8.01x - Lect 3 - Vectors - Dot Products - Cross Products - 3D Kinematics
Summary
TLDRIn this educational video, Professor Lewin explores the fundamentals of vectors, crucial for understanding physics. He explains scalars, vectors, their addition, and the difference between them. The lecture delves into vector decomposition, the dot and cross products, and their applications in physics. With a practical demonstration involving a moving golf ball, he illustrates the independent behavior of motion in different dimensions, emphasizing the power of vector analysis in simplifying complex physical phenomena.
Takeaways
- 📚 The lecture introduces the concept of scalars and vectors in physics, explaining that scalars like mass, temperature, and speed are described by a single number, while vectors like velocity and acceleration require both magnitude and direction.
- 📝 Vectors are represented by arrows to indicate direction and can be manipulated using the 'head-tail' technique or the 'parallelogram method' for addition.
- 🔍 The concept of negative vectors is explored, showing that subtracting a vector from itself results in zero, and that a negative vector is the original vector flipped 180 degrees.
- ⚖️ Vector subtraction is explained as being equivalent to adding a negative vector, which can be visualized using both the head-tail technique and the parallelogram technique.
- 📊 The magnitude of a vector is calculated as the square root of the sum of the squares of its components, and the angles with the axes (theta and phi) are used to decompose a vector into its components.
- 📐 Unit vectors are introduced as vectors with a magnitude of one that point in the direction of the positive axes, and are used to express vectors in terms of their components along the axes.
- ✖️ The dot product of two vectors is defined as a scalar resulting from the sum of the products of their corresponding components or as the product of the magnitudes and the cosine of the angle between them.
- ✂️ The cross product, or vector product, is introduced as a method to multiply vectors resulting in another vector perpendicular to the plane containing the original vectors, with direction determined by the right-hand rule.
- 🔄 The motion of a particle in three-dimensional space is described by decomposing its position, velocity, and acceleration into components along the x, y, and z axes, allowing for the analysis of complex motion as a combination of independent one-dimensional motions.
- 🚀 The independence of motion in the x and y directions is demonstrated through projectile motion, where the horizontal velocity remains constant while the vertical motion is influenced by gravity.
- 🎯 An experiment is proposed to launch a golf ball with a horizontal velocity matching that of a moving cart to illustrate the principle that the horizontal motion is independent of the vertical motion influenced by gravity.
Q & A
What is the main topic discussed in the provided script?
-The main topic discussed in the script is the concept of vectors in physics, including their addition, subtraction, and multiplication (dot and cross products), as well as their applications in motion and forces.
What is a scalar in physics?
-A scalar in physics is a quantity that is determined by a single number and has no direction, such as mass, temperature, and speed.
How is a vector represented?
-A vector is represented by an arrow, where the length of the arrow indicates the magnitude and the direction of the arrow indicates the direction of the vector.
What are the two common methods for adding vectors?
-The two common methods for adding vectors are the 'head-tail' technique and the 'parallelogram method'.
What is the significance of the negative vector in the context of vector subtraction?
-The negative vector is significant in vector subtraction because it represents the vector that, when added to a given vector, results in a zero vector. It is essentially the original vector flipped over 180 degrees.
What is the dot product of two vectors?
-The dot product of two vectors is a scalar value obtained by multiplying corresponding components of the vectors and summing the results. It can also be represented as the product of the magnitudes of the two vectors and the cosine of the angle between them.
What is the cross product of two vectors?
-The cross product of two vectors results in a vector that is perpendicular to both of the original vectors. It is calculated using a determinant involving the unit vectors and components of the original vectors.
How does the magnitude of a vector relate to its components?
-The magnitude of a vector is the square root of the sum of the squares of its components along each axis (Ax^2 + Ay^2 + Az^2)^(1/2).
What is the physical interpretation of the dot product being zero?
-A dot product of zero indicates that the two vectors are perpendicular to each other, as the cosine of the angle between them (90 degrees) is zero.
How can the motion of a particle in three-dimensional space be decomposed?
-The motion of a particle in three-dimensional space can be decomposed into three independent one-dimensional motions along the x, y, and z axes, each with its own position, velocity, and acceleration components.
What is the practical demonstration mentioned in the script to illustrate the independent behavior of motion in the x and y directions?
-The practical demonstration involves shooting a golf ball with a horizontal velocity that matches the motion of a moving cart, showing that the ball maintains a constant horizontal velocity while the cart moves underneath it.
Outlines
📚 Introduction to Scalars and Vectors
The script begins by introducing the concept of scalars and vectors in physics. Scalars are quantities defined by a single number, such as mass, temperature, and speed. Vectors, on the other hand, require both magnitude and direction, such as velocity and acceleration. The script explains that vectors are represented by arrows, and their addition can be visualized using the 'head-tail' technique or the 'parallelogram method'. The importance of understanding vectors is emphasized as it is fundamental to the study of physics.
🔍 Vector Addition and Scalar Multiplication
This paragraph delves deeper into vector operations, specifically the addition and subtraction of vectors. It clarifies that the sum of vectors can vary greatly depending on their direction relative to each other, contrasting this with the straightforward nature of scalar addition. The concept of vector decomposition is introduced, where a single vector in three-dimensional space can be broken down into its x, y, and z components. The paragraph also introduces unit vectors and their role in representing the components of a vector in a given direction.
📐 Understanding Vector Projections and Magnitudes
The script discusses the process of projecting a vector onto the axes in a three-dimensional space and using these projections to decompose a vector into its components. It explains how to calculate the magnitude of a vector by taking the square root of the sum of the squares of its components. The paragraph also covers how to determine the angles associated with a vector in three-dimensional space and how these angles relate to the vector's components.
🤔 Exploring Vector Multiplication
The script introduces the concept of vector multiplication, which is more complex than addition or subtraction. Two types of multiplication are discussed: the dot product (or scalar product) and the cross product. The dot product is a scalar value obtained by multiplying corresponding components of two vectors and summing the results. The paragraph also presents an alternative method for calculating the dot product using the magnitudes of the vectors and the cosine of the angle between them.
🔄 The Dot Product and Its Implications
This paragraph expands on the dot product, explaining its geometric interpretation as the product of the magnitudes of two vectors and the cosine of the angle between them. It discusses the implications of the dot product for determining the angle between vectors and its role in physics, such as in calculating work done by a force. The script provides examples to illustrate how the dot product is calculated in different scenarios.
🌐 The Cross Product and Its Geometric Interpretation
The script introduces the cross product, a vector multiplication that results in a vector perpendicular to the plane containing the two original vectors. It presents a method for calculating the cross product using a determinant with unit vectors and components of the original vectors. The paragraph also offers a geometric interpretation of the cross product, relating it to the sine of the angle between the vectors and emphasizing the importance of using a right-handed coordinate system.
🎯 Direction of the Cross Product and Right-Handed System
This paragraph focuses on determining the direction of the cross product, explaining the right-hand rule for finding the direction of the resulting vector. It emphasizes the importance of using a right-handed coordinate system and the consequences of not doing so. The script uses the analogy of a corkscrew to help visualize the direction of the cross product and discusses the relationship between the cross product and physical concepts such as torque and angular momentum.
🚀 Equations of Motion for a Particle in 3D Space
The script presents the equations of motion for a particle moving in three-dimensional space. It breaks down the position, velocity, and acceleration of the particle into their x, y, and z components, demonstrating how to express these quantities as functions of time. The paragraph shows how to decompose a complex three-dimensional motion into simpler, independent one-dimensional motions along each axis.
🏐 Projectile Motion Decomposition
This paragraph applies the concept of motion decomposition to the example of projectile motion, such as throwing a ball at an angle. It explains how to calculate the initial velocity components in the x and y directions and how these components evolve over time. The script highlights that the horizontal motion (x-direction) maintains a constant velocity, while the vertical motion (y-direction) is affected by gravity, resulting in a parabolic trajectory.
🎾 Demonstrating Independent Horizontal Motion
The script concludes with a demonstration of the independent horizontal motion in projectile motion. It describes an experiment where a golf ball is shot with a horizontal velocity that matches the velocity of a moving cart, illustrating that the ball can be caught by the cart if the initial conditions are met. The paragraph emphasizes the superposition of the horizontal and vertical motions to describe the actual trajectory of the projectile.
Mindmap
Keywords
💡Scalars
💡Vectors
💡Head-Tail Technique
💡Parallelogram Method
💡Negative Vector
💡Decomposition
💡Unit Vectors
💡Dot Product
💡Cross Product
💡Right-Handed Coordinate System
💡Projectile Motion
Highlights
Introduction to the concept of scalars and vectors in physics, emphasizing the unique determination by a single number for scalars and the need for both magnitude and direction for vectors.
Explanation of vector representation through arrows, illustrating direction and magnitude.
Demonstration of vector addition using the 'head-tail' technique and the 'parallelogram method'.
Clarification on the commutative property of vector addition, showing A + B is equivalent to B + A.
Introduction to the concept of negative vectors and their role in vector subtraction.
Illustration of vector subtraction using both head-tail and parallelogram techniques.
Discussion on the range of possible magnitudes for the sum of two vectors based on their direction.
Introduction to vector decomposition, a key concept for advanced physics applications.
Projection of a three-dimensional vector onto the x, y, and z axes, and the introduction of unit vectors.
Expression of a vector in terms of its components along the axes using unit vectors.
Calculation of a vector's magnitude from its components.
Introduction to the dot product, a method of multiplying vectors resulting in a scalar.
Geometric interpretation of the dot product using the angle between two vectors.
Introduction to the cross product, a vector multiplication resulting in a vector perpendicular to both original vectors.
Geometric interpretation of the cross product direction using the right-hand rule.
Equations for the motion of a particle in three-dimensional space, decomposing motion into components along each axis.
Demonstration of constant horizontal velocity in projectile motion due to the independence of x and y motion.
Experimental demonstration of the independence of horizontal and vertical motion using a moving cart and a projectile.
Transcripts
The bad news today is that there will be quite a bit of math.
But the good news is that we will only do it once
and it will only take something like half-hour.
There are quantities in physics
which are determined uniquely by one number.
Mass is one of them.
Temperature is one of them.
Speed is one of them.
We call those scalars.
There are others where you need more than one number
for instance, on a one- dimensional motion, velocity
it has a certain magnitude-- that's the speed--
but you also have to know
whether it goes this way or that way.
So there has to be a direction.
Velocity is a vector and acceleration is a vector
and today we're going to learn how to work with these vectors.
A vector has a length and a vector has a direction
and that's why we actually represent it by an arrow.
We all have seen... this is a vector.
Remember this-- this is a vector.
If you look at the vector head-on, you see a dot.
If you look at the vector from behind, you see a cross.
This is a vector
and that will be our representation of vectors.
Imagine that I am standing on the table in 26.100.
This is the table and I am standing, say, at point O
and I move along a straight line from O to point P
so I move like so.
That's why I am on the table
and that's where you will see me when you look from 26.100.
It just so happens
that someone is also going to move the table--
in that same amount of time-- from here to there.
So that means that the table will have moved down
and so my point P will have moved down exactly the same way
and so you will see me now at point S.
You will see me at point S in 26.100
although I am still standing
at the same location on the table.
The table has moved.
This is now the position of the table.
See, the whole table has shifted.
Now, if these two motions take place simultaneously
then what you will see from where you are sitting...
you will see me move in 26.100 from O straight line to S
and this holds the secret behind the adding of vectors.
We say here that the vector OS-- we'll put an arrow over it--
is the vector OP, with an arrow over it, plus PS.
This defines how we add vectors.
There are various ways that you can add vectors.
Suppose I have here vector A and I have here vector B.
Then you can do it this way
which I call the "head-tail" technique.
I take B and I bring it to the head of A.
So this is B, this is a vector
and then the net result is A plus B.
This vector C equals A plus B.
That's one way of doing it.
It doesn't matter whether you take B...
the tail of B to the head of A
or whether you take the tail of A and bring it to the head of B.
You will get the same result.
There's another way you can do it
and I call that "the parallelogram method."
Here you have A.
You bring the two tails together, so here is B now
so the tails are touching
and now you complete this parallelogram.
And now this vector C is the same sum vector
that you have here, whichever way you prefer.
You see immediately
that A plus B is the same as B plus A.
There is no difference.
What is the meaning of a negative vector?
Well, A minus A equals zero--
vector A subtract from vector A equals zero.
So here is vector A.
So which vector do I have to add to get zero?
I have to add minus A.
Well, if you use the head-tail technique...
This is A.
You have to add this vector to have zero
so this is minus A
and so minus A is nothing but the same as A
but flipped over 180 degrees.
We'll use that very often.
And that brings us to the point of subtraction of vectors.
How do we subtract vectors?
So A minus B equals C.
Here we have vector A and here we have--
let me write this down here-- and here we have vector B.
One way to look at this is the following.
You can say A minus B is A plus minus B
and we know how to add vectors and we know what minus B is.
Minus B is the same vector but flipped over
so we put here minus B
and so this vector now here equals A minus B.
Here's vector C, here's A minus B.
And, of course, you can do it in different ways.
You can also think of it as A plus... as C plus B is A.
Right? You can say you can bring this to the other side.
You can say C plus B is A, C plus B is A.
In other words, which vector do I have to add to B to get A?
And then you have the parallelogram technique again.
There are many ways you can do it.
The head-tail technique
is perhaps the easiest and the safest.
So you can add a countless number of vectors
one plus the other, and the next one
and you finally have the sum of five or six or seven vectors
which, then, can be represented by only one.
When you add scalars, for instance, five and four
then there is only one answer, that is nine.
Five plus four is nine.
Suppose you have two vectors.
You have no information on their direction
but you do know that the magnitude of one is four
and the magnitude of the other is five.
That's all you know.
Then the magnitude of the sum vector could be nine
if they are both in the same direction-- that's the maximum--
or it could be one, if they are in opposite directions.
So then you have a whole range of possibilities
because you do not know the direction.
So the adding and the subtraction of vectors
is way more complicated than just scalars.
As we have seen, that the sum of vectors
can be represented by one vector
equally can we take one vector
and we can replace it by the sum of others.
And we call that "decomposition" of a vector.
And that's going to be very important in 801
and I want you to follow this, therefore, quite closely.
I have a vector which is in three-dimensional space.
This is my z axis...
this is my x axis, y axis and z axis.
This is the origin O and here is a point P
and I have a vector OP-- that's the vector.
And what I do now, I project this vector
onto the three axes, x, y and z.
So there we go.
Each one has her or his own method of doing this.
There we are.
I call this vector vector A.
Now, this angle will be theta, and this angle will be phi.
Notice that the projection of A on the y axis has here
a number which I call A of y.
This number is A of x and this number here is A of z--
simply a projection of that vector onto the three axes.
We now introduce what we call "unit vectors."
Unit vectors are always pointing in the direction
of the positive axis
and the unit vector in the x direction is this one.
It has a length one, and we write for it "x roof."
"Roof" always means unit vector.
And this is the unit vector in the y direction
and this is the unit vector in the z direction.
And now I'm going to rewrite vector A
in terms of the three components that we have here.
So the vector A, I'm going to write
as "A of x times x roof, plus A of y times y roof
plus A of z times z roof."
And this A of x times x is really a vector
that runs from the origin to this point.
So we could put in that as a vector, if you want to.
This makes it a vector.
This is that vector.
A of y times... oh, sorry, it is A of x, this one.
A of y times y roof is this one
and A of z times z roof is this one.
And so these three green vectors added together
are exactly identical to the vector OP
so we have decomposed one vector into three directions.
And we will see that very often, this is of great use in 801.
The magnitude of the vector is
the square root of Ax squared plus Ay squared plus Az squared
and so we can take a simple example.
For instance, I take a vector A--
this is just an example, to see this in action--
and we call A three X roof,
so A of axis is three minus five y roof plus 6 Z roof
so that means that it's three units in this direction
it is five units in this direction--
in the minus y direction--
and six in the plus z direction.
That makes up a vector and I call that vector A.
What is the magnitude of that vector--
which I always write down with vertical bars--
if I put two bars on one side, that's always the magnitude
or sometimes I simply leave the arrow off,
but to be always on the safe side, I like this idea
that you know it's really the magnitude
becomes the scalar when you do that.
So that would be the square root of three squared is nine
five squared is 25, six squared is 36
so that's the square root of 70.
And suppose I asked you, "What is theta?"
It's uniquely determined, of course.
This vector is uniquely determined
in three-dimensional space
so you should be able to find phi and theta.
Well, the cosine of theta...
See, this angle here... 90 degrees projection.
So the cosine of theta is A of z divided by A itself.
So the cosine of theta equals A of z divided by A itself
which in our case
would be six divided by the square root of 70.
And you can do fine.
It's just simply a matter of manipulating some numbers.
We now come to a much more difficult part of vectors
and that is multiplication of vectors.
We're not going to need this until October, but I decided
we might as well get it over with now.
Now that we introduced vectors, you can add and subtract
you might as well learn about multiplication.
It's sort of, the job is done, it's like going to the dentist.
It's a little painful, but it's good for you
and when it's behind you, the pain disappears.
So we're going to talk about multiplication of vectors
something that will not come back until October
and later in the course.
There are two ways that we multiply vectors
and one is called the "dot product"
often also called the scalar product.
A dot B, a fat dot, and that is defined as it is a scalar.
A of x times B of x, just a number
plus A of y times B of y-- that's another number--
plus A of z times B of z-- that's another number.
It is a scalar.
It has no longer a direction.
That is the dot product.
So that's method number one.
That's completely legitimate and you can always use that.
There is another way to find the dot product
depending upon what you're being given--
how the problem is presented to you.
If someone gives you the vector A and you have the vector B
and you happen to know this angle between them,
this angle theta--
which has nothing to do with that angle theta;
it's the angle between the two--
then the dot product is also the following
and you may make an attempt to prove that.
You project the vector B on A.
This is that projection.
The length of this vector is B cosine theta.
And then the dot product
is the magnitude of A times the magnitude of B
times the cosine of the angle theta.
The two are completely identical.
Now, you may ask me, you may say,
"Gee, how do I know what theta is?
"How do I know I should take theta this angle
"or maybe I should take theta this angle?
I mean, what angle is A making with B?"
It makes no difference
because the cosine of this angle here
is the same as the cosine of 360 degrees minus theta
so that makes no difference.
Sometimes this is faster
depending upon how the problem is presented to you;
sometimes the other is faster.
You can immediately see by looking at this--
it's easier to see than looking here--
that the dot product can be larger than zero
it can be equal to zero and it can be smaller than zero.
A and B are, by definition, always positive.
They are a magnitude.
That's always determined by the cosine of theta.
If the cosine of theta is larger than zero,
well, then it's larger than zero.
The cosine of theta can be zero.
If the angle for theta is pi over two--
in other words, if the two vectors
are perpendicular to each other--
then the dot product is zero, and if this angle theta
is between 90 degrees and 180 degrees
then the cosine is negative.
We will see that at work, no pun implied
when we're going to deal with work in physics.
You will see that we can do positive work
and we can do negative work
and that has to do with this dot product.
Work is a dot product.
I could do an extremely simple example with you;
the simplest that I can think of.
Perhaps it's almost an insult-- it's not meant that way.
Suppose we have A dot B
and A is the one that you really have on the blackboard there.
Right here, that's A.
But B is just two y roof.
Two y roof, that's all it is.
Well, what is A dot B?
A dot B... there's no x component of B
so that becomes zero, this term becomes zero.
There is only a y component of B
so it is minus five times plus two
so I get minus ten, because there was no z component.
Simple as that, so it's minus ten.
I can give you another example, example two.
Suppose A itself is the unit vector in the y direction
and B is the unit vector in the z direction.
Then A dot B is what?
I want to hear it loud and clear.
CLASS: Zero.
LEWIN: Yeah! Zero.
It is zero-- you don't even have to think about anything.
You know that these two are at 90 degrees.
If you want to waste your time
and want to substitute it in here
you will see that it comes out to be zero.
It should work, because clearly A of y means
that this... this is one.
That's what it means.
And B is z, that means that B of z... this is one
and all the others do not exist.
Well, I wish you luck with that and we now go
to a way more difficult part of multiplication
and that is vector multiplication
which is called "the vector product."
Or also called... most of the time
I refer to it as "the cross product."
The cross product is written like so: A cross B equals C.
It's a cross, very clear cross.
And I will tell you how I remember...
that is, method number one.
I'm going to teach you-- just like with the dot product--
two methods.
I will tell you method number one
which is the one that always works.
It's time-consuming, but it always works.
You write down here a matrix with three rows.
The first row is x roof, y roof, z roof.
The second one is A of x, A of y, A of z.
It's important, if A is here first
that that second row must be A and the third row is then B.
B of x, B of y, B of z.
So these six are numbers and these are the unit vectors.
I repeat this here verbatim--
you will see in a minute why I need that--
and I will do the same here.
Okay, and now comes the recipe.
You take... you go from the upper left-hand corner
to the one in this direction.
You multiply them, all three, and that's a plus sign.
So you get Ay... so C
which is A cross B equals Ay, times Bz, times the x roof--
but I'm not going to put the x roof in yet--
because I have to subtract this one... minus sign
which has Az By
so it is minus Az By, and that is in the direction x.
The next one is this one.
Az Bx...
minus this one
Ax Bz
in the direction y.
And last but not least
Ax By...
minus Ay Bx...
in the direction of the unit vector z.
So this part here is what we call "C of x".
It's the x component of this vector
and this we can call "C of y" and this we can call "C of z."
So we can also write that vector, then,
that C equals C of x, x roof, plus C of y, y roof
plus C of z, z roof.
Cross product of A and B.
We will have lots of exercises,
lots of chances you will have on assignment, too
to play with this a little bit.
Now comes my method number two and method number two is, again
as we had with the dot product, is a geometrical method.
Let me try to work on this board in between.
If you know vector A and you know vector B
and you know that the angle is theta
then the cross product, C, equals A cross B
is the magnitude of A times the magnitude of B
times the sine of theta
not the cosine of theta as we had before with the dot product.
It is the sine of theta.
So you can really immediately see that this will be zero
if theta is either zero degrees or 180 degrees
whereas the dot product was zero
when the angle between them was 90 degrees.
This number can be larger than zero
if the sine theta is larger than zero.
It can also be smaller than zero.
Now we only have the magnitude of the vector
and now comes the hardest part.
What is the direction of the vector?
And that is something
that you have to engrave in your mind and not forget.
The direction is found as follows.
You take A, because it's first mentioned
and you rotate A over the shortest possible angle to B.
If you had in your hand a corkscrew--
and I will show that in a minute--
then you turn the corkscrew as seen from your seats clockwise
and the corkscrew would go into the blackboard.
And if the corkscrew goes into the blackboard
you will see the tail of the vector
and you will see a cross, little plus sign
and therefore we put that like so.
A cross product is always perpendicular to both A and B
but it leaves you with two choices:
It can either come out of the blackboard
or it can go in the blackboard
and I just told you which convention to use.
And I want to show that to you
in a way that may appeal to you more.
This is what I have used before
on my...
television help sessions that I have given at MIT.
I have an apple-- not an apple...
This is a tomato-- not a tomato...
It's a potato.
(class laughs)
I have a potato here and here is a corkscrew.
There is a corkscrew.
I'm going to turn the corkscrew
as seen from your side, clockwise.
And you'll see that the corkscrew goes into the potato
in -- that's the direction, then, of the vector.
If we had B cross A, then you take B in your hands
and you rotate it over the shortest angle to A.
Now you have to rotate counterclockwise
and when you rotate counterclockwise
the corkscrew comes to you-- there you go--
and so the vector is now pointing in this direction.
And if the vector is pointing towards you
then we would indicate that with a circle and a dot.
In other words, for this vector
B cross A would have exactly the same magnitude--
no difference-- but it would be coming out of the blackboard.
In other words, A cross B equals minus B cross A
whereas A dot B is the same as B dot A.
We will encounter cross products when we deal with torques
and when we deal with angular momentum
which is not the easiest part of 801.
Let's take an extremely simple example.
Again, I don't mean to insult you with such a simple example
but you will get chances,
more advanced chances on your assignment.
Suppose I have the vector A is x roof.
It's a unit vector in the x direction.
That means A of x is one
and A of y is zero and A of z is zero.
And suppose B is y roof.
That means B of y is one
and B of x is zero and B of z is zero.
What, now, is the dot product, the cross product, A cross B?
Well, you can apply that recipe
but it's much easier to go
to the x, y, z axes that we have here.
A was in the x direction, the unit vector
and B in the y direction.
I take A in my hand, I rotate over the smallest angle
which is 90 degrees to y, and my corkscrew will go up.
So I know the whole thing already.
I know that this cross product must be z roof.
The magnitude must be one.
That's immediately clear.
But I immediately have the direction
by using the corkscrew rule.
Now if you're very smart
you may say, "Aha! You find plus z
"only because you have used this coordinate system.
"If this axis had been x, and this one had been y
"then the cross product of x and y would be
in the minus z direction."
Yeah, you're right.
But if you ever do that, I WILL KILL YOU!
(class laughs)
You will always, always have to work
with what we call "a right- handed coordinate system."
And a right-handed coordinate system, by definition
is one whereby the cross product
of x with y is z and not y minus z.
So whenever you get, in the future, involved
with cross products and torques and angular momentum
always make yourself an xyz diagram
for which x cross y is z.
Never, ever make it such that x cross y is minus z.
You're going to hang yourself.
Because for one thing, that wouldn't work anymore.
So be very, very careful.
You must work... if you use the right-hand corkscrew rule
make sure you work with the right-handed coordinate system.
All right, now the worst part is over.
And now I would like to write down for you...
We pick up some of the fruits now
although it will penetrate slowly.
I want to write down for you equations for a moving particle
a moving object in three-dimensional space--
a very complicated motion
which I can hardly imagine what it's like.
It is a point that is going to move around in space
and it is this point P
this point P is going to move around in space
and I call this vector OP, I call that now vector r
and I give it a sub-index t
which indicates it's changing with time.
I call this location A of y, I am going to call that y of t.
It's changing with time.
I call this x of t-- it's going to change with time--
and I call this point z of t
which is going to change with time
because point P is going to move.
And so I'm going to write down the vector r
in its most general form that I can do that.
R, which changes with time
is now x of t-- which is the same as a over x there, before--
times x roof plus y of t,
y roof plus z of t, z roof.
I have decomposed my vector r into three independent vectors.
Each one of those change with time.
What is the velocity of this particle?
Well, the velocity is the first derivative of the position
so that it is dr dt.
So there we go-- first the derivative of this one
which is dx dt, x roof.
I am going to write for dx dt "x dot," because I am lazy
and I am going to write for d2x dt squared, "x double dots."
It's often done, but not in your book.
But it is a notation that I will often use
because otherwise the equations look so clumsy.
Plus y dot times y roof plus z dot times z roof.
So z dot is the dz/dt.
What is the acceleration as a function of time?
Well, the acceleration as a function of time
equals dv/dt.
So that's the second derivative of x versus time
and so that becomes x double dot times x roof
plus y double dot times y roof plus z double dot times z roof.
And look what we have now accomplished.
It looks like minor, but it's going to be big later on.
We have a point P going in three-dimensional space
and here we have the entire behavior of the object
as it moves its projection along the x axis.
This is the position, this is its velocity
and this is its acceleration.
And here you can see the entire behavior on the z axis.
This is the position on the z axis
this is the velocity component in the z direction
and this is the acceleration on the z axis.
And here you have the y.
In other words, we have now... the three-dimensional motion
we have cut into three one-dimensional motions.
This is a one-dimensional motion.
This is behavior only along the x axis
and this is a behavior only along the y axis
and this is a behavior only along the z axis
and the three together make up
the actual motion of that particle.
What have we gained now?
It looks like... this looks like a mathematical zoo.
You would say, "Well, if this is what it is going to be like
it's going to be hell."
Well, not quite--
in fact, it's going to help you a great deal.
First of all, if I throw up a tennis ball in class
like this, then the whole trajectory is...
the whole trajectory is in one plane
in the vertical plane.
So even though it is in three dimensions
we can always represent it by two axes, by two dimensionally
a y axis and an x axis
so already the three-dimensional problem
often becomes a two-dimensional problem.
We will, with great success, analyze these trajectories
by decomposing this very complicated motion.
Imagine what an incredibly complicated arc that is
and yet we are going to decompose it
into a motion in the x direction
which lives a life of its own
independent of the motion in the y direction
which lives a life of its own
and, of course, you always have to combine the two
to know what the particle is doing.
We know the equations so well from our last lecture
from one-dimensional motion with constant acceleration.
The first line tells you
what the x position is as a function of time.
The index t tells you that it is changing with time.
It is the position at t equals zero
plus the velocity at t equals zero
times t plus one-half ax t squared
if there is an acceleration in the x direction.
The velocity immediately comes
from taking the derivative of this function
and the acceleration comes
from taking the derivative of this function.
Now, if we have a motion which is more complicated--
which reaches out to two or three dimensions--
we can decompose the motion in three perpendicular axes
and you can replace every x here by a y
which gives you the entire behavior in the y direction
and if you want to know the behavior in the z direction
you replace every x here by z
and then you have decomposed the motion in three directions.
Each of them are linear.
And that's what I want to do now.
I'm going to throw up an object, golf ball or an apple in 26.100
and we know that it's in the vertical plane, so we have...
we only deal with a two-dimensional problem
this being...
I call this my x axis and I'm going to call this my y axis.
I call this increasing value of x
and I call this increasing value of y.
I could have called this increasing value of y.
Today I have decided to call this increasing value of y.
I am free in that choice.
I throw up an object at a certain angle
and I see a motion like this-- boing!--
and it comes back to the ground.
My initial speed when I threw it was v zero
and the angle here is alpha.
The x component of that initial velocity
is v zero cosine alpha
and the y component equals v zero sine alpha.
So that's the "begin"-velocity of the x direction.
And this is the "begin"-velocity in the y direction.
A little later in time, that object is here at point P
and this is now the position vector
which we have called r of t, it's this vector.
That's the vector that is moving through space.
At this moment in time, x of t is here
and at this moment in time, y of t is here.
And now you're going to see, for the first time
the big gain by the way that we have divided the two axes
which live an independent life.
First x.
I want to know everything about x that there has to be known.
I want to know where it is at any moment in time
velocity and the acceleration, only in x.
First I want to know that at t = 0.
Well, at t = 0, I look there
X zero-- that's the, I can choose that to be zero.
So I can say x zero is zero, that's my free choice.
Now I need v zero x-- what is the velocity?
The velocity at t = 0, which we have called v zero x
is this velocity-- v zero cosine alpha.
And it's not going to change.
Why is it not going to change?
Because there is no a of x, so this term here is zero
we only have this one.
So at all moments in time
the velocity in the x direction is v zero cosine alpha
and the a of x equals zero.
Now I want to do the same in the x direction for time t.
Well, at time t, I look there at the first equation.
There it is-- x zero is zero.
I know v zero x, that is v zero cosine alpha
so x of t is v zero cosine alpha times t
but there is no acceleration, so that's it.
What is vx of t?
The velocity in the x direction at any moment in time.
That is that equation, that is simply v zero x.
It is not changing in time
because there is no acceleration.
So the initial velocity at t zero is the same
as t seconds later and the acceleration is zero.
Now we're going to do this for the y direction.
And now you begin to see the gain for the decomposition.
In the y direction, we change the x by y
and so we do it first at t = 0.
So look there.
This becomes y zero-- I call that zero.
I can always call my origin zero.
I get v zero y times t.
Well, v zero y is this quantity
is v zero sine alpha, v zero sine alpha.
This is v zero sine alpha.
That is the velocity at time zero, and this is zero.
At time zero... this is zero at time zero.
What is the acceleration in the y direction at time zero?
What is the acceleration? That has to do with gravity.
There is no acceleration in the x direction
but you better believe that there is one in the y direction.
So only when we deal with the y equations
does this acceleration come in--
not at all when we deal with the x direction.
Well, if we call the acceleration due to gravity
g equals plus 9.80, and I always call it g
what would be the acceleration in the y direction
given the fact that I call this increasing value of y?
CLASS: Minus 9.8.
LEWIN: Minus 9.8, which I will also say
always call minus g because my g is always positive.
So it is minus g.
So that tells the story of t equals zero in the y direction
and now we have to complete it at time t equals t.
At time t equals t, we have the first line there.
Y zero is zero.
So we have y as a function of time, y zero is zero
so we don't have to work with that.
Where is my... so this is zero, so I get v zero y times t
so I get v zero sine alpha times t
plus one-half, but it is minus one-half g t squared
and now I get the velocity in the y direction at time t--
that is my second line.
That is going to be v zero sine alpha minus g t
and the acceleration in the y direction at any moment in time
equals minus g.
And now I have done all I can
to completely decompose this complicated motion
into two entirely independent one-dimensional motions.
And the next lecture
we're going to use this again and again and again and again.
This lecture is not over yet but I want you to know
that this is what we're going to apply
for many lectures to come--
the decomposition of a complicated trajectory
into two simple ones.
Now, when you look at this
there is something quite remarkable
and the remarkable thing is
that the velocity in the x direction
throughout this whole trajectory--
if there is no air draft, if there is no friction--
is not changing.
It's only the velocity in the y direction that is changing.
It means if I throw up this golf ball--
I throw it up like this--
and it has a certain component in x direction
a certain velocity
if I move myself with exactly that same velocity--
with exactly the same horizontal velocity--
I could catch the ball here.
It would have to come back exactly in my hands.
That is because there is only an acceleration in the y direction
but the motion in the y direction
is completely independent of the x direction.
The x direction doesn't even know
what's going on with the y direction.
In the x direction, if I throw an object like this
the x direction simply, very boringly,
moves with a constant velocity.
There is no time dependence.
And the y direction, on its own, does its own thing.
It goes up, comes to a halt and it stops.
And, of course, the actual motion is the sum
the superposition of the two.
We have tried to find a way
to demonstrate this quite bizarre behavior
which is not so intuitive.
That the x direction really lives a life of its own.
And the way we want to do that is as follows.
We have here a golf ball, a...
a gun we can shoot up the golf ball
and we do that in such a way
that the golf ball, if we do it correctly
exactly comes back here.
That's not easy-- that takes hours and hours of adjustments.
The golf ball goes up and comes back here.
Not here, not here, not there-- that's easy.
You can shoot it up a little at an angle
and the golf ball will come back here.
Once we have achieved that--
that the golf ball will come back there--
then I'm going to give this cart a push
and the moment that it passes through this switch
the golf ball will fire
so that the golf ball will go straight up
as seen from the cart
but it has a horizontal velocity
which is exactly the same horizontal velocity as the cart
so the cart are like my hands.
As the golf ball goes like this
the cart stays always exactly under the golf ball
always exactly under the golf ball
and if all works well
the ball ends up exactly on the cart again.
Let me first show you--
otherwise, if that doesn't work, of course, it's all over--
that if we shoot the ball straight up
that it comes back here.
If it doesn't do that
I don't even have to try this more complicated experiment.
So here's the golf ball.
I'm going to fire the gun now.
Close... close.
Reasonably close.
Well, since it's only reasonably close, perhaps...
(class laughs)
Perhaps it would help if we give it a little bit of leeway.
There goes the gun.
Here comes the ball.
And this is just in case.
Tape it down.
So as I'm going to push this now, give it a push
the gun will be triggered
when the middle of the car is here.
You've seen how high that ball goes
so that ball will go... (makes whooshing sound)
And depending upon how hard I push it
they may meet here or they may meet there.
You ready for this?
You ready?
CLASS: Ready.
LEWIN: I'm ready.
Physics works!
(class applauds)
LEWIN: See you Wednesday.
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