Tootfinder

I woke up at 3am. So far, I’ve played Pokémon Go, Disney Spell Struck and some white noise on Noisli 😅

This https://arxiv.org/abs/2310.16796 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Sky location of Galactic white dwarf binaries in space-based gravitational wave detection
Quickly localizing the identified white dwarf (WD) binaries is the basic requirement for the space-based gravitational wave (GW) detection. In fact, the amplitude of GW signals are modulated by the periodic motion of GW detectors on the solar orbit. The intensity of the observed signals is enhanced according to the observation time beyond a year to enhance a high signal to noise ratio (SNR). As data gap exists, the completeness of the data observed for a long time depends on filling gaps in the…

Exact Solutions of Stochastic Burgers-KdV Equation with variable coefficients
Kolade Adjibi, Allan Martinez, Miguel Mascorro, Carlos Montes, Tamer Oraby, Rita Sandoval, Erwin Suazo
https://arxiv.org/abs/2403.19959

Exact Solutions of Stochastic Burgers-KdV Equation with variable coefficients
We will present exact solutions for three variations of stochastic Korteweg de Vries-Burgers (KdV-Burgers) equation featuring variable coefficients. In each variant, white noise exhibits spatial uniformity, and the three categories include additive, multiplicative, and advection noise. Across all cases, the coefficients are time-dependent functions. Our discovery indicates that solving certain deterministic counterparts of KdV-Burgers equations and composing the solution with a solution of stoc…

🔊 #NowPlaying on #BBC6Music's #CloudbustingWithLaurenLaverne
Disclosure:
🎵 White Noise (feat. AlunaGeorge)
#Disclosure
https://open.spotify.com/track/7ANO3LRdvefIongRYm5Smz
https://teaganbear.bandcamp.com/track/disclosure-white-noise-teaganbears-weird-remix

Exact Solutions of Stochastic Burgers-KdV Equation with variable coefficients
Kolade Adjibi, Allan Martinez, Miguel Mascorro, Carlos Montes, Tamer Oraby, Rita Sandoval, Erwin Suazo
https://arxiv.org/abs/2403.19959

Exact Solutions of Stochastic Burgers-KdV Equation with variable coefficients
We will present exact solutions for three variations of stochastic Korteweg de Vries-Burgers (KdV-Burgers) equation featuring variable coefficients. In each variant, white noise exhibits spatial uniformity, and the three categories include additive, multiplicative, and advection noise. Across all cases, the coefficients are time-dependent functions. Our discovery indicates that solving certain deterministic counterparts of KdV-Burgers equations and composing the solution with a solution of stoc…

#NowPlaying ❝We didn’t talk about what we were going to do on any of the shows we ever did. Only thing we had was that we knew how much longer we wanted to do it. We had an old darkroom timer that literally would turn off our equipment when the time came.❞
Dave and Greg, the duo known as #TheHearingTrumpet

In Conversation with The Hearing Trumpet
The Hearing Trumpet was one of the most important noise bands for Greh’s entry into the underground and we got a chance to talk with Dave and Greg, the duo that is the Hearing Trumpet. They provide…

This https://arxiv.org/abs/2309.16506 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the local linearization of the one-dimensional stochastic wave equation with a multiplicative space-time white noise forcing
In this note, we establish a bi-parameter linear localization of the one-dimensional stochastic wave equation with a multiplicative space-time white noise forcing.

Diffusion Posterior Proximal Sampling for Image Restoration
Hongjie Wu, Linchao He, Mingqin Zhang, Dongdong Chen, Kunming Luo, Mengting Luo, Ji-Zhe Zhou, Hu Chen, Jiancheng Lv
https://arxiv.org/abs/2402.16907

Diffusion Posterior Proximal Sampling for Image Restoration
Diffusion models have demonstrated remarkable efficacy in generating high-quality samples. Existing diffusion-based image restoration algorithms exploit pre-trained diffusion models to leverage data priors, yet they still preserve elements inherited from the unconditional generation paradigm. These strategies initiate the denoising process with pure white noise and incorporate random noise at each generative step, leading to over-smoothed results. In this paper, we introduce a refined paradigm …

This https://arxiv.org/abs/1907.13028 has been replaced.
link: https://scholar.google.com/scholar?q=a

BPHZ renormalisation and vanishing subcriticality asymptotics of the fractional $Φ^3_d$ model
We consider stochastic PDEs on the $d$-dimensional torus with fractional Laplacian of parameter $ρ\in(0,2]$, quadratic nonlinearity and driven by space-time white noise. These equations are known to be locally subcritical, and thus amenable to the theory of regularity structures, if and only if $ρ> d/3$. Using a series of recent results by the second named author, A. Chandra, I. Chevyrev, M. Hairer and L. Zambotti, we obtain precise asymptotics on the renormalisation counterterms as the molli…

Interpreting Deepcode, a learned feedback code
Yingyao Zhou, Natasha Devroye, Gyorgy Turan, Milos Zefran
https://arxiv.org/abs/2404.17519 https://

Interpreting Deepcode, a learned feedback code
Deep learning methods have recently been used to construct non-linear codes for the additive white Gaussian noise (AWGN) channel with feedback. However, there is limited understanding of how these black-box-like codes with many learned parameters use feedback. This study aims to uncover the fundamental principles underlying the first deep-learned feedback code, known as Deepcode, which is based on an RNN architecture. Our interpretable model based on Deepcode is built by analyzing the influence…

The muted, reduced colours and patina of noise that covers most of @…'s minimal #GenerativeArt projects result in unique, vintage works that often combine illustration and generative elements. "Viadukt", "Skalka" and the recent mini…

🔊 #NowPlaying on KEXP's #EasternEchoes
WHITE :
🎵 43 (Falling Down)
#WHITE
https://whitenoisecollectors.bandcamp.com/track/white-noise-43

A Linear Inverse Model for Colored-Gaussian Noise
Justin Lien, Yan-Ning Kuo, Hiroyasu Ando
https://arxiv.org/abs/2402.15184 https://a…

A Linear Inverse Model for Colored-Gaussian Noise
We propose a novel data-driven linear inverse model, called Colored-LIM, to extract the linear dynamics and diffusion matrix that define a linear stochastic process driven by an Ornstein-Uhlenbeck colored-noise. The Colored-LIM is a new variant of the classical linear inverse model (LIM) which relies on the white noise assumption. Similar to LIM, the Colored-LIM approximates the linear dynamics from a finite realization of a stochastic process and then solves the diffusion matrix based on, for …

It was when I’d spent 7 hours on one layer of white noise tape hiss in a short interlude track that I knew I lost the plot

what noise cancelling settings work on the recorder?

Non-parametric estimation for the stochastic wave equation
Eric Ziebell
https://arxiv.org/abs/2404.18823 https://arxiv.org/pdf/2404.1…

Non-parametric estimation for the stochastic wave equation
The spatially dependent wave speed of a stochastic wave equation driven by space-time white noise is estimated using the local observation scheme. Given a fixed time horizon, we prove asymptotic normality for an augmented maximum likelihood estimator as the resolution level of the observations tends to zero. We show that the expectation and variance of the observed Fisher information are intrinsically related to the kinetic energy within an associated deterministic wave equation and prove an as…

This https://arxiv.org/abs/2312.00376 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Dynamics of a quantum system interacting with white non-Gaussian baths: Poisson noise master equation
Quantum systems are unavoidably open to their surrounding degrees of freedom. The theory of open quantum systems is thus crucial to understanding the fluctuations, dissipation, and decoherence of a quantum system of interest. Typically, the bath is modeled as an ensemble of harmonic oscillators, which yields Gaussian statistics of the bath influence on the quantum systems. However, there are also phenomena in which the bath consists of two-state systems, spins, or anharmonic oscillators; theref…

Background music-to-work-to channels on YouTube (LoFi, Synthwave etc) have a trend towards tracks with rain-effect and similar "white noise" that's particularly effective at blocking out background sounds.
Symptomatic of increased return to office?

A Statistical Model of Bursty Mixed Gaussian-impulsive Noise: Model and Parameter Estimation
Tianfu Qi, Jun Wang
https://arxiv.org/abs/2402.06395 https://<…

A Statistical Model of Bursty Mixed Gaussian-impulsive Noise: Model and Parameter Estimation
Non-Gaussian impulsive noise (IN) with memory exists in many practical applications. When it is mixed with white Gaussian noise (WGN), the resultant mixed noise will be bursty. The performance of communication systems will degrade significantly under bursty mixed noise if the bursty characteristic is ignored. A proper model for the bursty mixed noise and corresponding algorithms needs to be designed to obtain desirable performance but there is no such model reported to the best of our knowledge…

Two Quantum Paradigms, but Still No Signal
Samuel Epstein
https://arxiv.org/abs/2402.13049 https://arxiv.org/pdf/2402.13049

Two Quantum Paradigms, but Still No Signal
An overwhelming majority of quantum (pure and mixed) states, when undertaking a POVM measurement, will result in a classical probability with no algorithmic information. Thus most quantum states produce white noise when measured. Furthermore most non-pointer states, when undergoing the decoherence process, will produce white noise. These results can be seen as consequences of the vastness of Hilbert spaces.

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
Olga Demler, Franco Giulianini, Yanyan Liu, Malte Londschien, Anja Sj\"ostr\"om, Tanmay Tanna, Heike Luttmann-Gibson, Antoine Jeanrenaud
https://arxiv.org/abs/2404.07906

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
We developed a method called batch and drift correction method by White Noise Normalization (WiNNbeta) to correct individual metabolites for batch effects and drifts. This method tests for white noise properties to identify metabolites in need of correction and corrects them by using fine-tuned splines. To test the method performance we applied WiNNbeta to LC-MS data from our metabolomic studies and computed CVs before and after WiNNbeta correction in quality control samples.

Testing the $\mathbf{\Lambda}$CDM Cosmological Model with Forthcoming Measurements of the Cosmic Microwave Background with SPT-3G
K. Prabhu, S. Raghunathan, M. Millea, G. Lynch, P. A. R. Ade, E. Anderes, A. J. Anderson, B. Ansarinejad, M. Archipley, L. Balkenhol, K. Benabed, A. N. Bender, B. A. Benson, F. Bianchini, L. E. Bleem, F. R. Bouchet, L. Bryant, E. Camphuis, J. E. Carlstrom, T. W. Cecil, C. L. Chang, P. Chaubal, P. M. Chichura, T. -L. Chou, A. Coerver, T. M. Crawford, A. Cukie…

Testing the $\mathbfΛ$CDM Cosmological Model with Forthcoming Measurements of the Cosmic Microwave Background with SPT-3G
We forecast constraints on cosmological parameters enabled by three surveys conducted with SPT-3G, the third-generation camera on the South Pole Telescope. The surveys cover separate regions of 1500, 2650, and 6000 ${\rm deg}^{2}$ to different depths, in total observing 25% of the sky. These regions will be measured to white noise levels of roughly 2.5, 9, and 12 $μ{\rm K-arcmin}$, respectively, in CMB temperature units at 150 GHz by the end of 2024. The survey also includes measurements at 95…

Role of long jumps in L\'evy noise induced multimodality
Przemys{\l}aw Pogorzelec, Bart{\l}omiej Dybiec
https://arxiv.org/abs/2403.02952 https://

Role of long jumps in Lévy noise induced multimodality
Lévy noise is a paradigmatic noise used to describe out-of-equilibrium systems. Typically, properties of Lévy noise driven systems are very different from their Gaussian white noise driven counterparts. In particular, under action of Lévy noise, stationary states in single-well, super-harmonic, potentials are no longer unimodal. Typically, they are bimodal however for fine-tuned potentials the number of modes can be further increased. The multimodality arises as a consequence of the competit…

This https://arxiv.org/abs/2311.06634 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Back to Basics: Fast Denoising Iterative Algorithm
We introduce Back to Basics (BTB), a fast iterative algorithm for noise reduction. Our method is computationally efficient, does not require training or ground truth data, and can be applied in the presence of independent noise, as well as correlated (coherent) noise, where the noise level is unknown. We examine three study cases: natural image denoising in the presence of additive white Gaussian noise, Poisson-distributed image denoising, and speckle suppression in optical coherence tomography…

This https://arxiv.org/abs/2309.04277 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Modulation and Estimation with a Helper
The problem of transmitting a parameter value over an additive white Gaussian noise (AWGN) channel is considered, where, in addition to the transmitter and the receiver, there is a helper that observes the noise non-causally and provides a description of limited rate $R_h$ to the transmitter and/or the receiver. We derive upper and lower bounds on the optimal achievable $α$-th moment of the estimation error and show that they coincide for small values of $α$ and for high values of $R_h$. The …

Laser Frequency Stabilization Using Light Shift in Compact Atomic Clocks
Claudio E. Calosso, Michele Gozzelino, Filippo Levi, Salvatore Micalizio
https://arxiv.org/abs/2404.14105 https://arxiv.org/pdf/2404.14105
arXiv:2404.14105v1 Announce Type: new
Abstract: This paper describes the Light-Shift Laser-Lock (LSLL) technique, a novel method intended for compact atomic clocks that greatly simplifies the laser setup by stabilizing the pumping-laser frequency to the atoms involved in the clock, without the need of an external reference. By alternating two clock sequences with different light shifts, the method estimates and cancels out a controlled amount of induced light shift, acting on the laser frequency. The LSLL technique is compatible with state-of-the-art 3-level clocks and was demonstrated with FPGA-based electronics on a pulsed-optically-pumped (POP) vapor-cell clock developed at INRIM. The results have shown that the LSLL technique operates robustly, having a capture range of gigahertz without significantly compromising clock stability. In our tests, the clock exhibited a white frequency noise of $3.2 \times 10^{-13}$ $\tau^{-1/2}$ for averaging time up to 4000 s, reaching a floor below $1 \times 10^{-14}$ up to 100 000 s. These performance levels meet the requirements of future Global Navigation Satellite Systems (GNSS) on-board clocks, and offer the added benefits of a reduced clock footprint, as well as increased reliability and robustness.

Colored Stochastic Multiplicative Processes with Additive Noise Unveil a Third-Order PDE, Defying Conventional FPE and Fick-Law Paradigms
Marco Bianucci, Mauro Bologna, Riccardo Mannella
https://arxiv.org/abs/2404.14229

Colored Stochastic Multiplicative Processes with Additive Noise Unveil a Third-Order PDE, Defying Conventional FPE and Fick-Law Paradigms
Research on stochastic differential equations (SDE) involving both additive and multiplicative noise has been extensive. In situations where the primary process is driven by a multiplicative stochastic process, additive white noise typically represents an intrinsic and unavoidable fast factor, including phenomena like thermal fluctuations, inherent uncertainties in measurement processes, or rapid wind forcing in ocean dynamics. This work focuses on a significant class of such systems, particula…

This https://arxiv.org/abs/2310.10784 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Almost sure central limit theorem for the hyperbolic Anderson model with Lévy white noise
In this paper, we present an almost sure central limit theorem (ASCLT) for the hyperbolic Anderson model (HAM) with a Lévy white noise in a finite-variance setting, complementing a recent work by Balan and Zheng (\emph{Trans.~Amer.~Math.~Soc.}, 2024) on the (quantitative) central limit theorems for the solution to the HAM. We provide two different proofs: one uses the Clark-Ocone formula and takes advantage of the martingale structure of the white-in-time noise, while the other is obtained by …

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
Olga Demler, Franco Giulianini, Yanyan Liu, Malte Londschien, Anja Sj\"ostr\"om, Tanmay Tanna, Heike Luttmann-Gibson, Antoine Jeanrenaud
https://arxiv.org/abs/2404.07906

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
We developed a method called batch and drift correction method by White Noise Normalization (WiNNbeta) to correct individual metabolites for batch effects and drifts. This method tests for white noise properties to identify metabolites in need of correction and corrects them by using fine-tuned splines. To test the method performance we applied WiNNbeta to LC-MS data from our metabolomic studies and computed CVs before and after WiNNbeta correction in quality control samples.

Scaling limit of fluctuations for high contrast stochastic homogenization of the Helmholtz equation: second order moments
Olivier Pinaud
https://arxiv.org/abs/2403.15359

Scaling limit of fluctuations for high contrast stochastic homogenization of the Helmholtz equation: second order moments
This work is concerned with the high contrast stochastic homogenization of the Helmholtz equation. Our goal is to characterize the second order moments of the scaling limit of the fluctuations of the wavefield. We show that these moments are those of a random wavefield solution to a homogenized Helmholtz equation with a white noise source term and obtain expressions for its variance. Two factors contribute to the white noise: fluctuations in the inverse permittivity of the high contrast inhomog…

Whiteness-based bilevel learning of regularization parameters in imaging
Carlo Santambrogio, Monica Pragliola, Alessandro Lanza, Marco Donatelli, Luca Calatroni
https://arxiv.org/abs/2403.07026

Whiteness-based bilevel learning of regularization parameters in imaging
We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussian noise. Compared to supervised and semi-supervised metrics relying either on the prior knowledge of reference data and/or on some (partial) knowledge on the noise statistics, the proposed approach optimizes the whiteness of the residual between the observed data and the observation model with no need of ground-truth…

The central limit theorems for integrable Hamiltonian systems perturbed by white noise
Chen Wang, Yong Li
https://arxiv.org/abs/2404.02704 https://<…

The central limit theorems for integrable Hamiltonian systems perturbed by white noise
In this paper, we consider the dynamics of integrable stochastic Hamiltonian systems. Utilizing the Nagaev-Guivarc'h method, we obtain several generalized results of the central limit theorem. Making use of this technique and the Birkhoff ergodic theorem, we prove that the invariant tori persist under stochastic perturbations. Moreover, they asymptotically follow a Gaussian distribution, which gives a positive answer to the stability of integrable stochastic Hamiltonian systems over time. Our r…

#TIL Brown noise is not named from a color analogy like with white noise. It's named because it is produced using Brownian motion, named after Robert Brown.

Couldn't figure out what the greyhound's face reminded me of, then I got it.

This https://arxiv.org/abs/2312.06057 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Improved convergence of the spectral proper orthogonal decomposition through time shifting
Spectral proper orthogonal decomposition (SPOD) is an increasingly popular modal analysis method in the field of fluid dynamics due to its specific properties: a linear system forced with white noise should have SPOD modes identical to response modes from resolvent analysis. The SPOD, coupled with the Welch method for spectral estimation, may require long time-resolved data sets. In this work, a linearised Ginzburg-Landau model is considered in order to study the method's convergence. SPOD mode…

P-Count: Persistence-based Counting of White Matter Hyperintensities in Brain MRI
Xiaoling Hu, Annabel Sorby-Adams, Frederik Barkhof, W Taylor Kimberly, Oula Puonti, Juan Eugenio Iglesias
https://arxiv.org/abs/2403.13996

P-Count: Persistence-based Counting of White Matter Hyperintensities in Brain MRI
White matter hyperintensities (WMH) are a hallmark of cerebrovascular disease and multiple sclerosis. Automated WMH segmentation methods enable quantitative analysis via estimation of total lesion load, spatial distribution of lesions, and number of lesions (i.e., number of connected components after thresholding), all of which are correlated with patient outcomes. While the two former measures can generally be estimated robustly, the number of lesions is highly sensitive to noise and segmentat…

The Guesswork of Ordered Statistics Decoding: Complexity and Practical Design
Chentao Yue, Changyang She, Branka Vucetic, Yonghui Li
https://arxiv.org/abs/2403.18488

The Guesswork of Ordered Statistics Decoding: Complexity and Practical Design
This paper investigates guesswork over ordered statistics and formulates the complexity of ordered statistics decoding (OSD) in binary additive white Gaussian noise (AWGN) channels. It first develops a new upper bound of guesswork for independent sequences, by applying the Holder's inequity to Hamming shell-based subspaces. This upper bound is then extended to the ordered statistics, by constructing the conditionally independent sequences within the ordered statistics sequences. We leverage the…

Continuous-Time Radar-Inertial and Lidar-Inertial Odometry using a Gaussian Process Motion Prior
Keenan Burnett, Angela P. Schoellig, Timothy D. Barfoot
https://arxiv.org/abs/2402.06174

Continuous-Time Radar-Inertial and Lidar-Inertial Odometry using a Gaussian Process Motion Prior
In this work, we demonstrate continuous-time radar-inertial and lidar-inertial odometry using a Gaussian process motion prior. Using a sparse prior, we demonstrate improved computational complexity during preintegration and interpolation. We use a white-noise-on-acceleration motion prior and treat the gyroscope as a direct measurement of the state while preintegrating accelerometer measurements to form relative velocity factors. Our odometry is implemented using sliding-window batch trajectory …

Hyperballistic transport in dense ionized matter under external AC electric fields
Daniele Gamba, Bingyu Cui, Alessio Zaccone
https://arxiv.org/abs/2402.08519

Hyperballistic transport in dense ionized matter under external AC electric fields
The Langevin equation is ubiquitously employed to numerically simulate plasmas and dusty plasmas. However, the usual assumption of white noise becomes untenable when the system is subject to an external AC electric field. This is because the charged particles in the plasma, which provide the thermal bath for the particle transport, become themselves responsive to the AC field and the thermal noise is field-dependent and non-Markovian. We theoretically study the particle diffusivity in a Langevi…

Non-unique Ergodicity for the 2D Stochastic Navier-Stokes Equations with Derivative of Space-Time White Noise
Huaxiang L\"u, Xiangchan Zhu
https://arxiv.org/abs/2402.13743

Non-unique Ergodicity for the 2D Stochastic Navier-Stokes Equations with Derivative of Space-Time White Noise
We prove existence of infinitely many stationary solutions as well as ergodic stationary solutions for the stochastic Navier-Stokes equations on $\mathbb{T}^2$ \begin{align*} \dif u+÷(u\otimes u)\dif t+\nabla p\dif t&=Δu\dif t + (-Δ)^{\fa/2}\dif B_t,\ \ \ \ ÷u=0,\notag \end{align*} driven by derivative of space-time white noise, where $\fa\in[0,\frac13)$. In this setting, the solutions are not function valued and probabilistic renormalization is required to give a meaning to the equations. …

Thermal noise squeezing and amplification in parametrically driven resonators
Adriano A. Batista, Raoni S. N. Moreira, A. A. Lisboa de Souza
https://arxiv.org/abs/2404.03758

Thermal noise squeezing and amplification in parametrically driven resonators
Here we propose several methods with increasing precision for analytically estimating white noise squeezing in the frequency domain of classical parametrically-driven resonators with added noise. The analytical model is based on obtaining the response of the resonator to the added noise using Green's function. The response consists of three parts: elastic, down, and up parametric conversions. We obtain the Green's function approximately using the first-order averaging method or exactly, in prin…

This https://arxiv.org/abs/2308.12437 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

A Stochastic Gravitational Wave Background in LISA from Unresolved White Dwarf Binaries in the Large Magellanic Cloud
The Laser Interferometer Space Antenna (LISA) is expected to detect a wide variety of gravitational wave sources in the mHz band. Some of these signals will elude individual detection, instead contributing as confusion noise to one of several stochastic gravitational-wave backgrounds (SGWBs) -- notably including the `Galactic foreground', a loud signal resulting from the superposition of millions of unresolved double white dwarf binaries (DWDs) in the Milky Way. It is possible that similar, wea…

Scaling limit of fluctuations for high contrast stochastic homogenization of the Helmholtz equation: second order moments
Olivier Pinaud
https://arxiv.org/abs/2403.15359

Scaling limit of fluctuations for high contrast stochastic homogenization of the Helmholtz equation: second order moments
This work is concerned with the high contrast stochastic homogenization of the Helmholtz equation. Our goal is to characterize the second order moments of the scaling limit of the fluctuations of the wavefield. We show that these moments are those of a random wavefield solution to a homogenized Helmholtz equation with a white noise source term and obtain expressions for its variance. Two factors contribute to the white noise: fluctuations in the inverse permittivity of the high contrast inhomog…

Laser Frequency Stabilization Using Light Shift in Compact Atomic Clocks
Claudio E. Calosso, Michele Gozzelino, Filippo Levi, Salvatore Micalizio
https://arxiv.org/abs/2404.14105 https://arxiv.org/pdf/2404.14105
arXiv:2404.14105v1 Announce Type: new
Abstract: This paper describes the Light-Shift Laser-Lock (LSLL) technique, a novel method intended for compact atomic clocks that greatly simplifies the laser setup by stabilizing the pumping-laser frequency to the atoms involved in the clock, without the need of an external reference. By alternating two clock sequences with different light shifts, the method estimates and cancels out a controlled amount of induced light shift, acting on the laser frequency. The LSLL technique is compatible with state-of-the-art 3-level clocks and was demonstrated with FPGA-based electronics on a pulsed-optically-pumped (POP) vapor-cell clock developed at INRIM. The results have shown that the LSLL technique operates robustly, having a capture range of gigahertz without significantly compromising clock stability. In our tests, the clock exhibited a white frequency noise of $3.2 \times 10^{-13}$ $\tau^{-1/2}$ for averaging time up to 4000 s, reaching a floor below $1 \times 10^{-14}$ up to 100 000 s. These performance levels meet the requirements of future Global Navigation Satellite Systems (GNSS) on-board clocks, and offer the added benefits of a reduced clock footprint, as well as increased reliability and robustness.

🔊 #NowPlaying on KEXP's #DriveTime
French Cassettes:
🎵 White Noise
#FrenchCassettes
https://open.spotify.com/track/20my9d2AdobuKH9CkaQybY

Persistent Diagram Estimation of Multivariate Piecewise H\"older-continuous Signals
Hugo Henneuse
https://arxiv.org/abs/2403.19396 https://

Persistent Diagram Estimation of Multivariate Piecewise Hölder-continuous Signals
To our knowledge, the analysis of convergence rates for persistent diagram estimation from noisy signals had remained limited to lifting signal estimation results through sup norm (or other functional norm) stability theorems. We believe that moving forward from this approach can lead to considerable gains. We illustrate it in the setting of Gaussian white noise model. We examine from a minimax perspective, the inference of persistent diagram (for sublevel sets filtration). We show that for pie…

This https://arxiv.org/abs/2401.10345 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Attack and Defense Analysis of Learned Image Compression
Learned image compression (LIC) is becoming more and more popular these years with its high efficiency and outstanding compression quality. Still, the practicality against modified inputs added with specific noise could not be ignored. White-box attacks such as FGSM and PGD use only gradient to compute adversarial images that mislead LIC models to output unexpected results. Our experiments compare the effects of different dimensions such as attack methods, models, qualities, and targets, conclu…

Whiteness-based bilevel learning of regularization parameters in imaging
Carlo Santambrogio, Monica Pragliola, Alessandro Lanza, Marco Donatelli, Luca Calatroni
https://arxiv.org/abs/2403.07026

Whiteness-based bilevel learning of regularization parameters in imaging
We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussian noise. Compared to supervised and semi-supervised metrics relying either on the prior knowledge of reference data and/or on some (partial) knowledge on the noise statistics, the proposed approach optimizes the whiteness of the residual between the observed data and the observation model with no need of ground-truth…

This https://arxiv.org/abs/2404.10698 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Drift estimation in stochastic flows using kernel integral operators
A stochastic differential equation (SDE) describes a motion in which a particle is governed simultaneously by the direction provided by a vector field / drift, and the scattering effects of white noise. The resulting motion can only be described as a random process instead of a solution curve. Due to the non-deterministic nature of this motion, the task of determining the drift from data is quite challenging, since the data does not directly represent the directional information of the flow. Th…

This https://arxiv.org/abs/2404.13685 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Second-Order Identification Capacity of AWGN Channels
In this paper, we establish the second-order randomized identification capacity (RID capacity) of the Additive White Gaussian Noise Channel (AWGNC). On the one hand, we obtain a refined version of Hayashi's theorem to prove the achievability part. On the other, we investigate the relationship between identification and channel resolvability, then we propose a finer quantization method to prove the converse part. Consequently, the second-order RID capacity of the AWGNC has the same form as the s…

Multimode-cavity picture of non-Markovian waveguide QED
Dario Cilluffo, Luca Ferialdi, G. Massimo Palma, Giuseppe Calaj\`o, Francesco Ciccarello
https://arxiv.org/abs/2403.07110 <…

Multimode-cavity picture of non-Markovian waveguide QED
We introduce a picture to describe and intrepret waveguide-QED problems in the non-Markovian regime of long photonic retardation times resulting in delayed coherent feedback. The framework is based on an intuitive spatial decomposition of the waveguide into blocks. Among these, the block directly coupled to the atoms embodies an effective lossy multimode cavity leaking into the rest of the waveguide, in turn embodying an effective white-noise bath. The dynamics can be approximated by retaining …

This https://arxiv.org/abs/2401.10345 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Attack and Defense Analysis of Learned Image Compression
Learned image compression (LIC) is becoming more and more popular these years with its high efficiency and outstanding compression quality. Still, the practicality against modified inputs added with specific noise could not be ignored. White-box attacks such as FGSM and PGD use only gradient to compute adversarial images that mislead LIC models to output unexpected results. Our experiments compare the effects of different dimensions such as attack methods, models, qualities, and targets, conclu…

Hyperballistic transport in dense ionized matter under external AC electric fields
Daniele Gamba, Bingyu Cui, Alessio Zaccone
https://arxiv.org/abs/2402.08519

Hyperballistic transport in dense ionized matter under external AC electric fields
The Langevin equation is ubiquitously employed to numerically simulate plasmas and dusty plasmas. However, the usual assumption of white noise becomes untenable when the system is subject to an external AC electric field. This is because the charged particles in the plasma, which provide the thermal bath for the particle transport, become themselves responsive to the AC field and the thermal noise is field-dependent and non-Markovian. We theoretically study the particle diffusivity in a Langevi…

This https://arxiv.org/abs/2305.14445 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Optimization and Validation of the DESIGNER dMRI preprocessing pipeline in white matter aging
Various diffusion MRI (dMRI) preprocessing pipelines are currently available to yield more accurate diffusion parameters. Here, we evaluated accuracy and robustness of the optimized Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline in a large clinical dMRI dataset and using ground truth phantoms. DESIGNER has been modified to improve denoising and target Gibbs ringing for partial Fourier acquisitions. We compared the revisited DESIGNER (Dv2) (including denoising, G…

This https://arxiv.org/abs/2311.07300 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Fragmentation of Colliding Liquid Rims
We present direct numerical simulations of the splashing process between two cylindrical liquid rims. This belongs to a class of impact and collision problems with a wide range of applications in science and engineering, and motivated here by splashing of breaking ocean waves. Interfacial perturbations with a truncated white noise frequency profile are introduced to the rims before their collision, whose subsequent morphological development is simulated by solving the two-phase incompressible N…

Spectral Analysis of Lattice Schr\"{o}dinger-Type Operators Associated with the Nonstationary Anderson Model and Intermittency
Dan Han, Stanislav Molchanov, Boris Vainberg
https://arxiv.org/abs/2403.13977

Spectral Analysis of Lattice Schrödinger-Type Operators Associated with the Nonstationary Anderson Model and Intermittency
The research explores a high irregularity, commonly referred to as intermittency, of the solution to the non-stationary parabolic Anderson problem: \begin{equation*} \frac{\partial u}{\partial t} = \varkappa \mathcal{L}u(t,x) + ξ_{t}(x)u(t,x) \end{equation*} with the initial condition \(u(0,x) \equiv 1\), where \((t,x) \in [0,\infty)\times \mathbb{Z}^d\). Here, \(\varkappa \mathcal{L}\) denotes a non-local Laplacian, and \(ξ_{t}(x)\) is a correlated white noise potential. The observed irreg…

Concentration estimates for SPDEs driven by fractional Brownian motion
Nils Berglund (Neamtu), Alexandra Blessing (Neamtu)
https://arxiv.org/abs/2404.16485

Concentration estimates for SPDEs driven by fractional Brownian motion
The main goal of this work is to provide sample-path estimates for the solution of slowly time-dependent SPDEs perturbed by a cylindrical fractional Brownian motion. Our strategy is similar to the approach by Berglund and Nader for space-time white noise. However, the setting of fractional Brownian motion does not allow us to use any martingale methods. Using instead optimal estimates for the probability that the supremum of a Gaussian process exceeds a certain level, we derive concentration es…

Second-Order Identification Capacity of AWGN Channels
Zhicheng Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma
https://arxiv.org/abs/2404.13685

Second-Order Identification Capacity of AWGN Channels
In this paper, we establish the second-order randomized identification capacity (RID capacity) of the Additive White Gaussian Noise Channel (AWGNC). On the one hand, we obtain a refined version of Hayashi's theorem to prove the achievability part. On the other, we investigate the relationship between identification and channel resolvability, then we propose a finer quantization method to prove the converse part. Consequently, the second-order RID capacity of the AWGNC has the same form as the s…

This https://arxiv.org/abs/2306.13556 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nli…

Amplification in parametrically-driven resonators near instability based on Floquet theory and Green's functions
Here we use Floquet theory to calculate the response of parametrically-driven time-periodic systems near the onset of parametric instability to an added external ac signal or white noise. We provide new estimates, based on the Green's function method, for the response of the system in the frequency domain. Furthermore, we write novel expressions for the power and the noise spectral densities. We validate our theoretical results by comparing our predictions for the specific cases of a single deg…

Consistent inclusion of fluctuations in first-order causal and stable relativistic hydrodynamics
Lorenzo Gavassino, Nicki Mullins, Mauricio Hippert
https://arxiv.org/abs/2402.06776

Consistent inclusion of fluctuations in first-order causal and stable relativistic hydrodynamics
We construct, for the first time, a BDNK theory for linear stochastic fluctuations, which is proved to be mathematically consistent, causal, and covariantly stable. The Martin-Siggia-Rose action is shown to be bilocal in most cases, and the noise is not white. The presence of non-hydrodynamic modes induces long-range correlations in the primary fluid variables (temperature, chemical potential, and flow velocity). However, correlators of conserved densities remain localized in space, and coincid…

Drift estimation in stochastic flows using kernel integral operators
Suddhasattwa Das
https://arxiv.org/abs/2404.10698 https://arxiv.…

Drift estimation in stochastic flows using kernel integral operators
A stochastic differential equation (SDE) describes a motion in which a particle is governed simultaneously by the direction provided by a vector field / drift, and the scattering effects of white noise. The resulting motion can only be described as a random process instead of a solution curve. Due to the non-deterministic nature of this motion, the task of determining the drift from data is quite challenging, since the data does not directly represent the directional information of the flow. Th…

This https://arxiv.org/abs/2312.05119 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI
Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pM…

This https://arxiv.org/abs/2303.07348 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Stochastic evolution equations with Wick-analytic nonlinearities
We study nonlinear stochastic partial differential equations with Wick-analytic type nonlinearities set in the framework of white noise analysis. These equations include the stochastic Fisher--KPP equations, stochastic Allen--Cahn, stochastic Newell--Whitehead--Segel, and stochastic Fujita--Gelfand equations. By implementing the theory of $C_0-$semigroups and evolution systems into the chaos expansion theory in infinite dimensional spaces, we prove existence and uniqueness of solutions for this…

This https://arxiv.org/abs/2208.01945 has been replaced.
link: https://scholar.google.com/scholar?q=a

Well-posedness of a parametrically forced nonlinear Schrödinger equation driven by translation-invariant noise
We prove well-posedness in $H^σ(\mathbb{R})$ for any $σ\in [0,\infty)$ of a parametrically forced nonlinear Schrödinger equation (PFNLS) in one dimension driven by multiplicative Stratonovich noise which has spatially homogeneous statistics. The noise is white in time and correlated in space. We first construct local mild solutions via a fixed-point argument. We then formulate a blow-up criterion by showing that the equation has persistence of integrability and regularity as long as the $L^2…

The spatial average of solutions to SPDEs is asymptotically independent of the solution
Ciprian A Tudor (LPP), J\'er\'emy Zurcher (LPP)
https://arxiv.org/abs/2404.11147

The spatial average of solutions to SPDEs is asymptotically independent of the solution
Let $\left(u(t,x), t\geq 0, x\in \mathbb{R}^d\right)$ be the solution to the stochastic heat or wave equation driven by a Gaussian noise which is white in time and white or correlated with respect to the spatial variable. We consider the spatial average of the solution $F_{R}(t)= \frac{1}{σ_R}\int_{\vert x\vert \leq R} \left( u(t,x)-1\right) dx$, where $σ^2_R= \mathbf{E} \left(\int_{\vert x\vert \leq R} \left( u(t,x)-1\right) dx\right)^2$. It is known that, when $R$ goes to infinity, $F_R(t)$…

This https://arxiv.org/abs/2310.03961 has been replaced.
link: https://scholar.google.com/scholar?q=a

Existence of martingale solutions to a nonlinearly coupled stochastic fluid-structure interaction problem
In this paper we study a nonlinear stochastic fluid-structure interaction problem with a multiplicative, white-in-time noise. The problem consists of the Navier-Stokes equations describing the flow of an incompressible, viscous fluid in a 2D cylinder interacting with an elastic lateral wall whose elastodynamics is described by a membrane/shell equation. The flow is driven by the inlet and outlet data, and by the stochastic forcing. The stochastic noise is applied both to the fluid equations as …

Multi-User SR-LDPC Codes via Coded Demixing with Applications to Cell-Free Systems
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
https://arxiv.org/abs/2402.06881

Multi-User SR-LDPC Codes via Coded Demixing with Applications to Cell-Free Systems
Novel sparse regression LDPC (SR-LDPC) codes exhibit excellent performance over additive white Gaussian noise (AWGN) channels in part due to their natural provision of shaping gains. Though SR-LDPC-like codes have been considered within the context of single-user error correction and massive random access, they are yet to be examined as candidates for coordinated multi-user communication scenarios. This article explores this gap in the literature and demonstrates that SR-LDPC codes, when combin…

This https://arxiv.org/abs/2402.02119 has been replaced.
link: https://scholar.google.com/scholar?q=a

Stochastic Partial Differential Equations, Space-time White Noise and Random Fields
This book is an introduction to the theory of stochastic partial differential equations (SPDEs), using the random field approach pioneered by J.B. Walsh (1986). The volume consists of two blocks: the core matter (Chapters 1 to 5) and the appendices (A, B and C). Chapter 1 introduces the subject, with a discussion of isonormal Gaussian processes, space-time white noise, and motivating examples of SPDEs. Chapter 2 presents a theory of stochastic integration with respect to space-time white noise.…

This https://arxiv.org/abs/2305.00164 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Estimation and inference for minimizer and minimum of convex functions: optimality, adaptivity and uncertainty principles
Optimal estimation and inference for both the minimizer and minimum of a convex regression function under the white noise and nonparametric regression models are studied in a nonasymptotic local minimax framework, where the performance of a procedure is evaluated at individual functions. Fully adaptive and computationally efficient algorithms are proposed and sharp minimax lower bounds are given for both the estimation accuracy and expected length of confidence intervals for the minimizer and m…

This https://arxiv.org/abs/2310.15756 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

On the Low-SNR Asymptotic Capacity of Two Types of Optical Wireless Channels under Average-Intensity Constraints
In this paper, we study two types of optical wireless channels under average-intensity constraints. One is called the Gaussian optical intensity channel, where the channel output models the converted electrical current corrupted by the additive white Gaussian noise. The other one is the Poisson optical intensity channel, where the channel output models the number of received photons corrupted by the positive dark current. When the average input intensity $\mathcal{E}$ is small, the capacity of …

An elementary approach to mixing and dissipation enhancement by transport noise
Dejun Luo, Bin Tang, Guohuan Zhao
https://arxiv.org/abs/2402.07484 https://…

An elementary approach to mixing and dissipation enhancement by transport noise
We investigate the mixing properties of solutions to the stochastic transport equation $d u= \circ d W \cdot\nabla u$, where the driving noise $W(t,x)$ is white in time, colored and divergence-free in space. Furthermore, we prove the dissipation enhancement in the presence of a small viscous term. Applying our results, we also derive the mixing properties for a regularized stochastic 2D Euler equation.

This https://arxiv.org/abs/2311.06987 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A 2D stochastic fluid-structure interaction problem in compliant arteries with non-zero longitudinal displacement
In this paper, we study a nonlinear fluid-structure interaction problem driven by a multiplicative, white-in-time noise. The problem consists of the Navier-Stokes equations describing the flow of an incompressible, viscous fluid in a 2D cylinder interacting with an elastic wall whose elastodynamics is described by membrane equations. The stochastic force is applied both to the fluid equations as a volumetric body force, and to the structure as an external forcing to the deformable fluid boundar…

This https://arxiv.org/abs/2310.15756 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

On the Low-SNR Asymptotic Capacity of Two Types of Optical Wireless Channels under Average-Intensity Constraints
In this paper, we study two types of optical wireless channels under average-intensity constraints. One is called the Gaussian optical intensity channel, where the channel output models the converted electrical current corrupted by the additive white Gaussian noise. The other one is the Poisson optical intensity channel, where the channel output models the number of received photons corrupted by the positive dark current. When the average input intensity $\mathcal{E}$ is small, the capacity of …

$(\log t)^\frac{2}{3}$-superdiffusivity for the 2d stochastic Burgers equation
Damiano De Gaspari, Levi Haunschmid-Sibitz
https://arxiv.org/abs/2404.07728 …

$(\log t)^\frac{2}{3}$-superdiffusivity for the 2d stochastic Burgers equation
The Stochastic Burgers equation was introduced in [H. van Beijeren, R. Kutner and H. Spohn, Excess noise for driven diffusive systems, PRL, 1985] as a continuous approximation of the fluctuations of the asymmetric simple exclusion process. It is formally given by $$\partial_tη=\frac{1}{2}Δη+ \mathfrak w\cdot\nabla(η^2) + \nabla\cdotξ,$$ where $ξ$ is $d$-dimensional space time white noise and $\mathfrak w$ is a fixed non-zero vector. In the critical dimension $d=2$ at stationarity, we show…

This https://arxiv.org/abs/2310.07677 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Exact variable selection in sparse nonparametric models
We study the problem of adaptive variable selection in a Gaussian white noise model of intensity $\varepsilon$ under certain sparsity and regularity conditions on an unknown regression function $f$. The $d$-variate regression function $f$ is assumed to be a sum of functions each depending on a smaller number $k$ of variables ($1 \leq k \leq d$). These functions are unknown to us and only few of them are nonzero. We assume that $d=d_\varepsilon \to \infty$ as $\varepsilon \to 0$ and consider the…

This https://arxiv.org/abs/2302.14178 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Hyperbolic Anderson model with Lévy white noise: spatial ergodicity and fluctuation
In this paper, we study one-dimensional hyperbolic Anderson models (HAM) driven by space-time pure-jump Lévy white noise in a finite-variance setting. Motivated by recent active research on limit theorems for stochastic partial differential equations driven by Gaussian noises, we present the first study in this Lévy setting. In particular, we first establish the spatial ergodicity of the solution and then a quantitative central limit theorem (CLT) for the spatial averages of the solution to H…

Exact Multi-Point Correlations in the Stochastic Heat Equation for Strictly Sublinear Coordinates
Pierre Yves Gaudreau Lamarre, Yier Lin
https://arxiv.org/abs/2403.06868

Exact Multi-Point Correlations in the Stochastic Heat Equation for Strictly Sublinear Coordinates
We consider the Stochastic Heat Equation (SHE) in $(1+1)$ dimensions with delta Dirac initial data and spacetime white noise. We prove exact large-time asymptotics for multi-point correlations of the SHE for strictly sublinear space coordinates. The sublinear condition is optimal, in the sense that different asymptotics are known to occur when the space coordinates grow linearly [Lin 2023, Theorem 1.1]. Lastly, a notable feature of our result is that it confirms the connection between multi-poi…

This https://arxiv.org/abs/2403.03638 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Stochastic partial differential equations for superprocesses in random environments
Let $X=(X_t, t\geq 0)$ be a superprocess in a random environment described by a Gaussian noise $W^g=\{W^g(t,x), t\geq 0, x\in \mathbb{R}^d\}$ white in time and colored in space with correlation kernel $g(x,y)$. We show that when $d=1$, $X_t$ admits a jointly continuous density function $X_t(x)$ that is a unique in law solution to a stochastic partial differential equation \begin{align*} \frac{\partial }{\partial t}X_t(x)=\fracΔ{2} X_t(x)+\sqrt{X_t(x)} \dot{V}(t,x)+X_t(x)\dot{W}^g(t, x) , \qu…

On the space-time fluctuations of the SHE and KPZ equation in the entire $L^{2}$-regime for spatial dimensions $d \geq 3$
Te-Chun Wang
https://arxiv.org/abs/2402.06874

On the space-time fluctuations of the SHE and KPZ equation in the entire $L^{2}$-regime for spatial dimensions $d \geq 3$
In this article, we consider the mollified stochastic heat equation with flat initial data and the corresponding Kardar-Parisi-Zhang (KPZ) equation in dimension $d \geq 3$ when the mollification parameter is turned off. In addition, we assume that the strength of the space-time white noise is small enough, such that the solution of the mollified stochastic heat equation has a finite limiting second moment. In this case, with regard to the mollified KPZ equation, we show that the fluctuation of …

Stochastic partial differential equations for superprocesses in random environments
Jieliang Hong, Jie Xiong
https://arxiv.org/abs/2403.03638 https://

Stochastic partial differential equations for superprocesses in random environments
Let $X=(X_t, t\geq 0)$ be a superprocess in a random environment described by a Gaussian noise $W^g=\{W^g(t,x), t\geq 0, x\in \mathbb{R}^d\}$ white in time and colored in space with correlation kernel $g(x,y)$. We show that when $d=1$, $X_t$ admits a jointly continuous density function $X_t(x)$ that is a unique in law solution to a stochastic partial differential equation \begin{align*} \frac{\partial }{\partial t}X_t(x)=\fracΔ{2} X_t(x)+\sqrt{X_t(x)} \dot{V}(t,x)+X_t(x)\dot{W}^g(t, x) , \qu…

The Smoluchowski-Kramers approximation with distribution-dependent potential and highly oscillating force
Chungang Shi, Wei Wang
https://arxiv.org/abs/2403.04237

The Smoluchowski-Kramers approximation with distribution-dependent potential and highly oscillating force
An approximation is derived for a Langevin equation with distribution-dependent potential and state-dependent, randomly fast oscillation. By some estimates and a diffusion approximation the limiting equation is shown to be distribution-dependent stochastic differential equation (SDEs) driven by white noise.

This https://arxiv.org/abs/2301.09225 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Skew-Normal Diffusions
We present a class of scalar Markovian diffusion processes whose transition probability densities are skewed Gaussian distributions. Their stochastic dynamics involve nonlinear and time-dependent drifts driven by White Gaussian noise sources. The drifts are obtained via generalized $h$-transforms of a novel class of local martingales. We can alternatively represent this class of processes as dynamic censoring models with partial observability and time-dependent correlations, which can be used a…