Entropy Confusion - Sixty Symbols

Entropy Confusion - Sixty Symbols

Professor Phil Moriarty talks about Entropy (again). Reddit discussion: http://redd.it/2l6ekd A little extra bit from this interview: http://youtu.be/maWvwuYR4VA An article Phil wrote after this video: http://physicsfocus.org/moriarty-confused-good-learn/ LINKS TO MENTIONED VIDEOS & RESEARCH The first entropy videos --- https://www.youtube.com/watch?v=lav6R7PpmgI and https://www.youtube.com/watch?v=av8aDFFtSs0 Daan Frenkel: http://www.ch.cam.ac.uk/person/df246 Sharon Glotzer’s group: http://sitemaker.umich.edu/glotzergroup/home TEDx talk from Glotzer: https://www.youtube.com/watch?v=chS8dpGB0E0 Disorder: A Cracked Crutch (not free to read): http://pubs.acs.org/doi/abs/10.1021/ed079p187 Visit our website at http://www.sixtysymbols.com/ We're on Facebook at http://www.facebook.com/sixtysymbols And Twitter at http://twitter.com/#!/periodicvideos This project features scientists from The University of Nottingham http://bit.ly/NottsPhysics Sixty Symbols videos by Brady Haran A run-down of Brady's channels: http://bit.ly/bradychannels

Entropy - Sixty Symbols

Entropy - Sixty Symbols

Broken vases, cups of tea and a scientist's tombstone - welcome to the world of entropy. More phsyics at http://www.sixtysymbols.com/

Second Law of Thermodynamics - Sixty Symbols

Second Law of Thermodynamics - Sixty Symbols

Professor Mike Merrifield discusses aspects of the Second Law of Thermodynamics. Referencing the work of Kelvin and Clausius, among others! Professor Merrifield is the Head of the School of Physics and Astronomy at the University of Nottingham. Gamma Trilogy: https://www.youtube.com/playlist?list=PLcUY9vudNKBNwkTA_1VWz8JeqO8HU15qo Patreon: https://www.patreon.com/sixtysymbols Visit our website at http://www.sixtysymbols.com/ We're on Facebook at http://www.facebook.com/sixtysymbols And Twitter at http://twitter.com/sixtysymbols This project features scientists from The University of Nottingham http://bit.ly/NottsPhysics Patreon: https://www.patreon.com/sixtysymbols Sixty Symbols videos by Brady Haran http://www.bradyharanblog.com Email list: http://eepurl.com/YdjL9

15.2 Predict the entropy change for a given reaction or process [HL IB Chemistry]

15.2 Predict the entropy change for a given reaction or process [HL IB Chemistry]

Remember that ENTROPY can also be thought of as DISORDER. Gas has the highest entropy in IB chemistry, so any reaction that produces gas will have a positive value of delta S, whereas any reaction that uses up gas will have a negative delta S. This is an oversimplification, e.g. what happens if both product and reactants are gaseous -- watch the vid!

Information theory: Entropy

Information theory: Entropy

An explanation of entropy in information theory and how to calculate it. (The last video ran long, so I had to slice it up.) More on information theory: http://tinyurl.com/zozlx http://tinyurl.com/8bueub http://tinyurl.com/bfpu8b http://tinyurl.com/as2txv http://tinyurl.com/dcsgt2 http://tinyurl.com/ct5phc The music is the third movement of Carl Maria von Weber's Clarinet Concerto No. 2, as performed by the Skidmore College Orchestra. http://www.musopen.com/music.php?type=piece&id=67 http://myspace.com/zjemptv http://emptv.com/

WII? (2a) Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits

WII? (2a) Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits

What is Information? - Part 2a - Introduction to Information Theory: Script: http://crackingthenutshell.org/what-is-information-part-2a-information-theory ** Please support my channel by becoming a patron: http://www.patreon.com/crackingthenutshell ** Or... how about a Paypal Donation? http://crackingthenutshell.org/donate Thanks so much for your support! :-) - Claude Shannon - Bell Labs - Father of Information Theory - A Mathematical Theory of Communication - 1948 - Book, co-written with Warren Weaver - How to transmit information efficiently, reliably & securely through a given channel (e.g. tackling evesdropping) - Applications. Lossless data compression (ZIP files). Lossy data compression (MP3, JPG). Cryptography, thermal physics, quantum computing, neurobiology - Shannon's definition not related to meaningfulness, value or other qualitative properties - theory tackles practical issues - Shannon's information, a purely quantitative measure of communication exchanges - Shannon's Entropy. John von Neumann. Shannon's information, information entropy - avoid confusion with with thermodynamical entropy - Shannon's Entropy formula. H as the negative of a certain sum involving probabilities - Examples: fair coin & two-headed coin - Information gain = uncertainty reduction in the receiver's knowledge - Shannon's entropy as missing information, lack of information - Estimating the entropy per character of the written English language - Constraints such as "I before E except after C" reduce H per symbol - Taking into account redundancy & contextuality - Redundancy, predictability, entropy per character, compressibility - What is data compression? - Extracting redundancy - Source Coding Theorem. Entropy as a lower limit for lossless data compression. - ASCII codes - Example using Huffman code. David Huffman. Variable length coding - Other compression techniques: arithmetic coding - Quality vs Quantity of information - John Tukey's bit vs Shannon's bit - Difference between storage bit & information content. Encoded data vs Shannon's information - Coming in the next video: error correction and detection, Noisy-channel coding theorem, error-correcting codes, Hamming codes, James Gates discovery, the laws of physics, How does Nature store Information, biology, DNA, cosmological & biological evolution

The Symbol for Entropy

The Symbol for Entropy

Provided to YouTube by Believe SAS The Symbol for Entropy · RE_P Abstract Tales ℗ Funk You Records Released on: 2014-10-14 Composer: RE_P Music Publisher: D.R Auto-generated by YouTube.

Entropy - Wiki Videos

Entropy - Wiki Videos

In thermodynamics, entropy (usual symbol S) is a measure of the number of specific ways in which a thermodynamic system may be arranged, commonly understood as a measure of disorder. Read more here: https://en.wikipedia.org/wiki/Entropy Watch similar videos here: https://www.youtube.com/playlist?list=PLVTxyJV-b3NbuyiC1mX_qT3oR1Qw47BG2 See more from Wiki Videos: https://www.youtube.com/channel/UC9pZsh1JbkZDC1LiwOHjwuQ/feed Follow us on Facebook : https://www.facebook.com/WikiVideoProductions Follow us on Twitter : https://twitter.com/VideosWiki Our Website : www.wvprod.com This video is the sole and exclusive property of WV Production Limited. WikiVideos and all related characters and elements are trademarks of and © 2015 WV Production Limited. All rights reserved.

Lecture 5: Entropy and Data Compression (IV): Shannon's Source Coding Theorem, Symbol Codes

Lecture 5: Entropy and Data Compression (IV): Shannon's Source Coding Theorem, Symbol Codes

Lecture 5 of the Course on Information Theory, Pattern Recognition, and Neural Networks. Produced by: David MacKay (University of Cambridge) Author: David MacKay, University of Cambridge A series of sixteen lectures covering the core of the book "Information Theory, Inference, and Learning Algorithms" (Cambridge University Press, 2003, http://www.inference.eng.cam.ac.uk/mackay/itila/) which can be bought at Amazon (http://www.amazon.co.uk/exec/obidos/ASIN/0521642981/davidmackay0f-21), and is available free online (http://www.inference.eng.cam.ac.uk/mackay/itila/). A subset of these lectures used to constitute a Part III Physics course at the University of Cambridge. The high-resolution videos and all other course material can be downloaded from the Cambridge course website (http://www.inference.eng.cam.ac.uk/mackay/itprnn/). Snapshots of the lecture can be found here: http://www.inference.eng.cam.ac.uk/itprnn_lectures/ These lectures are also available at http://videolectures.net/course_information_theory_pattern_recognition/ (synchronized with snapshots and slides)

Entropy applied to individual flourishing, Balance, Symbol, Emergence and Meaning

Entropy applied to individual flourishing, Balance, Symbol, Emergence and Meaning

Entropy, both in physics and in life, one of the core principles that underly the substructure of all domains of knowledge.Balance as it is represented in science, art, politics and economics, and then back to a discussion of emergence. In previous videos, Alex and I discussed resonance, critical mass, emergence, and the aggregation of color and light. Alex's website: "Viewers can visit my website to see a primordial pattern and practice transforming chaos into symbolic meaning: http://cosymbolic.com Karen's website: http://karenwongart.com “Materiality is a medium of communication.” Paul VanderKlay If every particle in the universe were perfectly equidistant from every other particle, is that the largest entropy possible? “The distribution with the largest entropy is the least informative default”. 1. Maximizing entropy minimizes the amount of prior information built into the distribution. One can explain it as the spread-outness. An example might be the way the heat in a cup of coffee spreads out to the air and to the cup. You could also think of a messy room where things aren’t where they should be but are spread out all over the place. 2. Many physical systems tend to move towards maximal configurations over time. Quantum physics, non-locality as it relates to Opportunity Cost. One choice prevents all others. “Reality is that which governs.” (Paul VanderKlay) The universe is a certain way, and if we don’t abide by the “rules”, we face the consequence. Balance includes the principle of proportionality. Art - a pleasing composition has to have balance. How do you find it? It can be a lot of one thing, a little of another. Unity with variety. Mostly cool blues and lavenders, but with a focal point and a few touches of orange and yellow to keep it from becoming too rigid or boring. Dominance brings unity and balance. You achieve balance by having Just the right amount of repetition, variation, gradation. Too much, chaotic, too little, boring The right balance is like the edge, the wave, between order and chaos where Jordan Peterson says is the most creative, productive place to be. That which is small and different gets the focus. Balance in the material world: An even distribution of weight - doesn’t this have to include force and speed? A smaller, heavier, more active object will balance a larger, lighter, less active object. A counteracting weight or force A condition in which different elements are equal or in correct proportions Remain in a steady position without falling. A state of potential dependent on the difference in height. The cost of obtaining such information has to balance its benefits. In Politics: The power held by a small group over larger groups - see Nassim Taleb article on the Dominance of the Minority from the book, Skin in the Game. https://medium.com/incerto/the-most-intolerant-wins-the-dictatorship-of-the-small-minority-3f1f83ce4e15 From a lecture on entropy and probabilities https://warwick.ac.uk/fac/cross_fac/complexity/study/msc_and_phd/co904/co904online/lecture-3-4.pdf “The maximum entropy solution assigns zero probabilities only when no other possibilities are allowed. This is a very desirable property: it would be a sure failure to propose that a certain state has zero probability, and then find out that a given observation happened to yield that state. The Maximum Entropy solution is guaranteed not to fail there.” (Note from The Meaning Code: When no other possibilities are allowed, there is only one solution, or at least that’s what he seems to say to me, and I wonder if this fits with the Glotzer lecture on particles self organizing into a crystalline structure when in a maximum constraint. https://youtu.be/et5KcmdCXRk So, God in His goodness, allows us the minimum constraint so that there are many possible solutions to allow for maximum creativity, information and individuality. ... the distribution with the largest entropy should be chosen as the least-informative default. The motivation is twofold: first, maximizing entropy minimizes the amount of prior information built into the distribution; second, many physical systems tend to move towards maximal entropy configurations over time. Explanation of the arrow of time and entropy where a seeming paradox is addressed: https://www.youtube.com/watch?v=L4XZP5XwWbk&list=PL_onPhFCkVQho9Zw9f1Xg12lvE-1VtTFJ&index=62 A further explanation of entropy and the arrow of time: https://www.youtube.com/watch?v=NGZ7LtwJPrM&list=PL_onPhFCkVQho9Zw9f1Xg12lvE-1VtTFJ&index=65 Part 1 interview with physicist Charlie Lineweaver talking about the so called "first paradox of entropy" by making a distinction between kinetic energy and gravity. https://www.youtube.com/watch?v=rMJ_FnyosR4

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