Simulating the evolution of Markovian open quantum systems on quantum computers

Simulating the evolution of quantum systems becomes one of the most appealing tasks researchers hope to perform when small quantum computers are emerging. The simulation of Hamiltonian evolution has been well studied in previous results: the best known gate complexity is $O(t\,\polylog(t/\epsilon))$, where $t$ is the evolution time and $\epsilon$ is the precision. In this talk, we consider simulating the evolution of a class of more generalized systems: the Markovian open quantum systems (a.k.a Lindblad evolution).

Entanglement transformation and the structure of matrix space

Entanglement is arguably the most important physical resources in quantum information processing, and a fundamental task is to transform a multipartite entangled pure state into a bipartite entangled pure state shared between two specific parties. In this talk, we study the following scenario: given a pure tripartite state shared by Alice, Bob and Charlie, what kind of pure bipartite entangled state can be recovered with a nonzero probability by Alice and Bob with the help of Charlie under local operations and classical communication (a.k.a. SLOCC transformation)?

Complexity, Quantum Field Theory, and Black Holes

Drawing on recent advances, I will discuss the circuit complexity of preparing ground states and thermal states of a variety of quantum many-body systems whose low energy physics is well described by a quantum field theory. I will then argue that the structure of the relevant circuits is such that they may be implementable on near term quantum devices. Finally, I will discuss how these ideas may be used to simulate aspects of black holes and quantum gravity.

*This talk is part of the Computational Complexity and High Energy Physics Workshop*

On the Relationship between Lower Bound Methods in Communication Complexity

Communication complexity studies the minimum number of bits distributed parties must communicate in order to perform some joint computation. In the restricted model of communication complexity, unconditional lower bounds can be proven, leading to hardness results for many other problems of interest in computer science. Over the past few decades, numerous lower bound methods have been introduced. Present work aims to unify these lower bounds through linear programming and characterize the relationship between them.

Pure state tomography with Pauli observables

Pure-state tomography requires expectation values on the order of the system’s dimension, a quadratic improvement compared to general tomography. We seek to understand the number of expectation values necessary to uniquely determine all pure states, with the additional restriction that we consider only the expectation values of Pauli observables. Applying results from classical computer science, we reduce this question to an instance of the hypergraph dualization problem, yielding a conjectured upper bound on the necessary number of expectation values.

Full and efficient characterisation of non-Markovian quantum processes

In science, we often want to characterise dynamical processes to identify the underlying physics and predict the future states of the system. If the state of the system at any time depends only on the state of the system at the previous time-step and some predetermined rule then the dynamics are characterised with relative ease. For instance, the dynamics of quantum mechanical systems in isolation is described in this way. However, when a quantum system repeatedly interact with an environment, the environment oft

Josephson Junction Arrays in Circuit QED Architecture

Understanding and engineering of quantum many-body systems is a big challenge in quantum physics and quantum information processing. Studies in artificial quantum many-body systems with well-controlled parameters should play a central role for that purpose. One of the promising platforms for realizing an artificial quantum many-body system is a Josephson junction array (JJA).