Novel directed search strategy to detect continuous gravitational waves from neutron stars in low- and high-eccentricity binary systems

We describe a novel, very fast and robust, directed search incoherent method for periodic gravitational waves (GWs) from neutron stars in binary systems. As directed search, we assume the source sky position to be known with enough accuracy, but all other parameters are supposed to be unknown. We exploit the frequency-modulation due to source orbital motion to unveil the signal signature by commencing from a collection of time and frequency peaks. We validate our pipeline adding 131 artificial continuous GW signals from pulsars in binary systems to simulated detector Gaussian noise, characterized by a power spectral density Sh = 4x10^-24 Hz^-1/2 in the frequency interval [70, 200] Hz, which is overall commensurate with the advanced detector design sensitivities. The pipeline detected 128 signals, and the weakest signal injected and detected has a GW strain amplitude of ~10^-24, assuming one month of gapless data collected by a single advanced detector. We also provide sensitivity estimations, which show that, for a single- detector data covering one month of observation time, depending on the source orbital Doppler modulation, we can detect signals with an amplitude of ~7x10^-25. By using three detectors, and one year of data, we would easily gain more than a factor 3 in sensitivity, translating into being able to detect weaker signals. We also discuss the parameter estimate proficiency of our method, as well as computational budget, which is extremely cheap. In fact, sifting one month of single-detector data and 131 Hz-wide frequency range takes roughly 2.4 CPU hours. Due to the high computational speed, the current procedure can be readily applied in ally-sky schemes, sieving in parallel as many sky positions as permitted by the available computational power

A method to search for long duration gravitational wave transients from isolated neutron stars using the generalized FrequencyHough

We describe a method to detect gravitational waves lasting $O(hours-days)$ emitted by young, isolated neutron stars, such as those that could form after a supernova or a binary neutron star merger, using advanced LIGO/Virgo data. The method is based on a generalization of the FrequencyHough (FH), a pipeline that performs hierarchical searches for continuous gravitational waves by mapping points in the time/frequency plane of the detector to lines in the frequency/spindown plane of the source. We show that signals whose spindowns are related to their frequencies by a power law can be transformed to coordinates where the behavior of these signals is always linear, and can therefore be searched for by the FH. We estimate the sensitivity of our search across different braking indices, and describe the portion of the parameter space we could explore in a search using varying fast Fourier Transform (FFT) lengths.Comment: 15 figure

A Human-Robot Interaction Perspective on Assistive and Rehabilitation Robotics

Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human–robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions

A Study of Systematics on the Cosmological Inference of the Hubble Constant from Gravitational Wave Standard Sirens

Gravitational waves (GWs) from compact binary coalescences (CBCs) can constrain the cosmic expansion of the universe. In the absence of an associated electromagnetic counterpart, the spectral sirens method exploits the relation between the detector frame and the source frame masses to jointly infer the parameters of the mass distribution of black holes (BH) and the cosmic expansion parameter $H_0$. This technique relies on the choice of the parametrization for the source mass population of BHs observed in binary black holes merger (BBHs). Using astrophysically motivated BBH populations, we study the possible systematic effects affecting the inferred value for $H_0$ when using heuristic mass models like a broken power law, a power law plus peak and a multi-peak distributions. We find that with 2000 detected GW mergers, the resulting $H_0$ obtained with a spectral sirens analysis can be biased up to $3\sigma$. The main sources of this bias come from the failure of the heuristic mass models used so far to account for a possible redshift evolution of the mass distribution and from their inability to model unexpected mass features. We conclude that future dark siren GW cosmology analyses should make use of source mass models able to account for redshift evolution and capable to adjust to unforeseen mass features.Comment: 21 pages, 14 figure

RICO-MR: An Open-Source Architecture for Robot Intent Communication through Mixed Reality

This article presents an open-source architecture for conveying robots' intentions to human teammates using Mixed Reality and Head-Mounted Displays. The architecture has been developed focusing on its modularity and re-usability aspects. Both binaries and source code are available, enabling researchers and companies to adopt the proposed architecture as a standalone solution or to integrate it in more comprehensive implementations. Due to its scalability, the proposed architecture can be easily employed to develop shared Mixed Reality experiences involving multiple robots and human teammates in complex collaborative scenarios.Comment: 6 pages, 3 figures, accepted for publication in the proceedings of the 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN

Understanding the progenitor formation galaxies of merging binary black holes

With nearly a hundred gravitational wave detections, the origin of black hole mergers has become a key question. Here, we focus on understanding the typical galactic environment in which binary black hole mergers arise. To this end, we synthesize progenitors of binary black hole mergers as a function of the redshift of progenitor formation, present-day formation galaxy mass, and progenitor stellar metallicity for $240$ star formation and binary evolution models. We provide guidelines to infer the formation galaxy properties and time of formation, highlighting the interplay between the star formation rate and the efficiency of forming merging binary black holes from binary stars, both of which strongly depend on metallicity. We find that across models, over 50% of BBH mergers have a progenitor metallicity of a few tenths of Solar metallicity, however, inferring formation galaxy properties strongly depends on both the binary evolution model and global metallicity evolution. The numerous, low-mass black holes ($\mathrm{\lesssim 15\,M_{\odot}}$) trace the bulk of the star formation in galaxies heavier than the Milky Way ($M_\mathrm{Gal}$ $\mathrm{\gtrsim 10^{10.5}\,M_{\odot}}$). In contrast, heavier BBH mergers typically stem from larger black holes forming in lower metallicity dwarf galaxies ($M_\mathrm{Gal}$ $\mathrm{\lesssim 10^{9}\,M_{\odot}}$). We find that the progenitors of detectable binary black holes tend to arise from dwarf galaxies at a lower formation redshift ($\lesssim \, 1$). We also produce a posterior probability of the progenitor environment for any detected gravitational wave signal. For the massive GW150914 merger, we show that it likely came from a very low metallicity ($Z$ $\mathrm{\lesssim}\,0.025\,\mathrm{Z_{\odot}}$) environment.Comment: 17 pages, 15 figures, 1 table, Accpeted for publication by MNRA

Establishing the significance of continuous gravitational-wave detections from known pulsars

We present a method for assigning a statistical significance to detection candidates in targeted searches for continuous gravitational waves from known pulsars, without assuming the detector noise is Gaussian and stationary. We take advantage of the expected Doppler phase modulation of the signal induced by Earth’s orbital motion, as well as the amplitude modulation induced by Earth’s spin, to effectively blind the search to real astrophysical signals from a given location in the sky. We use this “sky shifting” to produce a large number of noise-only data realizations to empirically estimate the background of a search and assign detection significances, in a similar fashion to the use of time slides in searches for compact binaries. We demonstrate the potential of this approach by means of simulated signals, as well as hardware injections into real detector data. In a study of simulated signals in non-Gaussian noise, we find that our method outperforms another common strategy for evaluating detection significance. We thus demonstrate that this and similar techniques have the potential to enable a first confident detection of continuous gravitational waves

Kinesthetic Teaching in Robotics: a Mixed Reality Approach

As collaborative robots become more common in manufacturing scenarios and adopted in hybrid human-robot teams, we should develop new interaction and communication strategies to ensure smooth collaboration between agents. In this paper, we propose a novel communicative interface that uses Mixed Reality as a medium to perform Kinesthetic Teaching (KT) on any robotic platform. We evaluate our proposed approach in a user study involving multiple subjects and two different robots, comparing traditional physical KT with holographic-based KT through user experience questionnaires and task-related metrics.This paper has been published in the Proceedings of the 2024 IEEE International Conference on Human and Robot Interactive Communication (RO-MAN), Pasadena, CA, USA, August 202

Investigating Mixed Reality for Communication Between Humans and Mobile Manipulators

This article investigates mixed reality (MR) to enhance human-robot collaboration (HRC). The proposed solution adopts MR as a communication layer to convey a mobile manipulator\u27s intentions and upcoming actions to the humans with whom it interacts, thus improving their collaboration. A user study involving 20 participants demonstrated the effectiveness of this MR-focused approach in facilitating collaborative tasks, with a positive effect on overall collaboration performances and human satisfaction.This paper has been published in the Proceedings of the 2024 IEEE International Conference on Human and Robot Interactive Communication (RO-MAN), Pasadena, CA, USA, August 202

ICAROGW: A python package for inference of astrophysical population properties of noisy, heterogeneous and incomplete observations

We present icarogw 2.0, a pure CPU/GPU python code developed to infer astrophysical and cosmological population properties of noisy, heterogeneous, and incomplete observations. icarogw 2.0 is mainly developed for compact binary coalescence (CBC) population inference with gravitational wave (GW) observations. The code contains several models for masses, spins, and redshift of CBC distributions, and is able to infer population distributions as well as the cosmological parameters and possible general relativity deviations at cosmological scales. We present the theoretical and computational foundations of icarogw, and we describe how the code can be employed for population and cosmological inference using (i) only GWs, (ii) GWs and galaxy surveys and (iii) GWs with electromagnetic counterparts. Although icarogw 2.0 has been developed for GW science, we also describe how the code can be used for any physical and astrophysical problem involving observations from noisy data in the presence of selection biases. With this paper, we also release tutorials on Zenodo.Comment: 33 pages, code available at (https://github.com/simone-mastrogiovanni/icarogw), tutorials available at (https://zenodo.org/record/7846415#.ZG0l0NJBxQo