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Jacob Pilawa

Publications and source records attributed to Jacob Pilawa.

7 recordsLinked to original sources

Prospects of resolving and localising individual supermassive black hole binaries with pulsar timing arrays: the host ranking challenge

Pulsar Timing Arrays (PTAs) are soon expected to detect individually resolved supermassive black hole (SMBH) binaries, opening the possibility for multi-messenger discoveries. The biggest challenge will be to pinpoint the host galaxy in a large localisation area. We simulate realistic binary populations consistent with the gravitational wave (GW) background, projecting the PTA sensitivity for the next 0-10 years. We inject the loudest binary on top of the background and use one of the standard detection pipelines to constrain its properties. We cross-match the localisation areas with comprehensive all-sky galaxy catalogues and estimate the number of candidate hosts in the localisation area assessing, for the first time, the number of missing galaxies due to incomplete coverage. We develop a ranking system that excludes galaxies with properties inconsistent with the GW posteriors, and prioritizes the remaining galaxies for follow-up observations. We find a $\approx$21, $\approx$38 and $\approx$51 percent probability of resolving a binary in the next 0, 5 and 10 years, respectively, reduced to 0.3, 3.8 and 14.1 percent if we require potentially well-constrained localisation areas. The localisation areas span hundreds of square degrees, but shrink significantly with the addition of more data. They contain on average $\approx$190,000 early type galaxies and $\approx$40,000 active galactic nuclei, with $\approx$25,000 missing candidate hosts. Our ranking method can exclude about half of the potential hosts and efficiently rank those remaining when the galaxy catalogue provides SMBH masses and redshifts, but becomes more inefficient when we rely on apparent magnitudes.

astro-ph.GA

The MASSIVE Survey. XX. A Triaxial Stellar Dynamical Measurement of the Supermassive Black Hole Mass and Intrinsic Galaxy Shape of Giant Radio Galaxy NGC 315

We present a new dynamical measurement of the supermassive black hole mass and intrinsic shape of the stellar halo of the massive radio galaxy NGC 315 as part of the MASSIVE survey. High signal-to-noise ratio spectra from integral-field spectrographs at the Gemini and McDonald Observatories provide stellar kinematic measurements in $304$ spatial bins from the central ${\sim}0.3''$ out to $30''$. Using ${\sim} 2300$ kinematic constraints, we perform triaxial stellar orbit modeling with the TriOS code and search over ${\sim}$15,000 galaxy models with a Bayesian scheme to simultaneously measure six mass and intrinsic shape parameters. NGC 315 is triaxial and highly prolate, with middle-to-long and short-to-long axis ratios of $p=0.854$ and $q=0.833$ and a triaxiality parameter of $T=0.89$. The black hole mass inferred from our stellar kinematics is $M_\mathrm{BH} = \left(3.0 {\pm} 0.3\right) {\times} 10^{9}\ M_\odot$, which is higher than $M_\mathrm{BH}=(1.96^{+0.30}_{-0.13}) {\times} 10^{9} M_\odot$ inferred from CO kinematics (scaled to our distance). When the seven galaxies with $M_\mathrm{BH}$ measurements from both stellar and CO kinematics are compared, we find an intrinsic scatter of 0.28 dex in $M_\mathrm{BH}$ from the two tracers and do not detect statistically significant biases between the two methods in the current data. The implied black hole shadow size (${\approx} 4.7\, \mu{\rm as}$) and the relatively high millimeter flux of NGC 315 makes this galaxy a prime candidate for future horizon-size imaging studies.

astro-ph.GA

TriOS Schwarzschild Orbit Modeling: Robustness of Parameter Inference for Masses and Shapes of Triaxial Galaxies with Supermassive Black Holes

Evidence for the majority of the supermassive black holes in the local universe has been obtained dynamically from stellar motions with the Schwarzschild orbit superposition method. However, there have been only a handful of studies using simulated data to examine the ability of this method to reliably recover known input black hole masses $M_{BH}$ and other galaxy parameters. Here we conduct a comprehensive assessment of the reliability of the triaxial Schwarzschild method at $\textit{simultaneously}$ determining $M_{BH}$, stellar mass-to-light ratio $M^{*}/L$, dark matter mass, and three intrinsic triaxial shape parameters of simulated galaxies. For each of 25 rounds of mock observations using simulated stellar kinematics and the $\texttt{TriOS}$ code, we derive best-fitting parameters and confidence intervals after a full search in the 6D parameter space with our likelihood-based model inference scheme. The two key mass parameters, $M_{BH}$ and $M^{*}/L$, are recovered within the 68% confidence interval, and other parameters are recovered between 68% and 95% confidence intervals. The spatially varying velocity anisotropy of the stellar orbits is also well recovered. We explore whether the goodness-of-fit measure used for galaxy model selection in our pipeline is biased by variable complexity across the 6D parameter space. In our tests, adding a penalty term to the likelihood measure either makes little difference, or worsens the recovery in some cases.

astro-ph.GA

Probing below the neutrino floor with the first generation of stars

We show that the mere observation of the first stars (Pop III stars) in the universe can be used to place tight constraints on the strength of the interaction between dark matter and regular, baryonic matter. We apply this technique to a candidate Pop III stellar complex discovered with the Hubble Space Telescope at $z \sim 7$ and find bounds that are competitive with, or even stronger than, current direct detection experiments, such as XENON1T, for dark matter particles with mass ($m_X$) larger than about $100$ GeV. We also show that the discovery of sufficiently massive Pop III stars could be used to bypass the main limitations of direct detection experiments: the neutrino background to which they will be soon sensitive.

astro-ph.CO

Constraining Dark Matter properties with the first generation of stars

Dark Matter (DM) can be trapped by the gravitational field of any star, since collisions with nuclei in dense environments can slow down the DM particle below the escape velocity ($v_{esc}$) at the surface of the star. If captured, the DM particles can self-annihilate, and, therefore, provide a new source of energy for the star. We investigate this phenomenon for capture of DM particles by the first generation of stars [Population III (Pop III) stars], by using the multiscatter capture formalism. Pop III stars are particularly good DM captors, since they form in DM-rich environments, at the center of$~\sim 10^6 M_\odot$ DM minihalos, at redshifts $z\sim 15$. Assuming a DM-proton scattering cross section ($\sigma)$ at the current deepest exclusion limits provided by the XENON1T experiment, we find that captured DM annihilations at the core of Pop III stars can lead, via the Eddington limit, to upper bounds in stellar masses that can be as low as a few $M_\odot$ if the ambient DM density ($\rho_X$) at the location of the Pop III star is sufficiently high. Conversely, when Pop III stars are identified, one can use their observed mass ($M_\star$) to place bounds on $\rho_X\sigma$. Using adiabatic contraction to estimate the ambient DM density in the environment surrounding Pop III stars, we place projected upper limits on $\sigma$, for $M_\star$ in the $100-1000~M_\odot$ range, and find bounds that are competitive with, or deeper than, those provided by the most sensitive current direct detection experiments for both spin independent and spin dependent interactions, for a wide range of DM masses. Most intriguingly, we find that Pop III stars with mass $M_\star \gtrsim 300 M_\odot$ could be used to probe the SD proton-DM cross section below the "neutrino floor," i.e. the region of parameter space where DM direct detection experiments will soon become overwhelmed by neutrino backgrounds.

astro-ph.CO

Comment on "Multiscatter stellar capture of dark matter"

Bramante, Delgado, and Martin [Phys. Rev. D96, 063002(2017)., hereafter BDM17] extended the analytical formalism of dark matter (DM) capture in a very important way, which allows, in principle, the use of compact astrophysical objects, such as neutron stars (NS), as dark matter detectors. In this comment, we point out the existence of a region in the dark matter neutron scattering cross section $(σ_{nX})$ vs. dark matter mass $(m_{X})$ where the constraining power of this method is lost. This corresponds to a maximal temperature ($T_{crit}$) the NS has to have, in order to serve as a dark matter detector. In addition, we point out several typos and errors in BDM17 that do not affect drastically their conclusions. Moreover, we provide semi-analytical approximations for the total capture rates of dark matter particle of arbitrary mass for various limiting regimes. Those analytical approximations are used to validate our numerical results.

astro-ph.CO

Classification of time-domain waveforms using a speckle-based optical reservoir computer

Reservoir computing is a recurrent machine learning framework that expands the dimensionality of a problem by mapping an input signal into a higher-dimension reservoir space that can capture and predict features of complex, non-linear temporal dynamics. Here, we report on a bulk optical demonstration of an analog reservoir computer using speckles generated by propagating a laser beam modulated with a spatial light modulator through a multimode waveguide. We demonstrate that the hardware can successfully perform a multivariate audio classification task performed using the Japanese vowel speakers public data set. We perform full wave optical calculations of this architecture implemented in a chip-scale platform using an SiO2 waveguide and demonstrate that it performs as well as a fully numerical implementation of reservoir computing. As all the optical components used in the experiment can be fabricated using a commercial photonic integrated circuit foundry, our result demonstrates a framework for building a scalable, chip-scale, reservoir computer capable of performing optical signal processing.

physics.optics