## Sunday, July 03, 2005

### depth of KMW-T and oracles

Suppose an oracle tells us that the depth of the KMW-T is 1. How can we verify that? by finding the witness vector or separation vector. which one??
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If we generalize the idea of the oracle further and say that we can verify in some time T \in POLY(n,m,d,max-distance), whether the KMW-T has depth is k or not. Suppose an oracle tells us that the depth of the KMW-T is <= k. A (binary?) search across k would give us the certificate to verify the statement. This would take the running time of the algorithm to be T * log k. How can we do better?
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to do:
• Get the definitions of witness and separation vectors (of various kinds).
• understand the concepts of independent sub-space and maximal independent subspace.
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Prime and composite nodes: In the previous post, there were a couple of analogies between the different decomposition trees. Let us call a leaf of a decomposition tree prime, if it is annotated with a component which is a node of the original graph. Otherwise, call the leaf as composite. The whole problem of ZC-detection is but seeing if there exists a composite node.
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Define an edge casting a shadow on another component if the edge is in the maximal independent subspace of the component????? So, can we begin with a node and keep adding edges to it till we detect a ZC?
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To do: get the idea of maximal independent subspace and difference between the witness and certificate of CM-Z.
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Top-down decomposition Vs. Bottom-up construction: How to unify two components?
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To-do: understand the KMW-EX with depth of 1 and 2. how and why are the depths of that size.
to-do: frame a LP program which takes a two connected components and returns a parent node with a certificate. Suppose we want to add a third node which is in the same strongly connected component as these two, it need not have a parent which is different from these two. It can be attached to the same parent as the original. The certificate stored at the parent may or maynot change.
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The KMW-EX -577 is very useful to know about the longest paths. Visalize a bounding box, with nodes of two colors and the dependences. If there is a circuit in G^\infty, there is a loop in the PRDG.
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The memory optimization by building through subspaces and simultaneously increasing the "range" of subspaces.