3 research outputs found
Learning A Foundation Language Model for Geoscience Knowledge Understanding and Utilization
Large language models (LLMs)have achieved great success in general domains of
natural language processing. In this paper, we bring LLMs to the realm of
geoscience, with the objective of advancing research and applications in this
field. To this end, we present the first-ever LLM in geoscience, K2, alongside
a suite of resources developed to further promote LLM research within
geoscience. For instance, we have curated the first geoscience instruction
tuning dataset, GeoSignal, which aims to align LLM responses to
geoscience-related user queries. Additionally, we have established the first
geoscience benchmark, GeoBenchmark, to evaluate LLMs in the context of
geoscience. In this work, we experiment with a complete recipe to adapt a
pretrained general-domain LLM to the geoscience domain. Specifically, we
further train the LLaMA-7B model on over 1 million pieces of geoscience
literature and utilize GeoSignal's supervised data to fine-tune the model.
Moreover, we share a protocol that can efficiently gather domain-specific data
and construct domain-supervised data, even in situations where manpower is
scarce. Experiments conducted on the GeoBenchmark demonstrate the the
effectiveness of our approach and datasets
Gate-tunable negative differential conductance in hybrid semiconductor-superconductor devices
Negative differential conductance (NDC) manifests as a significant
characteristic of various underlying physics and transport processes in hybrid
superconducting devices. In this work, we report the observation of
gate-tunable NDC outside the superconducting energy gap on two types of hybrid
semiconductor-superconductor devices, i.e., normal metal-superconducting
nanowire-normal metal and normal metal-superconducting nanowire-superconductor
devices. Specifically, we study the dependence of the NDCs on back-gate voltage
and magnetic field. When the back-gate voltage decreases, these NDCs weaken and
evolve into positive differential conductance dips; and meanwhile they move
away from the superconducting gap towards high bias voltage, and disappear
eventually. In addition, with the increase of magnetic field, the NDCs/dips
follow the evolution of the superconducting gap, and disappear when the gap
closes. We interpret these observations and reach a good agreement by combining
the Blonder-Tinkham-Klapwijk (BTK) model and the critical supercurrent effect
in the nanowire, which we call the BTK-supercurrent model. Our results provide
an in-depth understanding of the tunneling transport in hybrid
semiconductor-superconductor devices.Comment: 15+6 pages, 4+6 figure