While powerful tools have been developed to analyze quantum query complexity, there are still many natural problems that do not fit neatly into the black box model of oracles. We create a new model that allows multiple oracles with differing costs. T
his model captures more of the difficulty of certain natural problems. We test this model on a simple problem, Search with Two Oracles, for which we create a quantum algorithm that we prove is asymptotically optimal. We further give some evidence, using a geometric picture of Grovers algorithm, that our algorithm is exactly optimal.
Agile Software Development (ASD) methodology has become widely used in the industry. Understanding the challenges facing software engineering students is important to designing effective training methods to equip students with proper skills required
for effectively using the ASD techniques. Existing empirical research mostly focused on eXtreme Programming (XP) based ASD methodologies. There is a lack of empirical studies about Scrum-based ASD programming which has become the most popular agile methodology among industry practitioners. In this paper, we present empirical findings regarding the aspects of task allocation decision-making, collaboration, and team morale related to the Scrum ASD process which have not yet been well studied by existing research. We draw our findings from a 12 week long course work project in 2014 involving 125 undergraduate software engineering students from a renowned university working in 21 Scrum teams. Instead of the traditional survey or interview based methods, which suffer from limitations in scale and level of details, we obtain fine grained data through logging students activities in our online agile project management (APM) platform - HASE. During this study, the platform logged over 10,000 ASD activities. Deviating from existing preconceptions, our results suggest negative correlations between collaboration and team performance as well as team morale.
For software development companies, one of the most important objectives is to identify and acquire talented software engineers in order to maintain a skilled team that can produce competitive products. Traditional approaches for finding talented you
ng software engineers are mainly through programming contests of various forms which mostly test participants programming skills. However, successful software engineering in practice requires a wider range of skills from team members including analysis, design, programming, testing, communication, collaboration, and self-management, etc. In this paper, we explore potential ways to identify talented software engineering students in a data-driven manner through an Agile Project Management (APM) platform. Through our proposed HASE online APM tool, we conducted a study involving 21 Scrum teams consisting of over 100 undergraduate software engineering students in multi-week coursework projects in 2014. During this study, students performed over 10,000 ASD activities logged by HASE. We demonstrate the possibility and potentials of this new research direction, and discuss its implications for software engineering education and industry recruitment.
Inspired by the Elitzur-Vaidman bomb testing problem [arXiv:hep-th/9305002], we introduce a new query complexity model, which we call bomb query complexity $B(f)$. We investigate its relationship with the usual quantum query complexity $Q(f)$, and sh
ow that $B(f)=Theta(Q(f)^2)$. This result gives a new method to upper bound the quantum query complexity: we give a method of finding bomb query algorithms from classical algorithms, which then provide nonconstructive upper bounds on $Q(f)=Theta(sqrt{B(f)})$. We subsequently were able to give explicit quantum algorithms matching our upper bound method. We apply this method on the single-source shortest paths problem on unweighted graphs, obtaining an algorithm with $O(n^{1.5})$ quantum query complexity, improving the best known algorithm of $O(n^{1.5}sqrt{log n})$ [arXiv:quant-ph/0606127]. Applying this method to the maximum bipartite matching problem gives an $O(n^{1.75})$ algorithm, improving the best known trivial $O(n^2)$ upper bound.
Brightest Cluster Galaxies (BCGs) are mostly elliptical galaxies and very rarely have prominent star formation. We found that five out of 8,812 BCGs are E+A (i.e. post-starburst) galaxies, having the H$delta$~absorption line with an equivalent width
$>2.5AA$ and no distinct emission lines in [O II] and H$alpha$. The E+A features we identified from the BCGs for the first time are not as significant as those in general galaxies, indicating that historically the star formation were not very violent.
We report the discovery of 4 strong gravitational lensing systems by visual inspections of the Sloan Digital Sky Survey images of galaxy clusters in Data Release 6 (SDSS DR6). Two of the four systems show Einstein rings while the others show tangenti
al giant arcs. These arcs or rings have large angular separations (>8) from the bright central galaxies and show bluer color compared with the red cluster galaxies. In addition, we found 5 probable and 4 possible lenses by galaxy clusters.
