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Hagedorn wavepackets have been used with local harmonic approximation to partially capture the anharmonic effects on single vibronic level (SVL) spectra in model potentials. To make the Hagedorn approach practical for realistic anharmonic polyatomic molecules, here we combine local harmonic Hagedorn wavepacket dynamics with on-the-fly ab initio dynamics. We then test this method by computing the SVL fluorescence spectra of difluorocarbene, a small, floppy molecule with a very anharmonic potential energy surface. Our time-dependent approach obtains the emission spectra of all initial vibrational levels from a single anharmonic semiclassical wavepacket trajectory without the need to fit individual anharmonic vibrational wavefunctions and to calculate the Franck--Condon factors for all vibronic transitions. We show that, whereas global harmonic models are inadequate for CF$_2$, the spectra computed with the on-the-fly local harmonic Hagedorn wavepacket dynamics agree well with experimental data, especially for low initial excitations.

Hagedorn wavepacket dynamics yields exact single vibronic level (SVL) fluorescence spectra from any initial vibrational level in displaced, squeezed, and Duschinsky-rotated global harmonic models. Real molecules, however, have anharmonic potential energy surfaces. To partially describe effects of anharmonicity on the spectra, we combine the Hagedorn approach to spectroscopy with the local harmonic approximation of the potential. We compute the SVL spectra for several anharmonic Morse-type potentials in one, two, and twenty dimensions and compare them to the results of global harmonic approximations and, where possible, of exact quantum calculations. We show that the local harmonic approach yields more accurate results than global harmonic approximations, especially for the emission spectra from higher initial vibrational levels., Comment: 7 pages, 5 figures

AI-aided clinical diagnosis is desired in medical care. Existing deep learning models lack explainability and mainly focus on image analysis. The recently developed Dynamic Uncertain Causality Graph (DUCG) approach is causality-driven, explainable, and invariant across different application scenarios, without problems of data collection, labeling, fitting, privacy, bias, generalization, high cost and high energy consumption. Through close collaboration between clinical experts and DUCG technicians, 46 DUCG models covering 54 chief complaints were constructed. Over 1,000 diseases can be diagnosed without triage. Before being applied in real-world, the 46 DUCG models were retrospectively verified by third-party hospitals. The verified diagnostic precisions were no less than 95%, in which the diagnostic precision for every disease including uncommon ones was no less than 80%. After verifications, the 46 DUCG models were applied in the real-world in China. Over one million real diagnosis cases have been performed, with only 17 incorrect diagnoses identified. Due to DUCG's transparency, the mistakes causing the incorrect diagnoses were found and corrected. The diagnostic abilities of the clinicians who applied DUCG frequently were improved significantly. Following the introduction to the earlier presented DUCG methodology, the recommendation algorithm for potential medical checks is presented and the key idea of DUCG is extracted.

Using generative models to synthesize new data has become a de-facto standard in autonomous driving to address the data scarcity issue. Though existing approaches are able to boost perception models, we discover that these approaches fail to improve the performance of planning of end-to-end autonomous driving models as the generated videos are usually less than 8 frames and the spatial and temporal inconsistencies are not negligible. To this end, we propose Delphi, a novel diffusion-based long video generation method with a shared noise modeling mechanism across the multi-views to increase spatial consistency, and a feature-aligned module to achieves both precise controllability and temporal consistency. Our method can generate up to 40 frames of video without loss of consistency which is about 5 times longer compared with state-of-the-art methods. Instead of randomly generating new data, we further design a sampling policy to let Delphi generate new data that are similar to those failure cases to improve the sample efficiency. This is achieved by building a failure-case driven framework with the help of pre-trained visual language models. Our extensive experiment demonstrates that our Delphi generates a higher quality of long videos surpassing previous state-of-the-art methods. Consequentially, with only generating 4% of the training dataset size, our framework is able to go beyond perception and prediction tasks, for the first time to the best of our knowledge, boost the planning performance of the end-to-end autonomous driving model by a margin of 25%., Comment: Project Page: https://westlake-autolab.github.io/delphi.github.io/, 8 figures

Aqueous batteries play an increasingly important role for the development of sustainable and safety-prioritised energy storage solutions. Compared to conventional lithium-ion batteries, the cell chemistry in aqueous batteries share many common features with those of electrolyzer and pseudo-capacitor systems because of the involvement of aqueous electrolyte and proton activity. This imposes the needs for a better understanding of the corresponding ion solvation, intercalation and electron transfer processes at atomistic scale. Therefore, this chapter provides an up-to-date overview of molecular modelling techniques and their applications in aqueous batteries. In particular, we emphasize on the dynamical and reactive description of aqueous battery systems brought in by density functional theory-based molecular dynamics simulation (DFTMD) and its machine-learning (ML) accelerated counterpart. Moreover, we also cover the recent advancement of generative artificial intelligence (AI) in molecular and materials design of aqueous batteries. Case studies presented here include popular aqueous battery systems, such as water-in-salt electrolytes, proton-coupled cathode materials, Zn-ion batteries as well as organic redox flow batteries.

Hagedorn functions are carefully constructed generalizations of Hermite functions to the setting of many-dimensional squeezed and coupled harmonic systems. Wavepackets formed by superpositions of Hagedorn functions have been successfully used to solve the time-dependent Schr\"{o}dinger equation exactly in harmonic systems and variationally in anharmonic systems. For evaluating typical observables, such as position or kinetic energy, it is sufficient to consider orthonormal Hagedorn functions with a single Gaussian center. Here, we instead derive various relations between Hagedorn bases associated with different Gaussians, including their overlaps, which are necessary for evaluating quantities nonlocal in time, such as time correlation functions needed for computing spectra. First, we use the Bogoliubov transformation to obtain commutation relations between the ladder operators associated with different Gaussians. Then, instead of using numerical quadrature, we employ these commutation relations to derive exact recurrence relations for the overlap integrals between Hagedorn functions with different Gaussian centers. Finally, we present numerical experiments that demonstrate the accuracy and efficiency of our algebraic method as well as its suitability to treat problems in spectroscopy and chemical dynamics., Comment: 26 pages, 2 figures; corrected the prefactor in eqs. 43, 65 and 66

Image-text retrieval (ITR) plays a significant role in making informed decisions for various remote sensing (RS) applications. Nonetheless, creating ITR datasets containing vision and language modalities not only requires significant geo-spatial sampling area but also varing categories and detailed descriptions. To this end, we introduce an image caption dataset LuojiaHOG, which is geospatial-aware, label-extension-friendly and comprehensive-captioned. LuojiaHOG involves the hierarchical spatial sampling, extensible classification system to Open Geospatial Consortium (OGC) standards, and detailed caption generation. In addition, we propose a CLIP-based Image Semantic Enhancement Network (CISEN) to promote sophisticated ITR. CISEN consists of two components, namely dual-path knowledge transfer and progressive cross-modal feature fusion. Comprehensive statistics on LuojiaHOG reveal the richness in sampling diversity, labels quantity and descriptions granularity. The evaluation on LuojiaHOG is conducted across various state-of-the-art ITR models, including ALBEF, ALIGN, CLIP, FILIP, Wukong, GeoRSCLIP and CISEN. We use second- and third-level labels to evaluate these vision-language models through adapter-tuning and CISEN demonstrates superior performance. For instance, it achieves the highest scores with WMAP@5 of 88.47\% and 87.28\% on third-level ITR tasks, respectively. In particular, CISEN exhibits an improvement of approximately 1.3\% and 0.9\% in terms of WMAP@5 compared to its baseline. These findings highlight CISEN advancements accurately retrieving pertinent information across image and text. LuojiaHOG and CISEN can serve as a foundational resource for future RS image-text alignment research, facilitating a wide range of vision-language applications.

The interplay of lattice, electronic, and spin degrees of freedom at epitaxial complex oxide interfaces provides a route to tune their magnetic ground states. Unraveling the competing contributions is critical for tuning their functional properties. We investigate the relationship between magnetic ordering and magnetic anisotropy and the lattice symmetry, oxygen content, and film thickness in compressively strained LaMnO$_3$/LaCrO$_3$ superlattices. Mn-O-Cr antiferromagnetic superexchange interactions across the heterointerface resulting in a net ferrimagnetic magnetic structure. Bulk magnetometry measurements reveal isotropic in-plane magnetism for as-grown oxygen-deficient thinner thin samples due to equal fractions of orthorhombic a+a-c-, and a-a+c- twin domains. As the superlattice thickness is increased, in-plane magnetic anisotropy emerges as the fraction of the a+a-c- domain increases. On annealing in oxygen, the suppression of oxygen vacancies results in a contraction of the lattice volume, and an orthorhombic to rhombohedral transition leads to isotropic magnetism independent of the film thickness. The complex interactions are investigated using high-resolution synchrotron diffraction and X-ray absorption spectroscopy. These results highlight the role of the evolution of structural domains with film thickness, interfacial spin interactions, and oxygen-vacancy-induced structural phase transitions in tuning the magnetic properties of complex oxide heterostructures.

Single vibronic level (SVL) fluorescence spectroscopy contributes to the understanding of molecular vibrational structures and relaxation processes. Here, we present a practical method for computing SVL fluorescence spectra of polyatomic molecules from arbitrary initial vibrational levels. This method, which combines a time-dependent approach using Hagedorn wavepackets with accurate evaluation of electronic structure, captures both mode distortion and Duschinsky rotation. We apply the method to compute SVL spectra of anthracene by performing wavepacket dynamics on a 66- dimensional harmonic potential energy surface constructed from density functional theory calculations. With the Hagedorn approach, we not only reproduce the previously reported simulation results for singly excited $12^{1}$ and $\overline{11}^{1}$ levels, but also are able to compute SVL spectra from multiply excited levels in good agreement with experiments. All spectra were obtained from the same wavepacket trajectory without any additional propagation beyond what is required for ground-state emission spectra., Comment: 12 pages, 3 figures; v3: text revisions

In single vibronic level (SVL) fluorescence experiments, the electronically excited initial state is also excited in one or several vibrational modes. Whereas computing all contributing Franck-Condon factors individually becomes impractical in large systems, a time-dependent formalism has not been applied to simulate emission from arbitrary initial vibrational levels. Here, we use Hagedorn functions, which are products of a Gaussian and carefully generated polynomials, to represent SVL initial states. In systems where the potential is at most quadratic, the Hagedorn functions are exact solutions to the time-dependent Schr\"{o}dinger equation and can be propagated with the same equations of motion as a simple Gaussian wavepacket. Having developed an efficient recursive algorithm to compute the overlaps between two Hagedorn wavepackets, we can now evaluate emission spectra from arbitrary vibronic levels using a single trajectory. We validate the method in two-dimensional global harmonic models by comparing it with quantum split-operator calculations. Additionally, we study the effects of displacement, distortion (squeezing), and Duschinsky rotation on SVL spectra. Finally, we demonstrate the applicability of the Hagedorn approach to high-dimensional systems on an example of displaced, distorted, and Duschinsky-rotated harmonic model with 100 degrees of freedom., Comment: 8 pages, 5 figures

Ultrafast stimuli can stabilize metastable states of matter inaccessible by equilibrium means. Establishing the spatiotemporal link between ultrafast excitation and metastability is crucial to understanding these phenomena. Here, we use single-shot optical-pump, X-ray-probe measurements to provide snapshots of the emergence of a persistent polar vortex supercrystal in a heterostructure that hosts a fine balance between built-in electrostatic and elastic frustrations by design. By perturbing this balance with photoinduced charges, a starting heterogenous mixture of polar phases disorders within a few picoseconds, resulting in a soup state composed of disordered ferroelectric and suppressed vortex orders. On the pico-to-nanosecond timescales, transient labyrinthine fluctuations form in this soup along with a recovering vortex order. On longer timescales, these fluctuations are progressively quenched by dynamical strain modulations, which drive the collective emergence of a single supercrystal phase. Our results, corroborated by dynamical phase-field modeling, reveal how ultrafast excitation of designer systems generates pathways for persistent metastability.

Developing novel lead-free ferroelectric materials is crucial for next-generation microelectronic technologies that are energy efficient and environment friendly. However, materials discovery and property optimization are typically time-consuming due to the limited throughput of traditional synthesis methods. In this work, we use a high-throughput combinatorial synthesis approach to fabricate lead-free ferroelectric superlattices and solid solutions of (Ba0.7Ca0.3)TiO3 (BCT) and Ba(Zr0.2Ti0.8)O3 (BZT) phases with continuous variation of composition and layer thickness. High-resolution X-ray diffraction (XRD) and analytical scanning transmission electron microscopy (STEM) demonstrate high film quality and well-controlled compositional gradients. Ferroelectric and dielectric property measurements identify the optimal property point achieved at the morphotropic phase boundary (MPB) with a composition of 48BZT-52BCT. Displacement vector maps reveal that ferroelectric domain sizes are tunable by varying {BCT-BZT}N superlattice geometry. This high-throughput synthesis approach can be applied to many other material systems to expedite new materials discovery and properties optimization, allowing for the exploration of a large area of phase space within a single growth., Comment: submitted

We present a numerically exact approach for evaluating vibrationally resolved electronic spectra at finite temperatures using the coherence thermofield dynamics. In this method, which avoids implementing an algorithm for solving the von Neumann equation for coherence, the thermal vibrational ensemble is first mapped to a pure-state wavepacket in an augmented space, and this wavepacket is then propagated by solving the standard, zero-temperature Schr\"odinger equation with the split-operator Fourier method. We show that the finite-temperature spectra obtained with the coherence thermofield dynamics in a Morse potential agree exactly with those computed by Boltzmann-averaging the spectra of individual vibrational levels. Because the split-operator thermofield dynamics on a full tensor-product grid is restricted to low-dimensional systems, we briefly discuss how the accessible dimensionality can be increased by various techniques developed for the zero-temperature split-operator Fourier method., Comment: 5 pages, 4 figures

We reveal in this study the fundamental low-energy landscape in the ferrimagnetic Sr2CrReO6 double perovskite and describe the underlying mechanisms responsible for the three low-energy excitations below 1.4 eV. Based on resonant inelastic x-ray scattering and magnetic dynamics calculations, and experiments collected from both Sr2CrReO6 powders and epitaxially strained thin films, we reveal a strong competition between spin-orbit coupling, Hund's coupling, and the strain-induced tetragonal crystal field. We also demonstrate that a spin-flip process is at the origin of the lowest excitation at 200 meV, and we bring insights into the predicted presence of orbital ordering in this material. We study the nature of the magnons through a combination of ab initio and spin-wave theory calculations, and show that two nondegenerate magnon bands exist and are dominated either by rhenium or chromium spins. The rhenium band is found to be flat at about 200 meV ($\pm$25 meV) through X-L-W-U high-symmetry points and is dispersive toward $\Gamma$, Comment: 6 figures

Neuromorphic functionalities in memristive devices are commonly associated with the ability to electrically create local conductive pathways by resistive switching. The archetypal correlated material, VO2, has been intensively studied for its complex electronic and structural phase transition as well as its filament formation under applied voltages. Local structural studies of the filament behavior are often limited due to time-consuming rastering which makes impractical many experiments aimed at investigating large spatial areas or temporal dynamics associated with the electrical triggering of the phase transition. Utilizing Dark Field X-ray Microscopy (DFXM), a novel full-field x-ray imaging technique, we study this complex filament formation process in-operando in VO2 devices from a structural perspective. We show that prior to filament formation, there is a significant gain of the metallic rutile phase beneath the metal electrodes that define the device. We observed that the filament formation follows a preferential path determined by the nucleation sites within the device. These nucleation sites are predisposed to the phase transition and can persistently maintain the high-temperature rutile phase even after returning to room temperature, which can enable a novel training/learning mechanism. Filament formation also appears to follow a preferential path determined by a nucleation site within the device which is predisposed to the rutile transition even after returning to room temperature. Finally, we found that small isolated low-temperature phase clusters can be present inside the high-temperature filaments indicating that the filament structure is not uniform. Our results provide a unique perspective on the electrically induced filament formation in metal-insulator transition materials, which further the basic understanding of this resistive switching., Comment: 29 pages, 10 figures; 19 pages main text, 3 figures; 10 pages Supplementary material, 7 figures

Relaxor ferroelectrics are a class of materials that are widely perceived as deriving their exotic properties from structural heterogeneities. Understanding the microscopic origin of the superior electromechanical response requires knowledge not only concerning the formation of polar nanodomains (PNDs) built from individual atoms but more importantly the spatial distribution of PNDs over longer distances. The mesoscale PND arrangement is shaped by the interactions between these domains and, in turn, dictates the electric-field driven PND response directly relevant to the macroscopic material properties. Here, we show the emergence of mesoscale lattice order that we name "polar laminates" in the canonical relaxor ferroelectric 0.68PbMg$_{1/3}$Nb$_{2/3}$O$_{3}$-0.32PbTiO$_{3}$ (PMN-0.32PT) using X-ray coherent nano-diffraction. These laminates are nematic with a size of ~350 nm and arise from the staggered arrangement of ~13 nm monoclinic PNDs along the <110> of the pseudocubic lattice. The spatial distribution of c-axis strain is directly correlated with the tilting of the PNDs and is most prominent between the laminates. Further operando nano-diffraction studies demonstrate heterogeneous electric-field-driven responses. The most active regions tend to reside inside the laminates while the spatial pinning centers are between the laminates. This observation reveals the hierarchical assembly of lattice order as a novel form of electron and lattice self-organization in heterogenous materials and establishes the role of such mesoscale spatial arrangement in connecting the nanoscale heterogeneity and macroscopic material properties. These findings provide a guiding principle for the design and optimization of future relaxors and may shed light on the existence of similar behavior in a wide range of quantum and functional materials., Comment: 12 pages, 4 figures

The orbital, which represents the shape of the electron cloud, very often strongly influences the manifestation of various exotic phenomena, e.g., magnetism, metal-insulator transition, colossal magnetoresistance, unconventional superconductivity etc. in solid-state systems. The observation of the antiferromagnetism in $RE$TiO$_3$ ($RE$=rare earth) series has been puzzling since the celebrated Kugel-Khomskii model of spin-orbital super exchange predicts ferromagnetism in an orbitally degenerate $d^1$ systems. Further, the existence of the orbitally ordered vs. orbital liquid phase in both antiferromagnetic and paramagnetic phase have been unsettled issues thus far. To address these long-standing questions, we investigate single crystalline film of PrTiO$_3$. Our synchrotron X-ray diffraction measurements confirm the retention of bulk-like orthorhombic ($D_{2h}$) symmetry in the thin film geometry. We observe similar X-ray linear dichroism signal in both paramagnetic and antiferromagnetic phase, which can be accounted by ferro orbital ordering (FOO). While the presence of $D_{2h}$ crystal field does not guarantee lifting of orbital degeneracy always, we find it to be strong enough in these rare-earth titanates, leading to the FOO state. Thus, our work demonstrates the orthorhombic distortion is the driving force for the orbital ordering of antiferromagnetic $RE$TiO$_3$., Comment: 37 pages and 17 figures

Dark-field x-ray microscopy utilizes Bragg diffraction to collect full-field x-ray images of "mesoscale" structure of ordered materials. Information regarding the structural heterogeneities and their physical implications is gleaned through the quantitative analyses of these images. Namely, one must be able to extract diffraction features that arise from lattice modulations or inhomogeneities, quantify said features, and identify and track patterns in the relevant quantitative properties in subsequent images. Due to the necessity to track features with a wide array of shapes and length scales while maintaining spatial resolution, wavelet transforms were chosen as a potent signal analysis tool. In addition to addressing multiple length scales, this method can be used in conjunction with other signal processing methods such as image binarization for increased functionality. In this article, we demonstrate three effective use of wavelet analyses pertaining to DFXM. We show how to extract and track smooth linear features-which are diffraction manifestations of twin boundaries-as the sample orientation changes as it is rotated about momentum transfer. Secondly, we show that even the simplest wavelet transform, the Haar transform, can be used to capture the primary features in DFXM images, over a range of length scales in different regions of interest within a single image enabling localized reconstruction. As a final application, we extend these techniques to determine when a DFXM image is in focus.