Date of Award


Document Type

Thesis (Undergraduate)


Department of Computer Science

First Advisor

Amit Chakrabarti


Sensitivity and block sensitivity are useful and well-studied measures of computational complexity, but in spite of their similarities, the largest possible gap between them is still unknown. Rubinstein showed that this gap must be at least quadratic, and Kenyon and Kutin showed that it is at worst exponential, but many strongly suspect that the gap is indeed quadratic, or at worst polynomial. Our work shows that for a large class of functions, which includes Rubinstein's function, the quadratic gap between sensitivity and block sensitivity is the best we can possibly do.


Originally posted in the Dartmouth College Computer Science Technical Report Series, number TR2010-673.