Suchergebnis: Katalogdaten im Herbstsemester 2021

Quantum Engineering Master Information
Kernfächer
A minimum of 24 credits must be obtained from core courses during the MSc QE, course selection is subject to the tutor's agreement.
Quantum Technology Lab
This core course is a prerequisite for participation in the QuanTech Labs of the second and third semester.
NummerTitelTypECTSUmfangDozierende
227-1831-10LCase Studies: Applications of Quantum Technology Information Belegung eingeschränkt - Details anzeigen
Only for Quantum Engineering MSc
W+3 KP6GG. Raino
KurzbeschreibungIn this course students will be exposed to different topics of quantum engineering and develop ideas for possible projects. Based on presentations by ETH labs participating in the MSc QE program and with the assistance of a mentor students will work in groups to develop concrete plans for a quantum experiment.
LernzielAcquire a broad overview of quantum engineering activities at ETH and develop own ideas about future quantum engineering projects.
Engineering Core Courses
These core courses target students with a physics background and all those who need additional engineering foundations.
NummerTitelTypECTSUmfangDozierende
227-0103-00LRegelsysteme Information W6 KP2V + 2UF. Dörfler
KurzbeschreibungStudy of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems.
LernzielStudy of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems.
InhaltProcess automation, concept of control. Modelling of dynamical systems - examples, state space description, linearisation, analytical/numerical solution. Laplace transform, system response for first and second order systems - effect of additional poles and zeros. Closed-loop control - idea of feedback. PID control, Ziegler - Nichols tuning. Stability, Routh-Hurwitz criterion, root locus, frequency response, Bode diagram, Bode gain/phase relationship, controller design via "loop shaping", Nyquist criterion. Feedforward compensation, cascade control. Multivariable systems (transfer matrix, state space representation), multi-loop control, problem of coupling, Relative Gain Array, decoupling, sensitivity to model uncertainty. State space representation (modal description, controllability, control canonical form, observer canonical form), state feedback, pole placement - choice of poles. Observer, observability, duality, separation principle. LQ Regulator, optimal state estimation.
LiteraturK. J. Aström & R. Murray. Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press, 2010.
R. C. Dorf and R. H. Bishop. Modern Control Systems. Prentice Hall, New Jersey, 2007.
G. F. Franklin, J. D. Powell, and A. Emami-Naeini. Feedback Control of Dynamic Systems. Addison-Wesley, 2010.
J. Lunze. Regelungstechnik 1. Springer, Berlin, 2014.
J. Lunze. Regelungstechnik 2. Springer, Berlin, 2014.
Voraussetzungen / BesonderesPrerequisites: Signal and Systems Theory II.

MATLAB is used for system analysis and simulation.
227-0116-00LVLSI 1: HDL based design for FPGAs Information W6 KP5GF. K. Gürkaynak, L. Benini
KurzbeschreibungThis first course in a series that extends over three consecutive terms is concerned with tailoring algorithms and with devising high performance hardware architectures for their implementation as ASIC or with FPGAs. The focus is on front end design using HDLs and automatic synthesis for producing industrial-quality circuits.
LernzielUnderstand Very-Large-Scale Integrated Circuits (VLSI chips), Application-Specific Integrated Circuits (ASIC), and Field-Programmable Gate-Arrays (FPGA). Know their organization and be able to identify suitable application areas. Become fluent in front-end design from architectural conception to gate-level netlists. How to model digital circuits with SystemVerilog. How to ensure they behave as expected with the aid of simulation, testbenches, and assertions. How to take advantage of automatic synthesis tools to produce industrial-quality VLSI and FPGA circuits. Gain practical experience with the hardware description language SystemVerilog and with industrial Electronic Design Automation (EDA) tools.
InhaltThis course is concerned with system-level issues of VLSI design and FPGA implementations. Topics include:
- Overview on design methodologies and fabrication depths.
- Levels of abstraction for circuit modeling.
- Organization and configuration of commercial field-programmable components.
- FPGA design flows.
- Dedicated and general purpose architectures compared.
- How to obtain an architecture for a given processing algorithm.
- Meeting throughput, area, and power goals by way of architectural transformations.
- Hardware Description Languages (HDL) and the underlying concepts.
- SystemVerilog
- Register Transfer Level (RTL) synthesis and its limitations.
- Building blocks of digital VLSI circuits.
- Functional verification techniques and their limitations.
- Modular and largely reusable testbenches.
- Assertion-based verification.
- Synchronous versus asynchronous circuits.
- The case for synchronous circuits.
- Periodic events and the Anceau diagram.
- Case studies, ASICs compared to microprocessors, DSPs, and FPGAs.

During the exercises, students learn how to model FPGAs with SystemVerilog. They write testbenches for simulation purposes and synthesize gate-level netlists for FPGAs. Commercial EDA software by leading vendors is being used throughout.
SkriptTextbook and all further documents in English.
LiteraturH. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303.
Voraussetzungen / BesonderesPrerequisites:
Basics of digital circuits.

Examination:
In written form following the course semester (spring term). Problems are given in English, answers will be accepted in either English oder German.

Further details:
https://iis-students.ee.ethz.ch/lectures/vlsi-i/
227-0166-00LAnalog Integrated Circuits Information W6 KP2V + 2UT. Jang
KurzbeschreibungThis course provides a foundation in analog integrated circuit design based on bipolar and CMOS technologies.
LernzielIntegrated circuits are responsible for much of the progress in electronics in the last 50 years, particularly the revolutions in the Information and Communications Technologies we witnessed in recent years. Analog integrated circuits play a crucial part in the highly integrated systems that power the popular electronic devices we use daily. Understanding their design is beneficial to both future designers and users of such systems.
The basic elements, design issues and techniques for analog integrated circuits will be taught in this course.
InhaltReview of bipolar and MOS devices and their small-signal equivalent circuit models; Building blocks in analog circuits such as current sources, active load, current mirrors, supply independent biasing etc; Amplifiers: differential amplifiers, cascode amplifier, high gain structures, output stages, gain bandwidth product of op-amps; stability; comparators; second-order effects in analog circuits such as mismatch, noise and offset; data converters; frequency synthesizers; switched capacitors.
The exercise sessions aim to reinforce the lecture material by well guided step-by-step design tasks. The circuit simulator SPECTRE is used to facilitate the tasks. There is also an experimental session on op-amp measurements.
SkriptHandouts of presented slides. No script but an accompanying textbook is recommended.
LiteraturBehzad Razavi, Design of Analog CMOS Integrated Circuits (Irwin Electronics & Computer Engineering) 1st or 2nd edition, McGraw-Hill Education
227-0301-00LOptical Communication FundamentalsW6 KP2V + 1U + 1PJ. Leuthold
KurzbeschreibungThe path of an analog signal in the transmitter to the digital world in a communication link and back to the analog world at the receiver is discussed. The lecture covers the fundamentals of all important optical and optoelectronic components in a fiber communication system. This includes the transmitter, the fiber channel and the receiver with the electronic digital signal processing elements.
LernzielAn in-depth understanding on how information is transmitted from source to destination. Also the mathematical framework to describe the important elements will be passed on. Students attending the lecture will further get engaged in critical discussion on societal, economical and environmental aspects related to the on-going exponential growth in the field of communications.
Inhalt* Chapter 1: Introduction: Analog/Digital conversion, The communication channel, Shannon channel capacity, Capacity requirements.

* Chapter 2: The Transmitter: Components of a transmitter, Lasers, The spectrum of a signal, Optical modulators, Modulation formats.

* Chapter 3: The Optical Fiber Channel: Geometrical optics, The wave equations in a fiber, Fiber modes, Fiber propagation, Fiber losses, Nonlinear effects in a fiber.

* Chapter 4: The Receiver: Photodiodes, Receiver noise, Detector schemes (direct detection, coherent detection), Bit-error ratios and error estimations.

* Chapter 5: Digital Signal Processing Techniques: Digital signal processing in a coherent receiver, Error detection teqchniques, Error correction coding.

* Chapter 6: Pulse Shaping and Multiplexing Techniques: WDM/FDM, TDM, OFDM, Nyquist Multiplexing, OCDMA.

* Chapter 7: Optical Amplifiers : Semiconductor Optical Amplifiers, Erbium Doped Fiber Amplifiers, Raman Amplifiers.
SkriptLecture notes are handed out.
LiteraturGovind P. Agrawal; "Fiber-Optic Communication Systems"; Wiley, 2010
Voraussetzungen / BesonderesFundamentals of Electromagnetic Fields & Bachelor Lectures on Physics.
227-0417-00LInformation Theory IW6 KP4GA. Lapidoth
KurzbeschreibungThis course covers the basic concepts of information theory and of communication theory. Topics covered include the entropy rate of a source, mutual information, typical sequences, the asymptotic equi-partition property, Huffman coding, channel capacity, the channel coding theorem, the source-channel separation theorem, and feedback capacity.
LernzielThe fundamentals of Information Theory including Shannon's source coding and channel coding theorems
InhaltThe entropy rate of a source, Typical sequences, the asymptotic equi-partition property, the source coding theorem, Huffman coding, Arithmetic coding, channel capacity, the channel coding theorem, the source-channel separation theorem, feedback capacity
LiteraturT.M. Cover and J. Thomas, Elements of Information Theory (second edition)
Physics Core Courses
These core courses target students with an engineering background and all those who need additional physics foundations.
NummerTitelTypECTSUmfangDozierende
402-0205-00LQuantenmechanik IW10 KP3V + 2UM. Gaberdiel
KurzbeschreibungAllgemeine Struktur der Quantentheorie: Hilberträume, Zustände und Observable, Bewegungsgleichung, Heisenberg'sche Unschärferelation, Symmetrien, Drehimpulsaddition, EPR Paradox, Schrödinger- und Heisenberg-Bild.
Anwendungen: einfache Potentiale in der Wellenmechanik, Streuung und Resonanz, harmonischer Oszillator, Wasserstoffatom und Störungstheorie.
LernzielEinführung in die Einteilchen Quantenmechanik. Beherrschung grundlegender Ideen (Quantisierung, Operatorformalismus, Symmetrien, Drehimpuls, Störungstheorie) und generischer Beispiele und Anwendungen (gebundene Zustände, Tunneleffekt, Wasserstoffatom, harmonischer Oszillator). Fähigkeit zur Lösung einfacher Probleme.
InhaltDie Anfänge der Quantentheorie bei Planck, Einstein und Bohr; Wellennmechanik; Beispiele einfacher Systeme; Der Formalismus der Quantenmechanik (Zustände und Observablen, Hilberträume und Operatoren, der Messprozess); Heisenberg'sche Unschärferelation; Der harmonische Oszillator; Symmetrien (insbesondere Rotationen); Das Wasserstoffatom; Angular momentum addition; Quantenmechanik und klassische Physik (EPR Paradox und Bell'sche Ungleichung); Störungstheorie.
SkriptAuf Moodle, in deutscher Sprache
LiteraturG. Baym, Lectures on Quantum Mechanics
E. Merzbacher, Quantum Mechanics
L.I. Schiff, Quantum Mechanics
R. Feynman and A.R. Hibbs, Quantum Mechanics and Path Integrals
J.J. Sakurai: Modern Quantum Mechanics
A. Messiah: Quantum Mechanics I
S. Weinberg: Lectures on Quantum Mechanics
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengefördert
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggefördert
Medien und digitale Technologiengefördert
Problemlösunggeprüft
Projektmanagementgefördert
Soziale KompetenzenKommunikationgefördert
Kooperation und Teamarbeitgefördert
Kundenorientierunggefördert
Menschenführung und Verantwortunggefördert
Selbstdarstellung und soziale Einflussnahmegefördert
Sensibilität für Vielfalt gefördert
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgefördert
Kreatives Denkengeprüft
Kritisches Denkengefördert
Integrität und Arbeitsethikgefördert
Selbstbewusstsein und Selbstreflexion gefördert
Selbststeuerung und Selbstmanagement gefördert
402-0209-00LQuantum Physics for Non-PhysicistsW6 KP3V + 2UL. Pacheco Cañamero B. del Rio
KurzbeschreibungThis is an introduction to the physics of quantum mechanics, aimed primarily at students with little to no background in physics. We start from the basic postulates and follow an information-theoretical approach to study the behaviour of quantum systems, from a single spin to entangled particles in space and the hydrogen atom.
LernzielThis course teaches the basics of quantum physics, and complements
courses in quantum computation and information theory. Students are equipped with tools to tackle complex quantum mechanical problems and foundational questions. The course covers approximately the same content as QM1, but from an information-driven perspective.
Inhalt1. Quantum formalism, from qubits to particles in space

2. Time and dynamics for quantum systems

3. Problems in 1D

4. Uncertainty and open systems

5. Spin

6. Problems in 3D

7. Non-locality and foundational aspects of quantum theory
SkriptLecture notes will be distributed through the semester.
LiteraturQuantum Processes Systems, and Information, by Benjamin Schumacher and
Michael Westmoreland, available at

Link
Voraussetzungen / BesonderesThis course is aimed at non-physicists, and in particular at students
with a background in computer science, mathematics or engineering. Basic linear algebra and calculus knowledge is required (equivalent to
first-year courses). Physics knowledge is not required. Physicists and
students from a different background than outlined above are welcome at their own risk.

Note that while we follow an information-theoretical approach, this is
not a course on quantum information theory or quantum computing. It
therefore complements those courses offered at ETH in both semesters.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggefördert
Medien und digitale Technologiengefördert
Problemlösunggeprüft
Projektmanagementgefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgefördert
Kundenorientierunggefördert
Menschenführung und Verantwortunggefördert
Selbstdarstellung und soziale Einflussnahmegefördert
Sensibilität für Vielfalt gefördert
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgefördert
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion gefördert
Selbststeuerung und Selbstmanagement geprüft
402-0255-00LEinführung in die FestkörperphysikW10 KP3V + 2UC. Degen
KurzbeschreibungDie Vorlesung vermittelt die Grundlagen zur Physik kondensierter Materie und berührt einzelne Gebiete, welche später in Spezialvorlesungen eingehender behandelt werden. Im Stoff enthalten sind: Strukturen von Festkörpern, Interatomare Bindungen, elementare Anregungen, elektronische Eigenschaften von Isolatoren, Metalle, Halbleiter, Transportphänomene, Magnetismus, Supraleitung.
LernzielEinführung in die Physik der kondensierten Materie.
InhaltDie Vorlesung vermittelt die Grundlagen zur Physik kondensierter Materie und berührt einzelne Gebiete, welche später in Spezialvorlesungen eingehender behandelt werden. Im Stoff enthalten sind: Mögliche Formen von Festkörpern und deren Strukturen (Strukturklassifizierung und -bestimmung); Interatomare Bindungen; elementare Anregungen, elektronische Eigenschaften von Isolatoren, Metalle (klassische Theorie, quantenmechanische Beschreibung der Elektronenzustände, thermische Eigenschaften und Transportphänomene); Halbleiter (Bandstruktur, n/p-Typ Dotierungen, p/n-Kontakte); Magnetismus, Supraleitung
SkriptDas Skript wird auf Moodle verfügbar sein.
LiteraturIbach & Lüth, Festkörperphysik
C. Kittel, Festkörperphysik
Ashcroft & Mermin, Festkörperphysik
W. Känzig, Kondensierte Materie
Voraussetzungen / BesonderesVoraussetzungen: Physik I, II, III wünschenswert
402-0442-00LQuantum OpticsW10 KP3V + 2UT. Esslinger
KurzbeschreibungThis course gives an introduction to the fundamental concepts of Quantum Optics and will highlight state-of-the-art developments in this rapidly evolving discipline. The topics covered include the quantum nature of light, semi-classical and quantum mechanical description of light-matter interaction, laser manipulation of atoms and ions, optomechanics and quantum computation.
LernzielThe course aims to provide the knowledge necessary for pursuing research in the field of Quantum Optics. Fundamental concepts and techniques of Quantum Optics will be linked to modern experimental research. During the course the students should acquire the capability to understand currently published research in the field.
InhaltThis course gives an introduction to the fundamental concepts of Quantum Optics and will highlight state-of-the-art developments in this rapidly evolving discipline. The topics that are covered include:

- coherence properties of light
- quantum nature of light: statistics and non-classical states of light
- light matter interaction: density matrix formalism and Bloch equations
- quantum description of light matter interaction: the Jaynes-Cummings model, photon blockade
- laser manipulation of atoms and ions: laser cooling and trapping, atom interferometry,
- further topics: Rydberg atoms, optomechanics, quantum computing, complex quantum systems.
SkriptSelected book chapters will be distributed.
LiteraturText-books:

G. Grynberg, A. Aspect and C. Fabre, Introduction to Quantum Optics
R. Loudon, The Quantum Theory of Light
Atomic Physics, Christopher J. Foot
Advances in Atomic Physics, Claude Cohen-Tannoudji and David Guéry-Odelin
C. Cohen-Tannoudji et al., Atom-Photon-Interactions
M. Scully and M.S. Zubairy, Quantum Optics
Y. Yamamoto and A. Imamoglu, Mesoscopic Quantum Optics
402-0861-00LStatistical PhysicsW10 KP4V + 2UM. Sigrist
KurzbeschreibungThis lecture covers the concepts of classical and quantum statistical physics. Several techniques such as second quantization formalism for fermions, bosons, photons and phonons as well as mean field theory and self-consistent field approximation. These are used to discuss phase transitions, critical phenomena and superfluidity.
LernzielThis lecture gives an introduction in the basic concepts and applications of statistical physics for the general use in physics and, in particular, as a preparation for the theoretical solid state physics education.
InhaltKinetic approach to statistical physics: H-theorem, detailed balance and equilibirium conditions.
Classical statistical physics: microcanonical ensembles, canonical ensembles and grandcanonical ensembles, applications to simple systems.
Quantum statistical physics: density matrix, ensembles, Fermi gas, Bose gas (Bose-Einstein condensation), photons and phonons.
Identical quantum particles: many body wave functions, second quantization formalism, equation of motion, correlation functions, selected applications, e.g. Bose-Einstein condensate and coherent state, phonons in elastic media and melting.
One-dimensional interacting systems.
Phase transitions: mean field approach to Ising model, Gaussian transformation, Ginzburg-Landau theory (Ginzburg criterion), self-consistent field approach, critical phenomena, Peierls' arguments on long-range order.
Superfluidity: Quantum liquid Helium: Bogolyubov theory and collective excitations, Gross-Pitaevskii equations, Berezinskii-Kosterlitz-Thouless transition.
SkriptLecture notes available in English.
LiteraturNo specific book is used for the course. Relevant literature will be given in the course.
402-0461-00LQuantum Information TheoryW8 KP3V + 1UP. Kammerlander
KurzbeschreibungThe goal of this course is to introduce the concepts and methods of quantum information theory. It starts with an introduction to the mathematical theory of quantum systems and then discusses the basic information-theoretic aspects of quantum mechanics. Further topics include applications such as quantum cryptography and quantum coding theory.
LernzielBy the end of the course students are able to explain the basic mathematical formalism (e.g. states, channels) and the tools (e.g. entropy, distinguishability) of quantum information theory. They are able to adapt and apply these concepts and methods to analytically solve quantum information-processing problems primarily related to communication and cryptography.
InhaltMathematical formulation of quantum theory: entanglement, density operators, quantum channels and their representations. Basic tools of quantum information theory: distinguishability of states and channels, formulation as semidefinite programs, entropy and its properties.
Applications of the concepts and tools: communication of classical or quantum information over noisy channels, quantitative uncertainty relations, randomness generation, entanglement distillation, security of quantum cryptography.
SkriptDistributed via moodle.
LiteraturNielsen and Chuang, Quantum Information and Computation
Preskill, Lecture Notes on Quantum Computation
Wilde, Quantum Information Theory
Watrous, The Theory of Quantum Information
Wahlfächer
This is a selection of courses particularly suitable for the MSc QE. In agreement with the tutor, students may choose other courses from the ETH course catalogue.
NummerTitelTypECTSUmfangDozierende
227-0101-00LDiscrete-Time and Statistical Signal Processing Information W6 KP4GH.‑A. Loeliger
KurzbeschreibungThe course introduces some fundamental topics of digital signal processing with a bias towards applications in communications: discrete-time linear filters, inverse filters and equalization, DFT, discrete-time stochastic processes, elements of detection theory and estimation theory, LMMSE estimation and LMMSE filtering, LMS algorithm, Viterbi algorithm.
LernzielThe course introduces some fundamental topics of digital signal processing with a bias towards applications in communications. The two main themes are linearity and probability. In the first part of the course, we deepen our understanding of discrete-time linear filters. In the second part of the course, we review the basics of probability theory and discrete-time stochastic processes. We then discuss some basic concepts of detection theory and estimation theory, as well as some practical methods including LMMSE estimation and LMMSE filtering, the LMS algorithm, and the Viterbi algorithm. A recurrent theme throughout the course is the stable and robust "inversion" of a linear filter.
Inhalt1. Discrete-time linear systems and filters:
state-space realizations, z-transform and spectrum,
decimation and interpolation, digital filter design,
stable realizations and robust inversion.

2. The discrete Fourier transform and its use for digital filtering.

3. The statistical perspective:
probability, random variables, discrete-time stochastic processes;
detection and estimation: MAP, ML, Bayesian MMSE, LMMSE;
Wiener filter, LMS adaptive filter, Viterbi algorithm.
SkriptLecture Notes
227-0145-00LSolid State Electronics and Optics Information W6 KP4GN. Yazdani, V. Wood
Kurzbeschreibung"Solid State Electronics" is an introductory condensed matter physics course covering crystal structure, electron models, classification of metals, semiconductors, and insulators, band structure engineering, thermal and electronic transport in solids, magnetoresistance, and optical properties of solids.
LernzielUnderstand the fundamental physics behind the mechanical, thermal, electric, magnetic, and optical properties of materials.
Voraussetzungen / BesonderesRecommended background:
Undergraduate physics, mathematics, semiconductor devices
227-0146-00LAnalog-to-Digital Converters Information
Findet dieses Semester nicht statt.
W6 KP2V + 2U
KurzbeschreibungThis course provides a thorough treatment of integrated data conversion systems from system level specifications and trade-offs, over architecture choice down to circuit implementation.
LernzielData conversion systems are substantial sub-parts of many electronic systems, e.g. the audio conversion system of a home-cinema systems or the base-band front-end of a wireless modem. Data conversion systems usually determine the performance of the overall system in terms of dynamic range and linearity. The student will learn to understand the basic principles behind data conversion and be introduced to the different methods and circuit architectures to implement such a conversion. The conversion methods such as successive approximation or algorithmic conversion are explained with their principle of operation accompanied with the appropriate mathematical calculations, including the effects of non-idealties in some cases. After successful completion of the course the student should understand the concept of an ideal ADC, know all major converter architectures, their principle of operation and what governs their performance.
Inhalt- Introduction: information representation and communication; abstraction, categorization and symbolic representation; basic conversion algorithms; data converter application; tradeoffs among key parameters; ADC taxonomy.
- Dual-slope & successive approximation register (SAR) converters: dual slope principle & converter; SAR ADC operating principle; SAR implementation with a capacitive array; range extension with segmented array.
- Algorithmic & pipelined A/D converters: algorithmic conversion principle; sample & hold stage; pipe-lined converter; multiplying DAC; flash sub-ADC and n-bit MDAC; redundancy for correction of non-idealties, error correction.
- Performance metrics and non-linearity: ideal ADC; offset, gain error, differential and integral non-linearities; capacitor mismatch; impact of capacitor mismatch on SAR ADC's performance.
- Flash, folding an interpolating analog-to-digital converters: flash ADC principle, thermometer to binary coding, sparkle correction; limitations of flash converters; the folding principle, residue extraction; folding amplifiers; cascaded folding; interpolation for folding converters; cascaded folding and interpolation.
- Noise in analog-to-digital converters: types of noise; noise calculation in electronic circuit, kT/C-noise, sampled noise; noise analysis in switched-capacitor circuits; aperture time uncertainty and sampling jitter.
- Delta-sigma A/D-converters: linearity and resolution; from delta-modulation to delta-sigma modulation; first-oder delta-sigma modulation, circuit level implementation; clock-jitter & SNR in delta-sigma modulators; second-order delta-sigma modulation, higher-order modulation, design procedure for a single-loop modulator.
- Digital-to-analog converters: introduction; current scaling D/A converter, current steering DAC, calibration for improved performance.
SkriptSlides are available online under https://iis-students.ee.ethz.ch/lectures/analog-to-digital-converters/
Literatur- B. Razavi, Principles of Data Conversion System Design, IEEE Press, 1994
- M. Gustavsson et. al., CMOS Data Converters for Communications, Springer, 2010
- R.J. van de Plassche, CMOS Integrated Analog-to-Digital and Digital-to-Analog Converters, Springer, 2010
Voraussetzungen / BesonderesIt is highly recommended to attend the course "Analog Integrated Circuits" of Prof. T. Jang as a preparation for this course.
227-0157-00LSemiconductor Devices: Physical Bases and Simulation Information W4 KP3GA. Schenk, C. I. Roman
KurzbeschreibungThe course addresses the physical principles of modern semiconductor devices and the foundations of their modeling and numerical simulation. Necessary basic knowledge on quantum-mechanics, semiconductor physics and device physics is provided. Computer simulations of the most important devices and of interesting physical effects supplement the lectures.
LernzielThe course aims at the understanding of the principle physics of modern semiconductor devices, of the foundations in the physical modeling of transport and its numerical simulation. During the course also basic knowledge on quantum-mechanics, semiconductor physics and device physics is provided.
InhaltThe main topics are: transport models for semiconductor devices (quantum transport, Boltzmann equation, drift-diffusion model, hydrodynamic model), physical characterization of silicon (intrinsic properties, scattering processes), mobility of cold and hot carriers, recombination (Shockley-Read-Hall statistics, Auger recombination), impact ionization, metal-semiconductor contact, metal-insulator-semiconductor structure, and heterojunctions.
The exercises are focussed on the theory and the basic understanding of the operation of special devices, as single-electron transistor, resonant tunneling diode, pn-diode, bipolar transistor, MOSFET, and laser. Numerical simulations of such devices are performed with an advanced simulation package (Sentaurus-Synopsys). This enables to understand the physical effects by means of computer experiments.
SkriptThe script (in book style) can be downloaded from: https://iis-students.ee.ethz.ch/lectures/
LiteraturThe script (in book style) is sufficient. Further reading will be recommended in the lecture.
Voraussetzungen / BesonderesQualifications: Physics I+II, Semiconductor devices (4. semester).
227-0166-00LAnalog Integrated Circuits Information W6 KP2V + 2UT. Jang
KurzbeschreibungThis course provides a foundation in analog integrated circuit design based on bipolar and CMOS technologies.
LernzielIntegrated circuits are responsible for much of the progress in electronics in the last 50 years, particularly the revolutions in the Information and Communications Technologies we witnessed in recent years. Analog integrated circuits play a crucial part in the highly integrated systems that power the popular electronic devices we use daily. Understanding their design is beneficial to both future designers and users of such systems.
The basic elements, design issues and techniques for analog integrated circuits will be taught in this course.
InhaltReview of bipolar and MOS devices and their small-signal equivalent circuit models; Building blocks in analog circuits such as current sources, active load, current mirrors, supply independent biasing etc; Amplifiers: differential amplifiers, cascode amplifier, high gain structures, output stages, gain bandwidth product of op-amps; stability; comparators; second-order effects in analog circuits such as mismatch, noise and offset; data converters; frequency synthesizers; switched capacitors.
The exercise sessions aim to reinforce the lecture material by well guided step-by-step design tasks. The circuit simulator SPECTRE is used to facilitate the tasks. There is also an experimental session on op-amp measurements.
SkriptHandouts of presented slides. No script but an accompanying textbook is recommended.
LiteraturBehzad Razavi, Design of Analog CMOS Integrated Circuits (Irwin Electronics & Computer Engineering) 1st or 2nd edition, McGraw-Hill Education
227-0225-00LLinear System TheoryW6 KP5GA. Iannelli
KurzbeschreibungThe class is intended to provide a comprehensive overview of the theory of linear dynamical systems, stability analysis, and their use in control and estimation. The focus is on the mathematics behind the physical properties of these systems and on understanding and constructing proofs of properties of linear control systems.
LernzielStudents should be able to apply the fundamental results in linear system theory to analyze and control linear dynamical systems.
Inhalt- Proof techniques and practices.
- Linear spaces, normed linear spaces and Hilbert spaces.
- Ordinary differential equations, existence and uniqueness of solutions.
- Continuous and discrete-time, time-varying linear systems. Time domain solutions. Time invariant systems treated as a special case.
- Controllability and observability, duality. Time invariant systems treated as a special case.
- Stability and stabilization, observers, state and output feedback, separation principle.
SkriptAvailable on the course Moodle platform.
Voraussetzungen / BesonderesSufficient mathematical maturity, in particular in linear algebra, analysis.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Problemlösunggeprüft
Persönliche KompetenzenKreatives Denkengefördert
Kritisches Denkengefördert
Integrität und Arbeitsethikgefördert
227-0311-00LQubits, Electrons, PhotonsW6 KP3V + 2UT. Zambelli
KurzbeschreibungIn-depth analysis of the quantum mechanics origin of nuclear magnetic resonance (qubits, two-level systems), of LASER (quantization of the electromagnetic field, photons), and of electron transfer (from electrochemistry to photosynthesis).
LernzielBeside electronics nanodevices, D-ITET is pushing its research in the fields of NMR (MRI), electrochemistry, bioelectronics, nano-optics, and quantum information, which are all rationalized in terms of quantum mechanics.

Starting from the axioms of quantum mechanics, we will derive the fascinating theory describing spin and qubits, electron transitions and transfer, photons and LASER: quantum mechanics is different because it mocks our daily Euclidean intuition!

In this way, students will work out a robust quantum mechanics (theoretical!) basis which will help them in their advanced studies of the following masters: EEIT (batteries), Biomedical Engineering (NMR, bioelectronics), Quantum Engineering, Micro- and Nanosystems.
Inhalt• Lagrangian and Hamiltonian: Symmetries and Poisson Brackets
• Postulates of QM: Hilbert Spaces and Operators
• Heisenberg’s Matrix Mechanics: Hamiltonian and Time Evolution Operator
• Spin: Qubits, Bloch Equations, and NMR
• Entanglement
• Symmetries and Corresponding Operators
• Schrödinger's Wave Mechanics: Electrons in a Periodic Potential and Energy Bands
• Harmonic Oscillator: Creation and Annihilation Operators
• Identical Particles: Bosons and Fermions
• Quantization of the Electromagnetic Field: Photons, Absorption and Emission, LASER
• Electron Transfer: Marcus Theory via Born-Oppenheimer, Franck-Condon, Landau-Zener
SkriptNo lecture notes because the proposed textbooks together with the provided supplementary material are more than exhaustive!

!!!!! I am using OneNote. All lectures and exercises will be broadcast via ZOOM and correspondingly recorded (link in Moodle) !!!!!
Literatur• J.S. Townsend, "A Modern Approach to Quantum Mechanics", Second Edition, 2012, University Science Books

• M. Le Bellac, "Quantum Physics", 2011, Cambridge University Press

• (Lagrangian and Hamiltonian) L. Susskind, G. Hrabovsky, "Theoretical Minimum: What You Need to Know to Start Doing Physics", 2014, Hachette Book Group USA

Supplementary material will be uploaded in Moodle.

_ _ _ _ _ _ _

+ (as rigorous and profound presentation of the mathematical framework) G. Dell'Antonio, "Lectures on the Mathematics of Quantum Mechanics I", 2015, Springer

+ (as account of those formidable years) G. Gamow, "Thirty Years that Shook Physics", 1985, Dover Publications Inc.
Voraussetzungen / BesonderesThe course has been intentionally conceived to be self-consistent with respect to QM for those master students not having encountered it in their track yet. Therefore, a presumably large overlapping has to be expected with a (welcome!) QM introduction course like the D-ITET "Physics II".

A solid base of Analysis I & II as well as of Linear Algebra is really helpful.

IMPORTANT: Wed 22.9, 29.9, and 22.12 are lectures (NOT exercises!). Please, look at the details in moodle!
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengefördert
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Medien und digitale Technologiengefördert
Problemlösunggeprüft
Projektmanagementgeprüft
Soziale KompetenzenKommunikationgefördert
Kooperation und Teamarbeitgefördert
Kundenorientierunggefördert
Menschenführung und Verantwortunggefördert
Selbstdarstellung und soziale Einflussnahmegefördert
Sensibilität für Vielfalt geprüft
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
Selbststeuerung und Selbstmanagement geprüft
227-0427-00LSignal Analysis, Models, and Machine Learning
Findet dieses Semester nicht statt.
This course was replaced by "Introduction to Estimation and Machine Learning" and "Advanced Signal Analysis, Modeling, and Machine Learning".
W6 KP4GH.‑A. Loeliger
KurzbeschreibungMathematical methods in signal processing and machine learning.
I. Linear signal representation and approximation: Hilbert spaces, LMMSE estimation, regularization and sparsity.
II. Learning linear and nonlinear functions and filters: neural networks, kernel methods.
III. Structured statistical models: hidden Markov models, factor graphs, Kalman filter, Gaussian models with sparse events.
LernzielThe course is an introduction to some basic topics in signal processing and machine learning.
InhaltPart I - Linear Signal Representation and Approximation: Hilbert spaces, least squares and LMMSE estimation, projection and estimation by linear filtering, learning linear functions and filters, L2 regularization, L1 regularization and sparsity, singular-value decomposition and pseudo-inverse, principal-components analysis.
Part II - Learning Nonlinear Functions: fundamentals of learning, neural networks, kernel methods.
Part III - Structured Statistical Models and Message Passing Algorithms: hidden Markov models, factor graphs, Gaussian message passing, Kalman filter and recursive least squares, Monte Carlo methods, parameter estimation, expectation maximization, linear Gaussian models with sparse events.
SkriptLecture notes.
Voraussetzungen / BesonderesPrerequisites:
- local bachelors: course "Discrete-Time and Statistical Signal Processing" (5. Sem.)
- others: solid basics in linear algebra and probability theory
  •  Seite  1  von  3 Nächste Seite Letzte Seite     Alle