Gram Schmidt procedure, trouble finding inner product

In summary, the author tried to solve for y using x' and found that it was negative. They are not sure what the inner product of x' and y' will be, but they think it will be negative.
  • #1
Jimmy000
7
1

Homework Statement


Given basis |x>,|y>,|z> such that <x|x> = 2,<y|y> = 2,<z|z> = 3,<x|y> = i, <x|z> = i, and <y|z> = 2. Build an orthonormal basis|x'>,|y'>,|z'>. Each of the new basis vectors should be expressed in terms of the old ones multiplied by coefficients.

Homework Equations



|x'> = |x>/(<x|x>).5 (normalizing the original x ket)

|y'> = |y> - <x'|y> |x'>

The Attempt at a Solution


So far I have worked through that |x'> = (1/2).5|x>
Using this result I have moved through the calculation of |y'> and found it equals

|y> - (i/2) |x'>

I am now trying to normalize this expression, but I am not sure what my inner product on the denominator will look like for this normalization, but my best guess is
<y| - (i/2)<x'|y> - (i/2)|x'>

but that does not look legitimate to me, so I am stuck here.

How do I take the inner product of a bra and and ket, both of which are sums of two kets/bras?
 
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  • #2
Jimmy000 said:

Homework Statement


Given basis |x>,|y>,|z> such that <x|x> = 2,<y|y> = 2,<z|z> = 3,<x|y> = i, <x|z> = i, and <y|z> = 2. Build an orthonormal basis|x'>,|y'>,|z'>. Each of the new basis vectors should be expressed in terms of the old ones multiplied by coefficients.

Homework Equations



|x'> = |x>/(<x|x>).5 (normalizing the original x ket)

|y'> = |y> - <x'|y> |x'>

The Attempt at a Solution


So far I have worked through that |x'> = (1/2).5|x>
Using this result I have moved through the calculation of |y'> and found it equals

|y> - (i/2) |x'>

I am now trying to normalize this expression, but I am not sure what my inner product on the denominator will look like for this normalization, but my best guess is
<y| - (i/2)<x'|y> - (i/2)|x'>

but that does not look legitimate to me, so I am stuck here.

How do I take the inner product of a bra and and ket, both of which are sums of two kets/bras?
Use parentheses. If you had a = b + c, you wouldn't say ##a\times a = b + c\times b + c##, would you? That's effectively what you're doing right now, so it's not surprising it doesn't look right to you.
 
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  • #3
In the "bra"-"ket" formalisim the bra is the complex conjugate of the ket. In your normalizing denominator you must take the inner-product of the vector with its complex conjugate.
 
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  • #4
Thanks a million! I always mix up how kets and bras correlate to normal vector notation. I worked it through being mindful of parentheses and I got a much more logical answer :biggrin:
 

1. What is the Gram Schmidt procedure?

The Gram Schmidt procedure is a mathematical method used to transform a set of linearly independent vectors into a set of orthonormal vectors. This is useful in many areas of science and engineering, including signal processing, quantum mechanics, and computer graphics.

2. How does the Gram Schmidt procedure work?

The procedure involves a series of steps that use the inner product of vectors to create new, orthogonal vectors. First, a vector is chosen as the first basis vector. Then, each subsequent vector is projected onto the subspace spanned by the previous vectors, and the orthogonal projection is subtracted from the original vector. This process is repeated until all vectors have been transformed into orthogonal vectors.

3. What is the inner product used in the Gram Schmidt procedure?

The inner product used in the Gram Schmidt procedure is the dot product. This is a mathematical operation that takes two vectors and returns a scalar value. The dot product of two vectors is equal to the product of their magnitudes and the cosine of the angle between them.

4. What can cause trouble when using the Gram Schmidt procedure?

One common issue when using the Gram Schmidt procedure is rounding errors. This can occur when working with floating-point numbers, which have limited precision. These errors can accumulate and lead to incorrect results. Additionally, if the original set of vectors is not linearly independent, the resulting orthonormal vectors may not accurately represent the original set.

5. How is the Gram Schmidt procedure used in practical applications?

The Gram Schmidt procedure is used in many practical applications, such as signal processing, data compression, and computer graphics. In signal processing, it is used to transform a set of basis functions into a set of orthonormal functions that can be used to represent signals. In computer graphics, it is used to transform geometric data into a more efficient and accurate representation for rendering.

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