We have found experimentally that the rise time of voltage pulse in NbN superconducting single photon detectors increases nonlinearly with increasing the length of the detector L. The effect is connected with dependence of resistance of the detector Rn, which appears after photon absorption, on its kinetic inductance Lk and, hence, on the length of the detector. This conclusion is confirmed by our calculations in the framework of two temperature model.
We propose an implementation of quantum neural networks using an array of quantum dots with dipole-dipole interactions. We demonstrate that this implementation is both feasible and versatile by studying it within the framework of GaAs based quantum dotqubits coupled to a reservoir of acoustic phonons. Using numerically exact Feynman integral calculations, we have found that the quantum coherence in our neural networks survive for over a hundred ps even at liquid nitrogen temperatures (77 K), which is three orders of magnitude higher than current implementations, which are based on SQUID-based systems operating at temperatures in the mK range.