Mediated tunable coupling of flux qubits

It is sketched how a monostable rf- or dc-SQUID can mediate an inductive coupling between two adjacent flux qubits. The nontrivial dependence of the SQUID's susceptibility on external flux makes it possible to continuously tune the induced coupling from antiferromagnetic (AF) to ferromagnetic (FM). In particular, for suitable parameters, the induced FM coupling can be sufficiently large to overcome any possible direct AF inductive coupling between the qubits. The main features follow from a classical analysis of the multi-qubit potential. A fully quantum treatment yields similar results, but with a modified expression for the SQUID susceptibility. Since the latter is exact, it can also be used to evaluate the susceptibility--or, equivalently, energy-level curvature--of an isolated rf-SQUID for larger shielding and at degenerate flux bias, i.e., a (bistable) qubit. The result is compared to the standard two-level (pseudospin) treatment of the anticrossing, and the ensuing conclusions are verified numerically.Comment: REVTeX 4, 16 pp., 4 EPS figures. N.B.: "Alec" is my first, and "Maassen van den Brink" my family name. v2: major expansion and rewriting, new title and co-author; to appear in New Journal of Physics special issue (R. Fazio, ed.

New statistical method identifes cytokines that distinguish stool microbiomes

Regressing an outcome or dependent variable onto a set of input or independent variables allows the analyst to measure associations between the two so that changes in the outcome can be described by and predicted by changes in the inputs. While there are many ways of doing this in classical statistics, where the dependent variable has certain properties (e.g., a scalar, survival time, count), little progress on regression where the dependent variable are microbiome taxa counts has been made that do not impose extremely strict conditions on the data. In this paper, we propose and apply a new regression model combining the Dirichlet-multinomial distribution with recursive partitioning providing a fully non-parametric regression model. This model, called DM-RPart, is applied to cytokine data and microbiome taxa count data and is applicable to any microbiome taxa count/metadata, is automatically fit, and intuitively interpretable. This is a model which can be applied to any microbiome or other compositional data and software (R package HMP) available through the R CRAN website

Influenza surveillance among children with pneumonia admitted to a district hospital in coastal Kenya, 2007-2010

Background: Influenza data gaps in sub-Saharan Africa include incidence, case fatality, seasonal patterns, and associations with prevalent disorders. Methods: Nasopharyngeal samples from children aged <12 years who were admitted to Kilifi District Hospital during 2007–2010 with severe or very severe pneumonia and resided in the local demographic surveillance system were screened for influenza A, B, and C viruses by molecular methods. Outpatient children provided comparative data. Results: Of 2002 admissions, influenza A virus infection was diagnosed in 3.5% (71), influenza B virus infection, in 0.9% (19); and influenza C virus infection, in 0.8% (11 of 1404 tested). Four patients with influenza died. Among outpatients, 13 of 331 (3.9%) with acute respiratory infection and 1 of 196 without acute respiratory infection were influenza positive. The annual incidence of severe or very severe pneumonia, of influenza (any type), and of influenza A, was 1321, 60, and 43 cases per 100 000 <5 years of age, respectively. Peak occurrence was in quarters 3–4 each year, and approximately 50% of cases involved infants: temporal association with bacteremia was absent. Hypoxia was more frequent among pneumonia cases involving influenza (odds ratio, 1.78; 95% confidence interval, 1.04–1.96). Influenza A virus subtypes were seasonal H3N2 (57%), seasonal H1N1 (12%), and 2009 pandemic H1N1 (7%). Conclusions: The burden of influenza was small during 2007–2010 in this pediatric hospital in Kenya. Influenza A virus subtype H3N2 predominated, and 2009 pandemic influenza A virus subtype H1N1 had little impact

Probing High Frequency Noise with Macroscopic Resonant Tunneling

We have developed a method for extracting the high-frequency noise spectral density of an rf-SQUID flux qubit from macroscopic resonant tunneling (MRT) rate measurements. The extracted noise spectral density is consistent with that of an ohmic environment up to frequencies ~ 4 GHz. We have also derived an expression for the MRT lineshape expected for a noise spectral density consisting of such a broadband ohmic component and an additional strongly peaked low-frequency component. This hybrid model provides an excellent fit to experimental data across a range of tunneling amplitudes and temperatures

Untargeted analysis of the airway proteomes of children with respiratory infections using mass spectrometry based proteomics

The upper airway – which consists mainly of the naso- and oro-pharynx - is the first point of contact between the respiratory system and microbial organisms that are ubiquitous in the environment. It has evolved highly specialised functions to address these constant threats whilst facilitating seamless respiratory exchange with the lower respiratory tract. Dysregulation of its critical homeostatic and defence functions can lead to ingress of pathogens into the lower respiratory tract, potentially leading to serious illness. Systems-wide proteomic tools may facilitate a better understanding of mechanisms in the upper airways in health and disease. In this study, we aimed to develop a mass spectrometry based proteomics method for characterizing the upper airways proteome. Naso- and oropharyngeal swab samples used in all our experiments had been eluted in the Universal Transport Media (UTM) containing significantly high levels of bovine serum albumin. Our proteomic experiments tested the optimal approach to characterize airway proteome on swab samples eluted in UTM based on the number of proteins identified without BSA depletion (Total proteome: Protocol A) and with its depletion using a commercial kit; Allprep, Qiagen (cellular proteome: Protocol B, Ci, and Cii). Observations and lessons drawn from protocol A, fed into the design and implementation of protocol B, and from B to protocol Ci and finally Cii. Label free proteome quantification was used in Protocol A (n = 6) and B (n = 4) while commercial TMT 10plex reagents were used for protocols Ci and ii (n = 83). Protocols Ci and ii were carried out under similar conditions except for the elution gradient: 3 h and 6 h respectively. Swab samples tested in this study were from infants and children with and without upper respiratory tract infections from Kilifi County Hospital on the Kenyan Coast. Protocol A had the least number of proteins identified (215) while B produced the highest number of protein identifications (2396). When Protocol B was modified through sample multiplexing with TMT to enable higher throughput (Protocol Ci), the number of protein identified reduced to 1432. Modification of protocol Ci by increasing the peptide elution time generated Protocol Cii that substantially increased the number of proteins identified to 1875. The coefficient of variation among the TMT runs in Protocol Cii was <20%. There was substantial overlap in the identity of proteins using the four protocols. Our method was were able to identify marker proteins characteristically expressed in the upper airway. We found high expression levels of signature nasopharyngeal and oral proteins, including BPIFA1/2 and AMY1A, as well as a high abundance of proteins related to innate and adaptive immune function in the upper airway. We have developed a sensitive systems-level proteomic assay for the systematic quantification of naso-oro-pharyngeal proteins. The assay will advance mechanistic studies of respiratory pathology, by providing an untargeted and hypothesis-free approach of examining the airway proteome

Exploiting tree shadows on snow for estimating forest basal area using Landsat data

Basal area (BA) is a basic structural and ecological attribute of forests that is often used to describe forest composition, estimate volume of wood, and guide management decisions. BA is the sum of cross-sectional area of trees measured at 1.37 m above ground surface, per unit area, and is most commonly measured in-situ. The objective of this study was to supply estimates of BA for oak woodlands and savannas on the 12,828.5 ha Sherburne National Wildlife Refuge in Central Minnesota to guide management efforts. We used winter and summer Landsat imagery, combined with field measurements, to assess the potential for improving forest BA estimates by taking advantage of the high spectral contrast between sunlit snow, forest canopy elements, and shadows projected onto snow ground cover. We explained up to 90% of measured variation in BA using partial least squares regression models calibrated using single- and multiple-date winter Landsat data (R2 = 0.898, RMSE = 2.79 m2ha− 1), which performed better than models calibrated using summer imagery (R2 = 0.762, RMSE = 3.85 m2ha− 1). Success of the winter-based BA models may be driven, in part, by potential geometric/allometric relationships between cast shadow and forest BA, but definitive proof of this is a topic for future research. This method of BA estimation is not refuge-specific and may be extended for regional use to manage oak forest wherever winter snow coverage is consistent. Additional research is needed to determine the degree of robustness to variations in the empirical relationship between BA and tree shading patterns across different forest functional types

Superconducting Circuits and Quantum Information

Superconducting circuits can behave like atoms making transitions between two levels. Such circuits can test quantum mechanics at macroscopic scales and be used to conduct atomic-physics experiments on a silicon chip.Comment: 7 pages, 4 figures. See also: http://www.physicstoday.org/vol-58/iss-11/contents.htm

Hybrid quantum annealing for larger-than-QPU lattice-structured problems

Quantum processing units (QPUs) executing annealing algorithms have shown promise in optimization and simulation applications. Hybrid algorithms are a natural bridge to additional applications of larger scale. We present a straightforward and effective method for solving larger-than-QPU lattice-structured Ising optimization problems. Performance is compared against simulated annealing with promising results, and improvement is shown as a function of the generation of D-Wave QPU used.Comment: 21 pages, 15 figures, supplementary code attachmen

Probing Noise in Flux Qubits via Macroscopic Resonant Tunneling

Macroscopic resonant tunneling between the two lowest lying states of a bistable RF-SQUID is used to characterize noise in a flux qubit. Measurements of the incoherent decay rate as a function of flux bias revealed a Gaussian shaped profile that is not peaked at the resonance point, but is shifted to a bias at which the initial well is higher than the target well. The r.m.s. amplitude of the noise, which is proportional to the decoherence rate 1/T_2^*, was observed to be weakly dependent on temperature below 70 mK. Analysis of these results indicates that the dominant source of low frequency (1/f) flux noise in this device is a quantum mechanical environment in thermal equilibrium.Comment: 4 pages 4 figure