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At least 505 records · Page 28

Gravitational-wave Constraints on the Equatorial Ellipticity of Millisecond Pulsars

In this work, we present a search for continuous gravitational waves from five radio pulsars, comprising three recycled pulsars (PSR J0437-4715, PSR J0711-6830, and PSR J0737-3039A) and two young pulsars: the Crab pulsar (J0534+2200) and the Vela pulsar (J0835-4510). We use data from the third observing run of Advanced LIGO and Virgo combined with data from their first and second observing runs. For the first time, we are able to match (for PSR J0437-4715) or surpass (for PSR J0711-6830) the indirect limits on gravitational-wave emission from recycled pulsars inferred from their observed spin-downs, and constrain their equatorial ellipticities to be less than 10 -8 . For each of the five pulsars, we perform targeted searches that assume a tight coupling between the gravitational-wave and electromagnetic signal phase evolution. We also present constraints on PSR J0711-6830, the Crab pulsar, and the Vela pulsar from a search that relaxes this assumption, allowing the gravitational-wave signal to vary from the electromagnetic expectation within a narrow band of frequencies and frequency derivatives.

79 ASTRONOMY AND ASTROPHYSICS↗

Specific Effect of Peculiar Velocities on Dark-energy Constraints from Type Ia Supernovae

Peculiar velocities of Type Ia supernova (SN Ia) host galaxies affect the dark-energy parameter constraints in a small but very specific way: the parameters are biased in a single direction in parameter space that is a priori knowable for a given SN Ia data set. We demonstrate the latter fact with a combination of inference from a cosmological N-body simulation with overwhelming statistics applied to the Pantheon SN Ia data set, then confirm it by simple quantitative arguments. Here, we quantify small modifications to the current analyses that would ensure that the effect of cosmological parameters is essentially guaranteed to be negligible.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraints on the Electromagnetic Counterpart of the Neutron-star–Black-hole Merger GW200115

We report the results of our follow-up campaign for the neutron-star—black-hole (NSBH) merger GW200115 detected during the O3 run of the Advanced LIGO and Advanced Virgo detectors. We obtained wide-field observations with the Deca-Degree Optical Transient Imager covering ~20% of the total probability area down to a limiting magnitude of w = 20.5 AB at ~23 hr after the merger. Our search for counterparts returns a single candidate (AT2020aeo), likely not associated with the merger. In total, only 25 sources of interest were identified by the community and later discarded as unrelated to the GW event. We compare our upper limits with the emission predicted by state-of-the-art kilonova simulations and disfavor high-mass ejecta (>0.1 M⊙), indicating that the spin of the system is not particularly high. By combining our optical limits with gamma-ray constraints from Swift and Fermi, we disfavor the presence of a standard short-duration burst for viewing angles ≲15° from the jet axis. Our conclusions are, however, limited by the large localization region of this GW event, and accurate prompt positions remain crucial to improving the efficiency of follow-up efforts.

79 ASTRONOMY AND ASTROPHYSICS↗

A New Constraint on the Nuclear Equation of State from Statistical Distributions of Compact Remnants of Supernovae

Abstract Understanding how matter behaves at the highest densities and temperatures is a major open problem in both nuclear physics and relativistic astrophysics. Our understanding of such behavior is often encapsulated in the so-called high-temperature nuclear equation of state (EOS), which influences compact binary mergers, core-collapse supernovae, and other phenomena. Our focus is on the type (either black hole or neutron star) and mass of the remnant of the core collapse of a massive star. For each six candidates of equations of state, we use a very large suite of spherically symmetric supernova models to generate a sample of synthetic populations of such remnants. We then compare these synthetic populations to the observed remnant population. Our study provides a novel constraint on the high-temperature nuclear EOS and describes which EOS candidates are more or less favored by an information-theoretic metric.

79 ASTRONOMY AND ASTROPHYSICS↗

New Constraints on the Dark Matter Density Profiles of Dwarf Galaxies from Proper Motions of Globular Cluster Streams

The central density profiles in dwarf galaxy halos depend strongly on the nature of dark matter (DM). Recently, in Malhan et al. we employed N-body simulations to show that the cuspy cold DM subhalos predicted by cosmological simulations can be differentiated from cored subhalos using the properties of accreted globular cluster (GC) streams since these GCs experience tidal stripping within their parent halos prior to accretion onto the Milky Way. We previously found that clusters that are accreted within cuspy subhalos produce streams with larger physical widths and higher dispersions in line-of-sight velocity and angular momentum than streams that are accreted within cored subhalos. Here, we use the same suite of simulations to demonstrate that the dispersion in the tangential velocities of streams (${\sigma }_{{v}_{\mathrm{Tan}}}$) is also sensitive to the central DM density profiles of their parent dwarfs and GCs that they were accreted from; cuspy subhalos produce streams with larger ${\sigma }_{{v}_{\mathrm{Tan}}}$ than those accreted inside cored subhalos. Using Gaia EDR3 observations of multiple GC streams we compare their ${\sigma }_{{v}_{\mathrm{Tan}}}$ values with simulations. The measured ${\sigma }_{{v}_{\mathrm{Tan}}}$ values are consistent with both an “in situ” origin and with accretion inside cored subhalos of M ~ 10 8–9 M ⊙ (or very low-mass cuspy subhalos of mass ~10 8 M ⊙ ). Despite the large current uncertainties in ${\sigma }_{{v}_{\mathrm{Tan}}}$, we find a low probability that any of the progenitor GCs were accreted from cuspy subhalos of M ≳ 10 9 M ⊙ . The uncertainties on Gaia tangential velocity measurements are expected to decrease in future and will allow for stronger constraints on subhalo DM density profiles.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraints on cosmology and baryonic feedback with joint analysis of Dark Energy Survey Year 3 lensing data and ACT DR6 thermal Sunyaev-Zel'dovich effect observations

We present a joint analysis of weak gravitational lensing (shear) data obtained from the first three years of observations by the Dark Energy Survey and thermal Sunyaev-Zel'dovich (tSZ) effect measurements from a combination of Atacama Cosmology Telescope (ACT) and Planck data. A combined analysis of shear (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) can jointly probe both the distribution of matter and the thermodynamic state of the gas, accounting for the correlated effects of baryonic feedback on both observables. We detect the shear$~\times~$tSZ cross-correlation at a 21$\sigma$ significance, the highest to date, after minimizing the bias from cosmic infrared background leakage in the tSZ map. By jointly modeling the small-scale shear auto-correlation and the shear$~\times~$tSZ cross-correlation, we obtain $S_8 = 0.811^{+0.015}_{-0.012}$ and $\Omega_{\rm m} = 0.263^{+0.023}_{-0.030}$, results consistent with primary CMB analyses from Planck and P-ACT. We find evidence for reduced thermal gas pressure in dark matter halos with masses $M < 10^{14} \, M_{\odot}/h$, supporting predictions of enhanced feedback from active galactic nuclei on gas thermodynamics. A comparison of the inferred matter power suppression reveals a $2-4\sigma$ tension with hydrodynamical simulations that implement mild baryonic feedback, as our constraints prefer a stronger suppression. Finally, we investigate biases from cosmic infrared background leakage in the tSZ-shear cross-correlation measurements, employing mitigation techniques to ensure a robust inference. Our code is publicly available on GitHub.

Pandey, S. [Johns Hopkins U.; Columbia U.] (ORCID:↗

Inferring and evaluating satellite-based constraints on NO x emissions estimates in air quality simulations

Satellite observations of tropospheric NO 2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NO x ). Mass-balance-based methods are often applied for this purpose but do not isolate near-surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model. In the framework, satellite-constrained emissions totals are inferred using model simulations with and without data assimilation in the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to separately estimate lightning and anthropogenic NO x emissions over the Northern Hemisphere for 2019. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare separate NO x emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO 2 and O 3 . OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO 2 retrievals. Updated lightning NO x emissions from either satellite improve the chemical transport model's low tropospheric O 3 bias. The combined lighting and anthropogenic emissions updates improve the model's ability to reproduce measured ozone by adjusting natural, long-range, and local pollution contributions. Thus, the framework informs and supports the design of domestic and international control strategies.

54 ENVIRONMENTAL SCIENCES↗

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiagvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation.

54 ENVIRONMENTAL SCIENCES↗

Particle transport constraints via Bayesian spectral fitting of multiple atomic lines

Optimized operation of fusion devices demands detailed understanding of plasma transport, a problem that must be addressed with advances in both measurement and data analysis techniques. In this work, we adopt Bayesian inference methods to determine experimental particle transport, leveraging opportunities from high-resolution He-like ion spectra in a tokamak plasma. The Bayesian spectral fitting code is used to analyze resonance (w), forbidden (z), intercombination (x, y), and satellite (k, j) lines of He-like Ca following laser blow-off injections on Alcator C-Mod. This offers powerful transport constraints since these lines depend differently on electron temperature and density, but also differ in their relation to Li-like, He-like, and H-like ion densities, often the dominant Ca charge states over most of the C-Mod plasma radius. Using synthetic diagnostics based on the AURORA package, we demonstrate improved effectiveness of impurity transport inferences when spectroscopic data from a progressively larger number of lines are included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data release for A search for extremely-high-energy neutrinos and first constraints on the ultra-high-energy cosmic-ray proton fraction with IceCube

<h1 id="summary">Summary</h1> <p>Title: Data Release for A search for extremely-high-energy neutrinos and first constraints on the ultra-high-energy cosmic-ray proton fraction with IceCube</p> <p>The IceCube observatory analyzed 12.6 years of data in search of extremely-high-energy (EHE) neutrinos above 5 PeV. The resultant limit of the search (Fig 1), and the effective area of the event selection (Fig 7), are provided in this data release.</p> <h1 id="contents">Contents</h1> <ul> <li><p>README file: this file</p> </li> <li><p><code>differential_limit_and_sensitivity.csv</code>: a comma separated value file, giving the observed experimental differential limit, and sensitivity, of the search as a function of neutrino energy. This is the content of Fig 1 in the paper. The first column is the neutrino energy in GeV. The second column is the limit in units of GeV/cm2/s/sr. The third column is the sensitivity in units of GeV/cm2/s/sr.</p> </li> <li><p><code>effective_area.csv</code>: a comma separated value file, giving the effective area of the search as a function of energy. This is the content of Fig 7 in the paper. The first column is the neutrino energy in GeV. The second column is the total effective area of the search, summed across neutrino flavors, and averaged across neutrinos and antineutrinos, in meters-squared. The third column is the effective area of the search for the average of electron neutrino and electron antineutrinos in units of meters-squared. The fourth column is the same as the third, but for muon-flavor neutrinos. The fifth column is the same as the third and fourth, but for tau-flavor neutrinos.</p> </li> <li><p><code>demo.py</code>: a short python script to demonstrate how to read the files. Run like <code>python demo.py</code>. A standard base python installation is sufficient, as the only dependencies are numpy and matplotlib.</p> </li> </ul> <h1 id="contacts">Contacts</h1> <p>For any questions about this data release, please write to analysis@icecube.wisc.edu</p>

Astronomy and Astrophysics↗

Majorana versus Dirac Constraints on the Neutrino Dipole Moments

Massive neutrinos are guaranteed to have nonzero electromagnetic moments and, since there are at least three neutrino species, these dipole moments define a matrix. Here, we estimate the current upper bounds on all independent neutrino electromagnetic moments, concentrating on Earth-bound experiments and measurements with solar neutrinos, including the very recent results reported by XENONnT. We make no simplifying assumptions and compare the hypotheses that neutrinos are Majorana fermions or Dirac fermions. In particular, we fully explore constraints in the Dirac-neutrino parameter space. Majorana and Dirac neutrinos are different; for example, the upper bounds on the magnitudes of the elements of the dipole moment matrix are weaker for Dirac neutrinos, relative to Majorana neutrinos. The potential physics reach of next-generation experiments also depends on the nature of the neutrino. We find that a next-generation experiment two orders of magnitude more sensitive to the neutrino electromagnetic moments via $\nu_{\mu}$ elastic scattering may discover that the neutrino electromagnetic moments are nonzero if the neutrinos are Dirac fermions. Instead, if the neutrinos are Majorana fermions, such a discovery is ruled out by existing solar neutrino data, unless there are more than three light neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Autonomous Eco-Driving with Traffic Light and Lead Vehicle Constraints: An Application of Best Constrained Interpolation

Eco-Driving is a critical technology for improving automotive transportation efficiency. It is achieved by modifying the driving trajectory over a particular route to minimize required propulsion energy. Eco-Driving can be approached as an optimal control problem subject to driving constraints such as traffic lights and positions of other vehicles. Best interpolation in a strip is a problem in approximation theory and optimal control. The solution to this problem is a cubic spline. In this research, we demonstrate the connection between Eco-Driving and best interpolation in the strip. By exploiting this connection, we are able to generate optimal Eco-Driving trajectories that could be driven with an autonomous system. Using the simulation tool FASTSim, we can evaluate the trajectories using conventional, hybrid electric, and fully electric vehicle models. Our results quantify the energy efficiency improvements that can be achieved with the proposed approach.

Mahmoud, Yara Hazem↗

Autonomous Eco-Driving with Traffic Light and Lead Vehicle Constraints: An Application of Best Constrained Interpolation

Eco-Driving is a critical technology for improving automotive transportation efficiency. It is achieved by modifying the driving trajectory over a particular route to minimize required propulsion energy. Eco-Driving can be approached as an optimal control problem subject to driving constraints such as traffic lights and positions of other vehicles. Best interpolation in a strip is a problem in approximation theory and optimal control. The solution to this problem is a cubic spline. In this research, we demonstrate the connection between Eco-Driving and best interpolation in the strip. By exploiting this connection, we are able to generate optimal Eco-Driving trajectories that could be driven with an autonomous system. Using the simulation tool FASTSim, we can evaluate the trajectories using conventional, hybrid electric, and fully electric vehicle models. Our results quantify the energy efficiency improvements that can be achieved with the proposed approach.

Mahmoud, Yara Hazem↗

Thermal Constraint Violations as a Result of Ambient Adjusted Transmission Line Ratings

Ambient Adjusted Ratings allow transmission line current ratings to be increased above static ratings while requiring minimal weather monitoring. However, Ambient Adjusted Ratings are still contingent on static parameters that may not match real world conditions. This poster examines how simulation methods can estimate the extent to which using Ambient Adjusted Ratings could result in the violation of a transmission line's thermal constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but traditional Monte Carlo methods for cosmological inference are computationally prohibitive and inadequate for processing the thousands of lenses anticipated from future cosmic surveys. New tools for inference, such as SBI using Neural Ratio Estimation (NRE), address this challenge effectively. By training a machine learning model on simulated data of strong lenses, we can learn the likelihood-to-evidence ratio for robust inference. Our scalable approach enables more constrained population-level inference of $w$ compared to individual lens analysis, constraining $w$ to within $1\sigma$. Our model can be used to provide cosmological constraints from forthcoming strong lens surveys, such as the 4MOST Strong Lensing Spectroscopic Legacy Survey (4SLSLS), which is expected to observe 10,000 strong lenses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but traditional Monte Carlo methods for cosmological inference are computationally prohibitive and inadequate for processing the thousands of lenses anticipated from future cosmic surveys. New tools for inference, such as SBI using Neural Ratio Estimation (NRE), address this challenge effectively. By training a machine learning model on simulated data of strong lenses, we can learn the likelihood-to-evidence ratio for robust inference. Our scalable approach enables more constrained population-level inference of $w$ compared to individual lens analysis, constraining $w$ to within 1$\sigma$. Our model can be used to provide cosmological constraints from forthcoming strong lens surveys, such as the 4MOST Strong Lensing Spectroscopic Legacy Survey (4SLSLS), which is expected to observe 10,000 strong lenses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Cosmological Constraints on Secluded Dark Radiation

Dark radiation (DR) is ubiquitous in physics beyond the Standard Model (SM), and its interactions with the SM and dark matter (DM) lead to a variety of interesting effects on cosmological observables. However, even in scenarios where DR is 'secluded', i.e., only gravitationally interacting with SM and DM, it can leave discernible signatures. We present a comprehensive study of four different types of DR: free-streaming, self-interacting (coupled), decoupling, and recoupling DR, and vary initial conditions to include both adiabatic and isocurvature perturbations. In addition to these properties, we also vary neutrino energy density, DR energy density, and the SM neutrino masses to perform a general analysis and study degeneracies among neutrino and DR properties. We derive constraints using the cosmic microwave background, large-scale structure, and supernova datasets. We find no significant preference for physics beyond the $Λ$CDM model, but data exhibit interesting interplays between different physical quantities. When the neutrino energy density is allowed to vary, we find that the cosmological dataset prefers massless free-streaming DR over massive neutrinos, leading to a significant relaxation of the neutrino mass bound. Although we do not find any evidence of DR isocurvature, the data show support for a strong blue tilt of the isocurvature power spectrum. Our analysis also highlights the degeneracy of various DR parameters with the Hubble constant $H_0$ resulting in a mild relaxation of the $H_0$ tension.

Chang, Jae Hyeok [Fermilab; Illinois U., Chicago] ↗

First constraints on causal sources of primordial gravitational waves from BICEP/Keck, SPTpol, SPT-3G, Planck and WMAP $B$-mode data

Non-inflationary sources of gravitational waves in the early Universe generically predict causality-limited tensor power spectra at low frequencies. We report the first-ever constraints on such sources based on cosmic microwave background (CMB) $B$-mode polarization measurements. Using data from BICEP/Keck, SPTpol, SPT-3G, Planck, and WMAP, we constrain the amplitude of an early causal tensor (ECT) power spectrum parameterized by $r_{ect}$, the ratio of causal tensor power to total scalar power at $k~=~0.01$ Mpc$^{-1}$, and obtain a 95% CL upper limit of $r_{ect}<$ 0.0077. Since $r_{ect}$ can easily be related to the parameters of a given theory, our bound robustly constrains a broad class of well-motivated gravitational wave sources in the early universe, including first-order cosmological phase transitions, enhanced small-scale density perturbations, and various topological defects. Finally, we translate our limit into a bound on the present-day energy density in gravitational waves at ultra-low frequencies otherwise inaccessible to traditional gravitational wave detection strategies, including pulsar timing arrays, interferometers, and resonant cavities.

Zebrowski, Jessica A. [Fermilab; Chicago U., KICP]↗