Passive Superconducting Circulator on a Chip.

An on-chip microwave circulator that is compatible with superconducting devices is a key element for scale up of superconducting circuits. Previous approaches to integrating circulators on chip involve either external driving that requires extra microwave lines or a strong magnetic field that would compromise superconductivity. Here we report the first proof-of-principle realization of a passive on-chip circulator that is made from a superconducting loop interrupted by three notionally identical Josephson junctions and is tuned with only dc control fields. Our experimental results show evidence for nonreciprocal scattering, and excellent agreement with theoretical simulations. We also present a detailed analysis of quasiparticle tunneling in our device using a hidden Markov model. By reducing the junction asymmetry and utilizing the known methods of protection from quasiparticles, we anticipate that Josephson-loop circulator will become ubiquitous in superconducting circuits.

Functional connectivity subtypes associate robustly with ASD diagnosis.

Our understanding of the changes in functional brain organization in autism is hampered by the extensive heterogeneity that characterizes this neurodevelopmental disorder. Data driven clustering offers a straightforward way to decompose autism heterogeneity into subtypes of connectivity and promises an unbiased framework to investigate behavioral symptoms and causative genetic factors. Yet, the robustness and generalizability of functional connectivity subtypes is unknown. Here, we show that a simple hierarchical cluster analysis can robustly relate a given individual and brain network to a connectivity subtype, but that continuous assignments are more robust than discrete ones. We also found that functional connectivity subtypes are moderately associated with the clinical diagnosis of autism, and these associations generalize to independent replication data. We explored systematically 18 different brain networks as we expected them to associate with different behavioral profiles as well as different key regions. Contrary to this prediction, autism functional connectivity subtypes converged on a common topography across different networks, consistent with a compression of the primary gradient of functional brain organization, as previously reported in the literature. Our results support the use of data driven clustering as a reliable data dimensionality reduction technique, where any given dimension only associates moderately with clinical manifestations.