arXiv subjects

Kyle Miller

Publications and source records attributed to Kyle Miller.

18 recordsLinked to original sources

arXiv2026

HUGO-CS: A Hybrid-Labeled, Uncertainty-Aware, General-Purpose, Observational Dataset for Cold Spray

Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However, process optimization remains difficult due to many interdependent parameters and the lack of large-scale, machine-readable data to support modeling. While the scientific literature contains many relevant experiments, results are inconsistently reported (often in tables and figures) and use non-uniform units, limiting utilization at scale. To address these limitations, this work presents HUGO-CS, a literature-derived dataset of 4,383 cold-spray experiments with 144 features from 1,124 sources, exceeding the previous largest dataset (137 samples) by 30x. With completely manual extraction requiring an average of 91 minutes per document, this work designs and leverages a Hybrid-labeled, Uncertainty-aware, General-purpose, Observational extraction framework, called HUGO, to support this extraction. HUGO combines automated LLM-based labeling with targeted manual label refinement to handle this experimental result extraction process from scientific literature. To balance labeling efficiency with extraction accuracy, HUGO introduces a Hierarchical Risk Mitigation (HRM) to route LLM outputs with a high risk of potential errors for manual review, while retaining low-risk records as auto-labeled. Lastly, HUGO post-processing consolidates categorical descriptors, maps reported feedstock chemistries into structured continuous compositions, and normalizes units across sources. Of the 4,383 reported experiments, 1,765 are hand-labeled, providing a high-quality labeled subset for benchmarking, error analysis, and higher-fidelity data points. All code to replicate this work, along with the complete HUGO-CS dataset, are released under a CC-BY license at https://github.com/sprice134/HUGO.

cs.LG↗

arXiv2026

Tidal alignment and tidal torquing modeling for the cosmic shear three-point correlation function and mass aperture skewness

We present a model for the intrinsic alignment contamination of the shear three-point correlation function and skewness of the mass aperture statistic using the tidal alignment and tidal torquing (TATT) formalism. We compute the intrinsic alignment bispectra components in terms of the TATT model parameters. We consider two effective field theory approaches in the literature, relate them to the TATT model parameters and an extension to TATT that includes the velocity-shear (VS) parameter. We compare the impact of changing between NLA, TATT, and TATT+VS on the theoretical computation of the 3PCF using the best fit parameters and tomographic redshift distributions from Dark Energy Survey Year 3. We find that the TATT model significantly impacts the skewed triangle configurations of the 3PCF. Additionally, including the higher-order effects from TATT can introduce opposite effects on the two-point function and on the mass aperture skewness, damping the signal of the former while boosting the signal of the latter. We argue that a joint 2PCF+3PCF analysis with the TATT model can help break the degeneracy between its model parameters and provide more robust constraints on both cosmology and intrinsic alignment amplitude parameters. We show that typical values of order unity for the intrinsic alignment parameters introduce differences of around $10\%$ between NLA and TATT predictions.

astro-ph.CO↗

arXiv2025

Photon Phase-Space Dynamics in a Plasma Wakefield Accelerator

Frequency up-shifting of laser light in a beam-driven plasma wakefield has the potential to provide high-intensity sources of short wavelength radiation. Simulations have demonstrated that a laser pulse can undergo large frequency shifts, limited only by the drive beam energy, when the plasma density is tailored to match the accelerating phase of the wake to the group velocity of the pulse. Here, we study the dynamical evolution of photons in the phase-space vicinity of the plasma wake-phase matching condition. Numerical calculations using a photon kinetic model are validated by direct comparison with full electromagnetic particle-in-cell simulations. These calculations form the basis of a linear theory of the photon dynamics which reveals several important results, including scalings for the properties of the witness pulse and a self-similar solution for the photon phase-space dynamics. One prediction of the theory is that the pulse can be compressed indefinitely with no lower bound on the duration. This predication suggests that photon acceleration can provide a novel source of sub-femtosecond, short wavelength radiation.

physics.plasm-ph↗

arXiv2025

Detection of the Cosmological 21 cm Signal in Auto-correlation at z ~ 1 with the Canadian Hydrogen Intensity Mapping Experiment

We present the first detection of the cosmological 21 cm intensity mapping signal in auto-correlation at z ~ 1 with the Canadian Hydrogen Intensity Mapping Experiment (CHIME). Using 94 nights of observation, we have measured the 21 cm auto-power spectrum over a frequency range from 608.2 MHz to 707.8 MHz (z = 1.34 to 1.01) at 0.4 h Mpc^-1 < k < 1.5 h Mpc^-1, with a detection significance of 12.5 sigma. Our analysis employs significant improvements to the CHIME data processing pipeline compared to previous work, including novel radio frequency interference (RFI) detection and masking algorithms, achromatic beamforming techniques, and foreground filtering before time averaging to minimize spectral leakage. We establish the robustness and reliability of our detection through a comprehensive suite of validation tests. We also measure the 21 cm signal in two independent sub-bands centered at z ~ 1.08 and z ~ 1.24 with detection significance of 8.7 sigma and 9.2 sigma, respectively. We briefly discuss the theoretical interpretation of these measurements in terms of a power spectrum model, deferring the details to a companion paper. This auto-power spectrum detection demonstrates CHIME's capability to probe large-scale structure through 21 cm intensity mapping without reliance on external galaxy surveys.

astro-ph.CO↗

arXiv2025

Baryonic Feedback across Halo Mass: Impact on the Matter Power Spectrum

Upcoming weak-lensing surveys will probe the matter distribution at a few percent level on nonlinear scales ($k>1\,{\rm h\,Mpc}^{-1}$) where baryonic feedback from galaxy formation modifies the clustering of matter. Using the IllustrisTNG hydrodynamical simulations, we quantify the mass and radial dependence of baryonic suppression of the matter power spectrum by selectively replacing matter around the center of halos out to a specified radius in the collisionless run with that around their full-physics counterparts. We find that group-scale halos with $\log M_{\rm 200m}/h^{-1}M_\odot \in[13, 14]$ dominate the suppression, contributing a large fraction of the total reduction in power at $k\sim2-30\,h\,{\rm Mpc}^{-1}$, with smaller suppression on either sides of this mass bin. Correctly reproducing the full suppression of the power spectrum requires accounting for matter redistribution (while enforcing mass conservation) beyond the virial radius of each halo. We show that the same group-scale regime produces the most detectable deviations in the weak gravitational lensing of background galaxies measured around foreground galaxy groups binned by mass or richness. Such a lensing signal could be a powerful observational test of feedback models together with SZ measurements. Our results motivate emulators that jointly predict the matter power spectrum and halo-matter cross-power spectrum including baryonic effects, enabling unbiased cosmological inference from small scales.

astro-ph.CO↗

arXiv2024

Galaxy cluster profiles: A Gaussian mixture model approach to halo miscentering

Measurements of the galaxy density and weak-lensing profiles of galaxy clusters typically rely on an assumed cluster center, which is taken to be the brightest cluster galaxy or other proxies for the true halo center. Departure of the assumed cluster center from the true halo center bias the resultant profile measurements, an effect known as miscentering bias. Currently, miscentering is typically modeled in stacked profiles of clusters with a two parameter model. We use an alternate approach in which the profiles of individual clusters are used with the corresponding likelihood computed using a Gaussian mixture model. We test the approach using halos and the corresponding subhalo profiles from the IllustrisTNG hydrodynamic simulations. We obtain significantly improved estimates of the miscentering parameters for both 3D and projected 2D profiles relevant for imaging surveys. We discuss applications to upcoming cosmological surveys.

astro-ph.IM↗

arXiv2024

Demonstration of hybrid foreground removal on CHIME data

The main challenge of 21 cm cosmology experiments is astrophysical foregrounds which are difficult to separate from the signal due to telescope systematics. An earlier study has shown that foreground residuals induced by antenna gain errors can be estimated and subtracted using the hybrid foreground residual subtraction (HyFoReS) technique which relies on cross-correlating linearly filtered data. In this paper, we apply a similar technique to the CHIME stacking analysis to subtract beam-induced foreground contamination. Using a linear high-pass delay filter for foreground suppression, the CHIME collaboration reported a $11.1\sigma$ detection in the 21 cm signal stacked on eBOSS quasar locations, despite foreground residual contamination mostly due to the instrument chromatic transfer function. We cross-correlate the foreground-dominated data at low delay with the contaminated signal at high delay to estimate residual foregrounds and subtract them from the signal. We find foreground residual subtraction can improve the signal-to-noise ratio of the stacked 21 cm signal by $ 10 - 20\%$ after the delay foreground filter, although some of the improvement can also be achieved with an alternative flagging technique. We have shown that it is possible to use HyFoReS to reduce beam-induced foreground contamination, benefiting the analysis of the HI auto power spectrum with CHIME and enabling the recovery of large scale modes.

astro-ph.CO↗

arXiv2023

On the generation of attosecond gigawatt soft X-ray pulses through coherent Thomson backscattering

Collision between relativistic electron sheets and counter-propagating laser pulses is recognized as a promising way to produce intense attosecond X-rays through coherent Thomson backscattering (TBS). In a double-layer scheme, the electrons in an ultrathin solid foil are first pushed out by an intense laser driver and then interact with the laser reflected off a second foil to form a high-density relativistic electron sheet with vanishing transverse momentum. However, the repulsion between these concentrated electrons can increase the thickness of the layer, reducing both its density and subsequently the coherent TBS. Here, we present a systematic study on the evolution of the flying electron layer and find that its resulting thickness is determined by the interplay between the intrinsic space-charge expansion and the velocity compression induced by the drive laser. How the laser driver, the target areal density, the reflector and the collision laser intensity affect the properties of the produced X-rays is explored. Multi-dimensional particle-in-cell simulations indicate that employing this scheme in the nonlinear regime has the potential to stably produce soft X-rays with several GW peak power in hundreds of TW ultrafast laser facilities. The pulse duration can be tuned to tens of attoseconds. This compact and intense attosecond X-ray source may have broad applications in attosecond science.

physics.plasm-ph↗

arXiv2023

On the generation of ultra-bright and low energy spread electron beams in laser wakefield acceleration in a uniform plasma

The quality of electron beams produced from plasma-based accelerators, i.e., normalized brightness and energy spread, has made transformative progress in the past several decades in both simulation and experiment. Recently, full-scale particle-in-cell (PIC) simulations have shown that electron beams with unprecedented brightness ($10^{20}\sim10^{21}~\mathrm{A}/\mathrm{m}^2/\mathrm{rad}^2$) and $0.1\sim 1$ MeV energy spread can be produced through controlled injection in a slowly expanding bubble that arises when a particle beam or laser pulse propagates in density gradient, or when a particle beam self-focuses in uniform plasma or has a superluminal flying focus. However, in previous simulations of work on self-injection triggered by an evolving laser driver in a uniform plasma, the resulting beams did not exhibit comparable brightnesses and energy spreads. Here, we demonstrate through the use of large-scale high-fidelity PIC simulations that a slowly expanding bubble driven by a laser pulse in a uniform plasma can indeed produce self-injected electron beams with similar brightnesses and energy spreads as for an evolving bubble driven by an electron beam driver. We consider laser spot sizes roughly equal to the matched spot sizes in a uniform plasma and find that the evolution of the bubble occurs naturally through the evolution of the laser. The effects of the electron beam quality on the choice of physical as well as numerical parameters, e.g. grid sizes and field solvers used in the PIC simulations are presented. It is found that this original and simplest injection scheme can produce electron beams with beam quality exceeding that of the more recent concepts.

physics.acc-ph↗

arXiv2021

Structure of the Source I disk in Orion-KL

This paper analyses images from 43 to 340 GHz to trace the structure of the Source I disk in Orion-KL with $\sim$12 AU resolution. The data reveal an almost edge-on disk with an outside diameter $\sim$ 100 AU which is heated from the inside. The high opacity at 220-340 GHz hides the internal structure and presents a surface temperature $\sim$500 K. Images at 43, 86 and 99 GHz reveal structure within the disk. At 43 GHz there is bright compact emission with brightness temperature $\sim$1300 K. Another feature, most prominent at 99 GHz, is a warped ridge of emission. The data can be explained by a simple model with a hot inner structure, seen through cooler material. A wide angle outflow mapped in SiO emission ablates material from the interior of the disk, and extends in a bipolar outflow over 1000 AU along the rotation axis of the disk. SiO $v=0$ $J=5-4$ emission appears to have a localized footprint in the warped ridge. These observations suggest that the ridge is the working surface of the disk, and heated by accretion and the outflow. The disk structure may be evolving, with multiple accretion and outflow events. We discuss two sources of variability: 1) variable accretion onto the disk as Source I travels through the filamentary debris from the BN-Source I encounter $\sim$550 yr ago; and 2) episodic accretion from the disk onto the protostar which may trigger multiple outflows. The warped inner disk structure is direct evidence that SrcI could be a binary experiencing episodic accretion.

astro-ph.GA↗

arXiv2020

Generation and acceleration of high brightness electrons beams bunched at X-ray wavelengths using plasma-based acceleration

We show using particle-in-cell (PIC) simulations and theoretical analysis that a high-quality electron beam whose density is modulated at angstrom scales can be generated directly using density downramp injection in a periodically modulated density in nonlinear plasma wave wakefields. The density modulation turns on and off the injection of electrons at the period of the modulation. Due to the unique longitudinal mapping between the electrons' initial positions and their final trapped positions inside the wake, this results in an electron beam with density modulation at a wavelength orders of magnitude shorter than the plasma density modulation. The ponderomotive force of two counter propagating lasers of the same frequency can generate a density modulation at half the laser wavelength. Assuming a laser wavelength of $0.8\micro\meter$, fully self-consistent OSIRIS PIC simulations show that this scheme can generate high quality beams modulated at wavelengths between 10s and 100 angstroms. Such beams could produce fully coherent, stable, hundreds of GW X-rays by going through a resonant undulator.

physics.acc-ph↗

arXiv2020

System-Level Predictive Maintenance: Review of Research Literature and Gap Analysis

This paper reviews current literature in the field of predictive maintenance from the system point of view. We differentiate the existing capabilities of condition estimation and failure risk forecasting as currently applied to simple components, from the capabilities needed to solve the same tasks for complex assets. System-level analysis faces more complex latent degradation states, it has to comprehensively account for active maintenance programs at each component level and consider coupling between different maintenance actions, while reflecting increased monetary and safety costs for system failures. As a result, methods that are effective for forecasting risk and informing maintenance decisions regarding individual components do not readily scale to provide reliable sub-system or system level insights. A novel holistic modeling approach is needed to incorporate available structural and physical knowledge and naturally handle the complexities of actively fielded and maintained assets.

cs.AI↗

arXiv2019

L-space knots with tunnel number >1 by experiment

In Dunfield's catalog of the hyperbolic manifolds in the SnapPy census which are complements of L-space knots in $S^3$, we determine that $22$ have tunnel number $2$ while the remaining all have tunnel number $1$. Notably, these $22$ manifolds contain $9$ asymmetric L-space knot complements. Furthermore, using SnapPy and KLO we find presentations of these $22$ knots as closures of positive braids that realize the Morton-Franks-Williams bound on braid index. The smallest of these has genus $12$ and braid index $4$.

math.GT↗

arXiv2017

Characterization of Hemodynamic Signal by Learning Multi-View Relationships

Multi-view data are increasingly prevalent in practice. It is often relevant to analyze the relationships between pairs of views by multi-view component analysis techniques such as Canonical Correlation Analysis (CCA). However, data may easily exhibit nonlinear relations, which CCA cannot reveal. We aim to investigate the usefulness of nonlinear multi-view relations to characterize multi-view data in an explainable manner. To address this challenge, we propose a method to characterize globally nonlinear multi-view relationships as a mixture of linear relationships. A clustering method, it identifies partitions of observations that exhibit the same relationships and learns those relationships simultaneously. It defines cluster variables by multi-view rather than spatial relationships, unlike almost all other clustering methods. Furthermore, we introduce a supervised classification method that builds on our clustering method by employing multi-view relationships as discriminative factors. The value of these methods resides in their capability to find useful structure in the data that single-view or current multi-view methods may struggle to find. We demonstrate the potential utility of the proposed approach using an application in clinical informatics to detect and characterize slow bleeding in patients whose central venous pressure (CVP) is monitored at the bedside. Presently, CVP is considered an insensitive measure of a subject's intravascular volume status or its change. However, we reason that features of CVP during inspiration and expiration should be informative in early identification of emerging changes of patient status. We empirically show how the proposed method can help discover and analyze multiple-to-multiple correlations, which could be nonlinear or vary throughout the population, by finding explainable structure of operational interest to practitioners.

stat.ML↗

arXiv2017

Noise-Tolerant Interactive Learning from Pairwise Comparisons

We study the problem of interactively learning a binary classifier using noisy labeling and pairwise comparison oracles, where the comparison oracle answers which one in the given two instances is more likely to be positive. Learning from such oracles has multiple applications where obtaining direct labels is harder but pairwise comparisons are easier, and the algorithm can leverage both types of oracles. In this paper, we attempt to characterize how the access to an easier comparison oracle helps in improving the label and total query complexity. We show that the comparison oracle reduces the learning problem to that of learning a threshold function. We then present an algorithm that interactively queries the label and comparison oracles and we characterize its query complexity under Tsybakov and adversarial noise conditions for the comparison and labeling oracles. Our lower bounds show that our label and total query complexity is almost optimal.

stat.ML↗

arXiv2016

Do Public Events Affect Sex Trafficking Activity?

For several years the pervasive belief that the Super Bowl is the single biggest day for human trafficking in the United States each year has been perpetuated in popular press despite a lack of evidentiary support. The practice of relying on hearsay and popular belief for decision-making may result in misappropriation of resources in anti-trafficking efforts. We propose a data-driven approach to analyzing sex trafficking, especially as it is carried on during--and perhaps in response to--large public events such as the Super Bowl. We examine 33 public events, chosen for attendance numbers comparable to the Super Bowl from a diversity of types, and use the volume of escort advertisements posted online as an accessible and reasonable proxy measure for the actual levels of activity of sex-workers as well as trafficking victims. Our analysis puts the impact of local public events on sex advertisement activity into perspective. We find that many of the events we considered are not correlated with statistically significant impact on sex-worker advertising, though some are. Additionally, we demonstrate how our method can uncover evidence of other events, not included in our initial list, that are correlated with more significant increases in ad activity. Reliance on quantitative evidence accessible through data-driven analysis can inform wise resource allocation, guide good policies, and foster the most meaningful impact.

stat.AP↗

arXiv2015

An Entity Resolution approach to isolate instances of Human Trafficking online

Human trafficking is a challenging law enforcement problem, and a large amount of such activity manifests itself on various online forums. Given the large, heterogeneous and noisy structure of this data, building models to predict instances of trafficking is an even more convolved a task. In this paper we propose and entity resolution pipeline using a notion of proxy labels, in order to extract clusters from this data with prior history of human trafficking activity. We apply this pipeline to 5M records from backpage.com and report on the performance of this approach, challenges in terms of scalability, and some significant domain specific characteristics of our resolved entities.

cs.SI↗

arXiv2015

Performance Bounds for Pairwise Entity Resolution

One significant challenge to scaling entity resolution algorithms to massive datasets is understanding how performance changes after moving beyond the realm of small, manually labeled reference datasets. Unlike traditional machine learning tasks, when an entity resolution algorithm performs well on small hold-out datasets, there is no guarantee this performance holds on larger hold-out datasets. We prove simple bounding properties between the performance of a match function on a small validation set and the performance of a pairwise entity resolution algorithm on arbitrarily sized datasets. Thus, our approach enables optimization of pairwise entity resolution algorithms for large datasets, using a small set of labeled data.

stat.ML↗