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The introduction of AlphaFold 2 1 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design 2 , 3 , 4 , 5 – 6 . Here we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, ions and modified residues. The new AlphaFold model demonstrates substantially improved accuracy over many previous specialized tools: far greater accuracy for protein–ligand interactions compared with state-of-the-art docking tools, much higher accuracy for protein–nucleic acid interactions compared with nucleic-acid-specific predictors and substantially higher antibody–antigen prediction accuracy compared with AlphaFold-Multimer v.2.3 7 , 8 . Together, these results show that high-accuracy modelling across biomolecular space is possible within a single unified deep-learning framework. AlphaFold 3 has a substantially updated architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, ions and modified residues with greatly improved accuracy over many previous specialized tools.

The SNO+ experiment is the successor to the SNO neutrino detector, which replaces its heavy water target with a liquid scintillator one. The primary physics goal is the search for neutrinoless double beta decay (0vββ) in 130Te, which will be loaded into the scintillator. Fitted with > 9300 photo-multiplier tubes, the SNO+ detector will have the highest photo-cathode coverage of any large liquid scintillator detector. This thesis shows that, at this light collection level, SNO+ is sensitive to differences in the scintillation pulses produced by electrons, positrons and gammas, and that these differences may be used to classify single-site 0vββ events and multi-site radioactive backgrounds which emit γ. This pulse shape discrimination technique (PSD) is applied to background events from radiation originating outside the detector, which limit the experiment's fiducial volume, and potential internal radioactive decays, like 60Co, which are otherwise difficult to distinguish from 0vββ. A new signal extraction framework is described and used to perform 2D fits in energy and event radius, which estimate an expected limit on the 0vββ half-life of T0v1/2 1.76 x 1026 yr, at 90% confidence, assuming an exposure of 4.0 tonne yr of 130Te. The corresponding limit on the effective Majorana mass is mββ < 49.7meV, using the IBM-2 nuclear model. Further, it is shown that adding PSD as an additional fit dimension can reduce the SNO+ 3 sigma discovery level on mββ from 190meV to 91 meV, assuming the same exposure. The final portion of this work discusses what more could be achieved using a liquid scintillator experiment which can separate scintillation and Cherenkov signals in time. A simulation of a SNO+ style detector, filled with a slow scintillator and equipped with a high coverage of fast, high quantum efficiency PMTs is used to demonstrate separation of Cherenkov and scintillation signals and reconstruction algorithms for electron and 0vββ events are described. Differences in Cherenkov signals are used to distinguish 0vββ from the solar neutrino elastic scattering background, and to demonstrate for the first time that, in principle, the 0vββ mechanism may be determined in liquid scintillator by fitting the angular separation and energy split of the two emitted electrons.

Simulation studies have been carried out to explore the ability to discriminate between single-site and multi-site energy depositions in large scale liquid scintillation detectors. A robust approach has been found that is predicted to lead to a significant statistical separation for a large variety of event classes, providing a powerful tool to discriminate against backgrounds and break important degeneracies in signal extraction. This has particularly relevant implications for liquid scintillator searches for neutrinoless double beta decay (\\(0\\nu\\beta\\beta\\)) from \\(^{130}\\)Te and \\(^{136}\\)Xe, where it is possible for a true \\(0\\nu\\beta\\beta\\) signal to be distinguished from most radioactive backgrounds (including those from cosmogenic production) as well as unknown gamma lines from the target isotope.

The potential for using slow-fluor liquid scintillators to study low energy solar neutrinos and neutrinoless double beta decay (0nbb) is explored through a series of simulations. The fluorescence model assumed for the primary fluor has characteristics similar to acenaphthene, recently used to demonstrate Cherenkov separation at energies around 1 MeV. Results here indicate notably better directional reconstruction in large-scale detectors than has previously been suggested by other approaches, allowing better identification of low energy solar neutrinos. These studies indicate that a detector with as little as ~30% coverage using currently available photomultiplier tubes could be able to make a measurement of the CNO solar neutrino flux to a precision of better than 10% (enough to distinguish metallicity models) with a few kiloton-years of exposure. In terms of 0nbb studies here suggest that the ability to separate mechanisms based on angular distributions is weak, but that the rejection of solar neutrino backgrounds with such a technique might potentially approach a factor of 10 for endpoint energies near 2.5 MeV in the angular hemisphere defined by the solar direction.