Prompt interval temporal logic

Interval temporal logics are expressive formalisms for temporal representation and reasoning, which use time intervals as primitive temporal entities. They have been extensively studied for the past two decades and successfully applied in AI and computer science. Unfortunately, they lack the ability of expressing promptness conditions, as it happens with the commonly-used temporal logics, e.g., LTL: whenever we deal with a liveness request, such as \u201csomething good eventually happens\u201d, there is no way to impose a bound on the delay with which it is fulfilled. In the last years, such an issue has been addressed in automata theory, game theory, and temporal logic. In this paper, we approach it in the interval temporal logic setting. First, we introduce PROMPT-PNL, a prompt extension of the well-studied interval temporal logic PNL, and we prove the undecidability of its satisfiability problem; then, we show how to recover decidability (NEXPTIME-completeness) by imposing a natural syntactic restriction on it

Parametric Linear Dynamic Logic

We introduce Parametric Linear Dynamic Logic (PLDL), which extends Linear Dynamic Logic (LDL) by temporal operators equipped with parameters that bound their scope. LDL was proposed as an extension of Linear Temporal Logic (LTL) that is able to express all $\omega$-regular specifications while still maintaining many of LTL's desirable properties like an intuitive syntax and a translation into non-deterministic B\"uchi automata of exponential size. But LDL lacks capabilities to express timing constraints. By adding parameterized operators to LDL, we obtain a logic that is able to express all $\omega$-regular properties and that subsumes parameterized extensions of LTL like Parametric LTL and PROMPT-LTL. Our main technical contribution is a translation of PLDL formulas into non-deterministic B\"uchi word automata of exponential size via alternating automata. This yields a PSPACE model checking algorithm and a realizability algorithm with doubly-exponential running time. Furthermore, we give tight upper and lower bounds on optimal parameter values for both problems. These results show that PLDL model checking and realizability are not harder than LTL model checking and realizability.Comment: In Proceedings GandALF 2014, arXiv:1408.556

A 96-Channel FPGA-based Time-to-Digital Converter

We describe an FPGA-based, 96-channel, time-to-digital converter (TDC) intended for use with the Central Outer Tracker (COT) in the CDF Experiment at the Fermilab Tevatron. The COT system is digitized and read out by 315 TDC cards, each serving 96 wires of the chamber. The TDC is physically configured as a 9U VME card. The functionality is almost entirely programmed in firmware in two Altera Stratix FPGA's. The special capabilities of this device are the availability of 840 MHz LVDS inputs, multiple phase-locked clock modules, and abundant memory. The TDC system operates with an input resolution of 1.2 ns. Each input can accept up to 7 hits per collision. The time-to-digital conversion is done by first sampling each of the 96 inputs in 1.2-ns bins and filling a circular memory; the memory addresses of logical transitions (edges) in the input data are then translated into the time of arrival and width of the COT pulses. Memory pipelines with a depth of 5.5 $\mu$s allow deadtime-less operation in the first-level trigger. The TDC VME interface allows a 64-bit Chain Block Transfer of multiple boards in a crate with transfer-rates up to 47 Mbytes/sec. The TDC also contains a separately-programmed data path that produces prompt trigger data every Tevatron crossing. The full TDC design and multi-card test results are described. The physical simplicity ensures low-maintenance; the functionality being in firmware allows reprogramming for other applications.Comment: 32 pages, 13 figure

Prompt Multi-Gluon Production in High Energy Collisions from Singular Yang-Mills Solutions

We study non-perturbative parton-parton scattering in the Landau method using singular O(3) symmetric solutions to the Euclidean Yang-Mills equations. These solutions combine instanton dynamics (tunneling) and overlap (transition) between incoming and vacuum fields. We derive a high-energy solution at small Euclidean times, and assess its susequent escape and decay into gluons in Minkowski space-time. We describe the spectrum of the {\it outgoing} gluons and show that it is related through a particular rescaling to the Yang-Mills sphaleron explosion studied earlier. We assess the number of {\it incoming} gluons in the same configuration, and argue that the observed scaling is in fact more general and describes the energy dependence of the spectra and multiplicities at {\it all} energies. Applications to hadron-hadron and nucleus-nucleus collisions are discussed elsewhere

Fermi observations of high-energy gamma-ray emission from GRB 080825C

The Fermi Gamma-ray Space Telescope (FGST) has opened a new high-energy window in the study of Gamma-Ray Bursts (GRBs). Here we present a thorough analysis of GRB 080825C, which triggered the Fermi Gamma-ray Burst Monitor (GBM), and was the first firm detection of a GRB by the Fermi Large Area Telescope (LAT). We discuss the LAT event selections, background estimation, significance calculations, and localization for Fermi GRBs in general and GRB 080825C in particular. We show the results of temporal and time-resolved spectral analysis of the GBM and LAT data. We also present some theoretical interpretation of GRB 080825C observations as well as some common features observed in other LAT GRBs.Comment: 18 pages, 7 figures. Accepted for publication in ApJ. Corresponding authors: A. Bouvier, J. Granot, A.J. van der Hors

Expressive Stream Reasoning with Laser

An increasing number of use cases require a timely extraction of non-trivial knowledge from semantically annotated data streams, especially on the Web and for the Internet of Things (IoT). Often, this extraction requires expressive reasoning, which is challenging to compute on large streams. We propose Laser, a new reasoner that supports a pragmatic, non-trivial fragment of the logic LARS which extends Answer Set Programming (ASP) for streams. At its core, Laser implements a novel evaluation procedure which annotates formulae to avoid the re-computation of duplicates at multiple time points. This procedure, combined with a judicious implementation of the LARS operators, is responsible for significantly better runtimes than the ones of other state-of-the-art systems like C-SPARQL and CQELS, or an implementation of LARS which runs on the ASP solver Clingo. This enables the application of expressive logic-based reasoning to large streams and opens the door to a wider range of stream reasoning use cases.Comment: 19 pages, 5 figures. Extended version of accepted paper at ISWC 201

Water-Column Variability Assessment for Underway Profilers to Improve Efficiency and Accuracy of Multibeam Surveys

With the advent of underway profilers, sampling the water-column to obtain sound speed corrections is no longer a detriment to hydrographic survey efficiency. Instead, the challenge has become deciding how many casts are necessary to maintain a desired level of multibeam sounding accuracy, while not needlessly overworking the profiler. Ray tracing uncertainty analysis can determine in hindsight whether a particular sampling interval is adequate or not. Based on this methodology, an algorithm was developed to generate recommended sampling intervals based on successively acquired sound speed profiles, allowing the MVP to run in a “cruise-control” mode where the sampling interval is altered in response to changing oceanographic conditions. In collaboration with Rolls Royce, the algorithm was implemented in Python and loosely couples with the MVP controller software such that the recommended sampling interval can be adjusted without operator intervention. Integration of the software with the MVP controller was successfully tested aboard the NOAA Ship Ferdinand R. Hassler in September of 2012. Initial results from field trials and from analysis of existing data sets are presented