Compressing dictionaries of strings

The aim of this work is to develop a data structure capable of storing a set of strings in a compressed way providing the facility to access and search by prefix any string in the set. The notion of string will be formally exposed in this work, but it is enough to think a string as a stream of characters or a variable length dat}. We will prove that the data structure devised in our work will be able to search prefixes of the stored strings in a very efficient way, hence giving a performant solution to one of the most discussed problem of our age. In the discussion of our data structure, particular emphasis will be given to both space and time efficiency and a tradeoff between these two will be constantly searched. To understand how much string based data structures are important, think about modern search engines and social networks; they must store and process continuously immense streams of data which are mainly strings, while the output of such processed data must be available in few milliseconds not to try the patience of the user. Space efficiency is one of the main concern in this kind of problem. In order to satisfy real-time latency bounds, the largest possible amount of data must be stored in the highest levels of the memory hierarchy. Moreover, data compression allows to save money because it reduces the amount of physical memory needed to store abstract data and this particularly important since storage is the main source of expenditure in modern systems

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum

Measurement of Atmospheric Neutrino Mixing with Improved IceCube DeepCore Calibration and Data Processing

We describe a new data sample of IceCube DeepCore and report on the latest measurement of atmospheric neutrino oscillations obtained with data recorded between 2011-2019. The sample includes significant improvements in data calibration, detector simulation, and data processing, and the analysis benefits from a detailed treatment of systematic uncertainties, with significantly higher level of detail since our last study. By measuring the relative fluxes of neutrino flavors as a function of their reconstructed energies and arrival directions we constrain the atmospheric neutrino mixing parameters to be $\sin^2\theta_{23} = 0.51\pm 0.05$ and $\Delta m^2_{32} = 2.41\pm0.07\times 10^{-3}\mathrm{eV}^2$, assuming a normal mass ordering. The resulting 40\% reduction in the error of both parameters with respect to our previous result makes this the most precise measurement of oscillation parameters using atmospheric neutrinos. Our results are also compatible and complementary to those obtained using neutrino beams from accelerators, which are obtained at lower neutrino energies and are subject to different sources of uncertainties