Investigating non-Gaussianity in Cosmic Microwave Background temperature maps using spherical harmonic phases

In the era of precision cosmology, accurate estimation of cosmological parameters is based upon the implicit assumption of the Gaussian nature of Cosmic Microwave Background (CMB) radiation. Therefore, an important scientific question to ask is whether the observed CMB map is consistent with Gaussian prediction. In this work, we extend previous studies based on CMB spherical harmonic phases (SHP) to examine the validity of the hypothesis that the temperature field of the CMB is consistent with a Gaussian random field (GRF). The null hypothesis is that the corresponding CMB SHP are independent and identically distributed in terms of a uniform distribution in the interval [0, 2π] [1,2]. We devise a new model-independent method where we use ordered and non-parametric Rao's statistic, based on sample arc-lengths to comprehensively test uniformity and independence of SHP for a given ℓ mode and independence of nearby ℓ mode SHP. We performed our analysis on the scales limited by spherical harmonic modes ≤ 128, to restrict ourselves to signal-dominated regions. To find the non-uniform or dependent sets of SHP, we calculate the statistic for the data and 10000 Monte Carlo simulated uniformly random sets of SHP and use 0.05 and 0.001 α levels to distinguish between statistically significant and highly significant detections. We first establish the performance of our method using simulated Gaussian, non-Gaussian CMB temperature maps, along with observed non-Gaussian 100 and 143 GHz Planck channel maps. We find that our method, performs efficiently and accurately in detecting phase correlations generated in all of the non-Gaussian simulations and observed foreground contaminated 100 and 143 GHz Planck channel temperature maps. We apply our method on Planck satellite mission's final released CMB temperature anisotropy maps- COMMANDER, SMICA, NILC, and SEVEM along with WMAP 9 year released ILC map. We report that SHP corresponding to some of the m-modes are non-uniform, some of the ℓ mode SHP and neighboring mode pair SHP are correlated in cleaned CMB maps. The detection of non-uniformity or correlation in the SHP indicates the presence of non-Gaussian signals in the foreground minimized CMB maps.

High-resolution air temperature mapping in a data-scarce, arid area by means of low-cost mobile measurements and machine learning

The availability of gridded, screen-level air temperature data at an effective spatial and temporal resolution is important for many fields such as climatology, ecology, urban planning and design. This study aims at providing such data in a data-scarce, arid city within the greater Cairo region (Egypt), namely the Sixth of October, where, to our knowledge, no such data are available. By using (i) air temperature data, collected from mobile measurements, (ii) multiple spectral indices, (iii) spatial analysis techniques and (iv) random forest regression modelling, we produced air temperature maps (for both daytime and nighttime) at 30-m spatial resolution for the entire city. The proposed method is systematic and relies on low-cost instrumentation and freely-available satellite data and hence it can be replicated in similar data-scarce, arid areas to allow for better spatial and temporal monitoring of air temperature.

Development Of A Nonlinear Frequency Compounding Method With Applications In Ultrasound Imaging And Thermometry

<div>Frequency compounding is an ultrasound imaging technique used to reduce artifacts and improve signal-to-noise-ratio (SNR). In this work a new nonlinear frequency compounding (NLFC) method was introduced, and its application in B-mode imaging and noninvasive thermometry was investigated. NLFC input frequencies were optimized to maximize speckle-signal-to-noise-ratio (SSNR) in a tissue mimicking phantom, and the method was then used to produce maps of the temperature sensitive change in backscattered energy of acoustic harmonics (<i>h</i>CBE) during heating of ex vivo porcine tissue with a focused ultrasound transducer. A <i>h</i>CBE-to-temperature calibration was also performed and temperature maps produced. Lastly, a comparative study of the NLFC and previously used nonlinear single frequency (NLSF) method was completed. By using the NLFC method it was concluded that SSNR of B-mode and backscattered energy images, SNR of <i>h</i>CBE maps, and temperature map agreement with a theoretical COMSOL based model were improved over the previously used NLSF method.</div>

Development Of A Nonlinear Frequency Compounding Method With Applications In Ultrasound Imaging And Thermometry

<div>Frequency compounding is an ultrasound imaging technique used to reduce artifacts and improve signal-to-noise-ratio (SNR). In this work a new nonlinear frequency compounding (NLFC) method was introduced, and its application in B-mode imaging and noninvasive thermometry was investigated. NLFC input frequencies were optimized to maximize speckle-signal-to-noise-ratio (SSNR) in a tissue mimicking phantom, and the method was then used to produce maps of the temperature sensitive change in backscattered energy of acoustic harmonics (<i>h</i>CBE) during heating of ex vivo porcine tissue with a focused ultrasound transducer. A <i>h</i>CBE-to-temperature calibration was also performed and temperature maps produced. Lastly, a comparative study of the NLFC and previously used nonlinear single frequency (NLSF) method was completed. By using the NLFC method it was concluded that SSNR of B-mode and backscattered energy images, SNR of <i>h</i>CBE maps, and temperature map agreement with a theoretical COMSOL based model were improved over the previously used NLSF method.</div>

A novel tool for monitoring and assessing the outcome of thermal ablations of hepatic lesions

This paper presents a proof-of-concept intervention monitoring and outcome assessment tool for thermal ablative strategies like microwave ablation of hepatic tumours. For this purpose, simulated 3D+t temperature maps of the ablation progress are combined with liver MR imaging, as well as corresponding segmentations of the lesion and other relevant anatomical structures. The proposed tool mainly consists of a monitoring and validation part, each comprising 2D and 3D visualisations and various modifiable settings. With the aid of the monitoring features, the heat propagation during the ablation progress could be visually tracked, while the validation part of the tool provides the radiologist with comprehensible and detailed feedback to assess the treatment result. Hence, it could enable an immediate validation of the ablation progress and support interventional decision-making. For evaluation purposes, we used an exemplary patient case to demonstrate the benefits of the proposed prototype. This tool could represent a crucial step towards a suitable computerassisted and more accurate workflow of thermal ablations, with benefits for both, patients and radiologists.

Geometric correction for thermographic images of asteroid 162173 Ryugu by TIR (thermal infrared imager) onboard Hayabusa2

The thermal infrared imager (TIR) onboard the Hayabusa2 spacecraft performed thermographic observations of the asteroid 162173 Ryugu (1999 JU$$_3$$ 3 ) from June 2018 to November 2019. Our previous reports revealed that the surface of Ryugu was globally filled with porous materials and had high surface roughness. These results were derived from making the observed temperature maps of TIR using a projection method onto the shape model of Ryugu as geometric corrections. The pointing directions of TIR were calculated using an interpolation of data from the SPICE kernels (NASA/NAIF) during the periods when the optical navigation camera (ONC) and the light detection and ranging (LIDAR) observations were performed. However, the mapping accuracy of the observed TIR images was degraded when the ONC and LIDAR were not performed with TIR. Also, the orbital and attitudinal fluctuations of Hayabusa2 increased the error of the temperature maps. In this paper, to solve the temperature image mapping problems, we improved the correction method by fitting all of the observed TIR images with the surface coordinate addressed on the high-definition shape model of Ryugu (SFM 800k v20180804). This correction adjusted the pointing direction of TIR by rotating the TIR frame relative to the Hayabusa2 frame using a least squares fit. As a result, the temperature maps spatially spreading areas were converged within high-resolved $$0.5^\circ$$ 0 . 5 ∘ by $$0.5^\circ$$ 0 . 5 ∘ maps. The estimated thermal inertia, for instance, was approximately 300$$\sim$$ ∼ 350 Jm$$^{-2}$$ - 2 s$$^{-0.5}$$ - 0.5 K$$^{-1}$$ - 1 at the hot area of the Ejima Saxum. This estimation was succeeded in case that the surface topographic features were larger than the pixel scale of TIR. However, the thermal inertia estimation of smooth terrains, such as the Urashima crater, was difficult because of surface roughness effects, where roughness was probably much smaller than the pixel scale of TIR.

BUILDING OF TEMPERATURE MAPS OF NOVOSIBIRSK CITY BASED ON LANDSAT 8 DATA

An algorithm for constructing temperature maps of the underlying surface based on a multi-time series of atmospheric corrected satellite data from Landsat 8, implemented in the Google Earth Engine system, is presented. The results of the construction of temperature maps of Novosibirsk using this algorithm are discussed.

Homogeneous vs Biased IGM: Impact on Reionization

This paper considers the impact of large scale biasing of the IGM on reionization. The two simplest but extreme scenarios for IGM biasing are: an unbiased IGM which has a constant density and an IGM with density equal to the collapsed matter density. In this work, the relationship between the IGM density and the collapsed matter density is defined through an IGM bias parameter. The two extreme scenarios of homogeneous and perfectly biased IGM are produced for two extreme values of this bias parameter. It is found that, for the same level of reionization (i.e., for same global neutral hydrogen fraction). one could get very different 21 cm brightness temperature distributions for different values of this bias parameter. These distributions could give an order of magnitude more or less power as compared to the uniform case. It is also found that there exists a critical value for the IGM bias parameter for which there could be a near washout of the structure in the 21 cm brightness temperature distribution (i.e., zero power or a nearly uniform 21 cm brightness temperature distribution). To address the problem, a new method of generating 21 cm brightness temperature maps is used. The method uses the results of n-body simulations and then employs ray tracing to obtain the 21 cm brightness temperature maps. Towards the end, a prescription for the IGM bias parameter is given. This is derived within the framework of the Press-Schechter theory.