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  1. With the recent success of representation learning methods, which includes deep learning as a special case, there has been considerable interest in developing techniques that incorporate known physical constraints into the learned representation. As one example, in many applications that involve a signal propagating through physical media (e.g., optics, acoustics, fluid dynamics, etc.), it is known that the dynamics of the signal must satisfy constraints imposed by the wave equation. Here we propose a matrix factorization technique that decomposes such signals into a sum of components, where each component is regularized to ensure that it nearly satisfies wave equation constraints. Although our proposed formulation is non-convex, we prove that our model can be efficiently solved to global optimality. Through this line of work we establish theoretical connections between wave-informed learning and filtering theory in signal processing. We further demonstrate the application of this work on modal analysis problems commonly arising in structural diagnostics and prognostics. 
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    Free, publicly-accessible full text available January 1, 2025
  2. ABSTRACT

    The circum-galactic medium (CGM) can feasibly be mapped by multiwavelength surveys covering broad swaths of the sky. With multiple large data sets becoming available in the near future, we develop a likelihood-free Deep Learning technique using convolutional neural networks (CNNs) to infer broad-scale physical properties of a galaxy’s CGM and its halo mass for the first time. Using CAMELS (Cosmology and Astrophysics with MachinE Learning Simulations) data, including IllustrisTNG, SIMBA, and Astrid models, we train CNNs on Soft X-ray and 21-cm (H i) radio two-dimensional maps to trace hot and cool gas, respectively, around galaxies, groups, and clusters. Our CNNs offer the unique ability to train and test on ‘multifield’ data sets comprised of both H i and X-ray maps, providing complementary information about physical CGM properties and improved inferences. Applying eRASS:4 survey limits shows that X-ray is not powerful enough to infer individual haloes with masses log (Mhalo/M⊙) < 12.5. The multifield improves the inference for all halo masses. Generally, the CNN trained and tested on Astrid (SIMBA) can most (least) accurately infer CGM properties. Cross-simulation analysis – training on one galaxy formation model and testing on another – highlights the challenges of developing CNNs trained on a single model to marginalize over astrophysical uncertainties and perform robust inferences on real data. The next crucial step in improving the resulting inferences on the physical properties of CGM depends on our ability to interpret these deep-learning models.

     
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  3. Abstract

    Quenching of star formation in the central galaxies of cosmological halos is thought to result from energy released as gas accretes onto a supermassive black hole. The same energy source also appears to lower the central density and raise the cooling time of baryonic atmospheres in massive halos, thereby limiting both star formation and black hole growth, by lifting the baryons in those halos to greater altitudes. One predicted signature of that feedback mechanism is a nearly linear relationship between the central black hole’s mass (MBH) and the original binding energy of the halo’s baryons. We present the increasingly strong observational evidence supporting a such a relationship, showing that it extends up to halos of massMhalo∼ 1014M. We then compare current observational constraints on theMBHMhalorelation with numerical simulations, finding that black hole masses in IllustrisTNG appear to exceed those constraints atMhalo< 1013Mand that black hole masses in EAGLE fall short of observations atMhalo∼ 1014M. A closer look at IllustrisTNG shows that quenching of star formation and suppression of black hole growth do indeed coincide with black hole energy input that lifts the halo’s baryons. However, IllustrisTNG does not reproduce the observedMBHMhalorelation because its black holes gain mass primarily through accretion that does not contribute to baryon lifting. We suggest adjustments to some of the parameters in the IllustrisTNG feedback algorithm that may allow the resulting black hole masses to reflect the inherent links between black hole growth, baryon lifting, and star formation among the massive galaxies in those simulations.

     
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  4. Ultrafast affinity extraction (UAE) is a form of microscale affinity HPLC that can be employed to quickly measure equilibrium constants for solute-binding agent interactions in solution. This study used chromatographic and equilibrium theory with universal plots to examine the general conditions that are needed in UAE to obtain accurate, precise, and robust measurements of equilibrium constants for such interactions. The predicted results were compared to those obtained by UAE in studies that examined the binding of various drugs with two transport proteins: human serum albumin and α1-acid glycoprotein. The most precise and robust conditions for these binding studies occurred for systems with intermediate values for their equilibrium free fraction for the solute (F0 ≈ 0.20-0.80). These trends showed good agreement with those seen in prior studies using UAE. It was further determined how the apparent free fraction of a solute was related to the dissociation rate of this solute, the time allowed for solute dissociation during UAE, and the equilibrium free fraction for the solute. These results also agreed with experimental results, as obtained for the binding of warfarin and gliclazide with human serum albumin. The final section examined how a change in the apparent free fraction, as caused by solute dissociation, affected the accuracy of an equilibrium constant that was measured by UAE. In addition, theoretical plots were generated to allow the selection of conditions for UAE that provided a given level of accuracy during the measurement of an equilibrium constant. The equations created and trends identified for UAE were general ones that can be extended in future work to other solutes and binding agents. 
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    Free, publicly-accessible full text available September 1, 2024
  5. Abstract

    Dwarf galaxies are found to have lost most of their metals via feedback processes; however, there still lacks consistent assessment on the retention rate of metals in their circumgalactic medium (CGM). Here we investigate the metal content in the CGM of 45 isolated dwarf galaxies withM*= 106.5–9.5M(M200m= 1010.0–11.5M) using the Hubble Space Telescope/Cosmic Origins Spectrograph. While Hi(Lyα) is ubiquitously detected (89%) within the CGM, we find low detection rates (≈5%–22%) in Cii, Civ, Siii, Siiii, and Siiv, largely consistent with literature values. Assuming these ions form in the cool (T≈ 104K) CGM with photoionization equilibrium, the observed Hiand metal column density profiles can be best explained by an empirical model with low gas density and high volume filling factor. For a typical galaxy withM200m= 1010.9M(median of the sample), our model predicts a cool gas mass ofMCGM,cool∼ 108.4M, corresponding to ∼2% of the galaxy’s baryonic budget. Assuming a metallicity of 0.3 Z, we estimate that the dwarf galaxy’s cool CGM likely harbors ∼10% of the metals ever produced, with the rest either in more ionized states in the CGM or transported to the intergalactic medium. We further examine the EAGLE simulation and show that Hiand low ions may arise from a dense cool medium, while Civarises from a diffuse warmer medium. Our work provides the community with a uniform data set on dwarf galaxies’ CGM that combines our recent observations, additional archival data and literature compilation, which can be used to test various theoretical models of dwarf galaxies.

     
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  6. Abstract

    In this work, we investigate how the complex structure found in solar wind proton velocity distribution functions (VDFs), rather than the commonly assumed two-component bi-Maxwellian structure, affects the onset and evolution of parallel-propagating microinstabilities. We use theArbitrary Linear Plasma Solver, a numerical dispersion solver, to find the real frequencies and growth/damping rates of the Alfvén modes calculated for proton VDFs extracted from Wind spacecraft observations of the solar wind. We compare this wave behavior to that obtained by applying the same procedure to core-and-beam bi-Maxwellian fits of the Wind proton VDFs. We find several significant differences in the plasma waves obtained for the extracted data and bi-Maxwellian fits, including a strong dependence of the growth/damping rate on the shape of the VDF. By applying the quasilinear diffusion operator to these VDFs, we pinpoint resonantly interacting regions in velocity space where differences in VDF structure significantly affect the wave growth and damping rates. This demonstration of the sensitive dependence of Alfvén mode behavior on VDF structure may explain why the Alfvén ion-cyclotron instability thresholds predicted by linear theory for bi-Maxwellian models of solar wind proton background VDFs do not entirely constrain spacecraft observations of solar wind proton VDFs, such as those made by the Wind spacecraft.

     
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  7. Abstract

    Ticks are blood-feeding arthropods responsible for the transmission of disease-causing pathogens to a wide range of vertebrate hosts, including livestock and humans. Tick-borne diseases have been implicated in significant economic losses to livestock production, and this threat will increase as these obligate parasites widen their geographical ranges. Similar to other ectotherms, thermal stress due to changing global temperatures has been shown to influence tick survival and distribution. However, studies on the influence of extreme temperatures in ticks have focused on advanced, mobile stages, ignoring immobile stages that cannot move to more favorable microhabitats. In this study, low- and high-temperature regimens were assessed in relation to egg viability for hard tick species—Amblyomma maculatum (Gulf Coast tick), Ixodes scapularis (black-legged tick), Dermacentor variabilis (American dog tick), and Rhipicephalus sanguineus (Brown dog tick). Tick eggs exposed early in development (freshly laid during early embryo development) were significantly more susceptible to thermal stress when compared with those exposed later in development (late embryo development denoted by a fecal spot). Based on our studies, differences in egg hatching success among treatments were greater than in hatching success when comparing species. Lastly, there was evidence of extreme thermal exposure significantly altering the hatching times of tick eggs for specific treatments. These results provide insights into the critical period for tick egg viability in relation to thermal exposure and tick survival associated with stress and climate change.

     
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  8. Free, publicly-accessible full text available June 1, 2024
  9. Free, publicly-accessible full text available October 1, 2024
  10. Abstract

    Graph matching algorithms attempt to find the best correspondence between the nodes of two networks. These techniques have been used to match individual neurons in nanoscale connectomes—in particular, to find pairings of neurons across hemispheres. However, since graph matching techniques deal with two isolated networks, they have only utilized the ipsilateral (same hemisphere) subgraphs when performing the matching. Here, we present a modification to a state-of-the-art graph matching algorithm that allows it to solve what we call the bisected graph matching problem. This modification allows us to leverage the connections between the brain hemispheres when predicting neuron pairs. Via simulations and experiments on real connectome datasets, we show that this approach improves matching accuracy when sufficient edge correlation is present between the contralateral (between hemisphere) subgraphs. We also show how matching accuracy can be further improved by combining our approach with previously proposed extensions to graph matching, which utilize edge types and previously known neuron pairings. We expect that our proposed method will improve future endeavors to accurately match neurons across hemispheres in connectomes, and be useful in other applications where the bisected graph matching problem arises.

     
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