Topological lasers are a new class of lasers that seek to exploit the special properties of topological states of light. A typical limiting factor in their performance is the existence of non-topological states with quality factors comparable to the
desired topological states. We show theoretically that, by special design of uniform gain and loss on two sublattices of a two-dimensional higher-order topological insulator (HOTI) lattice, single-mode lasing based on topological corner states can be sustained over a wide dynamic range of laser. This behavior stems from the phenomenon of parity/time-reversal breaking of the topological corner states, where the undesired edge and bulk states are suppressed much more effectively than through localized pumping of the domain corners. These promising results shed light on the opportunities for exploiting non-Hermitian phenomena in the design of high performance topological lasers with small footprint.
Compressed sensing fluorescence microscopy (CS-FM) proposes a scheme whereby less measurements are collected during sensing and reconstruction is performed to recover the image. Much work has gone into optimizing the sensing and reconstruction portio
ns separately. We propose a method of jointly optimizing both sensing and reconstruction end-to-end under a total measurement constraint, enabling learning of the optimal sensing scheme concurrently with the parameters of a neural network-based reconstruction network. We train our model on a rich dataset of confocal, two-photon, and wide-field microscopy images comprising of a variety of biological samples. We show that our method outperforms several baseline sensing schemes and a regularized regression reconstruction algorithm.
We perform a combined theoretical and experimental investigation of the superradiance in the quantum coherent system generated by strong laser fields. The semiclassical theory of superradiance that includes the superradiant temporal profile, characte
r duration, time delay, intensity is derived. The experimental data and theoretical predictions of 391-nm forward emission as a function of nitrogen gas pressure are compared and show good agreement. Our results not only demonstrate that the time-delayed optical amplification inside the molecular nitrogen ions is superradiance, but also reveal the quantum optical properties of strong-field physics.
Hadwiger Conjecture has been an open problem for over a half century1,6, which says that there is at most a complete graph Kt but no Kt+1 for every t-colorable graph. A few cases of Hadwiger Conjecture, such as 1, 2, 3, 4, 5, 6-colorable graphs have
been completely proved to convince all1-5, but the proofs are tremendously difficult for over the 5-colorable graph6,7. Although the development of graph theory inspires scientists to understand graph coloring deeply, it is still an open problem for over 7-colorable graphs6,7. Therefore, we put forward a brand new chromatic graph configuration and show how to describe the graph coloring issues in chromatic space. Based on this idea, we define a chromatic plane and configure the chromatic coordinates in Euler space. Also, we find a method to prove Hadwiger Conjecture for every 8-coloring graph feasible.
For the four-color theorem that has been developed over one and half centuries, all people believe it right but without complete proof convincing all1-3. Former proofs are to find the basic four-colorable patterns on a planar graph to reduce a map co
loring4-6, but the unavoidable set is almost limitless and required recoloring hardly implements by hand7-14. Another idea belongs to formal proof limited to logical operation15. However, recoloring or formal proof way may block people from discovering the inherent essence of a coloring graph. Defining creation and annihilation operations, we show that four colors are sufficient to color a map and how to color it. We find what trapped vertices and boundary-vertices are, and how they decide how many colors to be required in coloring arbitrary maps. We reveal that there is the fourth color for new adding vertex differing from any three coloring vertices in creation operation. To implement a coloring map, we also demonstrate how to color an arbitrary map by iteratively using creation and annihilation operations. We hope our hand proof is beneficial to understand the mechanisms of the four-color theorem.
We present radio observation of a millisecond pulsar PSR J0621+1002 using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The pulsar shows periodic pulse intensity modulations for both the first and the third pulse components. The f
luctuation spectrum of the first pulse component has one peak of 3.0$pm$0.1 pulse periods, while that of the third pulse component has two diffused peaks of 3.0$pm$0.1 and 200$pm$1 pulse periods. The single pulse timing analysis is carried out for this pulsar and the single pulses can be divided into two classes based on the post-fit timing residuals. We examined the achievable timing precision using only the pulses in one class or bright pulses. However, the timing precision improvement is not achievable.
This article comes up with an intraday trading strategy under T+1 using Markowitz optimization and Multilayer Perceptron (MLP) with published stock data obtained from the Shenzhen Stock Exchange and Shanghai Stock Exchange. The empirical results reve
al the profitability of Markowitz portfolio optimization and validate the intraday stock price prediction using MLP. The findings further combine the Markowitz optimization, an MLP with the trading strategy, to clarify this strategys feasibility.
Despite theoretical predictions for a Cherenkov-type radiation of spin waves (magnons) by various propagating magnetic perturbations, fast-enough moving magnetic field stimuli have not been available so far. Here, we experimentally realize the Cheren
kov radiation of spin waves in a Co-Fe magnonic conduit by fast-moving (>1 km/s) magnetic flux quanta (Abrikosov vortices) in an adjacent Nb-C superconducting strip. The radiation is evidenced by the microwave detection of spin waves propagating a distance of 2 micrometers from the superconductor and it is accompanied by a magnon Shapiro step in its current-voltage curve. The spin-wave excitation is unidirectional and monochromatic, with sub-40 nm wavelengths determined by the period of the vortex lattice. The phase-locking of the vortex lattice with the excited spin wave limits the vortex velocity and reduces the dissipation in the superconductor.
Fluid dynamics is one of the cornerstones of modern physics and has recently found applications in the transport of electrons in solids. In most solids electron transport is dominated by extrinsic factors, such as sample geometry and scattering from
impurities. However in the hydrodynamic regime Coulomb interactions transform the electron motion from independent particles to the collective motion of a viscous `electron fluid. The fluid viscosity is an intrinsic property of the electron system, determined solely by the electron-electron interactions. Resolving the universal intrinsic viscosity is challenging, as it only affects the resistance through interactions with the sample boundaries, whose roughness is not only unknown but also varies from device to device. Here we eliminate all unknown parameters by fabricating samples with smooth sidewalls to achieve the perfect slip boundary condition, which has been elusive both in molecular fluids and electronic systems. We engineer the device geometry to create viscous dissipation and reveal the true intrinsic hydrodynamic properties of a 2D system. We observe a clear transition from ballistic to hydrodynamic electron motion, driven by both temperature and magnetic field. We directly measure the viscosity and electron-electron scattering lifetime (the Fermi quasiparticle lifetime) over a wide temperature range without fitting parameters, and show they have a strong dependence on electron density that cannot be explained by conventional theories based on the Random Phase Approximation.
Reconstructing under-sampled k-space measurements in Compressed Sensing MRI (CS-MRI) is classically solved with regularized least-squares. Recently, deep learning has been used to amortize this optimization by training reconstruction networks on a da
taset of under-sampled measurements. Here, a crucial design choice is the regularization function(s) and corresponding weight(s). In this paper, we explore a novel strategy of using a hypernetwork to generate the parameters of a separate reconstruction network as a function of the regularization weight(s), resulting in a regularization-agnostic reconstruction model. At test time, for a given under-sampled image, our model can rapidly compute reconstructions with different amounts of regularization. We analyze the variability of these reconstructions, especially in situations when the overall quality is similar. Finally, we propose and empirically demonstrate an efficient and data-driven way of maximizing reconstruction performance given limited hypernetwork capacity. Our code is publicly available at https://github.com/alanqrwang/RegAgnosticCSMRI.
