Feshbach Resonances and Medium Effects in ultracold atomic Gases

We develop an effective low energy theory for multi-channel scattering of cold atomic alkali atoms with particular focus on Feshbach resonances. The scattering matrix is expressed in terms of observables only and the theory allows for the inclusion of many-body effects both in the open and in the closed channels. We then consider the frequency and damping of collective modes for Fermi gases and demonstrate how medium effects significantly increase the scattering rate determining the nature of the modes. Our results obtained with no fitting parameters are shown to compare well with experimental data.Comment: Presented at the 5th workshop on Critical Stability, Erice, Italy 13-17 October 2008. 8 pages, 3 figures. Figure caption correcte

Hitchhikers Need Free Vehicles! Shared Repositories for Statistical Analysis in SBST

As a means for improving the maturity of the data analysis methods used in the search-based software testing field, this paper presents the need for shared repositories of well-documented statistical analysis code and replication data. In addition to explaining the benefits associated with using these repositories, the paper gives suggestions (e.g., the testing of analysis code) for improving the study of data arising from experiments with randomized algorithms

Automatic detection and removal of ineffective mutants for the mutation analysis of relational database schemas

Data is one of an organization’s most valuable and strategic assets. Testing the relational database schema, which protects the integrity of this data, is of paramount importance. Mutation analysis is a means of estimating the fault-finding “strength” of a test suite. As with program mutation, however, relational database schema mutation results in many “ineffective” mutants that both degrade test suite quality estimates and make mutation analysis more time consuming. This paper presents a taxonomy of ineffective mutants for relational database schemas, summarizing the root causes of ineffectiveness with a series of key patterns evident in database schemas. On the basis of these, we introduce algorithms that automatically detect and remove ineffective mutants. In an experimental study involving the mutation analysis of 34 schemas used with three popular relational database management systems—HyperSQL, PostgreSQL, and SQLite—the results show that our algorithms can identify and discard large numbers of ineffective mutants that can account for up to 24% of mutants, leading to a change in mutation score for 33 out of 34 schemas. The tests for seven schemas were found to achieve 100% scores, indicating that they were capable of detecting and killing all non-equivalent mutants. The results also reveal that the execution cost of mutation analysis may be significantly reduced, especially with “heavyweight” DBMSs like PostgreSQL

SchemaAnalyst: Search-Based Test Data Generation for Relational Database Schemas

Data stored in relational databases plays a vital role in many aspects of society. When this data is incorrect, the services that depend on it may be compromised. The database schema is the artefact responsible for maintaining the integrity of stored data. Because of its critical function, the proper testing of the database schema is a task of great importance. Employing a search-based approach to generate high-quality test data for database schemas, SchemaAnalyst is a tool that supports testing this key software component. This presented tool is extensible and includes both an evaluation framework for assessing the quality of the generated tests and full-featured documentation. In addition to describing the design and implementation of SchemaAnalyst and overviewing its efficiency and effectiveness, this paper coincides with the tool’s public release, thereby enhancing practitioners’ ability to test relational database schemas

Template coexistence in prebiotic vesicle models

The coexistence of distinct templates is a common feature of the diverse proposals advanced to resolve the information crisis of prebiotic evolution. However, achieving robust template coexistence turned out to be such a difficult demand that only a class of models, the so-called package models, seems to have met it so far. Here we apply Wright's Island formulation of group selection to study the conditions for the coexistence of two distinct template types confined in packages (vesicles) of finite capacity. In particular, we show how selection acting at the level of the vesicles can neutralize the pressures towards the fixation of any one of the template types (random drift) and of the type with higher replication rate (deterministic competition). We give emphasis to the role of the distinct generation times of templates and vesicles as yet another obstacle to coexistence.Comment: 7 pages, 8 figure

Interpolatory methods for H∞\mathcal{H}_\infty model reduction of multi-input/multi-output systems

We develop here a computationally effective approach for producing high-quality $\mathcal{H}_\infty$-approximations to large scale linear dynamical systems having multiple inputs and multiple outputs (MIMO). We extend an approach for $\mathcal{H}_\infty$ model reduction introduced by Flagg, Beattie, and Gugercin for the single-input/single-output (SISO) setting, which combined ideas originating in interpolatory $\mathcal{H}_2$-optimal model reduction with complex Chebyshev approximation. Retaining this framework, our approach to the MIMO problem has its principal computational cost dominated by (sparse) linear solves, and so it can remain an effective strategy in many large-scale settings. We are able to avoid computationally demanding $\mathcal{H}_\infty$ norm calculations that are normally required to monitor progress within each optimization cycle through the use of "data-driven" rational approximations that are built upon previously computed function samples. Numerical examples are included that illustrate our approach. We produce high fidelity reduced models having consistently better $\mathcal{H}_\infty$ performance than models produced via balanced truncation; these models often are as good as (and occasionally better than) models produced using optimal Hankel norm approximation as well. In all cases considered, the method described here produces reduced models at far lower cost than is possible with either balanced truncation or optimal Hankel norm approximation

Faster Approximate String Matching for Short Patterns

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have lengths $m$ and $n$, respectively. On a standard unit-cost word RAM with word size $w \geq \log n$ we present an algorithm using time $$O(nk \cdot \min(\frac{\log^2 m}{\log n},\frac{\log^2 m\log w}{w}) + n)$$ When $P$ is short, namely, $m = 2^{o(\sqrt{\log n})}$ or $m = 2^{o(\sqrt{w/\log w})}$ this improves the previously best known time bounds for the problem. The result is achieved using a novel implementation of the Landau-Vishkin algorithm based on tabulation and word-level parallelism.Comment: To appear in Theory of Computing System