Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement

We explore the methodology and theory of reward-directed generation via conditional diffusion models. Directed generation aims to generate samples with desired properties as measured by a reward function, which has broad applications in generative AI, reinforcement learning, and computational biology. We consider the common learning scenario where the data set consists of unlabeled data along with a smaller set of data with noisy reward labels. Our approach leverages a learned reward function on the smaller data set as a pseudolabeler. From a theoretical standpoint, we show that this directed generator can effectively learn and sample from the reward-conditioned data distribution. Additionally, our model is capable of recovering the latent subspace representation of data. Moreover, we establish that the model generates a new population that moves closer to a user-specified target reward value, where the optimality gap aligns with the off-policy bandit regret in the feature subspace. The improvement in rewards obtained is influenced by the interplay between the strength of the reward signal, the distribution shift, and the cost of off-support extrapolation. We provide empirical results to validate our theory and highlight the relationship between the strength of extrapolation and the quality of generated samples

Measurement of Stimulated Raman Side-Scattering Predominance and Energetic Importance in the Compression Stage of the Double-Cone Ignition Approach to Inertial Confinement Fusion

Due to its particular geometry, stimulated Raman side-scattering (SRSS) drives scattered light emission at non-conventional directions, leading to scarce and complex experimental observations. Experimental campaigns at the SG-II UP facility have measured the scattered light driven by SRSS over a wide range of angles, showing an emission at large polar angles, sensitive to the plasma profile and laser polarization. Furthermore, direct comparison with back-scattering measurement has evidenced SRSS as the dominant Raman scattering process in the compression stage, leading to the scattering loss of about 5\% of the total laser energy. The predominance of SRSS was confirmed by 2D particle-in-cell simulations, and its angular spread has been corroborated by ray-tracing simulations. The main implication is that a complete characterization of the SRS instability and an accurate measurement of the energy losses require the collection of the scattered light in a broad range of directions. Otherwise, spatially limited measurement could lead to an underestimation of the energetic importance of stimulated Raman scattering

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

An auto-reclosing scheme for DC circuit breaker in VSC-HVDC transmission system

When a DC line fault happens, the converter will be blocked instantly. This leads to an interruption of power transmission and influences the stability of DC and AC systems. To avoid the blocking of converters, this paper presents a novel protection scheme for VSC-HVDC system, which consists fault isolation and auto-reclosing of DC circuit breaker (DCCB). First, this paper coordinates the protective actions of converters and DCCB. The DC line fault is cut immediately by DCCB while the blocking signal of converter is isolated during the fault. Second, since the faults of long overhead transmission DC lines are mostly transient, an auto-reclosing strategy is developed. The emphasise of this part, which includes fault discrimination and time sequences, between DCCB and converter is elaborated, and the value of reclosing delay is derived by analysing the charging and discharging characteristics of capacitor paralleled with converter. Finally, the protection scheme is evaluated by overcurrent, overvoltage, and recovery time of DC system, and simulation results of a point-to-point VSC-HVDC transmission system proves its validity

Hydrogenation of Styrene-Butadiene Rubber Catalyzed by Tris(triisopropylphosphine)hydridorhodium(I)

The hydrogenation of C=C bonds in styrene−butadiene rubber (SBR), catalyzed by RhH(P(i-Pr)3)3, was experimentally investigated. Tris(triisopropylphosphine)hydridorhodium(I), RhH(P(i-Pr)3)3 (i-Pr=CH(CH3)2) was prepared by using rhodium chloride (RhCl3), tetrahydrofuran (THF), triisopropylphosphine (P(i-Pr)3) and a sodium mercury amalgam. The effect of catalyst/polymer ratio, reaction temperature, and hydrogen pressure on the reactivity of the catalytic system has been studied. The optimal experimental condition was obtained. The hydrogenated styrene-butadiene rubber (HSBR) was analyzed by FT-IR and 1H-NMR. In the absence of any additives, the conversion of C=C bonds in SBR could easily reach 95% in a short period of time, and no obvious cross-linking was observed. The dynamic properties of SBR did not change after the hydrogenation of the unsaturated C=C bonds. A preliminary reaction mechanism was also proposed. This study provides a new route, not only for the chemical modification of SBR by using a rhodium complex but also for the hydrogenation of other unsaturated polymers, such as diene-based rubbers

Recent Developments on Processes for Recovery of Rhodium Metal from Spent Catalysts

Rhodium (Rh) catalyst has played an indispensable role in many important industrial and technological applications due to its unique and valuable properties. Currently, Rh is considered as a strategic or critical metal as the scarce high-quality purity can only be supplemented by refining coarse ores with low content (2–10 ppm) and is far from meeting the fast-growing market demand. Nowadays, exploring new prospects has already become an urgent issue because of the gradual depletion of Rh resources, incidental pressure on environmental protection, and high market prices. Since waste catalyst materials, industrial equipment, and electronic instruments contain Rh with a higher concentration than that of natural minerals, recovering Rh from scrap not only offers an additional source to satisfy market demand but also reduces the risk of ore over-exploitation. Therefore, the recovery of Rh-based catalysts from scrap is of great significance. This review provides an overview of the Rh metal recovery from spent catalysts. The characteristics, advantages and disadvantages of several current recovery processes, including pyrometallurgy, hydrometallurgy, and biosorption technology, are presented and compared. Among them, the hydrometallurgical process is commonly used for Rh recovery from auto catalysts due to its technological simplicity, low cost, and short processing time, but the overall recovery rate is low due to its high remnant Rh within the insoluble residue and the unstable leaching. In contrast, higher Rh recovery and less effluent discharge can be ensured by a pyrometallurgical process which therefore is widely employed in industry to extract precious metals from spent catalysts. However, the related procedure is quite complex, leading to an expensive hardware investment, high energy consumption, long recovery cycles, and inevitable difficulties in controlling contamination in practice. Compared to conventional recovery methods, the biosorption process is considered to be a cost-effective biological route for Rh recovery owing to its intrinsic merits, e.g., low operation costs, small volume, and low amount of chemicals and biological sludge to be treated. Finally, we summarize the challenges and prospect of these three recovery processes in the hope that the community can gain more meaningful and comprehensive insights into Rh recovery