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Pre-training foundation models has become the de-facto procedure for deep learning approaches, yet its application remains limited in the geological studies, where in needs of the model transferability to break the shackle of data scarcity. Here we target on the X-ray fluorescence (XRF) scanning data, a standard high-resolution measurement in extensive scientific drilling projects. We propose a scalable self-supervised learner, masked autoencoders on XRF spectra (MAX), to pre-train a foundation model covering geological records from multiple regions of the Pacific and Southern Ocean. In pre-training, we find that masking a high proportion of the input spectrum (50\%) yields a nontrivial and meaningful self-supervisory task. For downstream tasks, we select the quantification of XRF spectra into two costly geochemical measurements, CaCO$_3$ and total organic carbon, due to their importance in understanding the paleo-oceanic carbon system. Our results show that MAX, requiring only one-third of the data, outperforms models without pre-training in terms of quantification accuracy. Additionally, the model's generalizability improves by more than 60\% in zero-shot tests on new materials, with explainability further ensuring its robustness. Thus, our approach offers a promising pathway to overcome data scarcity in geological discovery by leveraging the self-supervised foundation model and fast-acquired XRF scanning data.

The layered cobaltate CaCoO$_2$ exhibits a unique herringbone-like structure. Serving as a potential prototype for a new class of complex lattice patterns, we study the properties of CaCoO$_2$ using X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS). Our results reveal a significant inter-plane hybridization between the Ca $4s-$ and Co $3d-$orbitals, leading to an inversion of the textbook orbital occupation of a square planar geometry. Further, our RIXS data reveal a strong low energy mode, with anomalous intensity modulations as a function of momentum transfer close to a quasi-static response suggestive of electronic and/or orbital ordering. These findings indicate that the newly discovered herringbone structure exhibited in CaCoO$_2$ may serve as a promising laboratory for the design of materials having strong electronic, orbital and lattice correlations.

Let K/F be a CM extension satisfying the ordinary assumption for an odd prime p. In this article, we construct Hida families that interpolate theta lifts of algebraic Hecke characters to a definite unitary group U(2) defined from skew-Hermitian spaces over K, and show that the Hida family is primitive when the central L-value of the branch character of the family satisfies certain non-vanishing modulo p conditions.

In this research, patent prosecution is conceptualized as a system of reinforcement learning from human feedback. The objective of the system is to increase the likelihood for a language model to generate patent claims that have a higher chance of being granted. To showcase the controllability of the language model, the system learns from granted patents and pre-grant applications with different rewards. The status of "granted" and "pre-grant" are perceived as labeled human feedback implicitly. In addition, specific to patent drafting, the experiments in this research demonstrate the model's capability to learn from adjusting claim length and inclusion of limiting terms for narrowing claim scope. As proof of concept, the experiments focus on claim ones only and the training data originates from a patent dataset tailored specifically for artificial intelligence. Although the available human feedback in patent prosecution are limited and the quality of generated patent text requires improvement, the experiments following the 3-stage reinforcement learning from human feedback have demonstrated that generative language models are capable of reflecting the human feedback or intent in patent prosecution. To enhance the usability of language models, the implementation in this research utilizes modern techniques that enable execution on a single consumer-grade GPU. The demonstrated proof of concept, which reduces hardware requirements, will prove valuable in the future as more human feedback in patent prosecution become available for broader use, either within patent offices or in the public domain., Comment: 41 pages. Artif Intell Law (2024)

X-ray spectroscopy has been a key method to determine ground and excited state properties of quantum materials with atomic specificity. Now, new x-ray facilities are opening the door to the study of pump-probe x-ray spectroscopy - specifically time-resolved x-ray absorption (trXAS) and time-resolved resonant inelastic x-ray scattering (trRIXS). In this paper we will present simulations of each of these spectroscopies using a time-domain full atomic multiplet, charge transfer Hamiltonian, adapted to study the properties of a generalized cluster model including a central transition metal ion caged by ligand atoms in a planar geometry. The numerically evaluated trXAS and trRIXS cross-sections for representative electron configurations $3d^9$ and $3d^8$ demonstrate the insights that can be obtained from charge transfer pumping, and how this nonequilibrium process affects ground and excited state properties. The straightforward characterization of the excitations in these systems, based on our analysis of the simulations, can serve as a benchmark for future experiments, as access to these time-resolved spectroscopic techniques becomes more widely available.

Progress in the study of infinite-layer nickelates has always been highly linked to materials advances. In particular, the recent development of superconductivity via hole-doping was predicated on the controlled synthesis of Ni in a very high oxidation state, and subsequent topotactic reduction to a very low oxidation state, currently limited to epitaxial thin films. Here we demonstrate a process to combine these steps with a heterostructure which includes an epitaxial soluble buffer layer, enabling the release of freestanding membranes of (Nd,Sr)NiO2 encapsulated in SrTiO3, which serves as a protective layer. The membranes have comparable structural and electronic properties to that of optimized thin films, and range in lateral dimensions from millimeters to ~100 micron fragments, depending on the degree of strain released with respect to the initial substrate. The changes in the superconducting transition temperature associated with membrane release are quite similar to those reported for substrate and pressure variations, suggestive of a common underlying mechanism. These membranes structures should provide a versatile platform for a range of experimental studies and devices free from substrate constraints.

Taiwan has actively taken actions to support the aim of UNESCO's ESD (Education for Sustainable Development) for 2030 as well as SDGs (Sustainable Development Goals), and has to face and solve some emerging challenges that come with progress. This paper firstly introduces the status of STEM-related ESD/SDG Activities, and identifies the following five new challenges in teaching materials for STEM-related ESD/SDG activities: (1) Teachers are not familiar enough with teaching materials in non-specialized fields in cross-field STEM-related ESD/SDG activities; (2) Teachers need to spend too much time transforming ready-made social resources; (3) The ability of primary and secondary school teachers and students to use international teaching materials is often limited due to their language skills; (4) Lack of a comprehensive platform for exchange and sharing of teaching materials; and (5) The COVID-19 pandemic caused emergency remote teaching which suffered from limited quality online teaching materials.

Gravimetry is a versatile metrological approach in geophysics to accurately map subterranean mass and density anomalies. There is a broad diversification regarding the working principle of gravimeters, wherein atomic gravimeters are one of the most technologically progressive class of gravimeters which can monitor gravity at an absolute scale with a high-repetition without exhibiting drift. Despite the apparent utility for geophysical surveys, atomic gravimeters are (currently) laboratory-bound devices due to the vexatious task of transportation. Here, we demonstrated the utility of an atomic gravimeter on-site during a gravity survey, where the issue of immobility was circumvented with a relative spring gravimeter. The atomic gravimeter served as a means to map the relative data from the spring gravimeter to an absolute measurement with an effective precision of 7.7$\mu$Gal. Absolute measurements provide a robust and feasible method to define and control gravity data taken at different sites, or a later date, which is critical to analyze underground geological units, in particular when it is combined with other geophysical approaches.

Van der Waals (vdW) magnetic materials are comprised of layers of atomically thin sheets, making them ideal platforms for studying magnetism at the two-dimensional (2D) limit. These materials are at the center of a host of novel types of experiments, however, there are notably few pathways to directly probe their magnetic structure. We report the magnetic order within a single crystal of NiPS$_3$ and show it can be accessed with resonant elastic X-ray diffraction along the edge of the vdW planes in a carefully grown crystal by detecting structurally forbidden resonant magnetic X-ray scattering. We find the magnetic order parameter has a critical exponent of $\beta\sim0.36$, indicating that the magnetism of these vdW crystals is more adequately characterized by the three-dimensional (3D) Heisenberg universality class. We verify these findings with first-principle density functional theory, Monte-Carlo simulations, and density matrix renormalization group calculations.

Polarons - fermionic charge carriers bearing a strong companion lattice deformation - exhibit a natural tendency for self-localization due to the recursive interaction between electrons and the lattice. While polarons are ubiquitous in insulators, how they evolve in transitions to metallic and superconducting states in quantum materials remains an open question. Here, we use resonant inelastic x-ray scattering (RIXS) to track the electron-lattice coupling in the colossal magneto-resistive bi-layer manganite La$_{1.2}$Sr$_{1.8}$Mn$_2$O$_7$ across its metal-to-insulator transition. The response in the insulating high-temperature state features harmonic emissions of a dispersionless oxygen phonon at small energy transfer. Upon cooling into the metallic state, we observe a drastic redistribution of spectral weight from the region of these harmonic emissions to a broad high energy continuum. In concert with theoretical calculations, we show that this evolution implies a shift in electron-lattice coupling from static to dynamic lattice distortions that leads to a distinct polaronic ground state in the low temperature metallic phase - a dynamic polaron liquid.

This research aims to build generative language models specialized for the legal domain. The manuscript presents the development of LexGPT models based on GPT-J models and pre-trained with Pile of Law. The foundation model built in this manuscript is the initial step for the development of future applications in the legal domain, such as further training with reinforcement learning from human feedback. Another objective of this manuscript is to assist legal professionals in utilizing language models through the ``No Code'' approach. By fine-tuning models with specialized data and without modifying any source code, legal professionals can create custom language models for downstream tasks with minimum effort and technical knowledge. The downstream task in this manuscript is to turn a LexGPT model into a classifier, although the performance is notably lower than the state-of-the-art result. How to enhance downstream task performance without modifying the model or its source code is a research topic for future exploration., Comment: 10 pages and 2 figures. To be published in the Proceedings of the Seventeenth International Workshop on Juris-informatics (JURISIN 2023), hosted by JSAI International Symposia on AI 2023

Identifying quantum critical points (QCPs) and their associated fluctuations may hold the key to unraveling the unusual electronic phenomena observed in cuprate superconductors. Recently, signatures of quantum fluctuations associated with charge order (CO) have been inferred from the anomalous enhancement of CO excitations that accompany the reduction of the CO order parameter in the superconducting state. To gain more insight about the interplay between CO and superconductivity, here we investigate the doping dependence of this phenomenon throughout the Bi-2212 cuprate phase diagram using resonant inelastic x-ray scattering (RIXS) at the Cu L3- edge. As doping increases, the CO wavevector decreases, saturating at a commensurate value of 0.25 r.l.u. beyond a characteristic doping pc, where the correlation length becomes shorter than the apparent periodicity (4a0). Such behavior is indicative of the fluctuating nature of the CO; and the proliferation of CO excitations in the superconducting state also appears strongest at pc, consistent with expected behavior at a CO QCP. Intriguingly, pc appears to be near optimal doping, where the superconducting transition temperature Tc is maximal., Comment: This is a submitted version of the manuscript. The revised manuscript is now published on Physical Review B

Generative patent language models can assist humans to write patent text more effectively. The question is how to measure effectiveness from a human-centric perspective and how to improve effectiveness. In this manuscript, a simplified design of the autocomplete function is proposed to increase effectiveness by more than 10%. With the new design, the effectiveness of autocomplete can reach more than 60%, which means that more than 60% of keystrokes can be saved by autocomplete. Since writing patent text does not necessarily start from the beginning to the end, a question is whether the generative model can assist a user no matter where to start writing. To answer the question, the generative models in this manuscript are pre-trained with training data in both directions. The generative models become bidirectional. Since text generation is bidirectional, the calculation of autocomplete effectiveness can be bidirectional and starts from anywhere in the text. After thorough experiments, a key finding is that the autocomplete effectiveness of a model for the same text remains similar no matter where the calculation starts. The finding indicates that such bidirectional models can assist a user at a similar level, no matter where the user starts to write., Comment: 10 pages, 3 figures, 5 tables

Generative language models are promising for assisting human writing in various domains. This manuscript aims to build generative language models in the patent domain and evaluate model performance from a human-centric perspective. The perspective is to measure the ratio of keystrokes that can be saved by autocompletion based on generative patent language models. A higher ratio means a more effective model which can save more keystrokes. This metric can be used to benchmark model performance. The metric is different from conventional machine-centric metrics that are token-based instead of keystroke-based. In terms of model size, the largest model built in this manuscript is 6B, which is state-of-the-art in the patent domain. Based on the metric, it is found that the largest model is not necessarily the best for the human-centric metric. The finding means that keeping increasing model sizes in the patent domain might be unnecessary if the purpose is to assist human writing with autocompletion. Several patent language models are pre-trained from scratch in this research. The pre-trained models are released for future researchers. Several visualization tools are also provided. The importance of building a generative language model in the patent domain is the potential to facilitate creativity and innovations in the future., Comment: 12 pages, 7 figures, and 5 tables

A defining signature of strongly correlated electronic systems is the existence of competing phases with similar ground state energies, resulting in a rich phase diagram. While in the recently discovered nickelate superconductors, a high antiferromagnetic exchange energy has been reported, which implies the existence of strong electronic correlations, signatures of competing phases have not yet been observed. Here, we uncover a charge order (CO) in infinite-layer nickelates La1-xSrxNiO2 using resonant x-ray scattering across the Ni L-edge. In the parent compound, the CO arranges along the Ni-O bond direction with an incommensurate wave vector (0.344+/-0.002, 0) r.l.u., distinct from the stripe order in other nickelates which propagates along a direction 45 degree to the Ni-O bond. The CO resonance profile indicates that CO originates from the Ni 3d states and induces a parasitic charge modulation of La electrons. Upon doping, the CO diminishes and the ordering wave vector shifts toward a commensurate value of 1/3 r.l.u., indicating that the CO likely arises from strong correlation effects and not from Fermi surface nesting., Comment: 24 pages, 8 figures

We utilized high-energy-resolution resonant inelastic X-ray scattering (RIXS) at both the Ta and Ni $L_3$-edges to map out element-specific particle-hole excitations in Ta$_2$NiSe$_5$ across the phase transition. Our results reveal a momentum dependent gap-like feature in the low energy spectrum, which agrees well with the band gap in element-specific joint density of states calculations based on ab initio estimates of the electronic structure in both the low temperature monoclinic and the high temperature orthorhombic structure. Below $T_c$, the RIXS energy-momentum map shows a minimal gap at the Brillouin zone center ($\sim$ 0.16 eV), confirming that Ta$_2$NiSe$_5$ possesses a direct band gap in its low temperature ground state. However, inside the gap, no signature of anticipated collective modes with an energy scale comparable to the gap size can be identified. Upon increasing the temperature to above $T_c$, whereas the gap at the zone center closes, the RIXS map at finite momenta still possesses the gross features of the low temperature map, suggesting a substantial mixing between the Ta and Ni orbits in the conduction and valence bands, which does not change substantially across the phase transition. Our experimental observations and comparison to the theoretical calculations lend further support that the phase transition and the corresponding gap opening in Ta$_2$NiSe$_5$ is largely structural by nature with possible minor contribution from the putative exciton condensate., Comment: The manuscript has been accepted by Physical Review B