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Curl 1

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    Before I actually show you the
    mechanics of what the curl of a
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    vector field really is, let's
    try to get a little
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    bit of intuition.
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    So here I've drawn, I'm going
    to just draw a two-dimensional
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    vector field.
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    You can extrapolate to 3,
    but when we're getting
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    the intuition, it's
    good to do it in 2.
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    And so, let's see.
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    I didn't even label
    the x and y axis.
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    This is x, this is y.
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    So when y is relatively low,
    our magnitude vector goes in
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    the x direction, when it
    increases a little bit, it
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    gets a little bit longer.
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    So as we can see, as our change
    in the y-direction, as we go
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    in the y-direction, the
    x-component of our vectors
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    get larger and larger.
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    And maybe in the x-direction
    they're constant, regardless
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    of your level of x,
    the magnitude stays.
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    So for given y, the magnitude
    of your x-component vector
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    might stay the same.
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    So I mean, this vector field
    might look something like this.
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    I'm just making up numbers.
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    Maybe it's just, I don't
    know, y squared i.
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    So the magnitude of the
    x-direction is just a
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    function of your y-value.
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    And as your y-values get bigger
    and bigger, the magnitude in
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    your x-direction will get
    bigger and bigger, proportional
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    to the square of the magnitude
    of the y direction.
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    But for any given x, it's
    always going to be the same.
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    It's only dependent on y.
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    So here, even if we make
    x larger, we still get
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    the same magnitude.
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    And remember, these are
    just sample points
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    on our vector field.
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    But anyway.
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    That's enough of just getting
    the intuition behind
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    that vector field.
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    But let me ask you a question.
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    If I were to, let's say that
    this vector field shows the
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    velocity of a fluid
    at various points.
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    And so you can view this, we're
    looking down on a river, maybe.
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    If I were to take a little twig
    or something, and I were to
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    place it in this fluid, so let
    me place the twig right here.
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    Let me draw my twig.
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    So let's say I place a twig,
    it's a funny-looking twig,
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    but that's good enough.
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    Let's say I place a
    twig right there.
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    What's going to
    happen to the twig?
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    Well, at this point on the
    twig, the water's moving to the
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    right, so it'll push this part
    of the twig to the right.
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    At the top of the twig, the
    water is also moving to the
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    right, maybe with a faster
    velocity, but it's also going
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    to push the top of the
    twig to the right.
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    But the top of the twig is
    going to be being pushed to
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    the right faster than the
    bottom of the twig, right?
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    So what's going to happen?
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    The twig's going
    to rotate, right?
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    After, I don't know, some
    period of time, the
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    twig's going to look
    something like this.
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    The bottom will move a little
    bit to the right, but the
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    top will move a lot
    more to the right.
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    Right?
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    And the whole thing would have
    been shifted to the right.
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    But it's going to
    rotate a little bit.
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    And maybe after a little bit
    further, maybe it looks
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    something like this.
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    So you can see that because the
    vectors increasing in a
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    direction that is perpendicular
    to our direction
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    of motion, right?
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    This fairly simple example,
    all of the vectors point
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    in the x-direction.
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    But the magnitude of the
    vectors increase, they increase
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    perpendicular, they increase
    in the y-dimension, right?
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    And when this happens, when the
    flow is going in the same
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    direction, but it's going at a
    different magnitude, you see
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    that any object in it
    will rotate, right?
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    So let's think about that.
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    So if the derivative, the
    partial derivative, of this
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    vector field with respect to y
    is increasing or decreasing, if
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    it's just changing, that means
    as we increase in y, or as we
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    decrease in y, the magnitude of
    the x-component of our vectors,
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    right, the x-direction
    of our vectors changes.
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    And so if you have a different
    speed for different levels of
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    y, as something moves in the
    x-direction, it's going
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    to be rotated, right?
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    You could almost view it as if
    there's a net torque on an
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    object that sits in
    the water here.
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    And the ultimate would be, let
    me draw another vector field,
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    the ultimate would be if
    I had this situation.
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    Let me draw another
    vector field.
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    If I had this situation, where
    maybe down here it's like this,
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    then maybe it's like this, and
    then maybe it gets really
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    small, then maybe it switches
    directions, up here, and then
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    the vector field
    goes like this.
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    So you could imagine up here
    that's going to the left, with
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    a fairly large magnitude.
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    So if you put a twig here, you
    would definitely hopefully see
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    that the twig, not only will it
    not be shifted to the right,
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    this side is going to be moved
    to the left, this side is going
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    to be the right, it's
    going to be rotated.
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    And you'll see that there's
    a net torque on the twig.
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    So what's the intuition there?
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    All of a sudden, we care about
    how much is the magnitude of a
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    vector changing, not in its
    direction of motion, like in
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    the divergence example, but we
    care how much is the magnitude
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    of a vector changing as we go
    perpendicular to its
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    direction of motion.
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    So when we learned about
    dot and cross product,
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    what did we learn?
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    We learned that the dot product
    of 2 vectors tells you how much
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    2 vectors move together, and
    the cross product tells you how
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    much the perpendicular, it's
    kind of the multiplication
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    of the perpendicular
    components of a vector.
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    So this might give you a little
    intuition of what is the curl.
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    Because the curl essentially
    measures what is the rotational
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    effect, or I guess you could
    say, what is the curl of a
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    vector field at a given point?
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    And you can you
    can visualize it.
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    You put a twig there, what
    would happen to the twig?
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    If the twig rotates and there's
    some curl, if the magnitude
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    of the rotation is larger,
    then the curl is larger.
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    If it rotates in the other
    direction, you'll have the
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    negative direction of curl.
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    And so just like what we did
    with torque, we now care
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    about the direction.
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    Because we care whether it's
    going counterclockwise or
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    clockwise, so we're going to
    end up with a vector
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    quantity, right?
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    So, and all of this should
    hopefully start fitting
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    together at this point.
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    We've been dealing
    with this Dell
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    vector or this, you know, we
    could call this abusive
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    notation, but it kind of is
    intuitive, although it really
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    doesn't have any meaning when
    I describe it like this.
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    You can kind of write it as a
    vector operator, and then it
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    has a little bit more meeting.
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    But this Dell
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    operator, we use it
    a bunch of times.
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    You know, if the partial
    derivative of something in the
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    i-direction, plus the partial
    derivative, something with
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    respect to y in the
    j-direction, plus the partial
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    derivative, well, this is if we
    do it in three dimensions
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    with respect to z
    in the k-direction.
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    When we applied it to just a
    scalar or vector field, you
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    know, like a three-dimensional
    function, we just multiplied
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    this times that scalar
    function, we got the gradient.
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    When we took the dot product of
    this with a vector field, we
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    got the divergence of
    the vector field.
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    And this should be a
    little bit intuitive
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    to you, at this point.
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    Because when we, you might want
    to review our original videos
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    where we compared the dot
    product to the cross product.
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    Because the dot product
    was, how much do two
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    vectors move together?
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    So when you're taking this Dell
    operator and dotting it with a
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    vector field, you're saying,
    how much is the vector
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    field changing, right?
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    All a derivative is, a partial
    derivative or a normal
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    derivative, it's just
    a rate of change.
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    Partial derivative with respect
    to x is rate of change
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    in the x-direction.
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    So all you're saying is, when
    you're taking a dot product,
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    how much is my rate of
    change increasing in my
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    direction of movement?
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    How much is my rate of change
    in the y-direction increasing
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    in the y-direction?
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    And so it makes sense that it
    helps us with divergence.
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    Because remember, if this is a
    vector, and then as we increase
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    this in the x-direction, the
    vectors increase, we took a
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    little point, and we said, oh,
    at this point we're going to
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    have more leaving than
    entering, so we have a
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    positive divergence.
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    But that makes sense, also,
    because as you go in the
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    x-direction, the magnitudes
    of the vectors increase.
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    Anyway, I don't want to
    confuse you too much.
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    So now, the intuition, because
    now we don't care about the
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    rate of change along with the
    direction of the vector.
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    We care about the rate of
    change of the magnitudes of
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    the vectors perpendicular
    the direction of the vector.
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    So the curl, you might guess,
    is equal to the cross product
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    of our Dell operator
    and the vector field.
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    And if that was where your
    intuition led you, and that
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    is what your guess is,
    you would be correct.
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    That is the curl of
    the vector field.
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    And it is a measure of how much
    is that field rotating, or
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    maybe if you imagine an object
    in the field, how much is the
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    field causing something
    to rotate because it's
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    exerting a net torque?
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    Because at different points
    in the object, you have a
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    different magnitude of a
    field in the same direction.
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    Anyway, I don't want to
    confuse you too much.
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    Hopefully that example I
    just showed you will make
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    a little bit of sense.
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    Anyway, I realize I've
    already pushed 9 minutes.
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    In the next video, I'll
    actually compute curl, and
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    maybe we'll try to draw
    a couple more to hit
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    the intuition home.
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    See you in the next video.
  • 9:31 - 9:32
Title:
Curl 1
Description:

Introduction to the curl of a vector field

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Video Language:
English
Duration:
09:32
Maggie S (Amara staff) edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
Suba Jarrar edited English subtitles for Curl 1
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