High-pressure electride (HPE) superconductors often maintain structural symmetry over a wide pressure range, whereas their interstitial anion electrons (IAEs) undergo significant changes in topology and energy levels,...
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High-pressure electride (HPE) superconductors often maintain structural symmetry over a wide pressure range, whereas their interstitial anion electrons (IAEs) undergo significant changes in topology and energy levels, potentially resulting in topological Lifshitz transitions in their Fermi surfaces. These Lifshitz transitions can play critical roles in influencing superconducting properties. However, their impact on the superconductivity of HPEs remains largely unexplored. To address this gap, we investigate a novel HPE, Li4Pd, which features distinct Fermi surfaces, including a hole ellipsoid and a warped electron rectangular cylinder. This combination satisfies the conditions for a Kohn anomaly, suggesting that Li4Pd may be a potential HPE superconductor. Our theoretical calculations reveal that under high pressures, the Fermi surface of Li4Pd undergoes a Lifshitz transition that affects the momentum distribution of electrons on the Fermi surface, leading to changes in the energy provided by phonons for forming Cooper pairs. Moreover, this transition modifies the phonon frequencies involved in electron-phonon coupling. The superconducting transition temperature of Li4Pd is calculated to be 34.5 K at 250 GPa, which is comparable to that of Li6P (39.3 K at 270 GPa). Our findings indicate that the formation of closed Fermi surfaces with extended spatial scales is a general feature that could be leveraged to design new classes of high-temperature superconductors among HPEs.
Large models have achieved impressive performance in many downstream tasks. Using pipeline parallelism to fine-tune large models on commodity GPU servers is an important way to make the excellent performance of large ...
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1 Introduction In recent years,the Massively parallel Computation(MPC)model has gained significant ***,most of distributed and parallel graph algorithms in the MPC model are designed for static graphs[1].In fact,the g...
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1 Introduction In recent years,the Massively parallel Computation(MPC)model has gained significant ***,most of distributed and parallel graph algorithms in the MPC model are designed for static graphs[1].In fact,the graphs in the real world are constantly *** size of the real-time changes in these graphs is smaller and more *** graph algorithms[2,3]can deal with graph changes more efficiently[4]than the corresponding static graph ***,most studies on dynamic graph algorithms are limited to the single machine ***,a few parallel dynamic graph algorithms(such as the graph connectivity)in the MPC model[5]have been proposed and shown superiority over their parallel static counterparts.
Soft robots offer promising solutions for rehabilitation due to their inherent attributes such as suppleness, lightweight construction, and safety features. However, prevalent soft actuators face limitations in output...
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In the field of video surveillance security in public places, loitering anomaly detection is a very critical part. Currently, the detection targets often face difficulties in loitering anomaly detection due to the com...
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The computation on the surface of Overlapping Adaptive Mesh Refinement (AMR) is exclusively performed within the non-Overlapping zone of its multi-level patch-based mesh - a distinctive computing mode for Overlapping ...
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Traditional knowledge graph (KG) completion models learn embeddings to predict missing facts. Recent works attempt to complete KGs in a text-generation manner with large language models (LLMs). However, they need to g...
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Healthcare has undergone a revolution from version 1.0 to version 4.0, with version 2.0 introducing electronic health records (EHRs) to replace the analysis ones and version 3.0 focusing more on patients. Telehealth, ...
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This paper proposes an imitation learning method to learn a universal agent policy for unlabeled multi-agent pathfinding(unlabeled MAPF) in grid environments. The method transforms the unlabeled MAPF problem into a se...
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This paper proposes an imitation learning method to learn a universal agent policy for unlabeled multi-agent pathfinding(unlabeled MAPF) in grid environments. The method transforms the unlabeled MAPF problem into a series of temporal-independent homogeneous classification problems for each *** on this transformation, a neural network is designed to imitate a distance-optimal expert *** neural network consists of two successive modules: perception field learner and field integrating *** former refines and encodes the current system state into a perception field for each agent by combining a set of learnable field-generating functions. The latter takes an agent's perception field as input and decides the agent's next action based on a triplet cross-attention mechanism. We evaluate our method on a diverse set of unlabeled MAPF tasks. Compared with state-of-the-art counterparts, the experimental results manifest the superiority of the proposed method in both generalization ability and scalability.
Multi-hop question answering (QA) often requires sequential retrieval (multi-hop retrieval), where each hop retrieves missing knowledge based on information from previous hops. To facilitate more effective retrieval, ...
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