MICROWAVE: A GENERIC FRAMEWORK FOR MICRO SIMULATIONBASED EX ANTE POLICY EVALUATION

This paper presents the MicroWave approach that has been developed to improve the process of modeling in the context of micro simulation. It leads to a more efficient model development, better quality of models and their output and improvement in knowledge management. A conceptual framework has been developed and translated into a hierarchical structure of GAMS program code. Besides, several software applications and other tools have been developed for support. These products are presented and some examples illustrate how MicroWave can be applied. MicroWave is especially useful in interdisciplinary research in which different persons are involved in the modeling process and when different models have to be combined.Research Methods/ Statistical Methods,

Verified AIG Algorithms in ACL2

And-Inverter Graphs (AIGs) are a popular way to represent Boolean functions (like circuits). AIG simplification algorithms can dramatically reduce an AIG, and play an important role in modern hardware verification tools like equivalence checkers. In practice, these tricky algorithms are implemented with optimized C or C++ routines with no guarantee of correctness. Meanwhile, many interactive theorem provers can now employ SAT or SMT solvers to automatically solve finite goals, but no theorem prover makes use of these advanced, AIG-based approaches. We have developed two ways to represent AIGs within the ACL2 theorem prover. One representation, Hons-AIGs, is especially convenient to use and reason about. The other, Aignet, is the opposite; it is styled after modern AIG packages and allows for efficient algorithms. We have implemented functions for converting between these representations, random vector simulation, conversion to CNF, etc., and developed reasoning strategies for verifying these algorithms. Aside from these contributions towards verifying AIG algorithms, this work has an immediate, practical benefit for ACL2 users who are using GL to bit-blast finite ACL2 theorems: they can now optionally trust an off-the-shelf SAT solver to carry out the proof, instead of using the built-in BDD package. Looking to the future, it is a first step toward implementing verified AIG simplification algorithms that might further improve GL performance.Comment: In Proceedings ACL2 2013, arXiv:1304.712

Service-sector competition, innovation and R&D

The central prediction of the Aghion et al. (2005) model is an inverted U-shaped relation between innovation and competition. The model is built on the assumption of a product market and has not yet been empirically tested on service-sector firms. Using detailed firm-level data, we find the inverse U-shaped relation to hold for both small and large service-sector firms. However, non-exporting service firms deviate from the overall pattern. A more detailed breakdown of innovation expenditures shows that the inverse U-shaped pattern holds for both intramural R&D and training, but not for extramural R&D. Finally, as competition increases, small firms tend to seek more strategic alliances with competitors while large firms tend to decrease their collaboration with competitors. To some extent, the behavior of large firms can be due to their greater capacity to handle innovation projects internally and as competition increases, so does the payoff of an edge to competitors.R&D; innovation; competition; service sector

From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

The next few years will be exciting as prototype universal quantum processors emerge, enabling implementation of a wider variety of algorithms. Of particular interest are quantum heuristics, which require experimentation on quantum hardware for their evaluation, and which have the potential to significantly expand the breadth of quantum computing applications. A leading candidate is Farhi et al.'s Quantum Approximate Optimization Algorithm, which alternates between applying a cost-function-based Hamiltonian and a mixing Hamiltonian. Here, we extend this framework to allow alternation between more general families of operators. The essence of this extension, the Quantum Alternating Operator Ansatz, is the consideration of general parametrized families of unitaries rather than only those corresponding to the time-evolution under a fixed local Hamiltonian for a time specified by the parameter. This ansatz supports the representation of a larger, and potentially more useful, set of states than the original formulation, with potential long-term impact on a broad array of application areas. For cases that call for mixing only within a desired subspace, refocusing on unitaries rather than Hamiltonians enables more efficiently implementable mixers than was possible in the original framework. Such mixers are particularly useful for optimization problems with hard constraints that must always be satisfied, defining a feasible subspace, and soft constraints whose violation we wish to minimize. More efficient implementation enables earlier experimental exploration of an alternating operator approach to a wide variety of approximate optimization, exact optimization, and sampling problems. Here, we introduce the Quantum Alternating Operator Ansatz, lay out design criteria for mixing operators, detail mappings for eight problems, and provide brief descriptions of mappings for diverse problems.Comment: 51 pages, 2 figures. Revised to match journal pape

Characterization of pure quantum states of multiple qubits using the Groverian entanglement measure

The Groverian entanglement measure, G(psi), is applied to characterize a variety of pure quantum states |psi> of multiple qubits. The Groverian measure is calculated analytically for certain states of high symmetry, while for arbitrary states it is evaluated using a numerical procedure. In particular, it is calculated for the class of Greenberger-Horne-Zeilinger states, the W states as well as for random pure states of n qubits. The entanglement generated by Grover's algorithm is evaluated by calculating G(psi) for the intermediate states that are obtained after t Grover iterations, for various initial states and for different sets of the marked states.Comment: 28 pages, 5 figure