The formation and evolution of binary stars are critical components of several fields in astronomy. The most numerous sources for gravitational wave observatories are inspiraling or merging compact binaries, while binary stars are present in nearly every electromagnetic survey regardless of the target population. Simulations of large binary populations serve to both predict and inform observations of electromagnetic and gravitational wave sources. Binary population synthesis is a tool that balances physical modeling with simulation speed to produce large binary populations on timescales of days. We present a community-developed binary population synthesis suite, COSMIC, which is designed to simulate compact-object binary populations and their progenitors. As a proof of concept, we simulate the Galactic population of compact binaries and their gravitational wave signals observable by the Laser Interferometer Space Antenna.

Critical probes of dark matter come from tests of its elastic scattering with nuclei. The results are typically assumed to be model independent, meaning that the form of the potential need not be specified and that the cross sections on different nuclear targets can be simply related to the cross section on nucleons. For pointlike spin-independent scattering, the assumed scaling relation is σ χA ∝ A 2 μ 2 A σ χN ∝ A 4 σ χN , where the A 2 comes from coherence and the μ 2 A ≃ A 2 m 2 N from kinematics for m χ ≫ m A. Here we calculate where model independence ends, i.e., where the cross section becomes so large that it violates its defining assumptions. We show that the assumed scaling relations generically fail for dark matter-nucleus cross sections σ χA ∼ 10 −32-10 −27 cm 2 , significantly below the geometric sizes of nuclei and well within the regime probed by underground detectors. Last, we show on theoretical grounds, and in light of existing limits on light mediators, that pointlike dark matter cannot have σ χN ≳ 10 −25 cm 2 , above which many claimed constraints originate from cosmology and astrophysics. The most viable way to have such large cross sections is composite dark matter, which introduces significant additional model dependence through the choice of form factor. All prior limits on dark matter with cross sections σ χN > 10 −32 cm 2 with m χ ≳ 1 GeV must therefore be reevaluated and reinterpreted.

Evidence for a low-frequency stochastic gravitational-wave background has recently been reported based on analyses of pulsar timing array data. The most likely source of such a background is a population of supermassive black hole binaries, the loudest of which may be individually detected in these data sets. Here we present the search for individual supermassive black hole binaries in the NANOGrav 15 yr data set. We introduce several new techniques, which enhance the efficiency and modeling accuracy of the analysis. The search uncovered weak evidence for two candidate signals, one with a gravitational-wave frequency of ∼4 nHz, and another at ∼170 nHz. The significance of the low-frequency candidate was greatly diminished when Hellings–Downs correlations were included in the background model. The high-frequency candidate was discounted due to the lack of a plausible host galaxy, the unlikely astrophysical prior odds of finding such a source, and since most of its support comes from a single pulsar with a commensurate binary period. Finding no compelling evidence for signals from individual binary systems, we place upper limits on the strain amplitude of gravitational waves emitted by such systems. At our most sensitive frequency of 6 nHz, we place a sky-averaged 95% upper limit of 8 × 10−15 on the strain amplitude. We also calculate an exclusion volume and a corresponding effective radius, within which we can rule out the presence of black hole binaries emitting at a given frequency.

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Analytical models for magnetospheric mass density, ρm, and average ion mass, M, were created from a database of ρm and electron density, ne, values from six spacecraft missions by making use of the Eureqa nonlinear genetic regression algorithm. All values of ρm were determined from Alfvén frequencies, and the values of ne were determined from plasma wave or spacecraft potential data. Models of varying complexity are listed. The most complex models appearing in this paper are capable of modeling ρm within a factor of 1.81, and M within a factor of 1.34 if ne is used as an input parameter, or within a factor of 1.45 if ne is not used. The most important parameters for modeling ρm are L, the solar EUV index F10.7, magnetic local time, MLT, the geomagnetic activity index Kp, and the solar wind dynamic pressure, Pdyn. The very simplest model for M depends on Kp. In more complex models for M including ne, the most important parameters are ne with L, F10.7, and Pdyn or Kp. In more complex models for M not including ne, the most important parameters are Kp, MLT, F10.7, L, and the auroral electrojet index, AE. Explanations for most of the dependencies are given. We also demonstrate the danger of calculating spatial dependence without taking account of different conditions sampled in different regions. Here we avoid that problem by using multivariant models.