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At least 1,657 records · Page 92

The effects of the small-scale behaviour of dark matter power spectrum on CMB spectral distortion

After numerous astronomical and experimental searches, the precise particle nature of dark matter is still unknown. The standard Weakly Interacting Massive Particle(WIMP) dark matter, despite successfully explaining the large-scale features of the universe, has long-standing small-scale issues. The spectral distortion in the Cosmic Microwave Background(CMB) caused by Silk damping in the pre-recombination era allows one to access information on a range of small scales 0.3 Mpc < k < 10{sup 4} Mpc{sup −1}, whose dynamics can be precisely described using linear theory. In this paper, we investigate the possibility of using the Silk damping induced CMB spectral distortion as a probe of the small-scale power. We consider four suggested alternative dark matter candidates—Warm Dark Matter (WDM), Late Forming Dark Matter (LFDM), Ultra Light Axion (ULA) dark matter and Charged Decaying Dark Matter (CHDM); the matter power in all these models deviate significantly from the ΛCDM model at small scales. We compute the spectral distortion of CMB for these alternative models and compare our results with the ΛCDM model. We show that the main impact of alternative models is to alter the sub-horizon evolution of the Newtonian potential which affects the late-time behaviour of spectral distortion of CMB. The y -parameter diminishes by a few percent as compared to the ΛCDM model for a range of parameters of these models: LFDM for formation redshift z {sub f} = 10{sup 5} (7%); WDM for mass m {sub wdm} = 1 keV (2%); CHDM for decay redshift z {sub decay} = 10{sup 5} (5%); ULA for mass m {sub a} = 10{sup −24} eV (3%). This effect from the pre-recombination era can be masked by orders of magnitude higher y -distortions generated by late-time sources, e.g. the Epoch of Reionization and tSZ from the cluster of galaxies. We also briefly discuss the detectability of this deviation in light of the upcoming CMB experiment PIXIE, which might have the sensitivity to detect this signal from the pre-recombination phase.

79 ASTRONOMY AND ASTROPHYSICS↗

Primordial non-Gaussianity with μ-type and y -type spectral distortions: exploiting Cosmic Microwave Background polarization and dealing with secondary sources

Cross-correlations between Cosmic Microwave Background (CMB) temperature and y -spectral distortion anisotropies have been previously proposed as a way to measure the local bispectrum parameter f {sub NL}{sup loc}. in a range of scales inaccessible to either CMB ( T , E ) bispectra or μ T correlations. This is useful e.g. to test scale dependence of primordial non-Gaussianity. Unfortunately, the primordial y T signal is strongly contaminated by the late-time correlation between the Integrated Sachs Wolfe and Sunyaev-Zel'dovich (SZ) effects. Moreover, SZ itself generates a large noise contribution in the y -parameter map. We consider two original ways to address these issues. In order to remove the bias due to the SZ-CMB temperature coupling, while also providing additional signal, we include in the analysis the cross-correlation between y -distortions and CMB polarization . In order to reduce the noise, we propose to clean the y -map by subtracting a SZ template, reconstructed via cross-correlation with external tracers (CMB and galaxy-lensing signals). We combine this SZ template subtraction with the previously suggested solution of directly masking detected clusters. Our final forecasts show that, using y -distortions, a PRISM-like survey can achieve 1σ( f {sub NL}{sup loc}.) = 300, while an ideal experiment will achieve 1σ( f {sub NL}{sup loc}.) = 130 with improvements of a factor between 2.1 and 3.8, depending on the considered survey, from adding the y E signal, and a further 20–30 % from template cleaning. These forecasts are much worse than current f {sub NL}{sup loc}. boundaries from Planck , but we stress that they refer to completely different scales.

79 ASTRONOMY AND ASTROPHYSICS↗

Efficient optimal reconstruction of linear fields and band-powers from cosmological data

We present an efficient implementation of Wiener filtering of real-space linear field and optimal quadratic estimator of its power spectrum Band-powers. We first recast the field reconstruction into an optimization problem, which we solve using quasi-Newton optimization. We then recast the power spectrum estimation into the field marginalization problem, from which we obtain an expression that depends on the field reconstruction solution and a determinant term. We develop a novel simulation based method for the latter. We extend the simulations formalism to provide the covariance matrix for the power spectrum. We develop a flexible framework that can be used on a variety of cosmological fields and present results for a variety of test cases, using simulated examples of projected density fields, projected shear maps from galaxy lensing, and observed Cosmic Microwave Background (CMB) temperature anisotropies, with a wide range of map incompleteness and variable noise. For smaller cases where direct numerical inversion is possible, we show that our solution matches that created by direct Wiener Filtering at a fraction of the overall computation cost. Even more significant reduction of computational is achieved by this implementation of optimal quadratic estimator due to the fast evaluation of the Hessian matrix. This technique allows for accurate map and power spectrum reconstruction with complex masks and nontrivial noise properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Got plenty of nothing: cosmic voids as a probe of particle dark matter

The search for a particle dark matter signal in terms of radiation produced by dark matter annihilation or decay has to cope with the extreme faintness of the predicted signal and the presence of masking astrophysical backgrounds. It has been shown that using the correlated information between the dark matter distribution in the Universe with the fluctuations of the cosmic radiation fields has the potential to allow setting apart a pure dark matter signal from astrophysical emissions, since spatial fluctuations in the radiation field due to astrophysical sources and dark matter emission have different features. The cross-correlation technique has been proposed and adopted for dark matter studies by looking at dark matter halos (overdensities). Here in this paper we extend the technique by focusing on the information on dark matter distribution offered by cosmic voids, and by looking specifically at the gamma-ray dark matter emission: we show that, while being underdense and therefore producing a reduced emission as compared to halos, nevertheless in voids the relative size of the cross-correlation signal due to decaying dark matter vs. astrophysical sources is significantly more favourable, producing signal-to-background ratios S/B (even significantly) larger than 1 for decay lifetimes up to 2 × 10 30 s. This is at variance with the case of halos, where S/B is typically (even much) smaller than 1. We show that forthcoming galaxy surveys such as Euclid combined with future generation gamma-ray detectors with improved specifications have the ability to provide a hint of such a signal with a predicted significance up to 5.7σ for galaxies and 1.6σ for the cosmic shear. The bound on the dark matter lifetime attainable exploiting voids is predicted to improve on current bounds in a mass range for the WIMP of 25 ÷ 900 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Weak lensing trispectrum and Kurt-spectra

We introduce two kurt-spectra to probe fourth-order statistics of weak lensing convergence maps. Using state-of-the-art numerical simulations, we study the shapes of these kurt-spectra as a function of source redshifts and smoothing angular scales. We employ a pseudo-Cℓ approach to estimate the spectra from realistic convergence maps in the presence of an observational mask and noise for stage-IV large-scale structure surveys. We compare these results against theoretical predictions calculated using the FFTLog formalism, and find that a simple nonlinear clustering model — the hierarchical ansatz — can reproduce the numerical trends for the kurt-spectra in the nonlinear regime. In addition, we provide estimators for beyond fourth-order spectra where no definitive analytical results are available, and present corresponding results from numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Harmonic analysis of discrete tracers of large-scale structure

It is commonplace in cosmology to analyze fields projected onto the celestial sphere, and in particular density fields that are defined by a set of points e.g. galaxies. When performing an harmonic-space analysis of such data (e.g. an angular power spectrum) using a pixelized map one has to deal with aliasing of small-scale power and pixel window functions. We compare and contrast the approaches to this problem taken in the cosmic microwave background and large-scale structure communities, and advocate for a direct approach that avoids pixelization. We describe a method for performing a pseudo-spectrum analysis of a galaxy data set and show that it can be implemented efficiently using well-known algorithms for special functions that are suited to acceleration by graphics processing units (GPUs). The method returns the same spectra as the more traditional map-based approach if in the latter the number of pixels is taken to be sufficiently large and the mask is well sampled. The method is readily generalizable to cross-spectra and higher-order functions. It also provides a convenient route for distributing the information in a galaxy catalog directly in harmonic space, as a complement to releasing the configuration-space positions and weights, and a route to spectral apodization. Finally, we make public a code enabling the application of our method to existing and upcoming datasets.

79 ASTRONOMY AND ASTROPHYSICS↗

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗

DESI DR1 Ly α 1D power spectrum: Validation of estimators

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Lyα forest cosmology, accessed through its one-dimensional power spectrum (P 1D ). The Lyα forest P 1D is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure P 1D : the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest k values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 P 1D on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

Lyman alpha forest↗

Reviving sub-keV warm dark matter: a UVLF-based analysis

Thermal warm dark matter (WDM) particles with m WDM ≤ 1 keV are ruled out at more than 4σ by multiple observational probes, owing to the strong suppression of small-scale structure induced by early-time free-streaming. Recently, it was highlighted that a small admixture of ∼ 1% (f CDM ∼ 0.01) cold dark matter (CDM) endowed with a blue-tilted isocurvature spectrum could offset the WDM-induced suppression and relax the WDM mass bound by a factor of 𝒪(10). If viable, this “warm + cold-isocurvature” scenario would allow sub-keV WDM particles to constitute nearly the full dark matter abundance while potentially alleviating some small-scale tensions. In this work, we test this mechanism by constraining the WDM mass mWDM while marginalizing over CDM isocurvature parameters. We combine ultraviolet luminosity function measurements from the Hubble Space Telescope and James Webb Space Telescope over redshift 4 ≤ z ≤ 11 with CMB, BAO, and SNe data. For a pure WDM model, our joint analysis yields a lower bound m WDM > 1.8 keV (95% credible intervals). When CDM isocurvature is introduced at f CDM = 0.01, the limit relaxes to m WDM > 0.27 keV (95% credible intervals), reflecting a shallow degeneracy in which blue-tilted isocurvature fluctuations partially compensate for WDM suppression. These results provide new constraints on thermal WDM in the presence of CDM isocurvature fluctuations and quantify the extent to which such fluctuations can mask the small-scale signatures of light relics.

cosmological parameters from CMBR↗

Reconstructing Quasar Spectra and Measuring the Lyα Forest with SpenderQ

Quasar spectra carry the imprint of foreground intergalactic medium (IGM) through absorption features. In particular, absorption caused by neutral hydrogen gas, the "Lyα forest," is a key spectroscopic tracer for cosmological analyses used to measure cosmic expansion and test physics beyond the standard model. Despite their importance, current methods for measuring Lyα absorption cannot directly derive the intrinsic quasar continuum and make strong assumptions on its shape, thus distorting the measured Lyα clustering. We present SpenderQ , a ML-based approach for directly reconstructing the intrinsic quasar spectra and measuring the Lyα forest from observations. SpenderQ uses the Spender spectrum autoencoder to learn a compact and redshift-invariant latent encoding of quasar spectra, combined with an iterative procedure to identify and mask absorption regions. To demonstrate its performance, we apply SpenderQ to 400,000 synthetic quasar spectra created to validate the Dark Energy Spectroscopic Instrument Year 1 Lyα cosmological analyses. SpenderQ accurately reconstructs the true intrinsic quasar spectra, including the broad Lyβ, Lyα, SiIV, CIV, and CIII emission lines. Redward of Lyα, SpenderQ provides percent-level reconstructions of the true quasar spectra. Blueward of Lyα, SpenderQ reconstructs the true spectra to < 5%. SpenderQ reproduces the shapes of individual quasar spectra more robustly than the current state-of-the-art. We, thus, expect it will significantly reduce biases in Lyα clustering measurements and enable studies of quasars and their physical properties. SpenderQ also provides informative latent variable encodings that can be used to, e.g., classify quasars with Broad Absorption Lines. Overall, SpenderQ provides a new data-driven approach for unbiased Lyα forest measurements in cosmological, quasar, and IGM studies.

Hahn, ChangHoon [Arizona U., Astron. Dept. - Stewa↗

Photometry, Centroid and Point-spread Function Measurements in the LSST Camera Focal Plane Using Artificial Stars

Abstract The Vera C. Rubin Observatory’s LSST Camera (LSSTCam) pixel response has been characterized using laboratory measurements with a grid of artificial stars. We quantify the contributions to photometry, centroid, point-spread function size, and shape measurement errors due to small anomalies in the LSSTCam CCDs. The main sources of those anomalies are quantum efficiency variations and pixel area variations induced by the amplifier segmentation boundaries and “tree-rings”—circular variations in silicon doping concentration. This laboratory study using artificial stars projected on the sensors shows overall small effects. The residual effects on point-spread function (PSF) size and shape are below 0.1%, meeting the ten-year LSST survey science requirements. However, the CCD mid-line presents distortions that can have a moderate impact on PSF measurements. This feature can be avoided by masking the affected regions. Effects of tree-rings are observed on centroids and PSFs of the artificial stars and the nature of the effect is confirmed by a study of the flat-field response. Nevertheless, further studies of the full-focal plane with stellar data should more completely probe variations and might reveal new features, e.g., wavelength-dependent effects. The results of this study can be used as a guide for the on-sky operation of LSSTCam.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterization of the Cherenkov Photon Background for Low-noise Silicon Detectors in Space

Future space observatories that seek to perform imaging and spectroscopy of faint astronomical sources will require ultra-low-noise detectors that are sensitive over a broad wavelength range. Silicon charge-coupled devices (CCDs), such as EMCCDs, skipper CCDs, multi-amplifier sensing CCDs, and single-electron sensitive read out CCDs have demonstrated the ability to detect and measure single photons from X-ray energies to near the silicon band gap (∼1.1 μm), making them candidate technologies for this application. Here, in this context, we study a relatively unexplored source of low-energy background coming from Cherenkov radiation produced by energetic cosmic rays traversing a silicon detector. We present a model for Cherenkov photon production and absorption that is calibrated to laboratory data, and we use this model to characterize the residual background rate for ultra-low-noise silicon detectors in space. We study how the Cherenkov background rate depends on detector thickness, variations in solar activity, and the contribution of heavy cosmic ray species (Z > 2). We find that for thick silicon detectors, such as those required to achieve high quantum efficiency at long wavelengths, the rate of cosmic-ray-induced Cherenkov photon production is comparable to other detector and astrophysical backgrounds. We apply our Cherenkov background model to simulated spectroscopic observations of extra-solar planets, and we find that thick detectors continue to outperform their thinner counterparts at longer wavelengths despite a larger Cherenkov background rate. Furthermore, we find that minimal masking of cosmic-ray tracks continues to maximize the signal-to-noise ratio of very faint sources despite the existence of extended halos of Cherenkov photons.

Astronomical detectors↗

Heavy flavor dynamics across system size at the LHC

One of the fundamental signatures of the Quark Gluon Plasma has been the suppression of heavy flavor (specifically D mesons), which has been measured via the nuclear modification factor, R AA and azimuthal anisotropies, v n , in large systems. However, multiple competing models can reproduce the same data for R AA to v n . In this talk we break down the competing effects that conspire together to successfully reproduce R AA and v n in experimental data using Trento+v-USPhydro+DAB-MOD. Then using our best fit model we make predictions for R AA and v n across system size for 208 PbPb, 129 XeXe, 40 ArAr, and 16 OO collisions. We find that 0–10% centrality has a non-trivial interplay between the system size and eccentricities such that system size effects are masked in v 2 whereas in 30–50% centrality the eccentricities are approximately constant across system size and, therefore, is a better centrality class to study D meson dynamics across system size.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Higgs Factory muon collider superconducting magnets and their protection against beam decay radiation

We report a low-energy medium-luminosity Muon Collider (MC) is being studied as a possible Higgs Factory (HF). Electrons from muon decays will deposit more than 300 kW in superconducting (SC) magnets of the HF collider ring. This imposes significant challenges to SC magnets used in the HF storage ring (SR) and interaction regions (IR). Conceptual designs of SC dipole and quadrupole magnets are described which provide high operating gradient and field in a large aperture to accommodate the large size of muon beams (due to low β*), as well as a cooling system to intercept the large heat deposition from the showers induced by decay electrons. The distribution of heat deposition in the main elements of HF SR lattice requires large-aperture magnets to accommodate thick high-Z absorbers to protect the SC coils. Based on the developed MARS15 model and intensive simulations, a sophisticated protection system from radiation was designed for the collider SR and IR to bring the peak power density in the SC coils well below the quench limit and reduce the dynamic heat deposition in the cold mass of SC magnets by a factor of 100. The radiation protection system consists of tight tungsten masks in the magnet interconnect regions and elliptical tungsten liners in the magnet aperture optimized for each magnet. Lastly, these elements reduce also the background particle fluxes in the collider detector.

43 PARTICLE ACCELERATORS↗

Single photoelectron identification with Incom LAPPD 38

Incom Inc. Large Area Picosecond Photodetector (LAPPD) 38 has been tested at Jefferson Lab to identify single-photoelectron signals to assess the potential of this type of device for future applications in Cherenkov light detection. Here, single-photoelectron signals were clearly detected if a tight masking of photons impinging on the photocathode was used compared to the pixelation of the charge collection signal board.

47 OTHER INSTRUMENTATION↗

Comparison of measurement and simulation of ATLAS cavern radiation background

Sixteen Medipix2 pixel detector based (MPX) devices were operated at various positions within the ATLAS detector and cavern continuously from early 2008 up to 2013. In addition to photons, each MPX detector is capable to detect charged particles, and neutrons as it is covered with a mask of converter materials dividing its area into regions sensitive to thermal or fast neutrons. The MPX detector network was effectively used for real-time measurements of the spectral characteristics and composition of complex radiation fields in ATLAS. This article reports comparison of the results of measurements performed with MPX detectors during the LHC operation period in 2010 and 2011 with Monte Carlo simulations results from the FLUGG and GCALOR codes. For the purpose of this comparison, the MPX detectors were operated in tracking mode with low threshold (8–10 keV) allowing one to distinguish among particle categories based on the recognition of track patterns left by the particles in the MPX sensitive layer. The comparison of measurements with simulations shows that the agreement between measured and simulated data is satisfactory in most cases within a factor of two.

47 OTHER INSTRUMENTATION↗

Generative machine learning for detector response modeling with a conditional normalizing flow

In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. Here, we present a conditional normalizing flow model ($\mathcal{CNF}$) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the $\mathcal{CNF}$ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Convolutional L2LFlows: generating accurate showers in highly granular calorimeters using convolutional normalizing flows

Abstract In the quest to build generative surrogate models as computationally efficient alternatives to rule-based simulations, the quality of the generated samples remains a crucial frontier. So far, normalizing flows have been among the models with the best fidelity. However, as the latent space in such models is required to have the same dimensionality as the data space, scaling up normalizing flows to high dimensional datasets is not straightforward. The prior L2LFlows approach successfully used a series of separate normalizing flows and sequence of conditioning steps to circumvent this problem. In this work, we extend L2LFlows to simulate showers with a 9-times larger profile in the lateral direction. To achieve this, we introduce convolutional layers and U-Net-type connections, move from masked autoregressive flows to coupling layers, and demonstrate the successful modelling of showers in the ILD Electromagnetic Calorimeter as well as Dataset 3 from the public CaloChallenge dataset.

Instruments & Instrumentation↗