Excited Heavy Quarkonium Production at the LHC through WW-Boson Decays

Sizable amount of heavy-quarkonium events can be produced through $W$-boson decays at the LHC. Such channels will provide a suitable platform to study the heavy-quarkonium properties. The "improved trace technology", which disposes the amplitude ${\cal M}$ at the amplitude-level, is helpful for deriving compact analytical results for complex processes. As an important new application, in addition to the production of the lower-level Fock states $|(Q\bar{Q'})[1S]>$ and $|(Q\bar{Q'})[1P]>$, we make a further study on the production of higher-excited $|(Q\bar{Q'})>$-quarkonium Fock states $|(Q\bar{Q'})[2S]>$, $|(Q\bar{Q'})[3S]>$ and $|(Q\bar{Q'})[2P]>$. Here $|(Q\bar{Q'})>$ stands for the $|(c\bar{c})>$-charmonium, $|(c\bar{b})>$-quarkonium and $|(b\bar{b})>$-bottomonium respectively. We show that sizable amount of events for those higher-excited states can also be produced at the LHC. Therefore, we need to take them into consideration for a sound estimation.Comment: 7 pages, 9 figures and 6 tables. Typo errors are corrected, more discussions and two new figures have been adde

Enablers and Consequences of Interfirm Co-Production

As contemporary firms increase their reliance on information technology (IT) and are increasingly turning their attention to jointly creating value with their primary stakeholders, there is a growing need to understand what enablers promote from interfirm value co-creation from co-production in supply chains, how the co-production can be realized and what value can be created through the co-production. We integrate systems theory and the relational view perspectives to develop an explanatory model to explain how co-production mediates the impacts of enablers on the reciprocal benefits created in the global supply chain context. Drawing upon systems theory, we identify three constructs: platform compatibility (i.e., compatibility), co-production (i.e., synergy), and collaborative governance (i.e., integration effort). We draw on the relational view to identify two activities: process alignment and resource sharing for co-production, conceptualize three basic types of reciprocal benefits: market, innovation and anshin value, and theorize co-production—the synergy of process alignment and resource sharing activities—as key to the realization of synergy, thereby contributing to the reciprocal benefits in the context of interfirm supply chain. Based on survey data collected from 464 senior management representatives from 230 high-tech manufacturing firms from within Taiwan and China, we found 1) collaborative governance has a positive effect on platform compatibility, 2) both collaborative governance and platform compatibility promote co-production, 3) guanxi has a positive effect on collaborative governance and has a positive moderating effect on collaborative governance and co-production, and 4) co-production positively affects reciprocal benefits. Our findings highlight 1) the important role of co-production in mediating the platform compatibility and collaborative governance effects on reciprocal benefits, and 2) the complementary role of guanxi in strengthening the collaborative governance effect on co-production. These results provide insights into how firms can co-create value through enhanced interfirm co-production

DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines

Multi-task model training has been adopted to enable a single deep neural network model (often a large language model) to handle multiple tasks (e.g., question answering and text summarization). Multi-task training commonly receives input sequences of highly different lengths due to the diverse contexts of different tasks. Padding (to the same sequence length) or packing (short examples into long sequences of the same length) is usually adopted to prepare input samples for model training, which is nonetheless not space or computation efficient. This paper proposes a dynamic micro-batching approach to tackle sequence length variation and enable efficient multi-task model training. We advocate pipeline-parallel training of the large model with variable-length micro-batches, each of which potentially comprises a different number of samples. We optimize micro-batch construction using a dynamic programming-based approach, and handle micro-batch execution time variation through dynamic pipeline and communication scheduling, enabling highly efficient pipeline training. Extensive evaluation on the FLANv2 dataset demonstrates up to 4.39x higher training throughput when training T5, and 3.25x when training GPT, as compared with packing-based baselines. DynaPipe's source code is publicly available at https://github.com/awslabs/optimizing-multitask-training-through-dynamic-pipelines.Comment: 18 pages, 18 figure

Proposal for Studying N∗N^* Resonances with pˉp→pˉnπ+\bar{p}p \to \bar{p}n \pi^+ Reaction

A theoretical study of $\bar{p}p \to \bar{p}n \pi^+$ reaction for anti-proton beam energy from 1 to 4 GeV is made by including contributions from various known $N^*$ and $\Delta^*$ resonances. It is found that for the beam energy around 1.5 GeV, the contribution of the Roper resonance $N^*_{(1440)}$ produced by the t-channel $\sigma$ exchange dominates over all other contributions. Since such reaction can be studied in the forthcoming $\bar{P}$ANDA experiment at Facility of Antiproton and Ion Research (FAIR), the reaction will be realistically the cleanest place for studying the properties of the Roper resonance and the best place for looking for other "missing" $N^*$ resonances with large coupling to $N\sigma$.Comment: 18 pages, 21 figure

Bifurcation and chaos of a flag in an inviscid flow

A two-dimensional model is developed to study the flutter instability of a flag immersed in an inviscid flow. Two dimensionless parameters governing the system are the structure-to-fluid mass ratio M⁎ and the dimensionless incoming flow velocity U⁎. A transition from a static steady state to a chaotic state is investigated at a fixed M⁎=1 with increasing U⁎. Five single-frequency periodic flapping states are identified along the route, including four symmetrical oscillation states and one asymmetrical oscillation state. For the symmetrical states, the oscillation frequency increases with the increase of U⁎, and the drag force on the flag changes linearly with the Strouhal number. Chaotic states are observed when U⁎ is relatively large. Three chaotic windows are observed along the route. In addition, the system transitions from one periodic state to another through either period-doubling bifurcations or quasi-periodic bifurcations, and it transitions from a periodic state to a chaotic state through quasi-periodic bifurcations