Analog Property Checkers: A Ddr2 Case Study

The formal specification component of verification can be exported to simulation through the idea of property checkers. The essence of this approach is the automatic construction of an observer from the specification in the form of a program that can be interfaced with a simulator and alert the user if the property is violated by a simulation trace. Although not complete, this lighter approach to formal verification has been effectively used in software and digital hardware to detect errors. Recently, the idea of property checkers has been extended to analog and mixed-signal systems. In this paper, we apply the property-based checking methodology to an industrial and realistic example of a DDR2 memory interface. The properties describing the DDR2 analog behavior are expressed in the formal specification language stl/psl in form of assertions. The simulation traces generated from an actual DDR2 interface design are checked with respect to the stl/psl assertions using the amt tool. The focus of this paper is on the translation of the official (informal and descriptive) specification of two non-trivial DDR2 properties into stl/psl assertions. We study both the benefits and the current limits of such approach

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

We present a collection of optimizers tuned for usage on Noisy Intermediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization (QAOA) algorithms. They are also used for calibration tasks, hyperparameter tuning, in machine learning, etc. We analyze the efficiency and effectiveness of different optimizers in a VQE case study. VQE is a hybrid algorithm, with a classical minimizer step driving the next evaluation on the quantum processor. While most results to date concentrated on tuning the quantum VQE circuit, we show that, in the presence of quantum noise, the classical minimizer step needs to be carefully chosen to obtain correct results. We explore state-of-the-art gradient-free optimizers capable of handling noisy, black-box, cost functions and stress-test them using a quantum circuit simulation environment with noise injection capabilities on individual gates. Our results indicate that specifically tuned optimizers are crucial to obtaining valid science results on NISQ hardware, and will likely remain necessary even for future fault tolerant circuits

Quantum Computing in the NISQ era and beyond

Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass the capabilities of today's classical digital computers, but noise in quantum gates will limit the size of quantum circuits that can be executed reliably. NISQ devices will be useful tools for exploring many-body quantum physics, and may have other useful applications, but the 100-qubit quantum computer will not change the world right away --- we should regard it as a significant step toward the more powerful quantum technologies of the future. Quantum technologists should continue to strive for more accurate quantum gates and, eventually, fully fault-tolerant quantum computing.Comment: 20 pages. Based on a Keynote Address at Quantum Computing for Business, 5 December 2017. (v3) Formatted for publication in Quantum, minor revision

Errors in scalable quantum Computers

A functional quantum computer potentially outperforms any classical machine exponentially in a number of important computational tasks. Therefore, its physical implementation has to scale efficiently in the number of qubits, specifically in tasks such as treatment of external error sources. Due to the intrinsic complexity and limited accessibility of quantum systems, the validation of quantum gates is fundamentally difficult. Randomized Benchmarking is a protocol to efficiently assess the average fidelity of only Clifford group gates. In this thesis we present a hybrid of Randomized Benchmarking and Monte Carlo sampling for the validation of arbitrary gates. It improves upon the efficiency of current methods while preserving error amplification and robustness against imperfect measurement, but is still exponentially hard. To achieve polynomial scaling, we introduce a symmetry benchmarking protocol that validates the conservation of inherent symmetries in quantum algorithms instead of gate fidelities. Adiabatic quantum computing is believed to be more robust against environmental effects, which we investigate in the typical regime of a scalable quantum computer using renormalization group theory. We show that a k-local Hamiltonian is in fact robust against environmental influence but multipartite entanglement is limited to combined system-bath state which we conclude to result in a more classical behavior more susceptible to thermal noise.Ein Quantencomputer wäre in einer Reihe wichtiger Berechnungen exponenziell effizienter als klassische Computer, unter Vorraussetzung einer fehlerarmen und skalierbaren Implementierung. Aufgrund der intrinsischen Komplexität und beschränkten Auslesbarkeit von Quantensystemen ist die Validierung von Quantengattern ungleich schwerer als die klassischer. Das Randomized Benchmarking Protokoll leistet dies effizient, ist jedoch beschränkt auf Cliffordgatter. In dieser Arbeit präsentieren wir ein Hybridprotokoll aus Interleaved Randomized Benchmarking und Monte Carlo Sampling zur Validierung von beliebigen Gattern. Trotz Verbesserung gegenüber vergleichbaren Protokollen skalieren die benötigten Ressourcen exponenziell. Um dies zu vermeiden entwickeln wir ein Protokoll, welches die Erhaltung von spezifischen Symmetrien von Quantenalgorithmen untersucht und dadurch Rückschlüsse auf die Fehlerrate der Quantenprozesse zulässt und demonstrieren seine Effizienz an relevanten Beispielen. Der Effekt von Umgebungseinflüssen auf adiabatische Quantencomputer wird als weit weniger gravierend angenommen als im Falle von konventionellen Systemen, ist jedoch im gleichen Maße weniger verstanden. Wir untersuchen diese Effekte mithilfe von Renormalisierungsgruppentheorie und zeigen, dass k-lokale Hamiltonoperatoren robust sind, vielfach verschränkte Zustände hingegen nur verschränkt mit der Umgebung existieren. Wir folgern daraus ein verstärkt thermisches Verhalten des Annealingprozesses.QEO/IARPA, Google, ScaleQI

Constrained Nonlinear Model Predictive Control of an MMA Polymerization Process via Evolutionary Optimization

In this work, a nonlinear model predictive controller is developed for a batch polymerization process. The physical model of the process is parameterized along a desired trajectory resulting in a trajectory linearized piecewise model (a multiple linear model bank) and the parameters are identified for an experimental polymerization reactor. Then, a multiple model adaptive predictive controller is designed for thermal trajectory tracking of the MMA polymerization. The input control signal to the process is constrained by the maximum thermal power provided by the heaters. The constrained optimization in the model predictive controller is solved via genetic algorithms to minimize a DMC cost function in each sampling interval.Comment: 12 pages, 9 figures, 28 reference

Development of Hybrid PS-FW GMPPT Algorithm for improving PV System Performance Under Partial Shading Conditions

A global maximum power point tracking (MPPT) algorithm hybrid based on Particle Swarm Fireworks (PS-FW) algorithm is proposed which is formed with Particle Swarm Optimization and Fireworks Algorithm. The algorithm tracks the global maximum power point (MPP) when conventional MPPT methods fail due to occurrence of partial shading conditions. With the applied strategies and operators, PS-FW algorithm obtains superior performances verified under simulation and experimental setup with multiple cases of shading patterns

Hybrid Energy Storage Systems for UAV Applications

Energy storage constraints limit the range and endurance of electric based unmanned aerial vehicles (UAVs). Solving the energy storage problem allows the adoption of UAVs on a much wider scale. A solution to the problem would ideally retain the significant performance and efficiency benefits of the electric based propulsion system. The contents of this study focused on solving the energy storage problem through research, experiment, and simulation based testing of the application of hybrid energy storage systems (HESS) to existing UAV designs. A review of literature was done exploring existing and future applications of electric based aircraft propulsion systems. Research was conducted on current energy storage technology limitations and potential hybrid energy storage design solutions. The solution allows bridging the gap to full adoption of electric propulsion. After extensive research, a passively controlled hybrid battery and supercapacitor configuration was chosen for experimental and simulation based evaluations. The experiment and simulation tested for key battery performance improvements using the HESS and its applicability to UAV designs. Results showed a significant reduction to the peak amperage and peak temperature of the battery under identical load profiles. The experimentally tested passive HESS did not show a reduction in energy consumption, but the active HESS simulation results did. The simulation results showed a theoretical gain of 8.8% for state of charge (SOC) for the battery. Equating the SOC to range improvement, a 10% increase in range was possible for the UAV tested