Gundy's decomposition for non-commutative martingales and applications

Mathematics – Operator Algebras

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

25 pages

Scientific paper

We provide an analogue of Gundy's decomposition for L1-bounded non-commutative martingales. An important difference from the classical case is that for any L1-bounded non-commutative martingale, the decomposition consists of four martingales. This is strongly related with the row/column nature of non-commutative Hardy spaces of martingales. As applications, we obtain simpler proofs of the weak type (1,1) boundedness for non-commutative martingale transforms and the non-commutative analogue of Burkholder's weak type inequality for square functions. A sequence (x_n) in a normed space X is called 2-co-lacunary if there exists a bounded linear map from the closed linear span of (x_n) to l2 taking each x_n to the n-th vector basis of l2. We prove (using our decomposition) that any relatively weakly compact martingale difference sequence in L1(M,\tau) whose sequence of norms is bounded away from zero is 2-co-lacunary, generalizing a result of Aldous and Fremlin to non-commutative L1-spaces.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Gundy's decomposition for non-commutative martingales and applications does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Gundy's decomposition for non-commutative martingales and applications, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Gundy's decomposition for non-commutative martingales and applications will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-488993

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.