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Abstract The ICARUS-T600 Liquid Argon Time Projection Chamber is operating at Fermilab at shallow depth and thus exposed to a high flux of cosmic rays that can fake neutrino interactions. A cosmic ray tagging (CRT) system (∼ 1100 m²), surrounding the cryostat with two layers of fiber embedded plastic scintillators, was developed to mitigate the cosmic ray induced background. Using nanosecond-level timing information, the CRT can distinguish incoming cosmic rays from outgoing particles from neutrino interactions in the TPC. In this paper an overview of the CRT system, its installation and commissioning at Fermilab, and its performance are discussed. 

ABSTRACT In cosmology, we routinely choose between models to describe our data, and can incur biases due to insufficient models or lose constraining power with overly complex models. In this paper, we propose an empirical approach to model selection that explicitly balances parameter bias against model complexity. Our method uses synthetic data to calibrate the relation between bias and the χ2 difference between models. This allows us to interpret χ2 values obtained from real data (even if catalogues are blinded) and choose a model accordingly. We apply our method to the problem of intrinsic alignments – one of the most significant weak lensing systematics, and a major contributor to the error budget in modern lensing surveys. Specifically, we consider the example of the Dark Energy Survey Year 3 (DES Y3), and compare the commonly used non-linear alignment (NLA) and tidal alignment and tidal torque (TATT) models. The models are calibrated against bias in the Ωm–S8 plane. Once noise is accounted for, we find that it is possible to set a threshold Δχ2 that guarantees an analysis using NLA is unbiased at some specified level Nσ and confidence level. By contrast, we find that theoretically defined thresholds (based on, e.g. p-values for χ2) tend to be overly optimistic, and do not reliably rule out cosmological biases up to ∼1–2σ. Considering the real DES Y3 cosmic shear results, based on the reported difference in χ2 from NLA and TATT analyses, we find a roughly $$30{{\ \rm per\ cent}}$$ chance that were NLA to be the fiducial model, the results would be biased (in the Ωm–S8 plane) by more than 0.3σ. More broadly, the method we propose here is simple and general, and requires a relatively low level of resources. We foresee applications to future analyses as a model selection tool in many contexts. 

We present constraints on the $f\left(R\right)$gravity model using a sample of 1005 galaxy clusters in the redshift range 0.25–1.78 that have been selected through the thermal Sunyaev-Zel’dovich effect from South Pole Telescope data and subjected to optical and near-infrared confirmation with the multicomponent matched filter algorithm. We employ weak gravitational lensing mass calibration from the Dark Energy Survey Year 3 data for 688 clusters at $z<0.95$and from the Hubble Space Telescope for 39 clusters with $0.6<z<1.7$. Our cluster sample is a powerful probe of $f\left(R\right)$gravity, because this model predicts a scale-dependent enhancement in the growth of structure, which impacts the halo mass function (HMF) at cluster mass scales. To account for these modified gravity effects on the HMF, our analysis employs a semianalytical approach calibrated with numerical simulations. Combining calibrated cluster counts with primary cosmic microwave background temperature and polarization anisotropy measurements from the Planck 2018 release, we derive robust constraints on the $f\left(R\right)$parameter $f_{R0}$. Our results, ${\log }_{10}\left|f_{R0}\right|<-5.32$at the 95% credible level, are the tightest current constraints on $f\left(R\right)$gravity from cosmological scales. This upper limit rules out $f\left(R\right)$-like deviations from general relativity that result in more than a $\sim 20\%$enhancement of the cluster population on mass scales $M_{200\mathrm{c}}>3\times {10}^{14}{M}_{\odot }$. Published by the American Physical Society2025 

Context.The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches is machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims.The goal of this work is to calculate the photo-zsfor the Year 3 (Y3) Dark Energy Survey (DES) Deep Fields catalogue using the Directional Neighborhood Fitting (DNF) machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained by DNF on the Y3 DES Deep Fields catalogue with that of the EAzY template fitting approach. Methods.We emulated – at a brighter magnitude – the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We used a principal component analysis to graphically assess the incompleteness and relate it with the performance parameters provided by DNF. Finally, we applied the results on the incompleteness to the photo-zcomputation on the Y3 DES Deep Fields with DNF and estimated its performance. Results.The photo-zsof the galaxies in the DES deep fields were computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. We have developed some techniques to evaluate the performance in the absence of “true” redshift and to assess the completeness. We have studied the tradeoff in the training sample between the highest spectroscopic redshift quality versus completeness. We found some advantages in relaxing the highest-quality spectroscopic redshift requirements at fainter magnitudes in favour of completeness. The results achieved by DNF on the Y3 Deep Fields are competitive with the ones provided by EAzY, showing notable stability at high redshifts. It should be noted that the good results obtained by DNF in the estimation of photo-zsin deep field catalogues make DNF suitable for the future Legacy Survey of Space and Time (LSST) andEucliddata, which will have similar depths to the Y3 DES Deep Fields. 

We present a search for long-lived particles (LLPs), produced in kaon decays, that decay to two muons inside the ICARUS neutrino detector. This channel would be a signal of hidden sector models that can address outstanding issues in particle physics such as the strong CP problem and the microphysical origin of dark matter. The search is performed with data collected in the Neutrinos at the Main Injector (NuMI) beam at Fermilab corresponding to $2.41\times {10}^{20}$protons-on-target. No new physics signal is observed, and we set world leading limits on heavy QCD axions, as well as for the Higgs portal scalar among dedicated searches. Limits are also presented in a model-independent way applicable to any new physics model predicting the process $K\to \pi +S(\to \mu \mu )$, for a LLP $S$. This result is the first search for new physics performed with the ICARUS detector at Fermilab. It paves the way for the future program of LLP searches at ICARUS. Published by the American Physical Society2025 

Abstract The ICARUS liquid argon time projection chamber (LArTPC) neutrino detector has been taking physics data since 2022 as part of the Short-Baseline Neutrino (SBN) Program. This paper details the equalization of the response to charge in the ICARUS time projection chamber (TPC), as well as data-driven tuning of the simulation of ionization charge signals and electronics noise. The equalization procedure removes non-uniformities in the ICARUS TPC response to charge in space and time. This work leverages the copious number of cosmic ray muons available to ICARUS at the surface. The ionization signal shape simulation applies a novel procedure that tunes the simulation to match what is measured in data. The end result of the equalization procedure and simulation tuning allows for a comparison of charge measurements in ICARUS between Monte Carlo simulation and data, showing good performance with minimal residual bias between the two. 

Abstract This paper reports on a measurement of electron-ion recombination in liquid argon in the ICARUS liquid argon time projection chamber (LArTPC). A clear dependence of recombination on the angle of the ionizing particle track relative to the drift electric field is observed. An ellipsoid modified box (EMB) model of recombination describes the data across all measured angles. These measurements are used for the calorimetric energy scale calibration of the ICARUS TPC, which is also presented. The impact of the EMB model is studied on calorimetric particle identification, as well as muon and proton energy measurements. Accounting for the angular dependence in EMB recombination improves the accuracy and precision of these measurements. 

ABSTRACT Extracting precise cosmology from weak lensing surveys requires modelling the non-linear matter power spectrum, which is suppressed at small scales due to baryonic feedback processes. However, hydrodynamical galaxy formation simulations make widely varying predictions for the amplitude and extent of this effect. We use measurements of Dark Energy Survey Year 3 weak lensing (WL) and Atacama Cosmology Telescope DR5 kinematic Sunyaev–Zel’dovich (kSZ) to jointly constrain cosmological and astrophysical baryonic feedback parameters using a flexible analytical model, ‘baryonification’. First, using WL only, we compare the $$S_8$$ constraints using baryonification to a simulation-calibrated halo model, a simulation-based emulator model, and the approach of discarding WL measurements on small angular scales. We find that model flexibility can shift the value of $$S_8$$ and degrade the uncertainty. The kSZ provides additional constraints on the astrophysical parameters, with the joint WL + kSZ analysis constraining $$S_8=0.823^{+0.019}_{-0.020}$$. We measure the suppression of the non-linear matter power spectrum using WL + kSZ and constrain a mean feedback scenario that is more extreme than the predictions from most hydrodynamical simulations. We constrain the baryon fractions and the gas mass fractions and find them to be generally lower than inferred from X-ray observations and simulation predictions. We conclude that the WL + kSZ measurements provide a new and complementary benchmark for building a coherent picture of the impact of gas around galaxies across observations.