21 research outputs found

    Will More Expressive Graph Neural Networks do Better on Generative Tasks?

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    Graph generation poses a significant challenge as it involves predicting a complete graph with multiple nodes and edges based on simply a given label. This task also carries fundamental importance to numerous real-world applications, including de-novo drug and molecular design. In recent years, several successful methods have emerged in the field of graph generation. However, these approaches suffer from two significant shortcomings: (1) the underlying Graph Neural Network (GNN) architectures used in these methods are often underexplored; and (2) these methods are often evaluated on only a limited number of metrics. To fill this gap, we investigate the expressiveness of GNNs under the context of the molecular graph generation task, by replacing the underlying GNNs of graph generative models with more expressive GNNs. Specifically, we analyse the performance of six GNNs in two different generative frameworks -- autoregressive generation models, such as GCPN and GraphAF, and one-shot generation models, such as GraphEBM -- on six different molecular generative objectives on the ZINC-250k dataset. Through our extensive experiments, we demonstrate that advanced GNNs can indeed improve the performance of GCPN, GraphAF, and GraphEBM on molecular generation tasks, but GNN expressiveness is not a necessary condition for a good GNN-based generative model. Moreover, we show that GCPN and GraphAF with advanced GNNs can achieve state-of-the-art results across 17 other non-GNN-based graph generative approaches, such as variational autoencoders and Bayesian optimisation models, on the proposed molecular generative objectives (DRD2, Median1, Median2), which are important metrics for de-novo molecular design.Comment: 2nd Learning on Graphs Conference (LoG 2023). 26 pages, 5 figures, 11 table

    Observation of many-body Fock space dynamics in two dimensions

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    Quantum many-body simulation provides a straightforward way to understand fundamental physics and connect with quantum information applications. However, suffering from exponentially growing Hilbert space size, characterization in terms of few-body probes in real space is often insufficient to tackle challenging problems such as quantum critical behavior and many-body localization (MBL) in higher dimensions. Here, we experimentally employ a new paradigm on a superconducting quantum processor, exploring such elusive questions from a Fock space view: mapping the many-body system onto an unconventional Anderson model on a complex Fock space network of many-body states. By observing the wave packet propagating in Fock space and the emergence of a statistical ergodic ensemble, we reveal a fresh picture for characterizing representative many-body dynamics: thermalization, localization, and scarring. In addition, we observe a quantum critical regime of anomalously enhanced wave packet width and deduce a critical point from the maximum wave packet fluctuations, which lend support for the two-dimensional MBL transition in finite-sized systems. Our work unveils a new perspective of exploring many-body physics in Fock space, demonstrating its practical applications on contentious MBL aspects such as criticality and dimensionality. Moreover, the entire protocol is universal and scalable, paving the way to finally solve a broader range of controversial many-body problems on future larger quantum devices.Comment: 8 pages, 4 figures + supplementary informatio

    Solar Ring Mission: Building a Panorama of the Sun and Inner-heliosphere

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    Solar Ring (SOR) is a proposed space science mission to monitor and study the Sun and inner heliosphere from a full 360{\deg} perspective in the ecliptic plane. It will deploy three 120{\deg}-separated spacecraft on the 1-AU orbit. The first spacecraft, S1, locates 30{\deg} upstream of the Earth, the second, S2, 90{\deg} downstream, and the third, S3, completes the configuration. This design with necessary science instruments, e.g., the Doppler-velocity and vector magnetic field imager, wide-angle coronagraph, and in-situ instruments, will allow us to establish many unprecedented capabilities: (1) provide simultaneous Doppler-velocity observations of the whole solar surface to understand the deep interior, (2) provide vector magnetograms of the whole photosphere - the inner boundary of the solar atmosphere and heliosphere, (3) provide the information of the whole lifetime evolution of solar featured structures, and (4) provide the whole view of solar transients and space weather in the inner heliosphere. With these capabilities, Solar Ring mission aims to address outstanding questions about the origin of solar cycle, the origin of solar eruptions and the origin of extreme space weather events. The successful accomplishment of the mission will construct a panorama of the Sun and inner-heliosphere, and therefore advance our understanding of the star and the space environment that holds our life.Comment: 41 pages, 6 figures, 1 table, to be published in Advances in Space Researc

    Sedentary Behavior Estimation with Hip-worn Accelerometer Data: Segmentation, Classification and Thresholding

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    Cohort studies are increasingly using accelerometers for physical activity and sedentary behavior estimation. These devices tend to be less error-prone than self-report, can capture activity throughout the day, and are economical. However, previous methods for estimating sedentary behavior based on hip-worn data are often invalid or suboptimal under free-living situations and subject-to-subject variation. In this paper, we propose a local Markov switching model that takes this situation into account, and introduce a general procedure for posture classification and sedentary behavior analysis that fits the model naturally. Our method features changepoint detection methods in time series and also a two stage classification step that labels data into 3 classes(sitting, standing, stepping). Through a rigorous training-testing paradigm, we showed that our approach achieves > 80% accuracy. In addition, our method is robust and easy to interpret

    Monitoring of two-dimensional tungsten concentration profiles on the HL-2A tokamak

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    In this article, we demonstrate the inference of two-dimensional tungsten concentration profiles in tokamak plasmas, using Gaussian process tomography applied to bolometry and assuming a specific model for the tungsten cooling factor. In ITER, tungsten has been selected for divertor material due to its low tritium retention and ability to handle large heat and particle flux loads. On the other hand, this will cause tungsten impurities to enter the bulk plasma through various plasma-wall interaction processes. Therefore, a detailed understanding of tungsten impurity transport and active control of the impurity transport in tokamaks is crucial. The computational complexity of the method described in their article O(n(2)m) compares favorably to a simple least-squares approach O (n(3)), n represents the number of pixels and m the number of measurement channels, hence bringing real-time tungsten profile monitoring within reach (<10 ms repetition time). The feasibility study of this method has been demonstrated here to a discharge in HL-2A for observing the entire process of tungsten impurities entering the bulk plasma from the scrape-off layer area, tungsten pump-out by edge-localized modes, as well as the formation of a poloidally asymmetric tungsten distribution

    Enhanced quantum state transfer by circumventing quantum chaotic behavior

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    Abstract The ability to realize high-fidelity quantum communication is one of the many facets required to build generic quantum computing devices. In addition to quantum processing, sensing, and storage, transferring the resulting quantum states demands a careful design that finds no parallel in classical communication. Existing experimental demonstrations of quantum information transfer in solid-state quantum systems are largely confined to small chains with few qubits, often relying upon non-generic schemes. Here, by using a superconducting quantum circuit featuring thirty-six tunable qubits, accompanied by general optimization procedures deeply rooted in overcoming quantum chaotic behavior, we demonstrate a scalable protocol for transferring few-particle quantum states in a two-dimensional quantum network. These include single-qubit excitation, two-qubit entangled states, and two excitations for which many-body effects are present. Our approach, combined with the quantum circuit’s versatility, paves the way to short-distance quantum communication for connecting distributed quantum processors or registers, even if hampered by inherent imperfections in actual quantum devices

    Martian Bow Shock Oscillations Driven by Solar Wind Variations: Simultaneous Observations From Tianwen‐1 and MAVEN

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    International audienceThe Martian bow shock stands as the first defense against the solar wind and shapes the Martian magnetosphere. Previous studies showed the correlation between the Martian bow shock location and solar wind parameters. Here we present direct evidence of solar wind effects on the Martian bow shock by analyzing Tianwen‐1 and MAVEN data. We examined three cases where Tianwen‐1 data show rapid oscillations of the bow shock, while MAVEN data record changes in solar wind plasma and magnetic field. The results indicate that the bow shock is rapidly compressed and then expanded during the dynamic pressure pulse in the solar wind, and is also oscillated during the IMF rotation. The superposition of variations in multiple solar wind parameters leads to more intensive bow shock oscillation. This study emphasizes the importance of joint observations by Tianwen‐1 and MAVEN for studying the real‐time response of the Martian magnetosphere to the solar wind
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