Robust trajectory tracking control for unmanned surface vessels under motion constraints and environmental disturbances

To achieve a fully autonomous navigation for unmanned surface vessels (USVs), a robust control capability is essential. The control of USVs in complex maritime environments is rather challenging as numerous system uncertainties and environmental influences affect the control performance. This paper therefore investigates the trajectory tracking control problem for USVs with motion constraints and environmental disturbances. Two different controllers are proposed to achieve the task. The first approach is mainly based on the backstepping technique augmented by a virtual system to compensate for the disturbance and an auxiliary system to bound the input in the saturation limit. The second control scheme is mainly based on the normalisation technique, with which the bound of the input can be limited in the constraints by tuning the control parameters. The stability of the two control schemes is demonstrated by the Lyapunov theory. Finally, simulations are conducted to verify the effectiveness of the proposed controllers. The introduced solutions enable USVs to follow complex trajectories in an adverse environment with varying ocean currents

Preparing and probing atomic number states with an atom interferometer

We describe the controlled loading and measurement of number-squeezed states and Poisson states of atoms in individual sites of a double well optical lattice. These states are input to an atom interferometer that is realized by symmetrically splitting individual lattice sites into double wells, allowing atoms in individual sites to evolve independently. The two paths then interfere, creating a matter-wave double-slit diffraction pattern. The time evolution of the double-slit diffraction pattern is used to measure the number statistics of the input state. The flexibility of our double well lattice provides a means to detect the presence of empty lattice sites, an important and so far unmeasured factor in determining the purity of a Mott state

Preparation and detection of d-wave superfluidity in two-dimensional optical superlattices

We propose a controlled method to create and detect d-wave superfluidity with ultracold fermionic atoms loaded in two-dimensional optical superlattices. Our scheme consists in preparing an array of nearest-neighbor coupled square plaquettes or ``superplaquettes'' and using them as building blocks to construct a d-wave superfluid state. We describe how to use the coherent dynamical evolution in such a system to experimentally probe the pairing mechanism. We also derive the zero temperature phase diagram of the fermions in a checkerboard lattice (many weakly coupled plaquettes) and show that by tuning the inter-plaquette tunneling spin-dependently or varying the filling factor one can drive the system into a d-wave superfluid phase or a Cooper pair density wave phase. We discuss the use of noise correlation measurements to experimentally probe these phases.Comment: 8 pages, 6 figure

Driven Macroscopic Quantum Tunneling of Ultracold Atoms in Engineered Optical Lattices

Coherent macroscopic tunneling of a Bose-Einstein condensate between two parts of an optical lattice separated by an energy barrier is theoretically investigated. We show that by a pulsewise change of the barrier height, it is possible to switch between tunneling regime and a self-trapped state of the condensate. This property of the system is explained by effectively reducing the dynamics to the nonlinear problem of a particle moving in a double square well potential. The analysis is made for both attractive and repulsive interatomic forces, and it highlights the experimental relevance of our findings

A new method based on noise counting to monitor the frontend electronics of the LHCb muon detector

A new method has been developed to check the correct behaviour of the frontend electronics of the LHCb muon detector. This method is based on the measurement of the electronic noise rate at different thresholds of the frontend discriminator. The method was used to choose the optimal discriminator thresholds. A procedure based on this method was implemented in the detector control system and allowed the detection of a small percentage of frontend channels which had deteriorated. A Monte Carlo simulation has been performed to check the validity of the method

Near-optimal energy management for plug-in hybrid fuel cell and battery propulsion using deep reinforcement learning

Plug-in hybrid fuel cell and battery propulsion systems appear promising for decarbonising transportation applications such as road vehicles and coastal ships. However, it is challenging to develop optimal or near-optimal energy management for these systems without exact knowledge of future load profiles. Although efforts have been made to develop strategies in a stochastic environment with discrete state space using Q-learning and Double Q-learning, such tabular reinforcement learning agents’ effectiveness is limited due to the state space resolution. This article aims to develop an improved energy management system using deep reinforcement learning to achieve enhanced cost-saving by extending discrete state parameters to be continuous. The improved energy management system is based upon the Double Deep Q-Network. Real-world collected stochastic load profiles are applied to train the Double Deep Q-Network for a coastal ferry. The results suggest that the Double Deep Q-Network acquired energy management strategy has achieved a further 5.5% cost reduction with a 93.8% decrease in training time, compared to that produced by the Double Q-learning agent in discrete state space without function approximations. In addition, this article also proposes an adaptive deep reinforcement learning energy management scheme for practical hybrid-electric propulsion systems operating in changing environments

Muon identification for LHCb Run 3

Muon identification is of paramount importance for the physics programme of LHCb. In the upgrade phase, starting from Run 3 of the LHC, the trigger of the experiment will be solely based on software. The luminosity increase to $2\times10^{33}$ cm$^{-2}$s$^{-1}$ will require an improvement of the muon identification criteria, aiming at performances equal or better than those of Run 2, but in a much more challenging environment. In this paper, two new muon identification algorithms developed in view of the LHCb upgrade are presented, and their performance in terms of signal efficiency versus background reduction is shown

Collective decoherence of cold atoms coupled to a Bose-Einstein condensate

We examine the time evolution of cold atoms (impurities) interacting with an environment consisting of a degenerate bosonic quantum gas. The impurity atoms differ from the environment atoms, being of a different species. This allows one to superimpose two independent trapping potentials, each being effective only on one atomic kind, while transparent to the other. When the environment is homogeneous and the impurities are confined in a potential consisting of a set of double wells, the system can be described in terms of an effective spin-boson model, where the occupation of the left or right well of each site represents the two (pseudo)-spin states. The irreversible dynamics of such system is here studied exactly, i.e., not in terms of a Markovian master equation. The dynamics of one and two impurities is remarkably different in respect of the standard decoherence of the spin - boson system. In particular we show: i) the appearance of coherence oscillations, i) the presence of super and sub decoherent states which differ from the standard ones of the spin boson model, and iii) the persistence of coherence in the system at long times. We show that this behaviour is due to the fact that the pseudospins have an internal spatial structure. We argue that collective decoherence also prompts information about the correlation length of the environment. In a one dimensional configuration one can change even stronger the qualitative behaviour of the dephasing just by tuning the interaction of the bath.Comment: 18 pages, 6 figures, two references adde

Nonadiabatic Dynamics of Ultracold Fermions in Optical Superlattices

We study the time-dependent dynamical properties of two-component ultracold fermions in a one-dimensional optical superlattice by applying the adaptive time-dependent density matrix renormalization group to a repulsive Hubbard model with an alternating superlattice potential. We clarify how the time evolution of local quantities occurs when the superlattice potential is suddenly changed to a normal one. For a Mott-type insulating state at quarter filling, the time evolution exhibits a profile similar to that expected for bosonic atoms, where correlation effects are less important. On the other hand, for a band-type insulating state at half filling, the strong repulsive interaction induces an unusual pairing of fermions, resulting in some striking properties in time evolution, such as a paired fermion co-tunneling process and the suppression of local spin moments. We further address the effect of a confining potential, which causes spatial confinement of the paired fermions.Comment: 4 pages, 5 figure