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

Size: px
Start display at page:

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

Transcription

1 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, Uiversité Joseph Fourier, CNRS, B.P. 53, Greoble Frace Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

2 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Geeral layout of a Fizeau iterferometer B P 1 P 2 (P) Telescope 1 F C Telescope 2 Relay optics 1 APS 1 APS 2 beam 1 B beam 2 Relay optics 2 Covergig optics Divergig optics Fold mirror Beamsplitter Acromatic Phase Shifter Combiig optics (P ) F Focal plae All telescopes assumed to be idetical All exit pupils optically cojugated with etrace pupils Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

3 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers V -sky agular coordiates Sky object u v U P 2 P 3 s Y Iput pupils defied by vectors P utput pupils defied by vectors P 1 N s B P 1 P 4 D Etrace pupil plae X D P 4 P 1 Y B Coordiates systems P 3 P 2 s s Exit pupil plae X F M Y M Detectio plae X Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

4 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Image of a sky object projected oto the sky Most geeral bject-image relatioship : I( s) = s T = 1 Ω ( s ) PSF ( s - s ) N a exp [ iφ ] exp[ ikξ( s, s) ] 2 dω with ξ ( s, s ) = s P s' P' / m PSF T (s) : PSF of a idividual collectig telescope, projected back oto the sky a : amplitude trasmissio factor of the th telescope ϕ : phase-shift alog the th iterferometer arm for cophasig or ullig purpose k = 2/λ : waveumber of moochromatic electro-magetic field m : optical compressio factor betwee telescopes ad their relay optics Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

5 First-order approximatio Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Golde rule of Fizeau iterferometers Necessary coditio : P = m P bject-image relatioship [ PSF ( s) F( s) ] ( ) I( s) = T s Ivariat PSF over the Field of view (FoV) Pupil I Pupil ut N = PSFT ( s) a exp = 1 F( s) [ ] [ ] 2 iφ exp i k sp Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

6 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Examples of applicatio Effect of pupil aberratios Deviatios from the golde rule : ohomothetic exit pupil combiers Simulatio of images i ullig mode Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

7 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Effect of pupil aberratios Develop all vectors at 2 d -order, e.g. : si u u ' x ' ( 1+ dz F' ) ' ' s = cos u si v v = y ( 1+ dz F' ) cos u cos v 1 u 2 v Isert ito the PD : ξ Use geeral bject-image relatio : No loger a covolutio operator! ' P ' ' ' ' ' (, s ) dz dz m + u x + v y ( u x + v y )( 1+ dz F' ) s I( s) = s 0 T = 1 Ω ( s ) PSF ( s - s ) N 0 dz a dz 2 2 ' 2 2 ( u + v ) 2 dz ( u + v ) 2m 0 exp 0 [ iφ ] exp[ ikξ( s, s) ] ' 2 dω m B B Flat wavefrot Flat wavefrot P 1 P 1 dz 1 dz 1 (P) Iput pupils dz 2 P 2 Collectig telescopes utput pupils (P ) dz 2 P 2 Multi-axial combier (exit pupil plae) F F Beam compressors X Focal plae Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

8 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Pupil aberratio: 2 telescopes Achievable FoV PSF at FoV cetre PSF at 0.3 arcsec PSF at 0.6 arcsec Aberrated pupil Case 2 Aberrated pupil Case 1 0 No pupil aberratio Ivariat PSF Curved friges, chagig PSF Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

9 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Pupil aberratio: 8 telescopes Achievable FoV PSF at FoV cetre PSF at 0.3 arcsec PSF at 0.6 arcsec Aberrated pupil Case 2 Aberrated pupil Case No pupil aberratio Ivariat PSF Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

10 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Differet combiig schemes From collectig telescopes From collectig telescopes B B APS 1 APS 2 beam 1 Axial combier F Frige tracker (P ) Focal plae beam 2 beams 1-4 beams 2-3 Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui B F (P ) Focal plae Crossedcubes uller

11 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Axially Combied Iterferometer (ACI) Telescope 1 Relay optics 1 P 1 beam 1 Axial beam combier F B Telescope 2 APS 1 APS 2 Frige tracker (P ) Focal plae beam 2 Ι( s) = P 2 Relay optics 2 PSF Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui T (P) ( s) * Co-axial combiatio by meas of a balaced set of beamsplitters Extiguishes all diffracted light origiatig from cetral star ly leaves plaet photos Specific bject-image relatioship N = 1 a exp [ iφ ] exp[ iksp ] 2 ( s)

12 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Crossed-cubes uller (CCN) See the Cheapest uller i the World : e talk o Thursday afteroo, 2 posters o Wedesday afteroo Cube 1 Cube 2 Y Focusig optics X " Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

13 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Pseudo-images of a compaio 20 m 10 mm Star Plaet Fake sky objects Telescope array Phase-shifts maps Star Plaet photos oly Plaet Axial combier Maximal desificatio Fizeau iterferometer Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

14 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Coclusio A simple Fourier optics formalism allows fast evaluatio of ullig Fizeau iterferometers performace Icludig PSF, achievable Field of view (FoV), ullig maps ad pseudo-images Whatever is the telescope umber N I presece of optical defects (pupil aberratios) Also applicable to o-fizeau iterferometers Simple formalism, o actual Fourier or Fresel trasforms required (gai i accuracy ad computig time) Simulatios show that that the most efficiet ullig schemes should use axial combiers or multi-axial combiers with maximal desificatio (e.g. Crossed-cubes uller) Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

15 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Previous publicatios Fibered ullig telescope for extra-solar coroagraphy, ptics Letters vol. 34, 7, p (2009) Computig extictio maps of star ullig iterferometers, ptics Express vol. 16, (2008) Fie art of computig ullig iterferometer maps, Proceedigs of the SPIE 7013, 70131X (2008) Simple Fourier optics formalism for high agular resolutio systems ad ullig iterferometry, JSA A vol. 27, p (2010) PSF ad field of view characteristics of imagig ad ullig iterferometers, Proceedigs of the SPIE vol. 7734, (2010) Imagig power of multi-fibered ullig telescopes for extra-solar plaet characterizatio, Proceedigs of the SPIE vol. 8151, 81510A (2011) Cheapest uller i the world: crossed beamsplitter cubes, Proceedigs of the SPIE vol. 9146, this coferece Perhaps oe sythesis paper some day Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui

PSF and Field of View characteristics of imaging and nulling interferometers

PSF and Field of View characteristics of imaging and nulling interferometers PSF ad FoV characteristics of imagig ad ullig iterferometers PSF ad Field of View characteristics of imagig ad ullig iterferometers Fraçois Héault UMR CNRS 6525 H. Fizeau UNS, CNRS, CA Aveue Nicolas Coperic

More information

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 Fraçois Héault Istitut de Plaétologie et d Astrophysique de Greoble Uiversité Joseph Fourier, Cetre Natioal de la Recherche Scietifique.P.

More information

PSF and field of view characteristics of imaging and nulling interferometers

PSF and field of view characteristics of imaging and nulling interferometers PSF ad field of view characteristics of imagig ad ullig iterferometers Fraçois Héault UMR 6525 CRS H. Fizeau US, CA, Aveue icolas Coperic, 06130 Grasse Frace ASTRACT I this commuicatio are preseted some

More information

Cheapest nuller in the World: Crossed beamsplitter cubes

Cheapest nuller in the World: Crossed beamsplitter cubes Cheapest nuller in the World: François Hénault Institut de Planétologie et d Astrophysique de Grenoble, Université Joseph Fourier, CNRS, B.P. 53, 38041 Grenoble France Alain Spang Laboratoire Lagrange,

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

Fully achromatic nulling interferometer (FANI) for high SNR exoplanet characterization

Fully achromatic nulling interferometer (FANI) for high SNR exoplanet characterization Fully achromatic nulling interferometer (FANI) for high SNR exoplanet characterization François Hénault Institut de Planétologie et d Astrophysique de Grenoble Université Joseph Fourier Centre National

More information

Analysis of azimuthal phase mask coronagraphs

Analysis of azimuthal phase mask coronagraphs Aalysis of azimuthal phase mask coroagraphs Fraçois Héault Istitut de Plaétologie et d Astrophysique de Greoble Uiversité Greoble-Alpes, Cetre Natioal de la Recherche Scietifique B.P. 53, 384 Greoble Frace

More information

Computing the output response of LTI Systems.

Computing the output response of LTI Systems. Computig the output respose of LTI Systems. By breaig or decomposig ad represetig the iput sigal to the LTI system ito terms of a liear combiatio of a set of basic sigals. Usig the superpositio property

More information

Fizeau s Experiment with Moving Water. New Explanation. Gennady Sokolov, Vitali Sokolov

Fizeau s Experiment with Moving Water. New Explanation. Gennady Sokolov, Vitali Sokolov Fizeau s Experimet with Movig Water New Explaatio Geady Sokolov, itali Sokolov Email: sokolov@vitalipropertiescom The iterferece experimet with movig water carried out by Fizeau i 85 is oe of the mai cofirmatios

More information

ADVANCED DIGITAL SIGNAL PROCESSING

ADVANCED DIGITAL SIGNAL PROCESSING ADVANCED DIGITAL SIGNAL PROCESSING PROF. S. C. CHAN (email : sccha@eee.hku.hk, Rm. CYC-702) DISCRETE-TIME SIGNALS AND SYSTEMS MULTI-DIMENSIONAL SIGNALS AND SYSTEMS RANDOM PROCESSES AND APPLICATIONS ADAPTIVE

More information

Multi-spectral piston sensor for co-phasing giant segmented mirrors and multi-aperture interferometric arrays

Multi-spectral piston sensor for co-phasing giant segmented mirrors and multi-aperture interferometric arrays Multi-spectral pisto sesor for co-phasig giat segmeted mirrors Multi-spectral pisto sesor for co-phasig giat segmeted mirrors ad multi-aperture iterferometric arrays Fraçois Héault UMR 6525 CRS H. Fizeau

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

The Fizeau Experiment with Moving Water. Sokolov Gennadiy, Sokolov Vitali

The Fizeau Experiment with Moving Water. Sokolov Gennadiy, Sokolov Vitali The Fizeau Experimet with Movig Water. Sokolov Geadiy, Sokolov itali geadiy@vtmedicalstaffig.com I all papers o the Fizeau experimet with movig water, a aalysis cotais the statemet: "The beams travel relative

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

Probability of error for LDPC OC with one co-channel Interferer over i.i.d Rayleigh Fading

Probability of error for LDPC OC with one co-channel Interferer over i.i.d Rayleigh Fading IOSR Joural of Electroics ad Commuicatio Egieerig (IOSR-JECE) e-issn: 2278-2834,p- ISSN: 2278-8735.Volume 9, Issue 4, Ver. III (Jul - Aug. 24), PP 59-63 Probability of error for LDPC OC with oe co-chael

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

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

Fall 2011, EE123 Digital Signal Processing

Fall 2011, EE123 Digital Signal Processing Lecture 5 Miki Lustig, UCB September 14, 211 Miki Lustig, UCB Motivatios for Discrete Fourier Trasform Sampled represetatio i time ad frequecy umerical Fourier aalysis requires a Fourier represetatio that

More information

Olli Simula T / Chapter 1 3. Olli Simula T / Chapter 1 5

Olli Simula T / Chapter 1 3. Olli Simula T / Chapter 1 5 Sigals ad Systems Sigals ad Systems Sigals are variables that carry iformatio Systemstake sigals as iputs ad produce sigals as outputs The course deals with the passage of sigals through systems T-6.4

More information

Cork Institute of Technology Bachelor of Science (Honours) in Applied Physics and Instrumentation-Award - (NFQ Level 8)

Cork Institute of Technology Bachelor of Science (Honours) in Applied Physics and Instrumentation-Award - (NFQ Level 8) ork Istitute of Techology Bachelor of Sciece (Hoours) i Applied Physics ad Istrumetatio-Award - (NFQ Level 8) Istructios Aswer Four questios, at least TWO questios from each Sectio. Use separate aswer

More information

Signal Processing. Lecture 02: Discrete Time Signals and Systems. Ahmet Taha Koru, Ph. D. Yildiz Technical University.

Signal Processing. Lecture 02: Discrete Time Signals and Systems. Ahmet Taha Koru, Ph. D. Yildiz Technical University. Sigal Processig Lecture 02: Discrete Time Sigals ad Systems Ahmet Taha Koru, Ph. D. Yildiz Techical Uiversity 2017-2018 Fall ATK (YTU) Sigal Processig 2017-2018 Fall 1 / 51 Discrete Time Sigals Discrete

More information

2D DSP Basics: 2D Systems

2D DSP Basics: 2D Systems - Digital Image Processig ad Compressio D DSP Basics: D Systems D Systems T[ ] y = T [ ] Liearity Additivity: If T y = T [ ] The + T y = y + y Homogeeity: If The T y = T [ ] a T y = ay = at [ ] Liearity

More information

Warped, Chirp Z-Transform: Radar Signal Processing

Warped, Chirp Z-Transform: Radar Signal Processing arped, Chirp Z-Trasform: Radar Sigal Processig by Garimella Ramamurthy Report o: IIIT/TR// Cetre for Commuicatios Iteratioal Istitute of Iformatio Techology Hyderabad - 5 3, IDIA Jauary ARPED, CHIRP Z

More information

8. СОВЕТУВАЊЕ. Охрид, септември ANALYSIS OF NO LOAD APPARENT POWER AND FREQUENCY SPECTRUM OF MAGNETIZING CURRENT FOR DIFFERENT CORE TYPES

8. СОВЕТУВАЊЕ. Охрид, септември ANALYSIS OF NO LOAD APPARENT POWER AND FREQUENCY SPECTRUM OF MAGNETIZING CURRENT FOR DIFFERENT CORE TYPES 8. СОВЕТУВАЊЕ Охрид, 22 24 септември Leoardo Štrac Frajo Keleme Kočar Power Trasformers Ltd. ANALYSS OF NO LOAD APPARENT POWER AND FREQENCY SPECTRM OF MAGNETZNG CRRENT FOR DFFERENT CORE TYPES ABSTRACT

More information

Measurement uncertainty of the sound absorption

Measurement uncertainty of the sound absorption Measuremet ucertaity of the soud absorptio coefficiet Aa Izewska Buildig Research Istitute, Filtrowa Str., 00-6 Warsaw, Polad a.izewska@itb.pl 6887 The stadard ISO/IEC 705:005 o the competece of testig

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

Time-Domain Representations of LTI Systems

Time-Domain Representations of LTI Systems 2.1 Itroductio Objectives: 1. Impulse resposes of LTI systems 2. Liear costat-coefficiets differetial or differece equatios of LTI systems 3. Bloc diagram represetatios of LTI systems 4. State-variable

More information

x[0] x[1] x[2] Figure 2.1 Graphical representation of a discrete-time signal.

x[0] x[1] x[2] Figure 2.1 Graphical representation of a discrete-time signal. x[ ] x[ ] x[] x[] x[] x[] 9 8 7 6 5 4 3 3 4 5 6 7 8 9 Figure. Graphical represetatio of a discrete-time sigal. From Discrete-Time Sigal Processig, e by Oppeheim, Schafer, ad Buck 999- Pretice Hall, Ic.

More information

Signal Processing in Mechatronics

Signal Processing in Mechatronics Sigal Processig i Mechatroics Zhu K.P. AIS, UM. Lecture, Brief itroductio to Sigals ad Systems, Review of Liear Algebra ad Sigal Processig Related Mathematics . Brief Itroductio to Sigals What is sigal

More information

Session 5. (1) Principal component analysis and Karhunen-Loève transformation

Session 5. (1) Principal component analysis and Karhunen-Loève transformation 200 Autum semester Patter Iformatio Processig Topic 2 Image compressio by orthogoal trasformatio Sessio 5 () Pricipal compoet aalysis ad Karhue-Loève trasformatio Topic 2 of this course explais the image

More information

High-Resolution Imagers

High-Resolution Imagers 40 Telescopes and Imagers High-Resolution Imagers High-resolution imagers look at very small fields of view with diffraction-limited angular resolution. As the field is small, intrinsic aberrations are

More information

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [

More information

Lecture 3: Divide and Conquer: Fast Fourier Transform

Lecture 3: Divide and Conquer: Fast Fourier Transform Lecture 3: Divide ad Coquer: Fast Fourier Trasform Polyomial Operatios vs. Represetatios Divide ad Coquer Algorithm Collapsig Samples / Roots of Uity FFT, IFFT, ad Polyomial Multiplicatio Polyomial operatios

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

Discrete Orthogonal Moment Features Using Chebyshev Polynomials

Discrete Orthogonal Moment Features Using Chebyshev Polynomials Discrete Orthogoal Momet Features Usig Chebyshev Polyomials R. Mukuda, 1 S.H.Og ad P.A. Lee 3 1 Faculty of Iformatio Sciece ad Techology, Multimedia Uiversity 75450 Malacca, Malaysia. Istitute of Mathematical

More information

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

Journal of Ramanujan Mathematical Society, Vol. 24, No. 2 (2009)

Journal of Ramanujan Mathematical Society, Vol. 24, No. 2 (2009) Joural of Ramaua Mathematical Society, Vol. 4, No. (009) 199-09. IWASAWA λ-invariants AND Γ-TRANSFORMS Aupam Saikia 1 ad Rupam Barma Abstract. I this paper we study a relatio betwee the λ-ivariats of a

More information

Chapter 8. DFT : The Discrete Fourier Transform

Chapter 8. DFT : The Discrete Fourier Transform Chapter 8 DFT : The Discrete Fourier Trasform Roots of Uity Defiitio: A th root of uity is a complex umber x such that x The th roots of uity are: ω, ω,, ω - where ω e π /. Proof: (ω ) (e π / ) (e π )

More information

Robustness of spatial-coherence multiplexing under receiver misalignment

Robustness of spatial-coherence multiplexing under receiver misalignment Robustess of spatial-coherece multiplexig uder receiver misaligmet Lawrece J. Pelz ad Betty Lise Aderso It has bee show previously that the spatial coherece of a source ca be modulated ad demodulated;

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

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

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

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

Formation of A Supergain Array and Its Application in Radar

Formation of A Supergain Array and Its Application in Radar Formatio of A Supergai Array ad ts Applicatio i Radar Tra Cao Quye, Do Trug Kie ad Bach Gia Duog. Research Ceter for Electroic ad Telecommuicatios, College of Techology (Coltech, Vietam atioal Uiversity,

More information

: Transforms and Partial Differential Equations

: Transforms and Partial Differential Equations Trasforms ad Partial Differetial Equatios 018 SUBJECT NAME : Trasforms ad Partial Differetial Equatios SUBJECT CODE : MA 6351 MATERIAL NAME : Part A questios REGULATION : R013 WEBSITE : wwwharigaeshcom

More information

THE KALMAN FILTER RAUL ROJAS

THE KALMAN FILTER RAUL ROJAS THE KALMAN FILTER RAUL ROJAS Abstract. This paper provides a getle itroductio to the Kalma filter, a umerical method that ca be used for sesor fusio or for calculatio of trajectories. First, we cosider

More information

ELEC1200: A System View of Communications: from Signals to Packets Lecture 3

ELEC1200: A System View of Communications: from Signals to Packets Lecture 3 ELEC2: A System View of Commuicatios: from Sigals to Packets Lecture 3 Commuicatio chaels Discrete time Chael Modelig the chael Liear Time Ivariat Systems Step Respose Respose to sigle bit Respose to geeral

More information

Answers to test yourself questions

Answers to test yourself questions Aswers to test yourself questios Optio C C Itroductio to imagig a The focal poit of a covergig les is that poit o the pricipal axis where a ray parallel to the pricipal axis refracts through, after passage

More information

Image Segmentation on Spiral Architecture

Image Segmentation on Spiral Architecture Image Segmetatio o Spiral Architecture Qiag Wu, Xiagjia He ad Tom Hitz Departmet of Computer Systems Uiversity of Techology, Sydey PO Box 3, Broadway Street, Sydey 007, Australia {wuq,sea,hitz}@it.uts.edu.au

More information

REFLECTION AND REFRACTION

REFLECTION AND REFRACTION REFLECTION AND REFRACTION REFLECTION AND TRANSMISSION FOR NORMAL INCIDENCE ON A DIELECTRIC MEDIUM Assumptios: No-magetic media which meas that B H. No dampig, purely dielectric media. No free surface charges.

More information

Module 5 EMBEDDED WAVELET CODING. Version 2 ECE IIT, Kharagpur

Module 5 EMBEDDED WAVELET CODING. Version 2 ECE IIT, Kharagpur Module 5 EMBEDDED WAVELET CODING Versio ECE IIT, Kharagpur Lesso 4 SPIHT algorithm Versio ECE IIT, Kharagpur Istructioal Objectives At the ed of this lesso, the studets should be able to:. State the limitatios

More information

BHW #13 1/ Cooper. ENGR 323 Probabilistic Analysis Beautiful Homework # 13

BHW #13 1/ Cooper. ENGR 323 Probabilistic Analysis Beautiful Homework # 13 BHW # /5 ENGR Probabilistic Aalysis Beautiful Homework # Three differet roads feed ito a particular freeway etrace. Suppose that durig a fixed time period, the umber of cars comig from each road oto the

More information

Lecture 7: Fourier Series and Complex Power Series

Lecture 7: Fourier Series and Complex Power Series Math 1d Istructor: Padraic Bartlett Lecture 7: Fourier Series ad Complex Power Series Week 7 Caltech 013 1 Fourier Series 1.1 Defiitios ad Motivatio Defiitio 1.1. A Fourier series is a series of fuctios

More information

Mechanics Physics 151

Mechanics Physics 151 Mechaics Physics 151 Lecture 4 Cotiuous Systems ad Fields (Chapter 13) What We Did Last Time Built Lagragia formalism for cotiuous system Lagragia L = L dxdydz d L L Lagrage s equatio = dx η, η Derived

More information

LENS ANTENNAS. Oscar Quevedo-Teruel KTH Royal Institute of Technology

LENS ANTENNAS. Oscar Quevedo-Teruel KTH Royal Institute of Technology LENS ANTENNAS Oscar Quevedo-Teruel KTH Royal Istitute of Techology Outlie: Les ateas Part : Itroductio. Part : Homogeeous leses: Spherical. Part 3: Homogeeous leses: No-spherical. Part 4: Limitatios: Aberratios

More information

Probabilistic analyses in Phase 2 8.0

Probabilistic analyses in Phase 2 8.0 Probability desity Probabilistic aalyses i Phase 8.0 Beoît Valley & Damie Duff - CEMI - Ceter for Excellece i Miig Iovatio "Everythig must be made as simple as possible. But ot simpler." Albert Eistei

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

DESCRIPTION OF THE SYSTEM

DESCRIPTION OF THE SYSTEM Sychroous-Serial Iterface for absolute Ecoders SSI 1060 BE 10 / 01 DESCRIPTION OF THE SYSTEM TWK-ELEKTRONIK GmbH D-001 Düsseldorf PB 1006 Heirichstr. Tel +9/11/6067 Fax +9/11/6770 e-mail: ifo@twk.de Page

More information

A PROCEDURE TO MODIFY THE FREQUENCY AND ENVELOPE CHARACTERISTICS OF EMPIRICAL GREEN'S FUNCTION. Lin LU 1 SUMMARY

A PROCEDURE TO MODIFY THE FREQUENCY AND ENVELOPE CHARACTERISTICS OF EMPIRICAL GREEN'S FUNCTION. Lin LU 1 SUMMARY A POCEDUE TO MODIFY THE FEQUENCY AND ENVELOPE CHAACTEISTICS OF EMPIICAL GEEN'S FUNCTION Li LU SUMMAY Semi-empirical method, which divides the fault plae of large earthquake ito mets ad uses small groud

More information

Accuracy of TEXTOR He-beam diagnostics

Accuracy of TEXTOR He-beam diagnostics Accuracy of TEXTOR He-beam diagostics O. Schmitz, I.L.Beigma *, L.A. Vaishtei *, A. Pospieszczyk, B. Schweer, M. Krychoviak, U. Samm ad the TEXTOR team Forschugszetrum Jülich,, Jülich, Germay *Lebedev

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

PHYS 450 Spring semester Lecture 06: Dispersion and the Prism Spectrometer. Ron Reifenberger Birck Nanotechnology Center Purdue University

PHYS 450 Spring semester Lecture 06: Dispersion and the Prism Spectrometer. Ron Reifenberger Birck Nanotechnology Center Purdue University /0/07 PHYS 450 Sprig semester 07 Lecture 06: Dispersio ad the Prism Spectrometer Ro Reifeberger Birck Naotechology Ceter Purdue Uiversity Lecture 06 Prisms Dispersio of Light As early as the 3th cetury,

More information

PHYS-3301 Lecture 9. CHAPTER 5 Wave Properties of Matter and Quantum Mechanics I. 5.3: Electron Scattering. Bohr s Quantization Condition

PHYS-3301 Lecture 9. CHAPTER 5 Wave Properties of Matter and Quantum Mechanics I. 5.3: Electron Scattering. Bohr s Quantization Condition CHAPTER 5 Wave Properties of Matter ad Quatum Mecaics I PHYS-3301 Lecture 9 Sep. 5, 018 5.1 X-Ray Scatterig 5. De Broglie Waves 5.3 Electro Scatterig 5.4 Wave Motio 5.5 Waves or Particles? 5.6 Ucertaity

More information

Phase-shifting coronagraph

Phase-shifting coronagraph Phase-shifting coronagraph François Hénault, Alexis Carlotti, Christophe Vérinaud Institut de Planétologie et d Astrophysique de Grenoble Université Grenoble-Alpes Centre National de la Recherche Scientifique

More information

Finally, we show how to determine the moments of an impulse response based on the example of the dispersion model.

Finally, we show how to determine the moments of an impulse response based on the example of the dispersion model. 5.3 Determiatio of Momets Fially, we show how to determie the momets of a impulse respose based o the example of the dispersio model. For the dispersio model we have that E θ (θ ) curve is give by eq (4).

More information

Introduction to Computational Molecular Biology. Gibbs Sampling

Introduction to Computational Molecular Biology. Gibbs Sampling 18.417 Itroductio to Computatioal Molecular Biology Lecture 19: November 16, 2004 Scribe: Tushara C. Karuarata Lecturer: Ross Lippert Editor: Tushara C. Karuarata Gibbs Samplig Itroductio Let s first recall

More information

Design of multiplexed phase diffractive optical elements for focal depth extension

Design of multiplexed phase diffractive optical elements for focal depth extension Desig of multiplexed phase diffractive optical elemets for focal depth extesio Hua Liu, Zhewu Lu,,* Qiag Su ad Hu Zhag,,2 Opto_electroics techology ceter, Chagchu Istitute of Optics ad Fie Mechaics ad

More information

Optimum LMSE Discrete Transform

Optimum LMSE Discrete Transform Image Trasformatio Two-dimesioal image trasforms are extremely importat areas of study i image processig. The image output i the trasformed space may be aalyzed, iterpreted, ad further processed for implemetig

More information

Multiple Groenewold Products: from path integrals to semiclassical correlations

Multiple Groenewold Products: from path integrals to semiclassical correlations Multiple Groeewold Products: from path itegrals to semiclassical correlatios 1. Traslatio ad reflectio bases for operators Traslatio operators, correspod to classical traslatios, withi the classical phase

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

Shocks waves and discontinuities.

Shocks waves and discontinuities. Shocks waes ad discotiuities Laurece Rezeau http://www.lpp.fr/?laurece-rezeau OUTLINE Obseratios of discotiuities Jump coditios at the boudary Differet kids of discotiuities What about the boudaries aroud

More information

Discrete-Time Signals and Systems. Signals and Systems. Digital Signals. Discrete-Time Signals. Operations on Sequences: Basic Operations

Discrete-Time Signals and Systems. Signals and Systems. Digital Signals. Discrete-Time Signals. Operations on Sequences: Basic Operations -6.3 Digital Sigal Processig ad Filterig..8 Discrete-ime Sigals ad Systems ime-domai Represetatios of Discrete-ime Sigals ad Systems ime-domai represetatio of a discrete-time sigal as a sequece of umbers

More information

Part 1 - Basic Interferometers for Optical Testing

Part 1 - Basic Interferometers for Optical Testing Part 1 - Basic Interferometers for Optical Testing Two Beam Interference Fizeau and Twyman-Green interferometers Basic techniques for testing flat and spherical surfaces Mach-Zehnder Zehnder,, Scatterplate

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

MAXIMALLY FLAT FIR FILTERS

MAXIMALLY FLAT FIR FILTERS MAXIMALLY FLAT FIR FILTERS This sectio describes a family of maximally flat symmetric FIR filters first itroduced by Herrma [2]. The desig of these filters is particularly simple due to the availability

More information

Notes The Incremental Motion Model:

Notes The Incremental Motion Model: The Icremetal Motio Model: The Jacobia Matrix I the forward kiematics model, we saw that it was possible to relate joit agles θ, to the cofiguratio of the robot ed effector T I this sectio, we will see

More information

Last time: Moments of the Poisson distribution from its generating function. Example: Using telescope to measure intensity of an object

Last time: Moments of the Poisson distribution from its generating function. Example: Using telescope to measure intensity of an object 6.3 Stochastic Estimatio ad Cotrol, Fall 004 Lecture 7 Last time: Momets of the Poisso distributio from its geeratig fuctio. Gs () e dg µ e ds dg µ ( s) µ ( s) µ ( s) µ e ds dg X µ ds X s dg dg + ds ds

More information

Diversity Combining Techniques

Diversity Combining Techniques Diversity Combiig Techiques Whe the required sigal is a combiatio of several waves (i.e, multipath), the total sigal amplitude may experiece deep fades (i.e, Rayleigh fadig), over time or space. The major

More information

Hypertelescopes without delay lines.

Hypertelescopes without delay lines. Hypertelescopes without delay lines. V. Borkowski 1, O. Lardière 1, J. Dejonghe 1 and H. Le Coroller 2 1 LISE-Collège de France,Observatory of Haute Provence, France 2 Keck Observatory, Kamuela, Hawaii

More information

Support vector machine revisited

Support vector machine revisited 6.867 Machie learig, lecture 8 (Jaakkola) 1 Lecture topics: Support vector machie ad kerels Kerel optimizatio, selectio Support vector machie revisited Our task here is to first tur the support vector

More information

6.003 Homework #12 Solutions

6.003 Homework #12 Solutions 6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F for

More information

Fast Monte Carlo Method in Stochastic Modelling of Charged Particle Multiplication

Fast Monte Carlo Method in Stochastic Modelling of Charged Particle Multiplication Fast Mote Carlo Method i Stochastic Modellig of Charged Particle Multiplicatio Alla V. Shymaska *, Vitali A. Babakov School of Computer ad Mathematical Scieces, Aucklad Uiversity of Techology, Private

More information

Large Deviations Performance Analysis for Biometrics Recognition

Large Deviations Performance Analysis for Biometrics Recognition J.A. O Sulliva, 2002 Allerto Coferece Large Deviatios erformace Aalysis for Biometrics Recogitio Joseph A. O Sulliva ad Natalia Schmid Electroic Systems ad Sigals Research Laboratory Departmet of Electrical

More information

2 1. The r.s., of size n2, from population 2 will be. 2 and 2. 2) The two populations are independent. This implies that all of the n1 n2

2 1. The r.s., of size n2, from population 2 will be. 2 and 2. 2) The two populations are independent. This implies that all of the n1 n2 Chapter 8 Comparig Two Treatmets Iferece about Two Populatio Meas We wat to compare the meas of two populatios to see whether they differ. There are two situatios to cosider, as show i the followig examples:

More information

A novel laser guide star: Projected Pupil Plane Pattern

A novel laser guide star: Projected Pupil Plane Pattern A novel laser guide star: Projected Pupil Plane Pattern Huizhe Yang a, Nazim Barmal a, Richard Myers a, David F. Buscher b, Aglae Kellerer c, Tim Morris a, and Alastair Basden a a Department of Physics,

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

M2.The Z-Transform and its Properties

M2.The Z-Transform and its Properties M2.The Z-Trasform ad its Properties Readig Material: Page 94-126 of chapter 3 3/22/2011 I. Discrete-Time Sigals ad Systems 1 What did we talk about i MM1? MM1 - Discrete-Time Sigal ad System 3/22/2011

More information

MCT242: Electronic Instrumentation Lecture 2: Instrumentation Definitions

MCT242: Electronic Instrumentation Lecture 2: Instrumentation Definitions Faculty of Egieerig MCT242: Electroic Istrumetatio Lecture 2: Istrumetatio Defiitios Overview Measuremet Error Accuracy Precisio ad Mea Resolutio Mea Variace ad Stadard deviatio Fiesse Sesitivity Rage

More information

1 Duality revisited. AM 221: Advanced Optimization Spring 2016

1 Duality revisited. AM 221: Advanced Optimization Spring 2016 AM 22: Advaced Optimizatio Sprig 206 Prof. Yaro Siger Sectio 7 Wedesday, Mar. 9th Duality revisited I this sectio, we will give a slightly differet perspective o duality. optimizatio program: f(x) x R

More information

6.003 Homework #12 Solutions

6.003 Homework #12 Solutions 6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] (below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F

More information

Structuring Element Representation of an Image and Its Applications

Structuring Element Representation of an Image and Its Applications Iteratioal Joural of Cotrol Structurig Automatio Elemet ad Represetatio Systems vol. of a o. Image 4 pp. ad 50955 Its Applicatios December 004 509 Structurig Elemet Represetatio of a Image ad Its Applicatios

More information

Quantum Information & Quantum Computation

Quantum Information & Quantum Computation CS9A, Sprig 5: Quatum Iformatio & Quatum Computatio Wim va Dam Egieerig, Room 59 vadam@cs http://www.cs.ucsb.edu/~vadam/teachig/cs9/ Admiistrivia Do the exercises. Aswers will be posted at the ed of the

More information

Bivariate Sample Statistics Geog 210C Introduction to Spatial Data Analysis. Chris Funk. Lecture 7

Bivariate Sample Statistics Geog 210C Introduction to Spatial Data Analysis. Chris Funk. Lecture 7 Bivariate Sample Statistics Geog 210C Itroductio to Spatial Data Aalysis Chris Fuk Lecture 7 Overview Real statistical applicatio: Remote moitorig of east Africa log rais Lead up to Lab 5-6 Review of bivariate/multivariate

More information

1 Review of Probability & Statistics

1 Review of Probability & Statistics 1 Review of Probability & Statistics a. I a group of 000 people, it has bee reported that there are: 61 smokers 670 over 5 960 people who imbibe (drik alcohol) 86 smokers who imbibe 90 imbibers over 5

More information

SENSOR ARRAY ABLE TO DETECT AND RECOGNISE CHEMICAL WARFARE AGENTS

SENSOR ARRAY ABLE TO DETECT AND RECOGNISE CHEMICAL WARFARE AGENTS Abstract SENSOR ARRAY ABLE TO DETECT AND RECOGNISE CHEMICAL WARFARE AGENTS I. Bucur, S. Serba, A. Surpateau, N. Cupcea 1 C. Viespe, C. Grigoriu 2 C. Toader, N. Grigoriu 3 I this paper we studied a device

More information

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement Practical Spectral Aaysis (cotiue) (from Boaz Porat s book) Frequecy Measuremet Oe of the most importat applicatios of the DFT is the measuremet of frequecies of periodic sigals (eg., siusoidal sigals),

More information

Matsubara-Green s Functions

Matsubara-Green s Functions Matsubara-Gree s Fuctios Time Orderig : Cosider the followig operator If H = H the we ca trivially factorise this as, E(s = e s(h+ E(s = e sh e s I geeral this is ot true. However for practical applicatio

More information

Complex Algorithms for Lattice Adaptive IIR Notch Filter

Complex Algorithms for Lattice Adaptive IIR Notch Filter 4th Iteratioal Coferece o Sigal Processig Systems (ICSPS ) IPCSIT vol. 58 () () IACSIT Press, Sigapore DOI:.7763/IPCSIT..V58. Complex Algorithms for Lattice Adaptive IIR Notch Filter Hog Liag +, Nig Jia

More information

Complex Numbers. Brief Notes. z = a + bi

Complex Numbers. Brief Notes. z = a + bi Defiitios Complex Numbers Brief Notes A complex umber z is a expressio of the form: z = a + bi where a ad b are real umbers ad i is thought of as 1. We call a the real part of z, writte Re(z), ad b the

More information