Imaging and Aberration Theory

Size: px
Start display at page:

Download "Imaging and Aberration Theory"

Transcription

1 Imagig ad Aberratio Theory Lecture 9: Chromatical aberratio 07-- Herbert Gro Witer term 07

2 Prelimiary time chedule 6.0. Paraxial imagig paraxial optic, fudametal law of geometrical imagig, compoud ytem Pupil, ourier optic, pupil defiitio, baic ourier relatiohip, phae pace, aalogy optic ad 3.0. Hamiltoia coordiate mechaic, Hamiltoia coordiate Eikoal ermat priciple, tatioary phae, Eikoal, relatio ray-wave, geometrical approximatio, ihomogeeou media Aberratio expaio igle urface, geeral Taylor expaio, repreetatio, variou order, top hift formula Repreetatio of aberratio differet type of repreetatio, field of applicatio, limitatio ad pitfall, meauremet of aberratio Spherical aberratio pheomeology, ph-free urface, kew pherical, correctio of ph, apherical urface, higher order Ditortio ad coma pheomeology, relatio to ie coditio, aplaatic ytem, effect of top poitio, variou topic, correctio optio Atigmatim ad curvature pheomeology, Coddigto equatio, Petzval law, correctio optio 9.. Chromatical aberratio Diperio, axial chromatical aberratio, travere chromatical aberratio, pherochromatim, ecodary poectrum 0 Sie coditio, aplaatim ad Sie coditio, ioplaatim, relatio to coma ad hift ivariace, pupil 8.. ioplaatim aberratio, Herchel coditio, relatio to ourier optic Wave aberratio defiitio, variou expaio form, propagatio of wave aberratio 5.0. Zerike polyomial pecial expaio for circular ymmetry, problem, calculatio, optimal balacig, ifluece of ormalizatio, meauremet 3.0. Poit pread fuctio ideal pf, pf with aberratio, Strehl ratio Trafer fuctio trafer fuctio, reolutio ad cotrat Additioal topic Vectorial aberratio, geeralized urface cotributio, Aldi theorem, itriic ad iduced aberratio, revertability

3 3 Cotet. Material diperio. Partial diperio 3. Aomalou partial diperio 4. Axial chromatical error 5. Achromatic 6. Apochromate 7. Spherochromatim 8. Chromatical variatio of magificatio 9. Example

4 4 Diperio ad Abbe umber Decriptio of diperio: refractive idex.8 viible Abbe umber C.75 D large Viual rage of wavelegth: typically d,,c or e,,c ued.7.65 S lit e e C.6.55 Typical rage of glae e = Two fudametal type of gla: Crow glae: mall, large, diperio low lit glae: large, mall, diperio high.5.45 D mall BK7 crow [mm]

5 Curvature c of the radii of a le ocal power at the ceter wavelegth e for a thi le Differece i focal power for outer wavelegth, C with the Abbe umber ocal legth at the ceter wavelegth Differece of the focal legth for outer wavelegth Achromatizatio coditio for two thi lee cloe together Abbe Number ad Achromatizatio, r c r c c c c e e e D ) ( ) )( ( e e e e C C C c c D D D ) ( ) ( c f e e e D ) ( e e e C C C C f c c f f f D D D ) ( ) )( ( C e e 0 D f f 5

6 6 Gla Diagram Uual repreetatio of glae: diagram of refractive idex v diperio () Left to right: Icreaig diperio decreaig Abbe umber

7 7 Diperio Material with differet diperio value: - Differet lope ad curvature of the diperio curve - Stroger chage of idex over wavelegth for large diperio - Iverio of idex equece at the boudarie of the pectrum poible refractive idex flit mall lope large.65 crow large lope mall.65 SK8A.6 VIS

8 Atomic model for the refractive idex: ocillator approach of atomic field iteractio Sellmeier diperio formula: correpodig fuctio Special cae of coupled reoace: example quartz, degeerated ocillator Atomic Model of Diperio i r i c f m c Ne i log [mm] viible (UV) (UV) 3 (IR) 4 (IR) vi () C B A 4 0 o C B B A 8

9 9 Diperio formula Schott formula empirical Sellmeier Baed o ocillator model 4 6 a a a a a a o ( ) A B C Bauch-Lomb empirical Herzberger Baed o ocillator model 4 D E ( ) A B C ( o) a a3 ) ao a ( o o mit 0.68 mm o o Hartma Baed o ocillator model ( ) a o a a 3 a4 a 5

10 0 Relative partial diperio Relative partial diperio : Chage of diperio lope with Differet curvature of diperio curve Defiitio of local lope for elected wavelegth relative to ecodary color P C i - g g - - e - C C - C - t () Special -electio for characteritic rage of the viible pectrum.49 = 656 / 04 m far IR = 656 / 85 m ear IR = 486 / 546 m blue edge of VIS = 435 / 486 m ear UV = 365 / 435 m far UV.48 i : 365 m UV edge g : 435 m UV edge e : 546 m d : 588 m mai color : 480 m C : 644 m : 486 m C : 656 m. ecodary color. ecodary color : 85 m IR edge t : 04 m IR edge

11 Partial Diperio ad Normal Lie The relative partial diperio chage approximately liear with the diperio for glae P b, a, d, P 0.6 Nearly all glae are located o the ormal lie i a P--diagram P g The lope of the ormal lie deped o the electio of wavelegth 0.55 Glae apart from the ormal lie how aomalou partial diperio DP 0.5 P C P a d b DP thee material are importat for chromatical correctio of higher order

12 Partial Diperio Aormal partial diperio ad ormal lie P g, N-K5 N-PK5 ormal lie GG375G34 N-BA5 N-BA3 N-BA5 K5G0 N-BAK4 N-BA0 N-SK N-SK8 N-LA3 SK0G0 N-BAL5 N-LL6 BAKG N-SSK8 SK4G3 N-BAL4 N-SK5 SSK5G06 N-SK4 N-SSK5 N-K5 SK5 N-BAK N-K9 K7 N-SK N-PK5 N-SK5 N-PSK53 N-PSK57 N-PSK58 BK7G5 N-PSK3 N-K5 N-BK0 BK7G8 N-BK7 N-LAK7 N-LAK N-ZK7 N-SK6 N-PSK3 N-SK4 SK5G06 N-LL N-LA N-BA4 BAS5 5 N-BAK N-LAK4 S5 N-LA7 N-S64 N-S8 N-S5 N-S9 N-LAS40 N-L5 N-BAS N- G N-LAK33 N-LAK N-LAK9 N-LAK LAKL N-SK0 N-S N-S0 N-S5 S0 N-LAK8 S S5 N-LAS45 N-LAS36 LAN7 N-KZS N-BAS64 L5G5 L5 KZSN5 N-LAS43 N-LAS3 N-LA LL N-LAS4 N-LA33 N-KZS KZSN4 KZS4G0 N-LAS30 N-LAS44 N-KZS4 N-LA N-LA3 LAK9G5 K0 N-LAK34 N-KZS N-S4 N-S6 S4 N-S57 N-LA35 N-LA8 N-LA34 N-LAK0 N-SSK LAKN3 S66 SL57 S57 S S N-S56 S6G05 S6 S56A S4 N-LAS35 S8G07 N-LAS46 LASN9 S5G0

13 3 Aomalou Partial Diperio There are ome pecial glae with a large deviatio from the ormal lie Of pecial iteret: log crow ad hort flit P g, lie of ormal diperio S N-S57 KZSN4 K5 K5 PSK53A ZKN7 LAK8 LASN30 P g, heavy flit with character of log crow flit log crow log crow hort flit hort flit crow ormal lie

14 4 Aomalou Partial Diperio Normal glae: Partial diperio chage liear with Abbe umber Defiitio of P deped o elected wavelegth Normal lie defied by ad K7 P P P P P C, t C,, e g, i, g d d d d d Deviatio from liear behavior: aomalou partial diperio DP P a d b DP P g D d The value of DP deped o the wavelegth electio Typical DP coidered at the red ad the blue ed of the viible pectrum ormal lie D P g real curve Large deviatio value DP are eceary for apochromatic chromatical correctio d

15 5 Aomalou Partial Diperio Arrow i the gla map: idicatio of the deviatio from the ormal lie P h Vertical compoet: at the red horizotal: at the blue ed of the pectrum P a d b DP ormal lie Gla D d DP h arrow of deviatio DP tc d gla locatio DP h blue ide red ide d

16 6 Chromatical Aberratio Axial chromatical aberratio: - diperio of margial ray - differet image locatio Travere chromatical aberratio: - diperio of chief ray - differet image ize obect ideal image ideal image margial ray chief ray margial ray axial chromatical aberratio ExP ExP chief ray travere chromatical aberratio

17 7 Overview o Chromatical Aberratio. Primary/t order chromatical aberratio: - axial chromatical aberratio error of the margial ray by diperio - travere chromatical aberratio error of the chief ray by diperio. Higher order chromatical aberratio: - ecodary pectrum reidual axial error, if oly elected wavelegth are coicidig - pherochromatim chromatical variatio of the pherical aberratio, oberved i a achromate - chromatical variatio of all moochromatic aberratio e.g. atigmatim, coma, pupil locatio,...

18 8 Chromatical Aberratio Variou cae of chromatical aberratio correctio a) axial ad lateral color corrected b) axial color corrected MR CR C C C C c) lateral color corrected d) o color corrected C C C C

19 9 Axial Chromatical Aberratio Axial chromatical aberratio: Higher refractive idex i the blue reult i a horter iterectio legth for a igle le The colored image are defocued alog the axi Defiitio of the error: chage i image locatio / iterectio legth Correctio eed everal glae with differet diperio Sigle le: ormal diperio blue iterectio legth i horter tha red P Notatio: white. CHL = chromatical logitudial. AXCL = axial chromatic D CHL C e blue C gree red

20 0 Axial Chromatical Aberratio Logitudial chromatical aberratio for a igle le Bet image plae chage with wavelegth bet image plae = 648 m = 546 m = 480 m defocu z Ref : H. Zügge

21 Secodary Spectrum P Simple achromatizatio / firt order correctio: - two glae with differet diperio - equal iterectio legth for outer wavelegth (blue, red C) white C ecodary pectrum Reidual deviatio for middle wavelegth (gree e): ecodary pectrum ( ) P, C P D SSP C f ( ), C 644 C e achromate blue red gree D 546 e iglet reidual error achromate e C 480 D

22 Achromate: Baic ormula Idea:. Two thi lee cloe together with differet material. Total power 3. Achromatic correctio coditio 0 Idividual power value Propertie:. Oe poitive ad oe egative le eceary. Two differet equece of plu (crow) / miu (flit) 3. Large -differece relaxe the bedig 4. Achromatic correctio idipedet from bedig 5. Bedig correct pherical aberratio at the margi 6. Aplaatic coma correctio for pecial gla choice 7. urther optimizatio of material reduce the pherical zoal aberratio

23 3 Achromate Compeatio of axial colour by appropriate gla choice (a) (b) Chromatical variatio of the pherical aberratio: pherochromatim (Gauia aberratio) Therefore perfect axial color correctio (o axi) are ofte ot feaable BK7 =.568 = 64.7 = BK7 = = = = = = r p r p 486 m 588 m 656 m Dz Dz -00 Ref : H. Zügge

24 4 Achromate Achromate Logitudial aberratio Travere aberratio Spot diagram Dy 486 m 587 m 656 m = 486 m axi r p = 587 m = 656 m iu m 587 m 656 m D [mm]

25 Achromate: Correctio Cemeted achromate: 6 degree of freedom: 3 radii, idice, ratio / D MR aplaatic cae Correctio of pherical aberratio: divergig cemeted urface with poitive pherical cotributio for eg > po Choice of gla: poible goal. aplaatic coma correctio. miimizatio of pherochromatim 3. miimizatio of ecodary pectrum Bedig ha o impact o chromatical correctio: i ued to correct pherical aberratio at the edge Three olutio regio for bedig. o pherical correctio. two equivalet olutio 3. oe aplaatic olutio, very table cae without olutio, oly pherical miimum R cae with olutio cae with oe olutio ad coma correctio

26 6 Bedig of a Achromate - Aplaatic Cae D too mall: o pherical correctio Aplaatic cae: ame zero poit of bedig for coma ad pherical aberratio oly oe olutio for pherical Large D: Two olutio for bedig with corrected pherical correctio o coicidece with coma zero poit aberratio 0 aplaatic lie of crow pherical aberratio crow o pherical correctio due to mall D aplaatic cae coma flit alterative value for the crow gla coma corrected o pherical correctio due to mall D X aplaatic cae 3 pherical aberratio crow crow / / / / bedig for correctio X zero

27 7 Aplaatic Achromate Appropriate gla combiatio for aplaatic correctio Cae of NA = 0. with Rayleigh rage R u = mm Compario of reidual aberratio lit Crow Vedor crow coma z 8 zoal pherical [mm] ecodary pectrum [mm] S66 EL4 Hoya S5 BAL5 Ohara S6 N-BAL5 Schott S57 KZ Schott S58 S-TIL Ohara S ADC Hoya S AD Hoya

28 8 Achromatic Solutio i the Gla Diagram large -differece give relaxed bedig crow poitive le flit egative le Achromat

29 9 Achromate Correctio axial color require a larger -differece i the gla map: if the differece D become maller, the axial focal power are icreaig Correctio of the pherical aberratio require a igificat maller i the poitive crow le e) N-LAK33 LAK9 d) K0 good olutio a) D à 0 TI3 b) D < 0 D mall TIN5 c) D very mall S

30 or oe give flit a lie idicate the uefull crow glae ad vice vera Perfect aplaatic lie of correpodig glae (corrected for coma) Coditio: Optimizatio of Achromatic Glae fixed flit gla lie of miimal pherical aberratio fixed crow gla lie of miimal pherical aberratio r 30

31 3 Achromate Reidual aberratio of a achromate Clearly ee:. Ditortio. Chromatical magificatio 3. Atigmatim

32 Surface ad Le cotributio of Axial Color Coiderig the Abbe ivariat Derivative after the wavelegth Summig over all urface of a ytem with the margial ray height ratio ad the propagatio of the ratio Surface ummatio for axial chromatical aberratio with the urface cotributio coefficiet h h d d r d d d d r d d r r Q Q D D D N N N CHL r r D N CHL N N N N N N CHL K Q CHL Q K 3

33 33 Geeral Achromatizatio Cotributio of a thi le to the axial chromatical aberratio Axial chromatical aberratio of a ytem of thi lee K D CHL le CHL N f Coditio of achromatizatio of a ytem of lee 0 Special cae of lee cloe together 0 Coditio of apochromatic (polychromatic) correctio with the partial relative diperio P 0

34 Dialyt approach: Achromatizatio with two lee at fiite ditace Scalig parameter k: With fiite margial ray height ocal legth coditio Achromatizatio ocal legth of the lee Le ditace a f t k a f b k f f 0 b b b a a a f y f y k f f a b a b a b k k f f f k k d a b ) ( Dialyt-Achromat 34

35 35 Dialyt Achromat Uage of oly oe gla material with achromatic correctio: dialyt achromate No real imagig poible Parameter: Setup kf f a f b k f ( k ) k le a k t k f le b image plae y a y b t f a

36 36 Axial Color Correctio with Schupma Le Special layout of dialyte approach accordig to Schupma Mirror guaratee real imagig f = -00 mm mirror f = 300 mm real image

37 37 Axial Colour : Apochromate Choice of at leat oe pecial gla P g Correctio of ecodary pectrum: aomalou partial diperio 0,6 0,60 N-S6 () At leat oe gla hould deviate igificatly form the ormal gla lie 0,58 0,56 ()+() T N-KZS (3) 656m 588m 0,54 () 90 N-K m -0.mm Dz -0.mm 436m 0 mm Dz

38 ocal power coditio Achromatic coditio Secodary pectrum Curvature of lee Parameter E The 3 material are ot allowed to be o the ormal lie The triagle of the 3 poit hould be large: mall c give relaxed deig P P P r r c 3,, a a c b c a a P P E f c 3,, b b a c c a b P P E f c 3,, c c b a c a c P P E f c [ ] b a c a c b c b a c a P P P P P P E Apochromate 38

39 39 Relative Partial Diperio Preferred gla electio for apochromate N-S N-S6 N-S57 N-S66 P-S68 P-S67 N-K5A N-PK5A N-PK5 N-KZS N-KZS4 N-LA33 N-LAS4 N-LA37 N-LA N-LA35 N-LAK0 N-KZS

40 40 Axial Colour: Achromate ad Apochromate Effect of differet material Axial chromatical aberratio chage with wavelegth Differet level of correctio:.no correctio: le, oe zero croig poit.achromatic correctio: - coicidece of outer color - remaiig error for ceter wavelegth - two zero croig poit 3. Apochromatic correctio: - coicidece of at leat three color - mall reidual aberratio - at leat 3 zero croig poit - pecial choice of gla type with aomalou partial dipertio eceery apochromate iglet C reidual error apochromate e reidual error achromate achromate D le

41 4 Spherochromatim Spherochromatim: variatio of pherical aberratio with wavelegth, Alterative otatio: Gauia chromatical error Idividual curve of pherical aberratio with color Covetioal achromate: - coicidig image locatio for red (C ) ad blue ( ) o axi (paraxial) - differece ad ecodary pectrum for gree (e) - but differet iterectio legth for fiite aperture ray r p Better balacig with half pherochromatim o axi 480 m 644 m aperture m 480 m 546 m 644 m D i R U 0 D ec 0. mm D 0. mm D chl D tot

42 Spherochromatim: Correctio by plitted achromate Split of cemeted urface: reduced zoal reidual aberratio poible a) Claical achromate Larger ditace of air gap: reduced pherochromatim Correctio priciple: Differet ray height at ecod le ad differet depedecie o ray height: ocu Spherical aberratio ~ ~ 4 b) Splitted achromate zoe mall Dy red blue c) Splitted achromate with large air gap pherochromatim mall Ref: D. Oche 4

43 43 New Achromate Covetioal achromate: trog bedig of image hell, typical R ptz.3 f Petzval hell mea image hell y Special electio of glae:. achromatizatio. Petzval flatteig Reidual field curvature: Combied coditio R ptz But uually o pherical correctio poible 0 0 f f R P elected crow gla perfect image plae lie of olutio for flit gla

44 44 New Achromate Thi coditio correpod to the requiremet to fid two glae o oe traight lie through the origi i the gla map D 0 Abbe umber PSK5 LAK33 K5 LL LAS40 S idex Example: K5 / PSK5: D = S / N-LAS40: D = LL / LAK33: D = The olutio i well kow a imple photographic le (ladcape le) LL LAK33 top Origi

45 45 Priciple of Gla Selectio i Optimizatio Deig rule for gla electio Differet deig goal:. Color correctio: idex large diperio differece deired poitive le field flatteig Petzval curvature. ield flatteig: large idex differece + + deired egative le color correctio + - availability of glae - - diperio Ref : H. Zügge

46 46 Burried Surface Nearly equal refractive idice Differece i Abbe umber ot larger tha 30.9 Gla Gla D D KZN N-PK KZN PSK N-LL Ultra KZSN L N-PSK SK SK N-SSK SK PSK SSK SSK4A LAKL N-PSK N-SK SK SK N-SK N-S4 N-LAK SL4 N-LAK SL56 LAN S LA D 30 D 30 D

47 47 Burried Surface Cemeted compoet with plae outer urface or ceter wavelegth oly plae parallel plate, ot ee i collimated light Curved cemeeted urface: - diperio for outer pectral weavelegth - color correctio without diturbig the mai wavelegth Example gree udeflected a) iglet b) color corrected iglet corrected Dz

48 48 Lateral Color Aberratio Diperio of the chief ray deviatio i the le Effect reemble the diperio of a prim i the upper part of the le I the image plae, the differece i the colored ray agle caue chage i the ray height The lateral color aberratio correpod to a chage of magificatio with the wavelegth diperio prim effect y Dy CHV chief ray z top image plae

49 49 Chromatic Variatio of Magificatio Lateral chromatical aberratio: Higher refractive idex i the blue reult i a troger ray bedig of the chief ray for a igle le The colored image have differet ize, the magificatio i wavelegth depedet Defiitio of the error: chage i image height/magificatio Correctio eed everal glae with differet diperio The aberratio trogly deped o the top poitio Dy Dy CHV CHV y y y y y e C C top red Dy CHV blue referece image plae

50 Surface ad Le cotributio of Lateral Color If the imagig of the etrace to the exit pupil uffer from axial chromatical aberratio, thi deliver a error of the exit pupil locatio ad alo of the chief ray agle: cheomatical lateral aberratio Travere chromatical aberratio of a le ytem Surface cotributio coefficiet of lateral color Correpodig le ummatio formula p p p p CHV Q H D y y H CHV CHV D p p p p CHV Q y y D p p p CHV y y 50

51 5 Lateral Color Correctio: Priciple of Symmetry Perfect ymmetrical ytem: magificatio m = - Stop i cetre of ymmetry Symmetrical cotributio of wave aberratio are doubled (pherical) Aymmetrical cotributio of wave aberratio vaihe W(-x) = -W(x) Eay correctio of: coma, ditortio, chromatical chage of magificatio frot part rear part 3

52 5 Chromatic Variatio of Magificatio Repreetatio of CHV:. Spot diagram. Magificatio m() 3. Travere aberratio: offet of chief ray referece chromatical magificatio differece pot diagram Y field height CHV 0.08 travere aberratio curve Dy axi field tagetial Dy field agital Dx Dy y p y p x p

53 Lateral color: Stop hift theorem Lateral color (LAC) for two differet top poitio a ad b (with top ize that defie the ame margial ray) relate to logitudial color (LOC) like thi: LAC a LAC b Dq LOC Where Dq i the top hift parameter which i the ame for every urface Dq If there i logitudial color i the ytem, there will be a top poitio for which lateral color vaihe If there i o logitudial color, lateral color i idepedet of the top poitio h a p h h b p 3 3 Ref: D. Oche Spot diagram for maximal field at differet top poitio 53

54 A M I fo : e c a f r u S oitarugifoc latot laixa fo oitarugifoc y a R m µ m m ) g e d ( : : A M I tops : J B O y r i A 3. m µ e r a 0 0 : : A M I : e c a f r u S e l a c S G E O S M R i e l d m m : A M I tops : J B O A M I : e c a f r u S tuoyal Lateral color: Stop hift theorem Example ytem with four N-BK7 lee corrected for e-lie Goal: Correct alo for C ad lie Spot diagram for maximal field with Airy dik : J B O : A M I m m ) g e d ( fo oitarugifoc tops. id the top poitio for which lateral color vaihe t i U y r i A. m µ e r a : u i d a R m µ 3 : S M R i e l d u i d a r : e l a c S G E O r a b 0 0 e c e r e f e R : y a R. Eure the ytem ha logitudial color top f e i h C margaid XMZ.tfihpotSleipieB top latot laixa :htgel mm Correct logitudial color there ad move top back oitarugifoc XMZ.tfihpotSleipieB fo r a b u i d a r t i U e c e r e f e R : u i d a R ) g e d ( f e i h C margaid xmz.tfihpotsleipieb top :htgel N-S6 tuoyal mm Ref: D. Oche xmz.tfihpotsleipieb margaid 54

55 55 Chromatic Variatio of Magificatio Impreio of CHV i real image Typical colored frige blue/red at edge viible Color equece deped o ig of CHV origial without lateral chromatic aberratio 0.5 % lateral chromatic aberratio % lateral chromatic aberratio

56 56 Chromatical Differece i Magificatio Color rig are hardly ee due to colored image Lateral hift of colored pf poitio Ref: J. Kaltebach

57 57 Axial Chromatical Aberratio Special effect ear black-white edge boarder mageta blue boarder Ref: J. Kaltebach

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig ad Aberratio Theory Leture 9: Chromatial aberratio 05-0-08 Herbert Gro Witer term 04 www.iap.ui-ea.de Prelimiary time hedule 30.0. Paraxial imagig paraxial opti, fudametal law of geometrial imagig,

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig ad Aberratio Theory Leture 9: Chromatial aberratio 04-0-09 Herbert Gro Witer term 03 www.iap.ui-ea.de Prelimiary time hedule 4.0. Paraxial imagig paraxial opti, fudametal law of geometrial imagig,

More information

Design and Correction of Optical Systems

Design and Correction of Optical Systems Deig ad Correctio of Optical Stem Lecture 3: Paraial optic 06-04-0 Herbert Gro Summer term 06 www.iap.ui-ea.de Prelimiar Schedule 06.04. Baic 3.04. Material ad Compoet 3 0.04. Paraial Optic 4 7.04. Optical

More information

Coma aberration. Lens Design OPTI 517. Prof. Jose Sasian

Coma aberration. Lens Design OPTI 517. Prof. Jose Sasian Coma aberratio Les Desig OPTI 517 Coma 0.5 wave 1.0 wave.0 waves 4.0 waves Spot diagram W W W... 040 0 H,, W 4 H W 131 W 00 311 H 3 H H cos W 3 W 00 W H cos W 400 111 H H cos cos 4 Coma though focus Cases

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig ad Aberratio Theor Lecture : Paraxial imagig 3--7 Herbert Gro Witer term 3 www.iap.ui-ea.de Overview Time: Thurda, 4. 5.3 Locatio: Abbeaum, HS, röbeltieg Web page o IAP homepage uder learig/material

More information

x z Increasing the size of the sample increases the power (reduces the probability of a Type II error) when the significance level remains fixed.

x z Increasing the size of the sample increases the power (reduces the probability of a Type II error) when the significance level remains fixed. ] z-tet for the mea, μ If the P-value i a mall or maller tha a pecified value, the data are tatitically igificat at igificace level. Sigificace tet for the hypothei H 0: = 0 cocerig the ukow mea of a populatio

More information

ME 410 MECHANICAL ENGINEERING SYSTEMS LABORATORY REGRESSION ANALYSIS

ME 410 MECHANICAL ENGINEERING SYSTEMS LABORATORY REGRESSION ANALYSIS ME 40 MECHANICAL ENGINEERING REGRESSION ANALYSIS Regreio problem deal with the relatiohip betwee the frequec ditributio of oe (depedet) variable ad aother (idepedet) variable() which i (are) held fied

More information

Design and Correction of Optical Systems

Design and Correction of Optical Systems Desig ad Correctio of Optical Systems Lecture : Materials ad compoets 07-04-4 Herbert Gross Summer term 07 www.iap.ui-jea.de Prelimiary Schedule - DCS 07 07.04. Basics.04. Materials ad Compoets 3 8.04.

More information

Overview of Aberrations

Overview of Aberrations Overview of Aberratios Les Desig OPTI 57 Aberratio From the Lati, aberrare, to wader from; Lati, ab, away, errare, to wader. Symmetry properties Overview of Aberratios (Departures from ideal behavior)

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig a Aberratio Theor Lecture : Paraxial imagig --9 Herbert Gro Witer term www.iap.ui-ea.e Overview Time: ria,. 3.3 Locatio: Abbeaum, HS, röbeltieg Web page o IAP homepage uer learig/material provie

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig ad Aberratio Theory Lecture 10: Sie coditio, alaatim ad ilaatim 017-1-18 Herbert Gro Witer term 017 www.ia.ui-ea.de Prelimiary time chedule 1 16.10. Paraxial imagig araxial otic, fudametal law of

More information

u t u 0 ( 7) Intuitively, the maximum principles can be explained by the following observation. Recall

u t u 0 ( 7) Intuitively, the maximum principles can be explained by the following observation. Recall Oct. Heat Equatio M aximum priciple I thi lecture we will dicu the maximum priciple ad uiquee of olutio for the heat equatio.. Maximum priciple. The heat equatio alo ejoy maximum priciple a the Laplace

More information

State space systems analysis

State space systems analysis State pace ytem aalyi Repreetatio of a ytem i tate-pace (tate-pace model of a ytem To itroduce the tate pace formalim let u tart with a eample i which the ytem i dicuio i a imple electrical circuit with

More information

Seidel sums and a p p l p icat a ion o s f or o r s imp m l p e e c as a es

Seidel sums and a p p l p icat a ion o s f or o r s imp m l p e e c as a es Seidel sums ad applicatios for simple cases Aspheric surface Geerally : o spherical rotatioally symmetric surfaces but ca be off-axis coic sectios Greatly help to improve performace, ad reduce the umber

More information

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION I liear regreio, we coider the frequecy ditributio of oe variable (Y) at each of everal level of a ecod variable (X). Y i kow a the depedet variable.

More information

Section 19. Dispersing Prisms

Section 19. Dispersing Prisms Sectio 9 Dispersig Prisms 9- Dispersig Prism 9- The et ray deviatio is the sum of the deviatios at the two surfaces. The ray deviatio as a fuctio of the iput agle : si si si cossi Prism Deviatio - Derivatio

More information

Section 19. Dispersing Prisms

Section 19. Dispersing Prisms 19-1 Sectio 19 Dispersig Prisms Dispersig Prism 19-2 The et ray deviatio is the sum of the deviatios at the two surfaces. The ray deviatio as a fuctio of the iput agle : 1 2 2 si si si cossi Prism Deviatio

More information

Capacitors and PN Junctions. Lecture 8: Prof. Niknejad. Department of EECS University of California, Berkeley. EECS 105 Fall 2003, Lecture 8

Capacitors and PN Junctions. Lecture 8: Prof. Niknejad. Department of EECS University of California, Berkeley. EECS 105 Fall 2003, Lecture 8 CS 15 Fall 23, Lecture 8 Lecture 8: Capacitor ad PN Juctio Prof. Nikejad Lecture Outlie Review of lectrotatic IC MIM Capacitor No-Liear Capacitor PN Juctio Thermal quilibrium lectrotatic Review 1 lectric

More information

Fig. 1: Streamline coordinates

Fig. 1: Streamline coordinates 1 Equatio of Motio i Streamlie Coordiate Ai A. Soi, MIT 2.25 Advaced Fluid Mechaic Euler equatio expree the relatiohip betwee the velocity ad the preure field i ivicid flow. Writte i term of treamlie coordiate,

More information

Erick L. Oberstar Fall 2001 Project: Sidelobe Canceller & GSC 1. Advanced Digital Signal Processing Sidelobe Canceller (Beam Former)

Erick L. Oberstar Fall 2001 Project: Sidelobe Canceller & GSC 1. Advanced Digital Signal Processing Sidelobe Canceller (Beam Former) Erick L. Obertar Fall 001 Project: Sidelobe Caceller & GSC 1 Advaced Digital Sigal Proceig Sidelobe Caceller (Beam Former) Erick L. Obertar 001 Erick L. Obertar Fall 001 Project: Sidelobe Caceller & GSC

More information

Design and Correction of Optical Systems

Design and Correction of Optical Systems Desig ad Correctio of Optical Systems Lecture : Materials ad compoets 08-04-6 Herbert Gross Summer term 08 www.iap.ui-jea.de Prelimiary Schedule - DCS 08 09.04. Basics 6.04. Materials ad Compoets 3 3.04.

More information

SOLUTION: The 95% confidence interval for the population mean µ is x ± t 0.025; 49

SOLUTION: The 95% confidence interval for the population mean µ is x ± t 0.025; 49 C22.0103 Sprig 2011 Homework 7 olutio 1. Baed o a ample of 50 x-value havig mea 35.36 ad tadard deviatio 4.26, fid a 95% cofidece iterval for the populatio mea. SOLUTION: The 95% cofidece iterval for the

More information

Design and Correction of Optical Systems

Design and Correction of Optical Systems Desig ad Correctio of Optical Sstems Lecture 3: Paraial optics 207-04-28 Herbert Gross Summer term 207 www.iap.ui-ea.de 2 Prelimiar Schedule - DCS 207 07.04. Basics 2 2.04. Materials ad Compoets 3 28.04.

More information

Explicit scheme. Fully implicit scheme Notes. Fully implicit scheme Notes. Fully implicit scheme Notes. Notes

Explicit scheme. Fully implicit scheme Notes. Fully implicit scheme Notes. Fully implicit scheme Notes. Notes Explicit cheme So far coidered a fully explicit cheme to umerically olve the diffuio equatio: T + = ( )T + (T+ + T ) () with = κ ( x) Oly table for < / Thi cheme i ometime referred to a FTCS (forward time

More information

Astigmatism Field Curvature Distortion

Astigmatism Field Curvature Distortion Astigmatism Field Curvature Distortio Les Desig OPTI 57 . Phil Earliest through focus images.t. Youg, O the mechaism of the eye, Tras Royal Soc Lod 80; 9: 3 88 ad plates. Astigmatism through focus Astigmatism

More information

Lens Design II. Lecture 1: Aberrations and optimization Herbert Gross. Winter term

Lens Design II. Lecture 1: Aberrations and optimization Herbert Gross. Winter term Lens Design II Lecture 1: Aberrations and optimization 18-1-17 Herbert Gross Winter term 18 www.iap.uni-jena.de Preliminary Schedule Lens Design II 18 1 17.1. Aberrations and optimization Repetition 4.1.

More information

ECEN620: Network Theory Broadband Circuit Design Fall 2014

ECEN620: Network Theory Broadband Circuit Design Fall 2014 ECE60: etwork Theory Broadbad Circuit Deig Fall 04 Lecture 3: PLL Aalyi Sam Palermo Aalog & Mixed-Sigal Ceter Texa A&M Uiverity Ageda & Readig PLL Overview & Applicatio PLL Liear Model Phae & Frequecy

More information

Last time: Completed solution to the optimum linear filter in real-time operation

Last time: Completed solution to the optimum linear filter in real-time operation 6.3 tochatic Etimatio ad Cotrol, Fall 4 ecture at time: Completed olutio to the oimum liear filter i real-time operatio emi-free cofiguratio: t D( p) F( p) i( p) dte dp e π F( ) F( ) ( ) F( p) ( p) 4444443

More information

Chapter 1 ASPECTS OF MUTIVARIATE ANALYSIS

Chapter 1 ASPECTS OF MUTIVARIATE ANALYSIS Chapter ASPECTS OF MUTIVARIATE ANALYSIS. Itroductio Defiitio Wiipedia: Multivariate aalyi MVA i baed o the tatitical priciple of multivariate tatitic which ivolve obervatio ad aalyi of more tha oe tatitical

More information

Long Wave Runup. Outline. u u. x 26 May 1983 Japan Sea (Shuto, 1985) Some Analytical Solutions in Long Wave Theory: Runup and Traveling Waves

Long Wave Runup. Outline. u u. x 26 May 1983 Japan Sea (Shuto, 1985) Some Analytical Solutions in Long Wave Theory: Runup and Traveling Waves Some Aalytical Solutio i og Wave Theory: uup ad Travelig Wave Ira Didekulova og Wave uup Ititute of Cyberetic at Talli Uiverity of Techology, Etoia Ititute of Applied Phyic Wave iduced by high-peed ferrie

More information

STA 4032 Final Exam Formula Sheet

STA 4032 Final Exam Formula Sheet Chapter 2. Probability STA 4032 Fial Eam Formula Sheet Some Baic Probability Formula: (1) P (A B) = P (A) + P (B) P (A B). (2) P (A ) = 1 P (A) ( A i the complemet of A). (3) If S i a fiite ample pace

More information

Brief Review of Linear System Theory

Brief Review of Linear System Theory Brief Review of Liear Sytem heory he followig iformatio i typically covered i a coure o liear ytem theory. At ISU, EE 577 i oe uch coure ad i highly recommeded for power ytem egieerig tudet. We have developed

More information

COMPARISONS INVOLVING TWO SAMPLE MEANS. Two-tail tests have these types of hypotheses: H A : 1 2

COMPARISONS INVOLVING TWO SAMPLE MEANS. Two-tail tests have these types of hypotheses: H A : 1 2 Tetig Hypothee COMPARISONS INVOLVING TWO SAMPLE MEANS Two type of hypothee:. H o : Null Hypothei - hypothei of o differece. or 0. H A : Alterate Hypothei hypothei of differece. or 0 Two-tail v. Oe-tail

More information

Chapter 9. Key Ideas Hypothesis Test (Two Populations)

Chapter 9. Key Ideas Hypothesis Test (Two Populations) Chapter 9 Key Idea Hypothei Tet (Two Populatio) Sectio 9-: Overview I Chapter 8, dicuio cetered aroud hypothei tet for the proportio, mea, ad tadard deviatio/variace of a igle populatio. However, ofte

More information

Lenses and Imaging (Part II)

Lenses and Imaging (Part II) Lee ad Imagig (Part II) emider rom Part I Surace o poitive/egative power eal ad virtual image Imagig coditio Thick lee Pricipal plae 09/20/04 wk3-a- The power o urace Poitive power : eitig ray coverge

More information

Heat Equation: Maximum Principles

Heat Equation: Maximum Principles Heat Equatio: Maximum Priciple Nov. 9, 0 I thi lecture we will dicu the maximum priciple ad uiquee of olutio for the heat equatio.. Maximum priciple. The heat equatio alo ejoy maximum priciple a the Laplace

More information

Statistics and Chemical Measurements: Quantifying Uncertainty. Normal or Gaussian Distribution The Bell Curve

Statistics and Chemical Measurements: Quantifying Uncertainty. Normal or Gaussian Distribution The Bell Curve Statitic ad Chemical Meauremet: Quatifyig Ucertaity The bottom lie: Do we trut our reult? Should we (or ayoe ele)? Why? What i Quality Aurace? What i Quality Cotrol? Normal or Gauia Ditributio The Bell

More information

Tables and Formulas for Sullivan, Fundamentals of Statistics, 2e Pearson Education, Inc.

Tables and Formulas for Sullivan, Fundamentals of Statistics, 2e Pearson Education, Inc. Table ad Formula for Sulliva, Fudametal of Statitic, e. 008 Pearo Educatio, Ic. CHAPTER Orgaizig ad Summarizig Data Relative frequecy frequecy um of all frequecie Cla midpoit: The um of coecutive lower

More information

Summary of formulas Summary of optical systems

Summary of formulas Summary of optical systems Summar of formulas Summar of optical sstems Les Desig OPTI 57 Imagig: cetral projectio X' Y' Z' a X b Y c Z d axbyczd 0 0 0 0 a X b Y c Z d axbyczd 0 0 0 0 a X byczd axbyczd 3 3 3 3 0 0 0 0 Colliear trasformatio

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig a Aberratio Theor Lecture : Paraxial imagig --9 Herbert Gro Witer term www.iap.ui-ea.e Overview Time: ria,. 3.3 Locatio: Abbeaum, HS, röbeltieg Web page o IAP homepage uer learig/material provie

More information

TESTS OF SIGNIFICANCE

TESTS OF SIGNIFICANCE TESTS OF SIGNIFICANCE Seema Jaggi I.A.S.R.I., Library Aveue, New Delhi eema@iari.re.i I applied ivetigatio, oe i ofte itereted i comparig ome characteritic (uch a the mea, the variace or a meaure of aociatio

More information

CONTROL SYSTEMS. Chapter 7 : Bode Plot. 40dB/dec 1.0. db/dec so resultant slope will be 20 db/dec and this is due to the factor s

CONTROL SYSTEMS. Chapter 7 : Bode Plot. 40dB/dec 1.0. db/dec so resultant slope will be 20 db/dec and this is due to the factor s CONTROL SYSTEMS Chapter 7 : Bode Plot GATE Objective & Numerical Type Solutio Quetio 6 [Practice Book] [GATE EE 999 IIT-Bombay : 5 Mark] The aymptotic Bode plot of the miimum phae ope-loop trafer fuctio

More information

Statistical Inference Procedures

Statistical Inference Procedures Statitical Iferece Procedure Cofidece Iterval Hypothei Tet Statitical iferece produce awer to pecific quetio about the populatio of iteret baed o the iformatio i a ample. Iferece procedure mut iclude a

More information

Chapter 7, Solution 1C.

Chapter 7, Solution 1C. hapter 7, Solutio 1. he velocity of the fluid relative to the immered olid body ufficietly far away from a body i called the free-tream velocity,. he uptream or approach velocity i the velocity of the

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

Optics. n n. sin. 1. law of rectilinear propagation 2. law of reflection = 3. law of refraction

Optics. n n. sin. 1. law of rectilinear propagation 2. law of reflection = 3. law of refraction Optics What is light? Visible electromagetic radiatio Geometrical optics (model) Light-ray: extremely thi parallel light beam Usig this model, the explaatio of several optical pheomea ca be give as the

More information

STUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN ( )

STUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN ( ) STUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN Suppoe that we have a ample of meaured value x1, x, x3,, x of a igle uow quatity. Aumig that the meauremet are draw from a ormal ditributio

More information

THE CONCEPT OF THE ROOT LOCUS. H(s) THE CONCEPT OF THE ROOT LOCUS

THE CONCEPT OF THE ROOT LOCUS. H(s) THE CONCEPT OF THE ROOT LOCUS So far i the tudie of cotrol yte the role of the characteritic equatio polyoial i deteriig the behavior of the yte ha bee highlighted. The root of that polyoial are the pole of the cotrol yte, ad their

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig ad Aberratio Theory Leture 9: Chromatia aberratio 0-- Herbert Gro Witer term 0 www.iap.ui-ea.de Preimiary time hedue 9.0. Paraxia imagig paraxia opti, fudameta aw of geometria imagig, ompoud ytem

More information

Imaging and Aberration Theory

Imaging and Aberration Theory Imagig ad Aberratio Theory Lectre 10: Sie coditio, alaatim ad ilaatim 016-01-05 Herbert Gro Witer term 015 www.ia.i-ea.de Prelimiary time chedle 1 0.10. Paraxial imagig araxial otic, fdametal law of geometrical

More information

Lecture 8: Light propagation in anisotropic media

Lecture 8: Light propagation in anisotropic media Lecture 8: Light propagatio i aiotropic media Petr Kužel Teor claificatio of aiotropic media Wave equatio igemode polariatio eigetate Normal urface (urface of refractive idice) Idicatri (ellipoid of refractive

More information

LECTURE 13 SIMULTANEOUS EQUATIONS

LECTURE 13 SIMULTANEOUS EQUATIONS NOVEMBER 5, 26 Demad-upply ytem LETURE 3 SIMULTNEOUS EQUTIONS I thi lecture, we dicu edogeeity problem that arie due to imultaeity, i.e. the left-had ide variable ad ome of the right-had ide variable are

More information

Lecture 30: Frequency Response of Second-Order Systems

Lecture 30: Frequency Response of Second-Order Systems Lecture 3: Frequecy Repoe of Secod-Order Sytem UHTXHQF\ 5HVSRQVH RI 6HFRQGUGHU 6\VWHPV A geeral ecod-order ytem ha a trafer fuctio of the form b + b + b H (. (9.4 a + a + a It ca be table, utable, caual

More information

a 1 = 1 a a a a n n s f() s = Σ log a 1 + a a n log n sup log a n+1 + a n+2 + a n+3 log n sup () s = an /n s s = + t i

a 1 = 1 a a a a n n s f() s = Σ log a 1 + a a n log n sup log a n+1 + a n+2 + a n+3 log n sup () s = an /n s s = + t i 0 Dirichlet Serie & Logarithmic Power Serie. Defiitio & Theorem Defiitio.. (Ordiary Dirichlet Serie) Whe,a,,3, are complex umber, we call the followig Ordiary Dirichlet Serie. f() a a a a 3 3 a 4 4 Note

More information

EE 508 Lecture 6. Dead Networks Scaling, Normalization and Transformations

EE 508 Lecture 6. Dead Networks Scaling, Normalization and Transformations EE 508 Lecture 6 Dead Network Scalig, Normalizatio ad Traformatio Filter Cocept ad Termiology 2-d order polyomial characterizatio Biquadratic Factorizatio Op Amp Modelig Stability ad Itability Roll-off

More information

VIII. Interval Estimation A. A Few Important Definitions (Including Some Reminders)

VIII. Interval Estimation A. A Few Important Definitions (Including Some Reminders) VIII. Iterval Etimatio A. A Few Importat Defiitio (Icludig Some Remider) 1. Poit Etimate - a igle umerical value ued a a etimate of a parameter.. Poit Etimator - the ample tatitic that provide the poit

More information

To the use of Sellmeier formula

To the use of Sellmeier formula To the use of Sellmeier formula by Volkmar Brücker Seior Experte Service (SES) Bo ad HfT Leipzig, Germay Abstract Based o dispersio of pure silica we proposed a geeral Sellmeier formula for various dopats

More information

A criterion for easiness of certain SAT-problems

A criterion for easiness of certain SAT-problems A criterio for eaie of certai SAT-problem Berd R. Schuh Dr. Berd Schuh, D-50968 Köl, Germay; berd.chuh@etcologe.de keyword: compleity, atifiability, propoitioal logic, P, NP, -i-3sat, eay/hard itace Abtract.

More information

The axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c.

The axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c. 5.4 Applicatio of Perturbatio Methods to the Dispersio Model for Tubular Reactors The axial dispersio model for tubular reactors at steady state ca be described by the followig equatios: d c Pe dz z =

More information

Section 7. Gaussian Reduction

Section 7. Gaussian Reduction 7- Sectio 7 Gaussia eductio Paraxial aytrace Equatios eractio occurs at a iterace betwee two optical spaces. The traser distace t' allows the ray height y' to be determied at ay plae withi a optical space

More information

R is a scalar defined as follows:

R is a scalar defined as follows: Math 8. Notes o Dot Product, Cross Product, Plaes, Area, ad Volumes This lecture focuses primarily o the dot product ad its may applicatios, especially i the measuremet of agles ad scalar projectio ad

More information

INF-GEO Solutions, Geometrical Optics, Part 1

INF-GEO Solutions, Geometrical Optics, Part 1 INF-GEO430 20 Solutios, Geometrical Optics, Part Reflectio by a symmetric triagular prism Let be the agle betwee the two faces of a symmetric triagular prism. Let the edge A where the two faces meet be

More information

TUTORIAL 6. Review of Electrostatic

TUTORIAL 6. Review of Electrostatic TUTOIAL 6 eview of Electrotatic Outlie Some mathematic Coulomb Law Gau Law Potulatio for electrotatic Electric potetial Poio equatio Boudar coditio Capacitace Some mathematic Del operator A operator work

More information

CHAPTER 6. Confidence Intervals. 6.1 (a) y = 1269; s = 145; n = 8. The standard error of the mean is = s n = = 51.3 ng/gm.

CHAPTER 6. Confidence Intervals. 6.1 (a) y = 1269; s = 145; n = 8. The standard error of the mean is = s n = = 51.3 ng/gm. } CHAPTER 6 Cofidece Iterval 6.1 (a) y = 1269; = 145; = 8. The tadard error of the mea i SE ȳ = = 145 8 = 51.3 g/gm. (b) y = 1269; = 145; = 30. The tadard error of the mea i ȳ = 145 = 26.5 g/gm. 30 6.2

More information

THE LEVEL SET METHOD APPLIED TO THREE-DIMENSIONAL DETONATION WAVE PROPAGATION. Wen Shanggang, Sun Chengwei, Zhao Feng, Chen Jun

THE LEVEL SET METHOD APPLIED TO THREE-DIMENSIONAL DETONATION WAVE PROPAGATION. Wen Shanggang, Sun Chengwei, Zhao Feng, Chen Jun THE LEVEL SET METHOD APPLIED TO THREE-DIMENSIONAL DETONATION WAVE PROPAGATION We Shaggag, Su Chegwei, Zhao Feg, Che Ju Laboratory for Shock Wave ad Detoatio Physics Research, Southwest Istitute of Fluid

More information

Zeta-reciprocal Extended reciprocal zeta function and an alternate formulation of the Riemann hypothesis By M. Aslam Chaudhry

Zeta-reciprocal Extended reciprocal zeta function and an alternate formulation of the Riemann hypothesis By M. Aslam Chaudhry Zeta-reciprocal Eteded reciprocal zeta fuctio ad a alterate formulatio of the Riema hypothei By. Alam Chaudhry Departmet of athematical Sciece, Kig Fahd Uiverity of Petroleum ad ieral Dhahra 36, Saudi

More information

100(1 α)% confidence interval: ( x z ( sample size needed to construct a 100(1 α)% confidence interval with a margin of error of w:

100(1 α)% confidence interval: ( x z ( sample size needed to construct a 100(1 α)% confidence interval with a margin of error of w: Stat 400, ectio 7. Large Sample Cofidece Iterval ote by Tim Pilachowki a Large-Sample Two-ided Cofidece Iterval for a Populatio Mea ectio 7.1 redux The poit etimate for a populatio mea µ will be a ample

More information

Ma 530 Infinite Series I

Ma 530 Infinite Series I Ma 50 Ifiite Series I Please ote that i additio to the material below this lecture icorporated material from the Visual Calculus web site. The material o sequeces is at Visual Sequeces. (To use this li

More information

Chapter 1 Econometrics

Chapter 1 Econometrics Chapter Ecoometric There are o exercie or applicatio i Chapter. 0 Pearo Educatio, Ic. Publihig a Pretice Hall Chapter The Liear Regreio Model There are o exercie or applicatio i Chapter. 0 Pearo Educatio,

More information

Questions about the Assignment. Describing Data: Distributions and Relationships. Measures of Spread Standard Deviation. One Quantitative Variable

Questions about the Assignment. Describing Data: Distributions and Relationships. Measures of Spread Standard Deviation. One Quantitative Variable Quetio about the Aigmet Read the quetio ad awer the quetio that are aked Experimet elimiate cofoudig variable Decribig Data: Ditributio ad Relatiohip GSS people attitude veru their characteritic ad poue

More information

IntroEcono. Discrete RV. Continuous RV s

IntroEcono. Discrete RV. Continuous RV s ItroEcoo Aoc. Prof. Poga Porchaiwiekul, Ph.D... ก ก e-mail: Poga.P@chula.ac.th Homepage: http://pioeer.chula.ac.th/~ppoga (c) Poga Porchaiwiekul, Chulalogkor Uiverity Quatitative, e.g., icome, raifall

More information

CE3502 Environmental Monitoring, Measurements, and Data Analysis (EMMA) Spring 2008 Final Review

CE3502 Environmental Monitoring, Measurements, and Data Analysis (EMMA) Spring 2008 Final Review CE35 Evirometal Moitorig, Meauremet, ad Data Aalyi (EMMA) Sprig 8 Fial Review I. Topic:. Decriptive tatitic: a. Mea, Stadard Deviatio, COV b. Bia (accuracy), preciio, Radom v. ytematic error c. Populatio

More information

Lens Design II. Lecture 6: Chromatical correction I Herbert Gross. Winter term

Lens Design II. Lecture 6: Chromatical correction I Herbert Gross. Winter term Ls Dsig II Lctur 6: Chromatical corrctio I 07--0 Hrbrt Gross Witr trm 07 www.iap.ui-a.d Prlimiary Schdul Ls Dsig II 07 6.0. Abrratios ad optimizatio Rptitio 3.0. Structural modificatios Zro oprads, ls

More information

Applied Mathematical Sciences, Vol. 9, 2015, no. 3, HIKARI Ltd,

Applied Mathematical Sciences, Vol. 9, 2015, no. 3, HIKARI Ltd, Applied Mathematical Sciece Vol 9 5 o 3 7 - HIKARI Ltd wwwm-hiaricom http://dxdoiorg/988/am54884 O Poitive Defiite Solutio of the Noliear Matrix Equatio * A A I Saa'a A Zarea* Mathematical Sciece Departmet

More information

Professor: Mihnea UDREA DIGITAL SIGNAL PROCESSING. Grading: Web: MOODLE. 1. Introduction. General information

Professor: Mihnea UDREA DIGITAL SIGNAL PROCESSING. Grading: Web:   MOODLE. 1. Introduction. General information Geeral iformatio DIGITL SIGL PROCESSIG Profeor: ihea UDRE B29 mihea@comm.pub.ro Gradig: Laboratory: 5% Proect: 5% Tet: 2% ial exam : 5% Coure quiz: ±% Web: www.electroica.pub.ro OODLE 2 alog igal proceig

More information

Content 1. Experimental Setup... 2

Content 1. Experimental Setup... 2 Cotet 1. Exerimetal Setu.... Theory... 3.1. Reflectio... 3.. Selliu law... 4.3. Parallel hift... 5.4. Total iteral reflectio... 6.5. Beam roagatio through rim... 7.6. Prim dierio... 8.7. Gratig dierio...

More information

M227 Chapter 9 Section 1 Testing Two Parameters: Means, Variances, Proportions

M227 Chapter 9 Section 1 Testing Two Parameters: Means, Variances, Proportions M7 Chapter 9 Sectio 1 OBJECTIVES Tet two mea with idepedet ample whe populatio variace are kow. Tet two variace with idepedet ample. Tet two mea with idepedet ample whe populatio variace are equal Tet

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 30 Sigal & Sytem Prof. Mark Fowler Note Set #8 C-T Sytem: Laplace Traform Solvig Differetial Equatio Readig Aigmet: Sectio 6.4 of Kame ad Heck / Coure Flow Diagram The arrow here how coceptual flow

More information

Lens Design II. Lecture 6: Chromatical correction I Herbert Gross. Winter term

Lens Design II. Lecture 6: Chromatical correction I Herbert Gross. Winter term Ls Dsig II Lctur 6: Chromatical corrctio I 08--8 Hrbrt Gross Witr trm 08 www.iap.ui-a.d Prlimiary Schdul Ls Dsig II 08 7.0. Abrratios ad optimizatio Rptitio 4.0. Structural modificatios Zro oprads, ls

More information

The Performance of Feedback Control Systems

The Performance of Feedback Control Systems The Performace of Feedbac Cotrol Sytem Objective:. Secify the meaure of erformace time-domai the firt te i the deig roce Percet overhoot / Settlig time T / Time to rie / Steady-tate error e. ut igal uch

More information

On The Computation Of Weighted Shapley Values For Cooperative TU Games

On The Computation Of Weighted Shapley Values For Cooperative TU Games O he Computatio Of Weighted hapley Value For Cooperative U Game Iriel Draga echical Report 009-0 http://www.uta.edu/math/preprit/ Computatio of Weighted hapley Value O HE COMPUAIO OF WEIGHED HAPLEY VALUE

More information

We will look for series solutions to (1) around (at most) regular singular points, which without

We will look for series solutions to (1) around (at most) regular singular points, which without ENM 511 J. L. Baai April, 1 Frobeiu Solutio to a d order ODE ear a regular igular poit Coider the ODE y 16 + P16 y 16 + Q1616 y (1) We will look for erie olutio to (1) aroud (at mot) regular igular poit,

More information

10-716: Advanced Machine Learning Spring Lecture 13: March 5

10-716: Advanced Machine Learning Spring Lecture 13: March 5 10-716: Advaced Machie Learig Sprig 019 Lecture 13: March 5 Lecturer: Pradeep Ravikumar Scribe: Charvi Ratogi, Hele Zhou, Nicholay opi Note: Lae template courtey of UC Berkeley EECS dept. Diclaimer: hee

More information

Imaging and nulling properties of sparse-aperture Fizeau interferometers Imaging and nulling properties of sparse-aperture Fizeau interferometers

Imaging and nulling properties of sparse-aperture Fizeau interferometers Imaging and nulling properties of sparse-aperture Fizeau interferometers Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Fraçois Héault Istitut de Plaétologie et d Astrophysique de Greoble,

More information

Lens Design I. Lecture 12: Correction I Herbert Gross. Summer term

Lens Design I. Lecture 12: Correction I Herbert Gross. Summer term Les Desig I Leture : Corretio I 05-07-06 Herbert Gross Summer term 05 www.iap.ui-jea.de relimiary Shedule 3.04. Basis 0.04. roperties of optial systrems I 3 7.05. 4 04.05. roperties of optial systrems

More information

CALCULUS BASIC SUMMER REVIEW

CALCULUS BASIC SUMMER REVIEW CALCULUS BASIC SUMMER REVIEW NAME rise y y y Slope of a o vertical lie: m ru Poit Slope Equatio: y y m( ) The slope is m ad a poit o your lie is, ). ( y Slope-Itercept Equatio: y m b slope= m y-itercept=

More information

EULER-MACLAURIN SUM FORMULA AND ITS GENERALIZATIONS AND APPLICATIONS

EULER-MACLAURIN SUM FORMULA AND ITS GENERALIZATIONS AND APPLICATIONS EULER-MACLAURI SUM FORMULA AD ITS GEERALIZATIOS AD APPLICATIOS Joe Javier Garcia Moreta Graduate tudet of Phyic at the UPV/EHU (Uiverity of Baque coutry) I Solid State Phyic Addre: Practicate Ada y Grijalba

More information

Geodynamics Lecture 11 Brittle deformation and faulting

Geodynamics Lecture 11 Brittle deformation and faulting Geodamic Lecture 11 Brittle deformatio ad faultig Lecturer: David Whipp david.whipp@heliki.fi! 7.10.2014 Geodamic www.heliki.fi/liopito 1 Goal of thi lecture Preet mai brittle deformatio mechaim()! Dicu

More information

Last time: Ground rules for filtering and control system design

Last time: Ground rules for filtering and control system design 6.3 Stochatic Etimatio ad Cotrol, Fall 004 Lecture 7 Lat time: Groud rule for filterig ad cotrol ytem deig Gral ytem Sytem parameter are cotaied i w( t ad w ( t. Deired output i grated by takig the igal

More information

Chapter 35 - Refraction

Chapter 35 - Refraction Chapter 35 - Refractio Objectives: After completig this module, you should be able to: Defie ad apply the cocept of the idex of refractio ad discuss its effect o the velocity ad wavelegth of light. Apply

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

Weak formulation and Lagrange equations of motion

Weak formulation and Lagrange equations of motion Chapter 4 Weak formulatio ad Lagrage equatio of motio A mot commo approach to tudy tructural dyamic i the ue of the Lagrage equatio of motio. Thee are obtaied i thi chapter tartig from the Cauchy equatio

More information

UNIVERSITY OF CALICUT

UNIVERSITY OF CALICUT Samplig Ditributio 1 UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION BSc. MATHEMATICS COMPLEMENTARY COURSE CUCBCSS 2014 Admiio oward III Semeter STATISTICAL INFERENCE Quetio Bak 1. The umber of poible

More information

Orthogonal transformations

Orthogonal transformations Orthogoal trasformatios October 12, 2014 1 Defiig property The squared legth of a vector is give by takig the dot product of a vector with itself, v 2 v v g ij v i v j A orthogoal trasformatio is a liear

More information

HE ATOM & APPROXIMATION METHODS MORE GENERAL VARIATIONAL TREATMENT. Examples:

HE ATOM & APPROXIMATION METHODS MORE GENERAL VARIATIONAL TREATMENT. Examples: 5.6 4 Lecture #3-4 page HE ATOM & APPROXIMATION METHODS MORE GENERAL VARIATIONAL TREATMENT Do t restrict the wavefuctio to a sigle term! Could be a liear combiatio of several wavefuctios e.g. two terms:

More information

Solving equations (incl. radical equations) involving these skills, but ultimately solvable by factoring/quadratic formula (no complex roots)

Solving equations (incl. radical equations) involving these skills, but ultimately solvable by factoring/quadratic formula (no complex roots) Evet A: Fuctios ad Algebraic Maipulatio Factorig Square of a sum: ( a + b) = a + ab + b Square of a differece: ( a b) = a ab + b Differece of squares: a b = ( a b )(a + b ) Differece of cubes: a 3 b 3

More information

1. (a) If u (I : R J), there exists c 0 in R such that for all q 0, cu q (I : R J) [q] I [q] : R J [q]. Hence, if j J, for all q 0, j q (cu q ) =

1. (a) If u (I : R J), there exists c 0 in R such that for all q 0, cu q (I : R J) [q] I [q] : R J [q]. Hence, if j J, for all q 0, j q (cu q ) = Math 615, Witer 2016 Problem Set #5 Solutio 1. (a) If u (I : R J), there exit c 0 i R uch that for all q 0, cu q (I : R J) [q] I [q] : R J [q]. Hece, if j J, for all q 0, j q (cu q ) = c(ju) q I [q], o

More information

Introduction to Extreme Value Theory Laurens de Haan, ISM Japan, Erasmus University Rotterdam, NL University of Lisbon, PT

Introduction to Extreme Value Theory Laurens de Haan, ISM Japan, Erasmus University Rotterdam, NL University of Lisbon, PT Itroductio to Extreme Value Theory Laures de Haa, ISM Japa, 202 Itroductio to Extreme Value Theory Laures de Haa Erasmus Uiversity Rotterdam, NL Uiversity of Lisbo, PT Itroductio to Extreme Value Theory

More information

17 Phonons and conduction electrons in solids (Hiroshi Matsuoka)

17 Phonons and conduction electrons in solids (Hiroshi Matsuoka) 7 Phoos ad coductio electros i solids Hiroshi Matsuoa I this chapter we will discuss a miimal microscopic model for phoos i a solid ad a miimal microscopic model for coductio electros i a simple metal.

More information

M 340L CS Homew ork Set 6 Solutions

M 340L CS Homew ork Set 6 Solutions 1. Suppose P is ivertible ad M 34L CS Homew ork Set 6 Solutios A PBP 1. Solve for B i terms of P ad A. Sice A PBP 1, w e have 1 1 1 B P PBP P P AP ( ).. Suppose ( B C) D, w here B ad C are m matrices ad

More information