Surface code architecture for donors and dots in silicon with imprecise and nonuniform qubit couplings

A scaled quantum computer with donor spins in silicon would benefit from a viable semiconductor framework and a strong inherent decoupling of the qubits from the noisy environment. Coupling neighbouring spins via the natural exchange interaction according to current designs requires gate control structures with extremely small length scales. We present a silicon architecture where bismuth donors with long coherence times are coupled to electrons that can shuttle between adjacent quantum dots, thus relaxing the pitch requirements and allowing space between donors for classical control devices. An adiabatic SWAP operation within each donor/dot pair solves the scalability issues intrinsic to exchange-based two-qubit gates, as it does not rely on sub-nanometer precision in donor placement and is robust against noise in the control fields. We use this SWAP together with well established global microwave Rabi pulses and parallel electron shuttling to construct a surface code that needs minimal, feasible local control.Comment: Published version - more detailed discussions, robustness to dephasing pointed out additionall

Analysis of genetic diversity in Brown Swiss, Jersey and Holstein populations using genome-wide single nucleotide polymorphism markers

BACKGROUND: Studies of genetic diversity are essential in understanding the extent of differentiation between breeds, and in designing successful diversity conservation strategies. The objective of this study was to evaluate the level of genetic diversity within and between North American Brown Swiss (BS, n = 900), Jersey (JE, n = 2,922) and Holstein (HO, n = 3,535) cattle, using genotyped bulls. GENEPOP and FSTAT software were used to evaluate the level of genetic diversity within each breed and between each pair of the three breeds based on genome-wide SNP markers (n = 50,972). RESULTS: Hardy-Weinberg equilibrium (HWE) exact test within breeds showed a significant deviation from equilibrium within each population (P < 0.01), which could be a result of selection, genetic drift and inbreeding within each breed. Hardy-Weinberg test also confirmed significant heterozygote deficit in each breed over several loci. Moreover, results from population differentiation tests showed that the majority of loci have alleles or genotypes drawn from different distributions in each breed. Average gene diversity, expressed in terms of observed heterozygosity, over all loci in BS, JE and HO was 0.27, 0.26 and 0.31, respectively. The proportion of genetic diversity due to allele frequency differences among breeds (F(st)) indicated that the combination of BS and HO in an ideally amalgamated population had higher genetic diversity than the other pairs of breeds. CONCLUSION: Results suggest that the three bull populations have substantially different gene pools. BS and HO show the largest gene differentiation and jointly the highest total expected gene diversity compared to when JE is considered. If the loss of genetic diversity within breeds worsens in the future, the use of crossbreeding might be an option to recover genetic diversity, especially for the breeds with small population size

Quantization of the massive gravitino on FRW spacetimes

In this article we study the quantization and causal properties of a massive spin 3/2 Rarita-Schwinger field on spatially flat Friedmann-Robertson-Walker (FRW) spacetimes. We construct Zuckerman's universal conserved current and prove that it leads to a positive definite inner product on solutions of the field equation. Based on this inner product, we quantize the Rarita-Schwinger field in terms of a CAR-algebra. The transversal and longitudinal parts constituting the independent on-shell degrees of freedom decouple. We find a Dirac-type equation for the transversal polarizations, ensuring a causal propagation. The equation of motion for the longitudinal part is also of Dirac-type, but with respect to an `effective metric'. We obtain that for all four-dimensional FRW solutions with a matter equation of state p = w rho and w in (-1,1] the light cones of the effective metric are more narrow than the standard cones, which are recovered for the de Sitter case w=-1. In particular, this shows that the propagation of the longitudinal part, although non-standard for w different from -1, is completely causal in cosmological constant, dust and radiation dominated universes.Comment: 6 pages, 1 figure; published in PR

IO-Top-k: index-access optimized top-k query processing

Top-k query processing is an important building block for ranked retrieval, with applications ranging from text and data integration to distributed aggregation of network logs and sensor data. Top-k queries operate on index lists for a query's elementary conditions and aggregate scores for result candidates. One of the best implementation methods in this setting is the family of threshold algorithms, which aim to terminate the index scans as early as possible based on lower and upper bounds for the final scores of result candidates. This procedure performs sequential disk accesses for sorted index scans, but also has the option of performing random accesses to resolve score uncertainty. This entails scheduling for the two kinds of accesses: 1) the prioritization of different index lists in the sequential accesses, and 2) the decision on when to perform random accesses and for which candidates. The prior literature has studied some of these scheduling issues, but only for each of the two access types in isolation. The current paper takes an integrated view of the scheduling issues and develops novel strategies that outperform prior proposals by a large margin. Our main contributions are new, principled, scheduling methods based on a Knapsack-related optimization for sequential accesses and a cost model for random accesses. The methods can be further boosted by harnessing probabilistic estimators for scores, selectivities, and index list correlations. We also discuss efficient implementation techniques for the underlying data structures. In performance experiments with three different datasets (TREC Terabyte, HTTP server logs, and IMDB), our methods achieved significant performance gains compared to the best previously known methods: a factor of up to 3 in terms of execution costs, and a factor of 5 in terms of absolute run-times of our implementation. Our best techniques are close to a lower bound for the execution cost of the considered class of threshold algorithms

Cosmological and Black Hole Spacetimes in Twisted Noncommutative Gravity

We derive noncommutative Einstein equations for abelian twists and their solutions in consistently symmetry reduced sectors, corresponding to twisted FRW cosmology and Schwarzschild black holes. While some of these solutions must be rejected as models for physical spacetimes because they contradict observations, we find also solutions that can be made compatible with low energy phenomenology, while exhibiting strong noncommutativity at very short distances and early times.Comment: LaTeX 12 pages, JHEP.st

Accuracy of genome-wide imputation in Braford and Hereford beef cattle.

Article 157

Machine learning classification of breeding protocol descriptions from Canadian Holsteins.

Dairy farmers are motivated to ensure cows become pregnant in an optimal and timely manner. Although timed artificial insemination (TAI) is a successful management tool in dairy cattle, it masks an animal's innate fertility performance, likely reducing the accuracy of genetic evaluations for fertility traits. Therefore, separating fertility traits based on the recorded management technique involved in the breeding process or adding the breeding protocol as an effect to the model can be viable approaches to address the potential bias caused by such management decisions. Nevertheless, there is a lack of specificity and uniformity in the recording of breeding protocol descriptions by dairy farmers. Therefore, this study investigated the use of 8 supervised machine learning algorithms to classify 1,835 unique breeding protocol descriptions from 981 herds into the following 2 classes: TAI or other than TAI. Our results showed that models that used a stacking classifier algorithm had the highest Matthews correlation coefficient (0.94 ± 0.04, mean ± SD) and maximized precision and recall (F1-score = 0.96 ± 0.03) on test data. Nonetheless, their F1-scores on test data were not different from 5 out of the other 7 algorithms considered. Altogether, results presented herein suggest machine learning algorithms can be used to produce robust models that correctly identify TAI protocols from dairy cattle breeding records, thus opening the opportunity for unbiased genetic evaluation of animals based on their natural fertility