Fast Parameter Inference on Pulsar Timing Arrays with Normalizing Flows.

Pulsar timing arrays perform Bayesian posterior inference with expensive Markov chain Monte Carlo (MCMC) methods. Given a dataset of ∼10-100 pulsars and O(10^{3}) timing residuals each, producing a posterior distribution for the stochastic gravitational wave background (SGWB) can take days to a week. The computational bottleneck arises because the likelihood evaluation required for MCMC is extremely costly when considering the dimensionality of the search space.

Simulating Collider Physics on Quantum Computers Using Effective Field Theories.

Simulating the full dynamics of a quantum field theory over a wide range of energies requires exceptionally large quantum computing resources. Yet for many observables in particle physics, perturbative techniques are sufficient to accurately model all but a constrained range of energies within the validity of the theory. We demonstrate that effective field theories (EFTs) provide an efficient mechanism to separate the high energy dynamics that is easily calculated by traditional perturbation theory from the dynamics at low energy and show how quantum algorithms can be used to simulate the dynamics of the low energy EFT from first principles.

Conditional deletion of RB1 in the Tie2 lineage leads to aortic valve regurgitation.

Objective: Aortic valve disease is a complex process characterized by valve interstitial cell activation, disruption of the extracellular matrix culminating in valve mineralization occurring over many years. We explored the function of the retinoblastoma protein (pRb) in aortic valve disease, given its critical role in mesenchymal cell differentiation including bone development and mineralization.

Approach And Results: We generated a mouse model of conditional pRb knockout (cKO) in the aortic valve regulated by Tie2-Cre-mediated excision of floxed RB1 alleles.

Standardizing Maternity Care Data to Improve Coordination of Care.

The amount of data generated by health information technology systems is staggering, and using those data to make meaningful care decisions that improve patient outcomes is difficult. The purpose of this article is to describe the Maternal Health Information Initiative, a multidisciplinary group of maternity care stakeholders charged with standardizing maternity care data. Complementary strategies that practicing clinicians can use to support this initiative and improve the usability of maternity care data are provided.

The American College of Nurse-Midwives Clarity in Collaboration Project: Describing Midwifery Care in Interprofessional Collaborative Care Models.

In 2014, the American College of Nurse-Midwives (ACNM) launched a project called Clarity in Collaboration to develop data definitions related to midwifery and maternity care delivery processes. These definitions are needed to ensure midwifery care delivered in collaborative care models is accurately and consistently captured in clinical documentation systems, data registries, and systems being developed as part of health care restructuring and payment reform. The Clarity in Collaboration project builds on the efforts of the Women's Health Registry Alliance (WHRA), which was recently established by the American College of Obstetricians and Gynecologists.