An Open-System Quantum Simulator with Trapped Ions

The control of quantum systems is of fundamental scientific interest and promises powerful applications and technologies. Impressive progress has been achieved in isolating the systems from the environment and coherently controlling their dynamics, as demonstrated by the creation and manipulation of entanglement in various physical systems. However, for open quantum systems, engineering the dynamics of many particles by a controlled coupling to an environment remains largely unexplored. Here we report the first realization of a toolbox for simulating an open quantum system with up to five qubits. Using a quantum computing architecture with trapped ions, we combine multi-qubit gates with optical pumping to implement coherent operations and dissipative processes. We illustrate this engineering by the dissipative preparation of entangled states, the simulation of coherent many-body spin interactions and the quantum non-demolition measurement of multi-qubit observables. By adding controlled dissipation to coherent operations, this work offers novel prospects for open-system quantum simulation and computation.Comment: Pre-review submission to Nature. For an updated and final version see publication. Manuscript + Supplementary Informatio

Wigner crystals of ions as quantum hard drives

Atomic systems in regular lattices are intriguing systems for implementing ideas in quantum simulation and information processing. Focusing on laser cooled ions forming Wigner crystals in Penning traps, we find a robust and simple approach to engineering non-trivial 2-body interactions sufficient for universal quantum computation. We then consider extensions of our approach to the fast generation of large cluster states, and a non-local architecture using an asymmetric entanglement generation procedure between a Penning trap system and well-established linear Paul trap designs.Comment: 5 pages, 4 figure

Distributed environmental control

We present an architecture of distributed, independent control agents designed to work with the Computer Aided System Engineering and Analysis (CASE/A) simulation tool. CASE/A simulates behavior of Environmental Control and Life Support Systems (ECLSS). We describe a lattice of agents capable of distributed sensing and overcoming certain sensor and effector failures. We address how the architecture can achieve the coordinating functions of a hierarchical command structure while maintaining the robustness and flexibility of independent agents. These agents work between the time steps of the CASE/A simulation tool to arrive at command decisions based on the state variables maintained by CASE/A. Control is evaluated according to both effectiveness (e.g., how well temperature was maintained) and resource utilization (the amount of power and materials used)

Relational oriented systems engineering framework for flight training

The integration of systems of systems (SoS) associated with a flight training mission directly reflects the problem of developing a system engineering process for the design of live, virtual and constructive (LVC) experiments. Due to the complexity and disparity of the technology in a flight training SoS (FTSoS), modeling and analysis of architecture is becoming increasingly important. Relational Oriented Systems Engineering (ROSE) methodology is used to develop a framework for simulation and analysis of a navigational SoS for a typical aircraft. The framework can be used for both the prescription of navigation systems entering and exiting the SoS and for the analysis of pilot behavior as navigation quality of service (QoS) changes. ROSE offers a novel approach to developing a model-based systems engineering (MBSE) process for simulation and analysis of a complex SoS problem

Simulation architecture definition for complex systems design: A tooled methodology

International audienceFor the design of complex systems like in the automotive industry, the use of Model Based Systems Engineering (MBSE) is being considered as a promising solution in order to formalize and communicate information. Numerical simulation is also routinely used as a tool to answer potential design questions that arise. However the link between MBSE and simulation still needs further improvement. In this work, a tooled methodology is proposed in order to enhance the link between system architecture and numerical simulation. In a first step, a solicitation package is formalized and implemented in a SysML-based tool to define the simulation needs. In a second step, a tool that allows to define the simulation architecture and to pilot the execution of the simulation is developed. We show that thanks to the proposed process and exchange format between the system and simulation architects, model reuse and agility is improved in a complex systems design

A domain decomposing parallel sparse linear system solver

The solution of large sparse linear systems is often the most time-consuming part of many science and engineering applications. Computational fluid dynamics, circuit simulation, power network analysis, and material science are just a few examples of the application areas in which large sparse linear systems need to be solved effectively. In this paper we introduce a new parallel hybrid sparse linear system solver for distributed memory architectures that contains both direct and iterative components. We show that by using our solver one can alleviate the drawbacks of direct and iterative solvers, achieving better scalability than with direct solvers and more robustness than with classical preconditioned iterative solvers. Comparisons to well-known direct and iterative solvers on a parallel architecture are provided.Comment: To appear in Journal of Computational and Applied Mathematic

Parametric CubeSat flight simulation architecture

This paper presents the architecture of a system of models that provides realistic simulation of the dynamic, in-orbit behaviour of a CubeSat. Time-dependent relationships between sub-systems and between the satellite and external nodes (ground stations and celestial bodies) are captured through numerical analysis of a multi-disciplinary set of state variables including position, attitude, stored energy, stored data and system temperature. Model-Based Systems Engineering and parametric modelling techniques are employed throughout to help visualise the models and ensure flexibility and expandability. Operational mode states are also incorporated within the design, allowing the systems engineer to assess flight behaviour over a range of mission scenarios. Finally, both long and short term dynamics are captured using a coupled-model philosophy; described as Lifetime and Operations models. An example mission is analysed and preliminary results are presented as an illustration of early capabilities