So the topic for today is we
have a system like the kind we
have been studying,
but there is now a difference.
A system of first order
differential equations,
just two of them.
It is an autonomous system
meaning, of course,
that there is no t explicitly
on the right-hand side.
But what makes this different,
now, is that it is nonlinear.
In other words,
the functions on the right-hand
side are no longer simple things
like ax plus by,
cx plus dy.
Those are the kind we have been
studying.
But we are going to allow them
to have quadratic terms,
sines, cosines,
different stuff there that are
not linear functions anymore.
And the problem is,
if it's a linear system you
know how to get a sketch of its
trajectories without using the
computer by using eigenlines.
You were very good at that on
the exam on Friday.
Most of you could do that very
well.
But what do you do if you have
a nonlinear system?
The problem is to sketch its
trajectories.
In general, there are not
analytic formulas for the
solutions to nonlinear systems
like that.
There are only computer-drawn
things.
But sometimes you have to get
qualitative information,
a quick idea of how the
trajectories look.
And, especially on Friday,
I will give you examples of
stuff that you can do that the
computer cannot do very well at
all.
Okay, so the problem is to
sketch those trajectories.
Now, what I am going to do is
--
The way I will give the lecture
is, this is the general problem.
We have to do two things sort
of simultaneously.
I will give a general
explanation using x and y,
but then, as we do each step of
the process and talk about it in
general, I would like to carry
it out on a specific example.
And so we will do it with a
specific example.
The example I am going to carry
out is that of the nonlinear
pendulum.
I am using this because it
illustrates virtually
everything.
And, in addition,
it has the great advantage
that, since we know how a
pendulum swings,
we will be able to,
when we get the answer,
verify it and,
at various stages of the
procedure, verify that the
mathematics is,
in fact, in agreement with our
physical intuition.
It is going to be a lightly
damped pendulum because I am
going to have to put in numbers
in order to do the calculations.
And that seems like a good case
which illustrates several types
of behavior.
Let's first of all,
before we talk in general,
remind you of the pendulum.
The pendulum I am talking about
has the vertex from which it
swings.
This is a rigid rod.
It is not one of these
string-type pendulums.
There is a mass here.
The rigid rod is of length l.
And so it swings in a circular
orbit like that back and forth
in a circle.
And let's put in the vertical
distance, the vertical position
rather.
And now, as variables,
of course normally we use
neutral variables like x and y.
But here x and y are not
relevant variables to describing
the way the mass moves.
The obviously relevant variable
is theta, this angle.
Now, I am taking it in the
positive direction.
Here theta is zero.
As it swings,
theta becomes positive.
Over here, when it is
horizontal, theta has the value
pi over two and then so on it
goes.
Values here correspond to
negative values of theta.
That is how it swings.
Now, just to remind you of the
equation that this satisfies,
it satisfies F equals ma,
rather ma equals F.
Now, the acceleration is along
the circular path.
And that is different from the
angular acceleration.
I have to put in the factor of
the length.
You had that a lot in 8.01 so I
am simply going to write it
down.
It is the mass.
Therefore, the linear
acceleration along the circular
path is equal to the angular
acceleration times l.
It is l times theta prime
prime, or double dot if you
prefer.
And so this much of it is the
acceleration vector.
Now, once the force is acting
on it, well, there is a force of
gravity which is pulling it
straight down.
But, of course,
that is not the relevant force.
I am interested in the force
that acts along that circular
line.
And that will not be all of the
pink line but only its component
in that direction.
And the component,
I fill out the little right
triangle.
And then the way to get the
component in that direction,
the vertical pink part has the
magnitude mg.
But, since I only want this
part, I have to multiply by the
sign of this angle.
Now, sometimes I have given on
a diagnostic test to students
when they enter to what angle is
that?
But, of course,
anybody can guess it must be
theta.
Otherwise, why would he be
asking it?
So this is still the angle
theta.
You can prove these two
triangles are similar.
One of them I haven't even
written in, but it would be the
right triangle whose leg is
perpendicular to it.
So the right angle is here.
If that is theta then the
length of this small pink line
is mg times the sine of theta.
That is the force due gravity.
It is mg sine theta.
Except in what direction is it?
It is acting in the negative
direction.
This is theta increasing.
This is the opposite direction,
so I should put a negative sign
in front of it.
But that is not the only force.
There is also a damping force
that goes with a velocity.
And that also occurs if the
angular velocity is positive,
the angle theta is increasing,
in other words,
the damping force resists that.
It is opposite to the velocity.
So the velocity is going to be
l times theta prime.
There is my velocity v.
Linear velocity,
not angular velocity.
And so this is going to be a
negative times some constant
times that c1.
Now, that is the equation.
But let's make it look a little
better by getting rid of some of
these constants.
If I write it out this way and
put everything on the left-hand
side, the way it is usually done
in writing a second order
differential equation.
Theta I am going to divide
through by ml and put everything
on the left-hand side and in the
right order.
Next should come the theta
prime term.
And so that is going to be c1l
divided by ml,
so that is c1 over m.
The l's cancel out.
And, finally,
the last term on the right,
I will move this over to the
left, but remember everything is
being divided by ml,
so the m's cancel out,
and it is plus g over l times
the sine of theta.
That is our differential
equation.
But let's make it look still a
little bit better by lumping
these constants and giving them
new names.
It is going to be finally theta
double prime.
I will simply call this thing
the damping constant.
I will lump those two together
into single damping constant.
And then g over l,
I will lump those together,
too.
And we usually call that k.
It is k sine theta.
Now, this is a second-order
different equation,
but it is not linear.
If this were a month and a half
ago and I said solve that,
you would stare at me.
But, anyway,
you couldn't solve that.
And nobody can,
in some sense.
It is a nonlinear equation.
It doesn't have any exact
solution.
The only thing you could do is
look for a solution in infinite
series or something like that.
Well, what do you do?
You throw it on the computer,
that is the easy answer,
but what does the computer do?
Well, the first thing the
computer does is turns it into a
system because the computer is
going to use numerical methods
to solve it.
But only those methods,
the formulas it uses,
Euler or modified or improved
Euler or the Runge-Cutta method,
they are always expressed not
for single higher-order
equations, but instead they
always assume that the equation
has been converted to a first
order system.
Let's do that for the computer,
even though it will do it
itself if nobody tells it not
to.
Theta prime is equal to,
now I have to figure out what
new variable to introduce.
Normally we use x prime and
call that y.
That really doesn't seem to be
very suitable here.
But what do the physicists call
it?
This is the angular velocity.
And the standard designation
for that is omega.
Two Greek letters.
I told you this was going to be
hard.
Omega prime equals what?
Well, omega prime equals,
now you do it in the standard
way, you convert the system,
but remember you have to put
the theta first.
So it is minus k sine theta.
The theta first and then the
omega term first.
So minus c times omega,
minus c theta prime,
but theta prime is,
in real life,
omega.
And now we have our acceptable
system.
The only problem is I have not
put in any numbers yet.
The numbers I am going to put
in will make it lightly damped.
I am going to give c,
think of it here,
this is the damping,
and this is the stuff
representing,
well, if I want to make it
lightly damped all I am saying
is that c should be small
compared with k,
but it doesn't have to be very
small.
I am going to take c equal one
and k equal two,
and that will make it
lightly enough damped.
This is the lightly damped
value, values which give
underdamping.
In other words,
they are going to allow the
pendulum to swing back and forth
instead of strictly going ug and
ending up there.
Finally, therefore,
the system that we are going to
calculate is where theta prime
equals omega and omega prime
equals negative two sine theta
minus omega.
And now what do we do with
that?
There is our example.
That is our system that
represents a pendulum swinging
back and forth,
damped away.
And now let's go back to the
general theory.
And, in general,
if you have a nonlinear system,
how do you go about analyzing
it?
The first step is to find the
simplest possible solutions,
solutions that you hope can be
found by inspection.
Now, what would they be?
They are the solutions that
consist of a single point.
How could a solution be a
single point?
Well, like the origin for a
linear system,
those points which form
solutions all by themselves are
called the critical points.
I am looking for the critical
points of the system.
That is the first step.
The definition is a critical
point x zero,
y zero.
For that to be a critical point
means that it makes the
right-hand side zero.
The f is zero there,
and the g is zero there.
See the significance of that?
If you have such a point,
let's say there is a critical
point, what is the velocity
field at that point?
Well, it is given by the
vectors on the right-hand side,
but the components are zero.
That means, at this point the
velocity vector is zero.
Well, that means if a solution
starts there,
you put the mouse there and
tell it to move,
where do you go?
It has no reason to go anywhere
since the velocity vector is
zero there.
So it sits there for all time.
And indeed it solves the
system, doesn't it?
It makes the right-hand side
zero and it makes the left-hand
side zero because x equals x
zero, y equals y zero for
all time.
If that is true for all time it
sits there then the derivatives,
with respect to time are zero,
so the left-hand sides are
zero, the right-hand sides are
zero and everybody is happy.
Well, these are great points.
How do I find them?
Well, by looking for points
that make these two functions
zero.
I find them by solving
simultaneously the equations f
of (x, y) equals zero and g of
(x, y) equals zero.
A pair of equations.
But the trouble is those are
not linear equations.
Linear equations you know how
to solve, but they are not
linear equations.
They are nonlinear equations
that you don't know how to
solve.
And, to some extent,
nobody else does either.
There are very fat books in the
library whose topic is how to
solve just a pair of equations,
f of (x, y) equals zero,
g of (x, y) equals zero.
And it is quite a hard problem.
It is even a hard problem by
computer.
Because, if you know
approximately where the solution
is going to be,
you can make up the little
screen and then the computer
will find it for you.
Or, even without a screen,
it will calculate it by
Newton's method or something
else, it will zero in.
The problem is,
if you don't know in advance
roughly where the critical point
is that you are looking for,
there are a lot of numbers.
They go to infinity that way
and infinity that way.
In general, it is almost an
impossible problem.
The only thing that makes it
possible is that these problems
always come from the real world
and one has some physical
feeling, one hopes,
for where the critical point
is.
I am going to assume breezily
and cheerily we can solve those.
And I am only going to give you
examples where it is possible to
solve them.
But even there,
you have to watch out.
There is a certain trickiness
that will be talked about in the
recitations tomorrow.
Okay, so we found the critical
points.
Let's do it for our example.
Let's find the critical point.
What is the pair of equations
we have to solve?
We have to solve the equations
omega equals zero,
minus two sine theta minus
omega equals zero.
Now, it is not always this
easy.
But the solution is omega is
zero.
If omega is zero,
then sine theta is zero,
and sine theta is zero at the
integral multiples of pi.
The critical points are omega
is always zero and theta is
zero, or it could be plus or
minus pi, plus or minus two pi
and so on.
In other words,
there are an infinity of
critical points.
That seems a little
discouraging.
On the other hand,
there are really only two.
There are really physically
only two because omega equals
zero means the mass is not
moving.
The angular velocity is zero,
so it is only the theta
position which is changing.
Now, what are the possible
theta positions?
Well, here is our nonlinear
pendulum.
Here is the critical point,
theta equals zero,
omega equals zero.
Theta equals zero means the rod
is vertical.
Omega equals zero means that it
is not moving,
despite the fact that it is
moving.
Theoretically it is not moving.
Now, what is the other one?
Well, there is theta equals pi.
Theta is now,
starting from zero and
increasing, I hope,
through positive theta.
And when it gets to pi,
it is sticking straight up in
the air.
And so the claim is that
another critical point is theta
equals pi and omega equals zero.
In other words,
if it gets to this position,
it starts out in this position
and stays there for all time,
as you see.
[LAUGHTER] But my point is what
about negative pi?
That is the same as pi.
Two pi is the same as zero.
So physically there really are
only two critical points,
this one and that one.
And they obviously have
something very different about
them.
This critical point is stable.
If I start near there,
I approach that critical point
in infinite time.
This one, if I start near
there, I do not stay near there.
I always leave it.
Of the two critical points,
physically it is clear that the
critical point is zero,
zero and the other guys that
look like it,
two pi zero and so on is a
stable critical point.
Whereas, pi zero,
when theta is sticking straight
up in the air,
is unstable.
Now, of course,
we will want to see that
mathematically also,
but basically there are just
physically two point.
There are just two critical
points.
Well, that raises the question
what about all the others?
As you will see,
we have to have those.
They are an essential part of
the problem.
They are not just redundant
baggage that is trailing along.
They are really important.
But you will see that when we
talk about finally how the
trajectories look and how the
solutions look.
Now what do we do?
Well, we found the critical
points, and now the work begins.
Virtually all the work is in
this next step.
What do we do?
Step two.
I can only describe it in
general terms,
but here is what you do.
For each critical point x zero,
y zero, a procedure that has to
be done at each one,
you linearize the system near
that point.
In other words,
you may find a linear system,
the good kind,
the kind you know about,
which is a good approximation
to the nonlinear system at that
critical point.
Plot the trajectories of this
linearized system.
And you do that near the
critical point.
How do you plot the
trajectories?
Well, that you knew how to do
on Friday so I am assuming you
still know how to do it on
Monday.
In other words,
if the system is linear you
know how to plot the
trajectories of it by
calculating eigenvalues and
eigenvectors and maybe the
direction of motion if it is a
spiral.
I will give you a couple of
examples of that when we work
out the pendulum.
But, on the other hand,
how do I line arise a system?
Well, there are two methods.
There is one method the book
gives you, which by and large I
do not want you to use,
although I will give you an
example of it now.
I want you to use another
method because it is much
faster.
Especially if you have to
handle several critical points
it is much, much faster.
Let's first carry this out on
an easy case,
and then I will show you how to
do it in general.
Just this once I will use the
book's method because I think it
is the method which would
naturally occur to you.
Let's linearize this example at
the point zero,
zero.
What should be the linearized
system?
In other words,
it's only the nonlinear terms I
have to worry about.
Well, the minus omega is fine.
It is that stupid sine theta
that I don't like.
But if theta is small,
in other words,
if I stay near zero,
I could replace sine theta by
theta.
The linearized system is minus
two.
You replace sine theta by
theta, since sine theta is
approximately theta if theta is
small, if theta is near zero.
It is the first term of its
Taylor series you can think of,
or it's just the linear
approximation starts out sine
theta equals theta.
That is it.
Or, you draw a picture.
I don't know.
There are a millions of ways to
do it.
So we have it.
Now what do I do?
Okay, now we will plot that.
The matrix, let's do our little
routine, in other words.
I am writing right to left for
no reason.
The matrix is,
now I am just going to make
marks on a board the way you did
on your exam,
zero, one.
[LAUGHTER] I don't know what I
am doing, but you know.
Negative two,
negative one,
and then I write down the
eigen-whatchamacallits.
Lambda squared,
plus lambda,
minus the trace.
The determinant is minus,
minus two, so it is plus two
equals zero.
And then, since it doesn't
occur to me how to factor this,
I will use the quadratic
formula.
It is negative one plus or
minus the square root of,
b squared minus 4ac,
minus seven.
Complex.
That means it is going to be a
spiral.
I am going to get a spiral.
Will it be a source or a sink
since they are complex roots?
Complex eigenvalues give a
spiral.
A source or a sink?
I tell that from the sine of
the real part.
The real part is negative
one-half.
Therefore, the amplitude is
shrinking like e to the minus t
over two.
And, therefore,
the spiral is coming into the
origin.
It is a spiral sink since
lambda equals minus one-half
plus some number times i.
Spiral sink.
And the other thing to
determine is its direction of
motion, which will be what?
I determine its direction of
motion by putting in a single
vector from the velocity field.
Here it is.
The vector at one,
zero will be the
same as the first column of the
matrix.
So that is zero,
negative two.
Here is a vector from the
velocity field,
and that shows that the motion
is clockwise and is spiraling
into the origin.
That is a picture,
therefore, at the origin of how
that looks.
Now, it is of the utmost
importance for your
understanding of what comes now
that you understand in what
sense this picture corresponds
to the physical behavior of the
pendulum.
Let's start it over here.
What is it doing?
That means that theta is some
number like one,
for example.
Let's make it smaller.
Let's say a little bit.
And this is the omega access.
If it starts over here that
means the angular velocity is
zero and theta is a small
positive number.
Theta is a small positive
number.
The angular velocity is zero.
It's velocity zero,
theta small and positive.
I release it and it does that.
What does this have to do with
the spiral?
Well, the spiral is exactly a
mathematical picture of this
motion.
What happens?
Theta starts to decrease.
And the angular velocity
increases but in the negative
direction.
This is negative angular
velocity.
Theta is decreasing.
The angular velocity gets
bigger and bigger.
And it is biggest,
most negative when theta is
zero.
It has reached the vertical
position is when the angular
velocity is biggest.
It continues then.
Theta gets negative,
but the angular velocity then
decreases to zero.
Now the angular velocity is
zero and theta is at its most
negative, and then it reverses.
Angular velocity gets positive
as theta increases again,
and so on.
These represent the successive
swings back and forth.
Notice the fact that it is
damped is reflected in the fact
that each successive swing,
the biggest that theta gets is
a little less than it was
before.
In other words,
this point is not quite as far
out as that one.
And this one isn't as far out
as that one.
In other words,
it is spiraling in.
Well, I hope that is clear
because we now have to go to the
next critical point.
And now we have a little
problem.
If I want to do the next
critical point,
so what I want to do now is,
in other words,
I want to linearize at the
point pi zero where theta is pi
and the thing is sticking up in
the air.
The question is,
how am I going to do that?
This trick of replacing sine
theta by theta,
that doesn't work at pi.
That works at zero.
Now we have to go to the next
step of the method.
The way to do this,
in general, as you will read in
the notes because,
as I say, this is not in the
book, is to calculate the
Jacobian.
I mean the Jacobian matrix.
The Jacobian is the
determinant.
I mean, before you put the two
bars down and made a
determinant, you called it just
the Jacobian matrix.
And the formula for it is,
it is calculated from f and g.
The top line is the partial of
f with respect to x and y,
and the bottom line is the
partial of g with respect to x
and y.
So that is the Jacobian matrix.
I hope I get a chance at the
end of the period to explain to
you why, but I am most anxious
right now to at least get you
familiar with the algorithm,
how to do it.
The notes describe the y of it,
if we don't get a chance to get
to it, but I hope we will.
What do you do?
The Jacobian matrix.
You calculate it at the point x
zero, y zero.
I will indicate that by putting
a subscript zero on it.
This means without the
subscript zero it is the
Jacobian matrix calculated out
of those four partial
derivatives.
When I put a subscript zero,
I mean I evaluated it at the
critical point by plugging in
each entry as a function of x
and y.
You plug in for x equals 
x zero, y equals y zero,
and you get a numerical
matrix.
That is the matrix which is the
matrix of the linearized system.
This is the matrix of the
linearized system.
Trust me, it is.
Now, since I don't expect you
to trust me, let's calculate it.
Here, we got the matrix another
way, by this procedure of saying
sine theta is theta-- What would
we have gotten if we had done it
instead by the linearized
system?
Let's do it that way.
Let's do it via the Jacobian.
I need to know the Jacobian of
the system, which I have
conveniently covered up.
There is the system.
The Jacobian matrix is what?
The top line,
I take the partial derivative
of omega first with respect to
theta and then with respect to
omega.
I then take the second line on
the right-hand side.
I take its partial with respect
to theta first.
That is negative two cosine
theta.
And, thinking ahead,
I erase the one and move it
over a little bit.
And what is the partial of that
thing with respect to omega?
It is negative one.
Does everyone see how I
calculated that Jacobian matrix?
And now I want to evaluate it.
Let's do our old case first.
At zero, zero what 
would this have
amounted to?
This would have given me zero,
one.
The cosine of theta at zero is
one, so this is negative two,
negative one.
I'm screwed.
[LAUGHTER]
That is the same as that.
Now you see it,
now you don't.
We got our old answer back.
That should give us enough
confidence to use it in the new
case, where I don't have an old
answer to compare it with.
What is it going to be at pi,
zero?
The answer is J zero is
now going to be --
Well, everything is the same.
Zero, one, negative one.
And here cosine of pi is
negative one,
so negative two times negative
one is two.
Everything is the same,
except there is a two there now
instead of negative two.
Lambda squared plus lambda,
the determinant,
is now negative two.
And this factors into lambda
plus two times 
lambda minus one.
So lambda equals one.
The corresponding eigenvector.
I subtract one here,
so the equation is minus a1
plus a2 is zero.
The solution is one,
one, e to the t.
And for the other one,
it's lambda is equal to
negative two.
This is the sort of stuff you
can do, so I am doing it fast.
Zero minus negative two is two.
So the equation is 2a1 plus a2
equals zero.
And the solution is now,
I give a1 the value one,
a2 will be negative two,
and that is times e to the
minus 2t.
Well, what does the thing then
actually look like?
What I am now going to do is,
I drew a picture before,
that spiral picture we had
before of the way the thing
looked at the point zero,
zero.
So at the point pi,
zero how does it
look, now?
Well, it looks like the origin,
but I am thinking of it really
as the point pi,
zero.
In other words,
I am thinking of a linear
variable change sliding along
the axis so that the point pi,
zero now looks like
the origin.
If I do that then those two
basic solutions,
there is the one,
one solution which
is going out that way.
And it is going out this way.
But the other guy is coming in
along the vector one,
negative two.
So one, negative two looks like
this.
This guy is coming in at a
somewhat sharper angle,
coming in because it is e to
the negative 2t.
And we recognize this,
of course, as a saddle.
And I would complete the
trajectories by putting in some
of the typical saddle lines like
that.
Now, I say that,
too, gives a picture of what is
happening to the pendulum near
that point.
Let's, for example,
look here.
What is happening here?
This is theta,
or really it is theta minus pi,
is this axis.
In other words,
this will be zero.
When theta is pi this will
correspond to the point zero.
Here is omega.
What is theta doing?
Starting up there this
represents a value of theta a
little bit less than pi,
a little bit to the negative.
A little bit less than pi.
Here is pi, so a little bit
less than pi is over here.
A little bit less than pi.
A little bit less.
And omega is zero.
What happened?
Theta started decreasing ever
more rapidly so that the omega
was zero here,
now omega is negative and gets
much more negative.
In other words,
both theta decreases from that
point and omega decreases also.
What happened here?
Here, theta is a little bit
more than pi.
Now it is a little bit more
than pi.
Theta now increases until it
gets to 2pi and then oscillates
around 2pi.
So theta increases.
And omega increases,
too, because the angular
velocity started at zero but,
as theta gets more positive,
omega gets positive,
too, because theta is
increasing.
So omega increases and theta
increases and it goes off like
that.
Well, the final step is to put
them all together to be the big
picture.
Here we are for three,
let's say, the big picture.
Plot trajectories around each
critical point and then add
some.
It's that last step that can
cause you a little grief,
but we will see how it works
out.
Add some more,
according to your best
judgment.
Let's make a big picture now of
our pendulum the way it
apparently ought to look.
Nice big axis since we are
going to accommodate a lot of
critical points here.
Let's put in some critical
points.
Here is the origin.
And now here is the one at pi,
let's say, here is one at 2pi.
I am going to add some of these
others, 3pi, 4pi.
I won't in their values.
You can figure out what I mean.
Zero here.
And then here it will be
negative pi, and here negative
2pi.
I guess I can stop there.
That is the theta axis,
and here is the omega axis.
And now, at each one of these,
I stay nearby and I draw the
linear trajectories,
the trajectories of the
corresponding linearized system.
We decided here that the spiral
went clockwise.
Now, this point is physically,
of course, the same as that
one.
But mathematically,
the Jacobian matrix is the same
also because if theta is 2pi the
cosine of 2pi is also one.
And this is the same matrix.
So the analysis is identical.
And, therefore,
this point will also correspond
to a counterclockwise spiral,
as will this one.
I am sorry, a clockwise spiral.
Here, too, all of these points
are the same.
The behavior near them,
clockwise spirals everywhere.
How about the other ones?
Well, the other ones correspond
to these saddles,
so let's draw them efficiently
by doing the same thing on every
one, mass production of saddles.
There.
And these guys go out.
And the other guys come in,
etc.
And so here we have a little
bit there, a little here,
here, there,
everywhere, etc.
Now what?
Now you pray for inspiration.
And what you have to do is add
trajectories that are compatible
with the ones you have.
Let's start with this guy.
Where is it going?
Well, a trajectory either goes
off to infinity,
but generally they get trapped
around critical points.
This guy must be surely doing
this.
How about this one?
Yeah, sure.
How about this one?
Why not?
How about that one?
Yeah.
But notice you are in trouble
when two arrows you want to put
in are near each other and going
in opposite directions.
That you cannot have.
Continuity forbids it.
But notice if I,
for example,
had gotten these eigenlines
wrong, if I made this come in
and those go out because I made
a simple error in drawing the
thing, I would have said but I
cannot draw this picture because
this spiral wants to go that way
but this, right next to it,
wants to go the other way.
That is the way you would know
if you made a mistake.
If you didn't make a mistake
you won't have any trouble
filling these things out.
The directions of motions of
the spirals, everything will be
compatible.
Okay.
What is this guy doing?
Oh, well, it must be joining up
with that.
How about this one?
Well, it must be coming back
there.
How about this one?
Well, trajectories cannot
cross.
This guy cannot cross so it
must be doing this.
All right.
What is that trajectory?
Starts zero.
Omega, on the other hand,
is big and positive.
Omega big and positive.
[LAUGHTER] I am scared.
Omega starts.
Theta is zero.
Omega big and positive.
It went around,
slowed up, but continued beyond
pi.
And, in fact,
went too far.
It continued to go here and
then finally wound around that
one.
Now do you see why we had to
have all the critical points?
You have to have all the
critical points.
And not just the two physicals
ones because the other critical
points are necessary to describe
a complicated motion that goes
round and round and round until
finally it crashes.
You are going to practice
drawing these pictures and
interpreting them in recitation
tomorrow.
