A course on electromagnetism, starting from the Maxwell equations and describing their application to electrostatics, magnetostatics, induction, light and radiation. The course also covers the relativistic form of the equations and electromagnetism in materials.
An introduction to the quantum Hall effect. The first half uses only quantum mechanicsand is at a levelsuitable for undergraduates. The second half covers more advanced field theoretic techniques of Chern-Simonsand conformal field theories.
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An introduction to fluid mechanics, aimed at undergraduates. The course covers the basic flows arising from the Euler and Navier-Stokes equations, including discussions of waves, stability, and turbulence.
An introduction to statistical mechanics and thermodynamics,aimed at final year undergraduates. After developing the fundamentals of the subject, the course covers classical gases, quantum gases and phase transitions.
An introduction to general relativity, aimed atfirst year graduate students. It starts with a gentle introduction to geodesics in curvedspacetime. The course then describes the basics of differential geometry before turning tomore advanced topics in gravitation.
These notes provide an introduction to the fun bits of quantum field theory, in particular those topics relatedto topology and strong coupling. They are aimed at beginning graduate students and assumea familiarity with the path integral.
An elementary course on elementary particles. This is, by some margin, the least mathematically sophisticated of all my lecture notes, requiring little more than high school mathematics. The lectures provide a pop-science, but detailed, account of particle physics and quantum field theory. These lectures were given at the CERN summer school.
A course on particle physics that most definitely uses more than high school mathematics. The lectures describe the mathematical structure of the Standard Model, and explore features of the stong and weak forces. There are also sections on spontaneous symmetry breaking and anomalies.
An introduction to N=1 supersymmetry in d=3+1 dimensions, aimed at first year graduate students. The lectures describe how to construct supersymmetric actions before unpacking the details of their quantum dynamics and dualities.
The Cornell method provides a systematic format for condensing and organizing notes without laborious recopying. After writing the notes in the main space, use the left-hand space to label each idea and detail with a key word or "cue."
Method: Rule your paper with a 2 _ inch margin on the left leaving a six-inch area on the right in which to make notes. During class, take down information in the six-inch area. When the instructor moves to a new point, skip a few lines. After class, complete phrases and sentences as much as possible. For every significant bit of information, write a cue in the left margin. To review, cover your notes with a card, leaving the cues exposed. Say the cue out loud, then say as much as you can of the material underneath the card. When you have said as much as you can, move the card and see if what you said matches what is written. If you can say it, you know it.
Advantages: Organized and systematic for recording and reviewing notes. Easy format for pulling outmajor concept and ideas. Simple and efficient. Saves time and effort. "Do-it-right-in-the-first-place system."
Method: Listening and then write in points in an organized pattern based on space indention. Place major points farthest to the left. Indent each more specific point to the right. Levels of importance will be indicated by distance away from the major point. Indention can be as simple as or as complex as labeling the indentions with Roman numerals or decimals. Markings are not necessary as space relationships will indicate the major/minor points.
Advantages: Well-organized system if done right. Outlining records content as well as relationships. It also reduces editing and is easy to review by turning main points into questions.
When to Use: The outline format can be used if the lecture is presented in outline organization. This may be either deductive (regular outline) or inductive (reverse outline where minor points start building to a major point). Use this format when there is enough time in the lecture to think about and make organization decisions when they are needed. This format can be most effective when your note-taking skills are super and sharp and you can handle the outlining regardless of the note-taking situation.
Mapping is a method that uses comprehension/concentration skills and evolves in a note-taking form which relates each fact or idea to every other fact or idea. Mapping is a graphic representation of the content of a lecture. It is a method that maximizes active participation, affords immediate knowledge as to its understanding, and emphasizes critical thinking.
Advantages: This format helps you to visually track your lecture regardless of conditions. Little thinking is needed and relationships can easily be seen. It is also easy to edit your notes by adding numbers, marks, and color coding. Review will call for you to restructure thought processes which will force you to check understanding. Review by covering lines for memory drill and relationships. Main points can be written on flash or note cards and pieced together into a table or larger structure at a later date.
When to Use: Use when the lecture content is heavy and well-organized. May also be used effectively when you have a guest lecturer and have no idea how the lecture is going to be presented.
Method: Determine the categories to be covered in lecture. Set up your paper in advance by columns headed by these categories. As you listen to the lecture, record information (words, phrases, main ideas, etc.) into the appropriate category.
Advantages: Helps you track conversation and dialogues where you would normally be confused and lose out on relevant content. Reduces amount of writing necessary. Provides easy review mechanism for both memorization of facts and study of comparisons and relationships.
When to Use: Test will focus on both facts and relationships. Contents is heavy and presented fast. You want to reduce the amount of time you spend editing and reviewing at test time. You want to get an overview of the whole course on one big paper sequence.
Example 1: A revolution is any occurrence that affects other aspects of life, such as economic life, social life, and so forth. Therefore revolutions cause change. (see page 29 to 30 in your text about this.)
Example 2: At first, Freud tried conventional, physical methods of treatment such as giving baths, massages, rest cures, and similar aids. But when these failed he tried techniques of hypnosis that he had seen used by Jean-Martin Charcot. Finally, he borrowed an idea from Jean Breuer and used direct verbal communication to get an unhypnotized patient to reveal unconscious thoughts.
The first 6 chapters were originally prepared in 1997-98, Chapter 7 wasadded in 1999, and Chapter 9 was added in 2004.A typeset version of Chapter 8 (on fault-tolerant quantum computation)is not yet available; nor are the figures for Chapter 7. Additional material isavailable in the form of handwritten notes.
The theory of quantum information and quantum computation. Overview ofclassical information theory, compression of quantum information, transmissionof quantum information through noisy channels, quantum entanglement, quantumcryptography. Overview of classical complexity theory, quantum complexity,efficient quantum algorithms, quantum error-correcting codes, fault-tolerantquantum computation, physical implementations of quantum computation.
Certainly it would be useful to have had a previous course on quantummechanics, though this may not be essential. It would also be useful to knowsomething about (classical) information theory, (classical)coding theory, and (classical) complexity theory, since a central goal ofthe course will be generalize these topics to apply to quantum information.But we will review this material when we get to it, so you don't need to worryif you haven't seen it before. In the discussion of quantum coding, we will usesome rudimentary group theory.
In fact, quantum information -- information storedin the quantum state of a physical system -- has weird properties that contrastsharply with the familiar properties of "classical" information. Anda quantum computer -- a new type of machine that exploits the quantumproperties of information -- could perform certain types of calculations farmore efficiently than any foreseeable classical computer.
In this course, we will study the properties that distinguish quantuminformation from classical information. And we will see how these propertiescan be exploited in the design of quantum algorithms that solve certain problemsfaster than classical algorithms can.
A quantum computer will be much more vulnerable than a conventional digitalcomputer to the effects of noise and of imperfections in the machine.Unavoidable interactions of the device with its surroundings will damage thequantum information that it encodes, a process known as decoherence.Schemes must be developed to overcome this difficulty if quantum computers areever to become practical devices.
In this course, we will study quantum error-correcting codes that can beexploited to protect quantum information from decoherenceand other potential sources of error. And we will see how coding can enable aquantum computer to perform reliably despite the inevitable effects of noise.
Science is a rigorous, systematic endeavor that builds and organizes knowledge in the form of testable explanations and predictions about the world.[1][2] Modern science is typically divided into three major branches:[3] the natural sciences (e.g., physics, chemistry, and biology), which study the physical world; the social sciences (e.g., economics, psychology, and sociology), which study individuals and societies;[4][5] and the formal sciences (e.g., logic, mathematics, and theoretical computer science), which study formal systems, governed by axioms and rules.[6][7] There is disagreement whether the formal sciences are science disciplines,[8][9][10] as they do not rely on empirical evidence.[11][9] Applied sciences are disciplines that use scientific knowledge for practical purposes, such as in engineering and medicine.[12][13][14] 152ee80cbc
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