Highly tunable repetition-rate multiplication of mode-locked lasers using all-fibre harmonic injection locking

Higher repetition-rate optical pulse trains have been desired for various applications such as high-bit-rate optical communication, photonic analogue-to-digital conversion, and multi- photon imaging. Generation of multi GHz and higher repetition-rate optical pulse trains directly from mode-locked oscillators is often challenging. As an alternative, harmonic injection locking can be applied for extra-cavity repetition-rate multiplication (RRM). Here we have investigated the operation conditions and achievable performances of all-fibre, highly tunable harmonic injection locking-based pulse RRM. We show that, with slight tuning of slave laser length, highly tunable RRM is possible from a multiplication factor of 2 to >100. The resulting maximum SMSR is 41 dB when multiplied by a factor of two. We further characterize the noise properties of the multiplied signal in terms of phase noise and relative intensity noise. The resulting absolute rms timing jitter of the multiplied signal is in the range of 20 fs to 60 fs (10 kHz - 1 MHz) for different multiplication factors. With its high tunability, simple and robust all-fibre implementation, and low excess noise, the demonstrated RRM system may find diverse applications in microwave photonics, optical communications, photonic analogue-to-digital conversion, and clock distribution networks.Comment: 25 pages, 9 figure

Bank partnership and liquidity crisis

This study empirically investigates the relationship between banking integration and liquidity management. To measure banks’ connectivity, we use the number of partnerships proxied via the syndicated loan arrangements in which they serve as lead arrangers. If banks establish more business partnerships through syndicated loan arrangements, those under market stress are more likely to face increased funding costs, create reduced liquidity, and originate declined small business loans and mortgages. Those banks with more partners are shown to have a lower liquidity coverage ratio, suggesting that business partnerships create a disincentive toward liquidity risk management

Cooperative control for a flight array of UAVs and an application in radar jamming

This paper proposes a flight array system and an integrated approach to cope with its operational issues raised in mission-planning level (i.e., task allocation) and control level (i.e., control allocation). The proposed flight array system consists of multiple ducted-fan UAVs that can assemble with each other to fly together, as well as dissemble themselves to fly individually for accomplishing a given mission. To address the task allocation problem, a game-theoretical framework is developed. This framework enables agents to converge into an agreed task allocation in a decentralised and scalable manner, while guaranteeing a certain level of global optimality. In addition, this paper suggests a cooperative control scheme based on sliding mode control and weighted pseudo-inverse techniques so that the system’s non-linearity and control allocation issue are effectively handled. As a proof-of-concept, a prototype simulation program is developed and validated in a cooperative jamming mission. The numerical simulations manifest the feasibility of effectiveness of the proposed approach

An integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirements

Given a cooperative mission consisting of multiple tasks spatially distributed, an aerial robotic swarm’s decision-making issues include team formation, team-to-task assignment, agent-to-work-position assignment and trajectory optimisation with collision avoidance. The problem becomes even more complicated when involving heterogeneous agents, tasks’ minimum requirements and fair allocation. This paper formulates all the combined issues as an optimisation problem and then proposes an integrated framework that addresses the problem in a decentralised fashion. We approximate and decouple the complex original problem into three subproblems (i.e. coalition formation, position allocation and path planning), which are sequentially addressed by three different proposed modules. The coalition formation module based on game theories deals with a max-min problem, the objective of which is to partition the agents into disjoint task-specific teams in a way that balances the agents’ work resources in proportion to the task’s minimum workload requirements. For agents assigned to the same task, given reasonable assumptions, the position allocation subproblem can be efficiently addressed in terms of computational complexity. For the trajectory optimisation, we utilise a Model Predictive Control and Sequential Convex Programming algorithm, which reduces the size of the problem so that the agents can generate collision-free trajectories on a real-time basis. As a proof of concept, we implement the framework into an unmanned aerial vehicle swarm’s cooperative stand-in jamming mission scenario and show its feasibility, fault tolerance and near-optimality based on numerical experiment