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Full-color tuning in multi-layer core-shell nanoparticles from single-wavelength excitation

Lanthanide-based luminescent materials have shown great capabilities in addressing scientific problems encountered in diverse fields. However, achieving full-color switchable output under single-wavelength irradiation has remained a daunting challenge. Here we report a conceptual model to realize this aim by the temporal control of full upconversion evolution in a multi-layer core-shell nanostructure upon a single commercial 980-nm laser, instead of two or more excitation wavelengths as reported previously. We show that it is able to realize the red-to-green color change (from Er3+) under non-steady state excitation by constructing the cooperative modulation effect in the Er-Tm-Yb triple system, and single out the blue light (from Tm3+) by filtering out the short-decay emissions via a time-gating technique. The key role of Tm3+ in manipulating up-transition dynamics of Er3+ is further demonstrated. Our results present a deep insight into the photophysics of lanthanides, and help develop new generation of smart luminescent materials toward emerging photonic applications.

Three-dimensional imaging of topologically protected strings in a multiferroic nanocrystal

Multiferroic materials can host a plethora of intriguing phenomena due to the presence of multiple ferroic properties that break both spatial inversion symmetry and time reversal symmetry at an observable scale. Hexagonal manganite multiferroics are of particular interest as the properties of their symmetry-lowering phase transition can be described by a Mexican-hat-like potential energy surface. The early universe is proposed to have undergone a symmetry-lowering phase transition that is described by a similar Mexican-hat-like potential that gives rise to the formation of one-dimensional topologically protected defects known as cosmic strings. According to the Kibble-Zurek mechanism, hexagonal manganite multiferroics can host the crystallographic equivalent of cosmic strings and can therefore serve as a testing ground for exploration of concepts in cosmology. To date, however, direct imaging of 1D topological defects in a condensed matter material system has not been achieved. Here we report on robust three-dimensional imaging of topologically protected strings in a single hexagonal manganite nanocrystal, enabled by advances in experimental techniques. Our findings reveal multiferroic strings with a preferred phase vortex winding direction and average separation of  ~93 nm.

Photonic-crystal surface-emitting lasers

High-performance lasers are important to realize a range of applications including smart mobility and smart manufacturing, for example, through their uses in key technologies such as light detection and ranging (LiDAR) and laser processing. However, existing lasers have a number of performance limitations that hinder their practical use. For example, conventional semiconductor lasers are associated with low brightness and low functionality, even though they are compact and highly efficient. Conventional semiconductor lasers therefore require external optics and mechanical elements for reshaping and scanning of emitted beams, resulting in large, complicated systems for various practical uses. Furthermore, even with such external elements, the brightness of these lasers cannot be sufficiently increased for use in laser processing. Similarly, gas and solid-state lasers, while having high-brightness, are also large and complicated. Photonic-crystal surface-emitting lasers (PCSELs) boast both high brightness and high functionality while maintaining the merits of semiconductor lasers, and thus PCSELs are solutions to the issues of existing laser technologies. In this Review, we discuss recent progress of PCSELs towards high-brightness and high-functionality operations. We then elaborate on new trends such as short-pulse and short-wavelength operations as well as the combination with machine learning and quantum technologies. Finally, we outline future research directions of PCSELs with regard to various applications, including not only LiDAR and laser processing, as described above, but also communications, mobile technologies, and even aerospace and laser fusion.

Composite vortex air laser

Structured air laser generated through establishing high-gain air media in a cavity-free scheme by intense ultrashort pulses is promising for optical manipulation and quantum communication at standoff distances. However, the mechanism how the orbital angular momentum (OAM) information can be entangled into strong-field-induced gain media is still controversial, making manipulation of the topological charges of structured air laser remain a challenge. Here, we report the realization of a composite vortex N2+ air laser with controllable OAM by manipulating the relative positions, polarization directions, and intensity ratio between a Gaussian-shaped pump and an external vortex seed. Numerical simulations reveal the essential role of the interference between self-seeded Gaussian-shaped and externally-seeded vortex lasing emissions in the topological charge transformation. Our findings not only shed light on the generation mechanism of vortex air lasers, but also open up avenues for quantum manipulation of structured light through strong-field laser ionization of molecules remotely.

Latent circuit inference from heterogeneous neural responses during cognitive tasks

Higher cortical areas carry a wide range of sensory, cognitive and motor signals mixed in heterogeneous responses of single neurons tuned to multiple task variables. Dimensionality reduction methods that rely on correlations between neural activity and task variables leave unknown how heterogeneous responses arise from connectivity to drive behavior. We develop the latent circuit model, a dimensionality reduction approach in which task variables interact via low-dimensional recurrent connectivity to produce behavioral output. We apply the latent circuit inference to recurrent neural networks trained to perform a context-dependent decision-making task and find a suppression mechanism in which contextual representations inhibit irrelevant sensory responses. We validate this mechanism by confirming the behavioral effects of patterned connectivity perturbations predicted by the latent circuit model. We find similar suppression of irrelevant sensory responses in the prefrontal cortex of monkeys performing the same task. We show that incorporating causal interactions among task variables is critical for identifying behaviorally relevant computations from neural response data.

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