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  1. Article ; Online: Self-similarity among energy eigenstates.

    Zhang, Zhelun / Wang, Zhenduo / Wu, Biao

    Physical review. E

    2023  Volume 107, Issue 3-1, Page(s) 34123

    Abstract: In a quantum system, different energy eigenstates have different properties or features, allowing us to define a classifier to divide them into different groups. We find that the ratio of each type of energy eigenstate in an energy shell [E_{c}-ΔE/2,E_{c} ...

    Abstract In a quantum system, different energy eigenstates have different properties or features, allowing us to define a classifier to divide them into different groups. We find that the ratio of each type of energy eigenstate in an energy shell [E_{c}-ΔE/2,E_{c}+ΔE/2] is invariant with changing width ΔE or Planck constant ℏ as long as the number of eigenstates in the shell is statistically large enough. We give an argument that such self-similarity in energy eigenstates is a general feature for all quantum systems, which is further illustrated numerically with various quantum systems, including circular billiard, double top model, kicked rotor, and Heisenberg XXZ model.
    Language English
    Publishing date 2023-04-18
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2844562-4
    ISSN 2470-0053 ; 2470-0045
    ISSN (online) 2470-0053
    ISSN 2470-0045
    DOI 10.1103/PhysRevE.107.034123
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The regulatory function of the d-orbital structure in TM@g-t-C

    Wang, Zhenduo / Wu, Meichen / Huang, Yuhong / Zhang, Jianmin / Wei, Xiumei

    Physical chemistry chemical physics : PCCP

    2023  Volume 26, Issue 1, Page(s) 558–568

    Abstract: Highly efficient catalysts for the oxygen evolution/reduction reaction (OER/ORR) have attracted great attention in research for energy devices with high conversion efficiency. Herein, systematic first-principles investigations are performed to explore ... ...

    Abstract Highly efficient catalysts for the oxygen evolution/reduction reaction (OER/ORR) have attracted great attention in research for energy devices with high conversion efficiency. Herein, systematic first-principles investigations are performed to explore the catalytic performance of graphitic C
    Language English
    Publishing date 2023-12-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 1476244-4
    ISSN 1463-9084 ; 1463-9076
    ISSN (online) 1463-9084
    ISSN 1463-9076
    DOI 10.1039/d3cp04249a
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration.

    Wang, Chao / Du, Pengyu / Wang, Zhenduo / Wang, Zhongkang

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 15

    Abstract: The emergence of underwater acoustic networks has greatly improved the potential capabilities of marine environment detection. In underwater acoustic network applications, node location is a basic and important task, and node location information is the ... ...

    Abstract The emergence of underwater acoustic networks has greatly improved the potential capabilities of marine environment detection. In underwater acoustic network applications, node location is a basic and important task, and node location information is the guarantee for the completion of various underwater tasks. Most of the current underwater positioning models do not consider the influence of the uneven underwater medium or the uncertainty of the position of the network beacon modem, which will reduce the accuracy of the positioning results. This paper proposes an underwater acoustic network positioning method based on spatial-temporal self-calibration. This method can automatically calibrate the space position of the beacon modem using only the GPS position and depth sensor information obtained in real-time. Under the asynchronous system, the influence of the inhomogeneity of the underwater medium is analyzed, and the unscented Kalman algorithm is used to estimate the position of underwater mobile nodes. Finally, the effectiveness of this method is verified by simulation and sea trials.
    MeSH term(s) Acoustics ; Calibration ; Computer Communication Networks ; Equipment Design ; Equipment Failure Analysis ; Transducers
    Language English
    Publishing date 2022-07-26
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22155571
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; Online: FARA

    Yang, Tao / Xu, Zhichao / Wang, Zhenduo / Ai, Qingyao

    Future-aware Ranking Algorithm for Fairness Optimization

    2023  

    Abstract: Ranking systems are the key components of modern Information Retrieval (IR) applications, such as search engines and recommender systems. Besides the ranking relevance to users, the exposure fairness to item providers has also been considered an ... ...

    Abstract Ranking systems are the key components of modern Information Retrieval (IR) applications, such as search engines and recommender systems. Besides the ranking relevance to users, the exposure fairness to item providers has also been considered an important factor in ranking optimization. Many fair ranking algorithms have been proposed to jointly optimize both ranking relevance and fairness. However, we find that most existing fair ranking methods adopt greedy algorithms that only optimize rankings for the next immediate session or request. As shown in this paper, such a myopic paradigm could limit the upper bound of ranking optimization and lead to suboptimal performance in the long term. To this end, we propose FARA, a novel Future-Aware Ranking Algorithm for ranking relevance and fairness optimization. Instead of greedily optimizing rankings for the next immediate session, FARA plans ahead by jointly optimizing multiple ranklists together and saving them for future sessions. Particularly, FARA first uses the Taylor expansion to investigate how future ranklists will influence the overall fairness of the system. Then, based on the analysis of the Taylor expansion, FARA adopts a two-phase optimization algorithm where we first solve an optimal future exposure planning problem and then construct the optimal ranklists according to the optimal future exposure planning. Theoretically, we show that FARA is optimal for ranking relevance and fairness joint optimization. Empirically, our extensive experiments on three semi-synthesized datasets show that FARA is efficient, effective, and can deliver significantly better ranking performance compared to state-of-the-art fair ranking methods.
    Keywords Computer Science - Information Retrieval
    Subject code 006
    Publishing date 2023-05-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: An In-depth Investigation of User Response Simulation for Conversational Search

    Wang, Zhenduo / Xu, Zhichao / Ai, Qingyao / Srikumar, Vivek

    2023  

    Abstract: Conversational search has seen increased recent attention in both the IR and NLP communities. It seeks to clarify and solve a user's search need through multi-turn natural language interactions. However, most existing systems are trained and demonstrated ...

    Abstract Conversational search has seen increased recent attention in both the IR and NLP communities. It seeks to clarify and solve a user's search need through multi-turn natural language interactions. However, most existing systems are trained and demonstrated with recorded or artificial conversation logs. Eventually, conversational search systems should be trained, evaluated, and deployed in an open-ended setting with unseen conversation trajectories. A key challenge is that training and evaluating such systems both require a human-in-the-loop, which is expensive and does not scale. One strategy for this is to simulate users, thereby reducing the scaling costs. However, current user simulators are either limited to only respond to yes-no questions from the conversational search system, or unable to produce high quality responses in general. In this paper, we show that current state-of-the-art user simulation system could be significantly improved by replacing it with a smaller but advanced natural language generation model. But rather than merely reporting this new state-of-the-art, we present an in-depth investigation of the task of simulating user response for conversational search. Our goal is to supplement existing works with an insightful hand-analysis of what challenges are still unsolved by the advanced model, as well as to propose our solutions for them. The challenges we identified include (1) dataset noise, (2) a blind spot that is difficult for existing models to learn, and (3) a specific type of misevaluation in the standard empirical setup. Except for the dataset noise issue, we propose solutions to cover the training blind spot and to avoid the misevaluation. Our proposed solutions lead to further improvements. Our best system improves the previous state-of-the-art significantly.

    Comment: 9 pages
    Keywords Computer Science - Information Retrieval
    Subject code 006
    Publishing date 2023-04-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: Reward-free Policy Imitation Learning for Conversational Search

    Wang, Zhenduo / Xu, Zhichao / Ai, Qingyao

    2023  

    Abstract: Existing conversational search studies mainly focused on asking better clarifying questions and/or improving search result quality. These works aim at retrieving better responses according to the search context, and their performances are evaluated on ... ...

    Abstract Existing conversational search studies mainly focused on asking better clarifying questions and/or improving search result quality. These works aim at retrieving better responses according to the search context, and their performances are evaluated on either single-turn tasks or multi-turn tasks under naive conversation policy settings. This leaves some questions about their applicability in real-world multi-turn conversations where realistically, each and every action needs to be made by the system itself, and search session efficiency is often an important concern of conversational search systems. While some recent works have identified the need for improving search efficiency in conversational search, they mostly require extensive data annotations and use hand-crafted rewards or heuristics to train systems that can achieve reasonable performance in a restricted number of turns, which has limited generalizability in practice. In this paper, we propose a reward-free conversation policy imitation learning framework, which can train a conversation policy without annotated conversation data or manually designed rewards. The trained conversation policy can be used to guide the conversational retrieval models to balance conversational search quality and efficiency. To evaluate the proposed conversational search system, we propose a new multi-turn-multi-response conversational evaluation metric named Expected Conversational Reciprocal Rank (ECRR). ECRR is designed to evaluate entire multi-turn conversational search sessions towards comprehensively evaluating both search result quality and search efficiency.
    Keywords Computer Science - Information Retrieval
    Subject code 006
    Publishing date 2023-04-17
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Quantum chaos and physical distance between quantum states.

    Wang, Zhenduo / Wang, Yijie / Wu, Biao

    Physical review. E

    2021  Volume 103, Issue 4-1, Page(s) 42209

    Abstract: We show that there is genuine chaos in quantum dynamics by introducing a physical distance between two quantum states. Qualitatively different from existing distances for quantum states, for example, the Fubini-Study distance, the physical distance ... ...

    Abstract We show that there is genuine chaos in quantum dynamics by introducing a physical distance between two quantum states. Qualitatively different from existing distances for quantum states, for example, the Fubini-Study distance, the physical distance between two mutually orthogonal quantum states, can be very small. As a result, two quantum states, which are initially very close by physical distance, can diverge from each other during the ensuing quantum dynamical evolution. We are able to use physical distance to define the quantum Lyapunov exponent and the quantum chaos measure. The latter leads to a quantum analog of the classical Poincaré section, which maps out the regions where quantum dynamics is regular and the regions where it is chaotic. Three different systems-a kicked rotor, the three-site Bose-Hubbard model, and the spin-1/2 XXZ model-are used to illustrate our results.
    Language English
    Publishing date 2021-04-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2844562-4
    ISSN 2470-0053 ; 2470-0045
    ISSN (online) 2470-0053
    ISSN 2470-0045
    DOI 10.1103/PhysRevE.103.042209
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: Marginal-Certainty-aware Fair Ranking Algorithm

    Yang, Tao / Xu, Zhichao / Wang, Zhenduo / Tran, Anh / Ai, Qingyao

    2022  

    Abstract: Ranking systems are ubiquitous in modern Internet services, including online marketplaces, social media, and search engines. Traditionally, ranking systems only focus on how to get better relevance estimation. When relevance estimation is available, they ...

    Abstract Ranking systems are ubiquitous in modern Internet services, including online marketplaces, social media, and search engines. Traditionally, ranking systems only focus on how to get better relevance estimation. When relevance estimation is available, they usually adopt a user-centric optimization strategy where ranked lists are generated by sorting items according to their estimated relevance. However, such user-centric optimization ignores the fact that item providers also draw utility from ranking systems. It has been shown in existing research that such user-centric optimization will cause much unfairness to item providers, followed by unfair opportunities and unfair economic gains for item providers. To address ranking fairness, many fair ranking methods have been proposed. However, as we show in this paper, these methods could be suboptimal as they directly rely on the relevance estimation without being aware of the uncertainty (i.e., the variance of the estimated relevance). To address this uncertainty, we propose a novel Marginal-Certainty-aware Fair algorithm named MCFair. MCFair jointly optimizes fairness and user utility, while relevance estimation is constantly updated in an online manner. In MCFair, we first develop a ranking objective that includes uncertainty, fairness, and user utility. Then we directly use the gradient of the ranking objective as the ranking score. We theoretically prove that MCFair based on gradients is optimal for the aforementioned ranking objective. Empirically, we find that on semi-synthesized datasets, MCFair is effective and practical and can deliver superior performance compared to state-of-the-art fair ranking methods. To facilitate reproducibility, we release our code https://github.com/Taosheng-ty/WSDM22-MCFair.

    Comment: 10 pages, 5 figures
    Keywords Computer Science - Information Retrieval ; H.3.3
    Subject code 005
    Publishing date 2022-12-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Book ; Online: Lorentz Quantum Computer

    He, Wenhao / Wang, Zhenduo / Wu, Biao

    2021  

    Abstract: A theoretical model of computation is proposed based on Lorentz quantum mechanics. Besides the standard qubits, this model has an additional bit, which we call hyperbolic bit (or hybit in short). A set of basic logical gates are constructed and their ... ...

    Abstract A theoretical model of computation is proposed based on Lorentz quantum mechanics. Besides the standard qubits, this model has an additional bit, which we call hyperbolic bit (or hybit in short). A set of basic logical gates are constructed and their universality is proved. As an application, a search algorithm is designed for this computer model and is found to be exponentially faster than the Grover's search algorithm.
    Keywords Quantum Physics ; Condensed Matter - Other Condensed Matter ; Computer Science - Computational Complexity ; F.4.1
    Publishing date 2021-03-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: Zero-shot Clarifying Question Generation for Conversational Search

    Wang, Zhenduo / Tu, Yuancheng / Rosset, Corby / Craswell, Nick / Wu, Ming / Ai, Qingyao

    2023  

    Abstract: A long-standing challenge for search and conversational assistants is query intention detection in ambiguous queries. Asking clarifying questions in conversational search has been widely studied and considered an effective solution to resolve query ... ...

    Abstract A long-standing challenge for search and conversational assistants is query intention detection in ambiguous queries. Asking clarifying questions in conversational search has been widely studied and considered an effective solution to resolve query ambiguity. Existing work have explored various approaches for clarifying question ranking and generation. However, due to the lack of real conversational search data, they have to use artificial datasets for training, which limits their generalizability to real-world search scenarios. As a result, the industry has shown reluctance to implement them in reality, further suspending the availability of real conversational search interaction data. The above dilemma can be formulated as a cold start problem of clarifying question generation and conversational search in general. Furthermore, even if we do have large-scale conversational logs, it is not realistic to gather training data that can comprehensively cover all possible queries and topics in open-domain search scenarios. The risk of fitting bias when training a clarifying question retrieval/generation model on incomprehensive dataset is thus another important challenge. In this work, we innovatively explore generating clarifying questions in a zero-shot setting to overcome the cold start problem and we propose a constrained clarifying question generation system which uses both question templates and query facets to guide the effective and precise question generation. The experiment results show that our method outperforms existing state-of-the-art zero-shot baselines by a large margin. Human annotations to our model outputs also indicate our method generates 25.2\% more natural questions, 18.1\% more useful questions, 6.1\% less unnatural and 4\% less useless questions.

    Comment: To appear in the Web Conference 2023
    Keywords Computer Science - Information Retrieval ; Computer Science - Computation and Language
    Subject code 006 ; 004
    Publishing date 2023-01-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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