Efficient evaluation of decoherence rates in complex Josephson circuits

A complete analysis of the decoherence properties of a Josephson junction qubit is presented. The qubit is of the flux type and consists of two large loops forming a gradiometer and one small loop, and three Josephson junctions. The contributions to relaxation (T_1) and dephasing (T_\phi) arising from two different control circuits, one coupled to the small loop and one coupled to a large loop, is computed. We use a complete, quantitative description of the inductances and capacitances of the circuit. Including two stray capacitances makes the quantum mechanical modeling of the system five dimensional. We develop a general Born-Oppenheimer approximation to reduce the effective dimensionality in the calculation to one. We explore T_1 and T_\phi along an optimal line in the space of applied fluxes; along this "S line" we see significant and rapidly varying contributions to the decoherence parameters, primarily from the circuit coupling to the large loop.Comment: 16 pages, 20 figures; v2: minor revisio

Efficient one- and two-qubit pulsed gates for an oscillator stabilized Josephson qubit

We present theoretical schemes for performing high-fidelity one- and two-qubit pulsed gates for a superconducting flux qubit. The "IBM qubit" consists of three Josephson junctions, three loops, and a superconducting transmission line. Assuming a fixed inductive qubit-qubit coupling, we show that the effective qubit-qubit interaction is tunable by changing the applied fluxes, and can be made negligible, allowing one to perform high fidelity single qubit gates. Our schemes are tailored to alleviate errors due to 1/f noise; we find gates with only 1% loss of fidelity due to this source, for pulse times in the range of 20-30ns for one-qubit gates (Z rotations, Hadamard), and 60ns for a two-qubit gate (controlled-Z). Our relaxation and dephasing time estimates indicate a comparable loss of fidelity from this source. The control of leakage plays an important role in the design of our shaped pulses, preventing shorter pulse times. However, we have found that imprecision in the control of the quantum phase plays the major role in the limitation of the fidelity of our gates.Comment: Published version. Added references. Corrected minor typos. Added discussion on how the influence of 1/f noise is modeled. 36 pages, 11 figure

Quantum noise in current biased Josephson junction

Quantum fluctuations in a current biased Josephson junction, described in terms of the RCSJ-model, are considered. The fluctuations of the voltage and phase across the junction are assumed to be initiated by equilibrium current fluctuations in the shunting resistor. This corresponds to low enough temperatures, when fluctuations of the normal current in the junction itself can be neglected. We used the quantum Langevin equation in terms of random variables related to the limit cycle of the nonlinear Josephson oscillator. This allows to go beyond the perturbation theory and calculate the widths of the Josephson radiation lines

Model for l/f Flux Noise in SQUIDs and Qubits

We propose a model for 1/f flux noise in superconducting devices (f is frequency). The noise is generated by the magnetic moments of electrons in defect states which they occupy for a wide distribution of times before escaping. A trapped electron occupies one of the two Kramers-degenerate ground states, between which the transition rate is negligible at low temperature. As a result, the magnetic moment orientation is locked. Simulations of the noise produced by randomly oriented defects with a density of 5*10^17 m^-2 yield 1/f noise magnitudes in good agreement with experiments.Comment: 16 pages, 4 figures; v2: Various minor changes. Physical Review Letters, in pres

Dispersion of Magnetic Fields in Molecular Clouds. III

We apply our technique on the dispersion of magnetic fields in molecular clouds to high spatial resolution Submillimeter Array polarization data obtained for Orion KL in OMC-1, IRAS 16293, and NGC 1333 IRAS 4A. We show how one can take advantage of such high resolution data to characterize the magnetized turbulence power spectrum in the inertial and dissipation ranges. For Orion KL we determine that in the inertial range the spectrum can be approximately fitted with a power law k^-(2.9\pm0.9) and we report a value of 9.9 mpc for {\lambda}_AD, the high spatial frequency cutoff presumably due to turbulent ambipolar diffusion. For the same parameters we have \sim k^-(1.4\pm0.4) and a tentative value of {\lambda}_AD \simeq 2.2 mpc for NGC 1333 IRAS 4A, and \sim k^-(1.8\pm0.3) with an upper limit of {\lambda}_AD < 1.8 mpc for IRAS 16293. We also discuss the application of the technique to interferometry measurements and the effects of the inherent spatial filtering process on the interpretation of the results.Comment: 25 pages, 9 figures; accepted for publication in The Astrophysical Journa

Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance–mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40–42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5–10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (\u3e100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean

Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance–mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40–42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5–10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (\u3e100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology