Optimal Dynamic R&D Programs

We study the optimal pattern of outlays for a single firm pursuing an R&D program over time. In the deterministic case, (a) the amount of progress required to complete the project is known, and (b) the relationship between outlays and progress is known. In this case, it is optimal to increase effort over time as the project nears completion. Relaxing (a), we find in general a simple, positive relationship between the optimal expenditure rate at any point in time and the (expected) value at that time of the research program. We also show that, for a given level ofexpected difficulty, a riskier project is always preferred to a safe project. Relaxing (b), we find again that research outlays increase as further progressis made.

Optimal Locally Repairable Linear Codes

Linear erasure codes with local repairability are desirable for distributed data storage systems. An [n, k, d] code having all-symbol (r, \delta})-locality, denoted as (r, {\delta})a, is considered optimal if it also meets the minimum Hamming distance bound. The existing results on the existence and the construction of optimal (r, {\delta})a codes are limited to only the special case of {\delta} = 2, and to only two small regions within this special case, namely, m = 0 or m >= (v+{\delta}-1) > ({\delta}-1), where m = n mod (r+{\delta}-1) and v = k mod r. This paper investigates the existence conditions and presents deterministic constructive algorithms for optimal (r, {\delta})a codes with general r and {\delta}. First, a structure theorem is derived for general optimal (r, {\delta})a codes which helps illuminate some of their structure properties. Next, the entire problem space with arbitrary n, k, r and {\delta} is divided into eight different cases (regions) with regard to the specific relations of these parameters. For two cases, it is rigorously proved that no optimal (r, {\delta})a could exist. For four other cases the optimal (r, {\delta})a codes are shown to exist, deterministic constructions are proposed and the lower bound on the required field size for these algorithms to work is provided. Our new constructive algorithms not only cover more cases, but for the same cases where previous algorithms exist, the new constructions require a considerably smaller field, which translates to potentially lower computational complexity. Our findings substantially enriches the knowledge on (r, {\delta})a codes, leaving only two cases in which the existence of optimal codes are yet to be determined.Comment: Under Revie

Possible Connection between the Optimal Path and Flow in Percolation Clusters

We study the behavior of the optimal path between two sites separated by a distance $r$ on a $d$-dimensional lattice of linear size $L$ with weight assigned to each site. We focus on the strong disorder limit, i.e., when the weight of a single site dominates the sum of the weights along each path. We calculate the probability distribution $P(\ell_{\rm opt}|r,L)$ of the optimal path length $\ell_{\rm opt}$, and find for $r\ll L$ a power law decay with $\ell_{\rm opt}$, characterized by exponent $g_{\rm opt}$. We determine the scaling form of $P(\ell_{\rm opt}|r,L)$ in two- and three-dimensional lattices. To test the conjecture that the optimal paths in strong disorder and flow in percolation clusters belong to the same universality class, we study the tracer path length $\ell_{\rm tr}$ of tracers inside percolation through their probability distribution $P(\ell_{\rm tr}|r,L)$. We find that, because the optimal path is not constrained to belong to a percolation cluster, the two problems are different. However, by constraining the optimal paths to remain inside the percolation clusters in analogy to tracers in percolation, the two problems exhibit similar scaling properties.Comment: Accepted for publication to Physical Review E. 17 Pages, 6 Figures, 1 Tabl