Implications of Recent Bˉ0→D(∗)0X0\bar{B}^0\to D^{(*)0}X^0 Measurements

The recent measurements of the color-suppressed modes $\bar B^0\to D^{(*)0}\pi^0$ imply non-vanishing relative final-state interaction (FSI) phases among various $\bar B\to D\pi$ decay amplitudes. Depending on whether or not FSIs are implemented in the topological quark-diagram amplitudes, two solutions for the parameters $a_1$ and $a_2$ are extracted from data using various form-factor models. It is found that $a_2$ is not universal: $|a_2(D\pi)|= 0.40-0.55$ and $|a_2(D^*\pi)|= 0.25-0.35$ with a relative phase of order $(50-55)^\circ$ between $a_1$ and $a_2$. If FSIs are not included in quark-diagram amplitudes from the outset, $a_2^{eff}/a_1^{eff}$ and $a_2^{eff}$ will become smaller. The large value of $|a_2(D\pi)|$ compared to $|a_2^{eff}(D\pi)|$ or naive expectation implies the importance of long-distance FSI contributions to color-suppressed internal $W$-emission via final-state rescatterings of the color-allowed tree amplitude.Comment: 17 pages. The Introduction is substantially revised and the order of the presentation in Sec. 2 is rearranged. To appear in Phys. Re

Multiwavelength properties of a new Geminga-like pulsar: PSR J2021+4026

In this paper, we report a detailed investigation of the multiwavelength properties of a newly detected gamma-ray pulsar, PSR J2021+4026, in both observational and theoretical aspects. We firstly identify an X-ray source in the XMM-Newton serendipitous source catalogue, 2XMM J202131.0+402645, located within the 95% confidence circle of PSR J2021+4026. With an archival Chandra observation, this identification provides an X-ray position with arcsecond accuracy which is helpful in facilitating further investigations. Searching for the pulsed radio emission at the position of 2XMM J202131.0+402645 with a 25-m telescope at Urumqi Astronomical Observatory resulted in null detection and places an upper-limit of 0.1~mJy for any pulsed signal at 18~cm. Together with the emission properties in X-ray and gamma-ray, the radio quietness suggests PSR J2021+4026 to be another member of Geminga-like pulsars. In the radio sky survey data, extended emission features have been identified in the gamma-ray error circle of PSR J2021+4026. We have also re-analyzed the gamma-ray data collected by FERMI's Large Area Telescope. We found that the X-ray position of 2XMM J202131.0+402645 is consistent with that of the optimal gamma-ray timing solution. We have further modeled the results in the context of outer gap model which provides us with constraints for the pulsar emission geometry such as magnetic inclination angle and the viewing angle. We have also discussed the possibility of whether PSR J2021+4026 has any physical association with the supernova remnant G78.2+2.1 (gamma-Cygni).Comment: 11 pages, 14 figure

Classification of Overlapped Audio Events Based on AT, PLSA, and the Combination of Them

Audio event classification, as an important part of Computational Auditory Scene Analysis, has attracted much attention. Currently, the classification technology is mature enough to classify isolated audio events accurately, but for overlapped audio events, it performs much worse. While in real life, most audio documents would have certain percentage of overlaps, and so the overlap classification problem is an important part of audio classification. Nowadays, the work on overlapped audio event classification is still scarce, and most existing overlap classification systems can only recognize one audio event for an overlap. In this paper, in order to deal with overlaps, we innovatively introduce the author-topic (AT) model which was first proposed for text analysis into audio classification, and innovatively combine it with PLSA (Probabilistic Latent Semantic Analysis). We propose 4 systems, i.e. AT, PLSA, AT-PLSA and PLSA-AT, to classify overlaps. The 4 proposed systems have the ability to recognize two or more audio events for an overlap. The experimental results show that the 4 systems perform well in classifying overlapped audio events, whether it is the overlap in training set or the overlap out of training set. Also they perform well in classifying isolated audio events