Quantum Information

In this talk I will expose different results concerning the properties of quantum many-body systems: on the one hand, I will introduce the concept of fine-grained entanglement loss together with its relation with majorization relations along parameter flows and Renormalization Group flows. The machinery of Conformal Field Theory will allow us to derive very general analytical properties, and some examples -like the XY quantum spin chain- will also be considered. On the other hand, I will describe results concerning the classical simulability of quantum many-body systems by means of Matrix Product States. In particular, I will present an approximated classical simulation of a quantum algorithm by adiabatic evolution solving hard instances of an NP-Complete problem up to 100 qubits.

I will discuss the design of degenerate quantum error correcting codes for an arbitrary Pauli channel. At noise levels slightly beyond those for which a random stabilizer code does not allow high fidelity transmission with a nonzero rate, our codes usually have a rate which is strictly positive. In fact, there exist Pauli channels for which our codes outperform a random stabilizer code whenever the random coding rate is less than 0.04, which is a couple of orders of magnitude larger than the previous examples of this effect. I'll also present a fairly straightforward explanation of why these codes work and discuss how their performance scales with block size and what this scaling suggests even better codes will look like.

The concept of entanglement plays a central role in the field of strongly correlated quantum systems: it gives rise to fascinating phenomena such as quantum phase transitions and topological quantum order, but also represents a main obstacle to our ability to simulate such systems. We will discuss some new developments in which ideas, originating from the field of quantum information theory, led to valuable insights into the structure of entanglement in quantum spin systems and to novel powerful simulation methods