+10**10**10
On Sep 10, 2016 3:32 PM, "Steven G. Johnson" wrote:
>
>
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> On Saturday, September 10, 2016 at 12:20:25 PM UTC-4, Stuart Brorson
wrote:
>>
>> However, from a physics perspective, this bugs me. In physics, an
>> important feature of a space is its orientation.
On Saturday, September 10, 2016 at 12:20:25 PM UTC-4, Stuart Brorson wrote:
>
> However, from a physics perspective, this bugs me. In physics, an
> important feature of a space is its orientation.
I should also remind you that a lot of modern physics tries to separate the
laws of physics
Yichao is right, you cannot give eigenvectors an orientation; A good way to
think of them is as defining linear subspaces.
So what is unique is the projector v\|v| \otimes v/|v| or in the case of
multiple e-vals the projector onto the eigenspace \sum v_i \otimes v_i.
But never the e-evecs
On Sat, Sep 10, 2016 at 2:18 PM, Yichao Yu wrote:
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> On Sat, Sep 10, 2016 at 2:12 PM, Stuart Brorson wrote:
>
>> I don't think you can define that in a continuous way.
>>> In general, if your application relies on certain property of the basis,
>>> you
On Sat, Sep 10, 2016 at 2:12 PM, Stuart Brorson wrote:
> I don't think you can define that in a continuous way.
>> In general, if your application relies on certain property of the basis,
>> you should just normalize it that way. If you don't have a requirement
>> than
>> you
I don't think you can define that in a continuous way.
In general, if your application relies on certain property of the basis,
you should just normalize it that way. If you don't have a requirement than
you should worry about it.
Thanks for the thoughts.
I did a little more thinking and
On Sat, Sep 10, 2016 at 12:20 PM, Stuart Brorson wrote:
> Just a question from a non-mathematician. Also, this is a math
> question, not a Julia/Matlab question.
>
> I agree that Matlab and Julia are both correct -- within the
> definitions of eigenvector and eigenvalue they
Just a question from a non-mathematician. Also, this is a math
question, not a Julia/Matlab question.
I agree that Matlab and Julia are both correct -- within the
definitions of eigenvector and eigenvalue they compute, it's OK that
one eigenvector differes between the two by a factor -1.