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A new micro-particle induced X-ray emission-computed tomography (PIXE-CT) system was developed at Takasaki Ion Accelerators for Advanced Radiation Application in Japan Atomic Energy Agency. In this system, scanning transmission ion microscopy-CT was performed as well as PIXE-CT for three-dimensional (3D) measurement of major elements' distributions, which are required for corrections of X-ray yields due to energy losses of projectiles and absorption of X-rays. Moreover, maximum likelihood expectation maximization algorithm has been introduced to image reconstruction because higher spatial resolution can be obtained even with less X-ray yields. Consequently, 3D distribution of trace elements in a minute biological cell less than 100 μm has been successfully obtained.

The construction of a new Nuclear Microprobe at the Livermore multi-user 10 MV FN tandem Laboratory has recently been completed. The facility is primarily used for PIXE, PIGE and Proton energy loss tomography (PELT) in a broad range of multi-disciplinary sciences. Details of the new facility and current applications/programs are discussed.

Recent advances in the technique of terahertz time-domain spectroscopy have led to the development of the first fiber-coupled room-temperature broadband terahertz sources and detectors. The fiber coupling permits the repositioning of the emitter and receiver antennas without loss of temporal calibration or alignment, thus enabling multistatic imaging. We describe a new imaging method which exploits this new capability. This technique emulates the data collection and image processing procedures developed for geophysical prospecting. We use a migration procedure to solve the inverse problem; this permits us to reconstruct the location, shape, and refractive index of targets. We show examples for both metallic and dielectric model targets, and we perform velocity analysis on dielectric targets to estimate the refractive indices of imaged components. These results broaden the capabilities of terahertz imaging systems, and also demonstrate the viability of the THz system as a test bed for the exploration of new seismic processing methods.

Micromegas-based detectors are used in a wide variety of neutron experiments. Their fast response meets the needs of time-of-flight facilities in terms of time resolution. The possibility of constructing low mass Micromegas detectors makes them appropriate for beam imaging and monitoring without affecting the beam quality or inducing background in parallel measurements. The good particle discrimination capability allows using Micromegas for neutron induced fission and (n, α) cross-section measurements. Their high radiation resistance make them suitable for working as flux monitors in the core of fission nuclear reactors as well as in the proximity of fusion chambers. New studies underlined the possibility of performing neutron computed tomography (CT) with Micromegas as neutron detectors, but also of exploiting its performances in experiments of fundamental nuclear physics.

We propose searching for deep underground cavities of different densities in the Earth’s crust using a long-baseline ${\bar{\nu }}_e$ disappearance experiment, realized through a low-energy $\beta$-beam with highly-enhanced luminosity. We focus on four cases: cavities with densities close to that of water, iron-banded formations, heavier mineral deposits, and regions of abnormal charge accumulation that have been posited to appear prior to the occurrence of an intense earthquake. The sensitivity to identify cavities attains confidence levels (C.L.s) higher than $3\sigma$ and $5\sigma$ for exposure times of three months and 1.5 years, respectively, and cavity densities below ${\mathrm{\text{1 g cm}}}^{-3}$ or above ${\mathrm{\text{5 g cm}}}^{-3}$, with widths greater than 200 km. We reconstruct the cavity density, width, and position, assuming one of them known while keeping the other two free. We obtain large allowed regions that improve as the cavity density differs more from the Earth’s mean density. Furthermore, we demonstrate that the knowledge of the cavity density is important to obtain O(10%) error on the width. Finally, we introduce an observable to quantify the presence of a cavity by changing the orientation of the ${\bar{\nu }}_e$ beam, with which we are able to identify the presence of a cavity at the $2\sigma$ to $5\sigma$ C.L.

Based on the observation that for an entangled-particles system, the physical meaning of the Wigner distribution function should lie in that its marginal distributions would give the probability of finding the particles in an entangled way, we establish a tomography theory for the Wigner function of tripartite entangled systems. The newly constructed tripartite entangled state representation of the three-mode Wigner operator plays a central role in realizing this goal.

We review how to rely on the quantum entanglement idea of Einstein–Podolsky–Rosen and the developed Dirac's symbolic method to set up two kinds of entangled state representations for describing the motion and states of an electron in uniform magnetic field. The entangled states can be employed for conveniently expressing Landau wave function and Laughlin wave function with a fresh look. We analyze the entanglement involved in electron's coordinates (or momenta) eigenstates, and in the angular momentum-orbit radius entangled state. Various applications of these two representations, such as in developing angular momentum theory, squeezing mechanism, Wigner function and tomography theory for this system are presented. Thus the present review systematically summarizes a distinct approach for tackling this physical system.

We seek to quantify both the classification performance and estimation error robustness of the authors' tomographic classifier fusion methodology by contrasting it in field tests and model scenarios with the sum and product classifier fusion methodologies.

In particular, we seek to confirm that the tomographic methodology represents a generally optimal strategy across the entire range of problem dimensionalities, and at a sufficient margin to justify the general advocation of its use. Final results indicate, in particular, a near 25% improvement on the next nearest performing combination scheme at the extremity of the tested dimensional range.

The present work includes the analysis of the porosity at different scales using image characterization techniques. Porosities were determined and compared for reservoir rocks through the fractal dimensions obtained from two-dimensional (2D) image analysis. Studies were developed using Optical Microscopy (OM), Scanning Electron Microscopy (SEM) and X-ray Computed Tomography (XCT). In order to compare the images and analyze the similarities in the porosities, the box-counting method was used to extract the power-law distributions and to obtain the fractal dimensions. Results showed that fractal dimensions were similar for the three different techniques, which included different scale analysis, fact that demonstrates the fractal character of the porosity in the studied systems. The effectiveness of the use of 2D image analysis and the importance of the multiscale study of the porosity were also demonstrated.

The momentum and position observables in an $n$-mode boson Fock space $\mathrm{\Gamma }({ℂ}^n)$ have the whole real line $ℝ$ as their spectrum. But the total number operator $N$ has a discrete spectrum ${\mathbb{Z}}_{+}=\{0,1,2,\dots \}$. An $n$-mode Gaussian state in $\mathrm{\Gamma }({ℂ}^n)$ is completely determined by the mean values of momentum and position observables and their covariance matrix which together constitute a family of $n(2n+3)$ real parameters. Starting with $N$ and its unitary conjugates by the Weyl displacement operators and operators from a representation of the symplectic group $\mathrm{\text{Sp}}(2n)$ in $\mathrm{\Gamma }({ℂ}^n)$, we construct $n(2n+3)$ observables with spectrum ${\mathbb{Z}}_{+}$ but whose expectation values in a Gaussian state determine all its mean and covariance parameters. Thus measurements of discrete-valued observables enable the tomography of the underlying Gaussian state and it can be done by using five one-mode and four two-mode Gaussian symplectic gates in single and pair mode wires of $\mathrm{\Gamma }({ℂ}^n)=\mathrm{\Gamma }{(ℂ)}^{\otimes n}$. Thus the tomography protocol admits a simple description in a language similar to circuits in quantum computation theory. Such a Gaussian tomography applied to outputs of a Gaussian channel with coherent input states permit a tomography of the channel parameters. However, in our procedure the number of counting measurements exceeds the number of channel parameters slightly. Presently, it is not clear whether a more efficient method exists for reducing this tomographic complexity.

As a byproduct of our approach an elementary derivation of the probability generating function of $N$ in a Gaussian state is given. In many cases the distribution turns out to be infinitely divisible and its underlying Lévy measure can be obtained. However, we are unable to derive the exact distribution in all cases. Whether this property of infinite divisibility holds in general is left as an open problem.

A method for increasing the specificity of an MR image using noise correlation measurements is presented. From an MR image different regions within the body are identified based on contrast. Noise signals measured at the ports of the experimental setup are functions of the conductivity at each region and the sensitivity map of the field probes. For a simulated sensitivity map, the ratio of conductivities of two regions of a phantom containing saline and distilled water was determined from the measured noise correlation at the ports.

Selecting a suitable Multi Criteria Decision-Making (MCDM) method is a crucial step in selecting appropriate medical equipment. The aim of the research is to define the most appropriate tomography equipment through the integration of the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. A hybrid model is presented. The AHP is used to define the weights of each criterion and sub-criterion through qualitative comparisons. Then, TOPSIS is used to evaluate the purchase options. This research provides decision makers with a scientific and rigorous decision support system useful in strategic and complex decision. A numerical example is also presented.

The efficiency of quantum state tomography is discussed from the point of view of quantum parameter estimation theory, in which the trace of the weighted covariance is to be minimized. It is shown that tomography is optimal only when a special weight is adopted.

Wigner and Husimi quasi-distributions, owing to their functional regularity, give the two archetypal and equivalent representations of all observable-parameters in continuous-variable quantum information. Balanced homodyning (HOM) and heterodyning (HET) that correspond to their associated sampling procedures, on the other hand, fare very differently concerning their state or parameter reconstruction accuracies. We present a general theory of a now-known fact that HET can be tomographically more powerful than balanced homodyning to many interesting classes of single-mode quantum states, and discuss the treatment for two-mode sources.

Minimal Informationally Complete quantum measurements, or MICs, illuminate the structure of quantum theory and how it departs from the classical. Central to this capacity is their role as tomographically complete measurements with the fewest possible number of outcomes for a given finite dimension. Despite their advantages, little is known about them. We establish general properties of MICs, explore constructions of several classes of them, and make some developments to the theory of MIC Gram matrices. These Gram matrices turn out to be a rich subject of inquiry, relating linear algebra, number theory and probability. Among our results are some equivalent conditions for unbiased MICs, a characterization of rank-1 MICs through the Hadamard product, several ways in which immediate properties of MICs capture the abandonment of classical phase space intuitions, and a numerical study of MIC Gram matrix spectra. We also present, to our knowledge, the first example of an unbiased rank-1 MIC which is not group covariant. This work provides further context to the discovery that the symmetric informationally complete quantum measurements (SICs) are in many ways optimal among MICs. In a deep sense, the ideal measurements of quantum physics are not orthogonal bases.

Studies of non-invasive glucose measurement with optical coherence tomography (OCT) in tissue-simulating phantoms and biological tissues show that glucose has an effect on the OCT signal slope. Choosing an efficient fitting range to calculate the OCT signal slope is important because it helps to improve the precision of glucose measurement. In this paper, we study the problem in two ways: (1) scattering-induced change of OCT signal slope versus depth in intralipid suspensions with different concentrations based on Monte Carlo (MC) simulations and experiments and (2) efficient fitting range for glucose measurement in 3% and 10% intralipid. The results show that the OCT signal slope expresses a contrary change with scattering coefficient below a certain depth in high intralipid concentrations, so that there is an effective fitting depth. With an efficient fitting range from 100 μm to the effective fitting depth, the precision of glucose measurement can be 4.4 mM for 10% intralipid and 2.2 mM for 3% intralipid.

To provide a computational efficient forward model with moderate accuracy for rapid 3D optical tomography in small volumes, radiative transport in the delta-P1 approximation combined with the approximation of the reciprocity was examined. Perturbations of optical signals caused by absorption and fluorescence heterogeneities submerged in a resin-based liquid phantom with background parameters close to rat brain tissues were measured using a recently constructed laminar optical tomography system. These measured perturbations were used to examine the theoretically calculated fluence perturbations based on the delta-P1 approximation and the reciprocity approximation. Results show that the errors between the predicted and measured data are acceptable, especially for fluorescence perturbations.

In this paper, we consider the use of blind deconvolution for optoacoustic (photoacoustic) imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond the physical restrictions of the system. The method is demonstrated with optoacoustic measurement obtained from six-day-old mice, imaged in the near-infrared using a broadband hydrophone in a circular scanning configuration. We find that estimates of the unknown point spread function, achieved by blind deconvolution, improve the resolution and contrast in the images and show promise for enhancing optoacoustic images.

Fluorescence molecular tomography (FMT) allows the detection and quantification of various biological processes in small animals in vivo, which expands the horizons of pre-clinical research and drug development. Efficient three-dimensional (3D) reconstruction algorithm is the key to accurate localization and quantification of fluorescent target in FMT. In this paper, 3D reconstruction of FMT is regarded as a sparse signal recovery problem and the compressive sampling matching pursuit (CoSaMP) algorithm is adopted to obtain greedy recovery of fluorescent signals. Moreover, to reduce the modeling error, the simplified spherical harmonics approximation to the radiative transfer equation (RTE), more specifically $S{P}_3$, is utilized to describe light propagation in biological tissues. The performance of the proposed reconstruction method is thoroughly evaluated by simulations on a 3D digital mouse model by comparing it with three representative greedy methods including orthogonal matching pursuit (OMP), stagewise OMP(StOMP), and regularized OMP (ROMP). The CoSaMP combined with $S{P}_3$ shows an improvement in reconstruction accuracy and exhibits distinct advantages over the comparative algorithms in multiple targets resolving. Stability analysis suggests that CoSaMP is robust to noise and performs stably with reduction of measurements. The feasibility and reconstruction accuracy of the proposed method are further validated by phantom experimental data.

We present for the first time in vivo imaging of rat brain using microwave-induced thermoacoustic tomography (TAT). The in vivo imaging of rat brain was realized through an unconventional delivery of microwave energy from the front of rat brain (while the transducer was scanned along coronal plane of the animal brain), which maximized the microwave penetration into the brain. In addition, we found that the imaging contrast was highly dependent on the direction of the electric field polarization (EFP) and that more tissue structures/compositions could be revealed when both $X$- and $Y$-EFPs were used for TAT. The in vivo TAT images of rat brain obtained were compared with the 3.0 T MRI images and histological photographs, and numerous important brain anatomical structures were identified. An example of our TAT approach for imaging a foreign object embedded in a rat brain was also demonstrated. This study suggests that TAT has a great potential to be used in neuroscience studies and in noninvasive imaging of brain disorders.