Real-time Information, Uncertainty and Quantum Feedback Control

Feedback is the core concept in cybernetics and its effective use has made great success in but not limited to the fields of engineering, biology, and computer science. When feedback is used to quantum systems, two major types of feedback control protocols including coherent feedback control (CFC) and measurement-based feedback control (MFC) have been developed. In this paper, we compare the two types of quantum feedback control protocols by focusing on the real-time information used in the feedback loop and the capability in dealing with parameter uncertainty. An equivalent relationship is established between quantum CFC and non-selective quantum MFC in the form of operator-sum representation. Using several examples of quantum feedback control, we show that quantum MFC can theoretically achieve better performance than quantum CFC in stabilizing a quantum state and dealing with Hamiltonian parameter uncertainty. The results enrich understanding of the relative advantages between quantum MFC and quantum CFC, and can provide useful information in choosing suitable feedback protocols for quantum systems.Comment: 24 page

Robust manipulation of superconducting qubits in the presence of fluctuations

Superconducting quantum systems are promising candidates for quantum information processing due to their scalability and design flexibility. However, the existence of defects, fluctuations, and inaccuracies is unavoidable for practical superconducting quantum circuits. In this paper, a sampling-based learning control (SLC) method is used to guide the design of control fields for manipulating superconducting quantum systems. Numerical results for one-qubit systems and coupled two-qubit systems show that the "smart" fields learned using the SLC method can achieve robust manipulation of superconducting qubits, even in the presence of large fluctuations and inaccuracies.Comment: 10 pages, 6 figure

Regge-like relation and a universal description of heavy-light systems

Using the Regge-like formula $(M-m_Q)^2=\pi\sigma L$ between hadron mass $M$ and angular momentum $L$ with a heavy quark mass $m_Q$ and a string tension $\sigma$, we analyze all the heavy-light systems, i.e., $D/D_s/B/B_s$ mesons and charmed and bottom baryons.Numerical plots are obtained for all the heavy-light mesons of experimental data whose slope becomes nearly equal to 1/2 of that for light hadrons. Assuming that charmed and bottom baryons consist of one heavy quark and one light cluster of two light quarks (diquark), we apply the formula to all the heavy-light baryons including recently discovered $\Omega_c$'s and find that these baryons experimentally measured satisfy the above formula. We predict the average mass values of $B$, $B_s$, $\Lambda_b$, $\Sigma_c$, $\Xi_c$, and $\Omega_c$ with $L=2$ as 6.01, 6.13, 6.15, 3.05, 3.07, and 3.34 GeV, respectively. Our results on baryons suggest that these baryons can be safely regarded as heavy quark-light cluster configuration. We also find a universal description for all the heavy-light mesons as well as baryons, i.e., one unique line is enough to describe both of charmed and bottom heavy-light systems. Our results suggest that instead of mass itself, gluon flux energy is essential to obtain a linear trajectory.Comment: 10 pages, 8 figures, 5 table

MEGA: An Energy Aware Algorithm for Self-Powered Wireless Sensor Networks in Sustainable Smart Infrastructure

Smart infrastructure is attractive for possessing many desirable features, such as uninterrupted monitoring of health conditions, timely response to damages, and human-infrastructure interactions. Embedded sensors that collectinformation are critical for decision making. However, the lifetime of electronic sensors is a constraint to infrastructure lifetime if sensors are physically embedded in the infrastructure at construction time. In this paper, we studied a self-powered wireless sensor network that harvests energy from mechan-ical vibration in the environment. A dynamic, hierarchical algorithm called MEGA is proposed that constructs clusters and elects the cluster head based on residue energy and energy harvest rate. Taking a smart bridge as an application example, the simulation study has verified the effectiveness of the proposed protocol