Discovering strongly lensed quasar candidates with catalogue-based methods from DESI Legacy Surveys

The Hubble tension, revealed by a $\sim 5\sigma$ discrepancy between measurements of the Hubble-Lemaitre constant from early- and local-Universe observations, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure $H_0$, such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys like DESI (Dark Energy Spectroscopic Instrument). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24,440,816 candidate QSOs contained in the 9th data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours of a group's members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identify 620 new candidate multiply imaged lensed quasars (101 Grade-A, 214 Grade-B, 305 Grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI. The catalogues and images of the candidates in this work are available online (https://github.com/EigenHermit/lensed_qso_cand_catalogue_He-22/).Comment: Accepted by A&A. 14 pages, 11 figures. Comments are welcom

Multifractal analysis of the heterogeneity of nanopores in tight reservoirs based on boosting machine learning algorithms

Exploring the geological factors that affect fluid flow has always been a hot topic. For tight reservoirs, the pore structure and characteristics of different lithofacies reveal the storage status of fluids in different reservoir environments. The size, connectivity, and distribution of fillers in different sedimentary environments have always posed a challenge in studying the microscopic heterogeneity. In this paper, six logging curves (gamma-ray, density, acoustic, compensated neutron, shallow resistivity, and deep resistivity) in two marker wells, namely, J1 and J2, of the Permian Lucaogou Formation in the Jimsar Basin are tested by using four reinforcement learning algorithms: LogitBoost, GBM, XGBoost, and KNN. The total percent correct of training well J2 is 96%, 96%, 96%, and 96%, and the total percent correct of validation well J1 is 75%, 68%, 72%, and 75%, respectively. Based on the lithofacies classification obtained by using reinforcement learning algorithm, micropores, mesopores, and macropores are comprehensively described by high-pressure mercury injection and low-pressure nitrogen gas adsorption tests. The multifractal theory servers for the quantitative characterization of the pore distribution heterogeneity regarding different lithofacies samples, and as observed, the higher probability measure area of the generalized fractal spectrum affects the heterogeneity of the local interval of mesopores and macropores of the estuary dam. In the micropore and mesopore, the heterogeneity of the evaporation lake showed a large variation due to the influence of the higher probability measure area, and in the mesopore and macropore, the heterogeneity of the evaporation lake was controlled by the lower probability measure area. According to the correlation analysis, the single-fractal dimension is well related to the multifractal parameters, and the individual fitting degree reaches up to 99%, which can serve for characterizing the pore size distribution uniformity. The combination of boosting machine learning and multifractal can help to better characterize the micro-heterogeneity under different sedimentary environments and different pore size distribution ranges, which is helpful in the exploration and development of oil fields

Photoprogrammable Circularly Polarized Phosphorescence Switching of Chiral Helical Polyacetylene Thin Films

The developments of pure organic room-temperature phosphorescence (RTP) materials with circularly polarized luminescence (CPL) have significantly facilitated the future integration and systemization of luminescent material in fundamental science and technological applications. Herein, a new type of photoinduced circularly polarized RTP materials was constructed by homogeneously dispersing phosphorescent chiral helical substituted polyacetylenes into a processable poly(methyl methacrylate) (PMMA) matrix. This substituted polyacetylenes play vital roles in the propagation of CPL and present prominently optical characteristics with high absorption and luminescent dissymmetric factors up to 0.029 (gabs) and 0.019 (glum). The oxygen consumption properties of PMMA films under UV light irradiation endowed materials with dynamic chiro-optical functionality, which can leverage of light to precisely control and manipulate the circularly polarized RTP properties with the remarkable advantages of being contactless, wireless and fatigue-resistant. Significantly, the distinct materials with dynamic properties can be used as novel anti-counterfeiting materials involving photoprogrammability

Engender Persistent Organic Room-Temperature Phosphorescence by Trace Ingredient Incorporation

The trace impurities in pure organic phosphors were always ignored because the ultra-low content impurities were considered to hardly affect the luminescent properties. Evidences from corresponding reports and research have shown that impurities may greatly affect room temperature phosphorescence (RTP) in some crystalline compounds. To date, very few literatures have clearly study the role of impurities in RTP because of the difficulty in the separation and structure identification of impurities. Also no reports have focused on utilizing trace impurities to form new strategies for efficient RTP. For the first time, an impurity was isolated from 1-(4-bromophenyl)-1H-imidazole (1BBI) and structural identified, which was proved to be the key to RTP in 1BBI crystal. Neither purified impurity nor 1BBI matrix shown any detectable RTP. The impurity could light up the unusual ultralong RTP in matrix even at 0.01 mol% content. Inspired by impurity/matrix phosphorescence, a trace-ingredient-mediated bicomponent strategy was introduced for high phosphorescence quantum yield (QY, up to 74.2%) and extralong lifetime (up to 430 ms).Research Highlights of this work are including1. The study of impurities in organic luminescent materials, including phosphorescent materials, is rarely reported due to the great difficulty of separation, purification and structure characterization. This work not only separated, purified and structure identified the trace impurity in the system but also confirmed the fact that the impurity engenders the RTP. And the corresponding mechanism was proposed as well.2. Inspired by the role of impurities in RTP, this work proposed an effective strategy for the design and preparation of persistent organic RTP based on active ingredient incorporation. Seven compounds were screened out to conduct the bicomponent RTP system and achieved bright RTP with high QY (up to 74.2%) and extra-long lifetime (up to 430 ms)) RTP with tunable colors.3. Combining the dual emission of blue fluorescence and yellow phosphorescence, a bicomponent system achieved a bright white-light emission, which shows its outstanding application potential. The design concept and strategy of this work supplies an efficient approach to develop RTP by simply mixing the matrix with a trace amount of active ingredients. And the trace-ingredient-mediated bicomponent system is preferred for its high efficiency, color-tunable, low cost and easy to prepare properties, which will make important sense for facilely developing organic persistent RTP materials. This work will not only lead to a new understanding of persistent organic RTP but also develop a facile and effective strategy for RTP afterglow materials.</p

RDBench: ML Benchmark for Relational Databases

Benefiting from high-quality datasets and standardized evaluation metrics, machine learning (ML) has achieved sustained progress and widespread applications. However, while applying machine learning to relational databases (RDBs), the absence of a well-established benchmark remains a significant obstacle to the development of ML. To address this issue, we introduce ML Benchmark For Relational Databases (RDBench), a standardized benchmark that aims to promote reproducible ML research on RDBs that include multiple tables. RDBench offers diverse RDB datasets of varying scales, domains, and relational structures, organized into 4 levels. Notably, to simplify the adoption of RDBench for diverse ML domains, for any given database, RDBench exposes three types of interfaces including tabular data, homogeneous graphs, and heterogeneous graphs, sharing the same underlying task definition. For the first time, RDBench enables meaningful comparisons between ML methods from diverse domains, ranging from XGBoost to Graph Neural Networks, under RDB prediction tasks. We design multiple classification and regression tasks for each RDB dataset and report averaged results over the same dataset, further enhancing the robustness of the experimental findings. RDBench is implemented with DBGym, a user-friendly platform for ML research and application on databases, enabling benchmarking new ML methods with RDBench at ease.Comment: Withdrawn by the authors to avoid conflict of interest

A Cocktail Approach Toward Tunable Organic Afterglow Systems

In this work, a cocktail approach toward tunable organic long-lived luminescence materials in solid, solution, and gel states is proposed. The tunable long-lived luminescence (τ > 0.7 s) is realized by controlling the energy transfer via manipulating the photo-induced isomerization of the energy acceptor (5). The afterglow can be regulated between blue and yellow emission upon irradiation of UV or visible light. And the “apparent lifetime” for the long-lived fluorescence is the same as the lifetime of the energy donor. The function is relying on the simple radiative energy transfer (reabsorption) between a long-lived phosphorescence and a highly efficient fluorescent isomer (5b), rather than the complicated communication between the excited state of the molecules such as Förster resonance energy transfer or Dexter energy transfer. The simple working principle endows this strategy with huge universality, flexibility, and operability. This work offers an extremely simple, feasible, and universal way to construct tunable afterglow materials in solid, solution, and gel states

Effect of pore morphology and surface roughness on wettability of porous titania films

Surface hydrophobicity/hydrophilicity of titania (TiO _2 ) films, spin-coated on silicon wafers, were tuned by introducing surface mesopores with various morphologies using a triblock copolymer F38 as the template agent of different weight ratios via a sol-gel method. It is found that both the porosity (2.92 ∼ 33.03%) and the surface roughness (0.22 ∼ 0.43 nm for arithmetic mean roughness and 0.28 ∼ 0.58 nm for root mean square roughness) of the films increase monotonically as increasing F38 ratio from 5 to 25 wt%, accompanied by distinct changes of pore morphology from isolated mesopores with pore sizes of 5 ∼ 7 nm to longer worm-like pores (30 ∼ 100 nm in length). The apparent static contact angle ( θ *) of the films with isolated mesopores is enhanced from ca. 90.6° to 100.1° as indicated by an increase of the roughness factor with incresing F38 from 5 to 15 wt%, which is in qualitative agreement with the Wenzel’s equation. Interestingly, the films with interconnected worm-like pores show obvious hydrophilicity ( θ *  =  80.7°) with further increasing F38 ratio higher than 20 wt%. The reversed surface wettability show that not only surface roughness but also pore morphology could significantly affect the wettability of the mesoporous TiO _2 films