Viewing angle of binary neutron star mergers

The joint detection of the gravitational wave (GW) GW170817 and its electromagnetic (EM) counterparts GRB170817A and kilonova AT 2017gfo has triggered extensive study of the EM emission of binary neutron star mergers. A parameter which is common to and plays a key role in both the GW and the EM analyses is the viewing angle of the binary's orbit. If a binary is viewed from different angles, the amount of GW energy changes (implying that orientation and distance are correlated) and the EM signatures can vary, depending on the structure of the emission. Information about the viewing angle of the binary orbital plane is therefore crucial to the interpretation of both the GW and the EM data, and can potentially be extracted from either side. In the first part of this study, we present a systematic analysis of how well the viewing angle of binary neutron stars can be measured from the GW data. We show that if the sky position and the redshift of the binary can be identified via the EM counterpart and an associated host galaxy, then for 50$\%$ of the systems the viewing angle can be constrained to $\leq 7^{\circ}$ uncertainty from the GW data, independent of electromagnetic emission models. On the other hand, if no redshift measurement is available, the measurement of the viewing angle with GW alone is not informative, unless the true viewing angle is close to $90^{\circ}$. This holds true even if the sky position is measured independently. Then, we consider the case where some constraints on the viewing angle can be placed from the EM data itself. We show that the EM measurements can then be used in the analysis of GW data to improve the precision of the luminosity distance, and hence of the Hubble constant, by a factor of 2 to 3.Comment: Accepted by Physical Review

GRB beaming and gravitational-wave observations

Using the observed rate of short-duration gamma-ray bursts (GRBs) it is possible to make predictions for the detectable rate of compact binary coalescences in gravitational-wave detectors. These estimates rely crucially on the growing consensus that short gamma-ray bursts are associated with the merger of two neutron stars or a neutron star and a black hole, but otherwise make no assumptions beyond the observed rate of short GRBs. In particular, our results do not assume coincident gravitational wave and electromagnetic observations. We show that the non-detection of mergers in the existing LIGO/Virgo data constrains the progenitor masses and beaming angles of gamma-ray bursts. For future detectors, we find that the first detection of a NS-NS binary coalescence associated with the progenitors of short GRBs is likely to happen within the first 16 months of observation, even in the case of a modest network of observatories (e.g., only LIGO-Hanford and LIGO-Livingston) operating at modest sensitivities (e.g., advanced LIGO design sensitivity, but without signal recycling mirrors), and assuming a conservative distribution of beaming angles (e.g. all GRBs beamed at \theta=30 deg). Less conservative assumptions reduce the waiting time until first detection to weeks to months. Alternatively, the compact binary coalescence model of short GRBs can be ruled out if a binary is not seen within the first two years of operation of a LIGO-Hanford, LIGO-Livingston, and Virgo network at advanced design sensitivity. We also demonstrate that the rate of GRB triggered sources is less than the rate of untriggered events if \theta<30 deg, independent of the noise curve, network configuration, and observed GRB rate. Thus the first detection in GWs of a binary GRB progenitor is unlikely to be associated with a GRB

No More Discrimination: Cross City Adaptation of Road Scene Segmenters

Despite the recent success of deep-learning based semantic segmentation, deploying a pre-trained road scene segmenter to a city whose images are not presented in the training set would not achieve satisfactory performance due to dataset biases. Instead of collecting a large number of annotated images of each city of interest to train or refine the segmenter, we propose an unsupervised learning approach to adapt road scene segmenters across different cities. By utilizing Google Street View and its time-machine feature, we can collect unannotated images for each road scene at different times, so that the associated static-object priors can be extracted accordingly. By advancing a joint global and class-specific domain adversarial learning framework, adaptation of pre-trained segmenters to that city can be achieved without the need of any user annotation or interaction. We show that our method improves the performance of semantic segmentation in multiple cities across continents, while it performs favorably against state-of-the-art approaches requiring annotated training data.Comment: 13 pages, 10 figure

A Deeply Pipelined CABAC Decoder for HEVC Supporting Level 6.2 High-tier Applications

High Efficiency Video Coding (HEVC) is the latest video coding standard that specifies video resolutions up to 8K Ultra-HD (UHD) at 120 fps to support the next decade of video applications. This results in high-throughput requirements for the context adaptive binary arithmetic coding (CABAC) entropy decoder, which was already a well-known bottleneck in H.264/AVC. To address the throughput challenges, several modifications were made to CABAC during the standardization of HEVC. This work leverages these improvements in the design of a high-throughput HEVC CABAC decoder. It also supports the high-level parallel processing tools introduced by HEVC, including tile and wavefront parallel processing. The proposed design uses a deeply pipelined architecture to achieve a high clock rate. Additional techniques such as the state prefetch logic, latched-based context memory, and separate finite state machines are applied to minimize stall cycles, while multibypass- bin decoding is used to further increase the throughput. The design is implemented in an IBM 45nm SOI process. After place-and-route, its operating frequency reaches 1.6 GHz. The corresponding throughputs achieve up to 1696 and 2314 Mbin/s under common and theoretical worst-case test conditions, respectively. The results show that the design is sufficient to decode in real-time high-tier video bitstreams at level 6.2 (8K UHD at 120 fps), or main-tier bitstreams at level 5.1 (4K UHD at 60 fps) for applications requiring sub-frame latency, such as video conferencing

On the Integrability of Four Dimensional N=2 Gauge Theories in the Omega Background

We continue to investigate the relationship between the infrared physics of N=2 supersymmetric gauge theories in four dimensions and various integrable models such as Gaudin, Calogero-Moser and quantum spin chains. We prove interesting dualities among some of these integrable systems by performing different, albeit equivalent, quantizations of the Seiberg-Witten curve of the four dimensional theory. We also discuss conformal field theories related to N=2 4d gauge theories by the Alday-Gaiotto-Tachikawa (AGT) duality and the role of conformal blocks of those CFTs in the integrable systems. As a consequence, the equivalence of conformal blocks of rank two Toda and Novikov-Wess-Zumino-Witten (WZNW) theories on the torus with punctures is found.Comment: 37 pages, 10 figures, references added, figures modified, JHEP versio