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We prove phase transitions for continuum percolation in a Boolean model based on a Cox point process with nonstabilizing directing measure. The directing measure, which can be seen as a stationary random environment for the classical…

Probability · Mathematics 2023-05-10 Benedikt Jahnel , Sanjoy Kumar Jhawar , Anh Duc Vu

We study a variety of stochastic contact processes -- directly related to models of rumor and disease spreading -- from the viewpoint of their constants of motion, either exact or approximated. Much as in deterministic systems, constants of…

Statistical Mechanics · Physics 2026-01-19 Damián H. Zanette , Eric A. Rozán

In this paper, we present a test for the maximal rank of the volatility process in continuous diffusion models observed with noise. Such models are typically applied in mathematical finance, where latent price processes are corrupted by…

Statistics Theory · Mathematics 2019-04-08 Tobias Fissler , Mark Podolskij

We present the Additive Poisson Process (APP), a novel framework that can model the higher-order interaction effects of the intensity functions in stochastic processes using lower dimensional projections. Our model combines the techniques…

Machine Learning · Statistics 2020-06-17 Simon Luo , Feng Zhou , Lamiae Azizi , Mahito Sugiyama

This paper introduces a new method for performing computational inference on log-Gaussian Cox processes. The likelihood is approximated directly by making novel use of a continuously specified Gaussian random field. We show that for…

Computation · Statistics 2015-11-02 Daniel Simpson , Janine Illian , Finn Lindgren , Sigrunn Sørbye , Håvard Rue

We develop a canonical framework for the study of the problem of registration of multiple point processes subjected to warping, known as the problem of separation of amplitude and phase variation. The amplitude variation of a real random…

Statistics Theory · Mathematics 2016-03-30 Victor M. Panaretos , Yoav Zemel

A method is proposed for obtaining the spectrum for noise that causes the phase decoherence of a qubit directly from experimentally available data. The method is based on a simple relationship between the spectrum and the coherence time of…

Quantum Physics · Physics 2015-05-28 Tatsuro Yuge , Susumu Sasaki , Yoshiro Hirayama

Automatic differentiation is an invaluable feature of machine learning and quantum machine learning software libraries. In this work it is shown how quantum automatic differentiation can be used to solve the condensed-matter problem of…

Quantum Physics · Physics 2022-11-29 Olivia Di Matteo , R. M. Woloshyn

This paper presents a finite difference quasi-Newton method for the minimization of noisy functions. The method takes advantage of the scalability and power of BFGS updating, and employs an adaptive procedure for choosing the differencing…

Optimization and Control · Mathematics 2019-01-09 Albert S. Berahas , Richard H. Byrd , Jorge Nocedal

The Hawkes process is a counting process that has self- and mutually-exciting features with many applications in various fields. In recent years, there have been many interests in the mean-field results of the Hawkes process and its…

Probability · Mathematics 2023-08-01 Fuqing Gao , Yunshi Gao , Lingjiong Zhu

In this paper, we consider a Cox point process driven by the Manhattan Poisson line process. We calculate the exact cumulative distribution function (CDF) of the path distance (L1 norm) between a randomly selected intersection and the…

Networking and Internet Architecture · Computer Science 2021-01-18 Konstantinos Koufos , Harpreet S. Dhillon , Mehrdad Dianati , Carl P. Dettmann

Qubit noise spectroscopy is an important tool for the experimental investigation of open quantum systems. However, conventional techniques for noise spectroscopy are time-consuming, because they require measurements of the noise spectral…

Quantum Physics · Physics 2025-06-24 Kaixin Huang , Demitry Farfurnik , Alireza Seif , Mohammad Hafezi , Yi-Kai Liu

In this paper, we develop simple, yet efficient, procedures for sampling approximations of the two-Parameter Poisson-Dirichlet Process and the normalized inverse-Gaussian process. We compare the efficiency of the new approximations to the…

Computation · Statistics 2012-09-25 Luai Al Labadi , Mahmoud Zarepour

We analyze noise in a quantum-enhanced fiber optic gyroscope (FOG), focusing on one of the leading sources of phase uncertainty - uncorrelated photon saturation. Taking a squeezed state input as a source for N00N states, we compute the…

Quantum Physics · Physics 2026-03-27 Stefan Evans , Joanna Ptasinski

We present an efficient algorithm to compute tight upper bounds of collision probability between two objects with positional uncertainties, whose error distributions are represented with non-Gaussian forms. Our approach can handle noisy…

Robotics · Computer Science 2019-12-17 Jae Sung Park , Dinesh Manocha

This is a review of shot noise, the time-dependent fluctuations in the electrical current due to the discreteness of the electron charge, in small conductors. The shot-noise power can be smaller than that of a Poisson process as a result of…

Mesoscale and Nanoscale Physics · Physics 2008-02-03 M. J. M. de Jong , C. W. J. Beenakker

We study the photon shot noise dephasing of a superconducting transmon qubit in the strong-dispersive limit, due to the coupling of the qubit to its readout cavity. As each random arrival or departure of a photon is expected to completely…

The problem of estimating the delays and amplitudes of a positive stream of pulses appears in many applications, such as single-molecule microscopy. This paper suggests estimating the delays and amplitudes using a convex program, which is…

Information Theory · Computer Science 2017-01-11 Tamir Bendory

In this work we detail the application of a fast convolution algorithm computing high dimensional integrals to the context of multiplicative noise stochastic processes. The algorithm provides a numerical solution to the problem of…

Computational Finance · Quantitative Finance 2015-03-19 Giacomo Bormetti , Sofia Cazzaniga

The large deviation principle in the small noise limit is derived for solutions of possibly degenerate It\^o stochastic differential equations with predictable coefficients, which may depend also on the large deviation parameter. The result…

Probability · Mathematics 2015-01-06 Alberto Chiarini , Markus Fischer
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