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Galaxy mergers produce pairs of supermassive black holes (SMBHs), which may be witnessed as dual quasars if both SMBHs are rapidly accreting. The kiloparsec (kpc)-scale separation represents a physical regime sufficiently close for merger-induced effects to be important1yet wide enough to be directly resolvable with the facilities currently available. Whereas many kpc-scale, dual active galactic nuclei—the low-luminosity counterparts of quasars—have been observed in low-redshift mergers2, no unambiguous dual quasar is known at cosmic noon (z≈ 2), the peak of global star formation and quasar activity3,4. Here we report multiwavelength observations of Sloan Digital Sky Survey (SDSS) J0749 + 2255 as a kpc-scale, dual-quasar system hosted by a galaxy merger at cosmic noon (z= 2.17). We discover extended host galaxies associated with the much brighter compact quasar nuclei (separated by 0.46″ or 3.8 kpc) and low-surface-brightness tidal features as evidence for galactic interactions. Unlike its low-redshift and low-luminosity counterparts, SDSS J0749 + 2255 is hosted by massive compact disk-dominated galaxies. The apparent lack of stellar bulges and the fact that SDSS J0749 + 2255 already follows the local SMBH mass–host stellar mass relation, suggest that at least some SMBHs may have formed before their host stellar bulges. While still at kpc-scale separations where the host-galaxy gravitational potential dominates, the two SMBHs may evolve into a gravitationally bound binary system in around 0.22 Gyr.

A software tool for data mining (DMiner-I) is introduced, which integrates pattern recognition (PCA, Fisher, clustering, HyperEnvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), and computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, HyperEnvelop, support vector machine and visualization. The principle, algorithms and knowledge representation of some function models of data mining are described. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining is realized by Visual C++ under Windows 2000. The software tool of data mining has been satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

The Na 2O-rich region of the phase diagram of Na 2O-Al 2O 3-H 2O system has been re-investigated. The triple points and solubility curves involving two sodium aluminate hydrates have been determined at 30 °C. The Na 2O-rich aluminate hydrate is identified to be 4Na 2O · Al 2O 3· 12H 2O by a tracer method. The phase diagram has been revised based on these results.

The artificial neural network (ANN) method has been used to investigate enthalpies of fusion of the transition metals. The results show the usefulness of this method for predicting enthalpies of fusion of transition metals.