Entanglement changing power of two-qubit unitary operations

We consider a two-qubit unitary operation along with arbitrary local unitary operations acts on a two-qubit pure state, whose entanglement is C_0. We give the conditions that the final state can be maximally entangled and be non-entangled. When the final state can not be maximally entangled, we give the maximal entanglement C_max it can reach. When the final state can not be non-entangled, we give the minimal entanglement C_min it can reach. We think C_max and C_min represent the entanglement changing power of two-qubit unitary operations. According to this power we define an order of gates.Comment: 11 page

Tidal Waves -- a non-adiabatic microscopic description of the yrast states in near-spherical nuclei

The yrast states of nuclei that are spherical or weakly deformed in their ground states are described as quadrupole waves running over the nuclear surface, which we call "tidal waves". The energies and E2 transition probabilities of the yrast states in nuclides with $Z$= 44, 46, 48 and $N=56, ~58,..., 66$ are calculated by means of the cranking model in a microscopic way. The nonlinear response of the nucleonic orbitals results in a strong coupling between shape and single particle degrees of freedom

Response-surface-model-based system sizing for nearly/net zero energy buildings under uncertainty

Properly treating uncertainty is critical for robust system sizing of nearly/net zero energy buildings (ZEBs). To treat uncertainty, the conventional method conducts Monte Carlo simulations for thousands of possible design options, which inevitably leads to computation load that is heavy or even impossible to handle. In order to reduce the number of Monte Carlo simulations, this study proposes a response-surface-model-based system sizing method. The response surface models of design criteria (i.e., the annual energy match ratio, self-consumption ratio and initial investment) are established based on Monte Carlo simulations for 29 specific design points which are determined by Box-Behnken design. With the response surface models, the overall performances (i.e., the weighted performance of the design criteria) of all design options (i.e., sizing combinations of photovoltaic, wind turbine and electric storage) are evaluated, and the design option with the maximal overall performance is finally selected. Cases studies with 1331 design options have validated the proposed method for 10,000 randomly produced decision scenarios (i.e., users’ preferences to the design criteria). The results show that the established response surface models reasonably predict the design criteria with errors no greater than 3.5% at a cumulative probability of 95%. The proposed method reduces the number of Monte Carlos simulations by 97.8%, and robustly sorts out top 1.1% design options in expectation. With the largely reduced Monte Carlo simulations and high overall performance of the selected design option, the proposed method provides a practical and efficient means for system sizing of nearly/net ZEBs under uncertainty