Search

We present a novel scattering emulator utilizing the complex scaling method to enhance nuclear reaction analysis. This approach leverages a single set of reduced bases, allowing for efficient and simultaneous emulation across multiple channels and potential parameters, significantly reducing computational storage and accelerating calculations. Demonstrated through \(n\)+\(^{40}\)Ca and \(^{11}\)Be+\(^{64}\)Zn elastic scattering, our method achieves high accuracy and efficiency. This emulator exhibits stable and reliable performance without anomalies inherent in other techniques, showcasing its robustness., Comment: 5 pages, 3 figures, published in Phys. Lett. B 858, 139070(2024)

We introduce COLOSS, a program designed to address the scattering problem using a bound-state technique known as complex scaling. In this method, the oscillatory boundary conditions of the wave function are transformed into exponentially decaying ones, accommodating the long-range Coulomb interaction. The program implements the Woods-Saxon form of a realistic optical potential, with all potential parameters included in a well-designed input format for ease of use. This design offers users straightforward access to compute \(S\)-matrices and cross-sections of the scattering process. We provide thorough discussions on the precision of Lagrange functions and their benefits in evaluating matrix elements. Additionally, COLOSS incorporates two distinct rotation methods, making it adaptable to potentials without analytical expressions. Comparative results demonstrate that COLOSS achieves high accuracy when compared with the direct integration method, Numerov, underscoring its utility and effectiveness in scattering calculations.

Adapting End-to-End ASR models to out-of-domain datasets with text data is challenging. Factorized neural Transducer (FNT) aims to address this issue by introducing a separate vocabulary decoder to predict the vocabulary. Nonetheless, this approach has limitations in fusing acoustic and language information seamlessly. Moreover, a degradation in word error rate (WER) on the general test sets was also observed, leading to doubts about its overall performance. In response to this challenge, we present the improved factorized neural Transducer (IFNT) model structure designed to comprehensively integrate acoustic and language information while enabling effective text adaptation. We assess the performance of our proposed method on English and Mandarin datasets. The results indicate that IFNT not only surpasses the neural Transducer and FNT in baseline performance in both scenarios but also exhibits superior adaptation ability compared to FNT. On source domains, IFNT demonstrated statistically significant accuracy improvements, achieving a relative enhancement of 1.2% to 2.8% in baseline accuracy compared to the neural Transducer. On out-of-domain datasets, IFNT shows relative WER(CER) improvements of up to 30.2% over the standard neural Transducer with shallow fusion, and relative WER(CER) reductions ranging from 1.1% to 2.8% on test sets compared to the FNT model., Comment: Interspeech 2024 cameraready

We examine the validity of surface approximation for breakup reactions using a fully quantum-mechanical model proposed by Ichimura, Austern, and Vincent (IAV). Analogous to the semi-classical picture, we introduce radial cut-offs to scattering waves in the IAV framework, which we refer to as IAV-cut. Systematic calculations are conducted for nonelastic breakup reactions induced by $^6$Li and deuterons at various incident energies. A comparison between the results obtained from IAV and IAV-cut is performed. The excellent agreement observed between IAV and IAV-cut in $^{6}$Li induced reactions, regardless of incident energy and target nuclei, signifies their insensitivity to the inner part of the scattering wave function, thus providing validation for the semi-classical picture. However, for deuteron induced breakup reactions, the IAV-cut results exhibit a suppression in the cross section, suggesting a strong dependence on the interior wave functions. This suppression is further enhanced as the incident energy increases.