps f there s low log rge etglemet. Refereces [] Else, D. V., Buer, B. & Ny, C. Floquet tme crystls. Phys. Rev. Lett. 7, (06). [] F. Wlce, Phys. Rev. Lett. 09, 6040 (0). [3] A. hpere d F. Wlce, Phys. Rev. Lett. 09, 6040 (0). [4] H. Wtbe d M. Oshw, Phys. Rev. Lett. 4, 5603 (05). [5] G. Vdl, Physcl Revew Letters 93, (004). [6] G. Vdl, Phys. Rev. Lett. 9, 4790 (003). [7] Esert, J., M. Crmer, d M. B. Pleo, Rev. Mod. Phys. 8, 77 (00).

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases Itertol Jourl of Advced Reserch Physcl Scece (IJARPS) Volume, Issue 5, September 204, PP 6-0 ISSN 2349-7874 (Prt) & ISSN 2349-7882 (Ole) www.rcourls.org Alytcl Approch for the Soluto of Thermodymc Idettes

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 Mtr Trsformtos usg Egevectors September 8, Mtr Trsformtos Usg Egevectors Lrry Cretto Mechcl Egeerg A Semr Egeerg Alyss September 8, Outle Revew lst lecture Trsformtos wth mtr of egevectors: = - A ermt

More information

Available online through

Available online through Avlble ole through wwwmfo FIXED POINTS FOR NON-SELF MAPPINGS ON CONEX ECTOR METRIC SPACES Susht Kumr Moht* Deprtmet of Mthemtcs West Begl Stte Uverst Brst 4 PrgsNorth) Kolt 76 West Begl Id E-ml: smwbes@yhoo

More information

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini DATA FITTING Itesve Computto 3/4 Als Mss Dt fttg Dt fttg cocers the problem of fttg dscrete dt to obt termedte estmtes. There re two geerl pproches two curve fttg: Iterpolto Dt s ver precse. The strteg

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ] Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles

More information

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11:

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11: Soo Kg Lm 1.0 Nested Fctorl Desg... 1.1 Two-Fctor Nested Desg... 1.1.1 Alss of Vrce... Exmple 1... 5 1.1. Stggered Nested Desg for Equlzg Degree of Freedom... 7 1.1. Three-Fctor Nested Desg... 8 1.1..1

More information

Section 7.2 Two-way ANOVA with random effect(s)

Section 7.2 Two-way ANOVA with random effect(s) Secto 7. Two-wy ANOVA wth rdom effect(s) 1 1. Model wth Two Rdom ffects The fctors hgher-wy ANOVAs c g e cosdered fxed or rdom depedg o the cotext of the study. or ech fctor: Are the levels of tht fctor

More information

MATRIX AND VECTOR NORMS

MATRIX AND VECTOR NORMS Numercl lyss for Egeers Germ Jord Uversty MTRIX ND VECTOR NORMS vector orm s mesure of the mgtude of vector. Smlrly, mtr orm s mesure of the mgtude of mtr. For sgle comoet etty such s ordry umers, the

More information

CURVE FITTING LEAST SQUARES METHOD

CURVE FITTING LEAST SQUARES METHOD Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued

More information

Lecture 3-4 Solutions of System of Linear Equations

Lecture 3-4 Solutions of System of Linear Equations Lecture - Solutos of System of Ler Equtos Numerc Ler Alger Revew of vectorsd mtrces System of Ler Equtos Guss Elmto (drect solver) LU Decomposto Guss-Sedel method (tertve solver) VECTORS,,, colum vector

More information

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be

More information

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University Advced Algorthmc Prolem Solvg Le Arthmetc Fredrk Hetz Dept of Computer d Iformto Scece Lköpg Uversty Overvew Arthmetc Iteger multplcto Krtsu s lgorthm Multplcto of polyomls Fst Fourer Trsform Systems of

More information

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is Mth Sprg 08 L Approxmtg Dete Itegrls I Itroducto We hve studed severl methods tht llow us to d the exct vlues o dete tegrls However, there re some cses whch t s ot possle to evlute dete tegrl exctly I

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

Chapter Unary Matrix Operations

Chapter Unary Matrix Operations Chpter 04.04 Ury trx Opertos After redg ths chpter, you should be ble to:. kow wht ury opertos mes,. fd the trspose of squre mtrx d t s reltoshp to symmetrc mtrces,. fd the trce of mtrx, d 4. fd the ermt

More information

Chapter 7. Bounds for weighted sums of Random Variables

Chapter 7. Bounds for weighted sums of Random Variables Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout

More information

MTH 146 Class 7 Notes

MTH 146 Class 7 Notes 7.7- Approxmte Itegrto Motvto: MTH 46 Clss 7 Notes I secto 7.5 we lered tht some defte tegrls, lke x e dx, cot e wrtte terms of elemetry fuctos. So, good questo to sk would e: How c oe clculte somethg

More information

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl Alyss for Egeers Germ Jord Uversty ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl soluto of lrge systems of ler lgerc equtos usg drect methods such s Mtr Iverse, Guss

More information

MATH2999 Directed Studies in Mathematics Matrix Theory and Its Applications

MATH2999 Directed Studies in Mathematics Matrix Theory and Its Applications MATH999 Drected Studes Mthemtcs Mtr Theory d Its Applctos Reserch Topc Sttory Probblty Vector of Hgher-order Mrkov Ch By Zhg Sho Supervsors: Prof. L Ch-Kwog d Dr. Ch Jor-Tg Cotets Abstrct. Itroducto: Bckgroud.

More information

Chapter Linear Regression

Chapter Linear Regression Chpte 6.3 Le Regesso Afte edg ths chpte, ou should be ble to. defe egesso,. use sevel mmzg of esdul cte to choose the ght cteo, 3. deve the costts of le egesso model bsed o lest sques method cteo,. use

More information

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector evel-2 BS trx-vector opertos wth 2 opertos sequetlly BS-Notto: S --- sgle precso G E geerl mtrx V --- vector defes SGEV, mtrx-vector product: r y r α x β r y ther evel-2 BS: Solvg trgulr system x wth trgulr

More information

Acoustooptic Cell Array (AOCA) System for DWDM Application in Optical Communication

Acoustooptic Cell Array (AOCA) System for DWDM Application in Optical Communication 596 Acoustooptc Cell Arry (AOCA) System for DWDM Applcto Optcl Commucto ml S. Rwt*, Mocef. Tyh, Sumth R. Ktkur d Vdy Nll Deprtmet of Electrcl Egeerg Uversty of Nevd, Reo, NV 89557, U.S.A. Tel: -775-78-57;

More information

Chapter 1. Introduction. Fundamental Concepts. Introduction. Historical background. Historical background. Fundamental Concepts

Chapter 1. Introduction. Fundamental Concepts. Introduction. Historical background. Historical background. Fundamental Concepts Chpter udmetl Cocepts Lecture Notes Dr Mohd Afed Uverst Mlys Perls N67 te lemet Alyss Itroducto A or sometmes referred s M, hs ecome powerful tool for umercl soluto of wde rge of egeerg prolems A s computtol

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I Uversty o Hw ICS: Dscrete Mthemtcs or Computer Scece I Dept. Iormto & Computer Sc., Uversty o Hw J Stelovsy bsed o sldes by Dr. Be d Dr. Stll Orgls by Dr. M. P. Fr d Dr. J.L. Gross Provded by McGrw-Hll

More information

On a class of analytic functions defined by Ruscheweyh derivative

On a class of analytic functions defined by Ruscheweyh derivative Lfe Scece Jourl ;9( http://wwwlfescecestecom O clss of lytc fuctos defed by Ruscheweyh dervtve S N Ml M Arf K I Noor 3 d M Rz Deprtmet of Mthemtcs GC Uversty Fslbd Pujb Pst Deprtmet of Mthemtcs Abdul Wl

More information

Rendering Equation. Linear equation Spatial homogeneous Both ray tracing and radiosity can be considered special case of this general eq.

Rendering Equation. Linear equation Spatial homogeneous Both ray tracing and radiosity can be considered special case of this general eq. Rederg quto Ler equto Sptl homogeeous oth ry trcg d rdosty c be cosdered specl cse of ths geerl eq. Relty ctul photogrph Rdosty Mus Rdosty Rederg quls the dfferece or error mge http://www.grphcs.corell.edu/ole/box/compre.html

More information

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES Avlble ole t http://sc.org J. Mth. Comput. Sc. 4 (04) No. 05-7 ISSN: 97-507 SUM PROPERTIES OR THE K-UCAS NUMBERS WITH ARITHMETIC INDEXES BIJENDRA SINGH POOJA BHADOURIA AND OMPRAKASH SIKHWA * School of

More information

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION St Joh s College UPPER V Mthemtcs: Pper Lerg Outcome d ugust 00 Tme: 3 hours Emer: GE Mrks: 50 Modertor: BT / SLS INSTRUCTIONS ND INFORMTION Red the followg structos crefull. Ths questo pper cossts of

More information

Chapter Gauss-Seidel Method

Chapter Gauss-Seidel Method Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos

More information

Preliminary Examinations: Upper V Mathematics Paper 1

Preliminary Examinations: Upper V Mathematics Paper 1 relmr Emtos: Upper V Mthemtcs per Jul 03 Emer: G Evs Tme: 3 hrs Modertor: D Grgortos Mrks: 50 INSTRUCTIONS ND INFORMTION Ths questo pper sts of 0 pges, cludg swer Sheet pge 8 d Iformto Sheet pges 9 d 0

More information

POWERS OF COMPLEX PERSYMMETRIC ANTI-TRIDIAGONAL MATRICES WITH CONSTANT ANTI-DIAGONALS

POWERS OF COMPLEX PERSYMMETRIC ANTI-TRIDIAGONAL MATRICES WITH CONSTANT ANTI-DIAGONALS IRRS 9 y 04 wwwrppresscom/volumes/vol9issue/irrs_9 05pdf OWERS OF COLE ERSERIC I-RIIGOL RICES WIH COS I-IGOLS Wg usu * Q e Wg Hbo & ue College of Scece versty of Shgh for Scece d echology Shgh Ch 00093

More information

DISCRETE TIME MODELS OF FORWARD CONTRACTS INSURANCE

DISCRETE TIME MODELS OF FORWARD CONTRACTS INSURANCE G Tstsshvl DSCRETE TME MODELS OF FORWARD CONTRACTS NSURANCE (Vol) 008 September DSCRETE TME MODELS OF FORWARD CONTRACTS NSURANCE GSh Tstsshvl e-ml: gurm@mdvoru 69004 Vldvosto Rdo str 7 sttute for Appled

More information

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ]

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ] Atervtves The Itegrl Atervtves Ojectve: Use efte tegrl otto for tervtves. Use sc tegrto rules to f tervtves. Aother mportt questo clculus s gve ervtve f the fucto tht t cme from. Ths s the process kow

More information

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Ke Kreutz-Delgdo (Nuo Vscocelos) ECE 75A Wter 22 UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) (+ )+ 5) l H 2) + + H 6) 3) H, + 7)

More information

Metric Spaces: Basic Properties and Examples

Metric Spaces: Basic Properties and Examples 1 Metrc Spces: Bsc Propertes d Exmples 1.1 NTODUCTON Metrc spce s dspesble termedte course of evoluto of the geerl topologcl spces. Metrc spces re geerlstos of Euclde spce wth ts vector spce structure

More information

Graphing Review Part 3: Polynomials

Graphing Review Part 3: Polynomials Grphig Review Prt : Polomils Prbols Recll, tht the grph of f ( ) is prbol. It is eve fuctio, hece it is smmetric bout the bout the -is. This mes tht f ( ) f ( ). Its grph is show below. The poit ( 0,0)

More information

On Several Inequalities Deduced Using a Power Series Approach

On Several Inequalities Deduced Using a Power Series Approach It J Cotemp Mth Sceces, Vol 8, 203, o 8, 855-864 HIKARI Ltd, wwwm-hrcom http://dxdoorg/02988/jcms2033896 O Severl Iequltes Deduced Usg Power Seres Approch Lored Curdru Deprtmet of Mthemtcs Poltehc Uversty

More information

Sequences and summations

Sequences and summations Lecture 0 Sequeces d summtos Istructor: Kgl Km CSE) E-ml: kkm0@kokuk.c.kr Tel. : 0-0-9 Room : New Mleum Bldg. 0 Lb : New Egeerg Bldg. 0 All sldes re bsed o CS Dscrete Mthemtcs for Computer Scece course

More information

24 Concept of wave function. x 2. Ae is finite everywhere in space.

24 Concept of wave function. x 2. Ae is finite everywhere in space. 4 Cocept of wve fucto Chpter Cocept of Wve Fucto. Itroucto : There s lwys qutty sscocte wth y type of wves, whch vres peroclly wth spce te. I wter wves, the qutty tht vres peroclly s the heght of the wter

More information

COMPLEX NUMBERS AND DE MOIVRE S THEOREM

COMPLEX NUMBERS AND DE MOIVRE S THEOREM COMPLEX NUMBERS AND DE MOIVRE S THEOREM OBJECTIVE PROBLEMS. s equl to b d. 9 9 b 9 9 d. The mgr prt of s 5 5 b 5. If m, the the lest tegrl vlue of m s b 8 5. The vlue of 5... s f s eve, f s odd b f s eve,

More information

Union, Intersection, Product and Direct Product of Prime Ideals

Union, Intersection, Product and Direct Product of Prime Ideals Globl Jourl of Pure d Appled Mthemtcs. ISSN 0973-1768 Volume 11, Number 3 (2015), pp. 1663-1667 Reserch Id Publctos http://www.rpublcto.com Uo, Itersecto, Product d Drect Product of Prme Idels Bdu.P (1),

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter.4 Newton-Rphson Method of Solvng Nonlner Equton After redng ths chpter, you should be ble to:. derve the Newton-Rphson method formul,. develop the lgorthm of the Newton-Rphson method,. use the Newton-Rphson

More information

European Journal of Mathematics and Computer Science Vol. 3 No. 1, 2016 ISSN ISSN

European Journal of Mathematics and Computer Science Vol. 3 No. 1, 2016 ISSN ISSN Euroe Jour of Mthemtcs d omuter Scece Vo. No. 6 ISSN 59-995 ISSN 59-995 ON AN INVESTIGATION O THE MATRIX O THE SEOND PARTIA DERIVATIVE IN ONE EONOMI DYNAMIS MODE S. I. Hmdov Bu Stte Uverst ABSTRAT The

More information

Integration by Parts for D K

Integration by Parts for D K Itertol OPEN ACCESS Jourl Of Moder Egeerg Reserc IJMER Itegrto y Prts for D K Itegrl T K Gr, S Ry 2 Deprtmet of Mtemtcs, Rgutpur College, Rgutpur-72333, Purul, West Begl, Id 2 Deprtmet of Mtemtcs, Ss Bv,

More information

Entropy ISSN by MDPI

Entropy ISSN by MDPI Etropy 2003, 5, 233-238 Etropy ISSN 1099-4300 2003 by MDPI www.mdp.org/etropy O the Measure Etropy of Addtve Cellular Automata Hasa Aı Arts ad Sceces Faculty, Departmet of Mathematcs, Harra Uversty; 63100,

More information

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1.

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1. SPECIAL MATRICES SYMMETRIC MATRICES Def: A mtr A s symmetr f d oly f A A, e,, Emple A s symmetr Def: A mtr A s skew symmetr f d oly f A A, e,, Emple A s skew symmetr Remrks: If A s symmetr or skew symmetr,

More information

under the curve in the first quadrant.

under the curve in the first quadrant. NOTES 5: INTEGRALS Nme: Dte: Perod: LESSON 5. AREAS AND DISTANCES Are uder the curve Are uder f( ), ove the -s, o the dom., Prctce Prolems:. f ( ). Fd the re uder the fucto, ove the - s, etwee,.. f ( )

More information

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Nuo Vscocelos (Ke Kreutz-Delgdo) UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) = (+ )+ 5) H 2) + = + H 6) = 3) H, + = 7) ( ) = (

More information

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields Lecture 38 (Trpped Prticles) Physics 6-01 Sprig 018 Dougls Fields Free Prticle Solutio Schrödiger s Wve Equtio i 1D If motio is restricted to oe-dimesio, the del opertor just becomes the prtil derivtive

More information

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares Itertol Jourl of Scetfc d Reserch Publctos, Volume, Issue, My 0 ISSN 0- A Techque for Costructg Odd-order Mgc Squres Usg Bsc Lt Squres Tomb I. Deprtmet of Mthemtcs, Mpur Uversty, Imphl, Mpur (INDIA) tombrom@gml.com

More information

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions HK Km Slghtly moded //9 /8/6 Frstly wrtte t Mrch 5 Itertve Methods er Systems: Guss-Sedel Noler Systems Cse Study: Chemcl Rectos Itertve or ppromte methods or systems o equtos cosst o guessg vlue d the

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Fll 4 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

Introduction to mathematical Statistics

Introduction to mathematical Statistics Itroducto to mthemtcl ttstcs Fl oluto. A grou of bbes ll of whom weghed romtely the sme t brth re rdomly dvded to two grous. The bbes smle were fed formul A; those smle were fed formul B. The weght gs

More information

On Solution of Min-Max Composition Fuzzy Relational Equation

On Solution of Min-Max Composition Fuzzy Relational Equation U-Sl Scece Jourl Vol.4()7 O Soluto of M-Mx Coposto Fuzzy eltol Equto N.M. N* Dte of cceptce /5/7 Abstrct I ths pper, M-Mx coposto fuzzy relto equto re studed. hs study s geerlzto of the works of Ohsto

More information

Xidian University Liu Congfeng Page 1 of 22

Xidian University Liu Congfeng Page 1 of 22 Rdom Sgl rocessg Chpter Expermets d robblty Chpter Expermets d robblty Cotets Expermets d robblty.... Defto of Expermet..... The Smple Spce..... The Borel Feld...3..3 The robblty Mesure...3. Combed Expermets...5..

More information

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b CS 70 Dscrete Mathematcs ad Probablty Theory Fall 206 Sesha ad Walrad DIS 0b. Wll I Get My Package? Seaky delvery guy of some compay s out delverg packages to customers. Not oly does he had a radom package

More information

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS . REVIEW OF PROPERTIES OF EIGENVLUES ND EIGENVECTORS. EIGENVLUES ND EIGENVECTORS We hll ow revew ome bc fct from mtr theory. Let be mtr. clr clled egevlue of f there et ozero vector uch tht Emle: Let 9

More information

ScienceDirect. About Verification of Discrete-Continual Finite Element Method of Structural Analysis. Part 2: Three-Dimensional Problems

ScienceDirect. About Verification of Discrete-Continual Finite Element Method of Structural Analysis. Part 2: Three-Dimensional Problems Avlle ole t wwwscecedrectcom SceceDrect Proced Egeerg 9 (04 4 9 XXIII R-S-P semr heoretcl Foudto of Cvl Egeerg (RSP (FoCE 04 Aout Verfcto of Dscrete-Cotul Fte Elemet Method of Structurl Alyss Prt : hree-dmesol

More information

Investigating Cellular Automata

Investigating Cellular Automata Researcher: Taylor Dupuy Advsor: Aaro Wootto Semester: Fall 4 Ivestgatg Cellular Automata A Overvew of Cellular Automata: Cellular Automata are smple computer programs that geerate rows of black ad whte

More information

Bond Additive Modeling 5. Mathematical Properties of the Variable Sum Exdeg Index

Bond Additive Modeling 5. Mathematical Properties of the Variable Sum Exdeg Index CROATICA CHEMICA ACTA CCACAA ISSN 00-6 e-issn -7X Crot. Chem. Act 8 () (0) 9 0. CCA-5 Orgl Scetfc Artcle Bod Addtve Modelg 5. Mthemtcl Propertes of the Vrble Sum Edeg Ide Dmr Vukčevć Fculty of Nturl Sceces

More information

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS Jourl of Algebr Nuber Theory: Advces d Applctos Volue 6 Nuber 6 ges 85- Avlble t http://scetfcdvces.co. DOI: http://dx.do.org/.864/t_779 ON NILOTENCY IN NONASSOCIATIVE ALGERAS C. J. A. ÉRÉ M. F. OUEDRAOGO

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

EFFECT OF CRACK PARAMETERS ON FREE VIBRATIONS OF THE BERNOULLI-EULER BEAM

EFFECT OF CRACK PARAMETERS ON FREE VIBRATIONS OF THE BERNOULLI-EULER BEAM Jourl of Appled themtcs d Computtol echcs 05 () 67-7 www.mcm.pcz.pl p-in 99-9965 DOI: 0.75/jmcm.05..7 e-in 353-0588 EFFECT OF CRACK PARAETER ON FREE VIBRATION OF THE BERNOULLI-EULER BEA Izbel Zmorsk Dwd

More information

Differential Method of Thin Layer for Retaining Wall Active Earth Pressure and Its Distribution under Seismic Condition Li-Min XU, Yong SUN

Differential Method of Thin Layer for Retaining Wall Active Earth Pressure and Its Distribution under Seismic Condition Li-Min XU, Yong SUN Itertol Coferece o Mechcs d Cvl Egeerg (ICMCE 014) Dfferetl Method of Th Lyer for Retg Wll Actve Erth Pressure d Its Dstrbuto uder Sesmc Codto L-M XU, Yog SUN Key Lbortory of Krst Evromet d Geologcl Hzrd

More information

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen.

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen. .5 x 54.5 a. x 7. 786 7 b. The raked observatos are: 7.4, 7.5, 7.7, 7.8, 7.9, 8.0, 8.. Sce the sample sze 7 s odd, the meda s the (+)/ 4 th raked observato, or meda 7.8 c. The cosumer would more lkely

More information

6.6 Moments and Centers of Mass

6.6 Moments and Centers of Mass th 8 www.tetodre.co 6.6 oets d Ceters of ss Our ojectve here s to fd the pot P o whch th plte of gve shpe lces horzotll. Ths pot s clled the ceter of ss ( or ceter of grvt ) of the plte.. We frst cosder

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

More information

6. Chemical Potential and the Grand Partition Function

6. Chemical Potential and the Grand Partition Function 6. Chemcl Potetl d the Grd Prtto Fucto ome Mth Fcts (see ppedx E for detls) If F() s lytc fucto of stte vrles d such tht df d pd the t follows: F F p lso sce F p F we c coclude: p I other words cross dervtves

More information

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y 4. Le Itegrls I ths secto we defe tegrl tht s smlr to sgle tegrl except tht sted of tegrtg over tervl [ ] we tegrte over curve. Such tegrls re clled le tegrls lthough curve tegrls would e etter termology.

More information

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek Optmlt of Strteges for Collpsg Expe Rom Vrles Smple Rom Smple E Stek troucto We revew the propertes of prectors of ler comtos of rom vrles se o rom vrles su-spce of the orgl rom vrles prtculr, we ttempt

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter 0.04 Newton-Rphson Method o Solvng Nonlner Equton Ater redng ths chpter, you should be ble to:. derve the Newton-Rphson method ormul,. develop the lgorthm o the Newton-Rphson method,. use the Newton-Rphson

More information

Patterns of Continued Fractions with a Positive Integer as a Gap

Patterns of Continued Fractions with a Positive Integer as a Gap IOSR Jourl of Mthemtcs (IOSR-JM) e-issn: 78-578, -ISSN: 39-765X Volume, Issue 3 Ver III (My - Ju 6), PP -5 wwwosrjourlsorg Ptters of Cotued Frctos wth Postve Iteger s G A Gm, S Krth (Mthemtcs, Govermet

More information

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS Course Project: Classcal Mechacs (PHY 40) Suja Dabholkar (Y430) Sul Yeshwath (Y444). Itroducto Hamltoa mechacs s geometry phase space. It deals

More information

A Brief Introduction to Olympiad Inequalities

A Brief Introduction to Olympiad Inequalities Ev Che Aprl 0, 04 The gol of ths documet s to provde eser troducto to olympd equltes th the stdrd exposto Olympd Iequltes, by Thoms Mldorf I ws motvted to wrte t by feelg gulty for gettg free 7 s o problems

More information

Schrödinger Equation Via Laplace-Beltrami Operator

Schrödinger Equation Via Laplace-Beltrami Operator IOSR Jourl of Mthemtics (IOSR-JM) e-issn: 78-578, p-issn: 39-765X. Volume 3, Issue 6 Ver. III (Nov. - Dec. 7), PP 9-95 www.iosrjourls.org Schrödiger Equtio Vi Lplce-Beltrmi Opertor Esi İ Eskitşçioğlu,

More information

4. Runge-Kutta Formula For Differential Equations

4. Runge-Kutta Formula For Differential Equations NCTU Deprme o Elecrcl d Compuer Egeerg 5 Sprg Course by Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos To solve e derel equos umerclly e mos useul ormul s clled Ruge-Ku ormul

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

Review of Linear Algebra

Review of Linear Algebra PGE 30: Forulto d Soluto Geosstes Egeerg Dr. Blhoff Sprg 0 Revew of Ler Alger Chpter 7 of Nuercl Methods wth MATLAB, Gerld Recktewld Vector s ordered set of rel (or cople) uers rrged s row or colu sclr

More information

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS Lecture Notes PH 4/5 ECE 598 A. L Ros INTRODUCTION TO QUANTUM MECHANICS CHAPTER-0 WAVEFUNCTIONS, OBSERVABLES d OPERATORS 0. Represettos the sptl d mometum spces 0..A Represetto of the wefucto the sptl

More information

The definite Riemann integral

The definite Riemann integral Roberto s Notes o Itegrl Clculus Chpter 4: Defte tegrls d the FTC Secto 4 The defte Rem tegrl Wht you eed to kow lredy: How to ppromte the re uder curve by usg Rem sums. Wht you c ler here: How to use

More information

18.413: Error Correcting Codes Lab March 2, Lecture 8

18.413: Error Correcting Codes Lab March 2, Lecture 8 18.413: Error Correctg Codes Lab March 2, 2004 Lecturer: Dael A. Spelma Lecture 8 8.1 Vector Spaces A set C {0, 1} s a vector space f for x all C ad y C, x + y C, where we take addto to be compoet wse

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

More information

PHYS Look over. examples 2, 3, 4, 6, 7, 8,9, 10 and 11. How To Make Physics Pay PHYS Look over. Examples: 1, 4, 5, 6, 7, 8, 9, 10,

PHYS Look over. examples 2, 3, 4, 6, 7, 8,9, 10 and 11. How To Make Physics Pay PHYS Look over. Examples: 1, 4, 5, 6, 7, 8, 9, 10, PHYS Look over Chapter 9 Sectos - Eamples:, 4, 5, 6, 7, 8, 9, 0, PHYS Look over Chapter 7 Sectos -8 8, 0 eamples, 3, 4, 6, 7, 8,9, 0 ad How To ake Phscs Pa We wll ow look at a wa of calculatg where the

More information

Bounds for the Connective Eccentric Index

Bounds for the Connective Eccentric Index It. J. Cotemp. Math. Sceces, Vol. 7, 0, o. 44, 6-66 Bouds for the Coectve Eccetrc Idex Nlaja De Departmet of Basc Scece, Humates ad Socal Scece (Mathematcs Calcutta Isttute of Egeerg ad Maagemet Kolkata,

More information

Rademacher Complexity. Examples

Rademacher Complexity. Examples Algorthmc Foudatos of Learg Lecture 3 Rademacher Complexty. Examples Lecturer: Patrck Rebesch Verso: October 16th 018 3.1 Itroducto I the last lecture we troduced the oto of Rademacher complexty ad showed

More information

MATH 247/Winter Notes on the adjoint and on normal operators.

MATH 247/Winter Notes on the adjoint and on normal operators. MATH 47/Wter 00 Notes o the adjot ad o ormal operators I these otes, V s a fte dmesoal er product space over, wth gve er * product uv, T, S, T, are lear operators o V U, W are subspaces of V Whe we say

More information

Random variables and sampling theory

Random variables and sampling theory Revew Rdom vrbles d smplg theory [Note: Beg your study of ths chpter by redg the Overvew secto below. The red the correspodg chpter the textbook, vew the correspodg sldeshows o the webste, d do the strred

More information

A conic cutting surface method for linear-quadraticsemidefinite

A conic cutting surface method for linear-quadraticsemidefinite A coc cuttg surface method for lear-quadratcsemdefte programmg Mohammad R. Osoorouch Calfora State Uversty Sa Marcos Sa Marcos, CA Jot wor wth Joh E. Mtchell RPI July 3, 2008 Outle: Secod-order coe: defto

More information

A New Measure of Probabilistic Entropy. and its Properties

A New Measure of Probabilistic Entropy. and its Properties Appled Mathematcal Sceces, Vol. 4, 200, o. 28, 387-394 A New Measure of Probablstc Etropy ad ts Propertes Rajeesh Kumar Departmet of Mathematcs Kurukshetra Uversty Kurukshetra, Ida rajeesh_kuk@redffmal.com

More information

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table.

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table. CURVE FITTING Obectve curve ttg s t represet set dscrete dt b uct curve. Csder set dscrete dt s gve tble. 3 3 = T use the dt eectvel, curve epress s tted t the gve dt set, s = + = + + = e b ler uct plml

More information

Linear Open Loop Systems

Linear Open Loop Systems Colordo School of Me CHEN43 Trfer Fucto Ler Ope Loop Sytem Ler Ope Loop Sytem... Trfer Fucto for Smple Proce... Exmple Trfer Fucto Mercury Thermometer... 2 Derblty of Devto Vrble... 3 Trfer Fucto for Proce

More information

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula NCTU Deprme o Elecrcl d Compuer Egeerg Seor Course By Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos A. Euler Formul B. Ruge-Ku Formul C. A Emple or Four-Order Ruge-Ku Formul

More information

Continuous Distributions

Continuous Distributions 7//3 Cotuous Dstrbutos Radom Varables of the Cotuous Type Desty Curve Percet Desty fucto, f (x) A smooth curve that ft the dstrbuto 3 4 5 6 7 8 9 Test scores Desty Curve Percet Probablty Desty Fucto, f

More information

PROGRESSIONS AND SERIES

PROGRESSIONS AND SERIES PROGRESSIONS AND SERIES A sequece is lso clled progressio. We ow study three importt types of sequeces: () The Arithmetic Progressio, () The Geometric Progressio, () The Hrmoic Progressio. Arithmetic Progressio.

More information

Single Valued Neutrosophic Similarity Measures for Multiple Attribute Decision-Making

Single Valued Neutrosophic Similarity Measures for Multiple Attribute Decision-Making 48 Neutrosophc ets d ystems Vol. 2 204 gle Vlued Neutrosophc mlrty Mesures for Multple ttrbute Decso-Mkg Ju Ye d Qsheg Zhg 2 Deprtmet of Electrcl d formto Egeerg hog Uversty 508 Hucheg West Rod hog Zheg

More information

Chem 253A. Crystal Structure. Chem 253B. Electronic Structure

Chem 253A. Crystal Structure. Chem 253B. Electronic Structure Chem 53, UC, Bereley Chem 53A Crystl Structure Chem 53B Electroic Structure Chem 53, UC, Bereley 1 Chem 53, UC, Bereley Electroic Structures of Solid Refereces Ashcroft/Mermi: Chpter 1-3, 8-10 Kittel:

More information

Section 6.3: Geometric Sequences

Section 6.3: Geometric Sequences 40 Chpter 6 Sectio 6.: Geometric Sequeces My jobs offer ul cost-of-livig icrese to keep slries cosistet with ifltio. Suppose, for exmple, recet college grdute fids positio s sles mger erig ul slry of $6,000.

More information

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS Lecture Notes PH 4/5 ECE 598 A. L Ros INTRODUCTION TO QUANTUM MECHANICS CHAPTER- WAVEFUNCTIONS, OBSERVABLES d OPERATORS. Represettos the sptl d mometum spces..a Represetto of the wvefucto the sptl coordtes

More information