Floquet engineering in superconducting circuits: from arbitrary spin-spin interactions to the Kitaev honeycomb model

We derive a theory for the generation of arbitrary spin-spin interactions in superconducting circuits via periodic time modulation of the individual qubits or the qubit-qubit interactions. The modulation frequencies in our approach are in the microwave or radio frequency regime so that the required fields can be generated with standard generators. Among others, our approach is suitable for generating spin lattices that exhibit quantum spin liquid behavior such as Kitaev's honeycomb model.Comment: 21 pages, 9 figure

Matrix Theory for the DLCQ of Type IIB String Theory on the AdS/Plane-wave

We propose a recipe to construct the DLCQ Hamiltonian of type IIB string theory on the AdS (and/or plane-wave) background. We consider a system of J number of coincident unstable non-BPS D0-branes of IIB theory in the light-cone gauge and on the plane-wave background with a compact null direction, the dynamics of which is described by the world-line U(J) gauge theory. This configuration suffers from tachyonic instabilities. Having instabilities been cured through the process of open string tachyon condensation, by expanding the theory about true minima of the effective potential and furthermore taking low energy limit to decouple the heavy modes, we end up with a 0+1-dimensional supersymmetric U(J) gauge theory, a Matrix Theory. We conjecture that the Hamiltonian of this Matrix Theory is just the DLCQ Hamiltonian of type IIB string theory on the AdS or equivalently plane-wave background in a sector with J units of light-cone momentum. We present some pieces of evidence in support of the proposal.Comment: LaTeX, 35 pages, 2 eps figures; v2: minor changes, references added; v3: minor change

Discrete Adaptive Second Order Sliding Mode Controller Design with Application to Automotive Control Systems with Model Uncertainties

Sliding mode control (SMC) is a robust and computationally efficient solution for tracking control problems of highly nonlinear systems with a great deal of uncertainty. High frequency oscillations due to chattering phenomena and sensitivity to data sampling imprecisions limit the digital implementation of conventional first order continuous-time SMC. Higher order discrete SMC is an effective solution to reduce the chattering during the controller software implementation, and also overcome imprecisions due to data sampling. In this paper, a new adaptive second order discrete sliding mode control (DSMC) formulation is presented to mitigate data sampling imprecisions and uncertainties within the modeled plant's dynamics. The adaptation mechanism is derived based on a Lyapunov stability argument which guarantees asymptotic stability of the closed-loop system. The proposed controller is designed and tested on a highly nonlinear combustion engine tracking control problem. The simulation test results show that the second order DSMC can improve the tracking performance up to 80% compared to a first order DSMC under sampling and model uncertainties.Comment: 6 pages, 6 figures, 2017 American Control Conferenc

Reliability Analysis of Complex NASA Systems with Model-Based Engineering

The emergence of model-based engineering, with Model- Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. The recognized benefits to systems development include moving from document-centric information systems and document-centric project communication to a model-centric environment in which control of design changes in the life cycles is facilitated. In addition, a single source of truth about the system, that is up-to-date in all respects of the design, becomes the authoritative source of data and information about the system. This promotes consistency and efficiency in regard to integration of the system elements as the design emerges and thereby may further optimize the design. Therefore Reliability Engineers (REs) supporting NASA missions must be integrated into model-based engineering to ensure the outputs of their analyses are relevant and value-needed to the design, development, and operational processes for failure risks assessment and communication