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ABSTRACT We employ a sample of 135 873 RR Lyrae stars (RRLs) with precise photometric-metallicity and distance estimates from the newly calibrated P–ϕ31–R21–[Fe/H] and Gaia G band P–R21–[Fe/H] absolute magnitude–metallicity relations of Li et al., combined with available proper motions from Gaia EDR3, and 6955 systemic radial velocities from Gaia DR3 and other sources, in order to explore the chemistry and kinematics of the halo of the Milky Way (MW). This sample is ideally suited for characterization of the inner- and outer-halo populations of the stellar halo, free from the bias associated with spectroscopically selected probes, and for estimation of their relative contributions as a function of Galactocentric distance. The results of a Gaussian mixture model analysis of these contributions are broadly consistent with other observational studies of the halo, and with expectations from recent MW simulation studies. We apply the hdbscan clustering method to the specific energies and cylindrical actions (E, Jr, Jϕ, Jz), identifying 97 dynamically tagged groups (DTGs) of RRLs, and explore their associations with recognized substructures of the MW. The precise photometric-distance determinations (relative distance errors on the order of 5 per cent or better), and the resulting high-quality determination of dynamical parameters, yield highly statistically significant (low) dispersions of [Fe/H] for the stellar members of the DTGs compared to random draws from the full sample, indicating that they share common star-formation and chemical histories, influenced by their birth environments. 

Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca 2+ . To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca 2+ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca 2+ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca 2+ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca 2+ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca 2+ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics.