On the Origin of Gamma-Ray Flares from Bright Fermi Blazars

The origin of γ-ray flares observed from blazars is one of the major mysteries in jet physics. We have attempted to address this problem following a novel spectral energy distribution (SED) fitting technique that explored the flaring patterns identified in the broadband SEDs of two γ-ray bright blazars, 3C 279 (z = 0.54) and 3C 454.3 (z = 0.86), using near-simultaneous radio-to-γ-ray observations. For both sources, the γ-ray flux strongly correlates with the separation of the SED peaks and the Compton dominance. We propose that spectral hardening of the radiating electron population and/or enhancement of the Doppler factor can naturally explain these observations. In both cases, magnetic reconnection may play a pivotal role in powering the luminous γ-ray flares.

Measuring fundamental jet properties with multi-wavelength fast timing of the black hole X-ray binary MAXI J1820+070

We present multi-wavelength fast timing observations of the black hole X-ray binary MAXI J1820+070 (ASASSN-18ey), taken with the Karl G. Jansky Very Large Array (VLA), Atacama Large Millimeter/Sub-Millimeter Array (ALMA), Very Large Telescope (VLT), New Technology Telescope (NTT), Neutron Star Interior Composition Explorer (NICER), and XMM-Newton. Our data set simultaneously samples ten different electromagnetic bands (radio – X-ray) over a 7-hour period during the hard state of the 2018–2019 outburst. The emission we observe is highly variable, displaying multiple rapid flaring episodes. To characterize the variability properties in our data, we implemented a combination of cross-correlation and Fourier analyses. We find that the emission is highly correlated between different bands, measuring time-lags ranging from hundreds of milliseconds between the X-ray/optical bands to minutes between the radio/sub-mm bands. Our Fourier analysis also revealed, for the first time in a black hole X-ray binary, an evolving power spectral shape with electromagnetic frequency. Through modelling these variability properties, we find that MAXI J1820+070 launches a highly relativistic ($\Gamma =6.81^{+1.06}_{-1.15}$) and confined ($\phi =0.45^{+0.13}_{-0.11}$ deg) jet, which is carrying a significant amount of power away from the system (equivalent to ∼0.6 L1 − 100keV). We additionally place constraints on the jet composition and magnetic field strength in the innermost jet base region. Overall, this work demonstrates that time-domain analysis is a powerful diagnostic tool for probing jet physics, where we can accurately measure jet properties with time-domain measurements alone.

First constraints on the AGN X-ray luminosity function at z ~ 6 from an eROSITA-detected quasar

Context. High-redshift quasars signpost the early accretion history of the Universe. The penetrating nature of X-rays enables a less absorption-biased census of the population of these luminous and persistent sources compared to optical/near-infrared colour selection. The ongoing SRG/eROSITA X-ray all-sky survey offers a unique opportunity to uncover the bright end of the high-z quasar population and probe new regions of colour parameter space. Aims. We searched for high-z quasars within the X-ray source population detected in the contiguous ~140 deg2 field observed by eROSITA during the performance verification phase. With the purpose of demonstrating the unique survey science capabilities of eROSITA, this field was observed at the depth of the final all-sky survey. The blind X-ray selection of high-redshift sources in a large contiguous, near-uniform survey with a well-understood selection function can be directly translated into constraints on the X-ray luminosity function (XLF), which encodes the luminosity-dependent evolution of accretion through cosmic time. Methods. We collected the available spectroscopic information in the eFEDS field, including the sample of all currently known optically selected z > 5.5 quasars and cross-matched secure Legacy DR8 counterparts of eROSITA-detected X-ray point-like sources with this spectroscopic sample. Results. We report the X-ray detection of eFEDSU J083644.0+005459, an eROSITA source securely matched to the well-known quasar SDSS J083643.85+005453.3 (z = 5.81). The soft X-ray flux of the source derived from eROSITA is consistent with previous Chandra observations. The detection of SDSS J083643.85+005453.3 allows us to place the first constraints on the XLF at z > 5.5 based on a secure spectroscopic redshift. Compared to extrapolations from lower-redshift observations, this favours a relatively flat slope for the XLF at z ~ 6 beyond L*, the knee in the luminosity function. In addition, we report the detection of the quasar with LOFAR at 145 MHz and ASKAP at 888 MHz. The reported flux densities confirm a spectral flattening at lower frequencies in the emission of the radio core, indicating that SDSS J083643.85+005453.3 could be a (sub-) gigahertz peaked spectrum source. The inferred spectral shape and the parsec-scale radio morphology of SDSS J083643.85+005453.3 indicate that it is in an early stage of its evolution into a large-scale radio source or confined in a dense environment. We find no indications for a strong jet contribution to the X-ray emission of the quasar, which is therefore likely to be linked to accretion processes. Conclusions. Our results indicate that the population of X-ray luminous AGNs at high redshift may be larger than previously thought. From our XLF constraints, we make the conservative prediction that eROSITA will detect ~90 X-ray luminous AGNs at redshifts 5.7 < z < 6.4 in the full-sky survey (De+RU). While subject to different jet physics, both high-redshift quasars detected by eROSITA so far are radio-loud; a hint at the great potential of combined X-ray and radio surveys for the search of luminous high-redshift quasars.

Tag N’ Train: a technique to train improved classifiers on unlabeled data

There has been substantial progress in applying machine learning techniques to classification problems in collider and jet physics. But as these techniques grow in sophistication, they are becoming more sensitive to subtle features of jets that may not be well modeled in simulation. Therefore, relying on simulations for training will lead to sub-optimal performance in data, but the lack of true class labels makes it difficult to train on real data. To address this challenge we introduce a new approach, called Tag N’ Train (TNT), that can be applied to unlabeled data that has two distinct sub-objects. The technique uses a weak classifier for one of the objects to tag signal-rich and background-rich samples. These samples are then used to train a stronger classifier for the other object. We demonstrate the power of this method by applying it to a dijet resonance search. By starting with autoencoders trained directly on data as the weak classifiers, we use TNT to train substantially improved classifiers. We show that Tag N’ Train can be a powerful tool in model-agnostic searches and discuss other potential applications.

Reframing Jet Physics with New Computational Methods

We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element – parton shower matching for large jet multiplicity, and efficient event generation of jets in complex, signal-like regions of phase space. We also introduce Ginkgo, a simplified, generative model for jets, that facilitates research into these tasks with techniques from statistics, machine learning, and combinatorial optimization. We also review some of the recent research in this direction that has been enabled with Ginkgo. We show how probabilistic programming can be used to efficiently sample the showering process, how a novel trellis algorithm can be used to efficiently marginalize over the enormous number of clustering histories for the same observed particles, and how the dynamic programming and reinforcement learning can be used to find the maximum likelihood clusterinng in this enormous search space. This work builds bridges with work in hierarchical clustering, statistics, combinatorial optmization, and reinforcement learning.

Eclipses of jets and discs of X-ray binaries as a powerful tool for understanding jet physics and binary parameters

ABSTRACT We calculate the expected effects on the spectral energy distributions and light curves in X-ray binary jets from eclipses by the donor stars. Jets will be eclipsed for all inclination angles, with just the height along the jet where the eclipse takes place being set by the orbital parameters. Typically, eclipses will lead to 5–10 per cent reductions in the jet emission over a range of a factor of few in wavelength with a periodic modulation. In ideal systems with high inclination angles, relatively even mass ratios, and modest jet speeds, the eclipses may be deeper. We discuss how eclipses can be used to measure binary system parameters, as well as the height of the bases of the jets. We also discuss how, with data sets that will likely require future facilities, more detailed tests of models of jet physics could be made by establishing deviations from the standard recipes for compact conical flat spectrum jets and by determining the ingress and egress durations of the eclipses and measuring the transverse size of the jets. We provide representative calculations of expectations for different classes of systems, demonstrating that the most promising target for showing this effect in the radio band is the longer period ‘atoll’-class neutron star X-ray binaries, while in the optical and infrared bands, the best candidates are likely to be the most edge-on black hole X-ray binaries. We also discuss the effects of the outer accretion disc eclipsing the inner jet.