Conventional, hadronic matter consists of baryons and mesons made of three quarks and a quark–antiquark pair, respectively1,2. Here, we report the observation of a hadronic state containing four quarks in the Large Hadron Collider beauty experiment. This so-called tetraquark contains two charm quarks, a $$\overline{{{{{u}}}}}$$ u ¯ and a $$\overline{{{{{d}}}}}$$ d ¯ quark. This exotic state has a mass of approximately 3,875 MeV and manifests as a narrow peak in the mass spectrum of D0D0π+ mesons just below the D*+D0 mass threshold. The near-threshold mass together with the narrow width reveals the resonance nature of the state.

Aerial photographs and satellite images are one of the resources used for earth observation. In practice, automated detection of roads on aerial images is of significant values for the application such as car navigation, law enforcement, and fire services. In this paper, we present a novel road extraction method from aerial images based on an improved generative adversarial network, which is an end-to-end framework only requiring a few samples for training. Experimental results on the Massachusetts Roads Dataset show that the proposed method provides better performance than several state of the art techniques in terms of detection accuracy, recall, precision and F1-score.

Conventional compressive sensing (CS) reconstruction is very slow for its characteristic of solving an optimization problem. Convolutional neural network can realize fast processing while achieving comparable results. While CS image recovery with high quality not only depends on good reconstruction algorithms, but also good measurements. In this paper, we propose an adaptive measurement network in which measurement is obtained by learning. The new network consists of a fully-connected layer and ReconNet. The fully-connected layer which has low-dimension output acts as measurement. We train the fully-connected layer and ReconNet simultaneously and obtain adaptive measurement. Because the adaptive measurement fits dataset better, in contrast with random Gaussian measurement matrix, under the same measurement rate, it can extract the information of scene more efficiently and get better reconstruction results. Experiments show that the new network outperforms the original one.

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Quantum chromodynamics, the theory of the strong force, describes interactions of coloured quarks and gluons and the formation of hadronic matter. Conventional hadronic matter consists of baryons and mesons made of three quarks and quark-antiquark pairs, respectively. Particles with an alternative quark content are known as exotic states. Here a study is reported of an exotic narrow state in the D0D0π+ mass spectrum just below the D*+D0 mass threshold produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The state is consistent with the ground isoscalar $${{{{{{\rm{T}}}}}}}_{{{{{{\rm{c}}}}}}{{{{{\rm{c}}}}}}}^{+}$$ T c c + tetraquark with a quark content of $${{{{{\rm{c}}}}}}{{{{{\rm{c}}}}}}\overline{{{{{{\rm{u}}}}}}}\overline{{{{{{\rm{d}}}}}}}$$ c c u ¯ d ¯ and spin-parity quantum numbers JP = 1+. Study of the DD mass spectra disfavours interpretation of the resonance as the isovector state. The decay structure via intermediate off-shell D*+ mesons is consistent with the observed D0π+ mass distribution. To analyse the mass of the resonance and its coupling to the D*D system, a dedicated model is developed under the assumption of an isoscalar axial-vector $${{{{{{\rm{T}}}}}}}_{{{{{{\rm{c}}}}}}{{{{{\rm{c}}}}}}}^{+}$$ T c c + state decaying to the D*D channel. Using this model, resonance parameters including the pole position, scattering length, effective range and compositeness are determined to reveal important information about the nature of the $${{{{{{\rm{T}}}}}}}_{{{{{{\rm{c}}}}}}{{{{{\rm{c}}}}}}}^{+}$$ T c c + state. In addition, an unexpected dependence of the production rate on track multiplicity is observed.