arXiv subjects

Z. Tan

Publications and source records attributed to Z. Tan.

4 recordsLinked to original sources

arXiv2025

Irradiation Study Using QA Test Pieces of ATLAS18 ITk Strip Sensors with 80MeV Protons

The ATLAS experiment is planning a complete replacement of its inner detector(ID) with a new all-silicon inner tracker (ITk) for the ATLAS Inner Tracker Phase-2 upgrade. The ATLAS18 silicon strip sensors are designed to operate up to the integrated luminosity of 4000 fb$^{-1}$, which corresponds to the maximum fluence of $1.6 \times 10^{15} \, \text n_{\text{eq}} / \text{cm}^2$ (including safety factor). To enhance the quality assurance (QA) program to monitor the key properties of the sensors, the strip sensor community is considering to include China Spallation Neutron Source (CSNS) as a proton irradiation site and Institute of High Energy Physics (IHEP) as a QA test site. A total of 18 ATLAS18 ITk QA test pieces were irradiated with $6.0 \times 10^{14}$, $1.6 \times 10^{15}$, and $2.6 \times 10^{15} \, \text n_{\text{eq}} / \text{cm}^2$ protons at CSNS, and measured at IHEP, including IV (leakage current-voltage), CV (capacitance-voltage) and CCE (charge collection efficiency) measurements. The upgraded irradiation setup at CSNS and measurement setup at IHEP are shown in this paper. Irradiated samples were exchanged between IHEP, Ljubljana and Birmingham to cross-check CCE measurements.

physics.ins-det↗

arXiv2014

Piterbarg's max-discretisation theorem for stationary vector Gaussian processes observed on different grids

In this paper we derive Piterbarg's max-discretisation theorem for two different grids considering centered stationary vector Gaussian processes. So far in the literature results in this direction have been derived for the joint distribution of the maximum of Gaussian processes over $[0,T]$ and over a grid $ \mathfrak{R}(δ_1(T))=\{kδ_1(T): k=0,1,\cdots\}$. In this paper we extend recent findings by considering additionally the \bE{maximum} over another grid $ \mathfrak{R}(δ_2(T))$. We derive the joint limiting distribution of maximum of stationary Gaussian vector processes for different choices of such grids by letting $T\to \infty$.

math.PR↗

arXiv2014

On Piterbarg Max-discretisation Theorem for Multivariate Stationary Gaussian Processes

Let $\{X(t), t\geq0\}$ be a stationary Gaussian process with zero-mean and unit variance. A deep result derived in Piterbarg (2004), which we refer to as Piterbarg's max-discretisation theorem gives the joint asymptotic behaviour ($T\to \infty$) of the continuous time maximum $M(T)=\max_{t\in [0,T]} X(t), $ and the maximum $M^δ(T)=\max_{t\in \mathfrak{R}(δ)}X(t), $ with $\mathfrak{R}(δ) \subset [0,T]$ a uniform grid of points of distance $δ=δ(T)$. Under some asymptotic restrictions on the correlation function Piterbarg's max-discretisation theorem shows that for the limit result it is important to know the speed $δ(T)$ approaches 0 as $T\to \infty$. The present contribution derives the aforementioned theorem for multivariate stationary Gaussian processes.

math.PR↗

arXiv2014

Asymptotics of maxima of strongly dependent Gaussian processes

Let $\{X_{n}(t), t\in[0,\infty)\}, n\in\mathbb{N}$ be a sequence of centered dependent stationary Gaussian processes. The limit distribution of $\sup_{t\in[0,T(n)]}|X_{n}(t)|$ is established as $r_{n}(t)$, the correlation function of $X_{n}$ satisfies the local and long range strong dependence conditions, which extends the results obtained by Seleznjev (1991).

math.PR↗