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The accomplished functions of a variety of quantum devices are closely associated with the controlling of exciton transport. To this end we study the exciton transport of the two-dimensional system consisting of two-level multichains with various coupling configurations in a cavity. Two types of the chains are considered, including Tavis-Cummings and Su-Schrieffer-Heeger chain. Two conformations of the coupling between chains are considered, including square and triangle type. The effects of the inter-chain coupling, dimerization parameter, the cavity, the length of chains, and the number of chains on the exciton transport are in detail investigated for different coupling configurations of the multi-chain system through spectra and steady-state dynamics. The results show that in the absence of a cavity the exciton transport effciency is decided by the distribution of population of exciton on whole chains. However, when the cavity is considered the exciton transport currents and effciency of the system is controlled by the cavity-dressed energy level crossings and anticrossings near zero-energy modes, at which the coherent excitation and Landau-Zener transitions occur. Therefore, the exciton transport can be enhanced or suppressed at the crossings and anticrossings, in which the polariton acts as crucial role. Besides, it is discovered that the exciton transport effciency is closely related with the parity of both the length and the number of chains. This work is important for the understanding of the exciton transport mechanism in the multichain-cavity system, and provides theoretical basis for excitonic devices with controllable and effcient exciton transport.

Observing that the key for robotic action planning is to understand the target-object motion when its associated part is manipulated by the end effector, we propose to generate the 3D object-part scene flow and extract its transformations to solve the action trajectories for diverse embodiments. The advantage of our approach is that it derives the robot action explicitly from object motion prediction, yielding a more robust policy by understanding the object motions. Also, beyond policies trained on embodiment-centric data, our method is embodiment-agnostic, generalizable across diverse embodiments, and being able to learn from human demonstrations. Our method comprises three components: an object-part predictor to locate the part for the end effector to manipulate, an RGBD video generator to predict future RGBD videos, and a trajectory planner to extract embodiment-agnostic transformation sequences and solve the trajectory for diverse embodiments. Trained on videos even without trajectory data, our method still outperforms existing works significantly by 27.7% and 26.2% on the prevailing virtual environments MetaWorld and Franka-Kitchen, respectively. Furthermore, we conducted real-world experiments, showing that our policy, trained only with human demonstration, can be deployed to various embodiments., Comment: 8 pages, 7 figures

Topological dislocation modes resulting from the interplay between spatial dislocations and momentum-space topology have recently attracted significant interest. Here, we theoretically and experimentally demonstrate time-dislocation topological modes which are induced by the interplay between temporal dislocations and Floquet-band topology. By utilizing an extra physical dimension to represent the frequency-space lattice, we implement a two-dimensional Floquet higher-order topological phase and observe time-dislocation induced $\pi$-mode topological corner modes in a three-dimensional circuit metamaterial. Intriguingly, the realized time-dislocation topological modes exhibit spatial localization at the temporal dislocation, despite homogeneous in-plane lattice couplings across it. Our study opens a new avenue to explore the topological phenomena enabled by the interplay between real-space, time-space and momentum-space topology., Comment: 9 pages, 4 figures

Local density of states (LDOS) is emerging as powerful means of exploring synthetic topological phases. However, the current LDOS detection method remains rare and merely works for static situations. Here, we introduce a generic dynamical method to detect both the static and Floquet LDOS, based on an elegant connection between dynamics of chiral density and local spectral densities. Moreover, we find that the Floquet LDOS allows to measure out Floquet quasienergy spectra and identify topological $\pi$ modes. As an example, we demonstrate that both the static and Floquet higher-order topological phase can be universally identified via LDOS detection, regardless of whether the topological corner modes are in energy gaps, bands or continue energy spectra without bandgaps. Our study opens a new avenue utilizing dynamics to detect topological spectral densities and provides a universal approach of identifying static and Floquet topological phases.

Topological phases of ultracold atoms recently have been intensively studied both in optical superlattices and Raman lattices. However, the topological features induced by the interplay between such two lattices remain largely unexplored. Here, we present an optical Raman superlattice system that incorporates an optical superlattice and a Raman superlattice. The Raman superlattice presented here supports tunable dimerized spin-orbit couplings and staggered on-site spin flips. We find that such system respects a spin-rotation symmetry and has much richer topological properties. Specifically, we show that various topological phases could emerge in the optical Raman superlattice, such as four different chiral topological insulator phases and two different quantum spin Hall insulator phases, identified by spin winding and spin Chern numbers respectively. We also demonstrate that the spin-dependent topological invariants could be directly measured by quench dynamics.

Ultracold atoms trapped in optical superlattices provide a simple platform for realizing the seminal Aubry-Andr\'{e}-Harper (AAH) model. However, the periodic modulations on the nearest-neighbour hoppings have been ignored in this model. In this paper, we find that optical superlattice system actually can be approximately described by a generalized AAH model in the case of $V_1\gg V_2$, with periodic modulations on both on-site energies and nearest-neighbour hoppings, supporting much richer topological properties that are absent in the standard AAH model. Specifically, by calculating Chern numbers and topological edge states, we show that the generalized AAH model possesses multifarious topological phases and topological phase transitions, as compared to the standard AAH model only supporting a single topological phase. Our findings can open up more opportunities for using optical superlattices to study topological and localization physics.

Cellulose nanocrystals (CNCs) are bioderived nanoparticles that can be isolated from various sources of natural cellulose via acid hydrolysis. However, the link between particle morphological characteristics and their ensemble behavior is poorly understood, partly because of the difficulties in controlling the CNC morphology during their extraction process. In this work, the impacts of common post-hydrolysis treatments on the CNC morphology are investigated. The results indicate that the centrifugation step commonly applied during CNC purification favors the formation of composite particles made of aligned crystallites, referred to as 'bundles'. Scanning nanobeam electron diffraction reveals that such bundles are associated preferentially along their hydrophobic faces. This is in stark contrast to the formation of misaligned composite particles that can be achieved with ionic treatments, where an uncontrolled aggregation occurs. The functional relevance of these morphological differences is demonstrated by their effect on the cholesteric self-organization of CNCs, with bundles found to exhibit a greater chiral enhancement, whereas the misaligned composite particles found to promote gelation. This study reveals the importance of the often-disregarded purification steps on the final morphology of CNCs and their resulting ensemble properties, thereby unlocking new routes for tailoring this promising material towards a variety of applications.

We perform a comprehensive investigation of the PSF smoothing effect on the measurement of concentration-related parameters ($C$, Gini, $M_{20}$) of high redshift galaxies in the HST and JWST surveys. Our sample contains massive galaxies from the CANDELS/EGS survey (0 < z < 2), and the CEERS survey (1 < z < 3). The non-parametric concentration-related parameters ($C$, Gini, $M_{20}$) and the model-dependent parameters (n, Re) of these galaxies are derived from Statmorph and GALFIT, respectively. We try to evaluate the PSF smoothing effect by comparing the concentration-related parameters to the S\'{e}rsic index in both observations and mock images. We find that the concentration index is generally underestimated, especially for smaller galaxies with higher S\'{e}rsic index (eventually converging to the concentration index of the PSF). However, galaxies with lower S\'{e}rsic index ($n \leq 1$) or larger relative size are less affected by the PSF smoothing effect. The Gini coefficient and the absolute $M_{20}$ statistic also show similar behaviour as the concentration index. Caution should be taken for the possible correction of the concentration-related parameters, where both the relative size and the S\'{e}rsic index of the galaxy are important. Compared to the HST images, the PSF smoothing is much less severe for images in the CEERS survey due to the much higher spatial resolution. In fact, it is better to use the S\'{e}rsic index rather than the non-parametric morphology indicators to trace the light concentration for galaxies at high redshifts. From the single S\'{e}rsic modelling of the HST and JWST images, we also confirm that galaxies at higher redshift are more compact with smaller $R_e$. The lower mass galaxies are more disc-like ($n\sim1$) compared to the higher mass galaxies that are more spheroid dominated ($n\sim3$)., Comment: Accepted by A&A, 21 pages, 20 figures. Comments are welcome

Spin-1/2 kagome antiferromagnet (AFM) is one of the most studied models in frustrated magnetism since it is a promising candidate to host exotic spin liquid states. However, despite numerous studies using both analytical and numerical approaches, the nature of the ground state and low-energy excitations in this system remain elusive. This is related to the difficulty in determining the spin gap in various calculations. We present the results of our investigation of the Kagome AFM using the recently developed group equivariant convolutional neural networks - an advanced machine learning technique for studying strongly frustrated models. The approach, combined with variational Monte Carlo, introduces significant improvement of the achievable results accuracy in comparison with approaches based on other neural network architectures that lack generalization quality for frustrated spin systems. Contrary to the results obtained previously with various methods, that predicted Z_2 or U(1) Dirac spin liquid states, our results strongly indicate that the ground state of the kagome lattice antiferromagnet is a spinon pair density wave that does not break time-reversal symmetry or any of the lattice symmetries. The found state appears due to the spinon Cooper pairing instability close to two Dirac points in the spinon energy spectrum and resembles the pair density wave state studied previously in the context of underdoped cuprate superconductors in connection with the pseudogap phase. The state has significantly lower energy than the lowest energy states found by the SU(2) symmetric density matrix renormalization group calculations and other methods., Comment: 17 pages, 18 figures, comments welcome