Towards Self-Correcting Quantum Memories

Abstract

This thesis presents a model of self-correcting quantum memories where quantum states are encoded using topological stabilizer codes and error correction is done using local measurements and local dynamics. Quantum noise poses a practical barrier to developing quantum memories. This thesis explores two types of models for suppressing noise. One model suppresses thermalizing noise energetically by engineering a Hamiltonian with a high energy barrier between code states. Thermalizing dynamics are modeled phenomenologically as a Markovian quantum master equation with only local generators. The second model suppresses stochastic noise with a cellular automaton that performs error correction using syndrome measurements and a local update rule. Several ways of visualizing and thinking about stabilizer codes are presented in order to design ones that have a high energy barrier: the non-local Ising model, the quasi-particle graph and the theory of welded stabilizer codes. I develop the theory of welded stabilizer codes and use it to construct a code with the highest known energy barrier in 3-d for spin Hamiltonians: the welded solid code. Although the welded solid code is not fully self correcting, it has some self correcting properties. It has an increased memory lifetime for an increased system size up to a temperature dependent maximum. One strategy for increasing the energy barrier is by mediating an interaction with an external system. I prove a no-go theorem for a class of Hamiltonians where the interaction terms are local, of bounded strength and commute with the stabilizer group. Under these conditions the energy barrier can only be increased by a multiplicative constant. I develop cellular automaton to do error correction on a state encoded using the toric code. The numerical evidence indicates that while there is no threshold, the model can extend the memory lifetime significantly. While of less theoretical importance, this could be practical for real implementations of quantum memories. Numerical evidence also suggests that the cellular automaton could function as a decoder with a soft threshold.