Search

Scaling laws for large language models (LLMs) have provided useful guidance on how to train ever larger models for predictable performance gains. Time series forecasting shares a similar sequential structure to language, and is amenable to large-scale transformer architectures. Here we show that foundational decoder-only time series transformer models exhibit analogous scaling-behavior to LLMs, while architectural details (aspect ratio and number of heads) have a minimal effect over broad ranges. We assemble a large corpus of heterogenous time series data on which to train, and establish, for the first time, power-law scaling relations with respect to parameter count, dataset size, and training compute, spanning five orders of magnitude., Comment: 8 pages, 3 figures

We present a framework for the efficient computation of optimal Bayesian decisions under intractable likelihoods, by learning a surrogate model for the expected utility (or its distribution) as a function of the action and data spaces. We leverage recent advances in simulation-based inference and Bayesian optimization to develop active learning schemes to choose where in parameter and action spaces to simulate. This allows us to learn the optimal action in as few simulations as possible. The resulting framework is extremely simulation efficient, typically requiring fewer model calls than the associated posterior inference task alone, and a factor of $100-1000$ more efficient than Monte-Carlo based methods. Our framework opens up new capabilities for performing Bayesian decision making, particularly in the previously challenging regime where likelihoods are intractable, and simulations expensive., Comment: 12 pages, 4 figures

We investigate the possibility of improving the accuracy of the phenomenological waveform model, IMRPhenomD, by jointly optimizing all the calibration coefficients at once, given a set of numerical relativity (NR) waveforms. When IMRPhenomD was first calibrated to NR waveforms, different parts (i.e., the inspiral, merger, and ringdown) of the waveform were calibrated separately. Using ripple, a library of waveform models compatible with automatic differentiation, we can, for the first time, perform gradient-based optimization on all the waveform coefficients at the same time. This joint optimization process allows us to capture previously ignored correlations between separate parts of the waveform. We found that after recalibration, the median mismatch between the model and NR waveforms decreases by 50%. We further explore how different regions of the source parameter space respond to the optimization procedure. We find that the degree of improvement correlates with the spins of the source. This work shows a promising avenue to help understand and treat systematic error in waveform models., Comment: 11 pages, 9 figures

We report results on the first matched-filtering search for binaries with compact objects having large tidal deformabilities in the LIGO-Virgo gravitational wave (GW) data. The tidal deformability of a body is quantified by the ``Love number" $\Lambda \propto \hskip 1pt (r/m)^5$, where $r/m$ is the body's (inverse) compactness. Due to its strong dependence on compactness, the $\Lambda$ of larger-sized compact objects can easily be many orders of magnitude greater than those of black holes and neutron stars, leaving phase shifts which are sufficiently large for these binaries to be missed by binary black hole (BBH) templated searches. In this paper, we conduct a search using inspiral-only waveforms with zero spins but finite tides, with the search space covering chirp masses $3 M_\odot < \mathcal{M} < 15 M_\odot$ and effective tidal deformabilities $10^2 \lesssim \tilde{\Lambda} \lesssim 10^6$. We find no statistically significant GW candidates. This null detection implies an upper limit on the merger rate of such binaries in the range $[1-300] \hskip 2pt \text{Gpc}^{-3} \text{year}^{-1}$, depending on $\mathcal{M}$ and $\tilde{\Lambda}$. While our constraints are model agnostic, we discuss the implications on beyond the Standard Model scenarios that give rise to boson stars and superradiant clouds. Using inspiral-only waveforms we recover many of the BBH signals which were previously identified with full inspiral-merger-ringdown templates. We also constrain the Love number of black holes to $\Lambda \lesssim 10^3$ at the 90\% credible interval. Our work is the first-ever dedicated template-based search for compact objects that are not only black holes and neutron stars. Additionally, our work demonstrates a novel way of finding new physics in GW data, widening the scope of potential discovery to previously unexplored parameter space., Comment: 42+11 pages, 12 figures

We present a lightweight, flexible, and high-performance framework for inferring the properties of gravitational-wave events. By combining likelihood heterodyning, automatically-differentiable and accelerator-compatible waveforms, and gradient-based Markov chain Monte Carlo (MCMC) sampling enhanced by normalizing flows, we achieve full Bayesian parameter estimation for real events like GW150914 and GW170817 within a minute of sampling time. Our framework does not require pretraining or explicit reparameterizations and can be generalized to handle higher dimensional problems. We present the details of our implementation and discuss trade-offs and future developments in the context of other proposed strategies for real-time parameter estimation. Our code for running the analysis is publicly available on GitHub https://github.com/kazewong/jim.

We propose the use of automatic differentiation through the programming framework jax for accelerating a variety of analysis tasks throughout gravitational wave (GW) science. Firstly, we demonstrate that complete waveforms which cover the inspiral, merger, and ringdown of binary black holes (i.e. IMRPhenomD) can be written in jax and demonstrate that the serial evaluation speed of the waveform (and its derivative) is similar to the lalsuite implementation in C. Moreover, jax allows for GPU-accelerated waveform calls which can be over an order of magnitude faster than serial evaluation on a CPU. We then focus on three applications where efficient and differentiable waveforms are essential. Firstly, we demonstrate how gradient descent can be used to optimize the $\sim 200$ coefficients that are used to calibrate the waveform model. In particular, we demonstrate that the typical match with numerical relativity waveforms can be improved by more than 50% without any additional overhead. Secondly, we show that Fisher forecasting calculations can be sped up by $\sim 100\times$ (on a CPU) with no loss in accuracy. This increased speed makes population forecasting substantially simpler. Finally, we show that gradient-based samplers like Hamiltonian Monte Carlo lead to significantly reduced autocorrelation values when compared to traditional Monte Carlo methods. Since differentiable waveforms have substantial advantages for a variety of tasks throughout GW science, we propose that waveform developers use jax to build new waveforms moving forward. Our waveform code, ripple, can be found at https://github.com/tedwards2412/ripple, and will continue to be updated with new waveforms as they are implemented., Comment: 12 pages, 6 figures, code can be found at https://github.com/tedwards2412/ripple

Minerals are solid state nuclear track detectors - nuclear recoils in a mineral leave latent damage to the crystal structure. Depending on the mineral and its temperature, the damage features are retained in the material from minutes (in low-melting point materials such as salts at a few hundred degrees C) to timescales much larger than the 4.5 Gyr-age of the Solar System (in refractory materials at room temperature). The damage features from the $O(50)$ MeV fission fragments left by spontaneous fission of $^{238}$U and other heavy unstable isotopes have long been used for fission track dating of geological samples. Laboratory studies have demonstrated the readout of defects caused by nuclear recoils with energies as small as $O(1)$ keV. This whitepaper discusses a wide range of possible applications of minerals as detectors for $E_R \gtrsim O(1)$ keV nuclear recoils: Using natural minerals, one could use the damage features accumulated over $O(10)$ Myr$-O(1)$ Gyr to measure astrophysical neutrino fluxes (from the Sun, supernovae, or cosmic rays interacting with the atmosphere) as well as search for Dark Matter. Using signals accumulated over months to few-years timescales in laboratory-manufactured minerals, one could measure reactor neutrinos or use them as Dark Matter detectors, potentially with directional sensitivity. Research groups in Europe, Asia, and America have started developing microscopy techniques to read out the $O(1) - O(100)$ nm damage features in crystals left by $O(0.1) - O(100)$ keV nuclear recoils. We report on the status and plans of these programs. The research program towards the realization of such detectors is highly interdisciplinary, combining geoscience, material science, applied and fundamental physics with techniques from quantum information and Artificial Intelligence., Comment: 115 pages, many pictures of tracks. Please see the source file for higher resolution versions of some plots. v2: matches the published version

We present highly accurate, dimensionally-reduced gravitational waveforms for binary inspirals whose components have large spin-induced quadrupole moments. The spin-induced quadrupole of a body first appears in the phase of a waveform at the early inspiral stage of the binary coalescence, making it a relatively clean probe of the internal structure of the body. However, for objects with large quadrupolar deviations from Kerr, searches using binary black hole (BBH) models would be ineffective. In order to perform a computationally-feasible search, we present two dimensionally-reduced models which are derived from the original six-dimensional post-Newtonian waveform for such systems. Our dimensional reduction method is guided by power counting in the post-Newtonian expansion, suitable reparameterizations of the source physics, and truncating terms in the phase that are small in most physically well-motivated regions of parameter space. In addition, we note that large quadrupolar deviations cause the frequency at which a binary system reaches its minimum binding energy to be reduced substantially. This minimum signals the end of the inspiral regime and provides a natural cutoff for the PN waveform. We provide accurate analytic estimates for these frequency cutoffs. Finally, we perform injection studies to test the effectualness of the dimensionally reduced waveforms. We find that over $80\%$ of the injections have an effectualness of $\varepsilon > 0.999$, significantly higher than is typically required for standard BBH banks, for systems with component spins of $|\chi_i| \lesssim 0.6$ and dimensionless quadrupole of $\kappa_i \lesssim 10^3$. Importantly, these waveforms represent an essential first step towards enabling an effective search for astrophysical objects with large quadrupoles., Comment: 18 pages, 10 figures

We explore the assumption, widely used in many astrophysical calculations, that the stellar initial mass function (IMF) is universal across all galaxies. By considering both a canonical Salpeter-like IMF and a non-universal IMF, we are able to compare the effect of different IMFs on multiple observables and derived quantities in astrophysics. Specifically, we consider a non-universal IMF which varies as a function of the local star formation rate, and explore the effects on the star formation rate density (SFRD), the extragalactic background light, the supernova (both core-collapse and thermonuclear) rates, and the diffuse supernova neutrino background. Our most interesting result is that our adopted varying IMF leads to much greater uncertainty on the SFRD at $z \approx 2-4$ than is usually assumed. Indeed, we find a SFRD (inferred using observed galaxy luminosity distributions) that is a factor of $\gtrsim 3$ lower than canonical results obtained using a universal Salpeter-like IMF. Secondly, the non-universal IMF we explore implies a reduction in the supernova core-collapse rate of a factor of $\sim2$, compared against a universal IMF. The other potential tracers are only slightly affected by changes to the properties of the IMF. We find that currently available data do not provide a clear preference for universal or non-universal IMF. However, improvements to measurements of the star formation rate and core-collapse supernova rate at redshifts $z \gtrsim 2$ may offer the best prospects for discernment., Comment: 15 pages, 11 figures, 1 appendix

The most sensitive search pipelines for gravitational waves from compact binary mergers use matched filters to extract signals from the noisy data stream coming from gravitational wave detectors. Matched-filter searches require banks of template waveforms covering the physical parameter space of the binary system. Unfortunately, template bank construction can be a time-consuming task. Here we present a new method for efficiently generating template banks that utilizes automatic differentiation to calculate the parameter space metric. Principally, we demonstrate that automatic differentiation enables accurate computation of the metric for waveforms currently used in search pipelines, whilst being computationally cheap. Additionally, by combining random template placement and a Monte Carlo method for evaluating the fraction of the parameter space that is currently covered, we show that search-ready template banks for frequency-domain waveforms can be rapidly generated. Finally, we argue that differentiable waveforms offer a pathway to accelerating stochastic placement algorithms. We implement all our methods into an easy-to-use Python package based on the jax framework, diffbank, to allow the community to easily take advantage of differentiable waveforms for future searches., Comment: 15 pages, 6 figures. Comments welcome! Code can be found at https://github.com/adam-coogan/diffbank. Updated to match PRD version

Microscale dynamic testing is vital to the understanding of material behavior at application relevant strain rates. However, despite two decades of intense micromechanics research, the testing of microscale metals has been largely limited to quasi-static strain rates. Here we report the dynamic compression testing of pristine 3D printed copper micropillars at strain rates from $\sim0.001$ s$^{-1}$ to $\sim500$ s$^{-1}$. It was identified that microcrystalline copper micropillars deform in a single-shear like manner exhibiting a weak strain rate dependence at all strain rates. Ultrafine grained (UFG) copper micropillars, however, deform homogenously via barreling and show strong rate-dependence and small activation volumes at strain rates up to $\sim0.1$ s$^{-1}$, suggesting dislocation nucleation as the deformation mechanism. At higher strain rates, yield stress saturates remarkably, resulting in a decrease of strain rate sensitivity by two orders of magnitude and a four-fold increase in activation volume, implying a transition in deformation mechanism to collective dislocation nucleation., Comment: Corresponding authors with equal contribution are: Szilvia Kal\'acska and Rajaprakash Ramachandramoorthy. Accepted manuscript: Applied Materials Today

Middle turbinate resection significantly alters the anatomy and redistributes the inhaled air. The superior half of the main nasal cavity is opened up, increasing accessibility to the region. This is expected to increase inhalation dosimetry to the region during exposure to airborne particles. This study investigated the influence of middle turbinate resection on the deposition of inhaled pollutants that cover spherical and non-spherical particles (e.g. pollen). A computational model of the nasal cavity from CT scans, and its corresponding post-operative model with virtual surgery performed was created. Two constant flow rates of 5_L/min, and 15_L/min were simulated under a laminar flow field. Inhaled particles including pollen (non-spherical), and a spherical particle with reference density of 1000 kg/m3 were introduced in the surrounding atmosphere. The effect of surgery was most prominent in the less patent cavity side, since the change in anatomy was proportionally greater relative to the original airway space. The left cavity produced an increase in particle deposition at a flow rate of 15_L/min. The main particle deposition mechanisms were inertial impaction, and to a lesser degree gravitational sedimentation. The results are expected to provide insight into inhalation efficiency of different aerosol types, and the likelihood of deposition in different nasal cavity surfaces.

Paleo-detectors are a proposed experimental technique to search for dark matter by reading out the damage tracks caused by nuclear recoils in small samples of natural minerals. Unlike a conventional real-time direct detection experiment, paleo-detectors have been accumulating these tracks for up to a billion years. These long integration times offer a unique possibility: by reading out paleo-detectors of different ages, one can explore the time-variation of signals on megayear to gigayear timescales. We investigate two examples of dark matter substructure that could give rise to such time-varying signals. First, a dark disk through which the Earth would pass every $\sim$45 Myr, and second, a dark matter subhalo that the Earth encountered during the past gigayear. We demonstrate that paleo-detectors are sensitive to these examples under a wide variety of experimental scenarios, even in the presence of substantial background uncertainties. This paper shows that paleo-detectors may hold the key to unraveling our Galactic history., Comment: 26 pages, 16 figures, 2 tables, code available at https://github.com/sbaum90/paleoSens and https://github.com/sbaum90/paleoSpec. Published version

Paleo-detectors are a proposed experimental technique to search for dark matter (DM). In lieu of the conventional approach of operating a tonne-scale real-time detector to search for DM-induced nuclear recoils, paleo-detectors take advantage of small samples of naturally occurring rocks on Earth that have been deep underground ($\gtrsim 5$ km), accumulating nuclear damage tracks from recoiling nuclei for $\mathcal{O}(1)$ Gyr. Modern microscopy techniques promise the capability to read out nuclear damage tracks with nanometer resolution in macroscopic samples. Thanks to their $\mathcal{O}(1)$ Gyr integration times, paleo-detectors could constitute nuclear recoil detectors with keV recoil energy thresholds and 100 kilotonne-yr exposures. This combination would allow paleo-detectors to probe DM-nucleon cross sections orders of magnitude below existing upper limits from conventional direct detection experiments. In this article, we use improved background modeling and a new spectral analysis technique to update the sensitivity forecast for paleo-detectors. We demonstrate the robustness of the sensitivity forecast to the (lack of) ancillary measurements of the age of the samples and the parameters controlling the backgrounds, systematic mismodeling of the spectral shape of the backgrounds, and the radiopurity of the mineral samples. Specifically, we demonstrate that even if the uranium concentration in paleo-detector samples is $10^{-8}$ (per weight), many orders of magnitude larger than what we expect in the most radiopure samples obtained from ultra basic rock or marine evaporite deposits, paleo-detectors could still probe DM-nucleon cross sections below current limits. For DM masses $\lesssim 10$ GeV/$c^2$, the sensitivity of paleo-detectors could still reach down all the way to the conventional neutrino floor in a Xe-based direct detection experiment., Comment: Invited contribution to Instruments "Special Issue Innovative Experimental Techniques for Direct Dark Matter Detection)". 30 pages, 5 figures, 1 table. Code available at https://github.com/sbaum90/paleoSpec and https://github.com/sbaum90/paleoSens

The most promising indirect search for the existence of axion dark matter uses radio telescopes to look for narrow spectral lines generated from the resonant conversion of axions in the magnetospheres of neutron stars. Unfortunately, a large list of theoretical uncertainties has prevented this search strategy from being fully accepted as robust. In this work we attempt to address major outstanding questions related to the role and impact of the plasma, including: $(i)$ does refraction and reflection of radio photons in the magnetosphere induce strong inhomogeneities in the flux, $(ii)$ can refraction induce premature axion-photon de-phasing, $(iii)$ to what extent do photon-plasma interactions induce a broadening of the spectral line, $(iv)$ does the flux have a strong time dependence, and $(v)$ can radio photons sourced by axions be absorbed by the plasma. We present an end-to-end analysis pipeline based on ray-tracing that exploits a state-of-the-art auto-differentiation algorithm to propagate photons from the conversion surface to asymptotically large distances. Adopting a charge symmetric Goldreich-Julian model for the magnetosphere, we show that for reasonable parameters one should expect a strong anisotropy of the signal, refraction induced axion-photon de-phasing, significant line-broadening, a variable time-dependence of the flux, and, for large enough magnetic fields, anisotropic absorption. Our simulation code is flexible enough to serve as the basis for follow-up studies with a large range of magnetosphere models., Comment: v3: Fix "?" citation. v2: Accepted for publication PRD. Convergence improved, plots updated, minor bugs and typos corrected. No major changes to results/conclusions. v1: 9 pages + Appendix

In recent years, there have been significant advances in multi-messenger astronomy due to the discovery of the first, and so far only confirmed, gravitational wave event with a simultaneous electromagnetic (EM) counterpart, as well as improvements in numerical simulations, gravitational wave (GW) detectors, and transient astronomy. This has led to the exciting possibility of performing joint analyses of the GW and EM data, providing additional constraints on fundamental properties of the binary progenitor and merger remnant. Here, we present a new Bayesian framework that allows inference of these properties, while taking into account the systematic modeling uncertainties that arise when mapping from GW binary progenitor properties to photometric light curves. We extend the relative binning method presented in Zackay et al. (2018) to include extrinsic GW parameters for fast analysis of the GW signal. The focus of our EM framework is on light curves arising from r-process nucleosynthesis in the ejected material during and after merger, the so called kilonova, and particularly on black hole - neutron star systems. As a case study, we examine the recent detection of GW190425, where the primary object is consistent with being either a black hole (BH) or a neutron star (NS). We show quantitatively how improved mapping between binary progenitor and outflow properties, and/or an increase in EM data quantity and quality are required in order to break degeneracies in the fundamental source parameters., Comment: 22 pages, 12 figures, comments are welcome

The QCD axion is expected to form dense structures known as axion miniclusters if the Peccei-Quinn symmetry is broken after inflation. Miniclusters that have survived until today will interact with neutron stars (NSs) in the Milky Way to produce transient radio signals from axion-photon conversion in the NS magnetosphere. We quantify the properties of these encounters and find that they occur frequently ($\mathcal{O}(1-100)\,\mathrm{day}^{-1}$); last between a day and a few months; are spatially clustered towards the Galactic center; and can reach observable fluxes. These radio transients are within reach of current generation telescopes and therefore offer a promising pathway to discovering QCD axion dark matter., Comment: 11 pages, 5 figures. Code is available online at https://github.com/bradkav/axion-miniclusters/ (archived at https://doi.org/10.5281/zenodo.4006128 ). Joint submission with "Stellar Disruption of Axion Miniclusters in the Milky Way" in astro-ph (arXiv:2011.05377). Updated to match published version

Axion miniclusters are dense bound structures of dark matter axions that are predicted to form in the post-inflationary Peccei-Quinn symmetry breaking scenario. Although dense, miniclusters can easily be perturbed or even become unbound by interactions with baryonic objects such as stars. Here, we characterize the spatial distribution and properties of miniclusters in the Milky Way (MW) today after undergoing these stellar interactions throughout their lifetime. We do this by performing a suite of Monte Carlo simulations which track the miniclusters' structure and, in particular, accounts for partial disruption and mass loss through successive interactions. We consider two density profiles - Navarro-Frenk-White (NFW) and Power-law (PL) - for the individual miniclusters in order to bracket the uncertainties on the minicluster population today due to their uncertain formation history. For our fiducial analysis at the Solar position, we find a survival probability of 99% for miniclusters with PL profiles and 46% for those with NFW profiles. Our work extends previous estimates of this local survival probability to the entire MW. We find that towards the Galactic center, the survival probabilities drop drastically. Although we present results for a particular initial halo mass function, our simulations can be easily recast to different models using the provided data and code. Finally, we comment on the impact of our results on lensing, direct, and indirect detection., Comment: 31 pages, 18 figures. Code available online at https://github.com/bradkav/axion-miniclusters/ (archived at https://doi.org/10.5281/zenodo.4006128 ). Joint submission w/ "Transient Radio Signatures from Neutron Star Encounters with QCD Axion Miniclusters", arXiv:2011.05378 . v2: Minor changes and references added. v3: Updated to match version published in PRD

We study whether binary black hole template banks can be used to search for the gravitational waves emitted by general binary coalescences. To recover binary signals from noisy data, matched-filtering techniques are typically required. This is especially true for low-mass systems, with total mass $M \lesssim 10 \, M_\odot$, which can inspiral in the LIGO and Virgo frequency bands for thousands of cycles. In this paper, we focus on the detectability of low-mass binary systems whose individual components can have large spin-induced quadrupole moments and small compactness. The quadrupole contributes to the phase evolution of the waveform whereas the compactness affects the merger frequency of the binary. We find that binary black hole templates (with dimensionless quadrupole $\kappa=1$) cannot be reliably used to search for objects with large quadrupoles ($\kappa\gtrsim 20$) over a wide range of parameter space. This is especially true if the general object is highly spinning and has a larger mass than its binary companion. A binary that consists of objects with small compactness could merge in the LIGO and Virgo frequency bands, thereby reducing its accumulated signal-to-noise ratio during the inspiraling regime. Template banks which include these more general waveforms must therefore be constructed. These extended banks would allow us to realistically search for the existence of new astrophysical and beyond the Standard Model compact objects., Comment: 16 pages, 5 figures. Additional figure added. Updated to match published version