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Abstract Subparsec binary supermassive black holes (BSBHs) should be common from galaxy mergers, yet direct evidence has been elusive. We present Hubble Space Telescope (HST)/WFC3IR F160W imaging for a sample of eight candidate subparsec BSBHs at redshiftsz ∼ 0.1–0.5, as well as cross-comparison with a sample of ordinary quasars with archival HST/WFC3 IR F160W images. These eight candidate subparsec BSBHs were identified from multiepoch spectroscopic surveys of quasars (including both typical quasars and those with single-peaked velocity-offset broad lines), whose broad Hβlines are significantly offset (by ≳ a few hundred kilometers per second) from the systemic redshifts. We directly test the prediction that the host galaxies of BSBHs would have a higher fraction of disturbed morphologies and younger stellar bulges from recent interactions than those of control quasars. After careful subtraction of the central quasar light, our candidate BSBH hosts show a statistically undifferentiated distribution of host asymmetry, indicative of a similar fraction of recent mergers. While a significantly larger sample is needed to place this result on a much firmer statistical ground, it opens questions as to the timescale differences between galaxy merger and BSBH formation, or the efficacy of the radial-velocity-shift-based selection of subparsec BSBH candidates. 

Abstract This work identifies and characterizes magnetic structures, especially in terms of small‐scale magnetic flux ropes (SFRs), in the solar wind and magnetosheath across the Earth's bow shock. We investigate the differences between the properties of SFR structures in these regions immediately upstream and downstream of the bow shock by employing two data analysis methods: one based on wavelet transforms and the other based on the Grad‐Shafranov (GS) detection and reconstruction techniques. In situ magnetic field and plasma data from the Magnetospheric Multiscale and Time History of Events and Macroscale Interactions during Substorms missions are used to identify these coherent structures through the two approaches. We identify thousands of SFR event intervals with a range of variable duration over a total time period of 1,000 hr in each region. We report parameters associated with the SFRs such as scale size, duration, magnetic flux content, and magnetic helicity density, derived from primarily the GS‐based analysis results. These parameters are summarized through statistical analysis, and their changes across the bow shock are shown based on comparisons of their respective distributions. We find that in general, the distributions of various parameters follow power laws. The SFR structures seem to be compressed in the magnetosheath, as compared with their counterparts in the solar wind. A significant rotation in the ‐axis defining the orientation of the structures is also seen across the bow shock. We also discuss the implications for the elongation of the SFRs in the magnetosheath along one spatial dimension. 

Probabilistic spin logic (PSL) has recently been proposed as a novel computing paradigm that leverages random thermal fluctuations of interacting bodies in a system rather than deterministic switching of binary bits. A PSL circuit is an interconnected network of thermally unstable units called probabilistic bits (p-bits), whose output randomly fluctuates between bits 0 and 1. While the fluctuations generated by p-bits are thermally driven, and therefore, inherently stochastic, the output probability is tunable with an external source. Therefore, information is encoded through probabilities of various configuration of states in the network. Recent studies have shown that these systems can efficiently solve various types of combinatorial optimization problems and Bayesian inference problems that modern computers are unfit for. Previous experimental studies have demonstrated that a single magnetic tunnel junctions (MTJ) designed to be thermally unstable can operate tunable random number generator making it an ideal hardware solution for p-bits. Most proposals for designing an MTJ to operate as a p-bit involve patterning the MTJ as a circular nano-pillar to make the device thermally unstable and then use spin transfer torque (STT) as a tuning mechanism. However, the practical realization of such devices is very challenging since the fluctuation rate of these devices are very sensitive to any device variations or defects caused during fabrication. Despite this challenge, MTJs are still the most promising hardware solution for p-bits because MTJs are very unique in that they can be tuned by multiple other mechanisms such spin orbit torque, magneto-electric coupling, and voltage-controlled exchange coupling. Furthermore, multiple forces can be used simultaneously to drive stochastic switching signals in MTJs. This means there are a large number of methods to tune, or termed as bias, MTJs that can be implemented in p-bit circuits that can alleviate the current challenges of conventional STT driven p-bits. This article serves as a review of all of the different methods that have been proposed to drive random fluctuations in MTJs to operate as a probabilistic bit. Not only will we review the single-biasing mechanisms, but we will also review all the proposed dual-biasing methods, where two independent mechanisms are employed simultaneously. These dual-biasing methods have been shown to have certain advantages such as alleviating the negative effects of device variations and some biasing combinations have a unique capability called ‘two-degrees of tunability’, which increases the information capacity in the signals generated. 

Abstract Redox, a native modality in biology involving the flow of electrons, energy, and information, is used for energy‐harvesting, biosynthesis, immune‐defense, and signaling. Because electrons (in contrast to protons) are not soluble in the medium, electron‐flow through the redox modality occurs through redox reactions that are sometimes organized into pathways and networks (e.g., redox interactomes). Redox is also accessible to electrochemistry, which enables electrodes to receive and transmit electrons to exchange energy and information with biology. In this Perspective, efforts to develop electrochemistry as a tool for redox‐based bio‐information processing: to interconvert redox‐based molecular attributes into interpretable electronic signals, are described. Using a series of Case Studies, how the information‐content of the measurements can be enriched using: diffusible mediators; tuned electrical input sequences; and cross‐modal measurements (e.g., electrical plus spectral), is shown. Also, theory‐guided feature engineering approaches to compress the information in the electronic signals into quantitative metrics (i.e., features) that can serve as correlating variables for pattern recognition by data‐driven analysis are described. Finally, how redox provides a modality for electrogenetic actuation is illustrated. It is suggested that electrochemistry's capabilities to provide real‐time, low‐cost, and high‐content data in an electronic format allow the feedback‐control needed for autonomous learning and deployable sensing/actuation. 

This paper addresses a gap in the AI governance literature in understanding collaboration between national governments and tribal nations in governing AI systems for emergency management. This conceptual work develops and presents a governance design framework for accountable AI systems to fill the knowledge gap by drawing from the fields of public administration, information systems, indigenous studies, and emergency management. This framework situates the governance framework in a cross-sovereignty historical, legal, and policy contexts. It captures the multi-level features and embeddedness of governance structures, including the levels of collaborative governance structure, software system governance rules, and technical software system design. The focal governance dynamics involve the collaborative process in the bi-directional relationship between governance rules and technical design for accountability and the feedback loop. The framework highlights the importance of multi-level and process considerations in designing accountable AI systems. Productive future research avenues include empirical investigation and resulting refinement of the framework and analytical rigor employing institutional grammar. 

Abstract High spatial and spectral resolution observations are essential for identifying subarcsecond dual and lensed quasars and confirming their redshifts. We present Gemini/Gemini Multi-Object Spectrograph and Hubble Space Telescope/STIS optical spectra for 27 dual quasar candidates selected based on their variability-induced astrometric noise or double detections in Gaia (the Varstrometry for Off-nucleus and Dual sub-Kpc AGN (VODKA) project). From this follow-up, we spectroscopically identify 11 star superpositions and seven dual/lensed quasars. Among the remaining targets, two are likely dual/lensed quasars based on additional radio imaging, while the rest are quasars with unknown companions. Without prior photometric or spectroscopic selection, we find the star contamination rate to be 41%–67%, while the dual/lensed quasar fraction is ≳26% in the follow-up VODKA sample. However, when combined with existing unresolved spectra and spatially resolved two-band color cuts, the dual/lensed quasar fraction can be increased to ≳67%. Our study highlights the need for high-quality spectral data, including a signal-to-noise ratio of at least 20, spatial resolution that is at least twice finer than the source separation, and a spectral resolution ofR ≳ 1000, in order to separate close sources, exclude stellar superpositions, and reliably identify dual quasars. 

Abstract Dual active galactic nuclei (AGNs), a phase in some galaxy mergers during which both central supermassive black holes (SMBHs) are active, are expected to be a key observable stage leading up to SMBH mergers. Constraining the population of dual AGNs in both the nearby and high-zUniverse has proven to be elusive until very recently. We present a multiwavelength follow-up campaign to confirm the nature of a sample of 20 candidate dual AGNs at cosmic noon (z ∼ 2) from the VODKA sample. Through a combination of Hubble Space Telescope and Very Large Array imaging, we refute the possibility of gravitational lensing in all but one target. We find evidence of dual AGNs in three systems, while seven exhibit a single AGN in galaxy pairs, through either strong radio emission or ancillary emission-line data. The remaining systems are confirmed as either quasar−star superpositions (seven) or nonlensed pairs (two) that require further investigations to establish AGN activity. Among the systems with radio detections, we find a variety of radio spectral slopes and UV/optical colors suggesting that our sample contains a range of AGN properties, from obscured radio-quiet objects to those with powerful synchrotron-emitting jets. This study presents one of the largest dedicated multiwavelength follow-up campaigns to date searching for dual AGNs at high redshift. We confirm several of the highest-zsystems at small physical separations, thus representing some of the most evolved dual-AGN systems at the epoch of peak quasar activity known to date.