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Tamara M. Davis

Publications and source records attributed to Tamara M. Davis.

At least 19 recordsLinked to original sources

DESI DR2 Results III: The Mass of the Milky Way

We present measurements of the mass of the Milky Way using distant halo stars selected from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2). We apply four dynamical modeling methods to 10,036 RR Lyrae (RRL) and blue horizontal branch (BHB) stars with 6D phase space coordinates that span from $\sim$10 to 95 kpc from the Galactic center, the largest samples of their kind. All methods are applied to mock surveys based on cosmological simulations that include generating individual tracer stars, convolving their phase-space coordinates with DESI and Gaia DR3-like uncertainties, and tailored models of the survey selection functions. By comparing the performance on these mocks, we quantify how systematic biases from both methodology assumptions and galaxy disequilibrium impact each estimate. The mock-based systematics, which differ by method and tracer, are used to correct the individual estimates and to derive joint estimates using a rigorous formalism that accounts for per-method biases and residual correlations between methods. We obtain a joint estimate of the mass within 80 kpc to be $M(r < 80 \mathrm{\,kpc}) = 6.36^{+0.53}_{-0.48} \times 10^{11}$ M$_\odot$ and a virial mass estimate of $M_\mathrm{200c} = 1.19^{+0.14}_{-0.12} \times 10^{12}$ M$_\odot$, with similar results when combining only RRL-based or BHB-based measurements. These results provide a roadmap for future DESI efforts, as well as those in other spectroscopic surveys, to reliably constrain the mass of our Galaxy.

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AGN Reverberation Mapping with LITMUS: Fundamental Limits on lag Recovery Rates

Reverberation mapping of active galactic nuclei provides one of the most direct probes of the geometry and kinematics of the broad-line region by measuring time delays between continuum and line variability. Modern RM surveys frequently suffer difficulties with lag measurements due to poor signal to noise and aliasing, whereby multimodal lag posterior distributions arise due to seasonal gaps in our data. These challenge the reliability of commonly used fitting tools such as JAVELIN, which can return a high rate of false positives. We implement a new lag measurement package, LITMUS, and introduce a new framework that uses Bayesian evidence to identify false positive lag measurements, as well as examine the question of how many AGN present detectable lags in high redshift industrial scale surveys like OzDES and SDSS. Our analysis differs from previous RM studies in six key respects: (i) our inference is robust to the previously under-diagnosed numerical component of aliasing, (ii) we use a consistent methodology for all sources, (iii) uncertainty in the underlying AGN variability is fully marginalised, (iv) lag significance is assessed via Bayesian model comparison rather than heuristic metrics, (v) false-positive rates are quantified by comparison against random-chance recoveries and (vi) we use marginal likelihoods to distinguish between sources where a lag is not detectable in our data and sources that show no evidence of reverberation. Applied to the OzDES sample, we find that previous RM studies are likely to have overestimated the confidence of recovered lags, and we find a stark contrast between a low reverberation percentage for the MgII line (3-28% depending on assumptions) and much higher percentages in the CIV and especially the H$β$ line, which is consistent with 100%. We also present a re-analysed set of lags from the OzDES sample with better quantified reliabilities

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The scale of homogeneity in DESI Data Release 1

We present measurements of the scale of cosmic homogeneity using the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI), the largest publicly available spectroscopic extragalactic survey to date. Using a counts-in-spheres estimator applied to nearly 5 million galaxies and quasars across six independent redshift bins spanning $0.1 < z < 2.1$, we measure the correlation dimension $D_2(r)$ and define the homogeneity scale $R_H$ as the point at which the galaxy distribution reaches within 1\% of the homogeneous asymptotic value. We find that all tracers clearly transition to homogeneity, with the galaxy homogeneity scale ranging from $93.8^{+0.9}_{-0.7}$ to $142.6^{+1.4}_{-1.4}$ $h^{-1}$Mpc depending on the tracer redshift, galaxy bias, and modelling used to extract the scale. Using a cosmology-dependent model, we reconstruct the underlying matter homogeneity scale, finding it decreases monotonically with redshift in excellent agreement with $Λ$CDM predictions. We identify a systematic offset of up to $\sim 10\%$ between measurements in the North and South Galactic Caps, largely due to fiber assignment effects reproduced in our simulations. Accounting for this, and with a complementary demonstration using toy models that our methodology correctly identifies inhomogeneous universes in all but rather finely-tuned observer configurations, this hence provides strong evidence in favour of the cosmological principle across our full redshift range. Our matter homogeneity scale measurements are consistent with, and substantially more precise than, previous constraints from WiggleZ and SDSS, demonstrating the power of DESI data for precision tests of the cosmological principle.

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The Radius-Luminosity Relationship for Active Galactic Nuclei with Hierarchical Bayesian Reverberation Mapping

Reverberation mapping of active galactic nuclei uses the time taken for variability to travel through the system as a measure of system size, with this size being used to inform estimates of the mass of the central black hole, a technique that has graduated to an industrial-scale effort in recent decades. Such large target-count, multi-year surveys have been consistently undercut by poor light curve quality and the aliasing problems of seasonal observations. These impacts compound with statistical approaches that are not consistent between works and sometimes combine inconsistent statistical frameworks. Here, we present a new end-to-end Bayesian framework for fitting lags at scale in large surveys, simultaneous with the fitting of population models such as the radius-luminosity relation, and formulated in a numerically tractable way. This procedure is a statistically and numerically robust generalisation of the stacking and quality cut procedures of past works, fully marginalising over data uncertainty and data quality. Our approach remains numerically stable when scaling to larger surveys, and can act as a basis for any Bayesian population modelling of large sets of AGN time series observations. Applied to the OzDES sample, we demonstrate that this new approach yields more than double the constraining power on population-level properties like the R-L relationship, and an order-of-magnitude increase in the number of recovered lags and masses. With this method, we go from 24 high quality lag recoveries with traditional methods to a new effective sample size of ~297, all while being robust against random chance false positive measurements.

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The velocity coherence scale: a novel probe of cosmic homogeneity and a potential standard ruler

We introduce the velocity coherence scale $R_v$, the scale at which the spherical volume average of the trace of the velocity correlation tensor transitions from scaling faster than the sphere radius to scaling more slowly. This corresponds to the radius at which the average motion of galaxies along their separation vectors transitions from correlated to anti-correlated. We derive a theoretical estimator for $R_v$ by defining the bulk in spheres $B_R$, a velocity-field analogue of the mean scale counts used in density-field correlation analyses. We show that, for a statistically homogeneous matter distribution, the logarithmic derivative of $B_R$ and the correlation dimension $D_2$ share the same asymptotic behaviour and therefore can be used to estimate the scale of transition to statistical homogeneity. Furthermore, we show that in standard $Λ$CDM cosmologies the velocity coherence scale is tightly connected to the matter-radiation equality scale $k_{eq}$, and that its value in comoving coordinates is redshift-independent. These results highlight the potential of $R_v$ both as a standard ruler and as a physically motivated scale characterising the onset of cosmic homogeneity. We present a proof of concept using measurements of the PV correlation functions from SDSS. We show that the main challenge in determining $R_v$ is the limited precision of PV measurements compared to density ones, as they typically rely on smaller samples with larger uncertainties that scale roughly linearly with survey depth. Fitting our theoretical estimators for $R_v$, we obtain $R_v \approx 138^{+23}_{-54}\,\mathrm{Mpc}/h$. Finally, we show that more precise determinations should be achievable with current and upcoming peculiar velocity surveys.

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Skipping the rungs! Calibrating distance indicators through their clustering with galaxies

We show that angular cross-correlations between distance indicators and galaxy redshift catalogues, when interpreted within an assumed cosmological model, can constrain potential biases in distance measurements induced by calibration systematics. As a test case, we consider a simple scenario in which a constant calibration offset $ΔM$ shifts all observed distances by a multiplicative factor, and we produce Fisher forecasts for the constraining power on $ΔM$ and $H_0$ from existing and upcoming surveys. In our most optimistic scenario, based on the expected number of SN Ia observed by LSST and the DESI final data release, we find $σ_{ΔM} \approx 0.05$ and $σ_{H_0} \approx 1.81~\mathrm{km~s^{-1}~Mpc^{-1}}$. This has important implications for the Hubble tension, since explaining the discrepancy purely as a calibration systematic in low-$z$ measurements would require $ΔM \approx 0.13$.

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Dark siren cross-correlations and the sensitivity of $H_0$ to methodological choices

Gravitational wave sources act as absolute distance indicators, making them powerful probes of the present-day expansion rate of the Universe, $H_0$. The cross-correlation method combines gravitational wave events with galaxy catalogues to constrain cosmological parameters through their shared large-scale structure. In this work, we investigate how key methodological choices -- including covariance treatment, bias parametrisation for galaxies and gravitational wave events, and distance and redshift binning width -- affect the inferred value of $H_0$. We also study catalogue incompleteness, showing that selection effects can be incorporated directly into the theoretical prediction, without the need to model the missing population explicitly, a key advantage over the standard galaxy catalogue approach. Our results indicate that, with appropriate modelling choices and a sufficiently large sample of precise gravitational wave events, the systematic biases considered here can be effectively mitigated, highlighting the potential of the cross-correlation method for future dark siren precision cosmology.

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LITMUS: Bayesian Lag Recovery in Reverberation Mapping with Fast Differentiable Models

Reverberation mapping is a technique in which the mass of a Seyfert I galaxy's central supermassive black hole is estimated, along with the system's physical scale, from the timescale at which variations in brightness propagate through the galactic nucleus. This mapping allows for a long baseline of time measurements to extract spatial information beyond the angular resolution of our telescopes, and is the main means of constraining supermassive black hole masses at high redshift. The most recent generation of multi-year reverberation mapping campaigns for large numbers of active galactic nuclei (e.g. OzDES) have had to deal with persistent complications of identifying false positives, such as those arising from aliasing due to seasonal gaps in time-series data. We introduce LITMUS (Lag Inference Through the Mixed Use of Samplers), a modern lag recovery tool built on the "damped random walk" model of quasar variability, built in the autodiff framework JAX. LITMUS is purpose built to handle the multimodal aliasing of seasonal observation windows and provides evidence integrals for model comparison, a more quantified alternative to existing methods of lag validation. LITMUS also offers a flexible modular framework for extending modelling of AGN variability, and includes JAX-enabled implementations of other popular lag recovery methods like nested sampling and the interpolated cross correlation function. We test LITMUS on a number of mock light curves modelled after the OzDES sample and find that it recovers their lags with high precision and a successfully identifies spurious lag recoveries, reducing its false positive rate to drastically outperform the state of the art program JAVELIN. LITMUS's high performance is accomplished by an algorithm for mapping the Bayesian posterior density which both constrains the lag and offers a Bayesian framework for model null hypothesis testing.

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The DESI DR1 Peculiar Velocity Survey: global zero-point and $H_0$ constraints

The Dark Energy Spectroscopic Instrument (DESI) in its first Data Release (DR1) already provides more than 100,000 galaxies with relative distance measurements. The primary purpose of this paper is to perform the calibration of the zero-point for the DESI Fundamental Plane and Tully-Fisher relations, which allows us to measure the Hubble constant, $H_0$. This sample has a lower statistical uncertainty than any previously used to measure $H_0$, and we investigate the systematic uncertainties in absolute calibration that could limit the accuracy of that measurement. We improve upon the DESI Early Data Release Fundamental Plane $H_0$ measurement by a) using a group catalog to increase the number of calibrator galaxies and b) investigating alternative calibrators in the nearby Universe. Our baseline measurement calibrates to the SH0ES/Pantheon+ type Ia supernovae, and finds $H_0=73.7\pm 0.06\;(\text{stat.})\pm 1.1\;(\text{syst.})$ km s$^{-1}$ Mpc$^{-1}$. Calibrating to surface brightness fluctuation (SBF) distances yields a similar $H_0$. We explore measurements using other calibrators, but these are currently less precise since the overlap with DESI peculiar velocity tracers is much smaller. In future data releases with an even larger peculiar velocity sample, we plan to calibrate directly to Cepheids and the tip of the red giant branch, which will enable the uncertainty to decrease towards a percent-level measurement of $H_0$. This will provide an alternative to supernovae as the Hubble flow sample for $H_0$ measurements.

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Inference of matter power spectrum at z=0 using DESI DR1 Full-Shape data

Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D matter power spectrum at redshift $ z = 0 $ using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the $ Λ\text{CDM} $ model, and compare it to the result assuming the $ w_0w_a \text{CDM} $ model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. The EFT approach offers a more robust methodology than traditional methods for modelling the galaxy power spectrum from galaxy clustering data, which can be used to test the consistency of the assumed cosmological model. By incorporating both CMB and galaxy clustering data across a range of redshifts, we can identify discrepancies between the datasets, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with $ Λ\text{CDM} $, this work extends the analysis with higher-quality data to further test the expansion histories of both $ Λ\text{CDM} $ and $ w_0w_a \text{CDM} $. Our findings show that both $ Λ\text{CDM} $ and $ w_0w_a \text{CDM} $ provide consistent fits to the matter power spectrum recovered from DESI DR1 data.

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Still Accelerating: Type Ia supernova cosmology is robust to host galaxy age evolution

Type Ia supernovae are a cornerstone of modern cosmology, providing first evidence for cosmic acceleration and new tests of dark energy. Son et al. 2025 (S25) claim a strong redshift evolution in standardized supernova luminosities driven by supernova progenitor age, with dramatic cosmological implications: rapidly evolving dark energy, decelerating expansion, and a $9σ$ tension with $Λ$CDM. We show that the underpinning evidence required for this conclusion -- the supernova progenitor-age dependence, the redshift-dependent age difference, and their combined impact -- is either negligible or relies on effects already corrected for in modern supernova analyses. First, the S25 analysis omits the standard host-galaxy stellar mass correction that captures known environmental dependencies that also correlate with stellar age. Applying this correction to the S25 sample, we find no dependence of standardized supernova brightness on host age. Independent data also show no significant difference at low-redshift in standardized brightness between star-forming galaxies and several Gyr older quiescent galaxies of the same stellar mass. Second, the S25 scenario predicts strong redshift evolution of the host-mass effect. Data from the Dark Energy Survey supernova survey measure evolution of $-0.028 \pm 0.034~\mathrm{mag}\,z^{-1}$, consistent with zero and altering the dark-energy equation-of-state measurement ($w$) by $<$0.01 if included. Third, we demonstrate that the claimed $\sim5$~Gyr progenitor age difference between nearby and distant supernovae is overstated by factors of three to five largely due to a conflation of host galaxy age with supernova progenitor age. We conclude that type~Ia supernova cosmology remains robust for current measurements of dark energy.

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Limits of self-interacting neutrinos from the BAO and CMB phase shift

Neutrinos with Standard Model interactions free-stream in the early Universe, leaving a distinct phase shift in the pattern of baryon acoustic oscillations (BAO). When isolated, this phase shift allows one to robustly infer the presence of the cosmic neutrino background in BAO and cosmic microwave background (CMB) data independently of other cosmological parameters. While in the context of the Standard Model, this phase shift follows a known scale-dependent relation, new physics in the cosmic neutrino background could alter the overall shape of this feature. In this paper, we discuss how changes in the neutrino phase shift could be used to constrain self-interactions among neutrinos. We produce simple models for this phase-shift assuming universal self-interactions, and use these in order to understand what constraining power is available for the strength of such interactions in BAO and CMB data. We find that, although challenging, it may be possible to use a detection of the phase to put a more robust limit on the strength of the self-interaction, $G_{\mathrm{eff}}$, which at present suffers from bimodality in cosmological constraints. Our forecast analysis reveals that BAO data alone will not provide the precision needed to tightly constrain self-interactions; however, the combined analysis of the phase shift signature in both CMB and BAO can potentially provide a way to detect the impact of new neutrino interactions. Our results could be extended upon for models with non-universal interactions.

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Probing the environment around GW170817 with DESI: insights on galaxy group peculiar velocities for standard siren measurements

We present a new measurement of the Hubble constant, $H_0$, following the gravitational wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance $\sim 40 $ Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy due to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group's properties and NGC 4993's membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a five-fold increase in galaxies compared to previous observations with many of these galaxies contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is part with a halo mass of order $\sim$$10^{13}~M_\odot$. Using peculiar velocity measurements from our Fundamental Plane galaxies observations, we find $H_0 =70.9^{+6.4}_{-8.5}$ km s$^{-1}$ Mpc$^{-1}$. In addition, using a peculiar velocity measurement for NGC 4993 from Surface Brightness Fluctuations in Cosmicflows-4 we find $H_0 =73.4^{+3.3}_{-3.9}$ km s$^{-1}$ Mpc$^{-1}$. We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on the $H_0$ measurement. Our results highlight the importance of multiplexed spectroscopic observations of the environments of gravitational wave events to probe local dynamics, which can ultimately affect standard siren measurements.

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Dark sirens and the impact of redshift precision

With the growing number of gravitational wave detections, achieving a competitive measurement of $H_0$ with dark sirens is becoming increasingly feasible. The expansion of the Ligo-Virgo-KAGRA Collaboration into a four detector network will reduce both the localisation area and the luminosity distance uncertainty associated with each gravitational wave event. It is therefore essential to identify and mitigate other major sources of error that could increase the uncertainty in $H_0$. In this work, we explore three scenarios relevant to the dark siren method in future observing runs. First, we demonstrate that there is a precision gain offered by a catalogue of spectroscopic-like redshifts compared to photometric-like redshifts, with the greatest improvements observed in smaller localisation areas. Second, we show that redshift outliers (as occur in realistic photometric redshift catalogues), do not introduce bias into the measurement of $H_0$. Finally, we find that uniformly sub-sampling spectroscopic-like redshift catalogues increases the uncertainty in $H_0$ as the completeness fraction is decreased; at a completeness of 50% the benefit of spectroscopic redshift precision is outweighed by the degradation from incompleteness. In all three scenarios, we obtain unbiased estimates of $H_0$. We conclude that a competitive measurement of $H_0$ using the dark siren method will require a hybrid catalogue of both photometric and spectroscopic redshifts, at least until highly complete spectroscopic catalogues become available. This, however, will come at the cost of a more complex selection function.

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Encyclopedia of Astrophysics: The Expanding Universe

The expansion of the Universe is the basis of modern cosmology. This chapter outlines the theory behind the expansion of the universe, including the cosmological principle, distances, velocities, and accelerations. We provide basic derivations of the key equations and highlight some interesting features, such as superluminal expansion, how pressure increases gravitational attraction, the subtleties of conservation of energy in the expanding universe, and the existence of cosmological horizons.

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Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform

We present a cosmology analysis of simulated weak lensing convergence maps using the Neural Field Scattering Transform (NFST) to constrain cosmological parameters. The NFST extends the Wavelet Scattering Transform (WST) by incorporating trainable neural field filters while preserving rotational and translational symmetries. This setup balances flexibility with robustness, ideal for learning in limited training data regimes. We apply the NFST to 500 simulations from the CosmoGrid suite, each providing a total of 1000 square degrees of noiseless weak lensing convergence maps. We use the resulting learned field compression to model the posterior over $Ω_m$, $σ_8$, and $w$ in a $w$CDM cosmology. The NFST consistently outperforms the WST benchmark, achieving a 16% increase in the average posterior probability density assigned to test data. Further, the NFST improves direct parameter prediction precision on $σ_8$ by 6% and $w$ by 11%. We also introduce a new visualization technique to interpret the learned filters in physical space and show that the NFST adapts its feature extraction to capture task-specific information. These results establish the NFST as a promising tool for extracting maximal cosmological information from the non-Gaussian information in upcoming large-scale structure surveys, without requiring large simulated training datasets.

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Learning Intrinsic Alignments from Local Galaxy Environments

We present DELTA (Data-Empiric Learned Tidal Alignments), a deep learning model that isolates galaxy intrinsic alignments (IAs) from weak lensing distortions using only observational data. The model uses an Equivariant Graph Neural Network backbone suitable for capturing information from the local galaxy environment, in conjunction with a probabilistic orientation output. Unlike parametric models, DELTA flexibly learns the relationship between galaxy shapes and their local environments, without assuming an explicit IA form or relying on simulations. When applied to mock catalogs with realistic noisy IAs injected, it accurately reconstructs the noise-free, pure IA signal. Mapping these alignments provides a direct visualization of IA patterns in the mock catalogs. Combining DELTA with deep learning interpretation techniques provides further insights into the physics driving tidal relationships between galaxies. This new approach to understanding and controlling IAs is suitable for application to joint photometric and spectroscopic surveys such as the combination of upcoming Euclid, Rubin, and DESI datasets.

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Constraining the phase shift of relativistic species in DESI BAOs

In the early Universe, neutrinos decouple quickly from the primordial plasma and propagate without further interactions. The impact of free-streaming neutrinos is to create a temporal shift in the gravitational potential that impacts the acoustic waves known as baryon acoustic oscillations (BAOs), resulting in a non-linear spatial shift in the Fourier-space BAO signal. In this work, we make use of and extend upon an existing methodology to measure the phase shift amplitude $β_ϕ$ and apply it to the DESI Data Release 1 (DR1) BAOs with an anisotropic BAO fitting pipeline. We validate the fitting methodology by testing the pipeline with two publicly available fitting codes applied to highly precise cubic box simulations and realistic simulations representative of the DESI DR1 data. We find further study towards the methods used in fitting the BAO signal will be necessary to ensure accurate constraints on $β_ϕ$ in future DESI data releases. Using DESI DR1, we present individual measurements of the anisotropic BAO distortion parameters and the $β_ϕ$ for the different tracers, and additionally a combined fit to $β_ϕ$ resulting in $β_ϕ = 2.7 \pm 1.7$. After including a prior on the distortion parameters from constraints using \textit{Planck} we find $β_ϕ = 2.7^{+0.60}_{-0.67} $ suggesting $β_ϕ > 0$ at 4.3$σ$ significance. This result may hint at a phase shift that is not purely sourced from the standard model expectation for $N_{\rm{eff}}$ or could be a upwards statistical fluctuation in the measured $β_ϕ$; this result relaxes in models with additional freedom beyond $Λ$CDM.

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