Search

After the final stage of the merger of two black holes, the ringdown signal takes an important role on providing information about the gravitational dynamics in strong field. We introduce a novel time-domain (TD) approach, predicated on the $\mathcal{F}$-statistic, for ringdown analysis. This method diverges from traditional TD techniques in that its parameter space remains constant irrespective of the number of modes incorporated. This feature is achieved by reconfiguring the likelihood and analytically maximizing over the extrinsic parameters that encompass the amplitudes and reference phases of all modes. Consequently, when performing the ringdown analysis under the assumption that the ringdown signal is detected by the Einstein Telescope, parameter estimation computation time is shortened by at most five orders of magnitude compared to the traditional TD method. We further establish that traditional TD methods become difficult when including multiple overtone modes due to close oscillation frequencies and damping times across different overtone modes. Encouragingly, this issue is effectively addressed by our new TD technique. The accessibility of this new TD method extends to a broad spectrum of research and offers flexibility for various topics within black hole spectroscopy applicable to both current and future gravitational wave detectors., Comment: 14 pages, 8 figures, accepted by ApJ

Following the recommendations to NASA and ESA, the search for life on exoplanets will be a priority in the next decades. Two direct imaging space mission concepts are being developed: the Habitable Worlds Observatory (HWO) and the Large Interferometer for Exoplanets (LIFE). HWO focuses on reflected light spectra in the ultraviolet/visible/near-infrared (UV/VIS/NIR), while LIFE captures the mid-infrared (MIR) emission of temperate exoplanets. We assess the potential of HWO and LIFE in characterizing a cloud-free Earth twin orbiting a Sun-like star at 10 pc, both separately and synergistically, aiming to quantify the increase in information from joint atmospheric retrievals on a habitable planet. We perform Bayesian retrievals on simulated data from an HWO-like and a LIFE-like mission separately, then jointly, considering the baseline spectral resolutions currently assumed for these concepts and using two increasingly complex noise simulations. HWO would constrain H$_2$O, O$_2$, and O$_3$, in the atmosphere, with ~ 100 K uncertainty on the temperature profile. LIFE would constrain CO$_2$, H$_2$O, O$_3$ and provide constraints on the thermal atmospheric structure and surface temperature (~ 10 K uncertainty). Both missions would provide an upper limit on CH$_4$. Joint retrievals on HWO and LIFE data would accurately define the atmospheric thermal profile and planetary parameters, decisively constrain CO$_2$, H$_2$O, O$_2$, and O$_3$, and weakly constrain CO and CH$_4$. The detection significance is greater or equal to single-instrument retrievals. Both missions provide specific information to characterize a terrestrial habitable exoplanet, but the scientific yield is maximized with synergistic UV/VIS/NIR+MIR observations. Using HWO and LIFE together will provide stronger constraints on biosignatures and life indicators, potentially transforming the search for life in the universe., Comment: 16 pages (main text, incl. 12 figures) + appendix; accepted for publication in A&A (current version: post 1st revision). Thirteenth paper of LIFE telescope series

The main challenge of exoplanet high-contrast imaging (HCI) is to separate the signal of exoplanets from their host stars, which are many orders of magnitude brighter. HCI for ground-based observations is further exacerbated by speckle noise originating from perturbations in the Earth's atmosphere and imperfections in the telescope optics. Various data post-processing techniques are used to remove this speckle noise and reveal the faint planet signal. Often, however, a significant part of the planet signal is accidentally subtracted together with the noise. In the present work, we use explainable machine learning to investigate the reason for the loss of the planet signal for one of the most used post-processing methods: Principal Component Analysis (PCA). We find that PCA learns the shape of the telescope point spread function for high numbers of PCA components. This representation of the noise captures not only the speckle noise, but also the characteristic shape of the planet signal. Building upon these insights, we develop a new post-processing method (4S) that constrains the noise model to minimize this signal loss. We apply our model to 11 archival HCI datasets from the VLT-NACO instrument in the L'-band and find that our model consistently outperforms PCA. The improvement is largest at close separations to the star ($\leq 4 \lambda /D$) providing up to 1.5 magnitudes deeper contrast. This enhancement enables us to detect the exoplanet AF Lep b in data from 2011, 11 years before its subsequent discovery. We present updated orbital parameters for this object., Comment: Submitted to AJ, 26 pages, 15 figures, comments welcome, code available on ReadtheDocs: https://fours.readthedocs.io/en/latest/

Glitching pulsars are expected to be important sources of gravitational waves. In this paper, we explore six different models that propose the emission of transient continuous waves, lasting days to months, coincident with glitches. The maximal gravitational wave energy is calculated for each model, which is then used to determine whether associated gravitational waves could be detectable with LIGO-Virgo-KAGRA's O4 detectors. We provide an analytical approximation to calculate the signal-to-noise ratio which includes information about the source's sky position, improving on previous estimates that assume isotropic or sky and orientation averaged sensitivities. By analysing the entire glitching population, we find that certain models predict detectable signals in O4, whereas others do not. We also rank glitching pulsars by signal-to-noise ratio, based on archival data, and we find that for all models, the Vela pulsar (PSR J0835$-$4510) would provide the strongest signal. Moreover, PSR J0537$-$6910 is not expected to yield a detectable signal in O4, but will start becoming relevant for next generation detectors. Our analysis also extends to the entire pulsar population, regardless of whether they have glitched, and we provide a list of pulsars that would present a significant signal, if they were to glitch. Finally, we apply our analysis to the April 2024 Vela glitch and find that a signal should be detectable under certain models. The non-detection of a supposedly detectable signal would provide an efficiency factor that quantifies a model's contribution to gravitational wave emission, eventually leading to a differentiation of models and independent constraints on physical parameters., Comment: 21 pages, 8 figures, 8 tables, 3 appendices. Accepted for publication in MNRAS

GWnext 2024 was a meeting held in the Kavli Institute for Astronomy and Astrophysics at Peking University in March $4^\text{th} - 8^\text{th}$, 2024. In the meeting researchers at different career stages -- with a particular focus on early career scientists -- working on the different aspects of gravitational wave (GW) astronomy gathered to discuss the current status as well as prospects of the field. The meeting was divided into three core sessions: Astrophysics, GW Theory, and Detection. Each session consisted of introductory talks and extended discussion sessions. Moreover, there was a poster session where students could present their results. In this paper, we summarize the results presented during the meeting and present the most important outcomes.

The advent of high-contrast imaging instruments combined with medium-resolution spectrographs allows spectral and temporal dimensions to be combined with spatial dimensions to detect and potentially characterize exoplanets with higher sensitivity. We develop a new method to effectively leverage the spectral and spatial dimensions in integral-field spectroscopy (IFS) datasets using a supervised deep-learning algorithm to improve the detection sensitivity to high-contrast exoplanets. We begin by applying a data transform whereby the IFS datasets are replaced by cross-correlation coefficient tensors obtained by cross-correlating our data with young gas giant spectral template spectra. This transformed data is then used to train machine learning (ML) algorithms. We train a 2D CNN and 3D LSTM with our data. We compare the ML models with a non-ML algorithm, based on the STIM map of arXiv:1810.06895. We test our algorithms on simulated young gas giants in a dataset that contains no known exoplanet, and explore the sensitivity of algorithms to detect these exoplanets at contrasts ranging from 1e-3 to 1e-4 at different radial separations. We quantify the sensitivity using modified receiver operating characteristic curves (mROC). We discover that the ML algorithms produce fewer false positives and have a higher true positive rate than the STIM-based algorithm, and the true positive rate of ML algorithms is less impacted by changing radial separation. We discover that the velocity dimension is an important differentiating factor. Through this paper, we demonstrate that ML techniques have the potential to improve the detection limits and reduce false positives for directly imaged planets in IFS datasets, after transforming the spectral dimension into a radial velocity dimension through a cross-correlation operation., Comment: Accepted for publication in A&A on 23/04/2024. Total 15 pages of text, 7 figures

The new generation of observatories and instruments (VLT/ERIS, JWST, ELT) motivate the development of robust methods to detect and characterise faint and close-in exoplanets. Molecular mapping and cross-correlation for spectroscopy use molecular templates to isolate a planet's spectrum from its host star. However, reliance on signal-to-noise ratio (S/N) metrics can lead to missed discoveries, due to strong assumptions of Gaussian independent and identically distributed noise. We introduce machine learning for cross-correlation spectroscopy (MLCCS); the method aims to leverage weak assumptions on exoplanet characterisation, such as the presence of specific molecules in atmospheres, to improve detection sensitivity for exoplanets. MLCCS methods, including a perceptron and unidimensional convolutional neural networks, operate in the cross-correlated spectral dimension, in which patterns from molecules can be identified. We test on mock datasets of synthetic planets inserted into real noise from SINFONI at K-band. The results from MLCCS show outstanding improvements. The outcome on a grid of faint synthetic gas giants shows that for a false discovery rate up to 5%, a perceptron can detect about 26 times the amount of planets compared to an S/N metric. This factor increases up to 77 times with convolutional neural networks, with a statistical sensitivity shift from 0.7% to 55.5%. In addition, MLCCS methods show a drastic improvement in detection confidence and conspicuity on imaging spectroscopy. Once trained, MLCCS methods offer sensitive and rapid detection of exoplanets and their molecular species in the spectral dimension. They handle systematic noise and challenging seeing conditions, can adapt to many spectroscopic instruments and modes, and are versatile regarding atmospheric characteristics, which can enable identification of various planets in archival and future data., Comment: 27 pages, 24 figures. Submitted for publication in A&A January 2, 2024. After first iteration with the referee, resubmitted May 17, 2024

Multiple-instance learning (MIL) is an attractive approach for digital pathology applications as it reduces the costs related to data collection and labelling. However, it is not clear how sensitive MIL is to clinically realistic domain shifts, i.e., differences in data distribution that could negatively affect performance, and if already existing metrics for detecting domain shifts work well with these algorithms. We trained an attention-based MIL algorithm to classify whether a whole-slide image of a lymph node contains breast tumour metastases. The algorithm was evaluated on data from a hospital in a different country and various subsets of this data that correspond to different levels of domain shift. Our contributions include showing that MIL for digital pathology is affected by clinically realistic differences in data, evaluating which features from a MIL model are most suitable for detecting changes in performance, and proposing an unsupervised metric named Fr\'echet Domain Distance (FDD) for quantification of domain shifts. Shift measure performance was evaluated through the mean Pearson correlation to change in classification performance, where FDD achieved 0.70 on 10-fold cross-validation models. The baselines included Deep ensemble, Difference of Confidence, and Representation shift which resulted in 0.45, -0.29, and 0.56 mean Pearson correlation, respectively. FDD could be a valuable tool for care providers and vendors who need to verify if a MIL system is likely to perform reliably when implemented at a new site, without requiring any additional annotations from pathologists.

The investigation of the atmospheres of closely separated, directly imaged gas giant exoplanets is challenging due to the presence of stellar speckles that pollute their spectrum. To remedy this, the analysis of medium- to high-resolution spectroscopic data via cross-correlation with spectral templates (cross-correlation spectroscopy) is emerging as a leading technique. We aim to define a robust Bayesian framework combining, for the first time, three widespread direct-imaging techniques, namely photometry, low-resolution spectroscopy, and medium-resolution cross-correlation spectroscopy in order to derive the atmospheric properties of close-in directly imaged exoplanets. Our framework CROCODILE (cross-correlation retrievals of directly imaged self-luminous exoplanets) naturally combines the three techniques by adopting adequate likelihood functions. To validate our routine, we simulated observations of gas giants similar to the well-studied $\beta$~Pictoris~b planet and we explored the parameter space of their atmospheres to search for potential biases. We obtain more accurate measurements of atmospheric properties when combining photometry, low- and medium-resolution spectroscopy into atmospheric retrievals than when using the techniques separately as is usually done in the literature. We find that medium-resolution ($R \approx 4000$) K-band cross-correlation spectroscopy alone is not suitable to constrain the atmospheric properties of our synthetic datasets; however, this problem disappears when simultaneously fitting photometry and low-resolution ($R \approx 60$) spectroscopy between the Y and M bands. Our framework allows the atmospheric characterisation of directly imaged exoplanets using the high-quality spectral data that will be provided by the new generation of instruments such as VLT/ERIS, JWST/MIRI, and ELT/METIS.

When considering the opening part of 1800 short stories, we find that the first dozen paragraphs of the average narrative follow an action principle as defined in arXiv:2309.06600. When the order of the paragraphs is shuffled, the average no longer exhibits this property. The findings show that there is a preferential direction we take in semantic space when starting a story, possibly related to a common Western storytelling tradition as implied by Aristotle in Poetics., Comment: 6 pages, 4 figures, 3 tables

There is increasing evidence that human activity in general, and narrative in particular, can be treated as a dynamical system in the physics sense; a system whose evolution is described by an action integral, such that the average of all possible paths from point A to point B is given by the extremum of the action. We create by construction three such paths by averaging about 500 different narratives, and we show that the average path is consistent with an action principle., Comment: 9 pages, 9 figures, 1 table

This work provides five explicit constructions of the exceptional Lie algebra $\mathfrak{e}_8$, based on its semisimple subalgebras of maximal rank. Each of these models is graded by an abelian group, namely, $\mathbb{Z}_4$, $\mathbb{Z}_5$, $\mathbb{Z}_6$, $\mathbb{Z}_3^2$ and $\mathbb{Z}_2\times\mathbb{Z}_4$; the neutral component is direct sum of special linear algebras and the remaining homogeneous components are irreducible modules for it., Comment: 44 pages

Gravitational waves from isolated sources have eluded detection so far. The upper limit of long-lasting continuous gravitational wave emission can now probe physically-motivated models with the most optimistic being strongly constrained. Naturally, one might want to relax the assumption of the gravitational wave being quasi-infinite in duration, leading to the idea of transient continuous gravitational waves. In this paper, we outline how to get transient continuous waves from magnetars (or strongly-magnetised neutron stars) that exhibit glitches and/or antiglitches and apply the model to magnetar SGR J1935+2154. The toy model hypothesizes that at a glitch or antiglitch, mass is ejected from the magnetar but becomes trapped on its outward journey through the magnetosphere. Depending on the height of the trapped ejecta and the magnetic inclination angle, we are able to reproduce both glitches and antiglitches from simple angular momentum arguments. The trapped ejecta causes the magnetar to precess leading to gravitational wave emission at once and twice the magnetar's spin frequency, for a duration equal to however long the ejecta is trapped for. We find that the gravitational waves are more detectable when the magnetar is: closer, rotating faster, or has larger glitches/antiglitches. The detectability also improves when the ejecta height and magnetic inclination angle have values near their critical values, though this requires more mass to be ejected to remain consistent with the observed glitch/antiglitch. We find it unlikely that gravitational waves will be detected from SGR J1935+2154 when using the trapped ejecta model., Comment: 14 pages, 6 figures, 1 appendix. Accepted for publication in MNRAS

Over the past decade, hundreds of nights have been spent on the worlds largest telescopes to search for and directly detect new exoplanets using high-contrast imaging (HCI). Thereby, two scientific goals are of central interest: First, to study the characteristics of the underlying planet population and distinguish between different planet formation and evolution theories. Second, to find and characterize planets in our immediate Solar neighborhood. Both goals heavily rely on the metric used to quantify planet detections and non-detections. Current standards often rely on several explicit or implicit assumptions about the noise. For example, it is often assumed that the residual noise after data post-processing is Gaussian. While being an inseparable part of the metric, these assumptions are rarely verified. This is problematic as any violation of these assumptions can lead to systematic biases. This makes it hard, if not impossible, to compare results across datasets or instruments with different noise characteristics. We revisit the fundamental question of how to quantify detection limits in HCI. We focus our analysis on the error budget resulting from violated assumptions. To this end, we propose a new metric based on bootstrapping that generalizes current standards to non-Gaussian noise. We apply our method to archival HCI data from the NACO-VLT instrument and derive detection limits for different types of noise. Our analysis shows that current standards tend to give detection limit that are about one magnitude too optimistic in the speckle-dominated regime. That is, HCI surveys may have excluded planets that can still exist., Comment: After first iteration with the referee, resubmitted to AJ. Comments welcome!

Magnetars are conjectured to be highly magnetized neutron stars (NSs). Strong internal magnetic field and elasticity in the crust may deform the stars and lead to free precession. We study the precession dynamics of triaxially-deformed NSs incorporating the near-field and the far-field electromagnetic torques. We obtain timing residuals for different NS geometries and torques. We also investigate the polarized X-ray and radio signals from precessing magnetars. The modulations on the Stokes parameters are obtained for thermal X-rays emitted from the surface of magnetars. For radio signals, we apply the simple rotating vector model (RVM) to give the modulations on the position angle (PA) of the polarization. Our results are comprehensive, ready to be used to search for magnetar precession with timing data and polarizations of X-ray and radio emissions. Future observations of precessing magnetars will give us valuable information on the geometry and the strength of the strong magnetic fields, the emission geometry, as well as the equation of state (EoS) of NSs., Comment: 18 pages, 18 figures; accepted by MNRAS

The Hubble Space Telescope (HST) archives constitute a rich dataset of high resolution images to mine for strong gravitational lenses. While many HST programs specifically target strong lenses, they can also be present by coincidence in other HST observations. We aim to identify non-targeted strong gravitational lenses in almost two decades of images from the ESA it Hubble Space Telescope archive (eHST), without any prior selection on the lens properties. We used crowdsourcing on the Hubble Asteroid Hunter (HAH) citizen science project to identify strong lenses, alongside asteroid trails, in publicly available large field-of-view HST images. We visually inspected 2354 objects tagged by citizen scientists as strong lenses to clean the sample and identify the genuine lenses. We report the detection of 252 strong gravitational lens candidates, which were not the primary targets of the HST observations. 198 of them are new, not previously reported by other studies, consisting of 45 A grades, 74 B grades and 79 C grades. The majority are galaxy-galaxy configurations. The newly detected lenses are, on average, 1.3 magnitudes fainter than previous HST searches. This sample of strong lenses with high resolution HST imaging is ideal to follow-up with spectroscopy, for lens modelling and scientific analyses. This paper presents an unbiased search of lenses, which enabled us to find a high variety of lens configurations, including exotic lenses. We demonstrate the power of crowdsourcing in visually identifying strong lenses and the benefits of exploring large archival datasets. This study shows the potential of using crowdsourcing in combination with artificial intelligence for the detection and validation of strong lenses in future large-scale surveys such as ESA's future mission Euclid or in JWST archival images., Comment: 24 page, 14 figures, 5 tables, accepted for publication in A&A June 28 2022

The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission described herein has been selected for flight to Venus as part of the NASA Discovery Program. DAVINCI will be the first mission to Venus to incorporate science-driven flybys and an instrumented descent sphere into a unified architecture. The anticipated scientific outcome will be a new understanding of the atmosphere, surface, and evolutionary path of Venus as a possibly once-habitable planet and analog to hot terrestrial exoplanets. The primary mission design for DAVINCI as selected features a preferred launch in summer/fall 2029, two flybys in 2030, and descent sphere atmospheric entry by the end of 2031. The in situ atmospheric descent phase subsequently delivers definitive chemical and isotopic composition of the Venus atmosphere during a cloud-top to surface transect above Alpha Regio. These in situ investigations of the atmosphere and near infrared descent imaging of the surface will complement remote flyby observations of the dynamic atmosphere, cloud deck, and surface near infrared emissivity. The overall mission yield will be at least 60 Gbits (compressed) new data about the atmosphere and near surface, as well as first unique characterization of the deep atmosphere environment and chemistry, including trace gases, key stable isotopes, oxygen fugacity, constraints on local rock compositions, and topography of a tessera., Comment: 41 pages, 14 figures, accepted for publication in the Planetary Science Journal

It was recently reported that there exists a population of "glitch candidates" and "anti-glitch candidates" which are effectively small spin-ups and spin-downs of a neutron star with magnitudes smaller than those seen in typical glitches. The physical origin of these small events is not yet understood. In this paper, we outline a model that can account for the changes in spin, and crucially, is independently testable with gravitational wave observations. In brief, the model posits that small spin-up/spin-down events are caused by the excitation and decay of non-axisymmetric $f$-modes which radiate angular momentum away in a burst-like way as gravitational waves. The model takes the change in spin frequency as an input and outputs the initial mode amplitude and the signal-to-noise ratio achievable from gravitational wave detectors. We find that the model presented here will become falsifiable once 3rd generation gravitational wave detectors, like the Einstein Telescope and Cosmic Explorer, begin taking data., Comment: 9 pages, 5 figures. Cosmic Explorer analysis added in v2. Accepted for publication in MNRAS

Electrons accelerated on Earth by a rich variety of wave scattering or stochastic processes generate hard non-thermal X-ray bremsstrahlung up to >~ 1 MeV and power Earth's various types of aurorae. Although Jupiter's magnetic field is an order of magnitude larger than Earth's, space-based telescopes have previously detected X-rays only up to ~7 keV. On the basis of theoretical models of the Jovian auroral X-ray production, X-ray emission in the ~2-7 keV band has been interpreted as thermal (arising from electrons characterized by a Maxwell-Boltzmann distribution) bremsstrahlung. Here we report the observation of hard X-rays in the 8-20 keV band from the Jovian aurorae, obtained with the NuSTAR X-ray observatory. The X-rays fit to a flat power-law model with slope 0.60+/-0.22 - a spectral signature of non-thermal, hard X-ray bremsstrahlung. We determine the electron flux and spectral shape in the keV to MeV energy range using coeval in situ measurements by the Juno spacecraft's JADE and JEDI instruments. Jovian electron spectra of the form we observe have previously been interpreted to arise in stochastic acceleration, rather than coherent acceleration by electric fields. We reproduce the X-ray spectral shape and approximate flux observed by NuSTAR, and explain the non-detection of hard X-rays by Ulysses, by simulating the non-thermal population of electrons undergoing precipitating electron energy loss, secondary electron generation and bremsstrahlung emission in a model Jovian atmosphere. The results highlight the similarities between the processes generating hard X-ray auroras on Earth and Jupiter, which may be occurring on Saturn, too., Comment: 39 pages, 6 figures, 2 tables. Published in Nature Astronomy (https://www.nature.com/articles/s41550-021-01594-8)