Gaussian modulation is one of the key steps for the implementation of continuous-variable quantum key distribution (CVQKD) schemes. However, imperfection in the Gaussian modulation may introduce modulation noise that can deteriorate the performance of CVQKD systems. In this paper, we mainly investigate how to improve the performance of a CVQKD system from different aspects. First, we explore the several different origins, impacts and monitoring schemes for the modulation noise in detail. Then, we discuss the practical performance of a CVQKD system with an untrusted noise model and neutral party model, respectively. These analyses indicate that the neutral party model should be reasonably regarded as a general noise model, which will passively and greatly raise the performance of the system. Further, we propose a dynamic auto-bias control scheme to actively resist the modulation noise which comes from the drift of bias point of the amplitude modulator. Together these methods contribute to the improvement of the practical performance of CVQKD systems with imperfect Gaussian modulation.
The rapid development of renewable-energy technologies such as water splitting, rechargeable metal–air batteries, and fuel cells requires highly efficient electrocatalysts capable of the oxygen-reduction reaction (ORR) and the oxygen-evolution reaction (OER). Herein, we report a facile sonication-driven synthesis to deposit the molecular manganese vanadium oxide precursor [Mn4V4O17(OAc)3]3− on multiwalled carbon nanotubes (MWCNTs). Thermal conversion of this composite at 900 °C gives nanostructured manganese vanadium oxides/carbides, which are stably linked to the MWCNTs. The resulting composites show excellent electrochemical reactivity for ORR and OER, and significant reactivity enhancements compared with the precursors and a Pt/C reference are reported. Notably, even under harsh acidic conditions, long-term OER activity at low overpotential is reported. In addition, we report exceptional activity of the composites for the industrially important Cl2 evolution from an aqueous HCl electrolyte. The new composite material shows how molecular deposition routes leading to highly active and stable multifunctional electrocatalysts can be developed. The facile design could in principle be extended to multiple catalyst classes by tuning of the molecular metal oxide precursor employed. 相似文献
Machine learning is currently the most active interdisciplinary field having numerous applications;additionally,machine-learning techniques are used to research quantum many-body problems.In this study,we first propose neural network quantum states(NNQSs)with general input observables and explore a few related properties,such as the tensor product and local unitary operation.Second,we determine the necessary and sufficient conditions for the representability of a general graph state using normalized NNQS.Finally,to quantify the approximation degree of a given pure state,we define the best approximation degree using normalized NNQSs.Furthermore,we observe that some 7V-qubit states can be represented by a normalized NNQS,such as separable pure states,Bell states and GHZ states. 相似文献