Efficient out-coupling of high-purity single photons from a coherent quantum dot in a photonic-crystal cavity

We demonstrate a single-photon collection efficiency of $(44.3\pm2.1)\%$ from a quantum dot in a low-Q mode of a photonic-crystal cavity with a single-photon purity of $g^{(2)}(0)=(4\pm5)\%$ recorded above the saturation power. The high efficiency is directly confirmed by detecting up to $962\pm46$ kilocounts per second on a single-photon detector on another quantum dot coupled to the cavity mode. The high collection efficiency is found to be broadband, as is explained by detailed numerical simulations. Cavity-enhanced efficient excitation of quantum dots is obtained through phonon-mediated excitation and under these conditions, single-photon indistinguishability measurements reveal long coherence times reaching $0.77\pm0.19$ ns in a weak-excitation regime. Our work demonstrates that photonic crystals provide a very promising platform for highly integrated generation of coherent single photons including the efficient out-coupling of the photons from the photonic chip.Comment: 13 pages, 8 figures, submitte

Ellipsometric measurements of the refractive indices of linear alkylbenzene and EJ-301 scintillators from 210 to 1000 nm

We report on ellipsometric measurements of the refractive indices of LAB-PPO, Nd-doped LAB-PPO and EJ-301 scintillators to the nearest +/-0.005, in the wavelength range 210-1000 nm.Comment: 7 pages, 4 figure

Simple Ginzburg-Landau Theory for Vortices in a Crystal Lattice

We study the Ginzburg-Landau model with a nonlocal quartic term as a simple phenomenological model for superconductors in the presence of coupling between the vortex lattice and the underlying crystal lattice. In mean-field theory, our model is consistent with a general oblique vortex lattice ranging from a triangular lattice to a square lattice. This simple formulation enables us to study the effect of thermal fluctuations in the vortex liquid regime. We calculate the structure factor of the vortex liquid nonperturbatively and find Bragg-like peaks with four-fold symmetry appearing in the structure factor even though there is only a short-range crystalline order.Comment: Revised version with new title and additional results for the vortex liquid regime, to be published in Phys. Rev. Lett. 5 pages RevTeX, 1 figure include

Detection of Gravitational Wave - An Application of Relativistic Quantum Information Theory

We show that a passing gravitational wave may influence the spin entropy and spin negativity of a system of $N$ massive spin-1/2 particles, in a way that is characteristic of the radiation. We establish the specific conditions under which this effect may be nonzero. The change in spin entropy and negativity, however, is extremely small. Here, we propose and show that this effect may be amplified through entanglement swapping. Relativistic quantum information theory may have a contribution towards the detection of gravitational wave.Comment: 9 page

A Patterned Architecture of Monoaminergic Afferents in the Cerebellar Cortex: Noradrenergic and Serotonergic Fibre Distributions within Lobules and Parasagittal Zones

The geometry of the glutamatergic mossy-parallel fibre and climbing fibre inputs to cerebellar cortical Purkinje cells has powerfully influenced thinking about cerebellar functions. The compartmentation of the cerebellum into parasagittal zones, identifiable in olivo-cortico-nuclear projections, and the trajectories of the parallel fibres, transverse to these zones and following the long axes of the cortical folia, are particularly important. Two monoaminergic afferent systems, the serotonergic and noradrenergic, are major inputs to the cerebellar cortex but their architecture and relationship with the cortical geometry are poorly understood. Immunohistochemistry for the serotonin transporter (SERT) and for the noradrenaline transporter (NET) revealed strong anisotropy of these afferent fibres in the molecular layer of rat cerebellar cortex. Individual serotonergic fibres travel predominantly medial-lateral, along the long axes of the cortical folia, similar to parallel fibres and Zebrin II immunohistochemistry revealed that they can influence multiple zones. In contrast, individual noradrenergic fibres run predominantly parasagittally with rostral-caudal extents significantly longer than their medial-lateral deviations. Their local area of influence has similarities in form and size to those of identified microzones. Within the molecular layer, the orthogonal trajectories of these two afferent systems suggest different information processing. An individual serotonergic fibre must influence all zones and microzones within its medial-lateral trajectory. In contrast, noradrenergic fibres can influence smaller cortical territories, potentially as limited as a microzone. Evidence is emerging that these monoaminergic systems may not supply a global signal to all of their targets and their potential for cerebellar cortical functions is discussed

Automatic Identification of Crystal Structures and Interfaces via Artificial-Intelligence-based Electron Microscopy

Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials. Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision. Here, we present AI-STEM, an automatic, artificial-intelligence based method, for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy (STEM) images of polycrystalline materials. The method is based on a Bayesian convolutional neural network (BNN) that is trained only on simulated images. AI-STEM automatically and accurately identifies crystal structure, lattice orientation, and location of interface regions in synthetic and experimental images. The model is trained on cubic and hexagonal crystal structures, yielding classifications and uncertainty estimates, while no explicit information on structural patterns at the interfaces is included during training. This work combines principles from probabilistic modeling, deep learning, and information theory, enabling automatic analysis of experimental, atomic-resolution images.Comment: Code (https://github.com/AndreasLeitherer/ai4stem) and data (https://doi.org/10.5281/zenodo.7756516) are available for public use. The manuscript contains 32 pages (10 pages main text, 15 pages for Methods & References & 5 Figures & 1 Table, as well as 7 pages Supplementary Information), including 5 main figures and 6 supplementary figure

Teleportation via thermally entangled state of a two-qubit Heisenberg XX chain

We find that quantum teleportation, using the thermally entangled state of two-qubit Heisenberg XX chain as a resource, with fidelity better than any classical communication protocol is possible. However, a thermal state with a greater amount of thermal entanglement does not necessarily yield better fidelity. It depends on the amount of mixing between the separable state and maximally entangled state in the spectra of the two-qubit Heisenberg XX model.Comment: 5 pages, 1 tabl

Memory consolidation in the cerebellar cortex

Several forms of learning, including classical conditioning of the eyeblink, depend upon the cerebellum. In examining mechanisms of eyeblink conditioning in rabbits, reversible inactivations of the control circuitry have begun to dissociate aspects of cerebellar cortical and nuclear function in memory consolidation. It was previously shown that post-training cerebellar cortical, but not nuclear, inactivations with the GABA(A) agonist muscimol prevented consolidation but these findings left open the question as to how final memory storage was partitioned across cortical and nuclear levels. Memory consolidation might be essentially cortical and directly disturbed by actions of the muscimol, or it might be nuclear, and sensitive to the raised excitability of the nuclear neurons following the loss of cortical inhibition. To resolve this question, we simultaneously inactivated cerebellar cortical lobule HVI and the anterior interpositus nucleus of rabbits during the post-training period, so protecting the nuclei from disinhibitory effects of cortical inactivation. Consolidation was impaired by these simultaneous inactivations. Because direct application of muscimol to the nuclei alone has no impact upon consolidation, we can conclude that post-training, consolidation processes and memory storage for eyeblink conditioning have critical cerebellar cortical components. The findings are consistent with a recent model that suggests the distribution of learning-related plasticity across cortical and nuclear levels is task-dependent. There can be transfer to nuclear or brainstem levels for control of high-frequency responses but learning with lower frequency response components, such as in eyeblink conditioning, remains mainly dependent upon cortical memory storage

Liquid-to-liquid phase transition in pancake vortex systems

We study the thermodynamics of a model of pancake vortices in layered superconductors. The model is based on the effective pair potential for the pancake vortices derived from the London approximation of a version of the Lawrence-Doniach model which is valid for extreme type-II superconductors. Using the hypernetted-chain (HNC) approximation, we find that there is a temperature below which multiple solutions to the HNC equations exist. By explicitly evaluating the free energy for each solution we find that the system undergoes a first-order transition between two vortex liquid phases. The low-temperature phase has larger correlations along the field direction than the high-temperature phase. We discuss the possible relation of this phase transition to the liquid-to-liquid phase transition recently observed in Y-Ba-Cu-O superconductors in high magnetic fields in the presence of disorder.Comment: 7 pages, 6 figure