Approximation of quantum control correction scheme using deep neural networks

We study the functional relationship between quantum control pulses in the idealized case and the pulses in the presence of an unwanted drift. We show that a class of artificial neural networks called LSTM is able to model this functional relationship with high efficiency, and hence the correction scheme required to counterbalance the effect of the drift. Our solution allows studying the mapping from quantum control pulses to system dynamics and then analysing the robustness of the latter against local variations in the control profile.Comment: 6 pages, 3 figures, Python code available upon request. arXiv admin note: text overlap with arXiv:1803.0516

Using the J1-J2 Quantum Spin Chain as an Adiabatic Quantum Data Bus

This paper investigates numerically a phenomenon which can be used to transport a single q-bit down a J1-J2 Heisenberg spin chain using a quantum adiabatic process. The motivation for investigating such processes comes from the idea that this method of transport could potentially be used as a means of sending data to various parts of a quantum computer made of artificial spins, and that this method could take advantage of the easily prepared ground state at the so called Majumdar-Ghosh point. We examine several annealing protocols for this process and find similar result for all of them. The annealing process works well up to a critical frustration threshold.Comment: 14 pages, 13 figures (2 added), revisions made to add citations and additional discussion at request of referee

99%-fidelity ballistic quantum-state transfer through long uniform channels

Quantum-state transfer with fidelity higher than 0.99 can be achieved in the ballistic regime of an arbitrarily long one-dimensional chain with uniform nearest-neighbor interaction, except for the two pairs of mirror symmetric extremal bonds, say x (first and last) and y (second and last-but-one). These have to be roughly tuned to suitable values x ~ 2 N^{-1/3} and y ~ 2^{3/4} N^{-1/6}, N being the chain length. The general framework can describe the end-to-end response in different models, such as fermion or boson hopping models and XX spin chains.Comment: 12 pages, 11 figures, 1 tabl

How to enhance quantum generative adversarial learning of noisy information

Quantum Machine Learning is where nowadays machine learning meets quantum information science. In order to implement this new paradigm for novel quantum technologies, we still need a much deeper understanding of its underlying mechanisms, before proposing new algorithms to feasibly address real problems. In this context, quantum generative adversarial learning is a promising strategy to use quantum devices for quantum estimation or generative machine learning tasks. However, the convergence behaviours of its training process, which is crucial for its practical implementation on quantum processors, have not been investigated in detail yet. Indeed here we show how different training problems may occur during the optimization process, such as the emergence of limit cycles. The latter may remarkably extend the convergence time in the scenario of mixed quantum states playing a crucial role in the already available noisy intermediate scale quantum devices. Then, we propose new strategies to achieve a faster convergence in any operating regime. Our results pave the way for new experimental demonstrations of such hybrid classical-quantum protocols allowing to evaluate the potential advantages over their classical counterparts.Comment: 16 pages, 9 figure

Optimal dynamics for quantum-state and entanglement transfer through homogeneous quantum wires

It is shown that effective quantum-state and entanglement transfer can be obtained by inducing a coherent dynamics in quantum wires with homogeneous intrawire interactions. This goal is accomplished by tuning the coupling between the wire endpoints and the two qubits there attached, to an optimal value. A general procedure to determine such value is devised, and scaling laws between the optimal coupling and the length of the wire are found. The procedure is implemented in the case of a wire consisting of a spin-1/2 XY chain: results for the time dependence of the quantities which characterize quantum-state and entanglement transfer are found of extremely good quality and almost independent of the wire length. The present approach does not require `ad hoc' engineering of the intrawire interactions nor a specific initial pulse shaping, and can be applied to a vast class of quantum channels.Comment: 5 pages, 5 figure

Nonperturbative Entangling Gates between Distant Qubits Using Uniform Cold Atom Chains

We propose a new fast scalable method for achieving a two-qubit entangling gate between arbitrary distant qubits in a network by exploiting dispersionless propagation in uniform chains. This is achieved dynamically by switching on a strong interaction between the qubits and a bus formed by a nonengineered chain of interacting qubits. The quality of the gate scales very efficiently with qubit separations. Surprisingly, a sudden switching of the couplings is not necessary. Moreover, our gate mechanism works for multiple gate operations without resetting the bus. We propose a possible experimental realization in cold atoms trapped in optical lattices and near field Fresnel trapping potentials

Spinal corollary discharge modulates motion sensing during vertebrate locomotion

During active movements, neural replicas of the underlying motor commands may assist in adapting motion-detecting sensory systems to an animal's own behaviour. The transmission of such motor efference copies to the mechanosensory periphery offers a potential predictive substrate for diminishing sensory responsiveness to self-motion during vertebrate locomotion. Here, using semi-isolated in vitro preparations of larval Xenopus, we demonstrate that shared efferent neural pathways to hair cells of vestibular endorgans and lateral line neuromasts express cyclic impulse bursts during swimming that are directly driven by spinal locomotor circuitry. Despite common efferent innervation and discharge patterns, afferent signal encoding at the two mechanosensory peripheries is influenced differentially by efference copy signals, reflecting the different organization of body/water motion-detecting processes in the vestibular and lateral line systems. The resultant overall gain reduction in sensory signal encoding in both cases, which likely prevents overstimulation, constitutes an adjustment to increased stimulus magnitudes during locomotion