Effects of hadronic potentials on elliptic flows in relativistic heavy ion collisions

Within the framework of a multiphase transport (AMPT) model that includes both initial partonic and final hadronic interactions, we show that including mean-field potentials in the hadronic phase leads to a splitting of the elliptic flows of particles and their antiparticles, providing thus a plausible explanation of the different elliptic flows between $p$ and ${\bar p}$, $K^+$ and $K^-$, and $\pi^+$ and $\pi^-$ observed in recent Beam Energy Scan (BES) program at the Relativistic Heavy-Ion Collider (RHIC).Comment: 5 pages, 7 figure

Enhanced Molecular Spectroscopy via Localized Surface Plasmon Resonance

Numerous novel spectroscopy techniques have been developed to perform detection and characterization at molecular level. Nevertheless, the resolution of spectroscopy remains to be the bottleneck, and local electric field is involved to solve this issue. Localized surface plasmon resonance (LSPR) occurred at the surface of noble metal nanoparticles is a major source of enhanced local electric field which provide notable enhancement factor of spectroscopy applying fluorescence and the Raman scattering. In this chapter, we will firstly present the physics of localized surface plasmon resonance to gain a basic understanding. Several current techniques to prepare a wide variety of nanoparticles and localized surface plasmon resonance detector are subsequently introduced. We further illustrate two examples taking advantage of experiments and modeling to elaborate the effect of localized surface plasmon resonance on spectroscopy under different circumstances. The combination of experimental and theoretical approaches elucidates the influence of each factor and promotes the design of localized surface plasmon resonance detector used in spectroscopy

Partonic effects on higher-order anisotropic flows in relativistic heavy-ion collisions

Higher-order anisotropic flows $v_{4}$ and $v_{6}$ in heavy ion collisions at the Relativistic Heavy Ion Collider are studied in a multiphase transport model that has previously been used successfully for describing the elliptic flow $v_2$ in these collisions. We find that the same parton scattering cross section of about 10 \textrm{mb} used in explaining the measured $v_2$ can also reproduce the recent data on $v_{4}$ and $v_{6}$ from Au + Au collisions at $\sqrt{s}=200$ \textrm{AGeV}. It is further found that the $$ is a more sensitive probe of the initial partonic dynamics in these collisions than $v_{2}$. Moreover, higher-order parton anisotropic flows are nonnegligible and satisfy the scaling relation $v_{n,q}(p_{T})\sim v_{2,q}^{n/2}(p_{T})$, which leads naturally to the observed similar scaling relation among hadron anisotropic flows when the coalescence model is used to describe hadron production from the partonic matter.Comment: 5 pages, 3 figures, version to appear in PRC as a Rapid Communicatio

Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods

We propose two approaches to solve large-scale compressed sensing problems. The first approach uses the parametric simplex method to recover very sparse signals by taking a small number of simplex pivots, while the second approach reformulates the problem using Kronecker products to achieve faster computation via a sparser problem formulation. In particular, we focus on the computational aspects of these methods in compressed sensing. For the first approach, if the true signal is very sparse and we initialize our solution to be the zero vector, then a customized parametric simplex method usually takes a small number of iterations to converge. Our numerical studies show that this approach is 10 times faster than state-of-the-art methods for recovering very sparse signals. The second approach can be used when the sensing matrix is the Kronecker product of two smaller matrices. We show that the best-known sufficient condition for the Kronecker compressed sensing (KCS) strategy to obtain a perfect recovery is more restrictive than the corresponding condition if using the first approach. However, KCS can be formulated as a linear program with a very sparse constraint matrix, whereas the first approach involves a completely dense constraint matrix. Hence, algorithms that benefit from sparse problem representation, such as interior point methods (IPMs), are expected to have computational advantages for the KCS problem. We numerically demonstrate that KCS combined with IPMs is up to 10 times faster than vanilla IPMs and state-of-the-art methods such as ℓ[subscript 1]_ℓ[subscript s] and Mirror Prox regardless of the sparsity level or problem size.National Science Foundation (U.S.) (Grant DMS-1005539

An asymmetric upwind flow, Yellow Sea Warm Current : 2. Arrested topographic waves in response to the northwesterly wind

Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 116 (2011): C04027, doi:10.1029/2010JC006514.A warm and salty water mass exists along the Yellow Sea Trough (YST) in winter. This oceanic water mass is distinct from the ambient shelf water and is distributed on the western side of the YST. It has long been reasoned that a Yellow Sea Warm Current (YSWC) must exist. A recent observational study indeed supports the existence of the YSWC and shows that its position moved progressively westward as the warm water intrudes further shoreward toward the northwest. In this paper, we explain mechanisms for sustaining the YSWC and for its westward displacement. The northwesterly monsoonal wind prevails in the winter and is directed against the YSWC. The cross-trough scale is small compared with the spatial scale of monsoonal variation, so one can assume, to the first order, that the wind stress is uniform across the trough. The curl of depth-averaged wind stress has opposite signs on the two sides of the trough. Consequently, two oppositely rotating gyres develop initially and they converge along the trough giving rise to a barotropic upwind flow. But this upwind flow lasts only for a few days as the two gyres evolve and propagate as topographic waves. For a northerly wind, both gyres move westward since the positive (negative) potential vorticity flux on the western (eastern) side of the trough pushes the water toward shore (trough). If the bottom friction is negligible, the steady response becomes a large anticyclonic gyre over the trough and the upwind current is squeezed toward the shore line. In this case, no YSWC is sustained along or near the trough. This runaway warm current can be arrested by a moderate bottom friction. We therefore propose that the YSWC is actually arrested topographic waves in response to local wind stress forcing.X.L. has been supported by China’s National Basic Research Priorities Programmer (2007CB411804 and 2005CB422303), the Ministry of Education’s 111 Project (B07036), the Program for New Century Excellent Talents in University (NECT‐07‐ 0781), and the China National Science Foundation (40976004, 40921004, and 40930844). J.Y. has been supported by the U.S. National Science Foundation and the Woods Hole Oceanographic Institution’s Coastal Ocean Institute

Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering

Existing deep learning models have achieved promising performance in recognizing skin diseases from dermoscopic images. However, these models can only recognize samples from predefined categories, when they are deployed in the clinic, data from new unknown categories are constantly emerging. Therefore, it is crucial to automatically discover and identify new semantic categories from new data. In this paper, we propose a new novel class discovery framework for automatically discovering new semantic classes from dermoscopy image datasets based on the knowledge of known classes. Specifically, we first use contrastive learning to learn a robust and unbiased feature representation based on all data from known and unknown categories. We then propose an uncertainty-aware multi-view cross pseudo-supervision strategy, which is trained jointly on all categories of data using pseudo labels generated by a self-labeling strategy. Finally, we further refine the pseudo label by aggregating neighborhood information through local sample similarity to improve the clustering performance of the model for unknown categories. We conducted extensive experiments on the dermatology dataset ISIC 2019, and the experimental results show that our approach can effectively leverage knowledge from known categories to discover new semantic categories. We also further validated the effectiveness of the different modules through extensive ablation experiments. Our code will be released soon.Comment: 10 pages, 1 figure,Accepted by miccai 202

System size dependence of elliptic flows in relativistic heavy-ion collisions

The elliptic flows in both Cu+Cu and Au+Au collisions at the Relativistic Heavy Ion Collider are studied in a multi-phase transport model. For both collisions at same reduced impact parameter and minimum bias collisions, the elliptic flow of partons in Cu+Cu collisions is about a factor of three smaller than that in Au+Au collisions at same energy. The reduction factor is similar to the ratio of the sizes of the two colliding systems and is also related to the combined effects of initial energy density and spatial elliptic deformation in the two reactions. A similar system size dependence is also seen in the elliptic flow of charged hadrons from minimum bias collisions.Comment: 5 pages, 5 figures, revised version, to appear in PL