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J/ψ, a charmonium bound state made of a charm and an anti-charm quark, was discovered in the 1970s and confirmed the quark model. Because the mass of charm quarks is significantly above the quantum chromodynamics (QCD) scale ΛQCD, charmonia are considered excellent probes to test perturbative quantum chromodynamics (pQCD) calculations. In recent decades, they have been studied extensively at different high-energy colliders. However, their production mechanisms, which involve multiple scales, are still not very well understood. Recently, in high-multiplicity p+p collisions at RHIC and at the LHC, a significant enhancement of J/ψ production yield has been observed, which suggests a strong contribution of multi-parton interaction (MPI). This is different from the traditional pQCD picture, where charm quark pairs are produced from a single hard scattering between partons in p+p collisions. In this work, we will report the J/ψ normalized production yield as a function of normalized charged particle multiplicity over a board range of rapidity and event multiplicity in the J/ψ→μ+μ− channel with PHENIX Run 15 p+p data at s=200 GeV. The results are compared with PYTHIA 8 simulations with the MPI option turned on and off. Finally, the outlooks of J/ψ in p+Au and Au+p collisions, along with color glass condensate (CGC) predictions and the multiplicity-dependent ψ(2S)/J/ψ ratio in p+p data, will be briefly discussed.

In this commentary, I suggest that it may be helpful to think about the formidable problem space that Westergaard’s (2021) Linguistic Proximity Model seeks to address at the three levels of analysis that Marr (1982) famously proposed are needed to understand any complex cognitive system. I argue that at the computational level of analysis, where it appears the Linguistic Proximity Model is epistemiologically situated, the notion of copying grammatical representations is unproblematic, contrary to Westergaard’s concerns.

Terminal iterative learning control (TILC) is developed to reduce the error between system output and a fixed desired point at the terminal end of operation interval over iterations under strictly identical initial conditions. In this work, the initial states are not required to be identical further but can be varying from iteration to iteration. In addition, the desired terminal point is not fixed any more but is allowed to change run-to-run. Consequently, a new adaptive TILC is proposed with a neural network initial state learning mechanism to achieve the learning objective over iterations. The neural network is used to approximate the effect of iteration-varying initial states on the terminal output and the neural network weights are identified iteratively along the iteration axis. A dead-zone scheme is developed such that both learning and adaptation are performed only if the terminal tracking error is outside a designated error bound. It is shown that the proposed approach is able to track run-varying terminal desired points fast with a specified tracking accuracy beyond the initial state variance.

Memristor synapse can be used to characterize the electromagnetic induction effect between two neurons that induces an action current by their membrane potential difference. This paper proposes a memristor synapse-coupled neuron network with no equilibrium, which is achieved using a memristor synapse to connect the membrane potentials of two identical three-dimensional memristive Hindmarsh–Rose neurons. Exponential synchronization is proved theoretically, and synchronous activities are discussed numerically. The theoretical and numerical results illustrate that the synchronicities of memristor synapse-coupled neuron network are related to the memristor coupling coefficient and especially related to the initial states of memristor synapse and coupling neurons. Furthermore, by constructing a ring network of memristor synapse-coupled neuron network, several types of collective behaviors including incoherent, coherent, imperfect synchronization, and chimera states are disclosed numerically, which indicate that the chimera states arisen in the ring network are dependent on the memristor coupling coefficient and sub-network coupling strength.

Because of the advent of discrete memristor, memristor effect in discrete map has become the important subject deserving discussion. To this end, this paper constructs a memristor-based neuron model considering magnetic induction by combining an existing map-based neuron model and a discrete memristor with absolute value memductance. Taking the coupling strength and initial state of the memristor as variables, complex mode transition behaviors induced by the introduced memristor are disclosed using numerical methods, including spiking-bursting behaviors, mode transition behaviors, and hyperchaotic spiking behaviors. In particular, all of these behaviors are greatly dependent on the memristor initial state, resulting in the existence of extreme multistability in the memristive neuron model. Therefore, this memristive neuron model can be used to effectively imitate the magnetic induction effects when complex mode transition behaviors appear in the neuronal action potential. Besides, a hardware platform based on FPGA is developed for implementing the memristive neuron model and various spiking-bursting sequences are experimentally captured therein. The results show that when biophysical memory effect is present, the memristive neuron model can better represent the firing activities of biological neurons than the original map-based neuron model.

In this corrigendum, we point out that the photon energy 16.3 eV is written as 13.6 eV by mistake in some statements in the article 2022 New J. Phys. 24 093019.

By simplifying connection topology of Hopfield neural network (HNN) with three neurons, a kind of HNN-based nonlinear system is proposed. Taking a coupling-connection weight as unique adjusting parameter and utilizing conventional dynamical analysis methods, dynamical behaviors with the variation of the adjusting parameter are discussed and coexisting multiple attractors’ behavior under different state initial values are investigated. The results imply that the HNN-based system displays point, periodic, and chaotic behaviors as well as period-doubling and tangent bifurcation routes; particularly, this system exhibits some striking phenomena of coexisting multiple attractors, such as, a pair of single-scroll chaotic attractors accompanied with a pair of periodic attractors, a pair of periodic attractors with two periodicities, and so on. Of particular interest, it should be highly significant that a hardware circuit of the HNN-based system is developed by using commercially available electronic components and many kinds of coexisting multiple attractors are captured from the hardware experiments. The results of the experimental measurements have well consistency to those of MATLAB and PSpice simulations.

Initial State Radiation (ISR) plays an important role in e + e − collision experiments such as the BESIII. To correct the ISR effects in measurements of hadronic cross-sections of e + e − annihilation, an iterative method that weights simulated ISR events is proposed here to assess the efficiency of event selection and the ISR correction factor for the observed cross-section. The simulated ISR events were generated only once, and the obtained cross-sectional line shape was used iteratively to weigh the same simulated ISR events to evaluate the efficiency and corrections until the results converge. Compared with the method of generating ISR events iteratively, the proposed weighting method provides consistent results, and reduces the computational time and disk space required by a factor of five or more, thus speeding-up e + e − hadronic cross-section measurements.

The angular distributions of the photoelectrons in ionization of hydrogen atom by both circularly and linearly polarized intense extreme ultraviolet (XUV) attosecond pulse are investigated by numerically solving the time-dependent Schrödinger equation. We clearly identify nonperturbative features in studying the asymmetrical photoelectron angular distributions in the polarization plane for the XUV photon energy (16.3 eV) close to the ionization threshold, while such nonperturbative features are absent for higher photon energy (36 eV) in the same pulse intensity region. In addition to the carrier-envelope phase (CEP) dependence, the ejection asymmetry of the photoelectron is also sensitive to the relative phases of transition amplitudes in absorbing one photon and two photons. As a consequence, the CEPs corresponding to the maximal (or zero) asymmetry obviously vary as the pulse intensity increases in a moderately large region from 1 × 10 15 W cm −2 to 30 × 10 15 W cm −2 . We attribute the intensity dependence of the transition amplitude phases to a consequence of the depletion of population as well as the Stark energy shift of the initial state. We show that the relative phases of transition amplitudes can be precisely decoded from the pulse intensity dependence of the ejection asymmetry and those phases are insensitive to the ellipticity of the laser pulse.