The case against ΛCDM rests on three pillars of modern observational cosmology: the clustering of galaxies, type Ia supernovae, and the Cosmic Microwave Background. Each probe measures a different aspect of the universe’s expansion history and growth of structure, and each comes with its own systematics. When combined, they constrain the equation-of-state parameter w, the ratio of dark energy’s pressure to its energy density. A pure cosmological constant corresponds to exactly w = −1, unchanging for all of cosmic time. Any statistically significant deviation from that value, or any evidence that w evolves, would amount to a conviction that dark energy is dynamical rather than constant.

The most prominent evidence has come from the Dark Energy Spectroscopic Instrument, or DESI, which measures baryon acoustic oscillations, the fossil imprint of sound waves in the early universe that serves as a standard ruler for mapping expansion. DESI’s first data release, published in 2024, and its second release in 2025, when combined with supernova and microwave background data, have shown hints that dark energy may be weakening over time. In the widely used Chevallier–Polarski–Linder parametrization, which allows w to vary as w(a) = w0 + wa(1 − a), the combined data prefer values that drift away from the ΛCDM point of w0 = −1 and wa = 0. The statistical significance of these hints depends on which supernova sample is used, but in some combinations it reaches the three-sigma level, enough to make the community sit up and take notice.

Supernova data themselves are under scrutiny. The Dark Energy Survey’s full five-year sample of roughly 1,500 high-redshift type Ia supernovae, together with the Pantheon+ and Union3.1 compilations of around 2,000 supernovae, have each been analyzed for evidence of evolving dark energy. A reanalysis of the DES supernova program with an updated calibration reported evidence for evolving dark energy, while other work has emphasized possible systematics. One particularly consequential issue is progenitor age bias: analyses have found strong evidence that the properties of type Ia supernovae correlate with the ages of their host galaxies, an effect that could mimic or mask cosmological signals. Counter-analyses, however, argue that supernova cosmology remains robust to host galaxy age evolution and that the universe is still accelerating regardless of how the dark energy debate is resolved. As Lahav and Shah note, the jury on supernova systematics is still deliberating.

The Cosmic Microwave Background adds its own complications. The Planck 2018 results remain strikingly consistent with ΛCDM, and newer measurements from the Atacama Cosmology Telescope DR6 and SPT-3G broadly confirm the picture, though with intriguing wrinkles. One wrinkle involves the optical depth to reionization, a parameter that governs how the first stars reionized the intergalactic medium. Some analyses suggest that an increased optical depth could relieve tensions within the CMB data, and related work has explored how inferences about neutrino masses, which have in some fits come out unphysically negative, might be entangled with the optical depth. Meanwhile, the flood of galaxies discovered by the James Webb Space Telescope has raised questions about whether there are enough early photons to account for reionization on the usual timescales, prompting proposals of rapid late-time reionization scenarios. Each of these threads shows how a single parameter adjustment can ripple through the entire inferential chain.

Weak gravitational lensing surveys, which measure how the clustering of matter distorts the images of distant galaxies, provide an independent test of ΛCDM’s predictions for the growth of cosmic structure. Results from the Kilo-Degree Survey, the Dark Energy Survey, and the Hyper Suprime-Cam have historically shown mild tension with Planck’s predictions for the amplitude of matter clustering, a discrepancy known as the S8 tension. The latest KiDS-Legacy analysis, using the complete survey, has moved the lensing constraints closer to the Planck values, weakening what once looked like a serious crack in the model. The DES Year 6 clustering and lensing results are expected to sharpen this picture further. For the prosecution, the fading of the S8 tension is an inconvenient development; for the defense, it is evidence that earlier anomalies were statistical fluctuations or systematic errors rather than signs of new physics.

Beyond the raw data, the debate has a statistical dimension that Lahav and Shah treat with care. Bayesian model comparison asks not merely which model fits the data best, but whether the improvement in fit justifies the additional parameters that dynamical dark energy models require. Several recent analyses have examined the DESI evidence for evolving dark energy from a Bayesian perspective, quantifying tensions and comparing standard cosmologies, and the conclusions range from cautious skepticism to modest support for evolution. There is also a deeper theoretical problem: as work on the underdetermination of dark energy has shown, many physically distinct models, including scalar fields with nonminimal couplings, theories that cross the so-called phantom divide where w < −1, and models that violate the null energy condition, can all be made consistent with current data. The mirage of a measured w exactly equal to −1, as Eric Linder warned nearly two decades ago, means that even a perfect agreement with ΛCDM would not prove the cosmological constant is real.

The trial, then, is far from over, and the next decade promises a flood of new evidence. Stage-5 spectroscopic surveys, including the continued operation of DESI and proposed facilities such as the MUltiplexed Survey Telescope and the Wide-field Spectroscopic Telescope, will map tens of millions of galaxies with unprecedented precision. The Nancy Grace Roman Space Telescope, the Vera C. Rubin Observatory’s Legacy Survey of Space and Time, and dedicated supernova programs such as TiDES on 4MOST and the Dark Energy Bedrock All-sky Supernova Program will multiply the supernova sample and control its systematics. The Simons Observatory, SPT-3G, and the LiteBIRD satellite will refine the CMB constraints, while the NASA Landolt Mission aims to deliver a new generation of fundamental photometric standards that could recalibrate the entire supernova distance ladder. Peculiar velocity surveys, such as the DESI Fundamental Plane program, offer yet another route to measuring cosmic expansion that is less dependent on supernova standardization.

What is at stake goes beyond a single parameter. If dark energy is truly constant, the universe will continue to expand forever at an accelerating rate, drifting toward a cold, empty future in which galaxies recede beyond each other’s horizons. If dark energy weakens, decays, or eventually reverses sign, the long-term fate of the cosmos could be very different, and the theoretical machinery of general relativity may need modification on the largest scales. Either outcome would be profound. A confirmation of Λ would deepen what physicists call the cosmological constant problem, the baffling discrepancy between the observed value of Λ and the enormous predictions of quantum field theory, arguably the worst quantitative prediction in the history of science. A detection of dynamical dark energy would point instead toward new fields or modified gravity, reshaping particle physics and cosmology alike.

Lahav and Shah’s verdict is deliberately measured. The recent measurements from galaxy clustering, supernovae, and the CMB have indeed put ΛCDM on trial, and some combinations of data show suggestive evidence against a constant Λ, but the case is not yet proven. Systematic uncertainties in supernova calibration, host galaxy evolution, reionization physics, and CMB foregrounds all remain active areas of investigation, and the history of cosmology offers many examples of anomalies that dissolved under scrutiny. At the same time, the convergence of independent hints from DESI and multiple supernova samples is unusual enough that the community is right to prepare for a paradigm shift. The coming years of Stage-5 surveys and space-based observations will act as the appeals court, and whichever way the evidence falls, our understanding of the universe’s most mysterious component, and of the universe’s own destiny, is set to be transformed.

Subject of Research: Testing the ΛCDM cosmological model and the evidence for dynamical dark energy from galaxy clustering, supernovae, and the Cosmic Microwave Background

Article Title: ΛCDM in a courtroom

Article References: Lahav, O., & Shah, P. (2026). ΛCDM in a courtroom. Nature Astronomy. https://doi.org/10.1038/s41550-026-02977-5

Image Credits: AI Generated

DOI: 10.1038/s41550-026-02977-5

Keywords: cosmology, dark energy, cosmological constant, ΛCDM, DESI, type Ia supernovae, Cosmic Microwave Background, baryon acoustic oscillations, weak gravitational lensing, Hubble tension, Bayesian model comparison, Stage-5 surveys

The question of how dark matter is distributed in the Galactic halo is far more than an exercise in curve-fitting. The shape of the halo determines the local dark matter density, which in turn sets the expected signal rate for direct detection experiments searching for weakly interacting massive particles deep underground. It also governs how astronomers model the orbits of stellar streams, the dynamics of satellite galaxies, and the total mass of the Milky Way out to its farthest reaches. For decades, simulations of cold dark matter have suggested that halos should follow the NFW profile, whose density diverges as a power law toward the galactic center, producing a so-called “cuspy” core. Yet observations of many galaxies, particularly dwarf spirals, have long hinted that their dark matter is more centrally diffuse, or “cored,” a tension that ranks among the most persistent small-scale challenges to the standard cosmological paradigm.

Singh and Desai approached the problem with the full machinery of modern Bayesian statistics. Rather than simply asking which model fits the data best in a least-squares sense, they computed the Bayesian evidence for each model, a quantity that balances goodness of fit against model complexity and naturally penalizes models that add parameters without earning them. The computations were performed using DYNESTY, a dynamic nested sampling package that efficiently estimates both posterior distributions and evidences for high-dimensional models. The team combined three different baryonic mass models, describing the visible matter in the Galactic bulge, disk, and gas, with seven dark matter halo profiles, including the NFW profile, the Einasto profile, the Burkert profile, the Plummer profile, and several cored variants such as the pseudo-isothermal halo and the core-modified profile of Lazar and collaborators.

On the data side, the authors exploited four recent rotation curve compilations built on Gaia Data Release 3, the third and most precise catalog of positions, distances, and proper motions for nearly two billion stars delivered by the Gaia spacecraft. These include the circular velocity curve of the Milky Way derived from luminous red giant branch stars by Zhou and colleagues, the kinematic mapping of the Galactic disk to roughly 30 kiloparsecs by Wang and collaborators, and related datasets that trace the Galaxy’s rotation from about 5 to 25 kiloparsecs from the Galactic center. Each dataset encodes the same fundamental observable: the orbital speed of stars and gas as a function of distance from the Galactic center. Because the visible matter alone cannot explain why orbital speeds remain roughly flat, or in some recent analyses even decline in Keplerian fashion, at large radii, the shape of the rotation curve at those distances is a direct probe of the invisible halo.

The results carry implications that ripple across dark matter physics. In nearly every dataset-baryon combination the authors tested, the Einasto profile emerged as the preferred phenomenological description, beating the NFW profile by decisive margins in the Bayesian evidence. The Einasto profile, first introduced by Jaan Einasto in 1965 in a completely different context as a model for galactic light distributions, describes the halo density as a slowly varying power of the radius, falling more gradually near the center than NFW’s sharp cusp. Its victory here suggests that the Milky Way’s inner halo is smoother and less centrally concentrated than the classic cold dark matter prediction, at least as probed by Gaia-era kinematics.

Equally significant was the performance of the cored profiles. Models in which the dark matter density flattens to a finite central value, such as the Burkert profile originally proposed to explain dwarf galaxy halos, were systematically preferred over the cuspy NFW model. This finding aligns the Milky Way with a broader pattern seen in external galaxies and lends indirect support to scenarios in which baryonic feedback, the energetic outflows from star formation that push gas and dark matter around, or even self-interacting dark matter, reshapes the inner halo. The authors caution, however, that their conclusions apply within the adopted modeling framework and the specific Gaia-based rotation curve datasets used; the comparison is phenomenological rather than a falsification of any particular particle physics model.

The study also delivered a pointed verdict on modified gravity. Modified Newtonian Dynamics, or MOND, proposed by Mordehai Milgrom in 1983, dispenses with particle dark matter altogether by altering the law of gravity at accelerations below a characteristic scale of roughly 10^-10 meters per second squared. Singh and Desai tested MOND using three different interpolating functions, the mathematical bridges that connect the Newtonian and deep-MOND regimes, coupled to the same baryonic models. Within the implementations they considered, all three MOND variants provided poorer fits to the Gaia-based Milky Way rotation curve than the best dark matter profiles, and the Bayesian evidence firmly ranked them below the Einasto and cored halo models. While the authors are careful to note that this does not exhaust every possible MOND formulation, particularly fully relativistic extensions, it adds the Milky Way’s own kinematics to the list of arenas where modified gravity struggles to compete on equal statistical footing.

One perhaps counterintuitive outcome of the analysis is what did not matter: the baryonic models. The team’s three descriptions of the Galaxy’s luminous content, differing in how they treat the stellar disk, thick disk, and gas distribution, produced no decisive winner. None of the baryonic models was consistently favored over the others across the dark matter profiles and datasets. This suggests that, at the level of precision currently offered by the rotation curve data, systematic uncertainties in the baryonic component are not the dominant driver of model preference; the dark matter profile itself is doing the discriminating work. It also underscores how much room remains for improvement, since future data with tighter errors at large Galactic radii could well sharpen the sensitivity to the visible mass distribution.

The timing of this work is notable. Recent analyses of Gaia DR3 data, including the detection of a Keplerian decline in the Milky Way rotation curve beyond the solar circle by Jiao and collaborators, have reignited debate about the Galaxy’s total mass and halo structure, with some authors arguing that a lighter, faster-declining Milky Way carries cosmological consequences. Assessing the robustness of rotation curves inferred through the Jeans equations against cosmological simulations, as Koop and colleagues have done, remains an active concern, since systematics in distance estimates and stellar selection can bias the inferred velocities. By folding multiple independent rotation curve compilations into a single Bayesian comparison framework, Singh and Desai have provided a way to see which conclusions survive the choice of dataset, a robustness check that single-dataset analyses cannot offer.

The broader stakes extend beyond Galactic astronomy. Dark matter remains one of the most profound unsolved problems in physics, evidenced across galaxy rotation curves, gravitational lensing, and the cosmic microwave background, yet still escaping direct detection after decades of increasingly sensitive experiments. Pinning down the precise shape of the Milky Way’s halo matters for interpreting those experiments, because the local density and velocity distribution of dark matter set the expected event rates in detectors. A smoother, cored, or Einasto-like halo changes the translation between detector limits and particle properties. As Gaia continues to refine our map of the Galaxy and future surveys extend rotation measurements to ever larger radii, the Bayesian machinery demonstrated in this study offers a template: rather than assuming a halo model, let the data adjudicate among them. For now, the Milky Way’s dark matter appears to prefer the gentle mathematics of Einasto over the sharp cusp of NFW, and to leave little statistical room for gravity itself to do the dark matter’s work.