arXiv subjects

Michael Coughlin

Publications and source records attributed to Michael Coughlin.

At least 19 recordsLinked to original sources

arXiv2026

Follow-up of SN 2025wny II: Superluminous Supernova Physics at Cosmic Noon

SN 2025wny is a gravitationally lensed, hydrogen-poor superluminous supernova (SLSN-I) at z = 2.015. To date, it is the most extensively observed high-redshift core-collapse SN and has the most detailed rest-frame UV observations of any SLSN. We present densely sampled rest-frame UV-to-optical photometry and spectroscopy out to +80 d post-peak (rest frame) from several facilities, including JWST, Keck, VLT, Gemini, the Palomar 200-inch, the Fraunhofer Telescope at Wendelstein, and the Liverpool Telescope. Correcting for lensing magnification, SN 2025wny reaches a peak pseudo-bolometric luminosity of $L_{\rm peak}\gtrsim4\times10^{44}$ erg s$^{-1}$ over rest-frame 1500-4230 \r{A}, placing it within the luminosity range of typical SLSNe-I. SN 2025wny exhibits several unusual features, including a continuum excess and sharp spectral features in the FUV from +20-60 d that coincide with an FUV light-curve plateau and higher inferred blackbody temperatures. SN 2025wny's spectra also show little to no UV line blanketing, no obvious O II absorption despite high temperatures, and evidence for C II, H$\alpha$, and possible He I. Light-curve modeling suggests that SN 2025wny may require a hybrid or non-standard power source. This work provides some of the first detailed constraints on high-redshift SLSNe and establishes SN 2025wny as an essential spectral and photometric reference for identifying and interpreting high-redshift SLSNe discovered by Rubin and Roman.

astro-ph.CO↗

arXiv2026

4th TDAMM Workshop White Paper

Time-Domain and Multi-Messenger Astrophysics (TDAMM) is entering a new era in which the rate and diversity of transient discoveries will grow rapidly across electromagnetic, gravitational-wave, neutrino, and cosmic-ray facilities. The scientific return from these investments will increasingly depend not on discovery alone, but on the ability to identify, prioritize, and coordinate follow-up observations across a heterogeneous and globally distributed network of observatories. This white paper summarizes the outcomes of the Fourth TDAMM Workshop and assesses the near-term discovery landscape, the infrastructure and tools that support coordinated observations, and the technical, policy, and capability gaps that may limit future progress. The workshop identified three principal challenges: insufficiently scalable and interoperable alert and coordination infrastructure, policies that impede rapid multi-facility observations and rare-event science, and the potential loss of critical high-energy, rapid-response, and spectroscopic capabilities. The white paper identifies the need for sustained support for alert distribution, brokers, standardized observatory metadata, cross-facility coordination platforms, and unified follow-up repositories; expanded joint observing opportunities and funding mechanisms for coordinated analysis; and strategic investment in future TDAMM facilities. The white paper also present a framework for community observing plans that would establish pre-coordinated responses to rare, high-impact events, supported by transparent governance, immediate public data release, and regular community revision. Science overviews and detailed observing strategies are provided for gamma-ray bursts, tidal disruption events, X-ray binaries, novae, supernovae, magnetars, compact binary mergers, and high-energy neutrino sources.

astro-ph.HE↗

arXiv2026

Can We Find the Emission Mechanism Behind the Extremely Bright GRB 230812B?

GRB 230812B is a bright long-duration GRB with a luminous, long-lived afterglow and an AstroSat/CZTI polarization measurement during the prompt phase, enabling a joint study of its prompt spectral evolution, polarization, and broadband afterglow. Time-resolved spectroscopy of the prompt emission shows that during the rising phase, the low-energy Band-function index exceeds the synchrotron line of death, favoring the presence of an additional thermal component. At later times, from $T_0+2$ s to $T_0+32$ s, the prompt spectra are consistent with predominantly non-thermal emission. Polarization analysis of the prompt emission in the $300$-$600$ keV band yields a marginal lower limit on the polarization fraction of $\Pi \gtrsim 50\%$ at the $1\sigma$ level. The long X-ray monitoring of the afterglow shows no jet break over the observed baseline. Multiwavelength afterglow modeling favors a wide jet with an inferred half-opening angle of $\theta_j = 15^{+6}_{-4}$ degrees observed close to the jet axis with a viewing angle of $\theta_v = 0.9^{+1.8}_{-0.6}$ degrees. The inferred circumburst density is low, $n_0 = 1.2^{+0.3}_{-0.1}\times10^{-4}\,\textrm{cm}^{-3}$, and the isotropic-equivalent kinetic energy of the jet is $E_{{\rm k}, iso} = 4.0^{+1.5}_{-0.8} \times 10^{53}$ erg. Taken together, the prompt spectral evolution favors an early phase with a thermal contribution followed by a later phase dominated by non-thermal emission. The polarization constraint in the late prompt phase is consistent with synchrotron emission, although a higher-significance polarization measurement will be required to robustly constrain the magnetic-field geometry and the relative contribution of photospheric emission.

astro-ph.HE↗

arXiv2026

EMBER: Machine-Learning Detection of Modulated Ion Acoustic Waves and Associated Core-Electron Heating in the Solar Wind with Parker Solar Probe

Modulated ion acoustic waves (IAWs) -- including triggered ion acoustic waves (TIAWs) and frequency-dispersed ion acoustic waves (FDIAWs) -- are increasingly recognized as efficient drivers of electron heating in the solar wind through nonlinear wave-particle interactions. Identification of these events in the Parker Solar Probe (PSP) FIELDS burst-mode archive has so far relied on expert visual inspection and does not scale to the full mission. We present EMBER (Electron heating from Modulated Burst-mode Event Recognition), an open-source pipeline that converts PSP FIELDS Digital Burst Memory (DBM) voltage bursts into log-scaled Fourier spectrograms and applies a multi-detector, background-only anomaly detection suite. The suite combines physics-motivated detectors, classical outlier detectors, and deep learning detectors. The EMBER ensemble recovers 93% of the anomalous events at 1% FAR (1 false positive per 100 held-out backgrounds). Coincident SWEAP/SPAN diagnostics show that flagged intervals exhibit core perpendicular electron temperatures above the adiabatic cooling expectation and elevated Te/Ti, reproducing the preferential-heating phenomenology established by prior manual studies without any use of electron temperatures in the detection step.

astro-ph.SR↗

arXiv2026

A Natural $\gtrsim 100\times$ Telescope: Discovery of the Strongly Lensed Type II SN 2025mkn at $z=1.37$

We present the discovery of SN 2025mkn, a gravitationally lensed Type II supernova. First detected as a blue transient in ZTF, 0.83$^{\prime\prime}$ from a $z=0.42$ elliptical galaxy, follow-up SNIFS/UH2.2m and LRIS/Keck spectra revealed absorption lines at $z=1.371$. Later JWST NIRCam imaging shows that the bright transient is a close pair of point sources separated by $\sim 0.07^{\prime\prime}$, and a 30 times fainter counterimage opposite the lens, for which NIRSpec reveals strong H$\alpha$ emission also at $z=1.371$. The light curves and spectra are consistent with the Type II supernova source being magnified $\gtrsim 100$ times, with $\sim 250$ required to reconcile its luminosity with that of nearby events such as SN 2023ixf. Lens models are consistent with such high magnifications, and always show that the faint image arrived first (undetected in earlier ZTF imaging), consistent with the later spectral phase of this fainter image. A fourth image is also predicted and possibly detected in the NIRSpec data. Light-curve-based time-delay measurements are not possible due to the first image being the faintest; however, the resolved NIRSpec spectra offer a future opportunity for time-delay cosmography through supernova phase measurements.

astro-ph.CO↗

arXiv2026

SN 2024iss: A Multi-Wavelength Expos\'e of a Type IIb Supernova with an Early-Time Ultraviolet Spectrum and Shock Breakout Constraints

We present multi-wavelength observations and a comprehensive analysis of the nearby (D$\sim$14 Mpc) Type IIb supernova (SN IIb) 2024iss. Observations of SN2024iss include an early ZTF detection at $\sim$40 minutes after first light and the earliest Hubble Space Telescope UV spectrum for a SN IIb to date at 7 days after first light. With the bolometric light curve and He-star models, we estimate an ejecta mass range of $\sim 1.1-3.3~M_{\odot}$ and a $^{56}\textrm{Ni}$ mass of $0.11 \pm 0.01~M_{\odot}$. We fit shock-cooling emission models to the first peak in the light curve and estimate a progenitor radius of $100-320~R_{\odot}$ and a H-rich envelope mass of $0.07-0.46~M_{\odot}$. We also compared optical/UV spectra to binary progenitor model spectra, which indicate a stripped H-rich envelope mass of $0.19-0.28~M_{\odot}$. We use early-time X-ray detections to calculate CSM densities that are consistent with a progenitor mass-loss rate of $5\times10^{-4}~M_{\odot}$ ($v_w = 100~$km/s), corresponding to a period of significant mass ejection in the final ~2-5 years before core collapse. In the UV spectrum, we observe strong Mg II emission extending to $\sim15,000 ~$km/s as well as weak P-Cygni profiles of iron-group elements (e.g., Fe, Ti, Al, Ni) present in the outer SN ejecta during the end of shock cooling phase. We find that the overall spectroscopic evolution of SN2024iss is comparable to other SNe IIb, but that the increased brightness following the initial light curve peak is likely influenced by SN ejecta-CSM interaction. Finally, optical/NIR nebular spectroscopy of SN2024iss at $\sim 260-412~$ days reveals multi-peaked forbidden line profiles of O I and Mg I] indicative of inner ejecta asymmetry and/or clumping. We demonstrate the utility of a rich, multi-wavelength dataset for constraining the progenitor systems and explosion dynamics of SNe IIb.

astro-ph.HE↗

arXiv2026

AT2024wpp: An Extremely Luminous Fast Ultraviolet Transient Powered by Accretion onto a Black Hole

We present the discovery of AT 2024wpp ("Whippet"), a fast and luminous 18cow-like transient. At a redshift of z=0.0868, revealed by Keck Cosmic Web Imager spectroscopy of its faint star-forming host, it is the fourth-nearest example of its class to date. Rapid identification of the source in the Zwicky Transient Facility data stream permitted ultraviolet-through-optical observations to be obtained prior to peak, allowing the first determination of the peak bolometric luminosity (2x10^45 erg/s), maximum photospheric radius (10^15 cm), and total radiated energy (10^51 erg) of an 18cow-like object. We present results from a comprehensive multiwavelength observing campaign, including a far-UV spectrum from the Cosmic Origins Spectrograph on the Hubble Space Telescope and deep imaging extending >100 days post-explosion from the Very Large Telescope, Hubble Space Telescope, Very Large Array, and Atacama Large Millimetre Array. We interpret the observations under a model in which a rapidly-accreting central engine blows a fast (~0.2c) wind into the surrounding medium and irradiates it with X-rays. The high Doppler velocities and intense ionization within this wind prevent identifiable spectroscopic features from appearing in the ejecta or in the surrounding circumstellar material. Weak H and He signatures do emerge in the spectra after 35 days in the form of double-peaked narrow lines. Each peak is individually narrow (full width ~3000 km/s) but the two components are separated by ~6600 km/s, indicating stable structures of denser material, possibly representing streams of tidal ejecta or an ablated companion star.

astro-ph.HE↗

arXiv2025

GRB 250704B: An Off-axis Short GRB with a Long-Lived Afterglow Plateau

We present a detailed multi-wavelength afterglow study of the short GRB 250704B, extensively monitored in optical and near-infrared bands. Its afterglow displays an unusually long-duration plateau followed by an achromatic break and a steep decline, deviating from canonical GRB afterglows. While long plateaus are often explained by central engine activity, we find that for GRB 250704B, an energy injection model requires unreasonable parameters. The afterglow is better explained by an off-axis power-law structured jet with a narrow core ($\theta_c \approx 0.7^{\circ}$) viewed at a modest angle ($\theta_v \approx 1.9^{\circ}$). A comparison with GRB 170817A shows that both events are consistent with the off-axis structured jet scenario, where the shape of the light curve is governed primarily by the geometry of the jet and the viewing angle rather than the energetics, microphysical parameters, or external density. Our results underscore the importance of incorporating the jet structure in GRB modeling.

astro-ph.HE↗

arXiv2025

A machine learning-enabled search for binary black hole mergers in LIGO-Virgo-KAGRAs third observing run

We conduct a search for stellar-mass binary black hole mergers in gravitational-wave data collected by the LIGO detectors during the LIGO-Virgo-KAGRA (LVK) third observing run (O3). Our search uses a machine learning (ML) based method, Aframe, an alternative to traditional matched filtering search techniques. The O3 observing run has been analyzed by the LVK collaboration, producing GWTC-3, the most recent catalog installment which has been made publicly available in 2021. Various groups outside the LVK have re-analyzed O3 data using both traditional and ML-based approaches. Here, we identify 38 candidates with probability of astrophysical origin ($p_\mathrm{astro}$) greater than 0.5, which were previously reported in GWTC-3. This is comparable to the number of candidates reported by individual matched-filter searches. In addition, we compare Aframe candidates with catalogs from research groups outside of the LVK, identifying three candidates with $p_\mathrm{astro} > 0.5$. No previously un-reported candidates are identified by Aframe. This work demonstrates that Aframe, and ML based searches more generally, are useful companions to matched filtering pipelines.

astro-ph.IM↗

arXiv2025

Inferring CSM Properties of Type II SNe Using a Magnitude-Limited ZTF Sample

Although all Type II supernovae (SNe) originate from massive stars possessing a hydrogen-rich envelope, their light curve morphology is diverse, reflecting poorly characterised heterogeneity in the physical properties of their progenitor systems. Here, we present a detailed light curve analysis of a magnitude-limited sample of 639 Type II SNe from the Zwicky Transient Facility Bright Transient Survey. Using Gaussian processes, we systematically measure empirical light curve features (e.g. rise times, peak colours and luminosities) in a robust sampling-independent manner. We focus on rise times as they are highly sensitive to pre-explosion progenitor properties, especially the presence of a dense circumstellar medium (CSM) shed by the progenitor in the years immediately pre-explosion. By correlating our feature measurements with physical parameters from an extensive grid of STELLA hydrodynamical models with varying progenitor properties (CSM structure, $\dot M$, $R_{CSM}$ and $M_{ZAMS}$), we quantify the proportion of events with sufficient pre-explosion mass-loss to significantly alter the initial light curve (roughly $M_{CSM} \geq 10^{-2.5} M_{\odot}$) in a highly complete sample of 377 spectroscopically classified Type II SNe. We find that 67 $\pm$ 6\% of observed SNe in our magnitude-limited sample show evidence for substantial CSM ($M_{CSM} \geq 10^{-2.5} M_{\odot}$) close to the progenitor ($R_{CSM} <10^{15}$ cm) at the time of explosion. After applying a volumetric-correction, we find 36$^{+5}_{-7}$\% of all Type II SN progenitors possess substantial CSM within $10^{15}$ cm at the time of explosion. This high fraction of progenitors with dense CSM, supported by photometric and spectroscopic evidence of previous SNe, reveals mass-loss rates significantly exceeding those measured in local group red supergiants or predicted by current theoretical models.

astro-ph.HE↗

arXiv2025

Building Machine Learning Challenges for Anomaly Detection in Science

Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not conform to the norms are an indication that the rules of science governing the data are incomplete, and something new needs to be present to explain these unexpected outliers. The challenge of finding anomalies can be confounding since it requires codifying a complete knowledge of the known scientific behaviors and then projecting these known behaviors on the data to look for deviations. When utilizing machine learning, this presents a particular challenge since we require that the model not only understands scientific data perfectly but also recognizes when the data is inconsistent and out of the scope of its trained behavior. In this paper, we present three datasets aimed at developing machine learning-based anomaly detection for disparate scientific domains covering astrophysics, genomics, and polar science. We present the different datasets along with a scheme to make machine learning challenges around the three datasets findable, accessible, interoperable, and reusable (FAIR). Furthermore, we present an approach that generalizes to future machine learning challenges, enabling the possibility of large, more compute-intensive challenges that can ultimately lead to scientific discovery.

cs.LG↗

arXiv2025

Coherence DeepClean: Toward autonomous denoising of gravitational-wave detector data

Technical and environmental noise in ground-based laser interferometers designed for gravitational-wave observations like Advanced LIGO, Advanced Virgo and KAGRA, can manifest as narrow (<1Hz) or broadband ($10'$s or even $100'$s of Hz) spectral lines and features in the instruments' strain amplitude spectral density. When the sources of this noise cannot be identified or removed, in cases where there are witness sensors sensitive to this noise source, denoising of the gravitational-wave strain channel can be performed in software, enabling recovery of instrument sensitivity over affected frequency bands. This noise hunting and removal process can be particularly challenging due to the wealth of auxiliary channels monitoring the interferometry and the environment and the non-linear couplings that may be present. In this work, we present a comprehensive analysis approach and corresponding cyberinfrastructure to promptly identify and remove noise in software using machine learning techniques. The approach builds on earlier work (referred to as DeepClean) in using machine learning methods for linear and non-linear regression of noise. We demonstrate how this procedure can be operated and optimized in a tandem fashion close to online data taking; it starts off with a coherence monitoring analysis that first singles out and prioritizes witness channels that can then be used by DeepClean. The resulting denoised strain by DeepClean reflects a 1.4\% improvement in the binary neutron star range, which can translate into a 4.3\% increase in the sensitive volume. This cyber infrastructure we refer to as Coherence DeepClean, or CDC, is a significant step toward autonomous operations of noise subtraction for ground-based interferometers.

gr-qc↗

arXiv2024

Kilonova Light Curve Parameter Estimation Using Likelihood-Free Inference

Rapid parameter estimation is critical when dealing with short lived signals such as kilonovae. We present a parameter estimation algorithm that combines likelihood-free inference with a pre-trained embedding network, optimized to efficiently process kilonova light curves. Our method is capable of retrieving the mass, velocity, and lanthanide fraction of the neutron star ejecta with an accuracy and precision on par with nested sampling methods while taking significantly less computational time. Our inference uniquely utilizes a pre-trained embedding network that marginalizes the time of arrival and the luminosity distance of the signal, allowing inference of signals at distances up to 200 Mpc. We find that including a pre-trained embedding outperforms the use of likelihood-free inference alone, reducing training time, model size, and offering the capability to marginalize over certain nuisance parameters. This framework has been integrated into the publicly available Nuclear Multi-Messenger Astronomy codebase, enabling the broader scientific community to deploy the model for their inference purposes. Our algorithm is broadly applicable to parameterized or simulated light curves of other transient objects, and can be adapted for quick sky localization.

astro-ph.IM↗

arXiv2024

Neutrino follow-up with the Zwicky Transient Facility: Results from the first 24 campaigns

The Zwicky Transient Facility (ZTF) performs a systematic neutrino follow-up program, searching for optical counterparts to high-energy neutrinos with dedicated Target-of-Opportunity (ToO) observations. Since first light in March 2018, ZTF has taken prompt observations for 24 high-quality neutrino alerts from the IceCube Neutrino Observatory, with a median latency of 12.2 hours from initial neutrino detection. From two of these campaigns, we have already reported tidal disruption event (TDE) AT 2019dsg and likely TDE AT 2019fdr as probable counterparts, suggesting that TDEs contribute >7.8% of the astrophysical neutrino flux. We here present the full results of our program through to December 2021. No additional candidate neutrino sources were identified by our program, allowing us to place the first constraints on the underlying optical luminosity function of astrophysical neutrino sources. Transients with optical absolutes magnitudes brighter that $-21$ can contribute no more than 87% of the total, while transients brighter than $-22$ can contribute no more than 58% of the total, neglecting the effect of extinction and assuming they follow the star formation rate. These are the first observational constraints on the neutrino emission of bright populations such as superluminous supernovae. None of the neutrinos were coincident with bright optical AGN flares comparable to that observed for TXS 0506+056/IC170922A, with such optical blazar flares producing no more than 26% of the total neutrino flux. We highlight the outlook for electromagnetic neutrino follow-up programs, including the expected potential for the Rubin Observatory.

astro-ph.HE↗

arXiv2024

Probing Quarkyonic Matter in Neutron Stars with the Bayesian Nuclear-Physics Multi-Messenger Astrophysics Framework

The interior of neutron stars contains matter at the highest densities realized in our Universe. Interestingly, theoretical studies of dense matter, in combination with the existence of two solar mass neutron stars, indicate that the speed of sound $c_s$ has to increase to values well above the conformal limit ($c_s^2\sim 1/3$) before decreasing again at higher densities. The decrease could be explained by either a strong first-order phase transition or a cross-over transition from hadronic to quark matter. The latter scenario leads to a pronounced peak in the speed of sound reaching values above the conformal limit, naturally explaining the inferred behavior. In this work, we use the Nuclear-Physics Multi-Messenger Astrophysics framework \textsc{NMMA} to compare predictions of the quarkyonic matter model with astrophysical observations of neutron stars, with the goal of constraining model parameters. Assuming quarkyonic matter to be realized within neutron stars, we find that there can be a significant amount of quarks inside the core of neutron stars with masses in the two solar mass range, amounting to up to $\sim 0.13M_\odot$, contributing $\sim 5.9\%$ of the total mass. Furthermore, for the quarkyonic matter model investigated here, the radius of a $1.4M_\odot$ neutron star would be $13.44^{+1.69}_{-1.54} (13.54^{+1.02}_{-1.04})$ km, at $95\%$ credibility, without (with) the inclusion of AT2017gfo.

nucl-th↗

arXiv2023

Bayesian model selection for GRB 211211A through multi-wavelength analyses

Although GRB 211211A is one of the closest gamma-ray bursts (GRBs), its classification is challenging because of its partially inconclusive electromagnetic signatures. In this paper, we investigate four different astrophysical scenarios as possible progenitors for GRB~211211A: a binary neutron-star merger, a black-hole--neutron-star merger, a core-collapse supernova, and an r-process enriched core collapse of a rapidly rotating massive star (a collapsar). We perform a large set of Bayesian multi-wavelength analyses based on different models describing these scenarios and priors to investigate which astrophysical scenarios and processes might be related to GRB~211211A. Our analysis supports previous studies in which the presence of an additional component, likely related to $r$-process nucleosynthesis, is required to explain the observed light curves of GRB~211211A, as it can not solely be explained as a GRB afterglow. Fixing the distance to about $350~\rm Mpc$, namely the distance of the possible host galaxy SDSS J140910.47+275320.8, we find a statistical preference for a binary neutron-star merger scenario.

astro-ph.HE↗

arXiv2023

Gamma-ray Transient Network Science Analysis Group Report

The Interplanetary Network (IPN) is a detection, localization and alert system that utilizes the arrival time of transient signals in gamma-ray detectors on spacecraft separated by planetary baselines to geometrically locate the origin of these transients. Due to the changing astrophysical landscape and the new emphasis on time domain and multi-messenger astrophysics (TDAMM) from the Pathways to Discovery in Astronomy and Astrophysics for the 2020s, this Gamma-ray Transient Network Science Analysis Group was tasked to understand the role of the IPN and high-energy monitors in this new era. The charge includes describing the science made possible with these facilities, tracing the corresponding requirements and capabilities, and highlighting where improved operations of existing instruments and the IPN would enhance TDAMM science. While this study considers the full multiwavelength and multimessenger context, the findings are specific to space-based high-energy monitors. These facilities are important both for full characterization of these transients as well as facilitating follow-up observations through discovery and localization. The full document reports a brief history of this field, followed by our detailed analyses and findings in some 68 pages, providing a holistic overview of the role of the IPN and high-energy monitors in the coming decades.

astro-ph.HE↗

arXiv2023

Demonstration of Machine Learning-assisted real-time noise regression in gravitational wave detectors

Real-time noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the detectability, source localization and pre-merger detectability of signals thereby enabling rapid multi-messenger follow-up. In this paper, we demonstrate the effectiveness of \textit{DeepClean}, a convolutional neural network architecture that uses witness sensors to estimate and subtract non-linear and non-stationary noise from gravitational-wave strain data. Our study uses LIGO data from the third observing run with injected compact binary signals. As a demonstration, we use \textit{DeepClean} to subtract the noise at 60 Hz due to the power mains and their sidebands arising from non-linear coupling with other instrumental noise sources. Our parameter estimation study on the injected signals shows that \textit{DeepClean} does not do any harm to the underlying astrophysical signals in the data while it can enhances the signal-to-noise ratio of potential signals. We show that \textit{DeepClean} can be used for low-latency noise regression to produce cleaned output data at latencies $\sim 1-2$\, s. We also discuss various considerations that may be made while training \textit{DeepClean} for low latency applications.

gr-qc↗