Long-lived quantum coherence of two-level spontaneous emission models within structured environments

We investigate the long-lived quantum coherence of two-level spontaneous emission models within structured environments. The population of the system under the asymptotic non-Markovian dynamics is linked to the spectral density of the reservoir through a general functional relation between them. We figure out explicitly the preservation of quantum coherence, via notions of entanglement and quantum discord, in connection with the spectral parameters of Ohmic class reservoirs and then show how to achieve them optimally. We expect these results to contribute towards reservoir engineering with the aim of enhancing stationary quantum coherence in noisy environments.Comment: 4 pages, 2 figures, accepted by Opt. Let

Suspending Effect on Low-Frequency Charge Noise in Graphene Quantum Dot

Charge noise is critical in the performance of gate-controlled quantum dots (QDs). Here we show the 1/f noise for a microscopic graphene QD is substantially larger than that for a macroscopic graphene field-effect transistor (FET), increasing linearly with temperature. To understand its origin, we suspended the graphene QD above the substrate. In contrast to large area graphene FETs, we find that a suspended graphene QD has an almost-identical noise level as an unsuspended one. Tracking noise levels around the Coulomb blockade peak as a function of gate voltage yields potential fluctuations of order 1 "{\mu}eV", almost one order larger than in GaAs/GaAlAs QDs. Edge states rather than substrate-induced disorders, appear to dominate the 1/f noise, thus affecting the coherency of graphene nano-devices.Comment: 14pages,5figur

Quantum delayed-choice experiment with a beam splitter in a quantum superposition

A quantum system can behave as a wave or as a particle, depending on the experimental arrangement. When for example measuring a photon using a Mach-Zehnder interferometer, the photon acts as a wave if the second beam-splitter is inserted, but as a particle if this beam-splitter is omitted. The decision of whether or not to insert this beam-splitter can be made after the photon has entered the interferometer, as in Wheeler's famous delayed-choice thought experiment. In recent quantum versions of this experiment, this decision is controlled by a quantum ancilla, while the beam splitter is itself still a classical object. Here we propose and realize a variant of the quantum delayed-choice experiment. We configure a superconducting quantum circuit as a Ramsey interferometer, where the element that acts as the first beam-splitter can be put in a quantum superposition of its active and inactive states, as verified by the negative values of its Wigner function. We show that this enables the wave and particle aspects of the system to be observed with a single setup, without involving an ancilla that is not itself a part of the interferometer. We also study the transition of this quantum beam-splitter from a quantum to a classical object due to decoherence, as observed by monitoring the interferometer output.Comment: 9 pages, 7 figures, Accepted by Physical Review Letter

Habitat use by giant pandas Ailuropoda melanoleuca in the Wanglang Nature Reserve, Sichuan, China

Abstract Background To better understand the ecological requirements of the giant panda Ailuropoda melanoleuca in the wild, field surveys were carried out at both the microhabitat scale and foraging site scale in Wanglang National Nature Reserve, Sichuan, China. Results The results indicated that (1) at the microhabitat scale, giant pandas usually occupied habitats with a high fallen-log density, lower shrub density, and bamboo coverage of 50% to 75%; (2) at the foraging site scale, pandas usually used sites with higher bamboo densities and taller and larger-diameter bamboo; and (3) giant pandas may abandon plots when the proportion of young bamboo decreases below average in the environment. Conclusions The availability of young bamboo is an important driving force in habitat selection by giant pandas, which could provide important reference for the conservation of giant pandas and their habitats. </jats:sec

Influences of commuting mode, air conditioning mode and meteorological parameters on fine particle (PM2.5) exposure levels in traffic microenvironments

With the aim of determining the impacts of various factors on commuter exposure to fine particulate matter (PM2.5), a series of field studies were carried out to measure commuter exposure to PM2.5 on six major commuting modes (in-cabin mode: bus, taxi and metro; on-roadway mode: walking, bicycle and motorcycle) in a highly industrialized city in the Pearl River Delta, China. The results showed that the exposure level was greatly influenced by the commuter mode, with the on-roadway mode showing a higher PM2.5 concentration (76 μg/m3). An experiment with the taxi mode suggested that the use of air-conditioning can effectively reduce exposure levels in most cases (by at least 83%). Apart from traffic-related emissions, ambient PM2.5 concentration also had important impacts on exposure levels in most commuting modes, which was further ascertained by the seasonal variations in exposure levels and their significant correlations (p < 0.05) with meteorological parameters (temperature, relative humidity, wind speed and direction). The results of a General Linear Model analysis show that temperature, traffic mode and wind speed were significant factors that explained 27.3% of variability for the in-cabin mode, while relative humidity and wind speed were the significant determinants for the on-roadway mode, which contributed 14.1% of variability. In addition, wind direction was also an important determinant for both in-cabin and on-roadway modes. This study has some valuable implications that can help commuters to adopt appropriate travel behavior to reduce their personal exposure to such pollutants

Alterations of Serum Levels of BDNF-Related miRNAs in Patients with Depression

Depression is a serious and potentially life-threatening mental disorder with unknown etiology. Emerging evidence shows that brain-derived neurotrophic factor (BDNF) and microRNAs (miRNAs) play critical roles in the etiology of depression. Here this study was aimed to identify and characterize the roles of BDNF and its putative regulatory miRNAs in depression. First, we identified that miR-182 may be a putative miRNA that regulates BDNF levels by bioinformatic studies, and characterized the effects of miR-182 on the BDNF levels using cell-based studies, side by side with miR-132 (a known miRNA that regulates BDNF expression). We showed that treatment of miR-132 and miR-182 respectively decreased the BDNF protein levels in a human neuronal cell model, supporting the regulatory roles of miR-132 and miR-182 on the BDNF expression. Furthermore, we explored the roles of miR-132 and miR-182 on the BDNF levels in depression using human subjects by assessing their serum levels. Compared with the healthy controls, patients with depression showed lower serum BDNF levels (via the enzyme-linked immunosorbent assays) and higher serum miR-132 and miR-182 levels (via the real-time PCR). Finally, the Pearson’s (or Spearman’s) correlation coefficient was calculated to study whether there was a relationship among the Self-Rating Depression Scale score, the serum BDNF levels, and serum BDNF-related miRNA levels. Our results revealed that there was a significant negative correlation between the SDS scores and the serum BDNF levels, and a positive correlation between the SDS scores and miR-132 levels. In addition, we found a reverse relationship between the serum BDNF levels and the miR-132/miR-182 levels in depression. Collectively, we provided evidence supporting that miR-182 is a putative BDNF-regulatory miRNA, and suggested that the serum BDNF and its related miRNAs may be utilized as important biomarkers in the diagnosis or as therapeutic targets of depression