This paper concerns the associative lower central series ideals M i of the free algebra A n on n generators. Namely, we study the successive quotients N i = M i /M i+1 , which admit an action of the Lie algebra W n of vector fields on C n . We bound the degree |λ| of tensor field modules F λ appearing in the Jordan-Hölder series of each N i , confirming a recent conjecture of Arbesfeld and Jordan. As an application, we compute these decompositions for small n and i.
Let Z = (Z t ) t≥0 be the Rosenblatt process with Hurst index H ∈ (1/2, 1). We prove joint continuity for the local time of Z, and establish Hölder conditions for the local time. These results are then used to study the irregularity of the sample paths of Z. Based on analogy with similar known results in the case of fractional Brownian motion, we believe our results are sharp. A main ingredient of our proof is a rather delicate spectral analysis of arbitrary linear combinations of integral operators, which arise from the representation of the Rosenblatt process as an element in the second chaos.
Let (X, Y ) = (Xn, Yn) n≥1 be the output process generated by a hidden chainaperiodic, time homogeneous, and irreducible Markov chain. Let LCn be the length of the longest common subsequences of X1, . . . , Xn and Y1, . . . , Yn. Under a mixing hypothesis, a rate of convergence result is obtained for E[LCn]/n.
The paper concerns the image, level and sojourn time sets associated with sample paths of the Rosenblatt process. We obtain results regarding the Hausdorff (both classical and macroscopic), packing and intermediate dimensions, and the logarithmic and pixel densities. As a preliminary step we also establish the time inversion property of the Rosenblatt process, as well as some technical points regarding the distribution of Z.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.