Constraining neutron-star matter with microscopic and macroscopic collisions.

Interpreting high-energy, astrophysical phenomena, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars1-9 and from heavy-ion collisions of gold nuclei at relativistic energies10,11 with microscopic nuclear theory calculations12-17 to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission5-8,18. Our findings show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.

Normalizing Flows as an Avenue to Studying Overlapping Gravitational Wave Signals.

Because of its speed after training, machine learning is often envisaged as a solution to a manifold of the issues faced in gravitational-wave astronomy. Demonstrations have been given for various applications in gravitational-wave data analysis. In this Letter, we focus on a challenging problem faced by third-generation detectors: parameter inference for overlapping signals. Because of the high detection rate and increased duration of the signals, they will start to overlap, possibly making traditional parameter inference techniques difficult to use. Here, we show a proof-of-concept application of normalizing flows to perform parameter estimation on overlapped binary black hole systems.

A study of whether video scoring is a reliable option for blinded scoring of the Gross Motor Function Measure-88.

OBJECTIVE: To investigate the agreement between live and video scores of the Gross Motor Function Measure-88. DESIGN: Reliability study. SUBJECTS: Forty children with bilateral spastic cerebral palsy. INTERVENTIONS: Fifty evaluations were administered according to the test guidelines, and were videotaped. After a minimum interval of one month, the video recordings were again rated by the same assessor. Two physical therapy students also each scored the recordings twice, with a minimal interval of one month. MAIN MEASURES: Agreement between live and video scores as well as inter-rater and intra-rater agreement of the video scores were assessed using intra-class correlation coefficients (ICC), standard error of measurements (SEM), and smallest detectable changes (SDC). Weighted kappa coefficients were used to analyse individual items. RESULTS: The live and video scores from the same assessor showed good to very good agreement for the total score (ICC, 0.973; SEM, 2.28; SDC, 6.32) and dimensions B (ICC, 0.938), D (ICC, 0.965), and E (ICC, 0.992) but lower agreement for A (ICC, 0.720) and C (ICC, 0.667). Live-versus-video agreement for the total score was higher than inter-rater agreement by video (ICC, 0.949; SEM, 3.15; SDC, 8.73) but lower than intra-rater agreement by video (ICC, 0.989; SEM, 1.42; SDC, 3.96). CONCLUSION: The Gross Motor Function Measure-88 can be reliably scored using video recordings. The agreement between live and video scores is lower than the intra-rater reliability using video recordings only. Future clinical trial results should be interpreted using the appropriate SEM and SDC values.

Demonstrating the feasibility of probing the neutron-star equation of state with second-generation gravitational-wave detectors.

Fisher matrix and related studies have suggested that, with second-generation gravitational-wave detectors, it may be possible to infer the equation of state of neutron stars using tidal effects in a binary inspiral. Here, we present the first fully Bayesian investigation of this problem. We simulate a realistic data analysis setting by performing a series of numerical experiments of binary neutron-star signals hidden in detector noise, assuming the projected final design sensitivity of the Advanced LIGO-Virgo network. With an astrophysical distribution of events (in particular, uniform in comoving volume), we find that only a few tens of detections will be required to arrive at strong constraints, even for some of the softest equations of state in the literature. Thus, direct gravitational-wave detection will provide a unique probe of neutron-star structure.

An updated nuclear-physics and multi-messenger astrophysics framework for binary neutron star mergers.

The multi-messenger detection of the gravitational-wave signal GW170817, the corresponding kilonova AT2017gfo and the short gamma-ray burst GRB170817A, as well as the observed afterglow has delivered a scientific breakthrough. For an accurate interpretation of all these different messengers, one requires robust theoretical models that describe the emitted gravitational-wave, the electromagnetic emission, and dense matter reliably. In addition, one needs efficient and accurate computational tools to ensure a correct cross-correlation between the models and the observational data. For this purpose, we have developed the Nuclear-physics and Multi-Messenger Astrophysics framework NMMA. The code allows incorporation of nuclear-physics constraints at low densities as well as X-ray and radio observations of isolated neutron stars. In previous works, the NMMA code has allowed us to constrain the equation of state of supranuclear dense matter, to measure the Hubble constant, and to compare dense-matter physics probed in neutron-star mergers and in heavy-ion collisions, and to classify electromagnetic observations and perform model selection. Here, we show an extension of the NMMA code as a first attempt of analyzing the gravitational-wave signal, the kilonova, and the gamma-ray burst afterglow simultaneously. Incorporating all available information, we estimate the radius of a 1.4M⊙ neutron star to be [Formula: see text] km.

A clinical decision framework for the identification of main problems and treatment goals for ambulant children with bilateral spastic cerebral palsy.

The primary aim of the study was to investigate how a clinical decision process based on the International Classification of Function, Disability and Health (ICF) and the Hypothesis-Oriented Algorithm for Clinicians (HOAC-II) can contribute to a reliable identification of main problems in ambulant children with cerebral palsy (CP). As a secondary aim, to evaluate how the additional information from three-dimensional gait analysis (3DGA) can influence the reliability. Twenty-two physical therapists individually defined the main problems and specific goals of eight children with bilateral spastic CP. In four children, the results of 3DGA were provided additionally to the results of the clinical examination and the GMFM-88 (gross motor function measure-88). Frequency analysis was used to evaluate the selected main problems and goals. For the main problems, pair-wise agreement was calculated by the number of corresponding problems between the different therapists and using positive and negative agreement per problem. Cluster analysis using Ward's method was used to evaluate correspondence between the main problems and specific goals. The pair-wise agreement revealed frequencies of 47%, 32% and 3% for the identification of one, two or three corresponding main problems. The number of corresponding main problems was higher when additional information of 3DGA was provided. Most of the specific goals were targeting strength (34%), followed by range of motion (15.2%) and GMFM-D (11.8%). In 29.7% of the cases, therapists could not prioritize and exceeded the number of eight specific goals. Cluster analysis revealed a logic connection between the selection of strength as a main problem and as specific goal parameters. Alignment as a main problem was very often associated with specific parameters like ROM and muscle length and with hypertonia as a main problem. The results show a moderate agreement for the selection of main problems. Therapists are able to use the proposed model for a logic and structured clinical reasoning. Setting priorities in the definition of specific goals is revealed as a remaining difficulty. Further research is required to investigate the additional value of 3DGA and to improve priority setting.