arXiv subjects

Berkin Uluutku

Publications and source records attributed to Berkin Uluutku.

5 recordsLinked to original sources

arXiv2026

Voxel-wise Bayesian Estimation for Multi-Population Positronium Lifetime Imaging

Positronium lifetime imaging (PLI) provides local annihilation environment data beyond conventional activity imaging. Existing approaches, however, often estimate lifetime parameters over predefined regions, neglecting multiple lifetime populations within the same location. We present a 3D, population-specific Bayesian framework for fast voxel-wise PLI. A partial system matrix describes the spatial probability of detected events, while measured lifetimes provide soft assignments to slow, fast, and noise populations. These event responsibilities are used to estimate a decay-rate posterior independently for each voxel, preserving local lifetime variation and statistical uncertainty. In simulations, our formulation recovered spatially varying slow-population decay rates and a common fast-population rate, whereas a single-population model produced systematic bias. Slow-population two-standard-deviation coverage ranged from 93.8% to 98.1%. Experimental validation using 124I triple-coincidence data from a Siemens Biograph Vision Quadra scanner produced separate slow- and fast-population maps for aluminum, nickel, copper, and quartz. The long-lived quartz component matched ortho-positronium, while the fast population showed material-dependent differences among metals. Fast-population coverage was lower (69.1%), indicating underestimated uncertainty. The method is highly efficient, requiring only seconds to minutes per population on a single CPU core. This framework provides fast, population-specific PLI with Bayesian uncertainty quantification, making spatially resolved statistical inference feasible and practical for volumetric applications.

stat.AP↗

arXiv2026

A Conjugate Bayesian Framework for Fast 3D Positronium Lifetime Estimation with a Partial System Matrix

Background: Positronium lifetime imaging extends conventional positron emission tomography by using the time interval between positron emission and annihilation as an additional contrast mechanism. Voxel-wise lifetime estimation in fully three-dimensional settings is computationally difficult because the number of feasible detector-time channels grows rapidly, whereas only a small subset is observed in practice. We developed a scalable statistical framework for three-dimensional positronium lifetime estimation based on a time-of-flight-aware partial system matrix restricted to observed detector-time channels, combined with posterior event-to-voxel weighting and a conjugate Gamma--Exponential update for closed-form voxel-wise effective-rate estimation. Results: Restricting the forward model to observed detector-time channels reduced memory and computational requirements while preserving the Poisson data model for retained detected triple coincidences. In simulated data with 4056 voxels, the analytic Bayesian estimator required 2.76 s versus 74.46 s for 10 L-BFGS-B iterations on the same CPU while accurately recovering the effective-rate map. In a triple-coincidence dataset acquired with a J-PET prototype scanner and a NEMA image-quality phantom, a 234 375-voxel effective-rate map was estimated in approximately 3 s from about $3.64\times10^5$ retained events. Conclusions: Restricting the system matrix to observed detector-time channels makes fully three-dimensional positronium lifetime estimation computationally practical for sparse triple-coincidence data. The proposed posterior-weighted conjugate update provides a fast and stable single-component surrogate estimator of voxel-wise effective lifetime for large-scale three-dimensional positronium lifetime imaging.

physics.med-ph↗

arXiv2022

Optimizing the Accuracy of Viscoelastic Characterization with AFM Force-Distance Experiments in the Time and Frequency Domains

We demonstrate that the method of characterizing viscoelastic materials with Atomic Force Microscopy (AFM) by fitting analytical models to force-distance (FD) curves often yields conflicting and physically unrealistic results. Because this method involves specifying a constitutive time-dependent viscoelastic model and then fitting said model to the experimental data, we show that the inconsistencies in this method are due to a lack of sensitivity of the model with respect to its parameters. Using approaches from information theory, this lack of sensitivity can be interpreted as a narrowed distribution of information which is obtained from the experiment. Furthermore, the equivalent representation of the problem in the frequency domain, achieved via modified Fourier transformation, offers an enhanced sensitivity through a widening of the information distribution. Using these distributions, we then define restrictions for the timescales which can be reliably accessed in both the time and frequency domains, which leads to the conclusion that the analysis of experiments in the time domain can frequently lead to inaccuracies. Finally, we provide an example where we use these restrictions as a guide to optimally design an experiment to characterize a polydimethylsiloxane (PDMS) polymer sample.

cond-mat.soft↗

arXiv2022

Direct Measurement of Storage and Loss Behavior in AFM Force-Distance Experiments Using the Modified Fourier Transformation

Force-distance curve experiments are commonly performed in Atomic Force Microscopy (AFM) to obtain the viscoelastic characteristics of materials, such as the storage and loss moduli or compliances. The classic methods used to obtain these characteristics consist of fitting a viscoelastic material model to the experimentally obtained AFM data. Here, we demonstrate a new method that utilizes the modified discrete Fourier transform to approximate the storage and loss behavior of a material directly from the data, without the need for a fit. Additionally, one may still fit a model to the resulting storage and loss behavior if a parameterized description of the material is desired. In contrast to fitting the data to a model chosen a priori, departing from a model-free description of the material's frequency behavior guides the selection of the model, such that the user may choose the one that is most appropriate for the particular material under study. To this end, we also include modified Fourier domain descriptions of commonly used viscoelastic models.

physics.app-ph↗

arXiv2020

Strain Induced Modulation of Local Transport of 2D Materials at the Nanoscale

Strain engineering offers unique control to manipulate the electronic band structure of two-dimensional materials (2DMs) resulting in an effective and continuous tuning of the physical properties. Ad-hoc straining 2D materials has demonstrated novel devices including efficient photodetectors at telecommunication frequencies, enhanced-mobility transistors, and on-chip single photon source, for example. However, in order to gain insights into the underlying mechanism required to enhance the performance of the next-generation devices with strain(op)tronics, it is imperative to understand the nano- and microscopic properties as a function of a strong non-homogeneous strain. Here, we study the strain-induced variation of local conductivity of a few-layer transition-metal-dichalcogenide using a conductive atomic force microscopy. We report a novel strain characterization technique by capturing the electrical conductivity variations induced by local strain originating from surface topography at the nanoscale, which allows overcoming limitations of existing optical spectroscopy techniques. We show that the conductivity variations parallel the strain deviations across the geometry predicted by molecular dynamics simulation. These results substantiate a variation of the effective mass and surface charge density by .026 me/% and .03e/% of uniaxial strain, respectively. Furthermore, we show and quantify how a gradual reduction of the conduction band minima as a function of tensile strain explains the observed reduced effective Schottky barrier height. Such spatially-textured electronic behavior via surface topography induced strain variations in atomistic-layered materials at the nanoscale opens up new opportunities to control fundamental material properties and offers a myriad of design and functional device possibilities for electronics, nanophotonics, flextronics, or smart cloths.

cond-mat.mes-hall↗