Factorization of 15 on an NMR quantum computer

Size: px
Start display at page:

Download "Factorization of 15 on an NMR quantum computer"

Transcription

1 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Studet Presettio Fctoriztio of 15 o NMR qutum computer Bsed o L. M. K. Vdersype, M. Steffe, G. Breyt, C. S. Yoi, M.. Sherwood, I. L. Chug, Eperimetl reliztio of Shor s qutum fctorig lgorithm usig ucler mgetic resoce, Nture 414 (001) D-PYS, Qutum Systems For Iformtio Processig (QSIT) FS 013/

2 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, 013 / 1 Motivtio Prime Fctoriztio - Clssiclly O( l/3 ) - Shor O(l 3 ) Fctoriztio of lrge primes (such s ecryptio keys) fesible o idel qutum computer Wht bout Shor s lgorithm o ctul qutum computers? 15 fctorized usig compiled lgorithms - 001: Nucler spis o molecule [1] - 009: Photos itegrted o chip [] - 01: Phse of Josephso juctios [3] s well s 1-01: Photos [4]

3 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Fctoriztio of 15 usig Shor s lgorithm 1 f () = mod 15 - Possible = [,, 4,,, 7, 8,,, 11,, 13, 14] Fid period r i of f () - mod 15 = 1 for = [4, 11, 14] r = - 4 mod 15 = 1 for = [, 7, 8, 13] r = 4 3 gcd( r ± 1, 15) - gcd(11 ± 1, 15) = [gcd(10, 15), gcd(1, 15)] = [5, 3] - gcd( 4 ± 1, 15) = [gcd( 3, 15), gcd( 5, 15)] = [3, 5] Lrgest period of r is 4

4 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Qutum Implemettio m iit clculte f() clculte r 1 3 0> Iverse QFT 1> 1 mod N Period fidig i by iverse QFT Prlleliztio - Qbits i superpositio sttes to store d f () - Epoetil sclig of ilbert spce Clssiclly epoetil problem rus i polyomil time Emple: N = 15, = 11 r = 3 qbits for, 4 qbits for m = { } 1 + { } 11 3 { } 1 delt comb delt comb + { 0 4 } 11 smple shift lier phse Redout of 3 o results i superpositio of 0 d 4, i.e. 000 d 100 see lso lecture otes (the lst few slides, but vlues bove for m represet ctul f() vlue.)

5 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 NMR Qutum Computtio Bsics [5] Qbits - Esemble of distiguishble d coupled ucler spis - Coherece times > 1 sec - ighly mied groud stte, E kt 1 Gtes - Sigle Qbit - Spi-selective RF pulses, σ, σ y or combitio, 0. - ms (d composite σ z ) - Double Qbit - Cotrolled phse by evolutio uder J for t = 1 J 5 10 ms Redout - Wek esemble mesuremet of σ d σ y F F F e 7 13 C C 5 5 (CO) F spectrum 1 C J coupligs o 1 5 Zeem terms + chem. shift [z] Iterspi terms

6 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Qutum Circuit for NMR Qbit ssigmet (N = 15) - r m = 4 requires = qbits for sufficiet, 3 qbits chose for ep - m requires log (N) qbits Iitiliztio - Temporl vergig for pseudopure stte Optimiztios - Gtes reduced for f () = mod N compiled circuits for = 11 d = 7 m 1: : 3: 4: 5: 6: 7: m T e m p or l iit clculte f() clculte r 1 3 0> Iverse QFT 1> 1 mod N v e r g i g A B C D E F G o o Specific optimiztios to reduce gtes 90 Temporl vergig: Cretio of pseudopure stte qbit swppig + vergig F F F e 7 13 C C 5 5 (CO) 1 C 36 5

7 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Pulse Sequece iit clculte f() clculte r 300+ pulses - π -pulses - Gussi-shped profile - Compestio of J Selective ecittio - either or CNOT = -CPASE- - π-pulses - ermite-shped profile - Compestio of J 1: : 3: 4: 5: 6: 7: 1: : 3: T e m p or l v e r g i g A B C D E F G Selective refocusig - to rewid J, where uwted - z-rottios - Used for f() d iqft 4: 5: 6: 7: (0) (1) () (3) 00 ms 400 ms 10 ms

8 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Pulse Sequece 300+ pulses - π -pulses - Gussi-shped profile - Compestio of J Selective ecittio F spectrum J coupligs o [z] J refocused durig free evolutio J compested uder RF pulse - either or CNOT = -CPASE- - π-pulses - ermite-shped profile - Compestio of J 1: : 3: Selective refocusig - to rewid J, where uwted - z-rottios - Used for f() d iqft 4: 5: 6: 7: (0) (1) () (3) 00 ms 400 ms 10 ms

9 Fctoriztio of 15 usig NMR Itroductio Adri Doll QSIT Studet Presettio NMR ep My 31, 013 Summry 8 / 1 Refereces Results for = 11 Epected result: { 0 i + i + 4 i + 6 i} 1 i + { 1 i + 3 i + 5 i + 7 i} 1 1 i 0> m 1> 1 1 Iverse QFT 3 mod N 3 { 0 i + 4 i} 1 i + { 0 i 4 i} 1 1 i therml Alysis of Spectr: For two spis I d S i pseudo-pure sttes d b, upo π pulse to I pseudo pure b obs ( 1 ) (I + ( 1 ) I Sz ) sim spectrl phse revels stte of observer spi ctul spectrl lie depeds o stte of coupled spi here: severl spectrl peks due to multiple spis detectio of observer spi stte vi spectrl phse desired superpositio of i d i, i.e. 0 i d 4 i + rtefcts ep sim + dec

10 Fctoriztio of 15 usig NMR Itroductio Adri Doll QSIT Studet Presettio NMR ep My 31, 013 Summry 9 / 1 Refereces Results for = 7 Epected result: 0> m 1> 1 1 Iverse QFT 3 mod N { 0 i + 4 i} 1 i + { 1 i + 5 i} 7 i + { i + 6 i} 4 i + { 3 i + 7 i} 1 3 i 3 { 0 i + i + 4 i + 6 i} 1 i + { 0 i i i 4 i + i 6 i} 7 i + { 0 i i + 4 i 6 i} 4 i therml pseudo pure + { 0 i + i i 4 i i 6 i} 1 3 i Alysis of Spectr: detectio of observer spi stte vi spectrl phse desired superpositio of i i i i i.e. 0 i, i, 4 i, 6 i + eve more proouced rtefcts sim ep sim + dec

11 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Summry Successful i-priciple demostrtio Clcultio of f () = mod N epesive Compiled/optimized lgoritm, bsed o kow d r Simplest cse lredy proe to decoherece Eperimetl reliztio very demdig Mi resos: - Number of qbits - 3 log (N) for full-scle implemettio - Number of gtes - ( + 1)/ for iqft plus wy more for modulr epoetitio (Fctoriztio of N = 1 usig photos [4] ws chieved by itertive decompositio of the iqft. The eecutio time ws therefore icresed, wheres oly oe qbit ws required for )

12 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Refereces [1] L. M. K. Vdersype, M. Steffe, G. Breyt, C. S. Yoi, M.. Sherwood, I. L. Chug, Eperimetl reliztio of Shor s qutum fctorig lgorithm usig ucler mgetic resoce, Nture 414 (001) [] A. Politi, J. C. F. Mtthews, J. L. O Brie, Shors qutum fctorig lgorithm o photoic chip, Sciece 35 (5945) (009) 11. [3] E. Lucero, R. Breds, Y. Che, J. Kelly, M. Mritoi, A. Megrt, P. O Mlley, D. Sk, A. Visecher, J. Weer, T. White, Y. Yi, A. N. Cleld, J. M. Mrtiis, Computig prime fctors with Josephso phse qubit qutum processor, Nt Phys 8 (01) [4] E. Mrti-Lopez, A. Lig, T. Lwso, R. Alvrez, X.-Q. Zhou, J. L. O Brie, Eperimetl reliztio of Shor s qutum fctorig lgorithm usig qubit recyclig, Nt Photo 6 (01) [5] J. A. Joes, Qutum computig with NMR, Prog Nucl Mg Res Sp 59 () (011) Figures dopted from [1] or lecture slides D-PYS, Qutum Systems For Iformtio Processig (QSIT) FS 013/

13 Fctoriztio of 15 usig NMR Adri Doll QSIT Studet Presettio My 31, / 1 Questios? D-PYS, Qutum Systems For Iformtio Processig (QSIT) FS 013/

Advanced Algorithmic Problem Solving Le 6 Math and Search

Advanced Algorithmic Problem Solving Le 6 Math and Search Advced Algorithmic Prolem Solvig Le Mth d Serch Fredrik Heitz Dept of Computer d Iformtio Sciece Liköpig Uiversity Outlie Arithmetic (l. d.) Solvig lier equtio systems (l. d.) Chiese remider theorem (l.5

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I ICS4: Discrete Mthemtics for Computer Sciece I Dept. Iformtio & Computer Sci., J Stelovsky sed o slides y Dr. Bek d Dr. Still Origils y Dr. M. P. Frk d Dr. J.L. Gross Provided y McGrw-Hill 3- Quiz. gcd(84,96).

More information

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS) Mthemtics Revisio Guides Itegrtig Trig, Log d Ep Fuctios Pge of MK HOME TUITION Mthemtics Revisio Guides Level: AS / A Level AQA : C Edecel: C OCR: C OCR MEI: C INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

More information

Fast Fourier Transform 1) Legendre s Interpolation 2) Vandermonde Matrix 3) Roots of Unity 4) Polynomial Evaluation

Fast Fourier Transform 1) Legendre s Interpolation 2) Vandermonde Matrix 3) Roots of Unity 4) Polynomial Evaluation Algorithm Desig d Alsis Victor Admchi CS 5-45 Sprig 4 Lecture 3 J 7, 4 Cregie Mello Uiversit Outlie Fst Fourier Trsform ) Legedre s Iterpoltio ) Vdermode Mtri 3) Roots of Uit 4) Polomil Evlutio Guss (777

More information

Particle in a Box. and the state function is. In this case, the Hermitian operator. The b.c. restrict us to 0 x a. x A sin for 0 x a, and 0 otherwise

Particle in a Box. and the state function is. In this case, the Hermitian operator. The b.c. restrict us to 0 x a. x A sin for 0 x a, and 0 otherwise Prticle i Box We must hve me where = 1,,3 Solvig for E, π h E = = where = 1,,3, m 8m d the stte fuctio is x A si for 0 x, d 0 otherwise x ˆ d KE V. m dx I this cse, the Hermiti opertor 0iside the box The

More information

Biomedical signal and image processing (Course ) Lect. 9. Signal parameter estimation and recognition.

Biomedical signal and image processing (Course ) Lect. 9. Signal parameter estimation and recognition. Biomedicl sigl d imge processig (Course 55-355-55) Lect. 9. Sigl prmeter estimtio d recogitio. Sttisticl ormultio. Additive white gussi oise (AWGN) model: r s(, ρ) + ; ρ ukow prmeter Sttisticll optiml

More information

Math 3B Midterm Review

Math 3B Midterm Review Mth 3B Midterm Review Writte by Victori Kl vtkl@mth.ucsb.edu SH 643u Office Hours: R 11:00 m - 1:00 pm Lst updted /15/015 Here re some short otes o Sectios 7.1-7.8 i your ebook. The best idictio of wht

More information

Improving XOR-Dominated Circuits by Exploiting Dependencies between Operands. Ajay K. Verma and Paolo Ienne. csda

Improving XOR-Dominated Circuits by Exploiting Dependencies between Operands. Ajay K. Verma and Paolo Ienne. csda Improvig XOR-Domited Circuits y Exploitig Depedecies etwee Operds Ajy K. Verm d Polo Iee csd Processor Architecture Lortory LAP & Cetre for Advced Digitl Systems CSDA Ecole Polytechique Fédérle de Luse

More information

Frequency-domain Characteristics of Discrete-time LTI Systems

Frequency-domain Characteristics of Discrete-time LTI Systems requecy-domi Chrcteristics of Discrete-time LTI Systems Prof. Siripog Potisuk LTI System descriptio Previous bsis fuctio: uit smple or DT impulse The iput sequece is represeted s lier combitio of shifted

More information

Merge Sort. Outline and Reading. Divide-and-Conquer. Divide-and-conquer paradigm ( 4.1.1) Merge-sort ( 4.1.1)

Merge Sort. Outline and Reading. Divide-and-Conquer. Divide-and-conquer paradigm ( 4.1.1) Merge-sort ( 4.1.1) Merge Sort 7 2 9 4 2 4 7 9 7 2 2 7 9 4 4 9 7 7 2 2 9 9 4 4 Merge Sort versio 1.3 1 Outlie d Redig Divide-d-coquer prdigm ( 4.1.1 Merge-sort ( 4.1.1 Algorithm Mergig two sorted sequeces Merge-sort tree

More information

EVALUATING DEFINITE INTEGRALS

EVALUATING DEFINITE INTEGRALS Chpter 4 EVALUATING DEFINITE INTEGRALS If the defiite itegrl represets re betwee curve d the x-xis, d if you c fid the re by recogizig the shpe of the regio, the you c evlute the defiite itegrl. Those

More information

Taylor Polynomials. The Tangent Line. (a, f (a)) and has the same slope as the curve y = f (x) at that point. It is the best

Taylor Polynomials. The Tangent Line. (a, f (a)) and has the same slope as the curve y = f (x) at that point. It is the best Tylor Polyomils Let f () = e d let p() = 1 + + 1 + 1 6 3 Without usig clcultor, evlute f (1) d p(1) Ok, I m still witig With little effort it is possible to evlute p(1) = 1 + 1 + 1 (144) + 6 1 (178) =

More information

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Dr. Hamid R. Rabiee Fall 2013

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Dr. Hamid R. Rabiee Fall 2013 Sigls & Systems Chpter 0: The Z-Trsform Adpted from: Lecture otes from MIT, Bighmto Uiversity Dr. Hmid R. Rbiee Fll 03 Lecture 5 Chpter 0 Lecture 6 Chpter 0 Outlie Itroductio to the -Trsform Properties

More information

Closed Newton-Cotes Integration

Closed Newton-Cotes Integration Closed Newto-Cotes Itegrtio Jmes Keeslig This documet will discuss Newto-Cotes Itegrtio. Other methods of umericl itegrtio will be discussed i other posts. The other methods will iclude the Trpezoidl Rule,

More information

Unit 1. Extending the Number System. 2 Jordan School District

Unit 1. Extending the Number System. 2 Jordan School District Uit Etedig the Number System Jord School District Uit Cluster (N.RN. & N.RN.): Etedig Properties of Epoets Cluster : Etedig properties of epoets.. Defie rtiol epoets d eted the properties of iteger epoets

More information

( ) k ( ) 1 T n 1 x = xk. Geometric series obtained directly from the definition. = 1 1 x. See also Scalars 9.1 ADV-1: lim n.

( ) k ( ) 1 T n 1 x = xk. Geometric series obtained directly from the definition. = 1 1 x. See also Scalars 9.1 ADV-1: lim n. Sclrs-9.0-ADV- Algebric Tricks d Where Tylor Polyomils Come From 207.04.07 A.docx Pge of Algebric tricks ivolvig x. You c use lgebric tricks to simplify workig with the Tylor polyomils of certi fuctios..

More information

Numbers (Part I) -- Solutions

Numbers (Part I) -- Solutions Ley College -- For AMATYC SML Mth Competitio Cochig Sessios v.., [/7/00] sme s /6/009 versio, with presettio improvemets Numbers Prt I) -- Solutios. The equtio b c 008 hs solutio i which, b, c re distict

More information

Student Success Center Elementary Algebra Study Guide for the ACCUPLACER (CPT)

Student Success Center Elementary Algebra Study Guide for the ACCUPLACER (CPT) Studet Success Ceter Elemetry Algebr Study Guide for the ACCUPLACER (CPT) The followig smple questios re similr to the formt d cotet of questios o the Accuplcer Elemetry Algebr test. Reviewig these smples

More information

lecture 16: Introduction to Least Squares Approximation

lecture 16: Introduction to Least Squares Approximation 97 lecture 16: Itroductio to Lest Squres Approximtio.4 Lest squres pproximtio The miimx criterio is ituitive objective for pproximtig fuctio. However, i my cses it is more ppelig (for both computtio d

More information

Prior distributions. July 29, 2002

Prior distributions. July 29, 2002 Prior distributios Aledre Tchourbov PKI 357, UNOmh, South 67th St. Omh, NE 688-694, USA Phoe: 4554-64 E-mil: tchourb@cse.ul.edu July 9, Abstrct This documet itroduces prior distributios for the purposes

More information

INTEGRATION IN THEORY

INTEGRATION IN THEORY CHATER 5 INTEGRATION IN THEORY 5.1 AREA AROXIMATION 5.1.1 SUMMATION NOTATION Fibocci Sequece First, exmple of fmous sequece of umbers. This is commoly ttributed to the mthemtici Fibocci of is, lthough

More information

Linear Algebra. Lecture 1 September 19, 2011

Linear Algebra. Lecture 1 September 19, 2011 Lier Algebr Lecture September 9, Outlie Course iformtio Motivtio Outlie of the course Wht is lier lgebr? Chpter. Systems of Lier Equtios. Solvig Lier Systems. Vectors d Mtrices Course iformtio Istructor:

More information

Quantum Simulation: Solving Schrödinger Equation on a Quantum Computer

Quantum Simulation: Solving Schrödinger Equation on a Quantum Computer Purdue Uiversity Purdue e-pubs Birc Poster Sessios Birc Naotechology Ceter 4-14-008 Quatum Simulatio: Solvig Schrödiger Equatio o a Quatum Computer Hefeg Wag Purdue Uiversity, wag10@purdue.edu Sabre Kais

More information

Quantum Computing Lecture 7. Quantum Factoring

Quantum Computing Lecture 7. Quantum Factoring Quatum Computig Lecture 7 Quatum Factorig Maris Ozols Quatum factorig A polyomial time quatum algorithm for factorig umbers was published by Peter Shor i 1994. Polyomial time meas that the umber of gates

More information

Analysis of Deutsch-Jozsa Quantum Algorithm

Analysis of Deutsch-Jozsa Quantum Algorithm Aalysis of Deutsch-Jozsa Quatum Algorithm Zhegju Cao Jeffrey Uhlma Lihua Liu 3 Abstract. Deutsch-Jozsa quatum algorithm is of great importace to quatum computatio. It directly ispired Shor s factorig algorithm.

More information

Topic 4 Fourier Series. Today

Topic 4 Fourier Series. Today Topic 4 Fourier Series Toy Wves with repetig uctios Sigl geertor Clssicl guitr Pio Ech istrumet is plyig sigle ote mile C 6Hz) st hrmoic hrmoic 3 r hrmoic 4 th hrmoic 6Hz 5Hz 783Hz 44Hz A sigle ote will

More information

 n. A Very Interesting Example + + = d. + x3. + 5x4. math 131 power series, part ii 7. One of the first power series we examined was. 2!

 n. A Very Interesting Example + + = d. + x3. + 5x4. math 131 power series, part ii 7. One of the first power series we examined was. 2! mth power series, prt ii 7 A Very Iterestig Emple Oe of the first power series we emied ws! + +! + + +!! + I Emple 58 we used the rtio test to show tht the itervl of covergece ws (, ) Sice the series coverges

More information

ELE B7 Power Systems Engineering. Symmetrical Components

ELE B7 Power Systems Engineering. Symmetrical Components ELE B7 Power Systems Egieerig Symmetrical Compoets Aalysis of Ubalaced Systems Except for the balaced three-phase fault, faults result i a ubalaced system. The most commo types of faults are sigle liegroud

More information

Approximate Integration

Approximate Integration Study Sheet (7.7) Approimte Itegrtio I this sectio, we will ler: How to fid pproimte vlues of defiite itegrls. There re two situtios i which it is impossile to fid the ect vlue of defiite itegrl. Situtio:

More information

is completely general whenever you have waves from two sources interfering. 2

is completely general whenever you have waves from two sources interfering. 2 MAKNG SENSE OF THE EQUATON SHEET terferece & Diffrctio NTERFERENCE r1 r d si. Equtio for pth legth differece. r1 r is completely geerl. Use si oly whe the two sources re fr wy from the observtio poit.

More information

1.3 Continuous Functions and Riemann Sums

1.3 Continuous Functions and Riemann Sums mth riem sums, prt 0 Cotiuous Fuctios d Riem Sums I Exmple we sw tht lim Lower() = lim Upper() for the fuctio!! f (x) = + x o [0, ] This is o ccidet It is exmple of the followig theorem THEOREM Let f be

More information

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory SMH Uit Polyomils, Epoets, Rdicls & Comple Numbers Notes.1 Number Theory .1 Addig, Subtrctig, d Multiplyig Polyomils Notes Moomil: A epressio tht is umber, vrible, or umbers d vribles multiplied together.

More information

Remarks: (a) The Dirac delta is the function zero on the domain R {0}.

Remarks: (a) The Dirac delta is the function zero on the domain R {0}. Sectio Objective(s): The Dirc s Delt. Mi Properties. Applictios. The Impulse Respose Fuctio. 4.4.. The Dirc Delt. 4.4. Geerlized Sources Defiitio 4.4.. The Dirc delt geerlized fuctio is the limit δ(t)

More information

Numerical Methods (CENG 2002) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. In this chapter, we will deal with the case of determining the values of x 1

Numerical Methods (CENG 2002) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. In this chapter, we will deal with the case of determining the values of x 1 Numericl Methods (CENG 00) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. Itroductio I this chpter, we will del with the cse of determiig the vlues of,,..., tht simulteously stisfy the set of equtios: f f...

More information

Limit of a function:

Limit of a function: - Limit of fuctio: We sy tht f ( ) eists d is equl with (rel) umer L if f( ) gets s close s we wt to L if is close eough to (This defiitio c e geerlized for L y syig tht f( ) ecomes s lrge (or s lrge egtive

More information

MAS221 Analysis, Semester 2 Exercises

MAS221 Analysis, Semester 2 Exercises MAS22 Alysis, Semester 2 Exercises Srh Whitehouse (Exercises lbelled * my be more demdig.) Chpter Problems: Revisio Questio () Stte the defiitio of covergece of sequece of rel umbers, ( ), to limit. (b)

More information

Titus Beu University Babes-Bolyai Department of Theoretical and Computational Physics Cluj-Napoca, Romania

Titus Beu University Babes-Bolyai Department of Theoretical and Computational Physics Cluj-Napoca, Romania 8. Systems of Lier Algeric Equtios Titus Beu Uiversity Bes-Bolyi Deprtmet of Theoreticl d Computtiol Physics Cluj-Npoc, Romi Biliogrphy Itroductio Gussi elimitio method Guss-Jord elimitio method Systems

More information

1 Section 8.1: Sequences. 2 Section 8.2: Innite Series. 1.1 Limit Rules. 1.2 Common Sequence Limits. 2.1 Denition. 2.

1 Section 8.1: Sequences. 2 Section 8.2: Innite Series. 1.1 Limit Rules. 1.2 Common Sequence Limits. 2.1 Denition. 2. Clculus II d Alytic Geometry Sectio 8.: Sequeces. Limit Rules Give coverget sequeces f g; fb g with lim = A; lim b = B. Sum Rule: lim( + b ) = A + B, Dierece Rule: lim( b ) = A B, roduct Rule: lim b =

More information

334 MATHS SERIES DSE MATHS PREVIEW VERSION B SAMPLE TEST & FULL SOLUTION

334 MATHS SERIES DSE MATHS PREVIEW VERSION B SAMPLE TEST & FULL SOLUTION MATHS SERIES DSE MATHS PREVIEW VERSION B SAMPLE TEST & FULL SOLUTION TEST SAMPLE TEST III - P APER Questio Distributio INSTRUCTIONS:. Attempt ALL questios.. Uless otherwise specified, ll worig must be

More information

SOLUTION OF SYSTEM OF LINEAR EQUATIONS. Lecture 4: (a) Jacobi's method. method (general). (b) Gauss Seidel method.

SOLUTION OF SYSTEM OF LINEAR EQUATIONS. Lecture 4: (a) Jacobi's method. method (general). (b) Gauss Seidel method. SOLUTION OF SYSTEM OF LINEAR EQUATIONS Lecture 4: () Jcobi's method. method (geerl). (b) Guss Seidel method. Jcobi s Method: Crl Gustv Jcob Jcobi (804-85) gve idirect method for fidig the solutio of system

More information

Chapter 25 Sturm-Liouville problem (II)

Chapter 25 Sturm-Liouville problem (II) Chpter 5 Sturm-Liouville problem (II Speer: Lug-Sheg Chie Reerece: [] Veerle Ledou, Study o Specil Algorithms or solvig Sturm-Liouville d Schrodiger Equtios. [] 王信華教授, chpter 8, lecture ote o Ordiry Dieretil

More information

Digital Signal Processing, Fall 2006

Digital Signal Processing, Fall 2006 Digitl Sigl Processig, Fll 6 Lecture 6: Sstem structures for implemettio Zeg-u T Deprtmet of Electroic Sstems Alorg Uiversit, Demr t@om.u.d Digitl Sigl Processig, VI, Zeg-u T, 6 Course t glce Discrete-time

More information

Quantum Annealing for Heisenberg Spin Chains

Quantum Annealing for Heisenberg Spin Chains LA-UR # - Quatum Aealig for Heiseberg Spi Chais G.P. Berma, V.N. Gorshkov,, ad V.I.Tsifriovich Theoretical Divisio, Los Alamos Natioal Laboratory, Los Alamos, NM Istitute of Physics, Natioal Academy of

More information

The Exponential Function

The Exponential Function The Epoetil Fuctio Defiitio: A epoetil fuctio with bse is defied s P for some costt P where 0 d. The most frequetly used bse for epoetil fuctio is the fmous umber e.788... E.: It hs bee foud tht oyge cosumptio

More information

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions Qudrtic Equtios ALGEBRA Remider theorem: If f() is divided b( ), the remider is f(). Fctor theorem: If ( ) is fctor of f(), the f() = 0. Ivolutio d Evlutio ( + b) = + b + b ( b) = + b b ( + b) 3 = 3 +

More information

Name: A2RCC Midterm Review Unit 1: Functions and Relations Know your parent functions!

Name: A2RCC Midterm Review Unit 1: Functions and Relations Know your parent functions! Nme: ARCC Midterm Review Uit 1: Fuctios d Reltios Kow your pret fuctios! 1. The ccompyig grph shows the mout of rdio-ctivity over time. Defiitio of fuctio. Defiitio of 1-1. Which digrm represets oe-to-oe

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

MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE

MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE Prt 1. Let be odd rime d let Z such tht gcd(, 1. Show tht if is qudrtic residue mod, the is qudrtic residue mod for y ositive iteger.

More information

Applied Databases. Sebastian Maneth. Lecture 16 Suffix Array, Burrows-Wheeler Transform. University of Edinburgh - March 10th, 2016

Applied Databases. Sebastian Maneth. Lecture 16 Suffix Array, Burrows-Wheeler Transform. University of Edinburgh - March 10th, 2016 Applied Dtbses Lecture 16 Suffix Arry, Burrows-Wheeler Trsform Sebsti Meth Uiversity of Ediburgh - Mrch 10th, 2016 2 Outlie 1. Suffix Arry 2. Burrows-Wheeler Trsform 3 Olie Strig-Mtchig how c we do Horspool

More information

( a n ) converges or diverges.

( a n ) converges or diverges. Chpter Ifiite Series Pge of Sectio E Rtio Test Chpter : Ifiite Series By the ed of this sectio you will be ble to uderstd the proof of the rtio test test series for covergece by pplyig the rtio test pprecite

More information

Numerical Solutions of Fredholm Integral Equations Using Bernstein Polynomials

Numerical Solutions of Fredholm Integral Equations Using Bernstein Polynomials Numericl Solutios of Fredholm Itegrl Equtios Usig erstei Polyomils A. Shiri, M. S. Islm Istitute of Nturl Scieces, Uited Itertiol Uiversity, Dhk-, gldesh Deprtmet of Mthemtics, Uiversity of Dhk, Dhk-,

More information

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Hamid R. Rabiee Arman Sepehr Fall 2010

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Hamid R. Rabiee Arman Sepehr Fall 2010 Sigls & Systems Chpter 0: The Z-Trsform Adpted from: Lecture otes from MIT, Bighmto Uiversity Hmid R. Riee Arm Sepehr Fll 00 Lecture 5 Chpter 0 Outlie Itroductio to the -Trsform Properties of the ROC of

More information

Westchester Community College Elementary Algebra Study Guide for the ACCUPLACER

Westchester Community College Elementary Algebra Study Guide for the ACCUPLACER Westchester Commuity College Elemetry Alger Study Guide for the ACCUPLACER Courtesy of Aims Commuity College The followig smple questios re similr to the formt d cotet of questios o the Accuplcer Elemetry

More information

POWER SERIES R. E. SHOWALTER

POWER SERIES R. E. SHOWALTER POWER SERIES R. E. SHOWALTER. sequeces We deote by lim = tht the limit of the sequece { } is the umber. By this we me tht for y ε > 0 there is iteger N such tht < ε for ll itegers N. This mkes precise

More information

Review of the Riemann Integral

Review of the Riemann Integral Chpter 1 Review of the Riem Itegrl This chpter provides quick review of the bsic properties of the Riem itegrl. 1.0 Itegrls d Riem Sums Defiitio 1.0.1. Let [, b] be fiite, closed itervl. A prtitio P of

More information

MA123, Chapter 9: Computing some integrals (pp )

MA123, Chapter 9: Computing some integrals (pp ) MA13, Chpter 9: Computig some itegrls (pp. 189-05) Dte: Chpter Gols: Uderstd how to use bsic summtio formuls to evlute more complex sums. Uderstd how to compute its of rtiol fuctios t ifiity. Uderstd how

More information

Quadrature Methods for Numerical Integration

Quadrature Methods for Numerical Integration Qudrture Methods for Numericl Itegrtio Toy Sd Istitute for Cle d Secure Eergy Uiversity of Uth April 11, 2011 1 The Need for Numericl Itegrtio Nuemricl itegrtio ims t pproximtig defiite itegrls usig umericl

More information

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k.

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k. . Computtio of Fourier Series I this sectio, we compute the Fourier coefficiets, f ( x) cos( x) b si( x) d b, i the Fourier series To do this, we eed the followig result o the orthogolity of the trigoometric

More information

Vectors. Vectors in Plane ( 2

Vectors. Vectors in Plane ( 2 Vectors Vectors i Ple ( ) The ide bout vector is to represet directiol force Tht mes tht every vector should hve two compoets directio (directiol slope) d mgitude (the legth) I the ple we preset vector

More information

M3P14 EXAMPLE SHEET 1 SOLUTIONS

M3P14 EXAMPLE SHEET 1 SOLUTIONS M3P14 EXAMPLE SHEET 1 SOLUTIONS 1. Show tht for, b, d itegers, we hve (d, db) = d(, b). Sice (, b) divides both d b, d(, b) divides both d d db, d hece divides (d, db). O the other hd, there exist m d

More information

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1.

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1. GRAPHING LINEAR EQUATIONS Qudrt II Qudrt I ORDERED PAIR: The first umer i the ordered pir is the -coordite d the secod umer i the ordered pir is the y-coordite. (, ) Origi ( 0, 0 ) _-is Lier Equtios Qudrt

More information

Module B3 3.1 Sinusoidal steady-state analysis (single-phase), a review 3.2 Three-phase analysis. Kirtley

Module B3 3.1 Sinusoidal steady-state analysis (single-phase), a review 3.2 Three-phase analysis. Kirtley Module B.1 Siusoidl stedy-stte lysis (sigle-phse), review.2 Three-phse lysis Kirtley Chpter 2: AC Voltge, Curret d Power 2.1 Soures d Power 2.2 Resistors, Idutors, d Cpitors Chpter 4: Polyphse systems

More information

We will begin by supplying the proof to (a).

We will begin by supplying the proof to (a). (The solutios of problem re mostly from Jeffrey Mudrock s HWs) Problem 1. There re three sttemet from Exmple 5.4 i the textbook for which we will supply proofs. The sttemets re the followig: () The spce

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

Solutions to Problem Set 7

Solutions to Problem Set 7 8.0 Clculus Jso Strr Due by :00pm shrp Fll 005 Fridy, Dec., 005 Solutios to Problem Set 7 Lte homework policy. Lte work will be ccepted oly with medicl ote or for other Istitute pproved reso. Coopertio

More information

, we would have a series, designated as + j 1

, we would have a series, designated as + j 1 Clculus sectio 9. Ifiite Series otes by Ti Pilchowski A sequece { } cosists of ordered set of ubers. If we were to begi ddig the ubers of sequece together s we would hve series desigted s. Ech iteredite

More information

Algebra II, Chapter 7. Homework 12/5/2016. Harding Charter Prep Dr. Michael T. Lewchuk. Section 7.1 nth roots and Rational Exponents

Algebra II, Chapter 7. Homework 12/5/2016. Harding Charter Prep Dr. Michael T. Lewchuk. Section 7.1 nth roots and Rational Exponents Algebr II, Chpter 7 Hrdig Chrter Prep 06-07 Dr. Michel T. Lewchuk Test scores re vilble olie. I will ot discuss the test. st retke opportuit Sturd Dec. If ou hve ot tke the test, it is our resposibilit

More information

Lecture 14. Encryption

Lecture 14. Encryption Lecture 4. Ecryptio T. H. Corme, C. E. Leiserso d R. L. Rivest Itroductio to Algorithms, 3rd Editio, MIT Press, 2009 Sugkyukw Uiversity Hyuseug Choo choo@skku.edu Copyright 2000-207 Networkig Lbortory

More information

b a 2 ((g(x))2 (f(x)) 2 dx

b a 2 ((g(x))2 (f(x)) 2 dx Clc II Fll 005 MATH Nme: T3 Istructios: Write swers to problems o seprte pper. You my NOT use clcultors or y electroic devices or otes of y kid. Ech st rred problem is extr credit d ech is worth 5 poits.

More information

Last time, we talked about how Equation (1) can simulate Equation (2). We asserted that Equation (2) can also simulate Equation (1).

Last time, we talked about how Equation (1) can simulate Equation (2). We asserted that Equation (2) can also simulate Equation (1). 6896 Quatum Complexity Theory Sept 23, 2008 Lecturer: Scott Aaroso Lecture 6 Last Time: Quatum Error-Correctio Quatum Query Model Deutsch-Jozsa Algorithm (Computes x y i oe query) Today: Berstei-Vazirii

More information

Chapter 2. LOGARITHMS

Chapter 2. LOGARITHMS Chpter. LOGARITHMS Dte: - 009 A. INTRODUCTION At the lst hpter, you hve studied bout Idies d Surds. Now you re omig to Logrithms. Logrithm is ivers of idies form. So Logrithms, Idies, d Surds hve strog

More information

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication Next. Covered bsics of simple desig techique (Divided-coquer) Ch. of the text.. Next, Strsse s lgorithm. Lter: more desig d coquer lgorithms: MergeSort. Solvig recurreces d the Mster Theorem. Similr ide

More information

Recurrece reltio & Recursio 9 Chpter 3 Recurrece reltio & Recursio Recurrece reltio : A recurrece is equtio or iequlity tht describes fuctio i term of itself with its smller iputs. T T The problem of size

More information

Lesson 4 Linear Algebra

Lesson 4 Linear Algebra Lesso Lier Algebr A fmily of vectors is lierly idepedet if oe of them c be writte s lier combitio of fiitely my other vectors i the collectio. Cosider m lierly idepedet equtios i ukows:, +, +... +, +,

More information

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2 Mth 3, Clculus II Fil Exm Solutios. (5 poits) Use the limit defiitio of the defiite itegrl d the sum formuls to compute 3 x + x. Check your swer by usig the Fudmetl Theorem of Clculus. Solutio: The limit

More information

B. Examples 1. Finite Sums finite sums are an example of Riemann Sums in which each subinterval has the same length and the same x i

B. Examples 1. Finite Sums finite sums are an example of Riemann Sums in which each subinterval has the same length and the same x i Mth 06 Clculus Sec. 5.: The Defiite Itegrl I. Riem Sums A. Def : Give y=f(x):. Let f e defied o closed itervl[,].. Prtitio [,] ito suitervls[x (i-),x i ] of legth Δx i = x i -x (i-). Let P deote the prtitio

More information

Fig. 1. I a. V ag I c. I n. V cg. Z n Z Y. I b. V bg

Fig. 1. I a. V ag I c. I n. V cg. Z n Z Y. I b. V bg ymmetricl Compoets equece impedces Although the followig focuses o lods, the results pply eqully well to lies, or lies d lods. Red these otes together with sectios.6 d.9 of text. Cosider the -coected lced

More information

Autar Kaw Benjamin Rigsby. Transforming Numerical Methods Education for STEM Undergraduates

Autar Kaw Benjamin Rigsby.   Transforming Numerical Methods Education for STEM Undergraduates Autr Kw Bejmi Rigsby http://m.mthforcollege.com Trsformig Numericl Methods Eductio for STEM Udergrdutes http://m.mthforcollege.com . solve set of simulteous lier equtios usig Nïve Guss elimitio,. ler the

More information

18.01 Calculus Jason Starr Fall 2005

18.01 Calculus Jason Starr Fall 2005 18.01 Clculus Jso Strr Lecture 14. October 14, 005 Homework. Problem Set 4 Prt II: Problem. Prctice Problems. Course Reder: 3B 1, 3B 3, 3B 4, 3B 5. 1. The problem of res. The ciet Greeks computed the res

More information

Canonical Form and Separability of PPT States on Multiple Quantum Spaces

Canonical Form and Separability of PPT States on Multiple Quantum Spaces Coicl Form d Seprbility of PPT Sttes o Multiple Qutum Spces Xio-Hog Wg d Sho-Mig Fei, 2 rxiv:qut-ph/050445v 20 Apr 2005 Deprtmet of Mthemtics, Cpitl Norml Uiversity, Beijig, Chi 2 Istitute of Applied Mthemtics,

More information

2017/2018 SEMESTER 1 COMMON TEST

2017/2018 SEMESTER 1 COMMON TEST 07/08 SEMESTER COMMON TEST Course : Diplom i Electroics, Computer & Commuictios Egieerig Diplom i Electroic Systems Diplom i Telemtics & Medi Techology Diplom i Electricl Egieerig with Eco-Desig Diplom

More information

General properties of definite integrals

General properties of definite integrals Roerto s Notes o Itegrl Clculus Chpter 4: Defiite itegrls d the FTC Sectio Geerl properties of defiite itegrls Wht you eed to kow lredy: Wht defiite Riem itegrl is. Wht you c ler here: Some key properties

More information

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form 0.5 Power Series I the lst three sectios, we ve spet most of tht time tlkig bout how to determie if series is coverget or ot. Now it is time to strt lookig t some specific kids of series d we will evetully

More information

The Elementary Arithmetic Operators of Continued Fraction

The Elementary Arithmetic Operators of Continued Fraction Americ-Eursi Jourl of Scietific Reserch 0 (5: 5-63, 05 ISSN 88-6785 IDOSI Pulictios, 05 DOI: 0.589/idosi.ejsr.05.0.5.697 The Elemetry Arithmetic Opertors of Cotiued Frctio S. Mugssi d F. Mistiri Deprtmet

More information

: : 8.2. Test About a Population Mean. STT 351 Hypotheses Testing Case I: A Normal Population with Known. - null hypothesis states 0

: : 8.2. Test About a Population Mean. STT 351 Hypotheses Testing Case I: A Normal Population with Known. - null hypothesis states 0 8.2. Test About Popultio Me. Cse I: A Norml Popultio with Kow. H - ull hypothesis sttes. X1, X 2,..., X - rdom smple of size from the orml popultio. The the smple me X N, / X X Whe H is true. X 8.2.1.

More information

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1 Appedix A.. Itroductio As discussed i the Chpter 9 o Sequeces d Series, sequece,,...,,... hvig ifiite umber of terms is clled ifiite sequece d its idicted sum, i.e., + + +... + +... is clled ifite series

More information

Indices and Logarithms

Indices and Logarithms the Further Mthemtics etwork www.fmetwork.org.uk V 7 SUMMARY SHEET AS Core Idices d Logrithms The mi ides re AQA Ed MEI OCR Surds C C C C Lws of idices C C C C Zero, egtive d frctiol idices C C C C Bsic

More information

Interpolation. 1. What is interpolation?

Interpolation. 1. What is interpolation? Iterpoltio. Wht is iterpoltio? A uctio is ote give ol t discrete poits such s:.... How does oe id the vlue o t other vlue o? Well cotiuous uctio m e used to represet the + dt vlues with pssig through the

More information

Discrete-Time Signals & Systems

Discrete-Time Signals & Systems Chpter 2 Discrete-Time Sigls & Systems 清大電機系林嘉文 cwli@ee.thu.edu.tw 03-57352 Discrete-Time Sigls Sigls re represeted s sequeces of umbers, clled smples Smple vlue of typicl sigl or sequece deoted s x =

More information

For students entering Honors Precalculus Summer Packet

For students entering Honors Precalculus Summer Packet Hoors PreClculus Summer Review For studets eterig Hoors Preclculus Summer Pcket The prolems i this pcket re desiged to help ou review topics from previous mthemtics courses tht re importt to our success

More information

Statistics for Financial Engineering Session 1: Linear Algebra Review March 18 th, 2006

Statistics for Financial Engineering Session 1: Linear Algebra Review March 18 th, 2006 Sttistics for Ficil Egieerig Sessio : Lier Algebr Review rch 8 th, 6 Topics Itroductio to trices trix opertios Determits d Crmer s rule Eigevlues d Eigevectors Quiz The cotet of Sessio my be fmilir to

More information

Numerical Integration

Numerical Integration Numericl tegrtio Newto-Cotes Numericl tegrtio Scheme Replce complicted uctio or tulted dt with some pproimtig uctio tht is esy to itegrte d d 3-7 Roerto Muscedere The itegrtio o some uctios c e very esy

More information

,... are the terms of the sequence. If the domain consists of the first n positive integers only, the sequence is a finite sequence.

,... are the terms of the sequence. If the domain consists of the first n positive integers only, the sequence is a finite sequence. Chpter 9 & 0 FITZGERALD MAT 50/5 SECTION 9. Sequece Defiitio A ifiite sequece is fuctio whose domi is the set of positive itegers. The fuctio vlues,,, 4,...,,... re the terms of the sequece. If the domi

More information

It is always the case that unions, intersections, complements, and set differences are preserved by the inverse image of a function.

It is always the case that unions, intersections, complements, and set differences are preserved by the inverse image of a function. MATH 532 Measurable Fuctios Dr. Neal, WKU Throughout, let ( X, F, µ) be a measure space ad let (!, F, P ) deote the special case of a probability space. We shall ow begi to study real-valued fuctios defied

More information

Applied Databases. Sebastian Maneth. Lecture 16 Suffix Array, Burrows-Wheeler Transform. University of Edinburgh - March 16th, 2017

Applied Databases. Sebastian Maneth. Lecture 16 Suffix Array, Burrows-Wheeler Transform. University of Edinburgh - March 16th, 2017 Applied Dtbses Lecture 16 Suffix Arry, Burrows-Wheeler Trsform Sebsti Meth Uiversity of Ediburgh - Mrch 16th, 2017 Outlie 2 1. Suffix Arry 2. Burrows-Wheeler Trsform Outlie 3 1. Suffix Arry 2. Burrows-Wheeler

More information

MTH 146 Class 16 Notes

MTH 146 Class 16 Notes MTH 46 Clss 6 Notes 0.4- Cotiued Motivtio: We ow cosider the rc legth of polr curve. Suppose we wish to fid the legth of polr curve curve i terms of prmetric equtios s: r f where b. We c view the cos si

More information

The total number of permutations of S is n!. We denote the set of all permutations of S by

The total number of permutations of S is n!. We denote the set of all permutations of S by DETERMINNTS. DEFINITIONS Def: Let S {,,, } e the set of itegers from to, rrged i scedig order. rerrgemet jjj j of the elemets of S is clled permuttio of S. S. The totl umer of permuttios of S is!. We deote

More information

Lincoln Land Community College Placement and Testing Office

Lincoln Land Community College Placement and Testing Office Licol Ld Commuity College Plcemet d Testig Office Elemetry Algebr Study Guide for the ACCUPLACER (CPT) A totl of questios re dmiistered i this test. The first type ivolves opertios with itegers d rtiol

More information

Qn Suggested Solution Marking Scheme 1 y. G1 Shape with at least 2 [2]

Qn Suggested Solution Marking Scheme 1 y. G1 Shape with at least 2 [2] Mrkig Scheme for HCI 8 Prelim Pper Q Suggested Solutio Mrkig Scheme y G Shpe with t lest [] fetures correct y = f'( ) G ll fetures correct SR: The mimum poit could be i the first or secod qudrt. -itercept

More information

Pre-Calculus - Chapter 3 Sections Notes

Pre-Calculus - Chapter 3 Sections Notes Pre-Clculus - Chpter 3 Sectios 3.1-3.4- Notes Properties o Epoets (Review) 1. ( )( ) = + 2. ( ) =, (c) = 3. 0 = 1 4. - = 1/( ) 5. 6. c Epoetil Fuctios (Sectio 3.1) Deiitio o Epoetil Fuctios The uctio deied

More information