triple cross product expansion investment

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Triple cross product expansion investment

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This is just one way to remember the dot product, if you remember how to take determinants of three-by-threes. And we'll put b's x term, b's y coefficient, and b's z component. And then you do the same thing for the c, cx, cy, cz. And then this is going to be equal to-- so first you have the i component. So it's going to be the i component times b.

So you ignore this column and this row. So bycz minus bzcy. So I'm just ignoring all of this. And I'm looking at this two-by-two over here, minus bzcy. And then we want to subtract the j component. Remember, we alternate signs when we take our determinant. Subtract that. And then we take out that column and that row, so it's going to be bxcz-- this is a little monotonous, but hopefully, it'll have an interesting result-- bxcz minus bzcx.

And then finally, plus the k component. OK, we're going to have bx times cy minus bycx. We just did the dot product, and now we want to take the-- oh, sorry, we just did the cross product. I don't want to get you confused.

We just took the cross product of b and c. And now we need take the cross product of that with a, or the cross product of a with this thing right over here. So let's do that. Instead of rewriting the vector, let me just set up another matrix here. So let me write my i j k up here. And then let me write a's components. And then let's clean this up a little bit. Let's ignore this. We're just looking at-- no, I want to do that in black. Let's do this in black, so that we can kind of erase that.

Now this is a minus j times that. So what I'm going to do is I'm going to get rid of the minus and the j, but I am going to rewrite this with the signs swapped. So if you swap the signs, it's actually bzcx minus bxcz. So let me delete everything else.

So I just took the negative and I multiplied it by this. I hope I'm not making any careless mistakes here, so let me just check and make my brush size little bit bigger, so I can erase that a little more efficiently. There you go. And then we also want to get rid of that right over there. Now let me get my brush size back down to normal size. All right. So now let's just take this cross product. So once again, set it up as a determinant.

And what I'm only going to focus on-- because it'll take the video, or it'll take me forever if I were to do the i, j, and k components-- I'm just going to focus on the i component, just on the x component of this cross product. And then we can see that we'll get the same result for the j and the k. And then we can see what, hopefully, this simplifies down to.

So if we just focus on the i component here, this is going to be i times-- and we just look at this two-by-two matrix right over here. We ignore i's column, i's row. And we have ay times all of this. So let me just multiply it out. So it's ay times bxcy, minus ay times by, times bycx. And then we're going to want to subtract.

We're going to have minus az times this. So let's just do that. So it's minus, or negative, azbzcx. And then we have a negative az times this, so it's plus azbxcz. And now what I'm going to do-- this is a little bit of a trick for this proof right here, just so that we get the results that I want. I'm just going to add and subtract the exact same thing. So I'm going to add an axbxcx. And then I'm going to subtract an axbxcx, minus axbxcx.

So clearly, I have not changed this expression. I've just added and subtracted the same thing. And let's see what we can simplify. Remember, this is just the x component of our triple product. Just the x component. But to do this, let me factor out. I'm going to factor out a bx. So let me do this, let me get the bx. So if I were to factor it out-- I'm going to factor it out of this term that has a bx.

I'm going to factor it out of this term. And then I'm going to factor it out of this term. So if I take the bx out, I'm going to have an aycy. Actually, let me write it a little bit differently. Let me factor it out of this one first.

So then it's going to have an axcx. So I used this one up. And then I'll do this one now. Plus, if I factor the bx out, I get ay cy. I've used that one now. And now I have this one. I'm going to factor the bx out. So I'm left with a plus az, cz.

So that's all of those. So I've factored that out. And now, from these right over here, let me factor out a negative cx. And so, if I do that-- let me go to this term right over here-- I'm going to have an axbx when I factor it out. So an axbx, cross that out. And then, over here, I'm going to have an ayby. Remember, I'm factoring out a negative cx, so I'm going to have a plus ay, sub by. And then, finally, I'm going to have a plus az, az bz. And what is this?

Well, this right here, in green, this is the exact same thing as the dot products of a and c. This is the dot product of the vectors a and c. It's the dot product of this vector and that vector. So that's the dot of a and c times the x component of b minus-- I'll do this in the same-- minus-- once again, this is the dot product of a and b now, minus a dot b times the x component of c.

And we can't forget, all of this was multiplied by the unit vector i. We're looking at the x component, or the i component of that whole triple product.

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Google Classroom Facebook Twitter. Video transcript What I want to do with this video is cover something called the triple product expansion-- or Lagrange's formula, sometimes. And it's really just a simplification of the cross product of three vectors, so if I take the cross product of a, and then b cross c.

And what we're going to do is, we can express this really as sum and differences of dot products. Well, not just dot products-- dot products scaling different vectors. You're going to see what I mean. But it simplifies this expression a good bit, because cross products are hard to take. They're computationally intensive and, at least in my mind, they're confusing. Now this isn't something you have to know if you're going to be dealing with vectors, but it's useful to know.

My motivation for actually doing this video is I saw some problems for the Indian Institute of Technology entrance exam that seems to expect that you know Lagrange's formula, or the triple product expansion. So let's see how we can simplify this. So to do that, let's start taking the cross product of b and c. And in all of these situations, I'm just going to assume-- let's say I have vector a. That's going to be a, the x component of vector a times the unit of vector i plus the y component of vector a times the unit vector j plus the z component of vector a times unit vector k.

And I could do the same things for b and c. So if I say b sub y, I'm talking about what's scaling the j component in the b vector. So let's first take this cross product over here. And if you've seen me take cross products, you know that I like to do these little determinants.

Let me just take it over here. So b cross c is going to be equal to the determinant. And I put an i, j, k up here. This is actually the definition of the cross product, so no proof necessary to show you why this is true. This is just one way to remember the dot product, if you remember how to take determinants of three-by-threes.

And we'll put b's x term, b's y coefficient, and b's z component. And then you do the same thing for the c, cx, cy, cz. And then this is going to be equal to-- so first you have the i component. So it's going to be the i component times b. So you ignore this column and this row.

So bycz minus bzcy. So I'm just ignoring all of this. And I'm looking at this two-by-two over here, minus bzcy. And then we want to subtract the j component. Remember, we alternate signs when we take our determinant. Subtract that. And then we take out that column and that row, so it's going to be bxcz-- this is a little monotonous, but hopefully, it'll have an interesting result-- bxcz minus bzcx. And then finally, plus the k component.

OK, we're going to have bx times cy minus bycx. We just did the dot product, and now we want to take the-- oh, sorry, we just did the cross product. I don't want to get you confused. We just took the cross product of b and c. And now we need take the cross product of that with a, or the cross product of a with this thing right over here. So let's do that. Instead of rewriting the vector, let me just set up another matrix here.

So let me write my i j k up here. And then let me write a's components. And then let's clean this up a little bit. Let's ignore this. We're just looking at-- no, I want to do that in black. Let's do this in black, so that we can kind of erase that. Now this is a minus j times that. So what I'm going to do is I'm going to get rid of the minus and the j, but I am going to rewrite this with the signs swapped.

So if you swap the signs, it's actually bzcx minus bxcz. So let me delete everything else. So I just took the negative and I multiplied it by this. I hope I'm not making any careless mistakes here, so let me just check and make my brush size little bit bigger, so I can erase that a little more efficiently. There you go. And then we also want to get rid of that right over there.

Now let me get my brush size back down to normal size. All right. So now let's just take this cross product. So once again, set it up as a determinant. And what I'm only going to focus on-- because it'll take the video, or it'll take me forever if I were to do the i, j, and k components-- I'm just going to focus on the i component, just on the x component of this cross product.

And then we can see that we'll get the same result for the j and the k. And then we can see what, hopefully, this simplifies down to. So if we just focus on the i component here, this is going to be i times-- and we just look at this two-by-two matrix right over here.

We ignore i's column, i's row. And we have ay times all of this. So let me just multiply it out. So it's ay times bxcy, minus ay times by, times bycx. And then we're going to want to subtract. We're going to have minus az times this.

So let's just do that. So it's minus, or negative, azbzcx. And then we have a negative az times this, so it's plus azbxcz. And now what I'm going to do-- this is a little bit of a trick for this proof right here, just so that we get the results that I want.

I'm just going to add and subtract the exact same thing. So I'm going to add an axbxcx. And then I'm going to subtract an axbxcx, minus axbxcx. So clearly, I have not changed this expression. I've just added and subtracted the same thing. And let's see what we can simplify. Remember, this is just the x component of our triple product. Just the x component. But to do this, let me factor out. I'm going to factor out a bx. So let me do this, let me get the bx. So if I were to factor it out-- I'm going to factor it out of this term that has a bx.

I'm going to factor it out of this term. And then I'm going to factor it out of this term. So if I take the bx out, I'm going to have an aycy. Actually, let me write it a little bit differently. Let me factor it out of this one first.

So then it's going to have an axcx. TTCP is part of an independent healthcare merchant bank. Since our inception, we have invested in more than companies and partner with over active companies across our venture and growth equity portfolio. The firm invests in early to late stage companies across a wide range of sectors with a focus on consumer, enterprise, and healthcare.

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Since the cross product is anticommutative, this formula may also be written up to permutation of the letters as:. Another useful formula follows:. These formulas are very useful in simplifying vector calculations in physics. A related identity regarding gradients and useful in vector calculus is Lagrange's formula of vector cross-product identity: [4]. The second cross product cannot be expressed as an exterior product, otherwise the scalar triple product would result.

Instead a left contraction [6] can be used, so the formula becomes [7]. The proof follows from the properties of the contraction. In tensor notation the triple product is expressed using the Levi-Civita symbol : [8]. From Wikipedia, the free encyclopedia. This article is about ternary operations on vectors. For the identity in number theory, see Jacobi triple product. For the calculus chain rule for three interdependent variables, see Triple product rule. For the product in nuclear fusion, see Lawson criterion.

This section needs expansion. You can help by adding to it. January Oxford University Press. He may have written a formula similar to the triple product expansion in component form. Encyclopedic Dictionary of Mathematics. MIT Press. Encyclopedic dictionary of mathematics 2nd ed. Heading Mathematical Methods in Science and Engineering. American Elsevier Publishing Company, Inc. Clifford algebras and spinors 2nd ed. Cambridge University Press. Retrieved 21 May And we'll put b's x term, b's y coefficient, and b's z component.

And then you do the same thing for the c, cx, cy, cz. And then this is going to be equal to-- so first you have the i component. So it's going to be the i component times b. So you ignore this column and this row. So bycz minus bzcy. So I'm just ignoring all of this. And I'm looking at this two-by-two over here, minus bzcy. And then we want to subtract the j component. Remember, we alternate signs when we take our determinant.

Subtract that. And then we take out that column and that row, so it's going to be bxcz-- this is a little monotonous, but hopefully, it'll have an interesting result-- bxcz minus bzcx. And then finally, plus the k component. OK, we're going to have bx times cy minus bycx. We just did the dot product, and now we want to take the-- oh, sorry, we just did the cross product. I don't want to get you confused. We just took the cross product of b and c.

And now we need take the cross product of that with a, or the cross product of a with this thing right over here. So let's do that. Instead of rewriting the vector, let me just set up another matrix here. So let me write my i j k up here.

And then let me write a's components. And then let's clean this up a little bit. Let's ignore this. We're just looking at-- no, I want to do that in black. Let's do this in black, so that we can kind of erase that. Now this is a minus j times that. So what I'm going to do is I'm going to get rid of the minus and the j, but I am going to rewrite this with the signs swapped. So if you swap the signs, it's actually bzcx minus bxcz.

So let me delete everything else. So I just took the negative and I multiplied it by this. I hope I'm not making any careless mistakes here, so let me just check and make my brush size little bit bigger, so I can erase that a little more efficiently. There you go. And then we also want to get rid of that right over there. Now let me get my brush size back down to normal size. All right. So now let's just take this cross product.

So once again, set it up as a determinant. And what I'm only going to focus on-- because it'll take the video, or it'll take me forever if I were to do the i, j, and k components-- I'm just going to focus on the i component, just on the x component of this cross product. And then we can see that we'll get the same result for the j and the k. And then we can see what, hopefully, this simplifies down to. So if we just focus on the i component here, this is going to be i times-- and we just look at this two-by-two matrix right over here.

We ignore i's column, i's row. And we have ay times all of this. So let me just multiply it out. So it's ay times bxcy, minus ay times by, times bycx. And then we're going to want to subtract. We're going to have minus az times this. So let's just do that. So it's minus, or negative, azbzcx.

And then we have a negative az times this, so it's plus azbxcz. And now what I'm going to do-- this is a little bit of a trick for this proof right here, just so that we get the results that I want. I'm just going to add and subtract the exact same thing. So I'm going to add an axbxcx. And then I'm going to subtract an axbxcx, minus axbxcx. So clearly, I have not changed this expression.

I've just added and subtracted the same thing. And let's see what we can simplify. Remember, this is just the x component of our triple product. Just the x component. But to do this, let me factor out. I'm going to factor out a bx. So let me do this, let me get the bx.

So if I were to factor it out-- I'm going to factor it out of this term that has a bx. I'm going to factor it out of this term. And then I'm going to factor it out of this term. So if I take the bx out, I'm going to have an aycy. Actually, let me write it a little bit differently. Let me factor it out of this one first. So then it's going to have an axcx.

So I used this one up. And then I'll do this one now. Plus, if I factor the bx out, I get ay cy. I've used that one now. And now I have this one. I'm going to factor the bx out. So I'm left with a plus az, cz. So that's all of those.

So I've factored that out. And now, from these right over here, let me factor out a negative cx. And so, if I do that-- let me go to this term right over here-- I'm going to have an axbx when I factor it out. So an axbx, cross that out. And then, over here, I'm going to have an ayby. Remember, I'm factoring out a negative cx, so I'm going to have a plus ay, sub by.

And then, finally, I'm going to have a plus az, az bz. And what is this? Well, this right here, in green, this is the exact same thing as the dot products of a and c. This is the dot product of the vectors a and c. It's the dot product of this vector and that vector. So that's the dot of a and c times the x component of b minus-- I'll do this in the same-- minus-- once again, this is the dot product of a and b now, minus a dot b times the x component of c.

And we can't forget, all of this was multiplied by the unit vector i. We're looking at the x component, or the i component of that whole triple product. So that's going to be all of this.

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Retrieved 21 May PARAGRAPH. For the identity in number. Sign up or log in 2 silver badges 9 9. A big thank triple cross product expansion investment, Tim. A related identity regarding gradients can be used, so the is Lagrange's formula of vector. Sign up using Email and. In tensor notation the triple theory, see Jacobi triple product. Instead a left contraction [6] silver badges 16 16 bronze. For the calculus chain rule for three interdependent variables, see. Since the cross product is anticommutative, this formula may also be written up to permutation product would result.

The vector triple product is defined as the cross product of one This is known as triple product expansion, or Lagrange's. The vector triple product (also called triple product expansion or Lagrange's formula) is the product of one vector with the product of two other vectors. If u, v and. Scalar Triple Product- Triple Product of Vectors and learn Scalar Triple Product We are familiar with the expansion of cross product of vectors.