Single-Step Quantum Search Using Problem Structure

The structure of satisfiability problems is used to improve search algorithms for quantum computers and reduce their required coherence times by using only a single coherent evaluation of problem properties. The structure of random k-SAT allows determining the asymptotic average behavior of these algorithms, showing they improve on quantum algorithms, such as amplitude amplification, that ignore detailed problem structure but remain exponential for hard problem instances. Compared to good classical methods, the algorithm performs better, on average, for weakly and highly constrained problems but worse for hard cases. The analytic techniques introduced here also apply to other quantum algorithms, supplementing the limited evaluation possible with classical simulations and showing how quantum computing can use ensemble properties of NP search problems.Comment: 39 pages, 12 figures. Revision describes further improvement with multiple steps (section 7). See also http://www.parc.xerox.com/dynamics/www/quantum.htm

Invoice from T. P. Hogg to Ogden Goelet

https://digitalcommons.salve.edu/goelet-personal-expenses/1080/thumbnail.jp

Double crystal x-ray diffraction simulations of diffusion in semiconductor microstructures

Diffusion in group IV, III-V and II-VI semiconductors is an interesting problem not only from a fundamental physics viewpoint but also in practical terms, since it could determine the useful lifetime of a device. Any attempt to control the amount of diffusion in a semiconductor device, whether it be a quantum well structure or not, requires an accurate determination of the diffusion coefficient. The present theoretical study shows that this could be achieved via x-ray diffraction studies in quantum well structures. It is demonstrated that the rocking curves of single quantum wells are not sensitive to diffusion. However the intensity of the first order satellite, which is characteristic of superlattice rocking curves, is strongly dependent upon diffusion and it is proposed that this technique could be used to measure the diffusion coefficient D. © 1998 American Institute of Physics

Multiple imputation and maximum likelihood principal component analysis of incomplete multivariate data from a study of the ageing of port

A multivariate data matrix containing a number of missing values was obtained from a study on the changes in colour and phenolic composition during the ageing of port. Two approaches were taken in the analysis of the data. The first involved the use of multiple imputation (MI) followed by principal components analysis (PCA). The second examined the use of maximum likelihood principal component analysis (MLPCA). The use of multiple imputation allows for missing value uncertainty to be incorporated into the analysis of the data. Initial estimates of missing values were firstly calculated using the Expectation Maximization algorithm (EM), followed by Data Augmentation (DA) in order to generate five imputed data matrices. Each complete data matrix was subsequently analysed by PCA, then averaging their principal component (PC) scores and loadings to give an estimation of errors. The first three PCs accounted for 93.3% of the explained variance. Changes to colour and monomeric anthocyanin composition were explained on PC1 (79.63% explained variance), phenolic composition and hue mainly on PC2 (8.61% explained variance) and phenolic composition and the formation of polymeric pigment on PC3 (5.04% explained variance). In MLPCA estimates of measurement uncertainty is incorporated in the decomposition step, with missing values being assigned large measurement uncertainties. PC scores on the first two PCs after multiple imputation and PCA (MI+PCA) were comparable to maximum likelihood scores on the first two PCs extracted by MLPCA

Single-shot single-gate RF spin readout in silicon

For solid-state spin qubits, single-gate RF readout can help minimise the number of gates required for scale-up to many qubits since the readout sensor can integrate into the existing gates required to manipulate the qubits (Veldhorst 2017, Pakkiam 2018). However, a key requirement for a scalable quantum computer is that we must be capable of resolving the qubit state within single-shot, that is, a single measurement (DiVincenzo 2000). Here we demonstrate single-gate, single-shot readout of a singlet-triplet spin state in silicon, with an average readout fidelity of $82.9\%$ at a $3.3~\text{kHz}$ measurement bandwidth. We use this technique to measure a triplet $T_-$ to singlet $S_0$ relaxation time of $0.62~\text{ms}$ in precision donor quantum dots in silicon. We also show that the use of RF readout does not impact the maximum readout time at zero detuning limited by the $S_0$ to $T_-$ decay, which remained at approximately $2~\text{ms}$. This establishes single-gate sensing as a viable readout method for spin qubits

Microbiological profile of salpicão de vinhais and chouriça de vinhais from raw materials to final products: Traditional dry sausages produced in the North of Portugal

Salpicão de Vinhais and Chouriça de Vinhais are traditional dry-fermented meat sausages produced in the North of Portugal. The microbiological profile during production of both products was followed in three small processing units. Lactic acid bacteria were the most prevalent microorganisms, with enhanced growth during the smoking process and a consequent decrease of pH. This study demonstrated that when highly contaminated raw ingredients are used, pathogens might not be eliminated during processing (from seasoning until the end of smoking). Therefore, it is important to highlight that to produce safe Salpicão and Chouriça following traditional recipes and methodologies it is necessary to work under hygienic conditions using raw materials of good microbiological quality. Industrial relevance: Preservation of pork meat in the form of semi-dry, fermented and smoked products having a long shelf-life, is an age-old artisanal process that is still practiced in many areas of the world. In many rural communities production has a significant impact on the local economy and food supply, but these products are now becoming increasingly popular in urban areas. In a more widespread distribution of such artisanal products, it is important that consumers are not exposed to undue risks of food-borne infections or intoxications. This study investigates the evolution of the microflora and microbiological safety during the production processes of two such traditional products in the North of Portugal, and during storage of the final products.info:eu-repo/semantics/acceptedVersio

Characterization of microbial population of “Alheira” (a traditional Portuguese fermented sausage) by PCR-DGGE and traditional cultural microbiological methods

This study evaluates the microbial ecology of ‘Alheira’ by traditional microbiological analysis and a PCR-denaturing gradient gel electrophoresis (DGGE) protocol. Methods and Results: Total microbial DNA from ‘Alheiras’ was extracted directly from the products and subjected to PCR using Eubacterial primers for 16S rDNA. The amplicons were separated by DGGE. The results demonstrated that different products of the same batch display identical profiles, whereas products from different batches of the same producer could display different DGGE profiles. ‘Alheiras’ from different producers were distinguishable based on the respective DGGE profiles. The obtained sequences from prevalent phylotypes affiliated with order Lactobacillales and order Bacillales and class Gammaproteobacteria. The same samples were subjected to traditional microbiological analysis. In both methods, lactic acid bacteria were dominant and were present together with other organisms, mainly members of the family Micrococcaceae. Conclusions: The approach explored in this study allowed the description of the microbial community present in ‘Alheira’ in particular the diversity of lactic acid bacteria. Significance and Impact of the Study: This can be useful for the microbiological characterization of traditional products in order to develop new methods of quality control capable of supporting a standardization of the processes, while preserving their typical traits

Nested quantum search and NP-complete problems

A quantum algorithm is known that solves an unstructured search problem in a number of iterations of order $\sqrt{d}$, where $d$ is the dimension of the search space, whereas any classical algorithm necessarily scales as $O(d)$. It is shown here that an improved quantum search algorithm can be devised that exploits the structure of a tree search problem by nesting this standard search algorithm. The number of iterations required to find the solution of an average instance of a constraint satisfaction problem scales as $\sqrt{d^\alpha}$, with a constant $\alpha<1$ depending on the nesting depth and the problem considered. When applying a single nesting level to a problem with constraints of size 2 such as the graph coloring problem, this constant $\alpha$ is estimated to be around 0.62 for average instances of maximum difficulty. This corresponds to a square-root speedup over a classical nested search algorithm, of which our presented algorithm is the quantum counterpart.Comment: 18 pages RevTeX, 3 Postscript figure