Semidefinite programming converse bounds for quantum communication

We derive several efficiently computable converse bounds for quantum communication over quantum channels in both the one-shot and asymptotic regime. First, we derive one-shot semidefinite programming (SDP) converse bounds on the amount of quantum information that can be transmitted over a single use of a quantum channel, which improve the previous bound from [Tomamichel/Berta/Renes, Nat. Commun. 7, 2016]. As applications, we study quantum communication over depolarizing channels and amplitude damping channels with finite resources. Second, we find an SDP strong converse bound for the quantum capacity of an arbitrary quantum channel, which means the fidelity of any sequence of codes with a rate exceeding this bound will vanish exponentially fast as the number of channel uses increases. Furthermore, we prove that the SDP strong converse bound improves the partial transposition bound introduced by Holevo and Werner. Third, we prove that this SDP strong converse bound is equal to the so-called max-Rains information, which is an analog to the Rains information introduced in [Tomamichel/Wilde/Winter, IEEE Trans. Inf. Theory 63:715, 2017]. Our SDP strong converse bound is weaker than the Rains information, but it is efficiently computable for general quantum channels.Comment: 17 pages, extended version of arXiv:1601.06888. v3 is closed to the published version, IEEE Transactions on Information Theory, 201

Video Captioning via Hierarchical Reinforcement Learning

Video captioning is the task of automatically generating a textual description of the actions in a video. Although previous work (e.g. sequence-to-sequence model) has shown promising results in abstracting a coarse description of a short video, it is still very challenging to caption a video containing multiple fine-grained actions with a detailed description. This paper aims to address the challenge by proposing a novel hierarchical reinforcement learning framework for video captioning, where a high-level Manager module learns to design sub-goals and a low-level Worker module recognizes the primitive actions to fulfill the sub-goal. With this compositional framework to reinforce video captioning at different levels, our approach significantly outperforms all the baseline methods on a newly introduced large-scale dataset for fine-grained video captioning. Furthermore, our non-ensemble model has already achieved the state-of-the-art results on the widely-used MSR-VTT dataset.Comment: CVPR 2018, with supplementary materia

Projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks

We study projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks. We relax some limitations of previous work, where projective-anticipating and projective-lag synchronization can be achieved only on two coupled chaotic systems. In this paper, we can realize projective-anticipating and projective-lag synchronization on complex dynamical networks composed by a large number of interconnected components. At the same time, although previous work studied projective synchronization on complex dynamical networks, the dynamics of the nodes are coupled partially linear chaotic systems. In this paper, the dynamics of the nodes of the complex networks are time-delayed chaotic systems without the limitation of the partial-linearity. Based on the Lyapunov stability theory, we suggest a generic method to achieve the projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random dynamical networks and find both the existence and sufficient stability conditions. The validity of the proposed method is demonstrated and verified by examining specific examples using Ikeda and Mackey-Glass systems on Erdos-Renyi networks.Comment: 14 pages, 6 figure

Experimental Investigation on the Feasibility and Optimal Frequency of Ultrasonic Assisted Ice Drilling Method

Exploitation of polar resources and scientific research require efficient ice drilling technology. Thermal drilling is a common method for polar ice drilling, and is similar to the principle of ultrasonic assisted drilling; both are drilled by melting ice layers, but improving energy utilization has always been a challenge. In order to improve energy utilization and drilling efficiency, this paper proposes a method for ice drilling with ultrasonic frequency vibration. The mechanism of ultrasonic vibration drilling into ice was analyzed, the solid theoretical foundation for the application of ice melting efficiency under ultrasonic frequency vibration was determined and a series of indoor experiments were conducted. According to experimental data obtained, two conclusions were provided. First, different frequencies have distinct influence on power density, drilling speed and melting rate, and the optimum range excitation frequency for ultrasonic ice drilling is at least 30~32 kHz, under which the ice melting efficiency and drilling speed reached the peak value. Second, ultrasonic assisted drilling was verified to have the ability of improving the efficiency of ice breaking by comparing to thermal drilling under the same power density under 30 kHz. As an environmentally friendly and efficient drilling method, ultrasonic assisted ice drilling has great application prospects in the field of polar exploration. By using Ultrasonic assisted drilling, we demonstrate a strategy for a faster and more efficient drilling method, which is important for humankind