Deterministic Loading of Microwaves onto an Artificial Atom Using a Time-Reversed Waveform.

Loading quantum information deterministically onto a quantum node is an important step toward a quantum network. Here, we demonstrate that coherent-state microwave photons with an optimal temporal waveform can be efficiently loaded onto a single superconducting artificial atom in a semi-infinite one-dimensional (1D) transmission-line waveguide. Using a weak coherent state (the number of photons () contained in the pulse ≪1) with an exponentially rising waveform, whose time constant matches the decoherence time of the artificial atom, we demonstrate a loading efficiency of 94.

Employing graphene acoustoelectric switch by dual surface acoustic wave transducers.

We implement a logic switch by using a graphene acoustoelectric transducer at room temperature. We operate two pairs of inter-digital transducers (IDTs) to launch surface acoustic waves (SAWs) on a LiNbO substrate and utilize graphene as a channel material to sustain acoustoelectric current I induced by SAWs. By cooperatively tuning the input power on the IDTs, we can manipulate the propagation direction of I such that the measured I can be deliberately controlled to be positive, negative, or even zero.

Mode Dependency of Quantum Decoherence Studied via an Aharonov-Bohm Interferometer.

We investigate the dependence of decoherence on the mode number M in a multiple-mode Aharonov-Bohm (AB) interferometer. The design of the AB interferometer allows us to precisely determine M by the additivity rule of ballistic conductors; meanwhile, the decoherence rate is simultaneously deduced by the variance of the AB oscillation amplitude. The AB amplitude decreases and fluctuates with depopulating M.

An interchangeable scanning Hall probe/scanning SQUID microscope.

We have constructed a scanning probe microscope for magnetic imaging, which can function as a scanning Hall probe microscope (SHPM) and as a scanning SQUID microscope (SSM). The scanning scheme, applicable to SHPM and SSM, consists of a mechanical positioning (sub) micron-XY stage and a flexible direct contact to the sample without a feedback control system for the Z-axis. With the interchangeable capability of operating two distinct scanning modes, our microscope can incorporate the advantageous functionalities of the SHPM and SSM with large scan range up to millimeter, high spatial resolution (⩽4 μm), and high field sensitivity in a wide range of temperature (4.

A delta-doped quantum well system with additional modulation doping.

A delta-doped quantum well with additional modulation doping may have potential applications. Utilizing such a hybrid system, it is possible to experimentally realize an extremely high two-dimensional electron gas (2DEG) density without suffering inter-electronic-subband scattering. In this article, the authors report on transport measurements on a delta-doped quantum well system with extra modulation doping.

On the direct insulator-quantum Hall transition in two-dimensional electron systems in the vicinity of nanoscaled scatterers.

A direct insulator-quantum Hall (I-QH) transition corresponds to a crossover/transition from the insulating regime to a high Landau level filling factor ν > 2 QH state. Such a transition has been attracting a great deal of both experimental and theoretical interests. In this study, we present three different two-dimensional electron systems (2DESs) which are in the vicinity of nanoscaled scatterers.

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis.

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA)--a production economics tool--to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions.

Interactive analysis of waste recycling and energy recovery program in a small-scale incinerator.

Conflicting goals affecting solid waste management are explored in this paper to find the best implementation of resource recovery with a small-scale waste-to-energy process. Recycling paper and plastic material often leaves a shortage of thermal energy to support incineration that forces operators to supplement the process with auxiliary fuels. Although there are considerable profits to be made from material recovery, the increase of fuel usage causes conflict given that it is cost prohibitive.

Deodorization of dimethyl sulfide using a discharge approach at room temperature.

The traditional technologies for odor removal of thiol usually create either secondary pollution for scrubbing, adsorption, and absorption processes, or sulfur (S) poisoning for catalytic incineration. This study applied a laboratory-scale radio-frequency plasma reactor to destructive percentage-grade concentrations of odorous dimethyl sulfide (CH3SCH3, or DMS). Odor was diminished effectively via reforming DMS into mainly carbon disulfide (CS2) or sulfur dioxide (SO2).

Rough set-based hybrid fuzzy-neural controller design for industrial wastewater treatment.

Recent advances in control engineering suggest that hybrid control strategies, integrating some ideas and paradigms existing in different soft computing techniques, such as fuzzy logic, genetic algorithms, rough set theory, and neural networks, may provide improved control performance in wastewater treatment processes. This paper presents an innovative hybrid control algorithm leading to integrate the distinct aspects of indiscernibility capability of rough set theory and search capability of genetic algorithms with conventional neural-fuzzy controller design. The methodology proposed in this study employs a three-stage analysis that is designed in series for generating a representative state function, searching for a set of multi-objective control strategies, and performing a rough set-based autotuning for the neural-fuzzy logic controller to make it applicable for controlling an industrial wastewater treatment process.