Collimated outflows from accreting white dwarfs have an important role to play in the study of astrophysical jets. Observationally, collimated outflows are associated with systems in which material is accreted though a disk. Theoretically, accretion disks provide the foundation for many jet models. Perhaps the best-understood of all accretion disks are those in cataclysmic variable stars (CVs). Since the disks in other accreting white-dwarf (WD) binaries are probably similar to CV disks (at least to the extent that one does not expect complications such as, for example, advection-dominated flows), with WD accretors one has the advantage of a relatively good grasp of the region from which the outflows are likely to originate. We briefly compare the properties of the three main classes of WD accretors, two of which have members that produce jets, and review the cases of three specific jet-producing WD systems.

J. L. Sokoloski S. J. Kenyon C. Brocksopp C. R. Kaiser E. M. Kellogg

The fiber g-ratio is the ratio of the inner to the outer diameter of the myelin sheath of a myelinated axon. It has a limited dynamic range in healthy white matter, as it is optimized for speed of signal conduction, cellular energetics, and spatial constraints. In vivo imaging of the g-ratio in health and disease would greatly increase our knowledge of the nervous system and our ability to diagnose, monitor, and treat disease. MRI based g-ratio imaging was first conceived in 2011, and expanded to be feasible in full brain with preliminary results in 2013. This manuscript reviews the growing g-ratio imaging literature and speculates on future applications. It details the methodology for imaging the g-ratio with MRI, and describes the known pitfalls and challenges in doing so.

Jennifer S. W. Campbell Ilana R. Leppert Mathieu Boudreau Sridar Narayanan Tanguy Duval Julien Cohen-Adad G. Bruce Pike Nikola Stikov

We summarize the scientific potential of high contrast optical space imaging for studies of extrasolar planets, debris disks, and planet formation. The unique scientific capabilities offered by a 2-m class optical telescope, the technical requirements to achieve 10^-9 contrast, and the programmatic means needed to advance such a mission are discussed.

Karl Stapelfeldt John Trauger Weslay Traub Mark Clampin William Oegerle Jennifer Wiseman Olivier Guyon

We present Suzaku X-ray observations of the recurrent nova T CrB in quiescence. T CrB is the first recurrent nova to be detected in the hard-X-ray band (E ~ 40.0 keV) during quiescence. The X-ray spectrum is consistent with cooling-flow emission emanating from an optically thin region in the boundary layer of an accretion disk around the white dwarf. The detection of strong stochastic flux variations in the light curve supports the interpretation of the hard X-ray emission as emanating from a boundary layer.

Gerardo J. M. Luna Jennifer L. Sokoloski Koji Mukai

The 2020s will be the most data-rich decade of astronomy in history. As the scale and complexity of our surveys increase, the problem of scheduling becomes more critical. We must develop high-quality scheduling approaches, implement them as open-source software, and begin linking the typically separate stages of observation and data analysis.

Eric C. Bellm Eric B. Ford Aaron Tohuvavohu Michael W. Coughlin Brett Morris Bryan Miller Jennifer Sobeck Reed Riddle Chuanfei Dong Peter Yoachim

Natural languages are believed to be (mildly) context-sensitive. Despite underpinning remarkably capable large language models, transformers are unable to model many context-free language tasks. In an attempt to address this limitation in the modeling power of transformer-based language models, we propose augmenting them with a differentiable, stack-based attention mechanism. Our stack-based attention mechanism can be incorporated into any transformer-based language model and adds a level of interpretability to the model. We show that the addition of our stack-based attention mechanism enables the transformer to model some, but not all, deterministic context-free languages.

Jiaoda Li Jennifer C. White Mrinmaya Sachan Ryan Cotterell

Since language models are used to model a wide variety of languages, it is natural to ask whether the neural architectures used for the task have inductive biases towards modeling particular types of languages. Investigation of these biases has proved complicated due to the many variables that appear in the experimental setup. Languages vary in many typological dimensions, and it is difficult to single out one or two to investigate without the others acting as confounders. We propose a novel method for investigating the inductive biases of language models using artificial languages. These languages are constructed to allow us to create parallel corpora across languages that differ only in the typological feature being investigated, such as word order. We then use them to train and test language models. This constitutes a fully controlled causal framework, and demonstrates how grammar engineering can serve as a useful tool for analyzing neural models. Using this method, we find that commonly used neural architectures exhibit different inductive biases: LSTMs display little preference with respect to word ordering, while transformers display a clear preference for some orderings over others. Further, we find that neither the inductive bias of the LSTM nor that of the transformer appears to reflect any tendencies that we see in attested natural languages.

Jennifer C. White Ryan Cotterell

Interacting binaries containing white dwarfs can lead to a variety of outcomes that range from powerful thermonuclear explosions, which are important in the chemical evolution of galaxies and as cosmological distance estimators, to strong sources of low frequency gravitational wave radiation, which makes them ideal calibrators for the gravitational low-frequency wave detector LISA mission. However, current theoretical evolution models still fail to explain the observed properties of the known populations of white dwarfs in both interacting and detached binaries. Major limitations are that the existing population models have generally been developed to explain the properties of sub-samples of these systems, occupying small volumes of the vast parameter space, and that the observed samples are severely biased. The overarching goal for the next decade is to assemble a large and homogeneous sample of white dwarf binaries that spans the entire range of evolutionary states, to obtain precise measurements of their physical properties, and to further develop the theory to satisfactorily reproduce the properties of the entire population. While ongoing and future all-sky high- and low-resolution optical spectroscopic surveys allow us to enlarge the sample of these systems, high-resolution ultraviolet spectroscopy is absolutely essential for the characterization of the white dwarfs in these binaries. The Hubble Space Telescope is currently the only facility that provides ultraviolet spectroscopy, and with its foreseeable demise, planning the next ultraviolet mission is of utmost urgency.

Odette Toloza Elme Breed Domitilla De Martino Jeremy Drake Alessandro Ederoclite Boris Gansicke Matthew Green Jennifer Johnson Christian Knigge Juna Kollmeier Thomas Kupfer Knox Long Thomas Marsh Anna Francesca Pala Steven Parsons Tom Prince Roberto Raddi Alberto Rebassa-Mansergas Pablo Rodriguez-Gil Simone Scaringi Linda Schmidtobreick Matthias Schreiber Ken Shen Danny Steeghs Paula Szkody Claus Tappert Silvia Toonen Axel Schwope Dean Townsley Monica Zorotovic

Most known white dwarfs in multiple systems with main sequence stars have been discovered with M-type companions, because the white dwarf causes detectable UV excess and bluer colors than expected from a single M star. Surveys have shown that the number of white dwarfs in Sirius-like systems within 100 pc of the Sun is lower than expected, suggesting that white dwarfs are being missed in the glare of their main sequence companions. In this work we have leveraged the angular resolution and high-contrast capabilities, as well as optimization for visible wavelengths, of the extreme adaptive optics instrument MagAO-X to detect new white dwarf companions to AFGK stars. We present the first results of our survey with the extreme AO instrument MagAO-X, called the Pup Search, of 18 targets with seven new candidate companions, five of which are confirmed to be white dwarfs. We discuss the new detections in the context of previous surveys and other detection metric sensitivities and show that we are sensitive to a region not probed by other surveys. Finally we discuss the future of the Pup Search in light of developing technologies.

Logan A. Pearce Jared R. Males Sebastiaan Y. Haffert Laird M. Close Joseph D. Long Eden A. McEwen Joshua Liberman Maggie Y. Kautz Jay K. Kueny Alycia J. Weinberger Jialin Li Elena Tonucci Katie Twitchell Avalon McLeod Warren B. Foster Olivier Guyon Alexander Hedglen Kyle Van Gorkom Jennifer Lumbres Lauren Schatz Victor Gasho Katie M. Morzinski Phil M. Hinz

We report on the analysis of selected single source data sets from the first round of the Mock LISA Data Challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pipeline consisting of a grid-based coherent pre-processing unit for signal detection, and an automatic Markov Chain Monte Carlo post-processing unit for signal evaluation. We demonstrate that signal detection with our coherent approach is secure and accurate, and is increased in accuracy and supplemented with additional information on the signal parameters by our Markov Chain Monte Carlo approach. We also demonstrate that the Markov Chain Monte Carlo routine is additionally able to determine accurately the noise level in the frequency window of interest.

Alexander Stroeer John Veitch Christian Roever Ed Bloomer James Clark Nelson Christensen Martin Hendry Chris Messenger Renate Meyer Matthew Pitkin Jennifer Toher Richard Umstaetter Alberto Vecchio Graham Woan