welcome to iit guwahatiiitg.ac.in/physics/fac/padmakumarp/courses/ph101/lecture...3. quantum physics...
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Welcome to Welcome to Welcome to Welcome to
IIT Guwahati IIT Guwahati IIT Guwahati IIT Guwahati
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PH101: PHYSICS-I
Lecture 1
Padma Kumar Padmanabhan
Uday Maiti
Department of Physics
IIT Guwahati
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Topics
1. Analytical (Classical) mechanics
(Up to Mid-Sem Exam; Of 50% marks)
2. Relativity
3. Quantum mechanics
(For End-Sem Exam; Of 50% marks)
Prof. P. Poulose
Prof. Girish Setlur
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Evaluations
Quiz-I of 10% marks on 27th August 2018 (tentatively)
Mid-Semester Exam of 40% (as per institute time table)
Quiz-II of 10 marks (Dates will be announced later)
End-Semester exam of 40% (as per institute time table)
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http://www.iitg.ac.in/physics/fac/padmakumarp/Courses/PH101/JulyNov2018.htm
Course Web Page:
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Syllabus
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Text Books:
1. Introduction to Classical Mechanics by Takwale R and Puranik P
(McGraw Hill Education, 1 st Ed., 2077) .
2. Classical mechanics by John Taylor (University Science, 2005).
3. Quantum Physics of Atoms, Molecules, Solids, Nuclei and Particles by
R. Eisbergand R, Resnick [f ohn-Wiley, 2nd Ed., 2006).
References:1. A Student's Guide to Lagrangians and Hamiltonians by Patrick Hamill
(Cambridge University Press, 1st edition, 2013).2. Theoretical Mechanics by M. R. Spiegel (Tata McGraw Hill, 2008).3. The Feynman Lectures on Physics, Vol. Iby R. P. Feynman, R. B.
Leighton, and M.Sands, [Narosa Publishing House, 1998J.
Books
Intro. Classical Mechanics, David Morin (Cambridge)
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Layout of mechanics course
• Mathematical concepts of partial differentiation and coordinate systems.
• Constraints, degree’s of freedom and generalized coordinates.
• Challenges with unknown nature of constrain forces in Newtonian Mechanics
• D’Alembert’s Principle of virtual work to remove the constrain forces from
analysis.
• Lagrange’s equation: An alternative to Newton’s law
• Variational method and Lagrange's equation from variational principle
• Hamiltonian equations of motion
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Analytical mechanics
Introduction of new concepts of mechanics
beyond Newton’s law:
Largangian and Hamiltonian equations
Why this is important?
Making the analysis easier, in particular complex dynamical
situations with imposed constrains/conditions.
More general concepts extendable to other modern area of
physics like quantum mechanics, field theory etc.
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Review of certain mathematical concepts
Key to understand classical mechanics
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Total Differential: Function of one variable
� = �(�)
�
∆�∆�
�� � = �� = �� ∆�
∆� = �� � � + ∆� − �(�)∆�∆� → 0 ∆� → 0
� = [��(�)] �
• Infinitesimal change of � around certain point (�) =(rate of change of � around the
point) (magnitude of change in � )
• At stationary points (A,B, C), � does not changes [� = 0] even if � is changed
infinitesimally,
which implies that at those points �� � = 0.
� = � � �� � �������� �� ��� �������� �
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Partial differential: function of more than one
variables�(�, �) depends on two independent variables � �� �.
Example: Height (�) of a hill as function of position
coordinate �, � .
The rate of change (slope) in the ‘����������, when �remains constant is denoted by
The rate of change in the ‘����������, when � remains
constant is denoted by
( � �)!= �� � � + ∆�, � − �(�, �)
∆�∆� → 0
( � �)"= �� � �, � + ∆� − �(�, �)
∆�∆� → 0
�-
direction
�-
direction
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• Change in height if I walk in the ‘#’ direction [keeping ‘�’
fixed] by ‘$#’ ?
[$%]$# =('%'#)$#
= ���� �� �(��)� �� ′�′ �������� �+���� �� �(��)� �� �
• Similarly, [$%]$, =('%',)$,
Partial differential
�-
direction
�-
direction
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Change in height if I go in the arbitrary direction so that ‘�’
changes by ‘�’ and ‘�’ also changes by ‘�’
$% = ('%'#)$#+(
'%',)$, =[�]-" + [�]-!
Partial differential
• Generalization for a function which depends on several
variables �(�., �/, �0…. �1)
�= (23
2"4)�.+ (
232"5
)�/+…….+ (23
2"6)�1=∑ (
232"8
)�9::
�-
direction
�-
direction
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Partial differential (Examples)
f(x,y) = a x2 + b y2
'%'# = ; < =
f(x,y) = a x2y + b
'%'# = ; < = >
f(x,θ) = a x Sin(θ) + b θ2
'%', = ; ? >
'%', = <=;
'%'# = < Sin(θθθθ)
'%'� = < = Cos(θ) + 2b θ
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Differentiation of function of functions
�(�, �) is such that � and � are function of another variable say, �.
We wish to find the derivative -3-@.
Example: � = �� + ln �/(we say, f depends x & y explicitly;
f depends u implicitly!)
Let, � = � cos � and � = � sin �How to calculate
-3-@ ?
Method 1: Direct substitution
Step 1: � = (� cos �)(� sin �) + ln(� sin �)/
Step 2: Find -3-@
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Example
G(�, �) = �/ + �/:
H������� �� �(� I��J������ ���+ �(� ���)��,
� � = �0cos � � &
� � = �0Sin � � - ./ ) �/
But
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Method 2: Chain rule
You know, �=(232")�+(
232!)�
$%$N=(
'%'#) $#
$N+('%',) $,
$N
Find the First differentials individually 232",
232!,
-"-@,
-!-@
and then substitute in the above relation.
Chain rule of partial differential
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Generalization for a function depends on several variables
�(�., �/, �0…. �1) and the variables are function of another
set of variables, Let, �9 (�., �/, …. �1)
�= (23
2"4)�.+ (
232"5
)�/+…….+ (23
2"6)�1= ∑ (
232"8
)�91.
232@4
= (23
2"4) 2"4
2@4+ (
232"5
) 2"52@4
+…….+ (23
2"6) 2"6
2@4=∑ (
232"8
) 2"82@4
1. � �O
= P ( � �9
) �9 �O
1
.
Chain rule of partial differential
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Questions?