Noise resilience and entanglement evolution in two nonequivalent classes of quantum algorithms

The speedup provided by quantum algorithms with respect to their classical counterparts is at the origin of scientific interest in quantum computation. However, the fundamental reasons for such a speedup are not yet completely understood and deserve further attention. In this context, the classical simulation of quantum algorithms is a useful tool that can help us in gaining insight. Starting from the study of general conditions for classical simulation, we highlight several important differences between two nonequivalent classes of quantum algorithms. We investigate their performance under realistic conditions by quantitatively studying their resilience with respect to static noise. This latter refers to errors affecting the initial preparation of the register used to run an algorithm. We also compare the evolution of the entanglement involved in the different computational processes.

Evolutionary agglomeration theory: increasing returns, diminishing returns, and the industry life cycle

According to Marshall’s agglomeration theory, Krugman’s New Economic Geography models, and Porter’s cluster policies, firms should receive increasing returns from a trinity of agglomeration economies: a local pool of skilled labour, local supplier linkages, and local knowledge spillovers. Recent evolutionary theories suggest that whether agglomeration economies generate increasing returns or diminishing returns depends on time, and especially the evolution of the industry life cycle. At the start of the twenty-first century, we re-examine Marshall’s trinity of agglomeration economies in the city-region where he discovered them. The econometric results from our multivariate regression models are the polar opposite of Marshall’s. During the later stages of the industry life cycle, Marshall’s agglomeration economies decrease the economic performance of firms and create widespread diminishing returns for the economic development of the city-region, which has evolved to become one of the poorest city-regions in Europe.

Analysis of Receiver Algorithms for LTE SC-FDMA Based Uplink MIMO Systems

This letter derives mathematical expressions for the received signal-to-interference-plus-noise ratio (SINR) of uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) multiuser MIMO systems. An improved frequency domain receiver algorithm is derived for the studied systems, and is shown to be significantly superior to the conventional linear MMSE based receiver in terms of SINR and bit error rate (BER) performance.

High incidence of cryptic repeated elements in microsatellite flanking regions of galatheid genomes and its evolutionary implications

During the development of PCR primer sets for icrosatellite marker loci from enriched genomic libraries for three squat lobster species from Galatheidae (Decapoda: Anomura); Munida rugosa (Fabricius, 1775), M. sarsi (Huus, 1935), and Galathea strigosa (Linnaeus, 1761) (collectively known as squat lobsters), a number of unforeseen problems were encountered. These included PCR amplification failure, lack of amplification consistency, and the amplification of multiple fragments. Careful examination of microsatellite containing sequences revealed the existence of cryptic repeated elements on presumed unique flanking regions. BLAST analysis of these and other VNTR containing sequences (N 5 252) indicates that these cryptic elements can be grouped into families based upon sequence similarities. The unique features characterising these families suggest that different molecular mechanisms are involved. Of particular relevance is the association of microsatellites with mobile elements. This is the first reported observation of this phenomenon in crustaceans, and it also helps to explain why microsatellite primer development in galatheids has been relatively unsuccessful to date. We suggest a number of steps that can be used to identify similar problems in microsatellite marker development for other species, and also alternative approaches for both marker development and for the study of molecular evolution of species characterised by complex genome organisation. More specifically, we argue that new generation sequencing methodologies, which capitalise on parallel and multiplexed sequencing may pave the way forward for future crustacean research.

Revealing differences in gene network inference algorithms on the network level by ensemble methods

Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.

Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.

Cryptic plasticity underlies a major evolutionary transition

The origin of eusociality is often regarded as a change of macroevolutionary proportions [1, 2]. Its hallmark is a reproductive division of labor between the members of a society: some individuals ("helpers" or "workers") forfeit their own reproduction to rear offspring of others ("queens"). In the Hymenoptera (ants, bees, wasps), there have been many transitions in both directions between solitary nesting and sociality [2-5]. How have such transitions occurred? One possibility is that multiple transitions represent repeated evolutionary gains and losses of the traits underpinning sociality. A second possibility, however, is that once sociality has evolved, subsequent transitions represent selection at just one or a small number of loci controlling developmental switches between preexisting alternative phenotypes [2, 6]. We might then expect transitional populations that can express either sociality or solitary nesting, depending on environmental conditions. Here, we use field transplants to directly induce transitions in British and Irish populations of the sweat bee Halictus rubicundus. Individual variation in social phenotype was linked to time available for offspring production, and to the genetic benefits of sociality, suggesting that helping was not simply misplaced parental care [7]. We thereby demonstrate that sociality itself can be truly plastic in a hymenopteran.

Low power field programmable gate array implementation of fast digital signal processing algorithms: characterisation and manipulation of data locality

Dynamic power consumption is very dependent on interconnect, so clever mapping of digital signal processing algorithms to parallelised realisations with data locality is vital. This is a particular problem for fast algorithm implementations where typically, designers will have sacrificed circuit structure for efficiency in software implementation. This study outlines an approach for reducing the dynamic power consumption of a class of fast algorithms by minimising the index space separation; this allows the generation of field programmable gate array (FPGA) implementations with reduced power consumption. It is shown how a 50% reduction in relative index space separation results in a measured power gain of 36 and 37% over a Cooley-Tukey Fast Fourier Transform (FFT)-based solution for both actual power measurements for a Xilinx Virtex-II FPGA implementation and circuit measurements for a Xilinx Virtex-5 implementation. The authors show the generality of the approach by applying it to a number of other fast algorithms namely the discrete cosine, the discrete Hartley and the Walsh-Hadamard transforms.