On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of $\sim 1.7\,{\rm{s}}$ with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of ${40}_{-8}^{+8}$ Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 $\,{M}_{\odot }$. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at $\sim 40\,{\rm{Mpc}}$) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient's position $\sim 9$ and $\sim 16$ days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.

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Multi-messenger observations of a binary neutron star merger

This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms.Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises.Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation

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Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms

We summarize our current knowledge of neutron-star masses and radii. Recent instrumentation and computational advances have resulted in a rapid increase in the discovery rate and precise timing of radio pulsars in binaries in the past few years, leading to a large number of mass measurements. These discoveries show that the neutron-star mass distribution is much wider than previously thought, with three known pulsars now firmly in the 1.9–2.0-M⊙ mass range. For radii, large, high-quality data sets from X-ray satellites as well as significant progress in theoretical modeling led to considerable progress in the measurements, placing them in the 10–11.5-km range and shrinking their uncertainties, owing to a better understanding of the sources of systematic errors. The combination of the massive-neutron-star discoveries, the tighter radius measurements, and improved laboratory constraints of the properties of dense matter has already made a substantial impact on our understanding of the composition and bulk p...

Masses, Radii, and the Equation of State of Neutron Stars

Gamma-ray bursts (GRBs) display a bimodal duration distribution with a separation between the short- and long-duration bursts at about 2 s. The progenitors of long GRBs have been identified as massive stars based on their association with Type Ic core-collapse supernovae (SNe), their exclusive location in star-forming galaxies, and their strong correlation with bright UV regions within their host galaxies. Short GRBs have long been suspected on theoretical grounds to arise from compact object binary mergers (neutron star–neutron star or neutron star–black hole). The discovery of short GRB afterglows in 2005 provided the first insight into their energy scale and environments, as well as established a cosmological origin, a mix of host-galaxy types, and an absence of associated SNe. In this review, I summarize nearly a decade of short GRB afterglow and host-galaxy observations and use this information to shed light on the nature and properties of their progenitors, the energy scale and collimation of the relativistic outflow, and the properties of the circumburst environments. The preponderance of the evidence points to compact object binary progenitors, although some open questions remain. On the basis of this association, observations of short GRBs and their afterglows can shed light on the on- and off-axis electromagnetic counterparts of gravitational wave sources from the Advanced LIGO/Virgo experiments.

Short-Duration Gamma-Ray Bursts

Modelling the electromagnetic emission of kilonovae enables the mass, velocity and composition (with some heavy elements) of the ejecta from a neutron-star merger to be derived from the observations. Merging neutron stars are potential sources of gravitational waves and have long been predicted to produce jets of material as part of a low-luminosity transient known as a 'kilonova'. There is growing evidence that neutron-star mergers also give rise to short, hard gamma-ray bursts. A group of papers in this issue report observations of a transient associated with the gravitational-wave event GW170817—a signature of two neutron stars merging and a gamma-ray flash—that was detected in August 2017. The observed gamma-ray, X-ray, optical and infrared radiation signatures support the predictions of an outflow of matter from double neutron-star mergers and present a clear origin for gamma-ray bursts. Previous predictions differ over whether the jet material would combine to form light or heavy elements. These papers now show that the early part of the outflow was associated with lighter elements whereas the later observations can be explained by heavier elements, the origins of which have been uncertain. However, one paper (by Stephen Smartt and colleagues) argues that only light elements are needed for the entire event. Additionally, Eleonora Troja and colleagues report X-ray observations and radio emissions that suggest that the 'kilonova' jet was observed off-axis, which could explain why gamma-ray-burst detections are seen as dim. The cosmic origin of elements heavier than iron has long been uncertain. Theoretical modelling1,2,3,4,5,6,7 shows that the matter that is expelled in the violent merger of two neutron stars can assemble into heavy elements such as gold and platinum in a process known as rapid neutron capture (r-process) nucleosynthesis. The radioactive decay of isotopes of the heavy elements is predicted8,9,10,11,12 to power a distinctive thermal glow (a ‘kilonova’). The discovery of an electromagnetic counterpart to the gravitational-wave source13 GW170817 represents the first opportunity to detect and scrutinize a sample of freshly synthesized r-process elements14,15,16,17,18. Here we report models that predict the electromagnetic emission of kilonovae in detail and enable the mass, velocity and composition of ejecta to be derived from observations. We compare the models to the optical and infrared radiation associated with the GW170817 event to argue that the observed source is a kilonova. We infer the presence of two distinct components of ejecta, one composed primarily of light (atomic mass number less than 140) and one of heavy (atomic mass number greater than 140) r-process elements. The ejected mass and a merger rate inferred from GW170817 imply that such mergers are a dominant mode of r-process production in the Universe.

Origin of the heavy elements in binary neutron-star mergers from a gravitational-wave event

One encounters the curse of dimensionality in the application of dynamic programming to determine optimal policies for large scale controlled Markov chains. In this chapter, we consider a base perimeter patrol stochastic control problem. To determine the optimal control policy, one has to solve a Markov decision problem,whose large size renders exact dynamic programming methods intractable. So, we propose a state aggregation based approximate linear programming method to construct provably good sub-optimal policies instead. The state-space is partitioned and the optimal cost-to-go or value function is approximated by a constant over each partition. By minimizing a non-negative cost function defined on the partitions, one can construct an approximate value function which also happens to be an upper bound for the optimal value function of the original Markov chain. As a general result, we show that this approximate value function is independent of the non-negative cost function (or state dependent weights; as it is referred to in the literature) and moreover, this is the least upper bound that one can obtain, given the partitions. Furthermore,we show that the restricted system of linear inequalities also embeds a family of Markov chains of lower dimension, one of which can be used to construct a tight lower bound on the optimal value function. In general, the construction of the lower bound requires the solution to a combinatorial problem. But the perimeter patrol problem exhibits a special structure that enables tractable linear programming formulations for both the upper and lower bounds. We demonstrate this and also provide numerical results that corroborate the efficacy of the proposed methodology.

Approximate Dynamic Programming Applied to UAV Perimeter Patrol

A new algorithm was developed for screening data from paired inductive traffic loop detectors. The algorithm estimates the effective vehicle length for each vehicle that passes the paired loop detectors and computes the average vehicle length for a fixed set of vehicles, the size of the set depending upon the vehicle volume flow. Error detection is done in two steps: 1) to calibrate the effective average vehicle length range for a detector; and 2) to compare this to the effective average vehicle length computation online.

Formulation of a new methodology to identify erroneous paired loop detectors

In this article, we address the problem of synthesizing UAV communication networks in the presence of resource constraints. UAVs can be deployed as backbone nodes in ad-hoc networks that can be central to civilian and military applications. The cost of operation of the network depends on the resources that are used such as the total power consumption associated with the network and the number of communication links in the network. The objective of the problem is to synthesize a communication network that maximizes connectivity subject to cost of operation being within the specified resource. We choose algebraic connectivity as a measure of connectivity of the network as it is known to be a measure of robust connectivity to random node failures in the network. We pose the network synthesis problem as a mixed-integer semi-definite program and provide (1) an algorithm for computing optimal solutions using cutting plane methods, and (2) construct feasible solutions using heuristics and estimate their quality. The network synthesis problem is a NP-hard problem and there are no guarantees on the running time of the algorithm that computes an optimal solution. We provide some computational results to corroborate the performance of the proposed algorithms.Copyright © 2012 by ASME

Synthesizing Robust Communication Networks for Unmanned Aerial Vehicles With Resource Constraints

In this article, we present the first approximation algorithm for a routing problem that is frequently encountered in the motion planning of Unmanned Vehicles (UVs). The considered problem is a variant of a Multiple Depot-Terminal Hamiltonian Path Problem and is stated as follows: There is a collection of m UVs equipped with different sensors on-board and there are n targets to be visited by them collectively. There are restrictions on the targets of the following type: (1) A target may be visited by any UV, (2) a target must be visited only by a subset of UVs (with appropriate on-board sensor) and (3) a target may not be visited by a subset of UVs (as the set of on-board sensors on the UV may not be suitable for viewing the targets). The UVs are otherwise identical from the viewpoint of dynamic constraints on their motion and hence, the cost of traveling from a target A to a target B is the same for all vehicles. We will assume that triangle inequality is satisfied by the cost associated with travel, i.e., it is cheaper to travel from a target A to a target B directly than to go via an intermediate target C. The UVs may possibly start from different locations (referred to as depots) and are not required to return to the depot. While there are different objectives that can be considered for this problem, we consider the total cost of travel of all the UVs as an objective to be minimized. The problem considered in this article is a generalized version of single depot-terminal Hamiltonian Path Problem and is NP-hard.

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Approximation algorithms for a heterogeneous Multiple Depot Hamiltonian Path Problem

In this paper, we present a new method of synthesizing digital PID controllers for discrete-time, Linear Time Invariant (LTI) Systems satisfying a class of transient response specifications. The problem of synthesizing a controller to achieve desirable transient specifications, such as requiring the transient response to be within an allowable range of overshoot, can be carried out as a problem of guaranteeing the impulse response of an appropriate closed loop error transfer function to be non-negative. An earlier result by the authors provides necessary and sufficient conditions for the impulse response of a discrete-time transfer function to be non-negative in terms of the requirement of a sequence of polynomials to be sign-invariant on the interval [1, ∞) . An application of this result to the error transfer function yields a sequence of polynomials which are required to be sign-invariant on [1, ∞) but whose coefficients are polynomial functions of the controller gains k1 , k2 and k3 .Copyright © 2011 by ASME

Swaroop Darbha

Papers

Approximate Dynamic Programming Applied to UAV Perimeter Patrol

Formulation of a new methodology to identify erroneous paired loop detectors

Synthesizing Robust Communication Networks for Unmanned Aerial Vehicles With Resource Constraints

Approximation algorithms for a heterogeneous Multiple Depot Hamiltonian Path Problem

Synthesis of Digital PID Controllers for Discrete-Time Systems With Guaranteed Non-Overshooting Transient Response