Counting Statistics Research Articles

Full counting statistics of 1d short range Riesz gases in confinement

We investigate the full counting statistics of a harmonically confined 1d short range Riesz gas consisting of N particles in equilibrium at finite temperature. The particles interact with each other through a repulsive power-law interaction with an exponent k > 1 which includes the Calogero–Moser model for k = 2. We examine the probability distribution of the number of particles in a finite domain [−W,W] called number distribution, denoted by N(W,N) . We analyze the probability distribution of N(W,N) and show that it exhibits a large deviation form for large N characterized by a speed N3k+2k+2 and by a large deviation function (LDF) of the fraction c=N(W,N)/N of the particles inside the domain and W. We show that the density profiles that create the large deviations display interesting shape transitions as one varies c and W. This is manifested by a third-order phase transition exhibited by the LDF that has discontinuous third derivatives. Monte–Carlo simulations based on Metropolis–Hashtings (MH) algorithm show good agreement with our analytical expressions for the corresponding density profiles. We find that the typical fluctuations of N(W,N) , obtained from our field theoretic calculations are Gaussian distributed with a variance that scales as Nνk , with νk=(2−k)/(2+k) . We also present some numerical findings on the mean and the variance. Furthermore, we adapt our formalism to study the index distribution (where the domain is semi-infinite (−∞,W]) , linear statistics (the variance), thermodynamic pressure and bulk modulus.

Full counting statistics of superconductor hybrid structures involving a time-dependent field

Here we discuss the charge transfer statistics of superconductor-quantum dot-superconductor contacts in nonequilibrium and involving a time-dependent field via the applied voltage. In this case, the effects of multiple Andreev reflections and the Josephson effect exhibit distinctive features. In addition to the effects observable in the conductance, we will also discuss the effects observable in the noise.

Occupational Priorities of People on Hemodialysis Who Participated in Energy Management Education.

Background. People with kidney failure who undergo hemodialysis treatment and experience chronic fatigue identify negative effects on occupational performance and participation as a key aspect of their illness experience. Purpose. To describe the occupational performance and participation problems of people treated with hemodialysis who live with debilitating fatigue. Method. Fifteen participants, who were randomized to participate in an energy management intervention as part of a randomized controlled trial, completed two occupation-based assessments at baseline and chose three priority occupational performance or participation problems to address as goals during the intervention. Results were analyzed using descriptive statistics (counts and percentages). Findings. Fifteen participants (mean age 60, 53% male) completed the occupation-based assessments. Participants stated that they wanted or needed more energy for a median of 22 of 55 occupations. Going out for food/drinks (n = 11), going to a movie/concert/performance (n = 10), and food preparation/clean-up (n = 10) were the top occupations for which participants required more energy. Prioritized occupational performance and participation problems most often fell within the household management (14 goals), self-care (6 goals), and hobbies (5 goals) domains. Conclusion. Occupational performance and participation problems are extensive among people treated with hemodialysis who live with debilitating fatigue. There is a clear need for occupation-based interventions that optimize occupational performance and participation in this population.

Importance sampling for counting statistics in one-dimensional systems.

In this paper, we consider the problem of numerical investigation of the counting statistics for a class of one-dimensional systems. Importance sampling, the cornerstone technique usually implemented for such problems, critically hinges on selecting an appropriate biased distribution. While an exponential tilt in the observable stands as the conventional choice for various problems, its efficiency in the context of counting statistics may be significantly hindered by the genuine discreteness of the observable. To address this challenge, we propose an alternative strategy, which we call importance sampling with the local tilt. We demonstrate the efficiency of the proposed approach through the analysis of three prototypical examples: a set of independent Gaussian random variables, Dyson gas, and symmetric simple exclusion process with a steplike initial condition.

Keyakinan terhadap Kitab Al Qur-An Terkait Penyembuhan

The Qur'an plays a major role in guiding humans to learn, gain knowledge, and direct all aspects of life both individually and socially in a positive direction. With the content of guidance, advice, and perfect laws, the Qur'an is the main source of reference for Muslims in living their daily lives and achieving success in this world and in the hereafter.The method that researchers use is descriptive qualitative research. Descriptive qualitative research is research conducted thoroughly on an object. The researcher becomes the main instrument in a qualitative study. Then, the results presented by the researcher are explained in the form of words obtained through valid data. Because qualitative research emphasizes meaning rather than generalization, and also the data cannot be resolved with statistical counts. The treatment process that occurs in one of the Tanjungpinang Kota communities affected by sticking disease is with the help of Koranic verses recited by the ustadz using mineral water media. The mineral water used is the condition that will be used in the treatment process. The water is then read the verses of the Qur'an by the ustadz and washed to several parts of the body of the person affected by sticking disease such as washing the head, hands, feet and finally the face. This paper describes the community's belief in the Qur'ān as a source of healing, which is deeply rooted in Islamic tradition and widely practiced in various Muslim communities, including in Tanjungpinang. The Qur'ān is not only seen as a holy book with high spiritual value but also as a source of alternative medicine that can cure physical, mental and spiritual illnesses.

Local Readout and Control of Current and Kinetic Energy Operators in Optical Lattices.

Quantum gas microscopes have revolutionized quantum simulations with ultracold atoms, allowing one to measure local observables and snapshots of quantum states. However, measurements so far were mostly carried out in the occupation basis. Here, we demonstrate how all kinetic operators, such as kinetic energy or current operators, can be measured and manipulated with single-bond resolution. Beyond simple expectation values of these observables, the single-shot measurements allow one to access full counting statistics and complex correlation functions. Our work paves the way for the implementation of efficient quantum state tomography and hybrid quantum computing protocols for itinerant particles on a lattice. In addition, we demonstrate how site-resolved programmable potentials enable a spatially selective, parallel readout in different bases as well as the engineering of arbitrary initial states.

Noninteracting particles in a harmonic trap with a stochastically driven center

Abstract We study a system of N noninteracting particles on a line in the presence of a harmonic trap U(x) = µ[x − z(t)]^2/2, where the trap center z(t) undergoes a bounded stochastic modulation. We show that this stochastic modulation drives the system into a nonequilibrium stationary state, where the joint distribution of the positions of the particles is not factorizable. This indicates strong correlations between the positions of the particles that are not inbuilt, but rather get generated by the dynamics itself. Moreover, we show that the stationary joint distribution can be fully characterized and has a special conditionally independent and identically distributed (CIID) structure. This special structure allows us to compute several observables analytically even in such a strongly correlated system, for an arbitrary bounded drive z(t). These observables include the average density profile, the correlations between particle positions, the order and gap statistics, as well as the full counting statistics. We then apply our general results to two specific examples where (i) z(t) represents a dichotomous telegraphic noise, and (ii) z(t) represents an Ornstein-Uhlenbeck process. Our analytical predictions are verified in numerical simulations, finding excellent agreement.

Quantification of radicals in aqueous solution by positronium lifetime: an experiment using a clinical PET scanner

Positrons entered into living organisms can form positronium (Ps), a bound state with electrons. Most of the triplet Ps (ortho-Ps) in insulating materials annihilate with electrons in surrounding molecules, and then the ortho-Ps lifetime varies depending on the surrounding electron density. The ortho-Ps lifetime may add new biological information to positron emission tomography (PET) scan information. In order to discuss the feasibility of quantifying (free) radicals in vivo by the Ps lifetime, we used a clinical PET system to make ortho-Ps lifetime measurements in aqueous solutions containing radicals. The results suggested that differences in radical concentrations in aqueous solutions of the order of a few mM could be quantified by the Ps lifetime if the counting statistic of the detection time difference spectra was more than 108 events. This concentration was much higher than the radical concentration generated in the physiological functions of living organisms. Therefore, we concluded that quantification of radicals generated in vivo by using the Ps lifetime is very difficult employing the current technology.

Precise quantification of skeletal muscle fibers reveals the physiological basis for growth rate discrepancies in broilers1

Skeletal muscle is composed of multinucleated muscle fibers, which play a crucial role in determining the quality of meat products in livestock. Quantifying the total number of muscle fibers (TNM) is essential for understanding muscle composition, yet remains challenging in poultry, particularly due to the size of the livestock that complicates the preparation of tissue sections for analysis and renders the counting process laborious. Our previous study developed an automatic muscle fiber quantification tool powered by deep learning, named MyoV, which has addressed this bottleneck. This study aimed to employ the tool for the accurate quantification of the TNM in the pectoral muscles of slow-growing (SL), medium-growing (ML), and fast-growing (FL) broilers. Results showed that FL exhibited higher growth performance compared to ML and SL from embryonic to rearing stages. Processing of whole slide images of pectoral muscle revealed significantly higher TNM in FL and ML than in SL (P < 0.01). The TNM of FL, ML and SL were 693,568.00 ± 54,169.80, 652,122.00 ± 65,822.60 and 539,778.57±40,722.94 at 7 days of age (D7), respectively. And the TNM at D35 were 663,014.93±58,801.11, 645,784.76±80,204.34 and 507,280.29±98,092.16 of FL, ML and SL. Differences in cross-sectional area (CSA) of muscle fibers among the three groups were consistent with TNM results. Correlation analysis showed a correlation coefficient of 0.73-0.89 between body weight (BW) and TNM and a correlation coefficient of 0.78-0.87 between BW and CSA. These findings directly indicate that the number of muscle fibers in broilers is an important foundation for their rapid growth and development. This study precisely quantifies the muscle fiber number of important skeletal muscle in poultry for the first time, providing the direct evidence for the physiological basis of rapid development in broilers and offering important data support for further in-depth researches on muscle fiber development.

Prototype Aplikasi Real Count Pemilihan Kepada Daerah Pada Badan Pengawas Pemilihan Umum Kota Palembang

PILKADA (Regional Head Election) and its deputy are routine activities carried out by each region to carry out democratic government activities. The Provincial KPU carries out Pilkada, and Regency / City KPU is collectively responsible for implementing general elections, supervised by the Provincial Bawaslu and Regency / City Bawaslu. The Palembang City Bawaslu's task in the vote counting process is to oversee the movement of recapitulation data from the TPS Supervisor level, Village / Sub-district Supervisors (PKD), and District Election Supervisory Committee (Panwascam) to the City Bawaslu so that there is no vote inflation which is considered dishonest and unfair. The process of collecting C1 and C-Plano form data to be recapitulated from the lower level to the upper level at the Palembang City Bawaslu collected, the process will take a relatively long time if done manually, especially limited by the long distance and poor natural conditions. In line with the development of increasingly modern technology, considering the need for data and the need for rapid dissemination of information on Pilkada results, in this study, the author will design Real Counting (also known as parallel vote aggregation) as a helpful way to monitor and accelerate the vote aggregation process in the form of an application prototype. This study aims to provide a prototype design for the Pilkada real count application at Bawaslu Palembang City. The software development method used in this study is the waterfall model method, which consists of analysis, design, coding, testing, and support or maintenance.

Hypokalemia, hypomagnesemia, and hyponatremia are associated with acute kidney injury in patients treated with cisplatin.

Cisplatin-associated acute kidney injury (C-AKI) is common. Predictive factors include age >60 years, hypertension, cisplatin dose, diabetes, and serum albumin < 3.5 g/L. The association between C-AKI and hypokalemia, hypomagnesemia or hyponatremia has not been well characterized. Data from a previous retrospective observational study was obtained. Patients were separated into three groups with similar cisplatin doses and schedules. Group A received cisplatin 60-100 mg/m2 every three weeks with laboratory assessments before treatment, group B received cisplatin 60-75 mg/m2 every three weeks with laboratory assessments before days 1 and 8 and group C had weekly cisplatin 40 mg/m2 with weekly laboratories assessments. The association between hypomagnesemia, hypokalemia, hyponatremia, and risk of AKI was determined using a counting process specification of Cox's regression models. A total of 1301 patients were separated into groups A (n = 713), B (n = 204), and C (n = 384). The proportion of patients with at least one event of hypokalemia, hypomagnesemia, or hyponatremia was lower in group A (29.2%, 57.6%, 36.2%) compared to groups B (43.6%, 67.2%, 59.8%) and C (49.0%, 78.7%, 51.0%). The incidence of all grade C-AKI was 35.6% (group A), 46.6% (group B), and 18.2% (group C). In group A, the risk of AKI doubled with hyponatremia or hypomagnesemia and tripled with hypokalemia. This association was not seen with other groups. Among patients with the highest doses of cisplatin, the presence of one electrolyte disorder was associated with an increased risk of C-AKI. Other studies are needed to characterize the presence of an electrolyte disorder as a predictive risk factor of C-AKI in this subpopulation.

Transformation of coastal wetlands in the Sundarban Delta (1999–2020)

Spanning across Bangladesh and India, the Sundarban Delta consists of over a thousand islands, the majority of which are protected. These islands are important for the rich biodiversity and unique species found here. However, these islands are also at the forefront of climate change due to the impact of rising sea levels and extreme weather events. Therefore, we analyzed the long-term transformations in the land use land cover (LULC) between 1999 and 2020. We used a variety of geostatistical methods, including optimized hot spots cold spots and join count statistics, to examine the spatial patterns of changes in LULC across the study area. The results of our analysis revealed substantial changes in the spatial patterns of mangroves and pond aquaculture. The changes revealed a distinct north–south demarcation in spatial patterns, in the form of clustering of mangroves in the uninhabited islands located in the south and pond aquaculture clustered in the northern inhabited islands. The loss of area under mangroves was concentrated in the southern edges of the islands, which were most exposed to erosion in the open ocean. Nevertheless, we observed an increase in the area under mangroves in some of the northern riverine islands (17 km2). In the case of pond aquaculture, it was mostly concentrated in inhabited islands in the north. Most of the expansions were concentrated in the Indian part of the delta (631 km2). It is noteworthy that because of effective conservation measures, there was very limited overlap between mangroves and pond aquaculture, denoting the conversion of agricultural land to pond aquaculture instead of mangroves. Thus, the results of our study revealed the importance of local level conservation policies and anthropogenic activities, such as deforestation and local level disturbance like over-extraction of water and pollution, on the changing patterns of LULC across this unique, fragile ecosystem. Future studies may incorporate a finer resolution time series of LULC changes over time and space to enable more detailed analysis.

Change of measure in a Heston–Hawkes stochastic volatility model

Abstract We consider the stochastic volatility model obtained by adding a compound Hawkes process to the volatility of the well-known Heston model. A Hawkes process is a self-exciting counting process with many applications in mathematical finance, insurance, epidemiology, seismology, and other fields. We prove a general result on the existence of a family of equivalent (local) martingale measures. We apply this result to a particular example where the sizes of the jumps are exponentially distributed. Finally, a practical application to efficient computation of exposures is discussed.

Stratified epidemic model using a latent marked Hawkes process

We extend the unstructured homogeneously mixing epidemic model introduced by Lamprinakou et al. (2023) to a finite population stratified by age bands. We model the actual unobserved infections using a latent marked Hawkes process and the reported aggregated infections as random quantities driven by the underlying Hawkes process. We apply a Kernel Density Particle Filter (KDPF) to infer the marked counting process, the instantaneous reproduction number for each age group and forecast the epidemic’s trajectory in the near future. Taking into account the individual inhomogeneity in age does not increase significantly the computational cost of the proposed inference algorithm compared to the cost of the proposed algorithm for the homogeneously unstructured epidemic model. We demonstrate that considering the individual heterogeneity in age, we can derive the instantaneous reproduction numbers per age group that provide a real-time measurement of interventions and behavioural changes of the associated groups. We illustrate the performance of the proposed inference algorithm on synthetic data sets and COVID-19-reported cases in various local authorities in the UK, and benchmark our model to the unstructured homogeneously mixing epidemic model. Our paper is a “demonstration” of a methodology that might be applied to factors other than age for stratification.

Computing macroscopic reaction rates in reaction-diffusion systems using Monte Carlo simulations.

Stochastic reaction-diffusion models are employed to represent many complex physical, biological, societal, and ecological systems. The macroscopic reaction rates describing the large-scale, long-time kinetics in such systems are effective, scale-dependent renormalized parameters that need to be either measured experimentally or computed by means of a microscopic model. In a Monte Carlo simulation of stochastic reaction-diffusion systems, microscopic probabilities for specific events to happen serve as the input control parameters. To match the results of any computer simulation to observations or experiments carried out on the macroscale, a mapping is required between the microscopic probabilities that define the Monte Carlo algorithm and the macroscopic reaction rates that are experimentally measured. Finding the functional dependence of emergent macroscopic rates on the microscopic probabilities (subject to specific rules of interaction) is a very difficult problem, and there is currently no systematic, accurate analytical way to achieve this goal. Therefore, we introduce a straightforward numerical method of using lattice Monte Carlo simulations to evaluate the macroscopic reaction rates by directly obtaining the count statistics of how many events occur per simulation time step. Our technique is first tested on well-understood fundamental examples, namely, restricted birth processes, diffusion-limited two-particle coagulation, and two-species pair annihilation kinetics. Next we utilize the thus gained experience to investigate how the microscopic algorithmic probabilities become coarse-grained into effective macroscopic rates in more complex model systems such as the Lotka-Volterra model for predator-prey competition and coexistence, as well as the rock-paper-scissors or cyclic Lotka-Volterra model and its May-Leonard variant that capture population dynamics with cyclic dominance motifs. Thereby we achieve a more thorough and deeper understanding of coarse graining in spatially extended stochastic reaction-diffusion systems and the nontrivial relationships between the associated microscopic and macroscopic model parameters, with a focus on ecological systems. The proposed technique should generally provide a useful means to better fit Monte Carlo simulation results to experimental or observational data.

Graphical criteria for the identification of marginal causal effects in continuous-time survival and event-history analyses

Abstract We consider continuous-time survival and event-history settings, where our aim is to graphically represent causal structures allowing us to characterize when a causal parameter is identified from observational data. This causal parameter is formalized as the effect on an outcome event of a (possibly hypothetical) intervention on the intensity of a treatment process. To establish identifiability, we propose novel graphical rules indicating whether the observed information is sufficient to obtain the desired causal effect by suitable reweighting. This requires a different type of graph than in discrete time. We formally define causal semantics for the corresponding dynamic graphs that represent local independence models for multivariate counting processes. Importantly, our work highlights that causal inference from censored data relies on subtle structural assumptions on the censoring process beyond independent censoring; these can be verified graphically. Put together, our results are the first to establish graphical rules for nonparametric causal identifiability in event processes in this generality for the continuous-time case, not relying on particular parametric survival models. We conclude with a data example on Human papillomavirus (HPV) testing for cervical cancer screening, where the assumptions are illustrated graphically and the desired effect is estimated by reweighted cumulative incidence curves.

Influence of loss function and electron dose on ptychography of 2D materials using the Wirtinger flow

Iterative phase retrieval is based on minimising a loss function as a measure of the consistency of an initial guess and underlying experimental data. Under ideal experimental conditions, real data contains Poissonian noise due to counting statistics. In this work, we use the Wirtinger Flow concept in combination with four common loss functions, being the L1 loss, the mean-squared error (MSE), the amplitude loss and the Poisson loss. Since only the latter reflects the counting statistics as an asymmetric Poisson distribution correctly, our simulation study focuses on two main cases. Firstly, high-dose momentum-resolved scanning transmission electron microscopy (STEM) of an MoS2 monolayer is considered for phase retrieval. In this case, it is found that the four losses perform differently with respect to chemical sensitivity and frequency transfer, which we interprete in terms of the substantially different signal level in the bright and dark field part of diffraction patterns. Remedies are discussed using further simulations, addressing the use of virtual ring detectors for the dark field, or restricting loss calculation to the bright field. Secondly, a dose series is presented down to 100 electrons per diffraction pattern. It is found that all losses yield qualitatively reasonable structural data in the phase, whereas only MSE and Poisson loss range at the correct amplitude level. Chemical contrast is, in general, reliably obtained using the Poisson concept, which also provides the most continuous spatial frequency transfer as to the reconstructed object transmission function.

Call center data modeling: a queueing science approach based on Markovian arrival process

ABSTRACT In this paper we analyze the well-known ‘Anonymous bank’ call center dataset from a queueing science viewpoint. For this purpose, fitted distributions for both the inter-arrival and service times as well as for customers patiences are integrated in a simulator to infer quantities of interest related to call centers managerial decisions as waiting times, abandonment rates and queue lengths. In particular, it is shown how a type of Markov renewal process, the Markovian arrival process (MAP), is able to capture some of the characterizing properties of arrivals in a modern call center as overdispersion and positive correlation between arrival counts. The work provides a new inference approach for the MAP based on the count process descriptors and presents new properties concerning the dependence structure of the cumulated number of arrivals in a MAP.

Large Deviation Full Counting Statistics in Adiabatic Open Quantum Dynamics.

The state of an open quantum system undergoing an adiabatic process evolves by following the instantaneous stationary state of its time-dependent generator. This observation allows one to characterize, for a generic adiabatic evolution, the average dynamics of the open system. However, information about fluctuations of dynamical observables, such as the number of photons emitted or the time-integrated stochastic entropy production in single experimental runs, requires controlling the whole spectrum of the generator and not only the stationary state. Here, we show how such information can be obtained in adiabatic open quantum dynamics by exploiting tools from large deviation theory. We prove an adiabatic theorem for deformed generators, which allows us to encode, in a biased quantum state, the full counting statistics of generic time-integrated dynamical observables. We further compute the probability associated with an arbitrary "rare" time history of the observable and derive a dynamics which realizes it in its typical behavior. Our results provide a way to characterize and engineer adiabatic open quantum dynamics and to control their fluctuations.

Optimization of contrast and dose in x-ray phase-contrast tomography with a Talbot-Lau interferometer

X-ray phase-contrast imaging has become a valuable tool for biomedical research due to its improved contrast abilities over regular attenuation-based imaging. The recently emerged Talbot-Lau interferometer can provide quantitative attenuation, phase-contrast and dark-field image data, even with low-brilliance x-ray tube sources. Thus, it has become a valid option for clinical environments. In this study, we analyze the effects of x-ray tube voltage and total number of images on the contrast-to-noise ratio (CNR) and dose-weighted CNR (CNRD) calculated from tomographic transmission and phase-contrast data of a phantom sample. Constant counting statistics regardless of the voltage was ensured by adjusting the image exposure time for each voltage setting. The results indicate that the x-ray tube voltage has a clear effect on both image contrast and noise. This effect is amplified in the case of phase-contrast images, which is explained by the polychromatic x-ray spectrum and the dependence of interferometer visibility on the spectrum. CNRD is additionally affected by the total imaging time. While submerging the sample into a water container effectively reduces image artefacts and improves the CNR, the additional attenuation of the water must be compensated with a longer exposure time. This reduces dose efficiency. Both the CNR and CNRD are higher in the phase-contrast images compared to transmission images. For transmission images, and phase-contrast images without the water container, CNRD can be increased by using higher tube voltages (in combination with a lower exposure time). For phase-contrast images with the water container, CNRD is increased with lower tube voltages. In general, the CNRD does not strongly depend on the number of tomographic angles or phase steps used.