Contravariant & Covariant Components of Vectors - An Introduction to the Metric Tensor

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  • Опубликовано: 25 ноя 2024

Комментарии • 37

  • @math2cool
    @math2cool Год назад +9

    What a gifted instructor. If you truly want to understand GR you must make this series a stop along your way. Thank you Eddie.

  • @LibertyAzad
    @LibertyAzad Год назад +6

    This is THE place to start studying GR. Then you can hit the books and other video lectures more profitably.

  • @jesuscuadrado2291
    @jesuscuadrado2291 10 месяцев назад +4

    The video is incredible, pure gold! The exhibition is masterful! It is the best EVER introduction to contravariant and covariant components, and metric tensor (I use many books and resources). I was reading the "Covariant Physics (Moataz)" book and I started to get lost in chapter 1.3, it is an easy chapter where the contravariant and covariant components are introduced along with the metric tensor in cartesian coordinates (metric tensor is not mentioned in any case, and it is used as the Kronecker delta like a kind of magic term to convert between contravariant and covariant components) . Only after watching the video, I have truly understood the chapter.
    I am excited about these GR videos, I have decided to study them carefully one by one. I have already seen the first one. I am a graduate in Physics who, after a long time, went back to studying certain topics to fill many gaps that were left during my career. Thanks Professor Edward D Boyes for this precious resource.

  • @astronomy-channel
    @astronomy-channel Год назад +6

    A superb series of videos which progress in slow logical steps. Impressive!

  • @christianfunintuscany1147
    @christianfunintuscany1147 9 месяцев назад +2

    I finally got the geometric interpretation of covariant and contravariant components … thank you!!!!

  • @jonathanlister5644
    @jonathanlister5644 4 месяца назад

    Just beyond belief! Wonderfully expressed, I love how you subtly hammer home the points to guide people away from the restrictions of geometry learned from a black board! " Be very careful what you put into that mind for you will never get it out!".

  • @r2k314
    @r2k314 Год назад +2

    Your series are wonderful. If I had studied them when I first started, I would be much much further along. Thank you
    I wish I could figure how to put this at the top of the intro to GR recommendations. You have no peer!

  • @manishankaryadav7307
    @manishankaryadav7307 10 месяцев назад +1

    Hi Eddie,
    Thank you for the videos. Everything (the content, the flow, the math, the questions, the voice, the presentation etc.) is fabulous.
    At time stamp 57:21 on LHS third entry's subscript needs to be 3. 🙂
    Thank you once again,
    Mani

  • @jaeimp
    @jaeimp 3 месяца назад

    Excellent series! Thank you! The contravariant and covariant components and the lowering indices made sense for the first time. Now I am all confused about the many places in which there seems to be a need for a dual vector space with a set of dual basis vectors, etc.

  • @jameskinnally4173
    @jameskinnally4173 Год назад +1

    This is an excellent series. Thank you very much!

  • @ImranMoezKhan
    @ImranMoezKhan 8 месяцев назад +2

    Small typographical error I suspect: for the matrix equation at around 50:46 , the right hand side is product of 1x2 and 2x2, which would produce a 1x2 row vector, but the left hand side is 2x1 column vector.
    I suppose the matrix of dot products should come first followed by the contravariant as a column vector.

  • @victoriarisko
    @victoriarisko 6 месяцев назад

    Beautiful instruction! Most enjoyable to learn quite sophisticated topics

  • @christosgeorgiadis7462
    @christosgeorgiadis7462 Год назад +1

    This is a great exposition of the subject thank you!
    Believe me, I have tried a lot of others ...

  • @perdehurcu
    @perdehurcu 2 месяца назад

    Muhteşem anlatım. Çok değerli bilgiler. Teşekkürler.

  • @Rauf_Akbaba
    @Rauf_Akbaba Год назад +1

    Excellent, thank you

  • @Mouse-qm8wn
    @Mouse-qm8wn 7 месяцев назад

    Eddie, you made my day😊🎉! What a great video. I am looking forward to see the whole series.
    I have a question. Do you have a reference to a good GR book which contains problems and solutions for practise?

  • @messapatingy
    @messapatingy 4 месяца назад

    Remember Co-Low-Pro
    Co: Covariant components
    Low: Use lower indices
    Pro: Represent projections onto coordinate axes

  • @eddieboyes
    @eddieboyes  10 месяцев назад

    Thanks Mani - another one I hadn't spotted! I'll probably put a "correction" into the Video Description rather than upload a new corrected version (as that would re-start the counts etc from scratch). Putting a "correction" into the Video Description ought to put a correction notice at the relevant time point (according to RUclips) ...... but I can't seem to get that to work at the moment. Thanks again anyway. Eddie

  • @miguelaphan58
    @miguelaphan58 7 месяцев назад

    .
    A Master explanation !!!

  • @jimmyraconteur
    @jimmyraconteur 4 месяца назад

    fantastic professor

  • @djordjekojicic
    @djordjekojicic Год назад +1

    Beautiful explanations and examples. I've seen a lot of GR videos but this series is one of the best. I have one question though. Why are covariant vector components with lower indices presented on same axis when they belong to dual vectors basis which are different in such manner that each one is perpendicular to the original one with different index?

    • @jesuscuadrado2291
      @jesuscuadrado2291 10 месяцев назад

      You are right, it is probably a simplification to not introduce dual basis vectors

    • @jesuscuadrado2291
      @jesuscuadrado2291 10 месяцев назад

      In any case, you can also have the covariant components with respect to the contravariant basis: ruclips.net/video/nNMY02udkHw/видео.htmlsi=l0YONDtcKOnksqLt&t=468

  • @maaspira
    @maaspira 6 месяцев назад +1

    Thank you very much!

  • @hasnounimohamed4710
    @hasnounimohamed4710 8 месяцев назад

    you make it very easy to understand thank you

  • @kevincleary627
    @kevincleary627 Год назад

    Great videos. Is there a playlist so that I can watch them sequentially? Thanks!

  • @sagsolyukariasagi
    @sagsolyukariasagi 6 месяцев назад

    Should the basis vectors always come from the covariant bases?

  • @johnwills3923
    @johnwills3923 День назад

    I think that the equation at time 33:07 is NOT correct. In order to be correct the contravariant & covariant vector components I think need to multiplied by the magnitude of their corresponding basis vectors

  • @SphereofTime
    @SphereofTime 6 месяцев назад +1

    1:00

  • @NEWDAWNrealizingself
    @NEWDAWNrealizingself Месяц назад

    THANKS !

  • @r2k314
    @r2k314 Год назад

    Thank You!

  • @Yuri-w8k4j
    @Yuri-w8k4j 11 месяцев назад

    1:06:52 Isn’t it a bit early to name g a tensor? We know :) that not every object with indexes is a tensor, right?

  • @RBRB-hb4mu
    @RBRB-hb4mu 7 месяцев назад

    Black background with light letters please, it make it easier to learn

    • @2pizen
      @2pizen 6 месяцев назад

      second that!

  • @jameshopkins3541
    @jameshopkins3541 Год назад

    You has no explain it!!!!! SoNOLIKE

  • @Altalex988
    @Altalex988 9 месяцев назад

    Thnks for the serie!
    One question: the proof @32:25 holds only if basis vectors are unit vector, otherwise general formula is V_n=gmnV_upper_n ?
    Tnhks, bye

  • @JoseAntonio-ml8yg
    @JoseAntonio-ml8yg 6 месяцев назад

    Thank you very much!