A survey of CO and its isotope lines for possible cloud-cloud collision candidates

In the 12CO (J=1-0) survey for the 1331 cold IRAS sources 214 sources show profiles with multiple-peak profiles and are selected as cloud-cloud collision candidates. In January 2005, 201 sources are detected with 12CO(1-0), 13CO(1-0), and C18O(1-0) emission by the 13.7m telescope at Purple Mount Observatory. This is the first CO and its isotope lines directed toward possible cloud-cloud collision regions. According to the statistics of the 201 sources in Galactic distribution, the 201 sources show a similar distribution to the parent sample (1331 cold IRAS sources). These sources are located over a wide range of the Galactocentric distances, and are partly associated with the star formation region. Based on preliminary criteria which describe the spectrum properties of the possible cloud-cloud collision region, the 201 sources are classified into four types by the fit of the spectral profiles between the optically thick and thin lines toward each source. The survey is focused on the possible cloud-cloud collision regions, and gives some evidences to help us with selecting the target region. Then we will carry on the mapping and multi-wavelength study for the selected region in future

A molecular line study towards massive extended green object clumps in the southern sky: chemical properties

We present a molecular line study towards 31 extended green object (EGO) clumps in the southern sky using data from MALT90 (Millimetre Astronomy Legacy Team 90 GHz). According to previous multiwavelength observations, we divide our sample into two groups: massive young stellar objects (MYSOs) and HII regions. Our results seem to support that N2H+ and C2H emissions mainly come from the gas inside quiescent clumps. In addition, we also find that the [N2H+]/[H13CO+] and [C2H]/[H13CO+] relative abundance ratios decrease from MYSOs to HII regions. These results suggest depletion of N2H+ and C2H in the late stages of massive-star formation, probably caused by the formation of HII regions inside. N2H+ and C2H might be used as chemical clocks for massive-star formation by comparing with other molecules such as H13CO+ and HC3N

Molecular line study of massive star forming regions from the RMS survey

In this paper we selected a sample of massive star forming regions from the Red MSX Source (RMS) survey, to study star formation activities (mainly outflow and inflow signatures)

A multiwavelength study of the star forming H II region Sh2-82

Based on a multiwavelength study, the interstellar medium and young stellar objects (YSOs) around the HII region Sh2-82 have been analyzed. Two molecular clumps were found from the archival data of the Galactic Ring Survey, and using the Two Micron All-Sky Survey catalog, we found two corresponding young clusters embedded in the molecular clumps. The very good relations between CO emission, infrared shells and YSOs suggest that it is probably a triggered star formation region from the expansion of Sh2-82. We further used the data from the Galactic Legacy Infrared Mid-Plane Survey Extraordinaire from Spitzer to study the YSOs within the two clumps, confirming star formation in this region. By spectral energy distribution fits to each YSO candidate with infrared excess, we derived the slope of the initial mass function. Finally, comparing the HII region's dynamical age and the fragmentation time of the molecular shell, we discard the "collect and collapse" process as being the triggering mechanism for YSO formation. Sh2-82 can be a mixture of other processes such as radiative-driven implosion and/or collisions with pre-existing clumps.Comment: in raa, 2012, 12, 65

A multi-transition molecular line study of infrared dark cloud G331.71+00.59

Using archive data from the Millimeter Astronomy Legacy Team Survey at 90 GHz (MALT90), carried out using the Mopra 22-m telescope, we made the first multi-transition molecular line study of infrared dark cloud (IRDC) MSXDC G331.71+00.59. Two molecular cores were found embedded in this IRDC. Each of these cores is associated with a known extended green object (EGO), indicating places of massive star formation. The HCO+ (1-0) and HNC (1-0) transitions show prominent blue or red asymmetric structures, suggesting outflow and inflow activities of young stellar objects (YSOs). Other detected molecular lines include H13CO+ (1-0), C2H (1-0), HC3N (10-9), HNCO(404-303) and SiO (2-1), which are typical of hot cores and outflows. We regard the two EGOs as evolving from the IRDC to hot cores. Using public GLIMPS data, we investigate the spectral energy distribution of EGO G331.71+0.60. Our results support this EGO being a massive YSO driving the outflow. G331.71+0.58 may be at an earlier evolutionary stage

Kinematics and chemistry of the hot core in G20.08-0.14N

We present Submillimeter Array observations of the massive star-forming region G20.08-0.14N at 335 and 345 GHz. With the SMA data, 41 molecular transitions were detected related to 11 molecular species and their isotopologues, including SO2, SO, C34S, NS, C17O, SiO, CH3OH, HC3N, H13CO+, HCOOCH3 and NH2CHO. In G20.08-0.14N, 10 transition lines of the detected 41 transition lines belong to SO2, which dominates the appearance of the submillimeter-wave spectrum. To obtain the spatial kinematic distribution of molecules in G20.08-0.14N, we chose the strongest and unblended lines for the channel maps. The channel maps of C34S an SiO, together with their position-velocity diagrams, present that there are two accretion flows in G20.08-0.14N. Additionally, SiO emission shows a collimated outflow at the NE-SW direction. The direction of the outflow is for the first time revealed. The rotational temperature and the column density of CH3OH are 105 K and 3.1*10^{17} cm^{-2}, respectively. Our results confirm that a hot core is associated with G20.08-0.14N. The hot core is heated by a protostar radiation at it center, not by the external excitation from shocks. The images of the spatial distribution of different species have shown that the different molecules are located at the different positions of the hot core. Through comparing the spatial distributions and abundances of the molecules, we discuss possible chemical processes for producing the complex sulfur-bearing, nitrogen-bearing and oxygen-bearing molecules in G20.08-0.14N.Comment: 13 pages, 7 figures. Accepted by MNRA

CO J=2-1 and CO J=3-2 observations toward the high-mass protostellar candidate IRAS 20188+3928

We have carried out 12CO J=2-1 and 12CO J=3-2 observations toward the high-mass protostellar candidate IRAS 20188+3928. Compared with previous observations, the 12CO J=2-1 and 12CO J=3-2 lines both have asymmetric profiles with an absorption dip. The velocity of the absorption dip is 1.0 km/s. The spectral shape may be caused by rotation. The velocity-integrated intensity map and position-velocity diagram of the 12CO J=2-1 line present an obvious bipolar component, further verifying that this region has an outflow motion. This region is also associated with an HII region, an IRAS source, and an H2O maser. The H2O maser has the velocity of 1.1 km/s. Compared with the components of the outflow, we find that the H2O maser is not associated with the outflow. Using the large velocity gradient model, we concluded that possible averaged gas densities of the blueshifted lobe and redshifted lobe are 1.0*10^{5}$cm^{-3} and 2.0*10$^{4} cm^{-3}, while kinetic temperatures are 26.9 K and 52.9 K, respectively. Additionally, the outflow has {a} higher integrated intensity ratio (I_{CO J=3-2}/I_{CO J=2-1}).Comment: 8 pages, 5 figures, Accepted by Research in Astronomy and Astrophysic

Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods

Sparse learning has recently received increasing attention in many areas including machine learning, statistics, and applied mathematics. The mixed-norm regularization based on the l1q norm with q>1 is attractive in many applications of regression and classification in that it facilitates group sparsity in the model. The resulting optimization problem is, however, challenging to solve due to the inherent structure of the mixed-norm regularization. Existing work deals with special cases with q=1, 2, infinity, and they cannot be easily extended to the general case. In this paper, we propose an efficient algorithm based on the accelerated gradient method for solving the general l1q-regularized problem. One key building block of the proposed algorithm is the l1q-regularized Euclidean projection (EP_1q). Our theoretical analysis reveals the key properties of EP_1q and illustrates why EP_1q for the general q is significantly more challenging to solve than the special cases. Based on our theoretical analysis, we develop an efficient algorithm for EP_1q by solving two zero finding problems. To further improve the efficiency of solving large dimensional mixed-norm regularized problems, we propose a screening method which is able to quickly identify the inactive groups, i.e., groups that have 0 components in the solution. This may lead to substantial reduction in the number of groups to be entered to the optimization. An appealing feature of our screening method is that the data set needs to be scanned only once to run the screening. Compared to that of solving the mixed-norm regularized problems, the computational cost of our screening test is negligible. The key of the proposed screening method is an accurate sensitivity analysis of the dual optimal solution when the regularization parameter varies. Experimental results demonstrate the efficiency of the proposed algorithm.Comment: arXiv admin note: text overlap with arXiv:1009.476

Predict Forex Trend via Convolutional Neural Networks

Deep learning is an effective approach to solving image recognition problems. People draw intuitive conclusions from trading charts; this study uses the characteristics of deep learning to train computers in imitating this kind of intuition in the context of trading charts. The three steps involved are as follows: 1. Before training, we pre-process the input data from quantitative data to images. 2. We use a convolutional neural network (CNN), a type of deep learning, to train our trading model. 3. We evaluate the model's performance in terms of the accuracy of classification. A trading model is obtained with this approach to help devise trading strategies. The main application is designed to help clients automatically obtain personalized trading strategies.Comment: 30 pages, 41 figure

Numerical Study of Drop Motion on a Surface with Wettability Gradient and Contact Angle Hysteresis

In this work, the motion of a 2-D drop on a surface with given wettability gradient is studied numerically by a hybrid lattice-Boltzmann finite-difference method using the multiple-relaxation-time collision model. We incorporate the geometric wetting boundary condition that allows accurate implementation of a contact angle hysteresis model. The method is first validated through three benchmark tests, including the layered Poiseuille flow with a viscosity contrast, the motion of a liquid column in a channel with specified wettability gradient and the force balance for a static drop attached to a surface with hysteresis subject to a body force. Then, simulations of a drop on a wall with given wettability gradient are performed under different conditions. The effects of the Reynolds number, the viscosity ratio, the wettability gradient, as well as the contact angle hysteresis on the drop motion are investigated in detail. It is found that the capillary number of the drop in steady state is significantly affected by the viscosity ratio, the magnitudes of the wettability gradient and the contact angle hysteresis, whereas it only shows very weak dependence on the Reynolds number