SearcharxivSearch

arXiv subjects

Adam Moss

Publications and source records attributed to Adam Moss.

At least 37 records · Page 2Linked to original sources

Massive White Dwarfs in the 100 pc Sample: Magnetism, Rotation, Pulsations, and the Merger Fraction

We present a detailed model atmosphere analysis of massive white dwarfs with $M > 0.9~M_\odot$ and $T_{\rm eff}\geq11,000$ K in the Montreal White Dwarf Database 100 pc sample and the Pan-STARRS footprint. We obtained follow-up optical spectroscopy of 109 objects with no previous spectral classification in the literature. Our spectroscopic follow-up is now complete for all 204 objects in the sample. We find 118 normal DA white dwarfs, including 45 massive DAs near the ZZ Ceti instability strip. There are no normal massive DBs: the six DBs in the sample are strongly magnetic and/or rapidly rotating. There are 20 massive DQ white dwarfs in our sample, and all are found in the crystallization sequence. In addition, 66 targets are magnetic (32% of the sample). We use magnetic white dwarf atmosphere models to constrain the field strength and geometry using offset dipole models. We also use magnetism, kinematics, and rotation measurements to constrain the fraction of merger remnant candidates among this population. The merger fraction of this sample increases from 25% for 0.9-$1~M_{\odot}$ white dwarfs to 49% for 1.2-$1.3~M_{\odot}$. However, this fraction is as high as $78_{-7}^{+4}$% for 1.1-$1.2~M_{\odot}$ white dwarfs. Previous works have demonstrated that 5-9% of high-mass white dwarfs stop cooling for $\sim8$ Gyr due to the $^{22}$Ne distillation process, which leads to an overdensity of Q-branch stars in the solar neighborhood. We demonstrate that the over-abundance of the merger remnant candidates in our sample is likely due to the same process.

astro-ph.SR

White Dwarf Merger Remnants: The DAQ Subclass

Four years after the discovery of a unique DAQ white dwarf with a hydrogen-dominated and carbon-rich atmosphere, we report the discovery of four new DAQ white dwarfs, including two that were not recognized properly in the literature. We find all five DAQs in a relatively narrow mass and temperature range of $M=1.14-1.19~M_{\odot}$ and $T_{\rm eff}=13,000-17,000$ K. In addition, at least two show photometric variations due to rapid rotation with $\approx10$ min periods. All five are also kinematically old, but appear photometrically young with estimated cooling ages of about 1 Gyr based on standard cooling tracks, and their masses are roughly twice the mass of the most common white dwarfs in the solar neighborhood. These characteristics are smoking gun signatures of white dwarf merger remnants. Comparing the DAQ sample with warm DQ white dwarfs, we demonstrate that there is a range of hydrogen abundances among the warm DQ population, and the distinction between DAQ and warm DQ white dwarfs is superficial. We discuss the potential evolutionary channels for the emergence of the DAQ subclass, and suggest that DAQ white dwarfs are trapped on the crystallization sequence, and may remain there for a significant fraction of the Hubble time.

astro-ph.SR

Discovery of a Magnetic Double-Faced DBA White Dwarf

We report the discovery of spectroscopic variations in the magnetic DBA white dwarf SDSS J091016.43+210554.2. Follow-up time-resolved spectroscopy at the Apache Point Observatory (APO) and the MMT show significant variations in the H absorption lines over a rotation period of 7.7 or 11.3 h. Unlike recent targets that show similar discrepancies in their H and He line profiles, such as GD 323 and Janus (ZTF J203349.8+322901.1), SDSS J091016.43+210554.2 is confirmed to be magnetic, with a field strength derived from Zeeman-split H and He lines of B ~ 0.5 MG. Model fits using a H and He atmosphere with a constant abundance ratio across the surface fail to match our time-resolved spectra. On the other hand, we obtain excellent fits using magnetic atmosphere models with varying H/He surface abundance ratios. We use the oblique rotator model to fit the system geometry. The observed spectroscopic variations can be explained by a magnetic inhomogeneous atmosphere where the magnetic axis is offset from the rotation axis by beta = 52 degrees, and the inclination angle between the line of sight and the rotation axis is i = 13 - 16 degrees. This magnetic white dwarf offers a unique opportunity to study the effect of the magnetic field on surface abundances. We propose a model where H is brought to the surface from the deep interior more efficiently along the magnetic field lines, thus producing H polar caps

astro-ph.SR

Scaling solutions as Early Dark Energy resolutions to the Hubble tension

A wide class of scalar field models including Quintessence and K-essence have the attractive property of tracker regimes, where the energy density stored in the field evolves so as to mimic that of the dominant background component for a period of time. During this evolution, for a brief period of time there is an increase in the energy density of the field as it spirals in towards it's attractor solution. We show that when the peak of this energy density occurs around the epoch of equality, we can address a key requirement of early dark energy (EDE), postulated as a solution to the Hubble tension. In particular we demonstrate how this can occur in a wide class of Quintessence, axion and K-essence models, before showing that the Quintessence models suffer in that they generally lead to sound speeds incompatible with the requirements of EDE, whereas the K-essence and axion models can do a better job of fitting the data.

astro-ph.CO

Using machine learning to optimise chameleon fifth force experiments

The chameleon is a theorised scalar field that couples to matter and possess a screening mechanism, which weakens observational constraints from experiments performed in regions of higher matter density. One consequence of this screening mechanism is that the force induced by the field is dependent on the shape of the source mass (a property that distinguishes it from gravity). Therefore an optimal shape must exist for which the chameleon force is maximised. Such a shape would allow experiments to improve their sensitivity by simply changing the shape of the source mass. In this work we use a combination of genetic algorithms and the chameleon solving software SELCIE to find shapes that optimise the force at a single point in an idealised experimental environment. We note that the method we used is easily customised, and so could be used to optimise a more realistic experiment involving particle trajectories or the force acting on an extended body. We find the shapes outputted by the genetic algorithm possess common characteristics, such as a preference for smaller source masses, and that the largest fifth forces are produced by small `umbrella'-like shapes with a thickness such that the source is unscreened but the field reaches its minimum inside the source. This remains the optimal shape even as we change the chameleon potential, and the distance from the source, and across a wide range of chameleon parameters. We find that by optimising the shape in this way the fifth force can be increased by $2.45$ times when compared to a sphere, centred at the origin, of the same volume and mass.

gr-qc

Signs of Binary Evolution in 7 Magnetic DA White Dwarfs

We present our findings on the spectral analysis of seven magnetic white dwarfs that were presumed to be double degenerates. We obtained time-resolved spectroscopy at the Gemini Observatory to look for evidence of binarity or fast rotation. We find three of our targets have rotation periods of less than an hour based on the shifting positions of the Zeeman-split H$α$ components: 13, 35, and 39 min, and we find one more target with a ~hour long period that is currently unconstrained. We use offset dipole models to determine the inclination, magnetic field strength, and dipole offset of each target. The average surface field strengths of our fast rotators vary by 1-2 MG between different spectra. In all cases, the observed absorption features are too shallow compared to our models. This could be due to extra flux from a companion for our three low-mass targets, but the majority of our sample likely requires an inhomogeneous surface composition. Including an additional magnetic white dwarf with similar properties presented in the literature, we find that 5 of the 8 targets in this sample show field variations on minute/hour timescales. A crystallization driven dynamo can potentially explain the magnetic fields in three of our targets with masses above $0.7~M_{\odot}$ but another mechanism is still needed to explain their rapid rotation. We suggest that rapid rotation or low-masses point to binary evolution as the likely source of magnetism in 7 of these 8 targets.

astro-ph.SR

Chameleon Screening in Cosmic Voids

A key goal in cosmology in the upcoming decade will be to form a better understanding of the accelerated expansion of the Universe. Upcoming surveys, such as the Vera C. Rubin Observatory's 10-year Legacy Survey of Space and Time (LSST), Euclid and the Square Killometer Array (SKA) will deliver key datasets required to tackle this and other puzzles in contemporary cosmology. With this data, constraints of unprecedented power will be put on different models of dark energy and modified gravity. In this context it is crucial to understand how screening mechanisms, which hide the deviations of these theories from the predictions of general relativity in local experiments, affect structure formation. In this work we approach this problem by using a combination of analytic and numerical methods to describe chameleon screening in the context of cosmic voids. We apply a finite element method (FEM) code, SELCIE, to solve the chameleon equation of motion for a number of void profiles derived from observational data and simulations. The obtained results indicate a complex relationship between the properties of cosmic voids and the size of the chameleon acceleration of a test particle. We find that the fifth force on a test particle in a void is primarily related to the depth and the inner density gradient of the void. For realistic void profiles, the obtained chameleon-to-Newtonian acceleration ratios range between $a_ϕ/a_{\rm Newt} \approx 10^{-6} - 10^{-5}$. However, it should be noted that in unusually deep voids with large inner density gradients, the acceleration ratios can be significantly higher. Similarly, other chameleon models, such as $f(R)$ Hu-Sawicki theory allow for significantly higher acceleration ratios. Given these results, we also discuss the optimal density profiles for detecting the fifth force in the upcoming observational surveys.

gr-qc

CMB constraints on monodromy inflation at strong coupling

We carry out a thorough numerical examination of field theory monodromy inflation at strong coupling. We perform an MCMC analysis using a Gaussian likelihood, fitting multiparameter models using CMB constraints on the spectral index and the tensor to scalar ratio. We show that models with uniquely positive Wilson coefficients are ruled out. If there are coefficients that can take on both signs, there can be a cancellation of terms that flattens the potentials and allows one to satisfy current data, and forecasts with strong constraints on the tensor to scalar ratio. Models of field theory monodromy are naturally enhanced to include a mechanism for canceling off radiative corrections to vacuum energy, via vacuum energy sequestering (VES). Although they include a much larger parameter space, we find that a similar numerical examination yields no significant change in the Bayesian evidence for VES enhanced models, with naturalness considerations making them more attractive from a theoretical perspective.

astro-ph.CO

Improving white dwarfs as chronometers with Gaia parallaxes and spectroscopic metallicities

White dwarfs (WDs) offer unrealized potential in solving two problems in astrophysics: stellar age accuracy and precision. WD cooling ages can be inferred from surface temperatures and radii, which can be constrained with precision by high quality photometry and parallaxes. Accurate and precise Gaia parallaxes along with photometric surveys provide information to derive cooling and total ages for vast numbers of WDs. Here we analyse 1372 WDs found in wide binaries with MS companions, and report on the cooling and total age precision attainable in these WD+MS systems. The total age of a WD can be further constrained if its original metallicity is known, because the main-sequence (MS) progenitor lifetime depends on metallicity at fixed mass, yet metallicity is unavailable via spectroscopy of the WD. We show that incorporating spectroscopic metallicity constraints from 38 wide binary MS companions substantially decreases internal uncertainties in WD total ages compared to a uniform constraint. Averaged over the 38 stars in our sample, the total (internal) age uncertainty improves from 21.04% to 16.77% when incorporating the spectroscopic constraint. Higher mass WDs yield better total age precision; for 8 WDs with zero age main sequence masses $\geq$ 2.0 solar masses, the mean uncertainty in total ages improves from 8.61% to 4.54% when incorporating spectroscopic metallicities. We find that it is often possible to achieve 5% total age precision for WDs with progenitor masses above 2.0 solar masses if parallaxes with $\leq$ 1% precision and Pan-STARRS $g, r$, and $i$ photometry with $\leq$ 0.01 mag precision are available.

astro-ph.SR

Chameleon Screening Depends on the Shape and Structure of NFW Halos

Chameleon gravity is an example of a model that gives rise to interesting phenomenology on cosmological scales while simultaneously possessing a screening mechanism, allowing it to avoid solar system constraints. Such models result in non-linear field equations, which can be solved analytically only in simple highly symmetric systems. In this work we study the equation of motion of a scalar-tensor theory with chameleon screening using the finite element method. More specifically, we solve the field equation for spherical and triaxial NFW cluster-sized halos. This allows a detailed investigation of the relationship between the NFW concentration and the virial mass parameters and the magnitude of the chameleon acceleration, as measured at the virial radius. In addition, we investigate the effects on the chameleon acceleration due to halo triaxiality. We focus on the parameter space regions that are still allowed by the observational constraints. We find that given our dataset, the largest allowed value for the chameleon-to-NFW acceleration ratio at the virial radius is $\sim 10^{-7}$. This result strongly indicates that the chameleon models that are still allowed by the observational constraints would not lead to any measurable effects on galaxy cluster scales. Nonetheless, we also find that there is a direct relationship between the NFW potential and the chameleon-to-NFW acceleration ratio at the virial radius. Similarly, there is a direct (yet a much more complicated) relationship between the NFW concentration, the virial mass and the acceleration ratios at the virial radius. Finally, we find that triaxiality introduces extra directional effects on the acceleration measurements. These effects in combination could potentially be used in future observational searches for fifth forces.

gr-qc

SELCIE: A tool for investigating the chameleon field of arbitrary sources

The chameleon model is a modified gravity theory that introduces an additional scalar field that couples to matter through a conformal coupling. This `chameleon field' possesses a screening mechanism through a nonlinear self-interaction term which allows the field to affect cosmological observables in diffuse environments whilst still being consistent with current local experimental constraints. Due to the self-interaction term the equations of motion of the field are nonlinear and therefore difficult to solve analytically. The analytic solutions that do exist in the literature are either approximate solutions and or only apply to highly symmetric systems. In this work we introduce the software package SELCIE (https://github.com/C-Briddon/SELCIE.git). This package equips the user with tools to construct an arbitrary system of mass distributions and then to calculate the corresponding solution to the chameleon field equation. It accomplishes this by using the finite element method and either the Picard or Newton nonlinear solving methods. We compared the results produced by SELCIE with analytic results from the literature including discrete and continuous density distributions. We found strong (sub-percentage) agreement between the solutions calculated by SELCIE and the analytic solutions.

gr-qc

A model-independent reconstruction of dark energy to very high redshift

We provide a model-independent reconstruction of dark energy from $z=0$ to $ \gtrsim 10^5$. We parameterise the model by a perfect fluid with a series of physically well-motivated bins in energy-density, such that the equation of state is always $-1 \le w \le 1$. Our method is capable of describing a range of theoretical models with smooth modifications to the expansion history. Combining the latest CMB, BAO, SN and local $H_0$ measurements, we obtain a large improvement of $Δχ^2=41.3$ over LCDM, at the expense of 33 additional parameters in the fit, with dark energy contributing significantly between $z \sim 10^4 - 10^5$, and intriguingly with a sound speed $c_s^2 \sim 1/3$. A significant part of the $Δχ^2$ improvement comes from \Planck\ + Atacama Cosmology Telescope (\textsc{Act}) data, alleviating tension between them within LCDM. We apply a correlation prior to penalise models with unnecessary degrees of freedom and find no preference for deviations from LCDM at late-times, but moderate Bayesian evidence of an early dark energy (EDE) component. Although the model has a large amount of freedom, it is unable to reduce $S_8 \equiv σ_8 (Ω_\mathrm{c} / 0.3)^{0.5}$ below that of \lcdm, to bring about full concordance with large-scale structure data.

astro-ph.CO

Constraints on primordial gravitational waves from the Cosmic Microwave Background

Searches for primordial gravitational waves have resulted in constraints in a large frequency range from a variety of sources. The standard Cosmic Microwave Background (CMB) technique is to parameterise the tensor power spectrum in terms of the tensor-to-scalar ratio, $r$, and spectral index, $n_{\rm t}$, and constrain these using measurements of the temperature and polarization power spectra. Another method, applicable to modes well inside the cosmological horizon at recombination, uses the shortwave approximation, under which gravitational waves behave as an effective neutrino species. In this paper we give model-independent CMB constraints on the energy density of gravitational waves, $Ω_\textrm{gw} h^2$, for the entire range of observable frequencies. On large scales, $f \lesssim 10^{-16}\, \text{Hz}$, we reconstruct the initial tensor power spectrum in logarithmic frequency bins, finding maximal sensitivity for scales close to the horizon size at recombination. On small scales, $f \gtrsim10^{-15}\,\mbox{Hz}$, we use the shortwave approximation, finding $Ω_\textrm{gw} h^2 < 1.7 \times10^{-6}$ for adiabatic initial conditions and $Ω_\textrm{gw} h^2 < 2.9 \times10^{-7}$ for homogeneous initial conditions (both $2σ$ upper limits). For scales close to the horizon size at recombination, we use second-order perturbation theory to calculate the back-reaction from gravitational waves, finding $Ω_\textrm{gw} h^2 < 8.4 \times10^{-7}$, in the absence of neutrino anisotropic stress and $Ω_\textrm{gw} h^2 < 8.6 \times10^{-7}$ when including neutrino anisotropic stress. These constraints are valid for $ 10^{-15}\, \text{Hz} \gtrsim f \gtrsim 3 \times 10^{-16}\, \text{Hz}$.

astro-ph.CO

A Deep Learning Functional Estimator of Optimal Dynamics for Sampling Large Deviations

In stochastic systems, numerically sampling the relevant trajectories for the estimation of the large deviation statistics of time-extensive observables requires overcoming their exponential (in space and time) scarcity. The optimal way to access these rare events is by means of an auxiliary dynamics obtained from the original one through the so-called ``generalised Doob transformation''. While this optimal dynamics is guaranteed to exist its use is often impractical, as to define it requires the often impossible task of diagonalising a (tilted) dynamical generator. While approximate schemes have been devised to overcome this issue they are difficult to automate as they tend to require knowledge of the systems under study. Here we address this problem from the perspective of deep learning. We devise an iterative semi-supervised learning scheme which converges to the optimal or Doob dynamics with the clear advantage of requiring no prior knowledge of the system. We test our method in a paradigmatic statistical mechanics model with non-trivial dynamical fluctuations, the fully packed classical dimer model on the square lattice, showing that it compares favourably with more traditional approaches. We discuss broader implications of our results for the study of rare dynamical trajectories.

cond-mat.stat-mech

Accelerated Bayesian inference using deep learning

We present a novel Bayesian inference tool that uses a neural network to parameterise efficient Markov Chain Monte-Carlo (MCMC) proposals. The target distribution is first transformed into a diagonal, unit variance Gaussian by a series of non-linear, invertible, and non-volume preserving flows. Neural networks are extremely expressive, and can transform complex targets to a simple latent representation. Efficient proposals can then be made in this space, and we demonstrate a high degree of mixing on several challenging distributions. Parameter space can naturally be split into a block diagonal speed hierarchy, allowing for fast exploration of subspaces where it is inexpensive to evaluate the likelihood. Using this method, we develop a nested MCMC sampler to perform Bayesian inference and model comparison, finding excellent performance on highly curved and multi-modal analytic likelihoods. We also test it on {\em Planck} 2015 data, showing accurate parameter constraints, and calculate the evidence for simple one-parameter extensions to LCDM in $\sim20$ dimensional parameter space. Our method has wide applicability to a range of problems in astronomy and cosmology.

astro-ph.CO

Improved Photometric Classification of Supernovae using Deep Learning

We present improved photometric supernovae classification using deep recurrent neural networks. The main improvements over previous work are (i) the introduction of a time gate in the recurrent cell that uses the observational time as an input; (ii) greatly increased data augmentation including time translation, addition of Gaussian noise and early truncation of the lightcurve. For post Supernovae Photometric Classification Challenge (SPCC) data, using a training fraction of $5.2\%$ (1103 supernovae) of a representational dataset, we obtain a type Ia vs. non type Ia classification accuracy of $93.2 \pm 0.1\%$, a Receiver Operating Characteristic curve AUC of $0.980 \pm 0.002$ and a SPCC figure-of-merit of $F_1=0.57 \pm 0.01$. Using a representational dataset of $50\%$ ($10660$ supernovae), we obtain a classification accuracy of $96.6 \pm 0.1\%$, an AUC of $0.995 \pm 0.001$ and $F_1=0.76 \pm 0.01$. We found the non-representational training set of the SPCC resulted in a large degradation in performance due to a lack of faint supernovae, but this can be migrated by the introduction of only a small number ($\sim 100$) of faint training samples. We also outline ways in which this could be achieved using unsupervised domain adaptation.

astro-ph.IM

The shape dependence of chameleon screening

Chameleon scalar fields can screen their associated fifth forces from detection by changing their mass with the local density. These models are an archetypal example of a screening mechanism, and have become an important target for both cosmological surveys and terrestrial experiments. In particular there has been much recent interest in searching for chameleon fifth forces in the laboratory. It is known that the chameleon force is less screened around non-spherical sources, but only the field profiles around a few simple shapes are known analytically. In this work we introduce a numerical code that solves for the chameleon field around arbitrary shapes with azimuthal symmetry placed in a spherical vacuum chamber. We find that deviations from spherical symmetry can increase the chameleon acceleration experienced by a test particle by up to a factor of $\sim 3$, and that the least screened objects are those which minimize some internal dimension.

astro-ph.CO

Deep Recurrent Neural Networks for Supernovae Classification

We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae\footnote{Code available at \href{https://github.com/adammoss/supernovae}{https://github.com/adammoss/supernovae}}. The observational time and filter fluxes are used as inputs to the network, but since the inputs are agnostic additional data such as host galaxy information can also be included. Using the Supernovae Photometric Classification Challenge (SPCC) data, we find that deep networks are capable of learning about light curves, however the performance of the network is highly sensitive to the amount of training data. For a training size of 50\% of the representational SPCC dataset (around $10^4$ supernovae) we obtain a type-Ia vs. non-type-Ia classification accuracy of 94.7\%, an area under the Receiver Operating Characteristic curve AUC of 0.986 and a SPCC figure-of-merit $F_1=0.64$. When using only the data for the early-epoch challenge defined by the SPCC we achieve a classification accuracy of 93.1\%, AUC of 0.977 and $F_1=0.58$, results almost as good as with the whole light-curve. By employing bidirectional neural networks we can acquire impressive classification results between supernovae types -I,~-II and~-III at an accuracy of 90.4\% and AUC of 0.974. We also apply a pre-trained model to obtain classification probabilities as a function of time, and show it can give early indications of supernovae type. Our method is competitive with existing algorithms and has applications for future large-scale photometric surveys.

astro-ph.IM