MRI relies on highly accurate gradient fields for signal preparation and spatial encoding. Deviation from prescribed gradient waveforms causes image artifacts and error in quantitative readouts. Much effort is thus dedicated to perfecting gradient hardware and correcting remaining error at the levels of input waveforms, image reconstruction, and image processing.One chief cause of perturbation is eddy current driven by gradient switching. Eddy currents outside the gradient tube, especially in the magnet and cryostat, can be largely

We investigate Josephson junctions on the surface of a three-dimensional topological insulator in planar, step, and edge geometries. The elliptical nature of the Dirac cone representing the side surface states of the topological insulator results in a scaling factor in the Josephson current in a step junction as compared to the planar junction. In edge junctions, the contribution of the Andreev bound states to the Josephson current vanishes due to spin-momentum locking of the surface states. Furthermore, we consider a junction with a ferromagnetic insulator between the superconducting regions. In these ferromagnetic junctions, we find an anomalous finite Josephson current at zero phase difference if the magnetization is pointing along the junction (and perpendicular to the Josephson current). An out-of-plane magnetization with respect to the central region of the junction opens up an exchange gap and leads to a non-monotonic behavior of the critical Josephson current for sufficiently large magnetization as the chemical potential increases.

Highlights• This work investigates the feasibility of using a one-time system calibration (called GIRF) based on a linear time-invariant gradient model to account for k-space trajectory deviations in spiral fMRI.• We show that the image quality and the spatial specificity of the fMRI activation are substantially improved when using the GIRF-prediction for trajectory correction while the nominal reconstructions suffer from artifacts and mis-placed fMRI activation.• We demonstrate that system characterization via the GIRF can enable spiral fMRI in situations when concurrent monitoring is not available. AbstractPurpose: Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B 0 inhomogeneity are more difficult to correct compared to EPI and requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step. Methods:GIRF-predicted reconstruction was tested for high-resolution (0.8mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the delay corrected nominal trajectory and concurrent field monitoring. Results:The reconstructions using nominal spiral trajectories contain substantial artifacts and activation maps contain mis-placed activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction. Conclusion:The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality highresolution fMRI in situations where concurrent monitoring is not available.