Search

Many early universe scenarios predict an enhancement of scalar perturbations at scales currently unconstrained by cosmological probes. These perturbations source gravitational waves (GWs) at second order in perturbation theory, leading to a scalar-induced gravitational wave (SIGW) background. The LISA detector, sensitive to mHz GWs, will be able to constrain curvature perturbations in a new window corresponding to scales $k \in [10^{10}, 10^{14}] \,{\rm Mpc}^{-1}$, difficult to probe otherwise. In this work, we forecast the capabilities of LISA to constrain the source of SIGWs using different approaches: i) agnostic, where the spectrum of curvature perturbations is binned in frequency space; ii) template-based, modeling the curvature power spectrum based on motivated classes of models; iii) ab initio, starting from first-principles model of inflation featuring an ultra-slow roll phase. We compare the strengths and weaknesses of each approach. We also discuss the impact on the SIGW spectrum of non-standard thermal histories affecting the kernels of SIGW emission and non-Gaussianity in the statistics of the curvature perturbations. Finally, we propose simple tests to assess whether the signal is compatible with the SIGW hypothesis. The pipeline used is built into the SIGWAY code., Comment: 95 pages, 31 figures

Stellar-mass black-hole binaries are the most numerous gravitational-wave sources observed to date. Their properties make them suitable for observation both by ground- and space-based detectors. Starting from synthetic catalogues constructed based on observational constraints from ground-based detectors, we explore the detection rates and the characteristic parameters of the stellar-mass black-hole binaries observable by LISA during their inspiral, using signal-to-noise ratio thresholds as a detection criterion. We find that only a handful of these sources will be detectable with signal-to-noise ratio larger than 8: about 5 sources on average in 4 years of mission duration, among which only one or two are multiband ones (i.e. merging in less than 15 years). We find that detectable sources have chirp mass $10 M_\odot\lesssim \mathcal{M}_c\lesssim 100 M_\odot$, residual time-to-coalescence $4\mathrm{yr}\lesssim \tau_c\lesssim 100 \mathrm{yr}$, and redshift $z\lesssim 0.1$, much closer than those observed up to now by ground-based detectors. We also explore correlations between the number of LISA detectable sources and the parameters of the population, suggesting that a joint measurement with the stochastic signal might be informative of the population characteristics. By performing parameter estimation on a subset of sources from the catalogues, we conclude that, even if LISA measurements will not be directly informative on the population due to the low number of resolvable sources, it will characterise a few, low-redshift candidates with great precision. Furthermore, we construct for the first time the LISA waterfall plot for low chirp mass, and demonstrate that LISA will also be able to discriminate and characterize, through very precise parameter estimation, a population of binaries with higher masses, $\mathcal{M}_c\sim \mathcal{O}(10^3) M_\odot$, if it exists., Comment: 28 pages, 10 figures, 3 tables

In the search for stochastic gravitational wave backgrounds (SGWB) of cosmological origin with LISA, it is crucial to account for realistic complications in the noise and astrophysical foreground modeling that may impact the signal reconstruction. To address these challenges, we updated the $\texttt{SGWBinner}$ code to incorporate both variable noise levels across LISA arms and more complex foreground spectral shapes. Our findings suggest that, while moderate variations of the noise amplitudes have a minimal impact, poor foreground modeling (i.e., templates requiring many free parameters) significantly degrades the reconstruction of cosmological signals. This underlines the importance of accurate modeling and subtraction of the astrophysical foregrounds to characterize possible cosmological components. To perform this more challenging analysis, we have integrated the $\texttt{JAX}$ framework, which significantly improves the computational efficiency of the code, in the $\texttt{SGWBinner}$ code, enabling faster Bayesian likelihood sampling and more effective exploration of complex SGWB signals., Comment: 30 pages, 9 figures

Variations in the instrumental noise of the Laser Interferometer Space Antenna (LISA) over time are expected as a result of e.g. scheduled satellite operations or unscheduled glitches. We demonstrate that these fluctuations can be leveraged to improve the sensitivity to stochastic gravitational wave backgrounds (SGWBs) compared to the stationary noise scenario. This requires optimal use of data segments with downward noise fluctuations, and thus a data analysis pipeline capable of analysing and combining shorter time segments of mission data. We propose that simulation based inference is well suited for this challenge. In an approximate, but state-of-the-art, modeling setup, we show by comparison with Fisher Information Matrix estimates that the optimal information gain can be achieved in practice., Comment: 12 pages, 5 figures. saqqara available at https://github.com/peregrine-gw/saqqara, GW_response available at https://github.com/Mauropieroni/GW_response

Pulsar Timing Array (PTA) observations have recently gathered substantial evidence for the existence of a gravitational wave background in the nHz frequency band. Searching for anisotropies in this signal is key to determining its origin, and in particular to distinguish possible astrophysical from cosmological sources. In this work, we assess the sensitivity of current and future pulsar timing arrays to such anisotropies using the full covariance matrix of pulsar timing delays. While current day pulsar timing arrays can only set mildly informative constraints on the dipole and quadrupole, we show that percent level accuracy for several low multipoles can be achieved in the near future. Moreover, we demonstrate that anisotropies in the gravitational wave background and the Hellings-Downs angular correlation, indicating the presence of GWs, are approximately uncorrelated, and can hence be reconstructed independently. These results can be reproduced with \href{https://github.com/Mauropieroni/fastPTA}{\texttt{fastPTA}}, a publicly available Python code to forecast the constraining power of PTA configurations., Comment: 20 pages, 10 figures, 3 appendices

We obtain new bounds for the optimal matching cost for empirical measures with unbounded support. For a large class of radially symmetric and rapidly decaying probability laws, we prove for the first time the asymptotic rate of convergence for the whole range of power exponents $p$ and dimensions $d$. Moreover we identify the exact prefactor when $p\le d$. We cover in particular the Gaussian case, going far beyond the currently known bounds. Our proof technique is based on approximate sub- and super-additivity bounds along a geometric decomposition adapted to some features the density, such as its radial symmetry and its decay at infinity.

Various scenarios of cosmic inflation enhance the amplitude of the stochastic gravitational wave background (SGWB) at frequencies detectable by the LISA detector. We develop tools for a template-based analysis of the SGWB and introduce a template databank to describe well-motivated signals from inflation, prototype their template-based searches, and forecast their reconstruction with LISA. Specifically, we classify seven templates based on their signal frequency shape, and we identify representative fundamental physics models leading to them. By running a template-based analysis, we forecast the accuracy with which LISA can reconstruct the template parameters of representative benchmark signals, with and without galactic and extragalactic foregrounds. We identify the parameter regions that can be probed by LISA within each template. Finally, we investigate how our signal reconstructions shed light on fundamental physics models of inflation: we discuss their impact for measurements of \emph{e.g.,} ~the couplings of inflationary axions to gauge fields; the graviton mass during inflation; the fluctuation seeds of primordial black holes; the consequences of excited states during inflation, and the presence of small-scale spectral features., Comment: 82 pages, 29 figures; v2 matches version published in JCAP

The existence of a primordial stochastic gravitational wave background (SGWB) is a common prediction in various models of the early Universe. Despite constraints at different frequency ranges and claims of detection in the nHz range by Pulsar Timing Arrays, the amplitude and spectral dependence of the SGWB in the mHz range remain largely unknown. Plausible models of early Universe Physics predict a wide range of SGWB amplitudes, from undetectable to exceeding the constraints from Big Bang Nucleosynthesis. This paper explores the potential impact of a prominent primordial SGWB on LISA's main scientific targets. Our main analyses focuses on Massive Black Hole Binaries (MBHBs). By employing publicly available MBHB population models and state-of-the-art LISA's forecasting pipeline, we analyze the effects of the SGWB on MBHB detections. We find that the decrease in the signal-to-noise ratio induced by a strong primordial GWB can significantly reduce the number of detectable events, compromise the precision of constraints, and even hinder sky localization for some events. We also examine the impact of the SGWB on Stellar Origin Black Hole Binaries (SOBHBs) and Galactic Binaries (GBs), which are fainter sources than MBHBs. Depending on the spectral properties of the SGWB, we conclude that these sources could be either marginally affected or rendered completely undetectable. This largely unexplored aspect raises critical questions about the potential challenges posed by a prominent SGWB to LISA's astrophysical objectives, including MBHBs, SOBHBs, and GBs., Comment: 15 pages, 7 figures; v2 matches version accepted by PRD

We initiate the LISA template databank for stochastic gravitational wave backgrounds sourced by cosmic strings. We include two templates, an analytical template, which enables more flexible searches, and a numerical template derived directly from large Nambu-Goto simulations of string networks. Using searches based on these templates, we forecast the parameter space within the reach of the experiment and the precision with which their parameters will be reconstructed, provided a signal is observed. The reconstruction permits probing the Hubble expansion and new relativistic DoF in the early universe. We quantify the impact that astrophysical foregrounds can have on these searches. Finally, we discuss the impact that these observations would have on our understanding of the fundamental models behind the string networks. Overall, we prove that LISA has great potential for probing cosmic string models and may reach tensions as low as $G\mu =10^{-16} - 10^{-17} $, which translates into energy scales of the order $10^{11}~\text{GeV}$., Comment: 59 pages, 15 figures

Pulsar Timing Array (PTA) observations hinted towards the existence of a stochastic gravitational wave background (SGWB) in the nHz frequency band. Still, the nature of the SGWB signal cannot be confidently inferred from current data, and the leading explanation invokes mergers of supermassive black holes. If confirmed, such discovery would not only represent a turning point in our understanding of astrophysics, but it may severely limit the capability of searching for additional cosmological sources in the nHz frequency range. In this work, we build a simple framework to forecast the sensitivity of future PTA configurations and assess the parameter estimation of SGWB, which could consist of several contributions. We release the python code fastPTA implementing this framework and ready to use., Comment: 16 pages, 9 figures

We develop a tool for the analysis of stochastic gravitational wave backgrounds from cosmological first-order phase transitions with LISA: we initiate a template databank for these signals, prototype their searches, and forecast their reconstruction. The templates encompass the gravitational wave signals sourced by bubble collisions, sound waves and turbulence. Accounting for Galactic and extra-Galactic foregrounds, we forecast the region of the parameter space that LISA will reconstruct with better than $\sim 10\,\%$ accuracy, if certain experimental and theoretical uncertainties are solved by the time LISA flies. We illustrate the accuracy with which LISA can reconstruct the parameters on a few benchmark signals, both in terms of the template parameters and the phase transition ones. To show the impact of the forecasts on physics beyond the Standard Model, we map the reconstructed benchmark measurements into the parameter spaces of the singlet extension of the Standard Model and of the classically conformal invariant $U(1)_{B-L}$ model., Comment: 54 pages, 18 figures; v2 matches version published in JCAP

This paper presents a novel multi-modal Multi-Object Tracking (MOT) algorithm for self-driving cars that combines camera and LiDAR data. Camera frames are processed with a state-of-the-art 3D object detector, whereas classical clustering techniques are used to process LiDAR observations. The proposed MOT algorithm comprises a three-step association process, an Extended Kalman filter for estimating the motion of each detected dynamic obstacle, and a track management phase. The EKF motion model requires the current measured relative position and orientation of the observed object and the longitudinal and angular velocities of the ego vehicle as inputs. Unlike most state-of-the-art multi-modal MOT approaches, the proposed algorithm does not rely on maps or knowledge of the ego global pose. Moreover, it uses a 3D detector exclusively for cameras and is agnostic to the type of LiDAR sensor used. The algorithm is validated both in simulation and with real-world data, with satisfactory results., Comment: Published at IEEE European Control Conference 2024

The Laser Interferometer Space Antenna (LISA) is the first scientific endeavour to detect and study gravitational waves from space. LISA will survey the sky for Gravitational Waves in the 0.1 mHz to 1 Hz frequency band which will enable the study of a vast number of objects ranging from Galactic binaries and stellar mass black holes in the Milky Way, to distant massive black-hole mergers and the expansion of the Universe. This definition study report, or Red Book, presents a summary of the very large body of work that has been undertaken on the LISA mission over the LISA definition phase., Comment: 155 pages, with executive summary and table of contents

We analyze the detection prospects for potential Primordial Black Hole Binary (PBHB) populations buried in the Stellar-Origin Black Hole Binary (SOBHB) population inferred by the LVK collaboration. We consider different PBHB population scenarios and several future Gravitational Wave (GW) detectors. To separate the PBHB component from the SOBHB one, we exploit the prediction that the PBHB merger rate does not decline as fast as the SOBHB one at high redshift. However, only a tiny fraction of PBHB events may be resolved individually, and the sub-threshold events may yield an undetectable Stochastic GW Background (SGWB). For this reason, we determine the statistical significance of the PBHB contributions in the number of resolvable events seen in future Earth-based detectors and the SGWB measured at LISA. We find that the synergy between these probes will consistently help assess whether or not a sizeable PBHB population is present., Comment: 31 pages, 8 figures

Gravitational Waves (GW) sourced by second-order primordial curvature fluctuations are among the favored models fitting the recent pulsar timing array (PTA) measurement of a stochastic GW background (SGWB). We study how spectral distortions (SDs) and anisotropies of the cosmic microwave background (CMB) can constrain such scalar fluctuations. Whereas COBE FIRAS data have no sufficient sensitivity to probe the PTA log-normal hypothesis, we show how future PIXIE-like experiments can detect the CMB SDs from the scalar-induced interpretation of the SGWB in PTA data. We finally show how the transformative synergy between PTA data and future CMB SD measurements is important for reconstructing primordial fluctuations at these small scales., Comment: 8 pages, 3 figures + supplemental materials. v2 matches version published by PRD

The next generation of space- and ground-based facilities promise to reveal an entirely new picture of the gravitational wave sky: thousands of galactic and extragalactic binary signals, as well as stochastic gravitational wave backgrounds (SGWBs) of unresolved astrophysical and possibly cosmological signals. These will need to be disentangled to achieve the scientific goals of experiments such as LISA, Einstein Telescope, or Cosmic Explorer. We focus on one particular aspect of this challenge: reconstructing an SGWB from (mock) LISA data. We demonstrate that simulation-based inference (SBI) - specifically truncated marginal neural ratio estimation (TMNRE) - is a promising avenue to overcome some of the technical difficulties and compromises necessary when applying more traditional methods such as Monte Carlo Markov Chains (MCMC). To highlight this, we show that we can reproduce results from traditional methods both for a template-based and agnostic search for an SGWB. Moreover, as a demonstration of the rich potential of SBI, we consider the injection of a population of low signal-to-noise ratio supermassive black hole transient signals into the data. TMNRE can implicitly marginalize over this complicated parameter space, enabling us to directly and accurately reconstruct the stochastic (and instrumental noise) contributions. We publicly release our TMNRE implementation in the form of the code saqqara., Comment: 6 pages, 2 figures, 1 table + supplemental material. Code: saqqara available at https://github.com/PEREGRINE-GW/saqqara. Matches published version

We discuss the interpretation of the detected signal by Pulsar Timing Array (PTA) observations as a gravitational wave background (GWB) of cosmological origin. We combine NANOGrav 15-years and EPTA-DR2new data sets and confront them against backgrounds from supermassive black hole binaries (SMBHBs), and cosmological signals from inflation, cosmic (super)strings, first-order phase transitions, Gaussian and non-Gaussian large scalar fluctuations, and audible axions. We find that scalar-induced, and to a lesser extent audible axion and cosmic superstring signals, provide a better fit than SMBHBs. These results depend, however, on modeling assumptions, so further data and analysis are needed to reach robust conclusions. Independently of the signal origin, the data strongly constrain the parameter space of cosmological signals, for example, setting an upper bound on primordial non-Gaussianity at PTA scales as $|f_{nl}| \lesssim 2.34$ at 95% CL., Comment: 5 pages, 2 figures, and Supplemental material. V3: The version published in PRL

We use the latest constraints on the population of stellar origin binary black holes (SOBBH) from LIGO/Virgo/KAGRA (LVK) observations, to estimate the stochastic gravitational wave background (SGWB) they generate in the frequency band of LISA. We account for the faint and distant binaries, which contribute the most to the SGWB, by extending the merger rate at high redshift assuming it tracks the star formation rate. We adopt different methods to compute the SGWB signal: an analytical evaluation, Monte Carlo sums over SOBBH population realisations, and a method that accounts for the role of the detector by simulating LISA data and iteratively removing resolvable signals until only the confusion noise is left, allowing for the extraction of both the expected SGWB and the number of resolvable SOBBHs. Since the latter are few for SNR thresholds larger than five, we confirm that the spectral shape of the SGWB in the LISA band follows the analytical prediction of a power law. We infer the probability distribution of the SGWB amplitude from the LVK GWTC-3 posterior of the binary population model; its interquartile range of $h^2\Omega_\mathrm{GW}(f=3\times10^{-3}\,\mathrm{Hz}) \in [5.65,\,11.5]\times10^{-13}$ is in agreement with most previous estimates. We perform a MC analysis to assess LISA's capability to detect and characterise this signal. Accounting for both the instrumental noise and the galactic binaries foreground, with four years of data, LISA will be able to detect the SOBBH SGWB with percent accuracy, narrowing down the uncertainty on the amplitude by one order of magnitude with respect to the range of possible amplitudes inferred from the population model. A measurement of this signal by LISA will help to break the degeneracy among some of the population parameters, and provide interesting constraints, in particular on the redshift evolution of the SOBBH merger rate., Comment: 39 pages, 15 figures. Prepared for submission to JCAP

We explore the impact of choosing different sets of Time-Delay Interferometry (TDI) variables for detecting and reconstructing Stochastic Gravitational Wave Background (SGWB) signals and estimating the instrumental noise in LISA. Most works in the literature build their data analysis pipelines relying on a particular set of TDI channels, the so-called AET variables, which are orthogonal under idealized conditions. By relaxing the assumption of a perfectly equilateral LISA configuration, we investigate to which degree these channels remain orthogonal and compare them to other TDI channels. We show that different sets of TDI variables are more robust under perturbations of the perfect equilateral configuration, better preserving their orthogonality and, thus, leading to a more accurate estimate of the instrumental noise. Moreover, we investigate the impact of considering the noise levels associated with each instrumental noise source to be independent of one another, generalizing the analysis from two to twelve noise parameters. We find that, in this scenario, the assumption of orthogonality is broken for all the TDI variables, leading to a misestimation of measurement error for some of the noise parameters. Remarkably, we find that for a flat power-law signal, the reconstruction of the signal parameters is nearly unaffected in these various configurations., Comment: 31 pages, 13 figures, and supplementary material

The Einstein Telescope (ET), the European project for a third-generation gravitational-wave detector, has a reference configuration based on a triangular shape consisting of three nested detectors with 10 km arms, where in each arm there is a `xylophone' configuration made of an interferometer tuned toward high frequencies, and an interferometer tuned toward low frequencies and working at cryogenic temperature. Here, we examine the scientific perspectives under possible variations of this reference design. We perform a detailed evaluation of the science case for a single triangular geometry observatory, and we compare it with the results obtained for a network of two L-shaped detectors (either parallel or misaligned) located in Europe, considering different choices of arm-length for both the triangle and the 2L geometries. We also study how the science output changes in the absence of the low-frequency instrument, both for the triangle and the 2L configurations. We examine a broad class of simple `metrics' that quantify the science output, related to compact binary coalescences, multi-messenger astronomy and stochastic backgrounds, and we then examine the impact of different detector designs on a more specific set of scientific objectives., Comment: 197 pages, 73 figures. v2: corrections in the part on the sensitivity to stochastic backgrounds. Accepted in JCAP

In this study, we tested users' perception of accuracy and engagement with TikTok videos in which ChatGPT responded to prompts about "at-home" abortion remedies. The chatbot's responses, though somewhat vague and confusing, nonetheless recommended consulting with health professionals before attempting an "at-home" abortion. We used ChatGPT to create two TikTok video variants - one where users can see ChatGPT explicitly typing back a response, and one where the text response is presented without any notion to the chatbot. We randomly exposed 100 participants to each variant and found that the group of participants unaware of ChatGPT's text synthetization was more inclined to believe the responses were misinformation. Under the same impression, TikTok itself attached misinformation warning labels ("Get the facts about abortion") to all videos after we collected our initial results. We then decided to test the videos again with another set of 50 participants and found that the labels did not affect the perceptions of abortion misinformation except in the case where ChatGPT explicitly responded to a prompt for a lyrical output. We also found that more than 60% of the participants expressed negative or hesitant opinions about chatbots as sources of credible health information.

We solve the Random Euclidean Matching problem with exponent 2 for the Gaussian distribution defined on the plane. Previous works by Ledoux and Talagrand determined the leading behavior of the average cost up to a multiplicative constant. We explicitly determine the constant, showing that the average cost is proportional to (log N)^2, where N is the number of points. Our approach relies on a geometric decomposition allowing an explicit computation of the constant. Our results illustrate the potential for exact solutions of random matching problems for many distributions defined on unbounded domains on the plane.

The scientific effort devoted to health misinformation mostly focuses on the implications of misleading vaccines and communicable disease claims with respect to public health. However, the proliferation of abortion misinformation following the Supreme Court's decision to overturn Roe v. Wade banning legal abortion in the US highlighted a gap in scientific attention to individual health-related misinformation. To address this gap, we conducted a study with 60 TikTok users to uncover their experiences with abortion misinformation and the way they conceptualize, assess, and respond to misleading video content on this platform. Our findings indicate that users mostly encounter short-term videos suggesting herbal "at-home" remedies for pregnancy termination. While many of the participants were cautious about scientifically debunked "abortion alternatives," roughly 30% of the entire sample believed in their safety and efficacy. Even an explicit debunking label attached to a misleading abortion video about the harms of "at-home" did not help a third of the participants to dismiss a video about self-administering abortion as misinformation. We discuss the implications of our findings for future participation on TikTok and other polarizing topics debated on social media.