A Proposal for Experimental Detection of Amplitude nth-power Squeezing

Size: px
Start display at page:

Download "A Proposal for Experimental Detection of Amplitude nth-power Squeezing"

Transcription

1 A Proposal for Experimetal Detectio of Amplitude th-power Squeezig Rajaa Prakash ǂ ad Ajay K. Yadav ǂǂ Physics Departmet, Uiversity of Allahabad, Allahabad-00 (U.P.), Idia ǂ ǂǂ Abstract Recetly, i several theoretical ivestigatios, amplitude th-power squeezig has bee studied with =, 3,, 5, although a scheme for experimetal detectio is kow for = oly. I the preset paper, we give a proposal for experimetal detectio of amplitude th-power squeezig usig ordiary homodyig with coheret light for arbitrary power ad discuss i detail its theory. The proposed scheme requires oly repeated measuremets of the factorial momets of umber of photos i the light obtaied after homodyig, with various shifts of phase of coheret light, ad ivolves o approximatios, whatsoever.. Itroductio A sigle mode light has two compoets i quadrature ad the operators correspodig to these i quatum mechaics are o-commutig [-3] ad satisfy a ucertaity relatio. For classical optical fields, which have a o-egative weight fuctio i Sudarsha-Glauber diagoal represetatio [], the variaces of the quadrature operators have equal lower bouds. Optical fields may have a o-classical feature ad variace of oe quadrature amplitude may be less tha this lower boud at the expese of icreased variace for the other. This o-classical feature, called squeezig, was studied earlier i academic iterest [5] but its importace has ow bee uderstood because of its applicatio to optical commuicatio [6], optical waveguide tap [7], gravitatioal wave detectio [8], iterferometric techiques [9], ehacig the chael capacity [0], quatum teleportatio [], quatum dese codig [], quatum cryptography [3], Nao-displacemet measuremet [], optical storage [5] ad amplificatio of sigals [6]. Geeratio of squeezed states has bee reported i a variety of oliear optical processes, e.g., multiphoto absorptio [7], degeerate parametric amplifier [8], free electro laser [9], harmoic geeratio [0], degeerate parametric oscillatio [], degeerate four-wave mixig [], degeerate hyper-rama scatterig [3], resoace fluorescece [], the sigle atom-sigle field mode iteractio [5], superposed coheret states [6], ad oliear beam splitter [7]. Squeezig is uderstood by writig the aihilatio operator â i terms of the two hermitia quadrature amplitude operators ˆX ad ˆX i the form, â X ix or X ˆ ( a a), ˆ i X ( a a), which gives i [ X, X] or ( Xˆ ˆ ) ( X), where 6 coical brackets deote expectatio values ad X ˆ, X, X,. ˆX is said to be squeezed if ˆ ( X) ad ˆX is said to be squeezed if ( Xˆ ). Istead of cosiderig Xˆ ˆ ad X oe ca cosider the most geeral quadrature amplitude operator, ˆ i i X Xcos X si ( a e ae ), the commutatio relatio, i [ X, X ], which gives ucertaity relatio, ( Xˆ ) ( ˆ X ), leads to idea 6 of squeezig of the geeral compoet ˆX whe ( ˆ ) <. That, squeezig is a o- X

2 classical feature, is clear from the fact that, for Sudarsha-Glauber diagoal represetatio [] d P, we have ˆ i ( X ) d P[Re{( ) e }] 0, d P. () This cocept has bee geeralized i a umber of ways. I the first, Hog ad Madel [8] cosider powers of variace of quadrature amplitudes ad the field is called squeezed to order wheever ( Xˆ ) is less tha its value for coheret state. This type of squeezig has bee studied by several authors [9]. I the secod geeralizatio, itroduced by Hillery [30] for the lowest order ( =, referred to as amplitude squared squeezig) ad by Zhag [3] for higher-orders, Hermitia ad ati-hermitia parts of the square or th-power of the aihilatio operator have bee cosidered ad the two Hermitia operators thus obtaied have bee used to defie squeezig. Explicitly, i the geeral case, we defie ˆ i i X ( e e ), () which gives commutatio relatio ˆ ˆ [, ˆ ] i i X X [ a, a ] W, (3) where ˆ r r r r W r!( C ) a a. () The ucertaity relatio is the ˆ ( X ) ( Xˆ ˆ ) W, (5) 6 ˆ ad therefore the defiitio of squeezig of X is ˆ ˆ ( X ) W. (6) This type of squeezig is called amplitude th-power squeezig. Sice we ca write ˆ ˆ ˆ : ( X ) : ( X ) W, we have ˆ ˆ ˆ : ( X ) : ( X ) W, where double dots (: :) deote ormal orderig of operators. This tells that Eq. (6) which gives the defiitio of th-order squeezig ca also be writte i the simpler form ˆ : ( X ) : 0. (7) Amplitude-squared squeezig has bee studied for a aharmoic oscillator [3], the iteractio betwee atom ad radiatio field [33], mixig of waves [3], Kerr medium [35], superposed coheret states [36]. Also ehacemet of amplitude-squared squeezig is studied by mixig it with coheret light beam [37]. Amplitude th-power squeezig has bee studied by several authors [38-]. It may be oted that sice the Hog ad Madel s cocept of th order squeezig is ot based o ay ucertaity relatio, th order squeezig ca be obtaied for both ˆX ad ˆX simultaeously []. Simultaeous squeezig of ˆ X ad ˆ X is however ruled out because of the ucertaity relatios. Hillery also cosidered a secod type of amplitude squared squeezig by separatig ( ) ito its Hermitia ad ati-hermitia parts. A differet type of amplitude th-power squeezig has bee defied by Bužek ad Jex [3]. Other geeralizatios of squeezig ivolve multi-mode operators ad their commutatio relatios; the commo examples beig sum ad differece squeezig [], spi squeezig [5], atomic squeezig [6], ad polarizatio squeezig [7]. Proposal for experimetal detectio of ordiary squeezig was give by Madel [8] usig homodyig with itese light with adjustable phase from a local oscillator ad measurig the umber of photos ad its square i oe of the outputs. Such homodyig of

3 squeezed light coverts squeezig ito sub-poissoia photo statistics [9] ad the degree of squeezig is obtaied from measuremets of expectatio values of photo umber operator ad its square. Prakash ad Kumar [50] showed a similar coversio of fourth-order squeezig ito secod-order sub-poissoia photo statistics ad proposed a balaced homodye method for detectio of fourth-order squeezed light i the similar fashio. Prakash ad Mishra [5] exteded the proposal of ordiary homodyig for experimetal detectio of amplitude-squared squeezig by measurig higher order momets of umber operator of mixed light with shifted phases. They also studied higher-order sub-poissoia photo statistics coditios for o-classicality ad discussed its use for the detectio of Hog ad Madel s squeezig of arbitrary order. Prakash et al reported recetly [5] a ordiary homodye method for detectio of secod type of amplitude-squared squeezig of Hillery by measurig the higher-order momets of the umber operator i light obtaied by homodyig with itese coheret light. A very large umber of theoretical papers has bee published o the study of amplitude th-power squeezig with = 3 [38], [39], 5 [0], ad for = k [] but o geeral method for detectio has bee reported for >. We preset here a proposal for experimetal detectio of amplitude th-power squeezig for ay arbitrary power by usig the ordiary homodye detectio method. It may be oted that we work without takig ay approximatio whatsoever like replacig operator for coheret state by c-umber or takig trasmittace or reflectace of the beam splitter very small.. The detectio scheme Schematic diagram for proposed detectio scheme, show i Fig., cotais the experimetal outlie ad also the coceptual meaig of quatum efficiecy of the experimetal detector []. The beam splitter ad ideal detector placed iside dotted rectagle model the real photodetector []. The sigal represeted by operator â is mixed usig beam splitter with sigal ˆ i be, obtaied by shiftig by φ the phase of sigal from a local oscillator represeted by operator b ˆ, to give output sigal ĉ ad c ˆ. Oe of the output sigals, say c ˆ, is detected. If the beam splitter has trasmittace T ad we write t T ad r T as coefficiets of trasmissio ad reflectio for the amplitudes, respectively, we ca write [3] ˆ i c ta rbe, (8) with t ad r real. Number operator of the mixed light is the ˆ ˆ i ( ˆ )( i Nc c c ta rb e ta rbe ). (9) I this model [] of photodetector with quatum efficiecy η, the beam splitter mixes (i) iput sigal ĉ ad (ii) vacuum sigal a ˆv, ad oe of the outputs ˆd give by dˆ cˆ v (0) is detected by a ideal detector havig 00% efficiecy. It is iterestig to ote that this model [] explais that the detected couts, dd, are η times the icidet umber of cc ˆˆ, photos, i.e., ˆ ˆ d d cˆˆ c () which is also obtaied directly from Eq. (0). For factorial momets of order, we get similarly ˆ ˆ d d cˆ cˆ. () The relatioship for th-power of photo umber operator is ot a simple oe. This is oe reaso why we ivolve factorial momets of photo umber operator ad ot powers of the photo umber operator i our aalysis ad result, as was doe earlier [5].

4 LO Local Oscillator ˆb Phase Shifter (φ) PS be ˆ i Squeezed Light â ĉ Beam Splitter ĉ v ˆd ˆd Detector with 00% Efficiecy Couter Photodetector Fig.. Schematic diagram of detectio of squeezig via ordiary homodyig For the setup uder cosideratio, the observed factorial momets of couts with phase shift φ is the If observatios are doe for l m l m l m ˆ l ˆm i( ml) l m. lm, 0 M c c C C t r a a b b e (3) M for φ = kπ/ with k = 0,,, - we ca easily fid the values of observables P M e ( tr ) [ a e i a e ], () ik i k k 0 Q M t ( C ) ( t r ) a a, l l l k l k0 l0 (5) if the local oscillator gives i the coheret state with e is the complex amplitude. Eq. () gives a method for measurig ˆ, usig θ β = θ/, but a method for measurig Wˆ l l ad therefore for momets is still to be desired. To achieve this ed, we ca solve Eq. (5) for factorial momets of photo umber operator by iteratio. This is doe i Appedix ad gives where K s is defied by Straight forward calculatios lead to P P ( tr ) s ( s) s( s) ( ) s s0 P P K C r Q X s s t Ks( Cs) ( r ) Q s, s0 (6) s s s l ( l ) with 0. l 0 K K C K (7) ( tr ) [ : ( Xˆ ) : cos ( ) : ( Xˆ ) : si ( ) ˆ ˆ ˆ ˆ ( X X X X )si ( )] i

5 ˆ ( tr ) : ( X ) :, if ( ) 0; ( tr ) : ( Xˆ ) :, if ( ). This equatio shows that amplitude th-power squeezig for ay value of θ, defied by Eqs. (6) or (7), ca be detected by measuremet of observables P, Q, η, T ad β. 3. Discussio of results We explaied how P ad Q ca be foud from measuremets of (8) ˆ ( ) N (see Eqs. () ad (5)). Measuremet of quatum efficiecy η for a give detector is somewhat tricky ad requires use of spotaeous parameter dow coversio [53]. If a photo of a large eergy ħω breaks to create two photos of eergies ħω ad ħω (with ω + ω = ω), the latter two photos should give coicidece couts oly ideally. If N photos break ad the quatum efficiecies for modes ω ad ω are η ad η (both < ), the experimet registers couts N = η N, N = η N ad coicidece couts N c = η η N. The quatum efficiecies are the η = N c /N ad η = N c /N. Oce η is determied for ay detector, the detector ca be used to measure T ad β easily. It should be oted that as icreases the choice of θ β becomes more sesitive ad for detectio of : ( ˆ X ) :, θ β is to be set as θ/. For =, i.e., for ordiary squeezig detectio was first studied by Madel [9]. His formula is differet from that obtaied from Eq. (8) after substitutig =. This is uderstadable as Madel s result is approximate, ad is obtaied uder the approximatio, r, i our otatios. Also, for =, i.e., for amplitude-squared squeezig, the results of Prakash ad Mishra [5] are differet from the results obtaied from Eq. (8) as their results are also approximate, the same approximatio ( r, i our otatios) beig used. Ackowledgemets We would like to thak Prof. H. Prakash ad Prof. N. Chadra for their iterest ad critical commets. We would like to ackowledge Dr. R. Kumar, Dr. P. Kumar, Dr. D. K. Mishra, Namrata Shukla, Ajay K. Maurya, Vikram Verma, ad Maoj K. Mishra for their valuable ad stimulatig discussios. Oe of the authors (Ajay K. Yadav) is grateful to the Uiversity Grats Commissio, New Delhi, Idia for fiacial support uder a UGC-JRF fellowship. Appedix We ca separate the ˆ ˆ a a term o right had side of Eq. (5) ad write l l l l 0( 0) ( l) ( ) l t Q K C C t r (A) with K 0 =. I the first term i summatio o the right had side we substitute for the expressio obtaied from Eq. (A) usig K 0 ( l C 0 ) = ad this gives with t Q K ( C ) ( t r ) [ t Q m m m l l l l ( C ) ( ) ] m t r a a K0( C0) ( Cl) ( t r ) a a m l K K ( C ). This ca be simplified ad writte as 0 0

6 t [ Q K ( C ) ( r ) Q ] [ K ( C ) K ( C ) ]( C ) ( t r ). l l l l l l 0 0 l If we agai substitute the first term i summatio the expressio obtaied for from Eq. (A) ad simplify, we get t [ Q K ( C ) ( r ) Q K ( C ) ( r ) Q ] l [ K ( C ) K ( C ) K ( C ) ]( C ) ( t r ) l l l l l l 0 0 l (A) with K [ K0( C0) K( C) ]. If we go o doig similar exercises we get required Eq. (6) where K s is defied by Eq. (7). Refereces [] See, e.g., the review articles D. F. Walls, Nature 306 (983) ; M. C. Teich ad B. E. A. Saleh, Quatum Opt. (989) 53; V. V. Dodoov, J. Opt. B: Quatum Semiclass. Opt. (00) R. [] See, e.g., the review article R. Loudo ad P. L. Kight, J. Mod. Opt. 3 (987) 709. [3] See, e.g., the review article U. Leohardt ad H. Paul, Prog. Quat. Electr. 9 (995) 89. [] E. C. G. Sudarsha, Phys. Rev. Lett. 0 (963) 77; R. J. Glauber, Phys. Rev. 3 (963) 766. [5] B. R. Mollow ad R. J. Glauber, Phys. Rev. 60 (967) 076, 097; N. Chadra ad H. Prakash, Lett. Nuovo. Cim. (970) 96; M. T. Raiford, Phys. Rev. A (970) 5; N. Chadra ad H. Prakash, Idia J. Pure Appl. Phys. 9 (97) 09, 677, 688, 767; H. Prakash, N. Chadra ad Vachaspati, Phys. Rev. A 9 (97) 67; H. Prakash et al, Idia J. Pure Appl. Phys. 3 (975) 757, 763; (976), 8. [6] H. P. Yue ad J. H. Shapiro, IEEE Tras. If. Theory (978) 657. [7] J. H. Shapiro, Opt. Lett. 5 (980) 35. [8] C. M. Caves, Phys. Rev. D 3 (98) 693; A. F. Pace, M. J. Collett ad D. F. Walls, Phys. Rev. A 7 (993) 373; K. McKezie et al, Phys. Rev. Lett. 93 (00) 605. [9] C. M. Caves ad B. L. Schumaker, Phys. Rev. A 3 (985) 3068; B. L. Schumaker ad C. M. Caves, Phys. Rev. A 3 (985) [0] B. E. A. Saleh ad M. C. Teich, Phys. Rev. Lett. 58 (987) 656. [] S. L. Braustei ad H. J. Kimble, Phys. Rev. Lett. 80 (998) 869; J. Zhag ad K. C. Peg, Phys. Rev. A 6 (000) 0630; W. P. Bowe, P. K. Lam ad T. C. Ralph, J. Mod. Opt. 50 (003) 80. [] M. Ba, J. Opt. B: Quatum Semiclass. Opt. (999) L9; S. L. Braustei ad H. J. Kimble, Phys. Rev. A 6 (000) 030. [3] M. Hillery, Phys. Rev. A 6 (000) [] N. Treps et al, J. Opt. B: Quatum Semiclass. Opt. 6 (00) S66. [5] M. T. L. Hsu et al, IEEE J. Quatum Electro. (006) 00. [6] A. V. Kozlovskii, Quatum Electroics 37 (007) 7; C. Laflamme ad A. A. Clerk, Phys. Rev. A 83 (0) [7] H. D. Simaa ad R. Loudo, J. Phys. A: Math. Ge. 8 (975) 539; R. Loudo, Opt. Commu. 9 (98) 67. [8] G. Milbur ad D. F. Walls, Opt. Commu. 39 (98) 0. [9] W. Becker, M. O. Scully ad M. S. Zubairy, Phys. Rev. Lett. 8 (98) 75. [0] L. Madel, Opt. Commu. (98) 37; L. A. Lugiato, G. Strii ad F. De Martii, Opt. Lett. 8 (983) 56. [] G. Milbur ad D. F. Walls, Phys. Rev. A 7 (983) 39. [] R. S. Bodurat et al, Phys. Rev. A 30 (98) 33; M. D. Reid ad D. F. Walls, Phys. Rev. A 3 (985) 6. [3] V. Periova ad R. Tiebel, Opt. Commu. 50 (98) 0. [] Z. Ficek et al, Phys. Rev. A 9 (98) 00. [5] H. Li ad L. Wu, Opt. Commu. 97 (00) 97; S.-B. Zheg, Opt. Commu. 73 (007) 60. [6] H. Prakash ad P. Kumar, Physica A 39 (003) 305; 3 (00) 0; Optik (0) 058. [7] H. Prakash ad D. K. Mishra, Opt. Lett. 35 (00). [8] C. K. Hog ad L. Madel, Phys. Rev. Lett. 5 (985) 33; Phys. Rev. A 3 (985) 97. [9] P. G.-Feradez et al, Phys. Lett. A 8 (986) 00; P. Tombesi ad A. Mecozzi, Phys. Rev. A 37 (988) 778; P. Maria, Phys. Rev. A (99) 335; 5 (99) 0; J.-S. Wag, T.-K. Liu ad M.-S. Zha, It. J. Theor. Phys. 39 (000) 583; H. Prakash ad P. Kumar, Acta Physica Poloica B 3 (003) 769; (A3)

7 D. K. Mishra, Opt. Commu. 83 (00) 38; H. Prakash, R. Kumar ad P. Kumar, Opt. Commu. 8 (0) 89. [30] M. Hillery, Opt. Commu. 6 (987) 35; Phys. Rev. A 36 (987) [3] Z.-M. Zhag et al, Phys. Lett. A 50 (990) 7. [3] C. C. Gerry ad E. R. Vrscay, Phys. Rev. A 37 (988) 779. [33] M. H. Mahra ad A.-S. F. Obada, Phys. Rev. A 0 (989) 76; A.-S. F. Obada ad A. M. Abdel-Hafez, Opt. Commu. 9 (99) 99; H. Prakash ad R. Kumar, It. J. Mod. Phys. B (007) 36. [3] D. K. Giri ad P. S. Gupta, J. Opt. B: Quatum Semiclass. Opt. 6 (00) 9; Mod. Phys. Lett. B (008) 9. [35] H. Prakash ad P. Kumar, It. J. Mod. Phys. B 0 (006) 58; Z.-X. Wu et al, Chi.Theor. Phys. 7 (007) 933. [36] H. Prakash ad P. Kumar, Euro. Phys. J. D 6 (008) 359. [37] H. Prakash ad D. K. Mishra, J. Phys. B: At. Mol. Opt. Phys. 38 (005) 665; D. K. Mishra, Acta Physica Poloica A (007) 859. [38] Y. Zha, Phys. Lett. A 60 (99) 98; A. Kumar ad P. S. Gupta, Quatum Semiclass. Opt. 8 (996) 053; D. K. Giri ad P. S. Gupta, It. J. Mod. Phys. B 0 (006) 65; S. Rai, J. Lal ad N. Sigh, Opt. Quat. Electro 39 (007) 57; B. Se ad S. Madal, J. Mod. Opt. 55 (008) 697. [39] S. Du ad C. Gog, Phys. Rev. A 8 (993) 98; J. Wag, Q. Sui ad C. Wag, Quat. Semi. Opt. 7 (995) 97; S. Rai, J. Lal ad N. Sigh, Opt. Quat. Electro 39 (007) 735; Opt. Commu. 77 (007) 7; 8 (008) 3. [0] D. K. Giri ad P. S. Gupta, It. J. Mod. Phys. B 9 (005) 93. [] Y. Zha, Phys. Rev. A 6 (99) 686; J. Wag et al, Acta Physica Siica (995) 7. [] R. Lych, Phys. Rev. A 33 (986) 3; 9 (99) 800; C. K. Hog ad L. Madel, Phys. Rev. A 33 (986) 3. [3] V. Bužek ad I. Jex, Phys. Rev. A (990) 079. [] M. Hillery, Phys. Rev. A 0 (989) 37; A. Kumar ad P. S. Gupta, Opt. Commu. 36 (997) ;Quatum Semiclass. Opt. 0 (998) 85; H. Prakash ad D. K. Mishra, Eur. Phys. J. D 5 (007) 363. [5] H. Prakash ad R. Kumar, J. Opt. B: Quatum Semiclass. Opt. 7 (005) S757. [6] H. Prakash ad R. Kumar, Eur. Phys. J. D (007) 75. [7] A. S. Chirki, A. A. Orlov ad D. Yu. Parashchuk, Quatum Electro. 3 (993) 870; R. Prakash ad N. Shukla, Opt. Commu. 8 (0) [8] L. Madel, Phys. Rev. Lett. 9 (98) 36; see also L. Madel ad E. Wolf, Optical Coherece ad Quatum Optics (Cambridge Uiversity Press, USA, 995) p [9] L. Madel, Opt. Lett. (979) 05; R. Short ad L. Madel, Phys. Rev. Lett. 5 (983) 38; R. Kumar ad H. Prakash, Ca. J. Phys. 88 (00) 8. [50] H. Prakash ad P. Kumar, J. Opt. B: Quatum Semiclass. Opt. 7 (005) S786. [5] H. Prakash ad D. K. Mishra, J. Phys. B: At. Mol. Opt. Phys. 39 (006) 9; 0 (007) 53 Corrigedum. [5] H. Prakash, P. Kumar ad D. K. Mishra, It. J. Mod. Phys. B (00) 557. [53] A. N. Pei ad A. V. Sergieko, Appl. Opt. 30 (99) 358; S. Castelletto et al, Metrologia 3 (995) 50; G. Brida et al, Metrologia 35 (998) 397; A. Migdall et al, Appl. Opt. (00) 9; S. Lu et al, Meas. Sci. Techol. 3 (00) 86.

Probability, Expectation Value and Uncertainty

Probability, Expectation Value and Uncertainty Chapter 1 Probability, Expectatio Value ad Ucertaity We have see that the physically observable properties of a quatum system are represeted by Hermitea operators (also referred to as observables ) such

More information

Assignment 2 Solutions SOLUTION. ϕ 1 Â = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ.

Assignment 2 Solutions SOLUTION. ϕ 1  = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ. PHYSICS 34 QUANTUM PHYSICS II (25) Assigmet 2 Solutios 1. With respect to a pair of orthoormal vectors ϕ 1 ad ϕ 2 that spa the Hilbert space H of a certai system, the operator  is defied by its actio

More information

Generalization of Samuelson s inequality and location of eigenvalues

Generalization of Samuelson s inequality and location of eigenvalues Proc. Idia Acad. Sci. Math. Sci.) Vol. 5, No., February 05, pp. 03. c Idia Academy of Scieces Geeralizatio of Samuelso s iequality ad locatio of eigevalues R SHARMA ad R SAINI Departmet of Mathematics,

More information

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001.

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001. Physics 324, Fall 2002 Dirac Notatio These otes were produced by David Kapla for Phys. 324 i Autum 2001. 1 Vectors 1.1 Ier product Recall from liear algebra: we ca represet a vector V as a colum vector;

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

The standard deviation of the mean

The standard deviation of the mean Physics 6C Fall 20 The stadard deviatio of the mea These otes provide some clarificatio o the distictio betwee the stadard deviatio ad the stadard deviatio of the mea.. The sample mea ad variace Cosider

More information

True Nature of Potential Energy of a Hydrogen Atom

True Nature of Potential Energy of a Hydrogen Atom True Nature of Potetial Eergy of a Hydroge Atom Koshu Suto Key words: Bohr Radius, Potetial Eergy, Rest Mass Eergy, Classical Electro Radius PACS codes: 365Sq, 365-w, 33+p Abstract I cosiderig the potetial

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

PH 425 Quantum Measurement and Spin Winter SPINS Lab 1

PH 425 Quantum Measurement and Spin Winter SPINS Lab 1 PH 425 Quatum Measuremet ad Spi Witer 23 SPIS Lab Measure the spi projectio S z alog the z-axis This is the experimet that is ready to go whe you start the program, as show below Each atom is measured

More information

3/21/2017. Commuting and Non-commuting Operators Chapter 17. A a

3/21/2017. Commuting and Non-commuting Operators Chapter 17. A a Commutig ad No-commutig Operators Chapter 17 Postulate 3. I ay measuremet of the observable associated with a operator A the oly values that will ever be observed are the eige values, a, which satisfy

More information

The Scattering Matrix

The Scattering Matrix 2/23/7 The Scatterig Matrix 723 1/13 The Scatterig Matrix At low frequecies, we ca completely characterize a liear device or etwork usig a impedace matrix, which relates the currets ad voltages at each

More information

Bertrand s Postulate

Bertrand s Postulate Bertrad s Postulate Lola Thompso Ross Program July 3, 2009 Lola Thompso (Ross Program Bertrad s Postulate July 3, 2009 1 / 33 Bertrad s Postulate I ve said it oce ad I ll say it agai: There s always a

More information

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT TR/46 OCTOBER 974 THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION by A. TALBOT .. Itroductio. A problem i approximatio theory o which I have recetly worked [] required for its solutio a proof that the

More information

1 6 = 1 6 = + Factorials and Euler s Gamma function

1 6 = 1 6 = + Factorials and Euler s Gamma function Royal Holloway Uiversity of Lodo Departmet of Physics Factorials ad Euler s Gamma fuctio Itroductio The is a self-cotaied part of the course dealig, essetially, with the factorial fuctio ad its geeralizatio

More information

Regression with an Evaporating Logarithmic Trend

Regression with an Evaporating Logarithmic Trend Regressio with a Evaporatig Logarithmic Tred Peter C. B. Phillips Cowles Foudatio, Yale Uiversity, Uiversity of Aucklad & Uiversity of York ad Yixiao Su Departmet of Ecoomics Yale Uiversity October 5,

More information

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series

More information

Zeros of Polynomials

Zeros of Polynomials Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree

More information

Kinetics of Complex Reactions

Kinetics of Complex Reactions Kietics of Complex Reactios by Flick Colema Departmet of Chemistry Wellesley College Wellesley MA 28 wcolema@wellesley.edu Copyright Flick Colema 996. All rights reserved. You are welcome to use this documet

More information

CALCULATION OF FIBONACCI VECTORS

CALCULATION OF FIBONACCI VECTORS CALCULATION OF FIBONACCI VECTORS Stuart D. Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA email: saderso@ithaca.edu ad Dai Novak Departmet of Mathematics, Ithaca College

More information

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense, 3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [

More information

THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS

THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS R775 Philips Res. Repts 26,414-423, 1971' THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS by H. W. HANNEMAN Abstract Usig the law of propagatio of errors, approximated

More information

1 Adiabatic and diabatic representations

1 Adiabatic and diabatic representations 1 Adiabatic ad diabatic represetatios 1.1 Bor-Oppeheimer approximatio The time-idepedet Schrödiger equatio for both electroic ad uclear degrees of freedom is Ĥ Ψ(r, R) = E Ψ(r, R), (1) where the full molecular

More information

Convergence of random variables. (telegram style notes) P.J.C. Spreij

Convergence of random variables. (telegram style notes) P.J.C. Spreij Covergece of radom variables (telegram style otes).j.c. Spreij this versio: September 6, 2005 Itroductio As we kow, radom variables are by defiitio measurable fuctios o some uderlyig measurable space

More information

Principle Of Superposition

Principle Of Superposition ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give

More information

Frequency Domain Filtering

Frequency Domain Filtering Frequecy Domai Filterig Raga Rodrigo October 19, 2010 Outlie Cotets 1 Itroductio 1 2 Fourier Represetatio of Fiite-Duratio Sequeces: The Discrete Fourier Trasform 1 3 The 2-D Discrete Fourier Trasform

More information

Asymptotic distribution of products of sums of independent random variables

Asymptotic distribution of products of sums of independent random variables Proc. Idia Acad. Sci. Math. Sci. Vol. 3, No., May 03, pp. 83 9. c Idia Academy of Scieces Asymptotic distributio of products of sums of idepedet radom variables YANLING WANG, SUXIA YAO ad HONGXIA DU ollege

More information

A Block Cipher Using Linear Congruences

A Block Cipher Using Linear Congruences Joural of Computer Sciece 3 (7): 556-560, 2007 ISSN 1549-3636 2007 Sciece Publicatios A Block Cipher Usig Liear Cogrueces 1 V.U.K. Sastry ad 2 V. Jaaki 1 Academic Affairs, Sreeidhi Istitute of Sciece &

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

SEQUENCES AND SERIES

SEQUENCES AND SERIES Sequeces ad 6 Sequeces Ad SEQUENCES AND SERIES Successio of umbers of which oe umber is desigated as the first, other as the secod, aother as the third ad so o gives rise to what is called a sequece. Sequeces

More information

A statistical method to determine sample size to estimate characteristic value of soil parameters

A statistical method to determine sample size to estimate characteristic value of soil parameters A statistical method to determie sample size to estimate characteristic value of soil parameters Y. Hojo, B. Setiawa 2 ad M. Suzuki 3 Abstract Sample size is a importat factor to be cosidered i determiig

More information

Chimica Inorganica 3

Chimica Inorganica 3 himica Iorgaica Irreducible Represetatios ad haracter Tables Rather tha usig geometrical operatios, it is ofte much more coveiet to employ a ew set of group elemets which are matrices ad to make the rule

More information

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece 1, 1, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet

More information

x a x a Lecture 2 Series (See Chapter 1 in Boas)

x a x a Lecture 2 Series (See Chapter 1 in Boas) Lecture Series (See Chapter i Boas) A basic ad very powerful (if pedestria, recall we are lazy AD smart) way to solve ay differetial (or itegral) equatio is via a series expasio of the correspodig solutio

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

DEPARTMENT OF ACTUARIAL STUDIES RESEARCH PAPER SERIES

DEPARTMENT OF ACTUARIAL STUDIES RESEARCH PAPER SERIES DEPARTMENT OF ACTUARIAL STUDIES RESEARCH PAPER SERIES Icreasig ad Decreasig Auities ad Time Reversal by Jim Farmer Jim.Farmer@mq.edu.au Research Paper No. 2000/02 November 2000 Divisio of Ecoomic ad Fiacial

More information

Signal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform

Signal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform Sigal Processig i Mechatroics Summer semester, 1 Lecture 3, Covolutio, Fourier Series ad Fourier rasform Dr. Zhu K.P. AIS, UM 1 1. Covolutio Covolutio Descriptio of LI Systems he mai premise is that the

More information

Chapter 5 Vibrational Motion

Chapter 5 Vibrational Motion Fall 4 Chapter 5 Vibratioal Motio... 65 Potetial Eergy Surfaces, Rotatios ad Vibratios... 65 Harmoic Oscillator... 67 Geeral Solutio for H.O.: Operator Techique... 68 Vibratioal Selectio Rules... 7 Polyatomic

More information

A Note on Matrix Rigidity

A Note on Matrix Rigidity A Note o Matrix Rigidity Joel Friedma Departmet of Computer Sciece Priceto Uiversity Priceto, NJ 08544 Jue 25, 1990 Revised October 25, 1991 Abstract I this paper we give a explicit costructio of matrices

More information

Modified Decomposition Method by Adomian and. Rach for Solving Nonlinear Volterra Integro- Differential Equations

Modified Decomposition Method by Adomian and. Rach for Solving Nonlinear Volterra Integro- Differential Equations Noliear Aalysis ad Differetial Equatios, Vol. 5, 27, o. 4, 57-7 HIKARI Ltd, www.m-hikari.com https://doi.org/.2988/ade.27.62 Modified Decompositio Method by Adomia ad Rach for Solvig Noliear Volterra Itegro-

More information

CALCULATING FIBONACCI VECTORS

CALCULATING FIBONACCI VECTORS THE GENERALIZED BINET FORMULA FOR CALCULATING FIBONACCI VECTORS Stuart D Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA email: saderso@ithacaedu ad Dai Novak Departmet

More information

Machine Learning for Data Science (CS 4786)

Machine Learning for Data Science (CS 4786) Machie Learig for Data Sciece CS 4786) Lecture & 3: Pricipal Compoet Aalysis The text i black outlies high level ideas. The text i blue provides simple mathematical details to derive or get to the algorithm

More information

Free Space Optical Wireless Communications under Turbulence Channel Effect

Free Space Optical Wireless Communications under Turbulence Channel Effect IOSR Joural of Electroics ad Commuicatio Egieerig (IOSR-JECE) e-issn: 78-834,p- ISSN: 78-8735.Volume 9, Issue 3, Ver. III (May - Ju. 014), PP 01-08 Free Space Optical Wireless Commuicatios uder Turbulece

More information

Some Features on Entropy Squeezing for Two-Level System with a New Nonlinear Coherent State

Some Features on Entropy Squeezing for Two-Level System with a New Nonlinear Coherent State Joural of Quatum Iformatio Sciece, 4, 4, 7-8 Published Olie March 4 i SciRes. http://www.scirp.org/joural/jqis http://d.doi.org/.436/jqis.4.47 Some Features o Etropy Squeezig for Two-Level System with

More information

Office: JILA A709; Phone ;

Office: JILA A709; Phone ; Office: JILA A709; Phoe 303-49-7841; email: weberjm@jila.colorado.edu Problem Set 5 To be retured before the ed of class o Wedesday, September 3, 015 (give to me i perso or slide uder office door). 1.

More information

The Heisenberg versus the Schrödinger picture in quantum field theory. Dan Solomon Rauland-Borg Corporation 3450 W. Oakton Skokie, IL USA

The Heisenberg versus the Schrödinger picture in quantum field theory. Dan Solomon Rauland-Borg Corporation 3450 W. Oakton Skokie, IL USA 1 The Heiseberg versus the chrödiger picture i quatum field theory by Da olomo Raulad-Borg Corporatio 345 W. Oakto kokie, IL 677 UA Phoe: 847-324-8337 Email: da.solomo@raulad.com PAC 11.1-z March 15, 24

More information

Chapter 7: The z-transform. Chih-Wei Liu

Chapter 7: The z-transform. Chih-Wei Liu Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability

More information

The Random Walk For Dummies

The Random Walk For Dummies The Radom Walk For Dummies Richard A Mote Abstract We look at the priciples goverig the oe-dimesioal discrete radom walk First we review five basic cocepts of probability theory The we cosider the Beroulli

More information

Subject: Differential Equations & Mathematical Modeling-III

Subject: Differential Equations & Mathematical Modeling-III Power Series Solutios of Differetial Equatios about Sigular poits Subject: Differetial Equatios & Mathematical Modelig-III Lesso: Power series solutios of differetial equatios about Sigular poits Lesso

More information

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer.

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer. 6 Itegers Modulo I Example 2.3(e), we have defied the cogruece of two itegers a,b with respect to a modulus. Let us recall that a b (mod ) meas a b. We have proved that cogruece is a equivalece relatio

More information

Frequency Response of FIR Filters

Frequency Response of FIR Filters EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we itroduce the idea of the frequecy respose of LTI systems, ad focus specifically o the frequecy respose of FIR filters.. Steady-state

More information

Random Variables, Sampling and Estimation

Random Variables, Sampling and Estimation Chapter 1 Radom Variables, Samplig ad Estimatio 1.1 Itroductio This chapter will cover the most importat basic statistical theory you eed i order to uderstad the ecoometric material that will be comig

More information

Statistics 511 Additional Materials

Statistics 511 Additional Materials Cofidece Itervals o mu Statistics 511 Additioal Materials This topic officially moves us from probability to statistics. We begi to discuss makig ifereces about the populatio. Oe way to differetiate probability

More information

Module 18 Discrete Time Signals and Z-Transforms Objective: Introduction : Description: Discrete Time Signal representation

Module 18 Discrete Time Signals and Z-Transforms Objective: Introduction : Description: Discrete Time Signal representation Module 8 Discrete Time Sigals ad Z-Trasforms Objective:To uderstad represetig discrete time sigals, apply z trasform for aalyzigdiscrete time sigals ad to uderstad the relatio to Fourier trasform Itroductio

More information

The Growth of Functions. Theoretical Supplement

The Growth of Functions. Theoretical Supplement The Growth of Fuctios Theoretical Supplemet The Triagle Iequality The triagle iequality is a algebraic tool that is ofte useful i maipulatig absolute values of fuctios. The triagle iequality says that

More information

arxiv: v1 [math-ph] 5 Jul 2017

arxiv: v1 [math-ph] 5 Jul 2017 O eigestates for some sl 2 related Hamiltoia arxiv:1707.01193v1 [math-ph] 5 Jul 2017 Fahad M. Alamrai Faculty of Educatio Sciece Techology & Mathematics, Uiversity of Caberra, Bruce ACT 2601, Australia.,

More information

INEQUALITIES BJORN POONEN

INEQUALITIES BJORN POONEN INEQUALITIES BJORN POONEN 1 The AM-GM iequality The most basic arithmetic mea-geometric mea (AM-GM) iequality states simply that if x ad y are oegative real umbers, the (x + y)/2 xy, with equality if ad

More information

Hauptman and Karle Joint and Conditional Probability Distributions. Robert H. Blessing, HWI/UB Structural Biology Department, January 2003 ( )

Hauptman and Karle Joint and Conditional Probability Distributions. Robert H. Blessing, HWI/UB Structural Biology Department, January 2003 ( ) Hauptma ad Karle Joit ad Coditioal Probability Distributios Robert H Blessig HWI/UB Structural Biology Departmet Jauary 00 ormalized crystal structure factors are defied by E h = F h F h = f a hexp ihi

More information

PHYC - 505: Statistical Mechanics Homework Assignment 4 Solutions

PHYC - 505: Statistical Mechanics Homework Assignment 4 Solutions PHYC - 55: Statistical Mechaics Homewor Assigmet 4 Solutios Due February 5, 14 1. Cosider a ifiite classical chai of idetical masses coupled by earest eighbor sprigs with idetical sprig costats. a Write

More information

A Combinatoric Proof and Generalization of Ferguson s Formula for k-generalized Fibonacci Numbers

A Combinatoric Proof and Generalization of Ferguson s Formula for k-generalized Fibonacci Numbers Jue 5 00 A Combiatoric Proof ad Geeralizatio of Ferguso s Formula for k-geeralized Fiboacci Numbers David Kessler 1 ad Jeremy Schiff 1 Departmet of Physics Departmet of Mathematics Bar-Ila Uiversity, Ramat

More information

Signals & Systems Chapter3

Signals & Systems Chapter3 Sigals & Systems Chapter3 1.2 Discrete-Time (D-T) Sigals Electroic systems do most of the processig of a sigal usig a computer. A computer ca t directly process a C-T sigal but istead eeds a stream of

More information

Appendix: The Laplace Transform

Appendix: The Laplace Transform Appedix: The Laplace Trasform The Laplace trasform is a powerful method that ca be used to solve differetial equatio, ad other mathematical problems. Its stregth lies i the fact that it allows the trasformatio

More information

1. Hydrogen Atom: 3p State

1. Hydrogen Atom: 3p State 7633A QUANTUM MECHANICS I - solutio set - autum. Hydroge Atom: 3p State Let us assume that a hydroge atom is i a 3p state. Show that the radial part of its wave fuctio is r u 3(r) = 4 8 6 e r 3 r(6 r).

More information

Physics 232 Gauge invariance of the magnetic susceptibilty

Physics 232 Gauge invariance of the magnetic susceptibilty Physics 232 Gauge ivariace of the magetic susceptibilty Peter Youg (Dated: Jauary 16, 2006) I. INTRODUCTION We have see i class that the followig additioal terms appear i the Hamiltoia o addig a magetic

More information

Similarity between quantum mechanics and thermodynamics: Entropy, temperature, and Carnot cycle

Similarity between quantum mechanics and thermodynamics: Entropy, temperature, and Carnot cycle Similarity betwee quatum mechaics ad thermodyamics: Etropy, temperature, ad Carot cycle Sumiyoshi Abe 1,,3 ad Shiji Okuyama 1 1 Departmet of Physical Egieerig, Mie Uiversity, Mie 514-8507, Japa Istitut

More information

An Introduction to Randomized Algorithms

An Introduction to Randomized Algorithms A Itroductio to Radomized Algorithms The focus of this lecture is to study a radomized algorithm for quick sort, aalyze it usig probabilistic recurrece relatios, ad also provide more geeral tools for aalysis

More information

Asymptotic Coupling and Its Applications in Information Theory

Asymptotic Coupling and Its Applications in Information Theory Asymptotic Couplig ad Its Applicatios i Iformatio Theory Vicet Y. F. Ta Joit Work with Lei Yu Departmet of Electrical ad Computer Egieerig, Departmet of Mathematics, Natioal Uiversity of Sigapore IMS-APRM

More information

Problem Set 4 Due Oct, 12

Problem Set 4 Due Oct, 12 EE226: Radom Processes i Systems Lecturer: Jea C. Walrad Problem Set 4 Due Oct, 12 Fall 06 GSI: Assae Gueye This problem set essetially reviews detectio theory ad hypothesis testig ad some basic otios

More information

P1 Chapter 8 :: Binomial Expansion

P1 Chapter 8 :: Binomial Expansion P Chapter 8 :: Biomial Expasio jfrost@tiffi.kigsto.sch.uk www.drfrostmaths.com @DrFrostMaths Last modified: 6 th August 7 Use of DrFrostMaths for practice Register for free at: www.drfrostmaths.com/homework

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information

Exercises 1 Sets and functions

Exercises 1 Sets and functions Exercises 1 Sets ad fuctios HU Wei September 6, 018 1 Basics Set theory ca be made much more rigorous ad built upo a set of Axioms. But we will cover oly some heuristic ideas. For those iterested studets,

More information

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece,, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet as

More information

The log-behavior of n p(n) and n p(n)/n

The log-behavior of n p(n) and n p(n)/n Ramauja J. 44 017, 81-99 The log-behavior of p ad p/ William Y.C. Che 1 ad Ke Y. Zheg 1 Ceter for Applied Mathematics Tiaji Uiversity Tiaji 0007, P. R. Chia Ceter for Combiatorics, LPMC Nakai Uivercity

More information

CHAPTER 10 INFINITE SEQUENCES AND SERIES

CHAPTER 10 INFINITE SEQUENCES AND SERIES CHAPTER 10 INFINITE SEQUENCES AND SERIES 10.1 Sequeces 10.2 Ifiite Series 10.3 The Itegral Tests 10.4 Compariso Tests 10.5 The Ratio ad Root Tests 10.6 Alteratig Series: Absolute ad Coditioal Covergece

More information

Linear Regression Demystified

Linear Regression Demystified Liear Regressio Demystified Liear regressio is a importat subject i statistics. I elemetary statistics courses, formulae related to liear regressio are ofte stated without derivatio. This ote iteds to

More information

Statistical Analysis on Uncertainty for Autocorrelated Measurements and its Applications to Key Comparisons

Statistical Analysis on Uncertainty for Autocorrelated Measurements and its Applications to Key Comparisons Statistical Aalysis o Ucertaity for Autocorrelated Measuremets ad its Applicatios to Key Comparisos Nie Fa Zhag Natioal Istitute of Stadards ad Techology Gaithersburg, MD 0899, USA Outlies. Itroductio.

More information

Analysis of Algorithms. Introduction. Contents

Analysis of Algorithms. Introduction. Contents Itroductio The focus of this module is mathematical aspects of algorithms. Our mai focus is aalysis of algorithms, which meas evaluatig efficiecy of algorithms by aalytical ad mathematical methods. We

More information

On a Smarandache problem concerning the prime gaps

On a Smarandache problem concerning the prime gaps O a Smaradache problem cocerig the prime gaps Felice Russo Via A. Ifate 7 6705 Avezzao (Aq) Italy felice.russo@katamail.com Abstract I this paper, a problem posed i [] by Smaradache cocerig the prime gaps

More information

ON POINTWISE BINOMIAL APPROXIMATION

ON POINTWISE BINOMIAL APPROXIMATION Iteratioal Joural of Pure ad Applied Mathematics Volume 71 No. 1 2011, 57-66 ON POINTWISE BINOMIAL APPROXIMATION BY w-functions K. Teerapabolar 1, P. Wogkasem 2 Departmet of Mathematics Faculty of Sciece

More information

Lecture 1 Probability and Statistics

Lecture 1 Probability and Statistics Wikipedia: Lecture 1 Probability ad Statistics Bejami Disraeli, British statesma ad literary figure (1804 1881): There are three kids of lies: lies, damed lies, ad statistics. popularized i US by Mark

More information

The picture in figure 1.1 helps us to see that the area represents the distance traveled. Figure 1: Area represents distance travelled

The picture in figure 1.1 helps us to see that the area represents the distance traveled. Figure 1: Area represents distance travelled 1 Lecture : Area Area ad distace traveled Approximatig area by rectagles Summatio The area uder a parabola 1.1 Area ad distace Suppose we have the followig iformatio about the velocity of a particle, how

More information

Topic 9: Sampling Distributions of Estimators

Topic 9: Sampling Distributions of Estimators Topic 9: Samplig Distributios of Estimators Course 003, 2016 Page 0 Samplig distributios of estimators Sice our estimators are statistics (particular fuctios of radom variables), their distributio ca be

More information

NEW FAST CONVERGENT SEQUENCES OF EULER-MASCHERONI TYPE

NEW FAST CONVERGENT SEQUENCES OF EULER-MASCHERONI TYPE UPB Sci Bull, Series A, Vol 79, Iss, 207 ISSN 22-7027 NEW FAST CONVERGENT SEQUENCES OF EULER-MASCHERONI TYPE Gabriel Bercu We itroduce two ew sequeces of Euler-Mascheroi type which have fast covergece

More information

Math 2784 (or 2794W) University of Connecticut

Math 2784 (or 2794W) University of Connecticut ORDERS OF GROWTH PAT SMITH Math 2784 (or 2794W) Uiversity of Coecticut Date: Mar. 2, 22. ORDERS OF GROWTH. Itroductio Gaiig a ituitive feel for the relative growth of fuctios is importat if you really

More information

How to Maximize a Function without Really Trying

How to Maximize a Function without Really Trying How to Maximize a Fuctio without Really Tryig MARK FLANAGAN School of Electrical, Electroic ad Commuicatios Egieerig Uiversity College Dubli We will prove a famous elemetary iequality called The Rearragemet

More information

Expectation and Variance of a random variable

Expectation and Variance of a random variable Chapter 11 Expectatio ad Variace of a radom variable The aim of this lecture is to defie ad itroduce mathematical Expectatio ad variace of a fuctio of discrete & cotiuous radom variables ad the distributio

More information

A collocation method for singular integral equations with cosecant kernel via Semi-trigonometric interpolation

A collocation method for singular integral equations with cosecant kernel via Semi-trigonometric interpolation Iteratioal Joural of Mathematics Research. ISSN 0976-5840 Volume 9 Number 1 (017) pp. 45-51 Iteratioal Research Publicatio House http://www.irphouse.com A collocatio method for sigular itegral equatios

More information

SOME TRIBONACCI IDENTITIES

SOME TRIBONACCI IDENTITIES Mathematics Today Vol.7(Dec-011) 1-9 ISSN 0976-38 Abstract: SOME TRIBONACCI IDENTITIES Shah Devbhadra V. Sir P.T.Sarvajaik College of Sciece, Athwalies, Surat 395001. e-mail : drdvshah@yahoo.com The sequece

More information

Generating Functions for Laguerre Type Polynomials. Group Theoretic method

Generating Functions for Laguerre Type Polynomials. Group Theoretic method It. Joural of Math. Aalysis, Vol. 4, 2010, o. 48, 257-266 Geeratig Fuctios for Laguerre Type Polyomials α of Two Variables L ( xy, ) by Usig Group Theoretic method Ajay K. Shula* ad Sriata K. Meher** *Departmet

More information

Chapter 1. Complex Numbers. Dr. Pulak Sahoo

Chapter 1. Complex Numbers. Dr. Pulak Sahoo Chapter 1 Complex Numbers BY Dr. Pulak Sahoo Assistat Professor Departmet of Mathematics Uiversity Of Kalyai West Begal, Idia E-mail : sahoopulak1@gmail.com 1 Module-2: Stereographic Projectio 1 Euler

More information

Square-Congruence Modulo n

Square-Congruence Modulo n Square-Cogruece Modulo Abstract This paper is a ivestigatio of a equivalece relatio o the itegers that was itroduced as a exercise i our Discrete Math class. Part I - Itro Defiitio Two itegers are Square-Cogruet

More information

The Method of Least Squares. To understand least squares fitting of data.

The Method of Least Squares. To understand least squares fitting of data. The Method of Least Squares KEY WORDS Curve fittig, least square GOAL To uderstad least squares fittig of data To uderstad the least squares solutio of icosistet systems of liear equatios 1 Motivatio Curve

More information

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING Lectures MODULE 5 STATISTICS II. Mea ad stadard error of sample data. Biomial distributio. Normal distributio 4. Samplig 5. Cofidece itervals

More information

Lecture 2: Monte Carlo Simulation

Lecture 2: Monte Carlo Simulation STAT/Q SCI 43: Itroductio to Resamplig ethods Sprig 27 Istructor: Ye-Chi Che Lecture 2: ote Carlo Simulatio 2 ote Carlo Itegratio Assume we wat to evaluate the followig itegratio: e x3 dx What ca we do?

More information

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3 MATH 337 Sequeces Dr. Neal, WKU Let X be a metric space with distace fuctio d. We shall defie the geeral cocept of sequece ad limit i a metric space, the apply the results i particular to some special

More information

Complex Number Theory without Imaginary Number (i)

Complex Number Theory without Imaginary Number (i) Ope Access Library Joural Complex Number Theory without Imagiary Number (i Deepak Bhalchadra Gode Directorate of Cesus Operatios, Mumbai, Idia Email: deepakm_4@rediffmail.com Received 6 July 04; revised

More information

An Intuitionistic fuzzy count and cardinality of Intuitionistic fuzzy sets

An Intuitionistic fuzzy count and cardinality of Intuitionistic fuzzy sets Malaya Joural of Matematik 4(1)(2013) 123 133 A Ituitioistic fuzzy cout ad cardiality of Ituitioistic fuzzy sets B. K. Tripathy a, S. P. Jea b ad S. K. Ghosh c, a School of Computig Scieces ad Egieerig,

More information

ECON 3150/4150, Spring term Lecture 3

ECON 3150/4150, Spring term Lecture 3 Itroductio Fidig the best fit by regressio Residuals ad R-sq Regressio ad causality Summary ad ext step ECON 3150/4150, Sprig term 2014. Lecture 3 Ragar Nymoe Uiversity of Oslo 21 Jauary 2014 1 / 30 Itroductio

More information

Central limit theorem and almost sure central limit theorem for the product of some partial sums

Central limit theorem and almost sure central limit theorem for the product of some partial sums Proc. Idia Acad. Sci. Math. Sci. Vol. 8, No. 2, May 2008, pp. 289 294. Prited i Idia Cetral it theorem ad almost sure cetral it theorem for the product of some partial sums YU MIAO College of Mathematics

More information

Ray Optics Theory and Mode Theory. Dr. Mohammad Faisal Dept. of EEE, BUET

Ray Optics Theory and Mode Theory. Dr. Mohammad Faisal Dept. of EEE, BUET Ray Optics Theory ad Mode Theory Dr. Mohammad Faisal Dept. of, BUT Optical Fiber WG For light to be trasmitted through fiber core, i.e., for total iteral reflectio i medium, > Ray Theory Trasmissio Ray

More information

A Simplified Binet Formula for k-generalized Fibonacci Numbers

A Simplified Binet Formula for k-generalized Fibonacci Numbers A Simplified Biet Formula for k-geeralized Fiboacci Numbers Gregory P. B. Dresde Departmet of Mathematics Washigto ad Lee Uiversity Lexigto, VA 440 dresdeg@wlu.edu Zhaohui Du Shaghai, Chia zhao.hui.du@gmail.com

More information