Physics

Galaxy Phase-space and Field-level Cosmology: The Strength of Semianalytic Models

(2026)

Semianalytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physically motivated prescriptions. They have also proven to be an efficient alternative for generating accurate galaxy catalogs, offering a faster and less computationally expensive option compared to full hydrodynamical simulations. In this paper, we demonstrate that, using only galaxy 3D positions and radial velocities, we can train a graph neural network coupled to a moment neural network to obtain a robust machine-learning-based model capable of estimating the matter density parameters, Ωm, with a precision of approximately 10%. The network is trained on (25 h−1 Mpc)3 volumes of galaxy catalogs from L-Galaxies and can successfully extrapolate its predictions to other semianalytic models (GAEA, SC-SAM, and Shark) and, more remarkably, to hydrodynamical simulations (Astrid, SIMBA, IllustrisTNG, and SWIFT-EAGLE). Our results show that the network is robust to variations in astrophysical and subgrid physics, cosmological and astrophysical parameters, and the different halo-profile treatments used across simulations. This suggests that the physical relationships encoded in the phase space of semianalytic models are largely independent of their specific physical prescriptions, reinforcing their potential as tools for the generation of realistic mock catalogs for cosmological parameter inference.

A prototype hybrid mode cavity for heterodyne axion detection

(2026)

In the heterodyne approach to axion detection, axion dark matter induces transitions between two modes of a microwave cavity, resulting in a parametrically enhanced signal power. We describe the fabrication and characterization of a prototype normal conducting cavity specifically optimized for heterodyne detection. Corrugations on the cavity walls support linearly polarized hybrid modes which maximize the signal power while strongly suppressing noise. We demonstrate tuning mechanisms which allow one mode frequency to be scanned across a 4 MHz range, while suppressing cross-coupling noise by at least 80 dB. A future superconducting cavity with identical geometry to our prototype would have the potential to probe orders of magnitude beyond astrophysical bounds.

Search for emerging jets in pp collisions at s=13TeV with the ATLAS experiment

(2026)

A search is presented for emerging jets using 140fb-1$$140~\textrm{fb}^{-1}$$ of proton–proton collision data at s=13TeV$$\sqrt{s} = 13~\textrm{TeV}$$, collected by the ATLAS experiment between 2015 and 2018. The search looks for the existence of a dark sector with symmetries similar to those in quantum chromodynamics. This dark sector is populated with dark quarks, which undergo showering similar to quarks in the Standard Model, leading to a high multiplicity of long-lived dark hadrons within a dark jet. These dark hadrons subsequently decay to Standard Model particles via a new heavy scalar mediating particle ϕ$$\phi $$. This results in jets which contain multiple displaced vertices, known as emerging jets. This analysis targets four-jet topologies, with two emerging jets and two Standard Model jets, resulting from the decay of pair-produced scalar mediators. No significant excess above the Standard Model background is observed. For dark pion proper decay lengths of 20mm$$20~\textrm{mm}$$, mediator masses are excluded between 1 and 2TeV$$2~\textrm{TeV}$$ assuming a dark pion mass of 20GeV$$20~\textrm{GeV}$$.

Combination of Measurements of CP Properties of Higgs Boson Interactions with Vector Bosons Using Proton-Proton Collisions at s=13 TeV with the ATLAS Detector

(2026)

A combination of measurements of the properties of Higgs boson interactions with electroweak gauge bosons is presented, using of proton-proton collisions at recorded by the ATLAS detector. Results from vector boson fusion , inclusive , and channels are combined. No evidence of violation is observed, and constrains on the -violating operators in the Standard Model effective field theory framework (SMEFT) are set in the Warsaw basis. The results from the combination improve by over 40% on previous individual limits on and, for the first time, simultaneous constraints on three coefficients , , and are set. These limits are the most stringent constraints to date on the relevant Wilson coefficients in the SMEFT framework with minimum model dependence.

Search for long-lived particles using displaced vertices of oppositely charged leptons in 140 fb − 1 of pp collisions at s = 13 TeV with the ATLAS detector

(2026)

A search is presented for long-lived particles decaying into an oppositely charged lepton pair, μ + μ − , e + e − , or e  ±  μ ∓, that form a vertex within the inner tracking system of the ATLAS detector at the Large Hadron Collider, displaced from the primary proton–proton interaction region. The analysis uses the 140 fb − 1 of Run-2 data collected at s = 13 TeV by the ATLAS experiment in 2015–2018. The results of the analysis are interpreted in the context of three benchmark models covering masses from 0.1 to 2.2 TeV and a range of mean proper lifetimes times the speed of light from 1 to 10 000 mm. The first model is a generic Z′ boson pair-produced by a new heavy scalar, with the Z′ decaying into lepton pairs. The remaining two models are R-parity violating supersymmetric models in which the lightest neutralino χ ˜ 1 0 decays into ℓ + ℓ ′ − ν ( ℓ , ℓ ′ = e , μ). The models differ by the mode of production of the χ ˜ 1 0 , which can be produced via the decay of pairs of gluinos or of pairs of charginos and neutralinos ( χ ˜ 1 ± χ ˜ 1 0 , χ ˜ 1 ± χ ˜ 2 0 , or χ ˜ 2 0 χ ˜ 1 0 ). Although each benchmark sample includes pair-produced LLPs, only a single vertex is required to be reconstructed. No dilepton displaced vertex candidate is observed and the results are presented as upper limits on the production cross-sections. This analysis sets leading limits on the production cross-sections for multiple models, including parameter space that has never been directly probed.

Search for massive, long-lived particles in events with displaced vertices and displaced muons in pp collisions at s = 13.6 TeV with the ATLAS experiment

(2026)

A search is presented for massive long-lived particles in events featuring at least one displaced vertex and at least one displaced muon, using proton–proton collision data collected by the ATLAS detector at the Large Hadron Collider from 2022 to 2024 at a centre-of-mass energy of 13.6 TeV. The data sample corresponds to an integrated luminosity of 164 fb − 1 . The analysis targets scenarios in which long-lived particles decay inside the ATLAS inner detector, resulting in a topology of at least one massive, displaced vertex (DV) with multiple associated tracks, and at least one muon with a large transverse impact parameter relative to the primary interaction point. The muon is not required to be associated with the DV. Two signal regions are defined by the transverse distance of the reconstructed DV from the interaction point. Background contributions are estimated by using fully data-driven techniques. No significant excess above the expected background is observed. Upper limits at 95% confidence level are set on the visible cross-section and on the production cross-sections of several benchmark models of R-parity-violating supersymmetry.

Search for electroweak tt¯Wj production in multileptonic final states at s=13 TeV with the ATLAS detector and bounds on effective field theory operators

(2026)

A search is presented for the electroweak production of a top-quark pair in association with a boson and at least one additional jet known as the process. This process has embedded within it a -scattering vertex, which is probed directly for the first time. The collision data were collected with the ATLAS detector during Run 2 of the LHC and correspond to an integrated luminosity of at . The search uses same-charge pairs of electrons and muons together with jets, of which at least one is -tagged. The properties of the most forward jet relative to the rest of the event are used to discriminate the electroweak production process from its strong production counterpart. A measured (expected) 95% CL upper limit on the cross section is set at (230 fb), to be compared with the expected Standard Model (SM) cross section of 47.7 fb. Limits are set on the SM effective field theory (EFT) operators and , which modify the electroweak couplings of the top quark through contributions to the -scattering vertex. The interpretation acts as a case study to emphasize the importance of energy-dependent sensitivity, multiprocess, and multioperator EFT contributions.

Predicting galaxy bias using machine learning

(2026)

Context. Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore a key ingredient in observational cosmology. This connection, commonly described through the galaxy bias, b , can be studied effectively using machine-learning (ML) techniques, which offer strong predictive capabilities and can capture nonlinear relationships in high-dimensional data. Recent work has also highlighted the need for probabilistic methods to properly account for the intrinsic stochasticity of this connection. Aims. We aim to incorporate the linear bias parameter assigned to individual galaxies into a ML framework, quantify its dependence on various halo and environmental properties, and evaluate whether different algorithms can accurately predict this parameter and reproduce the scatter in several bias relations. Methods. We use data from the IllustrisTNG300 magnetohydrodynamical simulation, including the distance to different cosmic web structures computed with DisPerSE. These data are complemented with an object-by-object estimator of the large-scale linear bias ( b i ), providing the individual contribution of each galaxy to the bias of the entire population. Our ML framework uses three models to predict b i : a random forest regressor, a single-output neural network and a probabilistic method (normalizing flows). Results. We recover the full hierarchy of galaxy bias dependencies, showing that the most informative features are the overdensities, particularly δ 8 , followed by the distances to cosmic-web structures and selected internal halo properties, most notably the formation redshift ( z 1/2 ). We also demonstrate that normalizing flows clearly outperform deterministic methods in predicting galaxy bias, including its joint distributions with galaxy properties, owing to their ability to capture the intrinsic variance associated with the stochastic nature of the matter-halo-galaxy connection. Our ML framework provides a foundation for future efforts to measure the individual bias with upcoming spectroscopic surveys.

Machine Learning-based Unfolding for Cross Section Measurements in the Presence of Nuisance Parameters

(2026)

Statistically correcting measured cross sections for detector effects is an important step across many applications. In particle physics, this inverse problem is known as unfolding. In cases with complex instruments, the distortions they introduce are often known only implicitly through simulations of the detector. Modern machine learning has enabled efficient simulation-based approaches for unfolding high-dimensional data. Among these, one of the first methods successfully deployed on experimental data is the OmniFold algorithm, a classifier-based Expectation-Maximization procedure. In practice, however, the forward model is only approximately specified, and the corresponding uncertainty is encoded through nuisance parameters. Building on the well-studied OmniFold algorithm, we show how to extend machine learning-based unfolding to incorporate nuisance parameters. Our new algorithm, called Profile OmniFold, is demonstrated using a Gaussian example as well as a particle physics case study using simulated data from the CMS Experiment at the Large Hadron Collider.

The DESI DR1 Peculiar Velocity Survey: Global Zero-point and H0 Constraints

(2026)

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, H0. This sample has a lower statistical uncertainty than any previously used to measure H0, 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 H0 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 H0 = 73.7 ± 0.06 (stat.) ± 1.1 (syst.) km s−1 Mpc−1. Calibrating to surface brightness fluctuation distances yields a similar H0. 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 H0. This will provide an alternative to supernovae as the Hubble flow sample for H0 measurements.

Physical Sciences

Physics