Study of direct CP violation for Bˉs0→π+π−π0(K0)\bar{B}_{s}^{0} \rightarrow \pi ^+\pi ^-\pi^{0}(K^{0}) decay in Perturbative QCD

We investigate the direct CP violation for the charmless three-body decay process of $\bar{B}_{s}^{0}\rightarrow \rho \left( \omega ,\phi \right) \pi^0(K^0)\rightarrow \pi^{+}\pi^{-} K ^0$. The mechanisms of $\rho-\omega$, $\rho-\phi$ and $\omega-\phi$ mixing are considered in perturbative QCD approach. Isospin symmetry breaking from the decays of $\omega \rightarrow \pi ^+\pi ^-$ and $\phi \rightarrow \pi ^+\pi ^-$ are known to be tiny. However, we find the direct CP violation of the decay processes of $\bar{B}_{s}^{0}\rightarrow \pi^{+}\pi^{-} \pi ^0$ and $\bar{B}_{s}^{0}\rightarrow \pi^{+}\pi^{-} K^0$ can reach $65\%$ and $36\%$ from isospin symmetry breaking, respectively. To better compare with experimental data in the future, the localized integrated direct CP violation of the decay processes are presented. The mechanism can provide a new way to explore CP violation from the three-body decay processes of $B_s$ meson for the LHC experiment.Comment: arXiv admin note: text overlap with arXiv:2201.0238

Interacting agegraphic tachyon model of dark energy

Scalar-field dark energy models like tachyon are often regarded as an effective description of an underlying theory of dark energy. In this Letter, we implement the interacting agegraphic dark energy models with tachyon field. We demonstrate that the interacting agegraphic evolution of the universe can be described completely by a single tachyon scalar field. We thus reconstruct the potential as well as the dynamics of the tachyon field according to the evolutionary behavior of interacting agegraphic dark energy.Comment: 11 pages, to appear in Phys. Lett.

Thermally activated and aggregation-regulated excitonic coupling enable emissive high-lying triplet excitons

Funding: Horizon 2020 Framework Programme (Grant Number(s): 897098; Grant recipient(s): Tao Wang, Eli Zysman-Colman); Horizon 2020 Framework Programme (Grant Number(s): 101025143; Grant recipient(s): Eli Zysman-Colman, Joydip De); Engineering and Physical Sciences Research Council (Grant Number(s): EP/P010482/1; Grant recipient(s): Eli Zysman-Colman); Royal Society (Grant Number(s): SRF\R1\201089; Grant recipient(s): Abhishek Kumar Gupta, Eli Zysman-Colman); China Scholarship Council (GrantNumber(s): 201906250199; Grant recipient(s): Sen Wu)Room-temperature phosphorescence (RTP) originating from higher-lying triplet excitons remains a rather rarely documented occurrence for purely organic molecular systems. Here, we report two naphthalene-based RTP luminophores whose phosphorescence emission is enabled by radiative decay of high-lying triplet excitons. In contrast, upon cooling the dominant phosphorescence originates from the lowest-lying triplet excited state, which is manifested by a red-shifted emission. Photophysical and theoretical studies reveal that the unusual RTP results from thermally activated excitonic coupling between different conformations of the compounds. Aggregation-regulated excitonic coupling is observed when increasing the doping concentration of the emitters in poly(methylmethacrylate) (PMMA). Further, the RTP quantum efficiency improves more than 80-fold in 1,3-bis(N-carbazolyl)benzene (mCP) compared to that in PMMA. This design principle offers important insight into triplet excited state dynamics and has been exploited in afterglow-indicating temperature sensing.Publisher PDFPeer reviewe

Adaptive low-level control of autonomous underwater vehicles using deep reinforcement learning

Low-level control of autonomous underwater vehicles (AUVs) has been extensively addressed by classical control techniques. However, the variable operating conditions and hostile environments faced by AUVs have driven researchers towards the formulation of adaptive control approaches. The reinforcement learning (RL) paradigm is a powerful framework which has been applied in different formulations of adaptive control strategies for AUVs. However, the limitations of RL approaches have lead towards the emergence of deep reinforcement learning which has become an attractive and promising framework for developing real adaptive control strategies to solve complex control problems for autonomous systems. However, most of the existing applications of deep RL use video images to train the decision making artificial agent but obtaining camera images only for an AUV control purpose could be costly in terms of energy consumption. Moreover, the rewards are not easily obtained directly from the video frames. In this work we develop a deep RL framework for adaptive control applications of AUVs based on an actor-critic goal-oriented deep RL architecture, which takes the available raw sensory information as input and as output the continuous control actions which are the low-level commands for the AUV's thrusters. Experiments on a real AUV demonstrate the applicability of the stated deep RL approach for an autonomous robot control problem.Fil: Carlucho, Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; ArgentinaFil: de Paula, Mariano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; ArgentinaFil: Wang, Sen. Heriot-Watt University; Reino UnidoFil: Petillot, Yvan. Heriot-Watt University; Reino UnidoFil: Acosta, Gerardo Gabriel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentin

Decay of Unstable D-branes with Electric Field

Using the techniques of two dimensional conformal field theory we construct time dependent classical solutions in open string theory describing the decay of an unstable D-brane in the presence of background electric field, and explicitly evaluate the time dependence of the energy momentum tensor and the fundamental string charge density associated with this solution. The final decay product can be interpreted as a combination of stretched fundamental strings and tachyon matter.Comment: 35 pages, LaTe

Improved Feature Distillation via Projector Ensemble

In knowledge distillation, previous feature distillation methods mainly focus on the design of loss functions and the selection of the distilled layers, while the effect of the feature projector between the student and the teacher remains under-explored. In this paper, we first discuss a plausible mechanism of the projector with empirical evidence and then propose a new feature distillation method based on a projector ensemble for further performance improvement. We observe that the student network benefits from a projector even if the feature dimensions of the student and the teacher are the same. Training a student backbone without a projector can be considered as a multi-task learning process, namely achieving discriminative feature extraction for classification and feature matching between the student and the teacher for distillation at the same time. We hypothesize and empirically verify that without a projector, the student network tends to overfit the teacher's feature distributions despite having different architecture and weights initialization. This leads to degradation on the quality of the student's deep features that are eventually used in classification. Adding a projector, on the other hand, disentangles the two learning tasks and helps the student network to focus better on the main feature extraction task while still being able to utilize teacher features as a guidance through the projector. Motivated by the positive effect of the projector in feature distillation, we propose an ensemble of projectors to further improve the quality of student features. Experimental results on different datasets with a series of teacher-student pairs illustrate the effectiveness of the proposed method

RADIATE: A Radar Dataset for Automotive Perception in Bad Weather

Datasets for autonomous cars are essential for the development and benchmarking of perception systems. However, most existing datasets are captured with camera and LiDAR sensors in good weather conditions. In this paper, we present the RAdar Dataset In Adverse weaThEr (RADIATE), aiming to facilitate research on object detection, tracking and scene understanding using radar sensing for safe autonomous driving. RADIATE includes 3 hours of annotated radar images with more than 200K labelled road actors in total, on average about 4.6 instances per radar image. It covers 8 different categories of actors in a variety of weather conditions (e.g., sun, night, rain, fog and snow) and driving scenarios (e.g., parked, urban, motorway and suburban), representing different levels of challenge. To the best of our knowledge, this is the first public radar dataset which provides high-resolution radar images on public roads with a large amount of road actors labelled. The data collected in adverse weather, e.g., fog and snowfall, is unique. Some baseline results of radar based object detection and recognition are given to show that the use of radar data is promising for automotive applications in bad weather, where vision and LiDAR can fail. RADIATE also has stereo images, 32-channel LiDAR and GPS data, directed at other applications such as sensor fusion, localisation and mapping. The public dataset can be accessed at http://pro.hw.ac.uk/radiate/.Comment: Accepted at IEEE International Conference on Robotics and Automation 2021 (ICRA 2021

New holographic scalar field models of dark energy in non-flat universe

Motivated by the work of Granda and Oliveros [L.N. Granda, A. Oliveros, Phys. Lett. B {\bf 671}, 199 (2009)], we generalize their work to the non-flat case. We study the correspondence between the quintessence, tachyon, K-essence and dilaton scalar field models with the new holographic dark energy model in the non-flat FRW universe. We reconstruct the potentials and the dynamics for these scalar field models, which describe accelerated expansion of the universe. In the limiting case of a flat universe, i.e. $k = 0$, all results given in [L.N. Granda, A. Oliveros, Phys. Lett. B {\bf 671}, 199 (2009)] are obtained.Comment: 11 page

BPS States, Refined Indices, and Quiver Invariants

For D=4 BPS state construction, counting, and wall-crossing thereof, quiver quantum mechanics offers two alternative approaches, the Coulomb phase and the Higgs phase, which sometimes produce inequivalent counting. The authors have proposed, in arXiv:1205.6511, two conjectures on the precise relationship between the two, with some supporting evidences. Higgs phase ground states are naturally divided into the Intrinsic Higgs sector, which is insensitive to wall-crossings and thus an invariant of quiver, plus a pulled-back ambient cohomology, conjectured to be an one-to-one image of Coulomb phase ground states. In this note, we show that these conjectures hold for all cyclic quivers with Abelian nodes, and further explore angular momentum and R-charge content of individual states. Along the way, we clarify how the protected spin character of BPS states should be computed in the Higgs phase, and further determine the entire Hodge structure of the Higgs phase cohomology. This shows that, while the Coulomb phase states are classified by angular momentum, the Intrinsic Higgs states are classified by R-symmetry.Comment: 51 pages, 5 figure