Mod-03 Lec-07 Linear response; dispersion relations (Part I)

[@pradyumnapatra1356]

So excellent, don't word to tell anything, simply marvelous Lecture..

[@johnsnguyen1901]

Wow this is a great video. I was skeptical thinking that his accent would be to strong to understand but his English is fantastic. I wish more of my non native english speaking profs at my school had his level of English.

[@amitozazad1584]

He is legend! I feel really blessed to study 3 courses from him.

[@albertogotta4983]

Fantastic video!

[@bishalthapa2179]

this person is brilliant

[@live4Cha]

excellent tnx for sharing

[@benjamincordes207]

Sir, you are an absolutely brilliant teacher! This was very clearly explained.

[@tonyfox1316]

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[@jaidenvicente7200]

@Tony Fox I watch on Flixzone. Just google for it :)

[@aaraveverett8696]

@Jaiden Vicente Yup, have been using flixzone for since april myself =)

[@tonyfox1316]

@Jaiden Vicente Thank you, I went there and it seems to work :D Appreciate it!!

[@jaidenvicente7200]

@Tony Fox you are welcome =)

[@bhuvaneshthurimerla3029]

great video sir. nice explanation

[@alute5532]

We want to measure response of a system. Now linear system The greater stimulus the greater the response Define response function, then define dispersion In linear fashion I'm. Ohms law Current proportional to voltage ⚡ Hookes law stress (on system) : Elastic region In elastic region the strain proportional to stress Electric field on dielectric Small field small dielectric polarization On magnet system apply magnet field, response magnetization I. E. In paramagnet Q. Does the system has 1 Kind of behavior (or another) AC DC voltage Physical system depends upon time dependent stimulus 1take stimulus breaks it to frequency components by Fourier analysis For each Fourier component, what's the system response 3 supoerpose all these Isotropic medium 2 independent elastic Bulk modulus Poisson ratios Young mid share modulus Don't expect system to increase Survival function decreasing cadlag Inverse Fourier exp i omega t R(t) Careful diracs delta has 1/ 2 pi You can interchange order of integration provided these things converge "Fast enough " Jacobson Dr = Dt' Fourier parts makes orthonormal functions Coefficients must be equal (symmetry) digference=0 or we won't able to superimpose Equating components vector function Space In a basis (orthonormal) Chi(onega) generalized Succeptibility (frequency dependent) E. G. Magnet proportional to field M/h = succeptibility (magnetization per unit applied force ) Unit is in frequency Chi measures response, at that frequency. Makes definite integeal Chi(omega) int(0 inf) Stephanus exp(i omega tdef only for posivitve values came from As t -t'is it's response

[@live4Cha]

i wonder how things change if we replace time variable t with space variable x?

[@wangshuoleon4400]

you can do exactly the same thing, however, you should integrate from [-inf, inf] instead of [-inf, t], see green's function for more details

[@saketpanigrahi]

So he is teaching proffessors of IIT.

[@riturajanand7133]

24.26, why x(w) , chi, can't be a Laplace Transform, having s=-iw? why sir named chi(w) = Fourier-Laplace transform?

[@cestaayush4644]

I also having same doubt.

[@Path_k_pradeep]

Please see complete lecture ..... at around 30 minute He explained this part ...

[@mahmudurrahman1696]

Can anyone suggest any reading material related to this lecture series for further study,

[@SureshGovindarajan]

Prof. Balakrishnan has a book on the subject. www.amazon.in/Mathematical-Physics-Applications-Problems-Solutions/dp/9388264827/