Large small sets

Some small large sets of t-designs

Enabling Reproducibility for Small and Large Scale Research Data Sets

A large portion of scientific results is based on analysing and processing research data. In order for an eScience experiment to be reproducible, we need to able to identify precisely the data set which was used in a study. Considering evolving data sources this can be a challenge, as studies often use subsets which have been extracted from a potentially large parent data set. Exporting and sto...

Finding large 3-free sets I: The small n case

There has been much work on the following question: given n, how large can a subset of {1, . . . , n} be that has no arithmetic progressions of length 3. We call such sets 3-free. Most of the work has been asymptotic. In this paper we sketch applications of large 3-free sets, present techniques to find large 3-free sets of {1, . . . , n} for n ≤ 250, and give empirical results obtained by codin...

Small vulnerable sets determine large network cascades in power grids.

The understanding of cascading failures in complex systems has been hindered by the lack of realistic large-scale modeling and analysis that can account for variable system conditions. Using the North American power grid, we identified, quantified, and analyzed the set of network components that are vulnerable to cascading failures under any out of multiple conditions. We show that the vulnerab...

Status Quo Bias in Large and Small Choice Sets∗

This paper introduces models of status quo bias based on the concept of decision avoidance, by which a decision maker may select the status quo in order to avoid a difficult decision. These models capture the experimental finding that the status quo is more frequently chosen in larger choice sets. This phenomenon violates the predictions of current preference-based models of status quo bias tha...