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We report new measurements of the cross sections for the production of Dbar D final states at the ψ(3770) resonance. Our data sample consists of an integrated luminosity of 2.93 fb−1 of e+e− annihilation data produced by the BEPCII collider and collected and analyzed with the BESIII detector. We exclusively reconstruct three D0 and six D+ hadronic decay modes and use the ratio of the yield of fully reconstructed Dbar D events ("double tags") to the yield of all reconstructed D or bar D mesons ("single tags") to determine the number of D0bar D0 and D+D− events, benefiting from the cancellation of many systematic uncertainties. Combining these yields with an independent determination of the integrated luminosity of the data sample, we find the cross sections to be σ(e+e− → D0bar D0) nb and σ(e+e− → D+D−) = (2.830 ± 0.011 ± 0.026) nb, where the uncertainties are statistical and systematic, respectively.
Using a data sample of 𝑒+𝑒− collisions corresponding to an integrated luminosity of 567 pb−1 collected at a center-of-mass energy of √𝑠=4.6 GeV with the BESIII detector, we measure the absolute branching fraction of the inclusive semileptonic Λ+𝑐 decay with a double-tag method. We obtain ℬ(Λ+𝑐→𝑋𝑒+𝜈𝑒)=(3.95±0.34±0.09)%, where the first uncertainty is statistical and the second systematic. Using the known Λ+𝑐 lifetime and the charge-averaged semileptonic decay width of nonstrange charmed mesons (𝐷0 and 𝐷+), we obtain the ratio of the inclusive semileptonic decay widths Γ(Λ+𝑐→𝑋𝑒+𝜈𝑒)/¯Γ(𝐷→𝑋𝑒+𝜈𝑒)=1.26±0.12.
We study the electromagnetic Dalitz decay 𝐽/𝜓→𝑒+𝑒−𝜂 and search for dielectron decays of a dark gauge boson (𝛾′) in 𝐽/𝜓→𝛾′𝜂 with the two 𝜂 decay modes 𝜂→𝛾𝛾 and 𝜂→𝜋+𝜋−𝜋0 using (1310.6±7.0)×106 𝐽/𝜓 events collected with the BESIII detector. The branching fraction of 𝐽/𝜓→𝑒+𝑒−𝜂 is measured to be (1.43±0.04(stat)±0.06(syst))×10−5, with a precision that is improved by a factor of 1.5 over the previous BESIII measurement. The corresponding dielectron invariant mass dependent modulus square of the transition form factor is explored for the first time, and the pole mass is determined to be Λ=2.84±0.11(stat)±0.08(syst) GeV/𝑐2. We find no evidence of 𝛾′ production and set 90% confidence level upper limits on the product branching fraction ℬ(𝐽/𝜓→𝛾′𝜂)×ℬ(𝛾′→𝑒+𝑒−) as well as the kinetic mixing strength between the standard model photon and 𝛾′ in the mass range of 0.01≤𝑚𝛾′≤2.4 GeV/𝑐2.
Using a data sample with an integrated luminosity of 2.93 fb−1 taken at the center-of-mass energy of 3.773 GeV, we search for the Majorana neutrino (𝜈𝑚) in the lepton number violating decays 𝐷→𝐾𝜋𝑒+𝑒+. No significant signal is observed, and the upper limits on the branching fraction at the 90% confidence level are set to be ℬ(𝐷0→𝐾−𝜋−𝑒+𝑒+)<2.8×10−6, ℬ(𝐷+→𝐾0𝑆𝜋−𝑒+𝑒+)<3.3×10−6 and ℬ(𝐷+→𝐾−𝜋0𝑒+𝑒+)<8.5×10−6. The Majorana neutrino is searched for with different mass assumptions ranging from 0.25 to 1.0 GeV/𝑐2 in the decays 𝐷0→𝐾−𝑒+𝜈𝑚,𝜈𝑚→𝜋−𝑒+ and 𝐷+→𝐾0𝑆𝑒+𝜈𝑚,𝜈𝑚→𝜋−𝑒+, and the upper limits on the branching fraction at the 90% confidence level are at the level of 10−7∼10−6, depending on the mass of the Majorana neutrino. The constraints on the mixing matrix element |𝑉𝑒𝜈𝑚|2 are also evaluated.
he process e+e−→pK0Sn¯K−+c.c. and its intermediate processes are studied for the first time, using data samples collected with the BESIII detector at BEPCII at center-of-mass energies of 3.773, 4.008, 4.226, 4.258, 4.358, 4.416, and 4.600 GeV, with a total integrated luminosity of 7.4 fb−1. The Born cross section of e+e−→pK0Sn¯K−+c.c. is measured at each center-of-mass energy, but no significant resonant structure in the measured cross-section line shape between 3.773 and 4.600 GeV is observed. No evident structure is detected in the pK−, nK0S, pK0S, nK+, pn¯, or K0SK− invariant mass distributions except for Λ(1520). The Born cross sections of e+e−→Λ(1520)n¯K0S+c.c. and e+e−→Λ(1520)p¯K++c.c. are measured, and the 90\% confidence level upper limits on the Born cross sections of e+e−→Λ(1520)Λ¯(1520) are determined at the seven center-of-mass energies.
We report on new measurements of Cabibbo-suppressed semileptonic D+s decays using 3.19 fb−1 of e+e− annihilation data sample collected at a center-of-mass energy of 4.178~GeV with the BESIII detector at the BEPCII collider. Our results include branching fractions B(D+s→K0e+νe)=(3.25±0.38(stat.)±0.16(syst.))×10−3 and B(D+s→K∗0e+νe)=(2.37±0.26(stat.)±0.20(syst.))×10−3 which are much improved relative to previous measurements, and the first measurements of the hadronic form-factor parameters for these decays. For D+s→K0e+νe, we obtain f+(0)=0.720±0.084(stat.)±0.013(syst.), and for D+s→K∗0e+νe, we find form-factor ratios rV=V(0)/A1(0)=1.67±0.34(stat.)±0.16(syst.) and r2=A2(0)/A1(0)=0.77±0.28(stat.)±0.07(syst.).
We report the first measurements of absolute branching fractions for the W -exchange-only processes + c → 0K + and + c → (1530)0K + with the double-tag technique, by analyzing an e+e− collision data sample, that corresponds to an integrated luminosity of 567 pb−1 collected at a center-of-mass energy of 4.6 GeV by the BESIII detector. The branching fractions are measured to be B(+c → 0K +) = (5.90 ± 0.86 ± 0.39) × 10−3 and B(+c → (1530)0K +) = (5.02 ± 0.99 ± 0.31) × 10−3, where the first uncertainties are statistical and the second systematic. Our results are more precise than the previous relative measurements.
We present a model for the autonomous and simultaneous learning of active binocular and motion vision. The model is based on the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model learns how to efficiently encode the incoming visual signals generated by an object moving in 3-D through sparse coding. Simultaneously, it learns how to produce eye movements that further improve the efficiency of the sensory coding. This learning is driven by an intrinsic motivation to maximize the system's coding efficiency. We test our approach on the humanoid robot iCub using simulations. The model demonstrates self-calibration of accurate object fixation and tracking of moving objects. Our results show that the model keeps improving until it hits physical constraints such as camera or motor resolution, or limits on its internal coding capacity. Furthermore, we show that the emerging sensory tuning properties are in line with results on disparity, motion, and motion-in-depth tuning in the visual cortex of mammals. The model suggests that vergence and tracking eye movements can be viewed as fundamentally having the same objective of maximizing the coding efficiency of the visual system and that they can be learned and calibrated jointly through AEC.
The efficient coding hypothesis posits that sensory systems of animals strive to encode sensory signals efficiently by taking into account the redundancies in them. This principle has been very successful in explaining response properties of visual sensory neurons as adaptations to the statistics of natural images. Recently, we have begun to extend the efficient coding hypothesis to active perception through a form of intrinsically motivated learning: a sensory model learns an efficient code for the sensory signals while a reinforcement learner generates movements of the sense organs to improve the encoding of the signals. To this end, it receives an intrinsically generated reinforcement signal indicating how well the sensory model encodes the data. This approach has been tested in the context of binocular vison, leading to the autonomous development of disparity tuning and vergence control. Here we systematically investigate the robustness of the new approach in the context of a binocular vision system implemented on a robot. Robustness is an important aspect that reflects the ability of the system to deal with unmodeled disturbances or events, such as insults to the system that displace the stereo cameras. To demonstrate the robustness of our method and its ability to self-calibrate, we introduce various perturbations and test if and how the system recovers from them. We find that (1) the system can fully recover from a perturbation that can be compensated through the system's motor degrees of freedom, (2) performance degrades gracefully if the system cannot use its motor degrees of freedom to compensate for the perturbation, and (3) recovery from a perturbation is improved if both the sensory encoding and the behavior policy can adapt to the perturbation. Overall, this work demonstrates that our intrinsically motivated learning approach for efficient coding in active perception gives rise to a self-calibrating perceptual system of high robustness.