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An integrated magnetic nanosensor based on a niobium dc SQUID (superconducting quantum interference device) for nanoscale applications is presented. The sensor, having a washer shape with a hole of 200 nm and two Josephson-Dayem nanobridges of 80 nm × 100 nm, consists of a Nb(30 nm)/Al(30 nm) bilayer patterned by electron beam lithography (EBL) and shaped by lift-off and reactive ion etch (RIE) processes. The presence of the niobium coils, integrated on-chip and tightly coupled to the SQUID, allows us to easily excite the sensor in order to get the voltage-flux characteristics and to flux bias the SQUID at its optimal point. The measurements were performed at liquid helium temperature. A voltage swing of 75 µV and a maximum voltage-flux transfer coefficient (responsivity) as high as 1 mV/Φ(0) were directly measured from the voltage-flux characteristic. The noise measurements were performed in open loop mode, biasing the SQUID with a dc magnetic flux at its maximum responsivity point and using direct-coupled low-noise readout electronics. A white magnetic flux noise spectral density as low as 2.5 μΦ(0) Hz(-1/2) was achieved, corresponding to a magnetization or spin sensitivity in units of the Bohr magneton of 100 spin Hz(-1/2). Possible applications of this nanosensor can be envisaged in magnetic detection of nanoparticles and small clusters of atoms and molecules, in the measurement of nanoobject magnetization, and in quantum computing.

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We investigate the properties of Josephson junction networks with inhomogeneous architecture. The networks are shaped as "square comb" planar lattices on which Josephson junctions link superconducting islands arranged in the plane to generate the pertinent topology. Compared to the behavior of reference linear arrays, the temperature dependencies of the Josephson currents of the branches of the network exhibit relevant differences. The observed phenomena evidence new and surprising behavior of superconducting Josephson arrays as well as remarkable similarities with bosonic junction arrays.