Secondary Indexing in One Dimension: Beyond B-trees and Bitmap Indexes

Let S be a finite, ordered alphabet, and let x = x_1 x_2 ... x_n be a string over S. A "secondary index" for x answers alphabet range queries of the form: Given a range [a_l,a_r] over S, return the set I_{[a_l;a_r]} = {i |x_i \in [a_l; a_r]}. Secondary indexes are heavily used in relational databases and scientific data analysis. It is well-known that the obvious solution, storing a dictionary for the position set associated with each character, does not always give optimal query time. In this paper we give the first theoretically optimal data structure for the secondary indexing problem. In the I/O model, the amount of data read when answering a query is within a constant factor of the minimum space needed to represent I_{[a_l;a_r]}, assuming that the size of internal memory is (|S| log n)^{delta} blocks, for some constant delta > 0. The space usage of the data structure is O(n log |S|) bits in the worst case, and we further show how to bound the size of the data structure in terms of the 0-th order entropy of x. We show how to support updates achieving various time-space trade-offs. We also consider an approximate version of the basic secondary indexing problem where a query reports a superset of I_{[a_l;a_r]} containing each element not in I_{[a_l;a_r]} with probability at most epsilon, where epsilon > 0 is the false positive probability. For this problem the amount of data that needs to be read by the query algorithm is reduced to O(|I_{[a_l;a_r]}| log(1/epsilon)) bits.Comment: 16 page

Stability of three neutrino flavor conversion in supernovae

Neutrino-neutrino interactions can lead to collective flavor conversion in the dense parts of a core collapse supernova. Growing instabilities that lead to collective conversions have been studied intensely in the limit of two-neutrino species and occur for inverted mass ordering in the case of a perfectly spherical supernova. We examine two simple models of colliding and intersecting neutrino beams and show, that for three neutrino species instabilities exist also for normal mass ordering even in the case of a fully symmetric system. Whereas the instability for inverted mass ordering is associated with $\Delta m_{31}^2$, the new instability we find for normal mass ordering is associated with $\Delta m_{21}^2$. As a consequence, the growth rate of these new instabilities for normal ordering is smaller by about an order of magnitude compared to the rates of the well studied case of inverted ordering.Comment: 18 pages, 5 figures Minor update on the consistency of the formulae and prefactors, actualized plot

Finite-temperature behavior of the Bose polaron

We consider a mobile impurity immersed in a Bose gas at finite temperature. Using perturbation theory valid for weak coupling between the impurity and the bosons, we derive analytical results for the energy and damping of the impurity for low and high temperatures, as well as for temperatures close to the critical temperature $T_c$ for Bose-Einstein condensation. These results show that the properties of the impurity vary strongly with temperature. In particular, the energy exhibits a non-monotonic behavior close to $T_c$, and the damping rises sharply close to $T_c$. We argue that this behaviour is generic for impurities immersed in an environment undergoing a phase transition that breaks a continuous symmetry. Finally, we discuss how these effects can be detected experimentally.Comment: 10 pages and 6 figure

IceCube Flavor Ratios with Identified Astrophysical Sources: Towards Improving New Physics Testability

Motivated by the discovery of the first high-energy astrophysical neutrino source, the blazar TXS 0506+056, we revisit the IceCube flavor ratio analysis. Assuming large statistics from identified blazars, collected in the forthcoming years by the IceCube detector and its successor IceCube-Gen2, we demonstrate that the constraints on several new physics scenarios in which the baseline dependent terms in neutrino oscillation probabilities are not averaged, can be improved. As a representative case, we consider pseudo-Dirac neutrinos while neutrino decay is also discussed.Comment: 17 pages, 5 figure

EEG source imaging assists decoding in a face recognition task

EEG based brain state decoding has numerous applications. State of the art decoding is based on processing of the multivariate sensor space signal, however evidence is mounting that EEG source reconstruction can assist decoding. EEG source imaging leads to high-dimensional representations and rather strong a priori information must be invoked. Recent work by Edelman et al. (2016) has demonstrated that introduction of a spatially focal source space representation can improve decoding of motor imagery. In this work we explore the generality of Edelman et al. hypothesis by considering decoding of face recognition. This task concerns the differentiation of brain responses to images of faces and scrambled faces and poses a rather difficult decoding problem at the single trial level. We implement the pipeline using spatially focused features and show that this approach is challenged and source imaging does not lead to an improved decoding. We design a distributed pipeline in which the classifier has access to brain wide features which in turn does lead to a 15% reduction in the error rate using source space features. Hence, our work presents supporting evidence for the hypothesis that source imaging improves decoding