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The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

We report on the polarization dynamics of regenerative light pulses in a micropillar laser with integrated saturable absorber coupled to an external feedback mirror. The delayed self-coupled microlaser is operated in the excitable regime, where it regenerates incident pulses with a supra-threshold intensity -- resulting in a pulse train with inter-pulse period approximately given by the feedback delay time, in analogy with a self-coupled biological neuron. We report the experimental observation of vectorial breathers in polarization angle, manifesting themselves as a modulation of the linear polarized intensity components without significant modulation of the total intensity. Numerical analysis of a suitable model reveals that the observed polarization mode competition is a consequence of symmetry-breaking bifurcations induced by polarization anisotropy. Our model reproduces well the observed experimental results and predicts different regimes as a function of the polarization anisotropy parameters and the pump parameter. We believe that these findings are relevant for the fabrication of flexible sources of polarized pulses with controlled properties, as well as for neuroinspired on-chip computing applications, where the polarization may be used to encode or process information in novel ways., Comment: 5 pages, 4 figures

Recent observations by the Event Horizon Telescope (EHT) of supermassive black holes M87* and Sgr A* offer valuable insights into their spacetime properties and astrophysical conditions. Utilizing a library of model images (~2 million for Sgr A*) generated from general-relativistic magnetohydrodynamic (GRMHD) simulations, limited and coarse insights on key parameters such as black hole spin, magnetic flux, inclination angle, and electron temperature were gained. The image orientation and black hole mass estimates were obtained via a scoring and an approximate rescaling procedure. Lifting such approximations, probing the space of parameters continuously, and extending the parameter space of theoretical models is both desirable and computationally prohibitive with existing methods. To address this, we introduce a new Bayesian scheme that adaptively explores the parameter space of ray-traced, GRMHD models. The general relativistic radiative transfer code \ipole is integrated with the EHT parameter estimation tool THEMIS. The pipeline produces a ray-traced model image from GRMHD data, computes predictions for VLBI observables from the image for a specific VLBI array configuration and compares to data thereby sampling the likelihood surface via an MCMC scheme. At this stage we focus on four parameters: accretion rate, electron thermodynamics, inclination, and source position angle. Our scheme faithfully recovers parameters from simulated VLBI data and accommodates time-variabibility via an inflated error budget. We highlight the impact of intrinsic variability on model fitting approaches. This work facilitates more informed inferences from GRMHD simulations and enables expansion of the model parameter space in a statistically robust and computationally efficient manner.

Wildfire frequency is increasing as the climate changes, and the resulting air pollution poses health risks. Just as people routinely use weather forecasts to plan their activities around precipitation, reliable air quality forecasts could help individuals reduce their exposure to air pollution. In the present work, we evaluate several existing forecasts of fine particular matter (PM2.5) within the continental United States in the context of individual decision-making. Our comparison suggests there is meaningful room for improvement in air pollution forecasting, which might be realized by incorporating more data sources and using machine learning tools. To facilitate future machine learning development and benchmarking, we set up a framework to evaluate and compare air pollution forecasts for individual decision making. We introduce a new loss to capture decisions about when to use mitigation measures. We highlight the importance of visualizations when comparing forecasts. Finally, we provide code to download and compare archived forecast predictions., Comment: 22 pages, 3 figures

A data analyst might worry about generalization if dropping a very small fraction of data points from a study could change its substantive conclusions. Finding the worst-case data subset to drop poses a combinatorial optimization problem. To overcome this intractability, recent works propose using additive approximations, which treat the contribution of a collection of data points as the sum of their individual contributions, and greedy approximations, which iteratively select the point with the highest impact to drop and re-run the data analysis without that point [Broderick et al., 2020, Kuschnig et al., 2021]. We identify that, even in a setting as simple as OLS linear regression, many of these approximations can break down in realistic data arrangements. Several of our examples reflect masking, where one outlier may hide or conceal the effect of another outlier. Based on the failures we identify, we provide recommendations for users and suggest directions for future improvements., Comment: 39 pages

If the conclusion of a data analysis is sensitive to dropping very few data points, that conclusion might hinge on the particular data at hand rather than representing a more broadly applicable truth. How could we check whether this sensitivity holds? One idea is to consider every small subset of data, drop it from the dataset, and re-run our analysis. But running MCMC to approximate a Bayesian posterior is already very expensive; running multiple times is prohibitive, and the number of re-runs needed here is combinatorially large. Recent work proposes a fast and accurate approximation to find the worst-case dropped data subset, but that work was developed for problems based on estimating equations -- and does not directly handle Bayesian posterior approximations using MCMC. We make two principal contributions in the present work. We adapt the existing data-dropping approximation to estimators computed via MCMC. Observing that Monte Carlo errors induce variability in the approximation, we use a variant of the bootstrap to quantify this uncertainty. We demonstrate how to use our approximation in practice to determine whether there is non-robustness in a problem. Empirically, our method is accurate in simple models, such as linear regression. In models with complicated structure, such as hierarchical models, the performance of our method is mixed., Comment: Shorter version appeared in ICML 2024 Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators (https://openreview.net/pdf?id=bCPhVcq9Mj)

Practitioners often aim to infer an unobserved population trajectory using sample snapshots at multiple time points. E.g., given single-cell sequencing data, scientists would like to learn how gene expression changes over a cell's life cycle. But sequencing any cell destroys that cell. So we can access data for any particular cell only at a single time point, but we have data across many cells. The deep learning community has recently explored using Schr\"odinger bridges (SBs) and their extensions in similar settings. However, existing methods either (1) interpolate between just two time points or (2) require a single fixed reference dynamic (often set to Brownian motion within SBs). But learning piecewise from adjacent time points can fail to capture long-term dependencies. And practitioners are typically able to specify a model family for the reference dynamic but not the exact values of the parameters within it. So we propose a new method that (1) learns the unobserved trajectories from sample snapshots across multiple time points and (2) requires specification only of a family of reference dynamics, not a single fixed one. We demonstrate the advantages of our method on simulated and real data., Comment: 33 pages, 7 figures

We present deep near-infrared $K_{\rm s}$-band imaging for 35 of the 53 sources from the high-redshift ($z > 2$) radio galaxy candidate sample defined in Broderick et al. (2022). These images were obtained using the High-Acuity Widefield $K$-band Imager (HAWK-I) on the Very Large Telescope. Host galaxies are detected for 27 of the sources, with $K_{\rm s} \approx 21.6$$-$$23.0$ mag (2$''$ diameter apertures; AB). The remaining eight targets are not detected to a median $3\sigma$ depth of $K_{\rm s} \approx 23.3$ mag ($2''$ diameter apertures). We examine the radio and near-infrared flux densities of the 35 sources, comparing them to the known $z > 3$ powerful radio galaxies with 500-MHz radio luminosities $L_{500\,{\rm MHz}} > 10^{27}$ W Hz$^{-1}$. By plotting 150-MHz flux density versus $K_{\rm s}$-band flux density, we find that, similar to the sources from the literature, these new targets have large radio to near-infrared flux density ratios, but extending the distribution to fainter flux densities. Five of the eight HAWK-I deep non-detections have a median $3\sigma$ lower limit of $K_{\rm s} \gtrsim 23.8$ mag ($1.5''$ diameter apertures); these five targets, along with a further source from Broderick et al. (2022) with a deep non-detection ($K_{\rm s} \gtrsim 23.7$ mag; $3\sigma$; $2''$ diameter aperture) in the Southern H-ATLAS Regions $K_{\rm s}$-band Survey, are considered candidates to be ultra-high-redshift ($z > 5$) radio galaxies. The extreme radio to near-infrared flux density ratios ($>10^5$) for these six sources are comparable to TN J0924$-$2201, GLEAM J0856$+$0223 and TGSS J1530$+$1049, the three known powerful radio galaxies at $z > 5$. For a selection of galaxy templates with different stellar masses, we show that $z \gtrsim 4.2$ is a plausible scenario for our ultra-high-redshift candidates if the stellar mass $M_{\rm *} \gtrsim 10^{10.5}\,{\rm M}_\odot$. [abridged], Comment: 24 pages, 5 figures (one of which is a multi-page figure with 30 separate panels), 2 tables, accepted for publication in PASA

We present a multi-wavelength study on three new $z\sim5.6$ quasi stellar objects (QSOs) selected based on their radio and optical/near-infrared properties in publicly available surveys and then identified with dedicated spectroscopic observations. These are among the radio-brightest QSOs currently known at $z>5.5$, having $\rm R=S_{\rm 5GHz}/S_{\rm 4400A}>100$. In this work we present their identification and we also discuss their multi-wavelength properties (from the radio to the X-ray band) based on the detection in public surveys as well as dedicated radio and X-ray observations. The three sources present a wide range of properties, in terms of relative intensity and spectral shape, highlighting the importance of multi-wavelength observations in order to accurately characterise these high-$z$ objects. In particular, from our analysis we found one source, at $z=5.61$, that presents clear blazars properties (strong and flat radio and X-ray emission), making it one of the most distant currently known in this class. Moreover, from the fit of the optical/near-infrared photometric measurements with an accretion disc model, as well as the analysis of the CIV broad emission line in one case, we were able to estimate the mass and the accretion rate of the central black holes in these systems, finding $\rm M_{\rm BH}\sim1-10\times10^9$ M$_\odot$ accreting at a rate $\lambda_{\rm Edd}\sim0.1-0.2$. With this work we increase the number of very-high redshift radio-powerful QSOs characterised with multi-wavelength observations, essential in order to understand the evolution and the properties of this still poorly constrained class of sources., Comment: Submitted to A&A on July 4th

The imaging of Sagittarius A* (Sgr A*) and the supermassive black hole at the center of Messier 87 (M87*) by the Event Horizon Telescope constrains the location and nature of emission from these objects. Coupled with flux limits from the near-infrared through the ultraviolet, the attendant size constraints provide strong evidence for the absence of an accretion-powered photosphere, and therefore for the existence of an event horizon about an astrophysical black hole. Here, we demonstrate that a broad class of naked singularities are also generically excluded, regardless of the nature and unknown physical impact of singularity itself, subject to a single weak assumption about locality. While we restrict our attention to static, spherically symmetric spacetimes, we are nevertheless able to exclude a large number of commonly invoked naked singularity spacetimes in this way., Comment: 16 pages, 5 figures, submitted to ApJ

We present a multi-wavelength analysis, from the radio to the X-ray band, of the redshift $z=6.44$ VIK J2318$-$31 radio-loud (RL) quasi stellar object (QSO), one of the most distant currently known in this class. The work is based on newly obtained (uGMRT, ATCA, Chandra) as well as archival (GNIRS and X-Shooter) dedicated observations that have not been published yet. Based on the observed X-ray and radio emission, its relativistic jets are likely young and misaligned from our line of sight. Moreover, we can confirm, with simultaneous observations, the presence of a turnover in the radio spectrum at $\nu_{\rm peak} \sim 650$ MHz which is unlikely to be associated with self-synchrotron absorption. From the NIR spectrum we derived the mass of the central black hole, M$_{\rm BH}=8.1^{+6.8}_{-5.6} \times 10^8 {\rm M_{\odot}}$, and the Eddington ratio, $\lambda_{\rm EDD} = 0.8^{+0.8}_{-0.6}$, using broad emission lines as well as an accretion disc model fit to the continuum emission. Given the high accretion rate, the presence of a $\sim$8$\times$10$^8$ M$_\odot$ black hole at $z=6.44$ can be explained by a seed black hole ($\sim$10$^{4}$ M$_\odot$) that formed at $z\sim25$, assuming a radiative efficiency $\eta_{\rm d}\sim0.1$. However, by assuming $\eta_{\rm d}\sim0.3$, as expected for jetted systems, the mass observed would challenge current theoretical models of black hole formation., Comment: Accepted for publication on A&A the 22nd April 2024

Collecting genomics data across multiple heterogeneous populations (e.g., across different cancer types) has the potential to improve our understanding of disease. Despite sequencing advances, though, resources often remain a constraint when gathering data. So it would be useful for experimental design if experimenters with access to a pilot study could predict the number of new variants they might expect to find in a follow-up study: both the number of new variants shared between the populations and the total across the populations. While many authors have developed prediction methods for the single-population case, we show that these predictions can fare poorly across multiple populations that are heterogeneous. We prove that, surprisingly, a natural extension of a state-of-the-art single-population predictor to multiple populations fails for fundamental reasons. We provide the first predictor for the number of new shared variants and new total variants that can handle heterogeneity in multiple populations. We show that our proposed method works well empirically using real cancer and population genetics data.

Spatial prediction tasks are key to weather forecasting, studying air pollution, and other scientific endeavors. Determining how much to trust predictions made by statistical or physical methods is essential for the credibility of scientific conclusions. Unfortunately, classical approaches for validation fail to handle mismatch between locations available for validation and (test) locations where we want to make predictions. This mismatch is often not an instance of covariate shift (as commonly formalized) because the validation and test locations are fixed (e.g., on a grid or at select points) rather than i.i.d. from two distributions. In the present work, we formalize a check on validation methods: that they become arbitrarily accurate as validation data becomes arbitrarily dense. We show that classical and covariate-shift methods can fail this check. We instead propose a method that builds from existing ideas in the covariate-shift literature, but adapts them to the validation data at hand. We prove that our proposal passes our check. And we demonstrate its advantages empirically on simulated and real data., Comment: 52 pages, 14 figures

3C84 is a nearby radio source with a complex total intensity structure, showing linear polarisation and spectral patterns. A detailed investigation of the central engine region necessitates the use of VLBI above the hitherto available maximum frequency of 86GHz. Using ultrahigh resolution VLBI observations at the highest available frequency of 228GHz, we aim to directly detect compact structures and understand the physical conditions in the compact region of 3C84. We used EHT 228GHz observations and, given the limited (u,v)-coverage, applied geometric model fitting to the data. We also employed quasi-simultaneously observed, multi-frequency VLBI data for the source in order to carry out a comprehensive analysis of the core structure. We report the detection of a highly ordered, strong magnetic field around the central, SMBH of 3C84. The brightness temperature analysis suggests that the system is in equipartition. We determined a turnover frequency of $\nu_m=(113\pm4)$GHz, a corresponding synchrotron self-absorbed magnetic field of $B_{SSA}=(2.9\pm1.6)$G, and an equipartition magnetic field of $B_{eq}=(5.2\pm0.6)$G. Three components are resolved with the highest fractional polarisation detected for this object ($m_\textrm{net}=(17.0\pm3.9)$%). The positions of the components are compatible with those seen in low-frequency VLBI observations since 2017-2018. We report a steeply negative slope of the spectrum at 228GHz. We used these findings to test models of jet formation, propagation, and Faraday rotation in 3C84. The findings of our investigation into different flow geometries and black hole spins support an advection-dominated accretion flow in a magnetically arrested state around a rapidly rotating supermassive black hole as a model of the jet-launching system in the core of 3C84. However, systematic uncertainties due to the limited (u,v)-coverage, however, cannot be ignored., Comment: 15 pages, 6 figures, published in A&A

We focus on the existence and persistence of families of saddle periodic orbits in a four-dimensional Hamiltonian reversible ordinary differential equation derived using a travelling wave ansatz from a generalised nonlinear Schr{\"o}dinger equation (GNLSE) with quartic dispersion. In this way, we are able to characterise different saddle periodic orbits with different signatures that serve as organising centres of homoclinic orbits in the ODE and solitons in the GNLSE. To achieve our objectives, we employ numerical continuation techniques to compute these saddle periodic orbits, and study how they organise themselves as surfaces in phase space that undergo changes as a single parameter is varied. Notably, different surfaces of saddle periodic orbits can interact with each other through bifurcations that can drastically change their overall geometry or even create new surfaces of periodic orbits. Particularly we identify three different bifurcations: symmetry-breaking, period-$k$ multiplying, and saddle-node bifurcations. Each bifurcation exhibits a degenerate case, which subsequently gives rise to two bifurcations of the same type that occurs at particular energy levels that vary as a parameter is gradually increased. Additionally, we demonstrate how these degenerate bifurcations induce structural changes in the periodic orbits that can support homoclinic orbits by computing sequences of period-$k$ multiplying bifurcations.

Differential expression (DE) plays a fundamental role toward illuminating the molecular mechanisms driving a difference between groups (e.g., due to treatment or disease). While any analysis is run on particular cells/samples, the intent is to generalize to future occurrences of the treatment or disease. Implicitly, this step is justified by assuming that present and future samples are independent and identically distributed from the same population. Though this assumption is always false, we hope that any deviation from the assumption is small enough that A) conclusions of the analysis still hold and B) standard tools like standard error, significance, and power still reflect generalizability. Conversely, we might worry about these deviations, and reliance on standard tools, if conclusions could be substantively changed by dropping a very small fraction of data. While checking every small fraction is computationally intractable, recent work develops an approximation to identify when such an influential subset exists. Building on this work, we develop a metric for dropping-data robustness of DE; namely, we cast the analysis in a form suitable to the approximation, extend the approximation to models with data-dependent hyperparameters, and extend the notion of a data point from a single cell to a pseudobulk observation. We then overcome the inherent non-differentiability of gene set enrichment analysis to develop an additional approximation for the robustness of top gene sets. We assess robustness of DE for published single-cell RNA-seq data and discover that 1000s of genes can have their results flipped by dropping <1% of the data, including 100s that are sensitive to dropping a single cell (0.07%). Surprisingly, this non-robustness extends to high-level takeaways; half of the top 10 gene sets can be changed by dropping 1-2% of cells, and 2/10 can be changed by dropping a single cell.

The Event Horizon Telescope (EHT) provides an avenue to study black hole accretion flows on event-horizon scales. Fitting a semi-analytical model to EHT observations requires the construction of synthetic images, which is computationally expensive. This study presents an image generation tool in the form of a generative machine learning model, which extends the capabilities of a variational autoencoder. This tool can rapidly and continuously interpolate between a training set of images and can retrieve the defining parameters of those images. Trained on a set of synthetic black hole images, our tool showcases success in both interpolating black hole images and their associated physical parameters. By reducing the computational cost of generating an image, this tool facilitates parameter estimation and model validation for observations of black hole system., Comment: 14 pages, 6 figures

The Event Horizon Telescope (EHT) Collaboration recently published the first images of the supermassive black holes in the cores of the Messier 87 and Milky Way galaxies. These observations have provided a new means to study supermassive black holes and probe physical processes occurring in the strong-field regime. We review the prospects of future observations and theoretical studies of supermassive black hole systems with the next-generation Event Horizon Telescope (ngEHT), which will greatly enhance the capabilities of the existing EHT array. These enhancements will open up several previously inaccessible avenues of investigation, thereby providing important new insights into the properties of supermassive black holes and their environments. This review describes the current state of knowledge for five key science cases, summarising the unique challenges and opportunities for fundamental physics investigations that the ngEHT will enable., Comment: To be submitted to journal. Comments are welcome

The Event Horizon Telescope (EHT) is a millimeter very long baseline interferometry (VLBI) array that has imaged the apparent shadows of the supermassive black holes M87* and Sagittarius A*. Polarimetric data from these observations contain a wealth of information on the black hole and accretion flow properties. In this work, we develop polarimetric geometric modeling methods for mm-VLBI data, focusing on approaches that fit data products with differing degrees of invariance to broad classes of calibration errors. We establish a fitting procedure using a polarimetric "m-ring" model to approximate the image structure near a black hole. By fitting this model to synthetic EHT data from general relativistic magnetohydrodynamic models, we show that the linear and circular polarization structure can be successfully approximated with relatively few model parameters. We then fit this model to EHT observations of M87* taken in 2017. In total intensity and linear polarization, the m-ring fits are consistent with previous results from imaging methods. In circular polarization, the m-ring fits indicate the presence of event-horizon-scale circular polarization structure, with a persistent dipolar asymmetry and orientation across several days. The same structure was recovered independently of observing band, used data products, and model assumptions. Despite this broad agreement, imaging methods do not produce similarly consistent results. Our circular polarization results, which imposed additional assumptions on the source structure, should thus be interpreted with some caution. Polarimetric geometric modeling provides a useful and powerful method to constrain the properties of horizon-scale polarized emission, particularly for sparse arrays like the EHT., Comment: 34 pages, 15 figures, published in The Astrophysical Journal Letters

Black holes can amplify incoming bosonic waves via rotational superradiance, inducing bound states of ultralight bosons around them. This phenomenon has the potential to confine the parameter spaces of new bosons. Axions and axion-like particles (ALPs) are candidate beyond-standard-model particles that can form such clouds around supermassive black holes (SMBHs) and impact the polarization signal in a similar fashion to Faraday rotation via axion-photon coupling. Prior efforts have used polarized images from the Event Horizon Telescope (EHT) M87 2017 observations to limit the dimensionless axion-photon coupling to previously unexplored regions. However, with the novel calibration-insensitive quantities, closure traces and conjugate closure trace products, it is possible to constrain the existence of axion clouds while avoiding the dominant sources of systematic uncertainties, e.g., station gains and polarization leakages. We utilize a simple geometric model for the polarization map of M87* to fit the model parameters with both simulated and real data sets and reach a comparable level of constraint in the accuracy with which an axion cloud may be excluded in M87. Future applications of our approach include subsequent M87* and Sgr A* observations by EHT and next-generation EHT (ngEHT) are expected to produce stronger constraints across a wider range of axion and ALP masses. Because it does not require imaging, closure trace analyses may be applied to target AGN for which imaging is marginal, extending the number of SMBHs from which axion limits may be obtained significantly., Comment: 12 pages, 11 figures, 1 table, submitted to ApJ

There are now multiple direct probes of the region near black hole horizons, including direct imaging with the Event Horizon Telescope (EHT). As a result, it is now of considerable interest to identify what aspects of the underlying spacetime are constrained by these observations. For this purpose, we present a new formulation of an existing broad class of integrable, axisymmetric, stationary spinning black hole spacetimes, specified by four free radial functions, that makes manifest which functions are responsible for setting the location and morphology of the event horizon and ergosphere. We explore the size of the black hole shadow and high-order photon rings for polar observers, approximately appropriate for the EHT observations of M87*, finding analogous expressions to those for general spherical spacetimes. Of particular interest, we find that these are independent of the properties of the ergosphere, but does directly probe on the free function that defines the event horizon. Based on these, we extend the nonperturbative, nonparametric characterization of the gravitational implications of various near-horizon measurements to spinning spacetimes. Finally, we demonstrate this characterization for a handful of explicit alternative spacetimes.

We present a theoretical analysis of mid-infrared radiative recombination in InAs/GaSb superlattices (SLs). We employ a semi-analytical plane wave expansion method in conjunction with an 8-band $\mathbf{k} \cdot \mathbf{p}$ Hamiltonian to compute the SL electronic structure, paying careful attention to the identification and mitigation of spurious solutions. The calculated SL eigenstates are used directly to compute spontaneous emission spectra and the radiative recombination coefficient $B$. We elucidate the origin of the relatively large $B$ coefficients in InAs/GaSb SLs which, despite the presence of spatially indirect (type-II-like) carrier confinement, are close to that of bulk InAs and compare favourably to those calculated for mid-infrared type-I pseudomorphic and metamorphic quantum well structures having comparable emission wavelengths. Our analysis explicitly quantifies the roles played by carrier localisation (specifically, partial delocalisation of bound electron states) and miniband formation (specifically, miniband occupation and optical selection rules) in determining the magnitude of $B$ and its temperature dependence. We perform a high-throughput optimisation of the room temperature $B$ coefficient in InAs/GaSb SLs across the 3.5 -- 7 $\mu$m wavelength range, quantifying the dependence of $B$ on the relative thickness of the electron-confining InAs and hole-confining GaSb layers. This analysis provides guidance for the growth of optimised SLs for mid-infrared light emitters. Our results, combined with the expected low non-radiative Auger recombination rates in structures having spatially indirect electron and hole confinement, corroborate recently observed high output power in prototype InAs/GaSb SL inter-band cascade light-emitting diodes., Comment: Published version

The Event Horizon Telescope (EHT) observed in 2017 the supermassive black hole at the center of the Milky Way, Sagittarius A* (Sgr A*), at a frequency of 228.1 GHz ($\lambda$=1.3 mm). The fundamental physics tests that even a single pulsar orbiting Sgr A* would enable motivate searching for pulsars in EHT datasets. The high observing frequency means that pulsars - which typically exhibit steep emission spectra - are expected to be very faint. However, it also negates pulse scattering, an effect that could hinder pulsar detections in the Galactic Center. Additionally, magnetars or a secondary inverse Compton emission could be stronger at millimeter wavelengths than at lower frequencies. We present a search for pulsars close to Sgr A* using the data from the three most-sensitive stations in the EHT 2017 campaign: the Atacama Large Millimeter/submillimeter Array, the Large Millimeter Telescope and the IRAM 30 m Telescope. We apply three detection methods based on Fourier-domain analysis, the Fast-Folding-Algorithm and single pulse search targeting both pulsars and burst-like transient emission; using the simultaneity of the observations to confirm potential candidates. No new pulsars or significant bursts were found. Being the first pulsar search ever carried out at such high radio frequencies, we detail our analysis methods and give a detailed estimation of the sensitivity of the search. We conclude that the EHT 2017 observations are only sensitive to a small fraction ($\lesssim$2.2%) of the pulsars that may exist close to Sgr A*, motivating further searches for fainter pulsars in the region., Comment: 33 pages, 7 figures, 6 Tables. Accepted for publication in ApJ