Has the nonlinear Meissner effect been observed?

We examine recent high-precision experimental data on the magnetic field, ${\bf H}$, dependence of the penetration depth $\lambda(H)$ in $\rm{YBa_2Cu_3O_{7-\delta}}$ (YBCO) for several field directions in the $a-b$ plane. In a new theoretical analysis that incorporates the effects of orthorhombic symmetry, we show that the data at sufficiently high magnetic fields and low temperatures are in quantitative agreement with the theoretical predictions of the nonlinear Meissner effect.Comment: 4 text pages plus 3 postscript figure

Inside Out: Transforming Images of Lab-Grown Plants for Machine Learning Applications in Agriculture

Machine learning tasks often require a significant amount of training data for the resultant network to perform suitably for a given problem in any domain. In agriculture, dataset sizes are further limited by phenotypical differences between two plants of the same genotype, often as a result of differing growing conditions. Synthetically-augmented datasets have shown promise in improving existing models when real data is not available. In this paper, we employ a contrastive unpaired translation (CUT) generative adversarial network (GAN) and simple image processing techniques to translate indoor plant images to appear as field images. While we train our network to translate an image containing only a single plant, we show that our method is easily extendable to produce multiple-plant field images. Furthermore, we use our synthetic multi-plant images to train several YoloV5 nano object detection models to perform the task of plant detection and measure the accuracy of the model on real field data images. Including training data generated by the CUT-GAN leads to better plant detection performance compared to a network trained solely on real data.Comment: 35 pages, 23 figure

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture

A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck in the development of machine learning (ML) applications in any domain. For agricultural applications, ML-based models designed to perform tasks such as autonomous plant classification will typically be coupled to just one or perhaps a few plant species. As a consequence, each crop-specific task is very likely to require its own specialized training data, and the question of how to serve this need for data now often overshadows the more routine exercise of actually training such models. To tackle this problem, we have developed an embedded robotic system to automatically generate and label large datasets of plant images for ML applications in agriculture. The system can image plants from virtually any angle, thereby ensuring a wide variety of data; and with an imaging rate of up to one image per second, it can produce lableled datasets on the scale of thousands to tens of thousands of images per day. As such, this system offers an important alternative to time- and cost-intensive methods of manual generation and labeling. Furthermore, the use of a uniform background made of blue keying fabric enables additional image processing techniques such as background replacement and plant segmentation. It also helps in the training process, essentially forcing the model to focus on the plant features and eliminating random correlations. To demonstrate the capabilities of our system, we generated a dataset of over 34,000 labeled images, with which we trained an ML-model to distinguish grasses from non-grasses in test data from a variety of sources. We now plan to generate much larger datasets of Canadian crop plants and weeds that will be made publicly available in the hope of further enabling ML applications in the agriculture sector.Comment: 35 pages, 8 figures, Preprint submitted to PLoS On

CeCoIn5 - a quantum critical superfluid

We have made the first complete measurements of the London penetration depth $\lambda(T)$ of CeCoIn5, a quantum-critical metal where superconductivity arises from a non-Fermi-liquid normal state. Using a novel tunnel diode oscillator designed to avoid spurious contributions to $\lambda(T)$, we have established the existence of intrinsic and anomalous power-law behaviour at low temperature. A systematic analysis raises the possibility that the unusual observations are due to an extension of quantum criticality into the superconducting state.Comment: 5 pages, 3 figure

Effect of Impurity Scattering on the Nonlinear Microwave Response in High-Tc Superconductors

We theoretically investigate intermodulation distortion in high-Tc superconductors. We study the effect of nonmagnetic impurities on the real and imaginary parts of nonlinear conductivity. The nonlinear conductivity is proportional to the inverse of temperature owing to the dependence of the damping effect on energy, which arises from the phase shift deviating from the unitary limit. It is shown that the final-states interaction makes the real part predominant over the imaginary part. These effects have not been included in previous theories based on the two-fluid model, enabling a consistent explanation for the experiments with the rf and dc fields

Theory of Nonlinear Meissner Effect in High-Tc Superconductors

We investigate the nonlinear Meissner effect microscopically. Previous studies did not consider a certain type of interaction effect on the nonlinear phenomena. The scattering amplitude barely appears without being renormalized into the Fermi-liquid parameter. With this effect we can solve the outstanding issues (the quantitative problem, the temperature and angle dependences). The quantitative calculation is performed with use of the fluctuation-exchange approximation on the Hubbard model. It is also shown that the perturbation expansion on the supercurrent by the vector potential converges owing to the nonlocal effect

Phenomenology of a-axis and b-axis charge dynamics from microwave spectroscopy of highly ordered YBa2Cu3O6.50 and YBa2Cu3O6.993

Extensive measurements of the microwave conductivity of highly pure and oxygen-ordered \YBCO single crystals have been performed as a means of exploring the intrinsic charge dynamics of a d-wave superconductor. Broadband and fixed-frequency microwave apparatus together provide a very clear picture of the electrodynamics of the superconducting condensate and its thermally excited nodal quasiparticles. The measurements reveal the existence of very long-lived excitations deep in the superconducting state, as evidenced by sharp cusp-like conductivity spectra with widths that fall well within our experimental bandwidth. We present a phenomenological model of the microwave conductivity that captures the physics of energy-dependent quasiparticle dynamics in a d-wave superconductor which, in turn, allows us to examine the scattering rate and oscillator strength of the thermally excited quasiparticles as functions of temperature. Our results are in close agreement with the Ferrell-Glover-Tinkham sum rule, giving confidence in both our experiments and the phenomenological model. Separate experiments for currents along the $\hat a$ and $\hat b$ directions of detwinned crystals allow us to isolate the role of the CuO chain layers in \YBCO, and a model is presented that incorporates both one-dimensional conduction from the chain electrons and two-dimensional transport associated with the \cuplane plane layers.Comment: 17 pages, 13 figure

Field Induced Reduction of the Low Temperature Superfluid Density in YBa2Cu3O6.95

A novel high magnetic field (8 T) spectrometer for muon spin rotation has been used to measure the temperature dependence of the in-plane magnetic penetration depth in YBa2Cu3O6.95. At low H and low T, the penetration depth exhibits the characteristic linear T dependence associated with the energy gap of a d_x^2-y^2-wave superconductor. However, at higher fields the penetration depth is essentially temperature independent at low T. We discuss possible interpretations of this surprising new feature in the low-energy excitation spectrum.Comment: 8 pages, 4 figures, 1 RevTex file and 4 postscript figure