The James Webb Space Telescope (JWST) has discovered a surprising abundance of bright galaxy candidates in the very early Universe (≤500 Myrs after the Big Bang), calling into question current galaxy formation models. Spectroscopy is needed to confirm the primeval nature of these candidates, as well as to understand how the first galaxies form stars and grow. Here we present deep spectroscopic and continuum ALMA observations towards GHZ2/GLASS-z12, one of the brightest and most robust candidates at z > 10 identified in the GLASS-JWST Early Release Science Program. We detect a 5.8σ line, offset 0.″5 from the JWST position of GHZ2/GLASS-z12 that, associating it with the [O iii] 88 $\mu {\rm m}$ transition, implies a spectroscopic redshift of z = 12.117 ± 0.001. We verify the detection using extensive statistical tests. The oxygen line luminosity places GHZ2/GLASS-z12 above the [O iii]-SFR relation for metal-poor galaxies, implying an enhancement of [O iii] emission in this system while the JWST-observed emission is likely a lower-metallicity region. The lack of dust emission seen by these observations is consistent with the blue UV slope observed by JWST, which suggest little dust attenuation in galaxies at this early epoch. Further observations will unambiguously confirm the redshift and shed light on the origins of the wide and offset line and physical properties of this early galaxy. This work illustrates the synergy between JWST and ALMA and paves the way for future spectroscopic surveys of z > 10 galaxy candidates.
Artificial neural networks (ANNs), which have excellent self-learning performance, have been applied to various applications, such as target detection and industrial control. In this paper, a reference-model-based ANN controller with integral-proportional-derivative (I-PD) compensation has been proposed for temperature control systems. To improve the ANN self-learning efficiency, a reference model is introduced for providing the teaching signal for the ANN. System simulations were carried out in the MATLAB/SIMULINK environment and experiments were carried out on a digital-signal-processor (DSP)-based experimental platform. The simulation and experimental results were compared with those for a conventional I-PD control system. The effectiveness of the proposed method was verified.
In recent years, thermal processing systems with integrated temperature control have been increasingly needed to achieve high quality and high performance. In this paper, responding to the growing demands for proper transient response and to provide more accurate temperature controls, a novel slow-mode-based control (SMBC) method is proposed for multi-point temperature control systems. In the proposed method, the temperature differences and the transient response of all points can be controlled and improved by making the output of the fast modes follow that of the slow mode. Both simulations and experiments were carried out, and the results were compared to conventional control methods in order to verify the effectiveness of the proposed method.
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