Orthochronous subspace of Lorentz group.

Join the discussion
Ask a follow-up here, or get your own question answered by working scientists, mathematicians and engineers — people, not an autocomplete.
Real named experts · corrections over time · the nuance an AI answer skips
18 replies · 4K views
LayMuon
Messages
149
Reaction score
1
In a Lorentz group we say there is a proper orthochronous subspace. How can I prove that the product of two orthchronous Lorentz matrices is orthochronous? Thanks. Would appreciate clear proofs.
 
on Phys.org
[itex]\Lambda^0_0 \geq 1[/itex]
 
LayMuon said:
In a Lorentz group we say there is a proper orthochronous subspace. How can I prove that the product of two orthchronous Lorentz matrices is orthochronous? Thanks. Would appreciate clear proofs.

Consider two such matrices, [itex]A[/itex] and [itex]B[/itex], call their product [itex]C[/itex]. Now take the [itex](0,0)[/itex] entries of the following matrix equations
[tex]A B = C , \ \ \ A \ \eta \ A^{ T } = B^{ T } \eta \ B = \eta .[/tex]
Now, if you use the Schwarz inequality
[tex] - \sqrt{ ( A^{ 0 }{}_{ i } )^{ 2 } ( B^{ i }{}_{ 0 } )^{ 2 } } \leq A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 } ,[/tex]
and
[tex]A^{ 0 }{}_{ 0 } \geq 1 , \ \ B^{ 0 }{}_{ 0 } \geq 1 ,[/tex]
you should be able to show that [itex]C^{ 0 }{}_{ 0 } \geq 1[/itex]
 
Thanks for reply. Why is there a minus sign in Schwartz inequality? Isn't it [itex]\sqrt{ ( A^{ 0 }{}_{ i } )^{ 2 } ( B^{ i }{}_{ 0 } )^{ 2 } } \geq |A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 }|[/itex]?

[tex] <br /> C^0 {}_0 - A^0 {}_0 B^0 {}_0 = A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 }<br /> [/tex]

How to proceed?
 
I don't (yet) see what Sam is doing there. But what you wrote isn't the standard Cauchy-Schwarz inequality either. I think what you're looking for is
$$\left|\sum_i A^0{}_i B^i{}_0\right|\leq \sqrt{\sum_i(A^0{}_i)^2}\sqrt{\sum_j(B^j{}_0)^2}.$$ Do you know how to prove that if ##\Lambda## is orthochronous, its 00 component is either ##\geq 1## or ##\leq -1##? If you have proved that, it will be sufficient to prove that the 00 component of the product transformation is ##\geq 0##. I think that makes the problem much easier. One approach is to try to show that (in a notation with all indices of matrix components written downstairs) ##(\bar\Lambda\Lambda)_{00}=\bar\Lambda_{00} \Lambda_{00} X,## where X is a non-negative real number.
 
Last edited:
So how does it work out?
 
[tex]|C^0 {}_0 - A^0 {}_0 B^0 {}_0 | \leq \sqrt{\sum_i(1-B^0{}_0{}^2)}\sqrt{\sum_j(A^0{}_i)^2}[/tex]. I don't know how to express $$ A^0{}_i^2$$ in terms of A00
 
Last edited:
I don't see what you're doing there.

I worked through the solution by my method again. I had to use Cauchy-Schwartz, the familiar version for vectors on ##\mathbb R^3##, but not until the very end.

You didn't answer if you have already proved that the 00 component of a Lorentz transformation can't be in the interval (-1,1). You should start with that, because it makes your task easier. You will find that result if you look at the 00 component of the matrix equation ##\Lambda^T\eta\Lambda=\eta##. (Use the definition of matrix multiplication). The next step is to use the definition of matrix multiplication on the 00 component of ##\bar\Lambda\Lambda##. Feel free to use the notation AB instead of ##\bar\Lambda\Lambda## if you prefer.
 
Fredrik said:
You didn't answer if you have already proved that the 00 component of a Lorentz transformation can't be in the interval (-1,1).

Yes, that's clear.
 
OK, I should also mention that I find it useful to know that if ##\Lambda## is the transformation from the coordinate system S to the coordinate system S', then (in my notation, where all matrix indices are downstairs), ##\Lambda_{i0}/\Lambda_{00}## is the velocity of S in S'. It's not absolutely necessary to know that, but it makes some steps easier to see.
 
LayMuon said:
Thanks for reply. Why is there a minus sign in Schwartz inequality? Isn't it [itex]\sqrt{ ( A^{ 0 }{}_{ i } )^{ 2 } ( B^{ i }{}_{ 0 } )^{ 2 } } \geq |A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 }|[/itex]?
Ok, doesn’t this imply that
[tex]- \sqrt{ ( A^{ 0 }{}_{ i } )^{ 2 } ( B^{ j }{}_{ 0 } )^{ 2 } } \leq A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 } .[/tex]

[tex] <br /> C^0 {}_0 - A^0 {}_0 B^0 {}_0 = A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 }<br /> [/tex]

How to proceed?

Now, from the other two equations, you have (sums over indices are implies)
[tex]( A^{ 0 }{}_{ i } )^{ 2 } = ( A^{ 0 }{}_{ 0 } )^{ 2 } - 1 ,[/tex]
[tex]( B^{ j }{}_{ 0 } )^{ 2 } = ( B^{ 0 }{}_{ 0 } )^{ 2 } - 1 .[/tex]
Using these, the Schwarz inequality becomes equivalent to
[tex]0 \leq | A^{ 0 }{}_{ 0 } | \ | B^{ 0 }{}_{ 0 } | \left( 1 - \sqrt{ ( 1 - | A^{ 0 }{}_{ 0 } |^{ - 2 } ) ( 1 - | B^{ 0 }{}_{ 0 } |^{ - 2 } ) } \right) \leq C^{ 0 }{}_{ 0 } .[/tex]
Now you can check that [itex]C^{ 0 }{}_{ 0 } \geq 1[/itex].
 
How did you get this: [itex]( A^{ 0 }{}_{ i } )^{ 2 } = ( A^{ 0 }{}_{ 0 } )^{ 2 } - 1[/itex]? I understand it for B. how are [itex]A^0{}_j[/itex] and [itex]A^j{}_0[/itex] related?
 
samalkhaiat said:
Lower indices number the rows in the matrix. Choose any convention you like and stick with it.

I still don't understand. They are different parts of lorentz matrix. One can only use the definition of lorentz group, I.e. orthogonality.
 
LayMuon said:
I still don't understand. They are different parts of lorentz matrix. One can only use the definition of lorentz group, I.e. orthogonality.

I don't really do homework. Any way, orthogonality is what I used in writing the matrix equations
[tex]\eta = A \eta A^{ T }, \ \ \eta = B^{ T } \eta B[/tex]
Now, forget about upper and lower indices, Can you find the first matrix element, i.e. the [itex](0,0)[/itex] entry in each of the above equations?
 
LayMuon said:
Thanks for reply. Why is there a minus sign in Schwartz inequality? Isn't it [itex]\sqrt{ ( A^{ 0 }{}_{ i } )^{ 2 } ( B^{ i }{}_{ 0 } )^{ 2 } } \geq |A^{ 0 }{}_{ i } \ B^{ i }{}_{ 0 }|[/itex]?
OK, I see now that I got confused by the notation. The inequality that samalkhaiat wrote down is an almost immediate consequence of Cauchy-Schwartz for vectors in ##\mathbb R^3##. If we use your inequality from the quote above, and then use that ##|x|\geq -x## for all real numbers x,...

Regarding notational conventions: Some people would write ##x_i x_i## rather than ##(x_i)^2## to ensure that the index to be summed over explicitly appears twice, but I suppose that can be weird too when we use a convention that typically has one of the indices upstairs and the other downstairs. I would denote the component on row ##\mu##, column ##\nu## of an arbitrary matrix X by ##X_{\mu\nu}##, ##X^\mu_\nu## or ##X^\mu{}_\nu##. Samalkhaiat apparently uses ##X^\nu{}_\mu##. That's fine too. As he said, "choose any convention you like and stick with it".