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1. Beta Diffusion

   Zhou, Mingyuan; Chen, Tianqi; Wang, Zhendong; Zheng, Huangjie (December 2023, Neural Information Processing Systems)

   We introduce beta diffusion, a novel generative modeling method that integrates demasking and denoising to generate data within bounded ranges. Using scaled and shifted beta distributions, beta diffusion utilizes multiplicative transitions over time to create both forward and reverse diffusion processes, maintaining beta distributions in both the forward marginals and the reverse conditionals, given the data at any point in time. Unlike traditional diffusion-based generative models relying on additive Gaussian noise and reweighted evidence lower bounds (ELBOs), beta diffusion is multiplicative and optimized with KL-divergence upper bounds (KLUBs) derived from the convexity of the KL divergence. We demonstrate that the proposed KLUBs are more effective for optimizing beta diffusion compared to negative ELBOs, which can also be derived as the KLUBs of the same KL divergence with its two arguments swapped. The loss function of beta diffusion, expressed in terms of Bregman divergence, further supports the efficacy of KLUBs for optimization. Experimental results on both synthetic data and natural images demonstrate the unique capabilities of beta diffusion in generative modeling of range-bounded data and validate the effectiveness of KLUBs in optimizing diffusion models, thereby making them valuable additions to the family of diffusion-based generative models and the optimization techniques used to train them. 

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2. Charge-carrier collective motion in germanium detectors for $$\beta \beta $$-decay searches

   https://doi.org/10.1140/epjc/s10052-021-08889-0  

   Comellato, Tommaso; Agostini, Matteo; Schönert, Stefan (January 2021, The European Physical Journal C)

   null (Ed.)

   Abstract The time analysis of the signal induced by the drift of charge carriers in high purity germanium detectors provides information on the event topology. Millions of charge carriers are produced in a typical event. Their initial distribution, stochastic diffusion and Coulomb self-repulsion affect the time structure of the signal. We present a comprehensive study of these effects and evaluate their impact on the event discrimination capabilities for the three geometries which will be used in the Legend  experiment for neutrinoless double-beta decay. 

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3. The “Beta-Delayed Neutrons at RIKEN” Project (BRIKEN): Conquering the Most Exotic Beta-Delayed Neutron-Emitters

   https://doi.org/10.1080/10619127.2018.1427937  

   Dillmann, Iris; Tarifeño-Saldivia, Ariel (January 2018, Nuclear Physics News)
4. The aCORN backscatter-suppressed beta spectrometer

   https://doi.org/10.1016/j.nima.2017.05.029  

   Hassan, M.T.; Bateman, F.; Collett, B.; Darius, G.; DeAngelis, C.; Dewey, M.S.; Jones, G.L.; Komives, A.; Laptev, A.; Mendenhall, M.P.; et al (September 2017, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment)

   null (Ed.)
5. Characterization of Additively Manufactured Beta Materials

   Dana, E.; Kumpaty, S.; Weston, J. (November 2022, ASME International Mechanical Engineering Conference and Exposition)

   IMECE2022-88301 Additive manufacturing (AM) is transforming industrial production. AM can produce parts with complex geometries and functionality. However, one of the biggest challenges in the AM world is limited material options. The purpose of this research is to develop new material mixtures and determine their mechanical properties for use at the MSOE Rapid Prototyping Center and provide valuable insight into beta materials for use in AM industry. Elastomeric polyurethane (EPU 40) and Rigid polyurethane (RPU 70), resins developed by Carbon3D, are employed for this research. Initially, EPU 40 (100%) and RPU 70 (100%) were used to print tensile and hardness test specimens so that their mechanical properties could be compared to the standard values presented by Carbon3D and used as benchmarks for newly developed material. Mixtures of the two materials, EPU 40 and RPU 70, in multiple ratios were then created and used to print tensile and hardness test specimens. Data collected from tensile and hardness tests show that EPU 40 and RPU 70 can be combined in various ratios to obtain material properties that lie between the two individual components. In addition to developing these new materials, the effect of printing orientation on mechanical properties was also studied in this paper. 

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