Results for “MATTER” — Page 9

DOE OSTI2024

Neutrino oscillations in matter using the adjugate of the Hamiltonian

We revisit neutrino oscillations in constant matter density for a number of different scenarios: three flavors with the standard Wolfenstein matter potential, four flavors with standard matter potential and three flavors with non-standard matter potentials. To calculate the oscillation probabilities for these scenarios one must determine the eigenvalues and eigenvectors of the Hamiltonians. We use a method for calculating the eigenvalues that is well known, determination of the zeros of determinant of matrix (λI - H), where H is the Hamiltonian, I the identity matrix and λ is a scalar. To calculate the associated eigenvectors we use a method that is little known in the particle physics community, the calculation of the adjugate (transpose of the cofactor matrix) of the same matrix, (λI - H). This method can be applied to any Hamiltonian, but provides a very simple way to determine the eigenvectors for neutrino oscillation in matter, independent of the complexity of the matter potential. This method can be trivially automated using the Faddeev–LeVerrier algorithm for numerical calculations. For the above scenarios we derive a number of quantities that are invariant of the matter potential, many are new such as the generalization of the Naumov–Harrison–Scott identity for four or more flavors of neutrinos. We also show how these matter potential independent quantities become matter potential dependent when off-diagonal non-standard matter effects are included.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1994

A hydrodynamic approach to cosmology: The mixed dark matter cosmological scenario

We compute the evolution of spatially flat, mixed cold and hot dark matter models containing both baryonic matter and two kinds of dark matter. Hydrodynamics is treated with a highly developed Eulerian hydrodynamic code (see Cen 1992). A standard particle-mesh (PM) code is also used in parallel to calculate the motion of the dark matter components. We adopt the following parameters: h equivalent to (sub 0)/100 km/s Mpc(exp -1) = 0.5, OMEGA(sub C) = 0.3, and OMEGA(sub B) = 0.06, with amplitude of the perturbation spectrum fixed by the Cosmic Background Explorer Satellite (COBE) Dark Matter Radiation (DMR) measurements (Smoot et al. 1992) being sigma (sub 8) = 0.67. Four different boxes are simulated with box sizes of L = (64, 16, 4, 1) h(exp -1) Mpc, respectively, the two small boxes providing good resolution but little valid information due to absence of large-scale power. We use 128(exp 3) approximate 10(exp 6.3) baryonic cells, 128(exp .3) cold dark matter particles, and 2 x 128(exp 3) hot dark matter particles. In addition to the dark matter we follow separately six baryonic species (H, H(+), He, He(+), He(++), e(-)) with allowance for both (nonequilibrium) collisional and radiative ionization in every cell. The background radiation field is also followed in detail with allowance made for both continuum and line processes, to allow nonequilibrium heating and cooling processes to be followed in detail. The mean final Zeldovich-Sunyaev y parameter is estimated to be y Bar = (5.4 + or - 2.7) x 10(exp -7) below currently attainable observations, with a rms fluctuation of approximately delta bar y = (0.6 + or - 3.0) x 10(exp -7) on arcminute scales. The rate of galaxy formation peaks at an even later epoch (z approximate 0.3) than in the standard (OMEGA = 1, sigma sub 8 = 0.67) cold dark matter (CDM) model (z approximate 0.5) and, at a redshift of z = 4, is nearly a factor of 100 lower than for the CDM model with the same value of sigma sub 8. With regard to mass function, the smallest objects are stabilized against collapse by thermal energy: the mass-weighted mass spectrum has a broad peak in the vicinity of M(sub B) = 10(exp 9.5) solar mass with a reasonable fit to the Schechter luminosity function if the ratio of baryon mass to blue light is approximately 4. In addition, one very large PM simulation was made in a box with size (320 h(exp - 1) Mpc) containing 3 x 200(exp 3) = 10(exp 7.4) particles. Utilizing this simulation we find that the model yields a cluster mass function which is about a factor of 4 higher than observed, but a cluster-cluster correlation length marginally lower than observed, but that both are closer to observations than in the (COBE) normalized CDM model. The one-dimensional pairwise velocity dispersion is 605 + or - 8 km/s at 1/h separation, lower than that of the DCM model normalized to COBE, but still significant higher than observations (Davis & Peebles 1983). A plausible velocity bias b(sub v) = 0.8 + or - 0.1 on this scale will reduce but not remove the discrepancy. The velocity auto-correlat ion function has a coherence length of 40/h Mpc, which is somewhat lower than the observed counterpart. In all these respects the model would be improved by decreasing the cold fraction of the dark OMEGA(sub CDM)/ (OMEGA(sub CDM) + OMEGA(sub HDB). But formation of galaxies and clusters of galaxies is much later in this model than in COBE-normalized CDM, perhaps too late. To improve on these constraints a larger ratio of OMEGA(sub CDM)/ (OMEGA(sub CDM) + OMEGA(sub HDM)) is required than the value of 0.67 adopted here. It does not seem possible to find a value for this ratio which would satisfy all tests. Overall, the model is similar both on large and intermediate scales to the standard CDM model normalized to the same value of sigma(sub B), but the problem with regard to late formation of galaxies is more severe in this model than in that CDM model. Adding hot dark matter, significantly improves the ability of the COBE-normalized CDM scenario to fit existing observations, but the model is in fact not as good as the CDM model with the same sigma(sub 8) and is still probably unsatisfactory with regard to several critical tests.

Cen, Renyue↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

DOE OSTI2019

Annihilation Signatures of Hidden Sector Dark Matter Within Early-Forming Microhalos

If the dark matter is part of a hidden sector with only very feeble couplings to the Standard Model, the lightest particle in the hidden sector will generically be long-lived and could come to dominate the energy density of the universe prior to the onset of nucleosynthesis. During this early matter-dominated era, density perturbations will grow more quickly than otherwise predicted, leading to a large abundance of sub-earth-mass dark matter microhalos. Since the dark matter does not couple directly to the Standard Model, the minimum halo mass is much smaller than expected for weakly interacting dark matter, and the smallest halos could form during the radiation-dominated era. In this paper, we calculate the evolution of density perturbations within the context of such hidden sector models and use a series of $N$-body simulations to determine the outcome of nonlinear collapse during radiation domination. The resulting microhalos are extremely dense, which leads to very high rates of dark matter annihilation and to large indirect detection signals that resemble those ordinarily predicted for decaying dark matter. We find that the Fermi Collaboration's measurement of the high-latitude gamma-ray background rules out a wide range of parameter space within this class of models. The scenarios that are most difficult to constrain are those that feature a very long early matter-dominated era; if microhalos form prior to the decay of the unstable hidden sector matter, the destruction of these microhalos effectively heats the dark matter, suppressing the later formation of microhalos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

A Likelihood Search for Low-mass Dark Matter via Inelastic Scattering in SuperCDMS

An abundance of evidence suggests that most of the Universe is composed of nonluminous matter. This "dark matter” is believed to be a new elementary particle and experiments around the world are attempting to directly detect rare collisions with terrestrial detectors.The properties of dark matter have yet to be identified, thus efforts are ongoing to explore a range of possible masses and interaction cross-sections. For the latter, experiments can increase exposure by scaling up the detector mass and operating for a longer time. To search for dark matter with less mass than a nucleon, new technologies and analysis techniques need to be developed to be sensitive to energy deposits less than a few keV.SuperCDMS is a direct detection experiment that measures ionization and phonon energy in cryogenic germanium crystal detectors. A special mode of operating the SuperCDMS detectors, called CDMSlite, amplifies the ionization signal via phonon creation. This amplification leads to a lower energy threshold, which provides sensitivity to smaller dark matter masses.Typically, direct detection experiments assume dark matter scatters elastically off the nuclei in the detector. In this thesis, I will highlight the most recent CDMSlite elastic dark matter search. Then I will describe how inelastic dark matter collisions can manifest in the detector and be useful for extending experimental sensitivity to lower dark matter masses. Finally, I will present a re-analysis of CDMSlite data using a profile likelihood to search for low-mass dark matter through two inelastic scattering channels: Bremsstrahlung radiation, and the Migdal Effect.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Boosted Dark Matter Search with the ICARUS Detector at the Gran Sasso Underground National Laboratory

The quest to discover dark matter is one of the most pressing topics in modern physics. Evidence of gravitational anomalies is present at different cosmological scales, spanning the stability and rotation of galaxies to the overall density profile of the entire observable Universe. Due to the discrepancy between the mass measured and the gravitational influence on the mass, if General Relativity is to correctly describe gravity at different scales, extra electromagnetically invisible matter termed dark matter must exist. In recent decades, many experiments have been performed to detect dark matter with masses that span many orders of magnitude, from Mass Compact Halo Objects (MACHOs) with masses several orders of magnitude that of our sun to very light particles on the order of $\sim\mu$eV. However, experiments have only been able to constrain the possible parameter space of dark matter models and, in general, probe dark matter models with single constituent dark matter like Weakly Interacting Massive Particles (WIMPs). In the Boosted Dark Matter (BDM) paradigm, there are four particles in the dark sector: $\chi_0$, $\chi_1$, $\chi_2$, and the dark photon $X$. WIMP-like properties are ascribed to $\chi_0$ to describe the physics of the gravitational anomalies, while relativistic components are assigned to $\chi_1$ and $\chi_2$. The inelastic boosted dark matter (iBDM) channel $\chi_1 e^-\rightarrow \chi_2 e^-\rightarrow \chi_1 Xe^-\rightarrow \chi_1 (e^+ e^- ) e^-$, where $\chi_2$ is an excited state of $\chi_1$, has a unique signature that is distinguishable from neutrino interactions, making neutrino experiments a viable search environment for BDM. Using data collected by the ICARUS collaboration with ICARUS T-600 Liquid Argon Time Projection Chamber (LArTPC) during its operation at the Gran Sasso Underground Laboratory (LNGS), the first-ever LArTPC dark matter search using the ICARUS detector is presented. With a total detector exposure of 0.13 kton$\cdot$year, a total of 4 iBDM candidate events were identified by several stages of data scanning. All were rejected due to defined selection criteria and a wire-by-wire $dE/dx$ evaluation, giving a null result. Exclusion plots at 90\%C.L. for the dark photon ($m_X$, $\epsilon$) parameter space for fixed ($m_0,m_1,m_2$) DM mass sets are presented, setting new limits on the dark photon visible decay parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Parkes Pulsar Timing Array constraints on ultralight scalar-field dark matter

It is widely accepted that dark matter contributes about a quarter of the critical mass-energy density in our Universe. The nature of dark matter is currently unknown, with the mass of possible constituents spanning nearly one hundred orders of magnitude. The ultralight scalar field dark matter, consisting of extremely light bosons with m~10 –22 eV and often called “fuzzy” dark matter, provides intriguing solutions to some challenges at sub-Galactic scales for the standard cold dark matter model. As shown by Khmelnitsky and Rubakov, such a scalar field in the Galaxy would produce an oscillating gravitational potential with nanohertz frequencies, resulting in periodic variations in the times of arrival of radio pulses from pulsars. The Parkes Pulsar Timing Array (PPTA) has been monitoring 20 millisecond pulsars at two- to three-week intervals for more than a decade. In addition to the detection of nanohertz gravitational waves, PPTA offers the opportunity for direct searches for fuzzy dark matter in an astrophysically feasible range of masses. We analyze the latest PPTA data set which includes timing observations for 26 pulsars made between 2004 and 2016. Here, we perform a search in this data set for evidence of ultralight dark matter in the Galaxy using Bayesian and Frequentist methods. No statistically significant detection has been made. We, therefore, place upper limits on the local dark matter density. Our limits, improving on previous searches by a factor of 2 to 5, constrain the dark matter density of ultralight bosons with m ≤ 10 –23 eV to be below 6 GeV cm –3 with 95% confidence in the Earth neighborhood. Finally, we discuss the prospect of probing the astrophysically favored mass range m ≳ 10 –22 eV with next-generation pulsar timing facilities.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Under the FIRElight: Stellar Tracers of the Local Dark Matter Velocity Distribution in the Milky Way

The Gaia era opens new possibilities for discovering the remnants of disrupted satellite galaxies in the Solar neighborhood. If the population of local accreted stars is correlated with the dark matter sourced by the same mergers, one can then map the dark matter distribution directly. Using two cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies from the Latte suite of Fire-2 simulations, we find a strong correlation between the velocity distribution of stars and dark matter at the solar circle that were accreted from luminous satellites. This correspondence holds for dark matter that is either relaxed or in kinematic substructure called debris flow, and is consistent between two simulated hosts with different merger histories. The correspondence is more problematic for streams because of possible spatial offsets between the dark matter and stars. Here, we demonstrate how to reconstruct the dark matter velocity distribution from the observed properties of the accreted stellar population by properly accounting for the ratio of stars to dark matter contributed by individual mergers. After demonstrating this method using the Fire-2 simulations, we apply it to the Milky Way and use it to recover the dark matter velocity distribution associated with the recently discovered stellar debris field in the Solar neighborhood. Finally, based on results from Gaia, we estimate that $42^{+26}_{-22}$% of the local dark matter that is accreted from luminous mergers is in debris flow.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2014

Searching for Dark Matter Annihilation in the Smith High-Velocity Cloud

Recent observations suggest that some high-velocity clouds may be confined by massive dark matter halos. In particular, the proximity and proposed dark matter content of the Smith Cloud make it a tempting target for the indirect detection of dark matter annihilation. We argue that the Smith Cloud may be a better target than some Milky Way dwarf spheroidal satellite galaxies and use gamma-ray observations from the Fermi Large Area Telescope to search for a dark matter annihilation signal. No significant gamma-ray excess is found coincident with the Smith Cloud, and we set strong limits on the dark matter annihilation cross section assuming a spatially extended dark matter profile consistent with dynamical modeling of the Smith Cloud. Notably, these limits exclude the canonical thermal relic cross section (approximately 3 x 10 (sup −26) cubic centimeters per second) for dark matter masses less than or approximately 30 gigaelectronvolts annihilating via the B/B- bar oscillation or tau/antitau channels for certain assumptions of the dark matter density profile; however, uncertainties in the dark matter content of the Smith Cloud may significantly weaken these constraints.

gamma rays: ISM aEuro" ISM: clouds↗

DOE OSTI2024

Curl up with a good B : detecting ultralight dark matter with differential magnetometry

Ultralight dark matter (such as kinetically mixed dark-photon dark matter or axionlike dark matter) can source an oscillating magnetic-field signal at the Earth’s surface, which can be measured by a synchronized array of ground-based magnetometers. The global signal of ultralight dark matter can be robustly predicted for low masses, when the wavelength of the dark matter is larger than the radius of the Earth, $λ_{DM}$ $\gg$ R. However, at higher masses, environmental effects, such as the Schumann resonances, can become relevant, making the global magnetic-field signal B difficult to reliably model. In this work, we show that ∇ × B is robust to global environmental details, and instead only depends on the local dark matter amplitude. We therefore propose to measure the local curl of the magnetic field at the Earth’s surface, as a means for detecting ultralight dark matter with $λ_{DM}$ ≲ R. As this measurement requires vertical gradients, it can be done near a hill/mountain. Our measurement scheme not only allows for a robust prediction, but also acts as a background rejection scheme for external noise sources. We show that our technique can be the most sensitive terrestrial probe of dark-photon dark matter for frequencies 10 Hz ≤ $f_{A'}$ ≤ 1 kHz (corresponding to masses 4 × 10 –14 eV ≤ $m_{A'}$ ≤ 4 × 10 –12 eV). It can also achieve sensitivities to axionlike dark matter comparable to the CAST helioscope, in the same frequency range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Light(ly)-coupled dark matter in the keV range: freeze-in and constraints

Dark matter produced from thermal freeze-out is typically restricted to have masses above roughly 1 MeV. However, if the couplings are small, the freeze-in mechanism allows for production of dark matter down to keV masses. We consider dark matter coupled to a dark photon that mixes with the photon and dark matter coupled to photons through an electric or magnetic dipole moment. We discuss contributions to the freeze-in production of such dark matter particles from standard model fermion-antifermion annihilation and plasmon decay. We also derive constraints on such dark matter from the cooling of red giant stars and horizontal branch stars, carefully evaluating the thermal processes as well as the bremsstrahlung process that dominates for masses above the plasma frequency. We find that the parameters needed to obtain the observed relic abundance from freeze-in are excluded below a few tens of keV, depending on the value of the dark gauge coupling constant for the dark photon portal model, and below a few keV, depending on the reheating temperature for dark matter with an electric or magnetic dipole moment. While laboratory probes are unlikely to probe these freeze-in scenarios in general, we show that for dark matter with an electric or magnetic dipole moment and for dark matter masses above the reheating temperature, the couplings needed for freeze-in to produce the observed relic abundance can be probed partially by upcoming direct-detection experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Production of dark-matter bound states in the early universe by three-body recombination

The small-scale structure problems of the universe can be solved by self-interacting dark matter that becomes strongly interacting at low energy. A particularly predictive model for the self-interactions is resonant short-range interactions with an S-wave scattering length that is much larger than the range. The velocity dependence of the cross section in such a model provides an excellent fit to self-interaction cross sections inferred from dark-matter halos of galaxies and clusters of galaxies if the dark-matter mass is about 19 GeV and the scattering length is about 17 fm. Such a model makes definite predictions for the few-body physics of weakly bound clusters of the dark-matter particles. The formation of the two-body bound cluster is a bottleneck for the formation of larger bound clusters. We calculate the production of two-body bound clusters by three-body recombination in the early universe under the assumption that the dark matter particles are identical bosons, which is the most favorable case. If the dark-matter mass is 19 GeV and the scattering length is 17 fm, the fraction of dark matter in the form of two-body bound clusters can increase by as much as 4 orders of magnitude when the dark-matter temperature falls below the binding energy, but its present value remains less than 10 -6 . The present fraction can be increased to as large as 10 -3 by relaxing the constraints from small-scale structure and decreasing the mass of the dark matter particle.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Galaxy cluster matter profiles - I. Self-similarity, mass calibration, and observable-mass relation validation employing cluster mass posteriors

We present a study of the weak lensing inferred matter profiles ΔΣ(R) of 698 South Pole Telescope (SPT) thermal Sunyaev-Zel’dovich effect (tSZE) selected and MCMF optically confirmed galaxy clusters in the redshift range 0.25 < z < 0.94 that have associated weak gravitational lensing shear profiles from the Dark Energy Survey (DES). Rescaling these profiles to account for the mass dependent size and the redshift dependent density produces average rescaled matter profiles ΔΣ(R/R200c)/(ρcritR200c) with a lower dispersion than the unscaled ΔΣ(R) versions, indicating a significant degree of self-similarity. Galaxy clusters from hydrodynamical simulations also exhibit matter profiles that suggest a high degree of self-similarity, with RMS variation among the average rescaled matter profiles with redshift and mass falling by a factor of approximately six and 23, respectively, compared to the unscaled average matter profiles. We employed this regularity in a new Bayesian method for weak lensing mass calibration that employs the so-called cluster mass posterior P(M200|ζ̂, λ̂, z), which describes the individual cluster masses given their tSZE (ζ̂) and optical (λ̂, z) observables. This method enables simultaneous constraints on richness λ-mass and tSZE detection significance ζ-mass relations using average rescaled cluster matter profiles. We validated the method using realistic mock datasets and present observable-mass relation constraints for the SPT×DES sample, where we constrained the amplitude, mass trend, redshift trend, and intrinsic scatter. Our observable-mass relation results are in agreement with the mass calibration derived from the recent cosmological analysis of the SPT×DES data based on a cluster-by-cluster lensing calibration. Our new mass calibration technique offers a higher efficiency when compared to the single cluster calibration technique. We present new validation tests of the observable-mass relation that indicate the underlying power-law form and scatter are adequate to describe the real cluster sample but that also suggest a redshift variation in the intrinsic scatter of the λ-mass relation may offer a better description. In addition, the average rescaled matter profiles offer high signal-to-noise ratio (S/N) constraints on the shape of real cluster matter profiles, which are in good agreement with available hydrodynamical ΛCDM simulations. This high S/N profile contains information about baryon feedback, the collisional nature of dark matter, and potential deviations from general relativity.Key words: gravitational lensing: weak / galaxies: clusters: general / large-scale structure of Universe

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Cosmic-ray boosted inelastic dark matter from neutrino-emitting active galactic nuclei

Cosmic rays may scatter off dark matter particles in active galactic nuclei, where both the densities of cosmic rays and dark matter are expected to be very large. These scatterings could yield a flux of boosted dark matter particles directly detectable on Earth, which enhances the sensitivity of dark matter direct detection and neutrino experiments to light and inelastic dark matter models. Here we calculate the cosmic-ray boosted dark matter flux from the neutrino-emitting active galactic nuclei, NGC 1068 and TXS 0506+056, by considering realistic cosmic-ray distributions, deep inelastic scatterings, and mass splittings in the dark sector. From this we derive novel bounds from these sources on light and/or inelastic dark matter models with Super-K and XENONnT. We find that cosmic-ray boosted dark matter from neutrino-emitting active galactic nuclei can test regions of parameter space favored to reproduce the observed relic abundance of dark matter in the Universe, and that are otherwise experimentally inaccessible.

Gustafson, R. Andrew [Virginia Tech.; KEK, Tsukuba↗

DOE OSTI2021

Bulk viscosity from Urca processes: npeμ matter in the neutrino-trapped regime

In this work, we extend our previous study of the bulk viscosity of hot and dense npe matter induced by the Urca process in the neutrino trapped regime to npeμ matter by adding the muonic Urca processes as well as the purely leptonic electroweak processes involving electron-muon transition. Here, the nuclear matter is modeled in a relativistic density functional approach with two different parametrizations which predict neutrino dominated matter (DDME2 model) and anti-neutrino dominated matter (NL3 model) at temperatures for which neutrinos/anti-neutrinos are trapped. In the case of neutrino-dominated matter, the main equilibration mechanism is lepton capture, whereas in the case of antineutrino-dominated matter this is due to neutron decay. We find that the equilibration rates of Urca processes are higher than that of the pure leptonic processes, which implies that the Urca bulk viscosity can be computed with the leptonic reactions assumed to be frozen. We find that the bulk viscosity decreases with temperature as ζ~T –2 at moderate temperatures. At high temperatures this scaling breaks down by sharp drops of the bulk viscosity close to the temperature where the proton fraction is density-independent and the matter becomes scale-invariant. This occurs also when the matter undergoes a transition from the antineutrino-dominated regime to the neutrino-dominated regime where the bulk viscosity attains a local maximum. We also estimate the bulk viscous dissipation timescales and find that these are in the range ≳ 1 s for temperatures above the neutrino trapping temperature. These timescales would be relevant only for long-lived objects formed in binary neutron star mergers and hot proto-neutron stars formed in core-collapse supernovas.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗