Kerr-effect-based quantum logical gates in decoherence-free subspace

Efficient implementations of two (or three) qubit logical gates are critical for the large-scale realization of quantum computation in decoherence-free subspace (DFS) immune to the influence of decoherence effect. In this paper, we propose some schemes for setting up a family of quantum control gates, including controlled-NOT (CNOT), Toffoli, and Fredkin gates for two or three logical qubits by means of cross-Kerr nonlinearities in DFS. These three logical gates require neither complicated quantum computational circuits nor auxiliary photons (or entangled states). The success probabilities of three logical gates are approximate unit by performing the corresponding classical feed-forward operations based on the different measuring results of the X homodyne detectors, and their fidelities are robust against the photon loss with the current technology.The proposed logical gates rely on only simple linear-optics elements, available single qubit operations, and mature measurement methods, making our proposed gates be feasible and efficient in practical applications.Comment: 11 pages, 9 figure

Effect of sodium hyaluronate in treating fungal corneal ulcer

AIM: To retrospectively analyze the effects of sodium hyaluronate in treating fungal corneal ulcer.<p>METHODS: Since June, 2006, there were 178 patients(178 eyes)with fungal corneal ulcer receiving medical treatment in our hospital. Among them, 81 patients(81 eyes)as the control group received the traditional antifungal treatment with the natamycin and fluconazole being the major medicine, from June 2006 to June 2008. While, 97 patients(97 eyes)as the treatment group received sodium hyaluronate treatment based on traditional antifungal treatment during the period of June 2008 to March 2010. Effects of two therapeutic methods were compared and analyzed. <p>RESULTS: Of the 97 cases in the treatment group, the average hospital stay was: 14.15±4.23d, with 90 cases(92.8%)cured, 5 cases(5.2%)improved, 2 cases(2.1%)ineffective, the final visual acuity of 51.6% patients better than 0.3. Of the 81 cases in the control group, average hospital stay was: 17.26±6.23d, with 69 cases(85.2%)cured, 7 cases(8.6%)improved, 5 cases(6.2%)ineffective, the final visual acuity of 39.5% patients better than 0.3. After statistical analysis, the average hospital stay, the cure rate, the effective rate and the final visual acuity in both groups showed statistically significant difference(<i>P</i><0.05). The average hospital stay of the treatment group was shorter than that of the control group, while the cure rate and effective rate and the final visual acuity was better than that of the control group.<p>CONCLUSION: Sodium hyaluronate can promote fungal corneal ulcer healing, improve the cure rate and reduce the formation of corneal scar

Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning

Large language models have shown astonishing performance on a wide range of reasoning tasks. In this paper, we investigate whether they could reason about real-world events and help improve the prediction performance of event sequence models. We design LAMP, a framework that integrates a large language model in event prediction. Particularly, the language model performs abductive reasoning to assist an event sequence model: the event model proposes predictions on future events given the past; instructed by a few expert-annotated demonstrations, the language model learns to suggest possible causes for each proposal; a search module finds out the previous events that match the causes; a scoring function learns to examine whether the retrieved events could actually cause the proposal. Through extensive experiments on several challenging real-world datasets, we demonstrate that our framework -- thanks to the reasoning capabilities of large language models -- could significantly outperform the state-of-the-art event sequence models.Comment: NeurIPS 2023 camera-read

Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China

One of four main focus areas of the PEEX initiative is to establish and sustain long-term, continuous, and comprehensive ground-based, airborne, and seaborne observation infrastructure together with satellite data. The Advanced Along-Track Scanning Radiometer (AATSR) aboard ENVISAT is used to observe the Earth in dual view. The AATSR data can be used to retrieve aerosol optical depth (AOD) over both land and ocean, which is an important parameter in the characterization of aerosol properties. In recent years, aerosol retrieval algorithms have been developed both over land and ocean, taking advantage of the features of dual view, which can help eliminate the contribution of Earth's surface to top-of-atmosphere (TOA) reflectance. The Aerosol_cci project, as a part of the Climate Change Initiative (CCI), provides users with three AOD retrieval algorithms for AATSR data, including the Swansea algorithm (SU), the ATSR-2ATSR dual-view aerosol retrieval algorithm (ADV), and the Oxford-RAL Retrieval of Aerosol and Cloud algorithm (ORAC). The validation team of the Aerosol-CCI project has validated AOD (both Level 2 and Level 3 products) and AE (Ångström Exponent) (Level 2 product only) against the AERONET data in a round-robin evaluation using the validation tool of the AeroCOM (Aerosol Comparison between Observations and Models) project. For the purpose of evaluating different performances of these three algorithms in calculating AODs over mainland China, we introduce ground-based data from CARSNET (China Aerosol Remote Sensing Network), which was designed for aerosol observations in China. Because China is vast in territory and has great differences in terms of land surfaces, the combination of the AERONET and CARSNET data can validate the L2 AOD products more comprehensively. The validation results show different performances of these products in 2007, 2008, and 2010. The SU algorithm performs very well over sites with different surface conditions in mainland China from March to October, but it slightly underestimates AOD over barren or sparsely vegetated surfaces in western China, with mean bias error (MBE) ranging from 0.05 to 0.10. The ADV product has the same precision with a low root mean square error (RMSE) smaller than 0.2 over most sites and the same error distribution as the SU product. The main limits of the ADV algorithm are underestimation and applicability; underestimation is particularly obvious over the sites of Datong, Lanzhou, and Urumchi, where the dominant land cover is grassland, with an MBE larger than 0.2, and the main aerosol sources are coal combustion and dust. The ORAC algorithm has the ability to retrieve AOD at different ranges, including high AOD (larger than 1.0); however, the stability deceases significantly with increasing AOD, especially when AOD > 1.0. In addition, the ORAC product is consistent with the CARSNET product in winter (December, January, and February), whereas other validation results lack matches during winter

WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine

We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain. Our system harnesses a large language model of GPT architecture that has been tuned using extensive corpora of finance-related text. As a result, our system possesses the capability to understand complex financial queries, such as "How should I manage my investments during inflation?", and provide informed responses. Furthermore, our system incorporates a local knowledge base and a search engine to retrieve relevant information. The final responses are conditioned on the search results and include proper citations to the sources, thus enjoying an enhanced credibility. Through a range of finance-related questions, we have demonstrated the superior performance of our system compared to other models. To experience our system firsthand, users can interact with our live demo at https://weaverbird.ttic.edu, as well as watch our 2-min video illustration at https://www.youtube.com/watch?v=fyV2qQkX6Tc

EasyTPP: Towards Open Benchmarking Temporal Point Processes

Continuous-time event sequences play a vital role in real-world domains such as healthcare, finance, online shopping, social networks, and so on. To model such data, temporal point processes (TPPs) have emerged as the most natural and competitive models, making a significant impact in both academic and application communities. Despite the emergence of many powerful models in recent years, there hasn't been a central benchmark for these models and future research endeavors. This lack of standardization impedes researchers and practitioners from comparing methods and reproducing results, potentially slowing down progress in this field. In this paper, we present EasyTPP, the first central repository of research assets (e.g., data, models, evaluation programs, documentations) in the area of event sequence modeling. Our EasyTPP makes several unique contributions to this area: a unified interface of using existing datasets and adding new datasets; a wide range of evaluation programs that are easy to use and extend as well as facilitate reproducible research; implementations of popular neural TPPs, together with a rich library of modules by composing which one could quickly build complex models. All the data and implementation can be found at https://github.com/ant-research/EasyTemporalPointProcess. We will actively maintain this benchmark and welcome contributions from other researchers and practitioners. Our benchmark will help promote reproducible research in this field, thus accelerating research progress as well as making more significant real-world impacts.Comment: ICLR 2024 camera read

Bis(2,4,6-triamino-1,3,5-triazin-1-ium) hydrogen phosphate trihydrate

In the title hydrated mol­ecular salt, 2C3H7N6 +·HPO4 2−·3H2O, three of the O atoms of the hydrogen phosphate anion are disordered over two positions, with relative occupancies of 0.763 (1) and 0.237 (1). In the crystal, the components are linked by N—H⋯N, N—H⋯O and O—H⋯O hydrogen bond