Quantum de Finetti Theorems for Local Measurements

The quantum de Finetti theorem states that subsystems of
symmetric quantum states are close to mixtures of i.i.d. states.
Depending on exactly how "close" is quantified, this theorem can have
many applications to quantum information theory, quantum complexity
theory, and even classical optimization algorithms. However, previous
bounds scaled badly with either dimension or the number of systems.
I'll give an overview of why de Finetti theorems are useful, describe
a way to use information theory to improve existing bounds, and
discuss applications and open problems.

Based on 1210.6367, which is joint work with Fernando Brandao.
Aram Harrow grew up in E. Lansing, MI, before attending MIT for
his undergraduate (math and physics) and graduate (physics) degrees.
He then served as a lecturer in the math and CS departments of the
University of Bristol for five years, and as a research assistant
professor in the University of Washington CS department for two years.
In 2013, he joined the MIT physics department as an assistant
professor.

His research focuses on quantum information theory, quantum algorithms
and quantum complexity, and often seeks to make connections to other
areas of math, physics and theoretical computer science.