Universal Quantum Degeneracy Point for Superconducting Qubits

The quantum degeneracy point approach [D. Vion et al., Science 296, 886 (2002)] effectively protects superconducting qubits from low-frequency noise that couples with the qubits as transverse noise. However, low-frequency noise in superconducting qubits can originate from various mechanisms and can couple with the qubits either as transverse or as longitudinal noise. Here, we present a quantum circuit containing a universal quantum degeneracy point that protects an encoded qubit from arbitrary low-frequency noise. We further show that universal quantum logic gates can be performed on the encoded qubit with high gate fidelity. The proposed scheme is robust against small parameter spreads due to fabrication errors in the superconducting qubits.Comment: 7 pages, 4 figure

Effect factors of part-load performance for various Organic Rankine cycles using in engine waste heat recovery

The Organic Rankine Cycle (ORC) is regarded as one of the most promising waste heat recovery technologies for electricity generation engines. Since the engine usually operates under different working conditions, it is important to research the part-load performance of the ORC. In order to reveal the effect factors of part-load performance, four different forms of ORCs are compared in the study with dynamic math models established in SIMULINK. They are the ORC applying low temperature working fluid R245fa with a medium heat transfer cycle, the ORCs with high temperature working fluid toluene heated directly by exhaust condensing at low pressure and high pressure, and the double-stage ORC. It is regarded that the more slowly the system output power decreases, the better part-load performance it has. Based on a comparison among the four systems, the effects of evaporating pressure, condensing condition, working fluid, and system structure on part-load performance are revealed in the work. Further, it is found that the system which best matches with the heat source not only performs well under the design conditions, but also has excellent part-load performance

A Palette of Deepened Emotions: Exploring Emotional Challenge in Virtual Reality Games

Recent work introduced the notion of ‘emotional challenge’promising for understanding more unique and diverse player experiences (PX). Although emotional challenge has immediately attracted HCI researchers’ attention, the concept has not been experimentally explored, especially in virtual reality (VR), one of the latest gaming environments. We conducted two experiments to investigate how emotional challenge affects PX when separately from or jointly with conventional challenge in VR and PC conditions. We found that relatively exclusive emotional challenge induced a wider range of different emotions in both conditions, while the adding of emotional challenge broadened emotional responses only in VR. In both experiments, VR significantly enhanced the measured PX of emotional responses, appreciation, immersion and presence. Our findings indicate that VR may be an ideal medium to present emotional challenge and also extend the understanding of emotional (and conventional) challenge in video games

Experimental study on transcritical Rankine cycle (TRC) using CO2/R134a mixtures with various composition ratios for waste heat recovery from diesel engines

A carbon dioxide (CO2) based mixture was investigated as a promising solution to improve system performance and expand the condensation temperature range of a CO2 transcritical Rankine cycle (C-TRC). An experimental study of TRC using CO2/R134a mixtures was performed to recover waste heat of engine coolant and exhaust gas from a heavy-duty diesel engine. The main purpose of this study was to investigate experimentally the effect of the composition ratio of CO2/R134a mixtures on system performance. Four CO2/R134a mixtures with mass composition ratios of 0.85/0.15, 0.7/0.3, 0.6/0.4 and 0.4/0.6 were selected. The high temperature working fluid was expanded through an expansion valve and then no power was produced. Thus, current research focused on the analysis of measured operating parameters and heat exchanger performance. Heat transfer coefficients of various heat exchangers using supercritical CO2/R134a mixtures were provided and discussed. These data may provide useful reference for cycle optimization and heat exchanger design in application of CO2 mixtures. Finally, the potential of power output was estimated numerically. Assuming an expander efficiency of 0.7, the maximum estimations of net power output using CO2/R134a (0.85/0.15), CO2/R134a (0.7/0.3), CO2/R134a (0.6/0.4) and CO2/R134a (0.4/0.6) are 5.07 kW, 5.45 kW, 5.30 kW, and 4.41 kW, respectively. Along with the increase of R134a composition, the estimation of net power output, thermal efficiency and exergy efficiency increased at first and then decreased. CO2/R134a (0.7/0.3) achieved the maximum net power output at a high expansion inlet pressure, while CO2/R134a (0.6/0.4) behaves better at low pressure

Deep Learning for Single Image Super-Resolution: A Brief Review

Single image super-resolution (SISR) is a notoriously challenging ill-posed problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions. To solve the SISR problem, recently powerful deep learning algorithms have been employed and achieved the state-of-the-art performance. In this survey, we review representative deep learning-based SISR methods, and group them into two categories according to their major contributions to two essential aspects of SISR: the exploration of efficient neural network architectures for SISR, and the development of effective optimization objectives for deep SISR learning. For each category, a baseline is firstly established and several critical limitations of the baseline are summarized. Then representative works on overcoming these limitations are presented based on their original contents as well as our critical understandings and analyses, and relevant comparisons are conducted from a variety of perspectives. Finally we conclude this review with some vital current challenges and future trends in SISR leveraging deep learning algorithms.Comment: Accepted by IEEE Transactions on Multimedia (TMM

Critical Current Density and Resistivity of MgB2 Films

The high resistivity of many bulk and film samples of MgB2 is most readily explained by the suggestion that only a fraction of the cross-sectional area of the samples is effectively carrying current. Hence the supercurrent (Jc) in such samples will be limited by the same area factor, arising for example from porosity or from insulating oxides present at the grain boundaries. We suggest that a correlation should exist, Jc ~ 1/{Rho(300K) - Rho(50K)}, where Rho(300K) - Rho(50K) is the change in the apparent resistivity from 300 K to 50 K. We report measurements of Rho(T) and Jc for a number of films made by hybrid physical-chemical vapor deposition which demonstrate this correlation, although the "reduced effective area" argument alone is not sufficient. We suggest that this argument can also apply to many polycrystalline bulk and wire samples of MgB2.Comment: 11 pages, 3 figure

Interest rate regulation, earnings transparency and capital structure: evidence from Chinese listed companies, 2003-2015

We use samples from Chinese listed companies to investigate the effects of interest rate deregulation and earnings transparency on company’s capital structure in China over the period of 2003-2015. In particular, we study the link between state-owned enterprises (SOEs), economic growth targets, and marketization in China's unique institutional context. The results show earnings transparency increases firm leverage and the additional tests suggest that such an effect takes place via a mechanism by reducing the cost of debt finance. However, information transparency could moderate the effects of interest rate deregulation on corporate capital structure. In addition, it finds that SOEs are less sensitive towards the changes of interest rates in China because lending to SOEs is policy-oriented and lacks of market evaluation of business risk. Government control is conducive to enhancing the transparency of the whole industry, however, market-oriented reform is conducive to enhancing the transparency of the company's own information. The results are robust to endogeneity tests and a variety of variable and model specifications. Lastly, we find that information transparency has little impact on equity financing because of IPO and SEO strictly controlled by the Chinese government. These findings are important for management and policy implications. The paper makes contribution to the relationship between earnings disclosure quality and capital structure in the Chinese unique institutional context, such as taking the progressive interest rate reform, SOES, different economic growth target and different marketization level in each province of China. We suggest that investors will pay more attention to the company's own unique information transparency in the provinces with high degree of marketization. As a potential direction for future research, we will investigate how the earnings transparency has impact on capital structure, and how such impact would depend on the transparency of specific business, the cap of foreign shareholding and the convenience of investment

Integer quantum Hall effect and topological phase transitions in silicene

We numerically investigate the effects of disorder on the quantum Hall effect (QHE) and the quantum phase transitions in silicene based on a lattice model. It is shown that for a clean sample, silicene exhibits an unconventional QHE near the band center, with plateaus developing at $\nu=0,\pm2,\pm6,\ldots,$ and a conventional QHE near the band edges. In the presence of disorder, the Hall plateaus can be destroyed through the float-up of extended levels toward the band center, in which higher plateaus disappear first. However, the center $\nu=0$ Hall plateau is more sensitive to disorder and disappears at a relatively weak disorder strength. Moreover, the combination of an electric field and the intrinsic spin-orbit interaction (SOI) can lead to quantum phase transitions from a topological insulator to a band insulator at the charge neutrality point (CNP), accompanied by additional quantum Hall conductivity plateaus.Comment: 7 pages, 4 figure