Large deviation principle for stochastic heat equation with general rough noise

Posted by klaurent Peking

Kavli Affiliate: Ran Wang | First 5 Authors: Ruinan Li, Ran Wang, Beibei Zhang, , | Summary: We study Freidlin-Wentzell’s large deviation principle for one dimensional nonlinear stochastic heat equation driven by a Gaussian noise: $$frac{partial u^varepsilon(t,x)}{partial t} = frac{partial^2 u^varepsilon(t,x)}{partial x^2}+sqrt{varepsilon} sigma(t, x, u^varepsilon(t,x))dot{W}(t,x),quad t> 0,, xinmathbb{R},$$ where $dot W$ is white in time […]


Continue.. Large deviation principle for stochastic heat equation with general rough noise

A large deviation principle for the stochastic heat equation with general rough noise

Posted by klaurent Peking

Kavli Affiliate: Ran Wang | First 5 Authors: Ruinan Li, Ran Wang, Beibei Zhang, , | Summary: We study Freidlin-Wentzell’s large deviation principle for one dimensional nonlinear stochastic heat equation driven by a Gaussian noise: $$frac{partial u^varepsilon(t,x)}{partial t} = frac{partial^2 u^varepsilon(t,x)}{partial x^2}+sqrt{varepsilon} sigma(t, x, u^varepsilon(t,x))dot{W}(t,x),quad t> 0,, xinmathbb{R},$$ where $dot W$ is white in time […]


Continue.. A large deviation principle for the stochastic heat equation with general rough noise

Observation of a multitude of correlated states at the surface of bulk 1T-TaSe$_2$ crystals

Posted by klaurent Berkeley

Kavli Affiliate: Michael F. Crommie | First 5 Authors: Yi Chen, Wei Ruan, Jeffrey D. Cain, Ryan L. Lee, Salman Kahn | Summary: The interplay between electron-electron interactions and structural ordering can yield exceptionally rich correlated electronic phases. We have used scanning tunneling microscopy to investigate bulk 1T-TaSe2 and have uncovered surprisingly diverse correlated surface […]


Continue.. Observation of a multitude of correlated states at the surface of bulk 1T-TaSe$_2$ crystals

Improving Subgraph Representation Learning via Multi-View Augmentation

Posted by klaurent UCAS

Kavli Affiliate: Yi Zhou | First 5 Authors: Yili Shen, Jiaxu Yan, Cheng-Wei Ju, Jun Yi, Zhou Lin | Summary: Subgraph representation learning based on Graph Neural Network (GNN) has broad applications in chemistry and biology, such as molecule property prediction and gene collaborative function prediction. On the other hand, graph augmentation techniques have shown […]


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High-Precision Redshifts for Type Ia Supernovae with the Nancy Grace Roman Space Telescope P127 Prism

Posted by klaurent Chicago

Kavli Affiliate: Richard Kessler | First 5 Authors: Bhavin A. Joshi, Louis-Gregory Strolger, Russell E. Ryan, Jr., Alexei V. Filippenko, Rebekah Hounsell | Summary: We present results from simulating slitless spectroscopic observations with the Nancy Grace Roman Space Telescope’s (Roman) Wide-Field Instrument (WFI) P127 prism spanning 0.75 $mu m$ to 1.8 $mu m$. We quantify […]


Continue.. High-Precision Redshifts for Type Ia Supernovae with the Nancy Grace Roman Space Telescope P127 Prism

High-Precision Redshifts for Type Ia Supernovae with the Nancy Grace Roman Space Telescope P127 Prism

Posted by Chicago

Kavli Affiliate: Richard Kessler | First 5 Authors: Bhavin A. Joshi, Louis-Gregory Strolger, Russell E. Ryan, Jr., Alexei V. Filippenko, Rebekah Hounsell | Summary: We present results from simulating slitless spectroscopic observations with the Nancy Grace Roman Space Telescope’s (Roman) Wide-Field Instrument (WFI) P127 prism spanning 0.75 $mu m$ to 1.8 $mu m$. We quantify […]


Continue.. High-Precision Redshifts for Type Ia Supernovae with the Nancy Grace Roman Space Telescope P127 Prism

Removing the fat from your posterior samples with margarine

Posted by klaurent Cambridge

Kavli Affiliate: George Efstathiou | First 5 Authors: Harry T. J. Bevins, William J. Handley, Pablo Lemos, Peter H. Sims, Eloy de Lera Acedo | Summary: Bayesian workflows often require the introduction of nuisance parameters, yet for core science modelling one needs access to a marginal posterior density. In this work we use masked autoregressive […]


Continue.. Removing the fat from your posterior samples with margarine

Removing the fat from your posterior samples with margarine

Posted by klaurent Cambridge

Kavli Affiliate: George Efstathiou | First 5 Authors: Harry T. J. Bevins, William J. Handley, Pablo Lemos, Peter H. Sims, Eloy de Lera Acedo | Summary: Bayesian analysis has become an indispensable tool across many different cosmological fields including the study of gravitational waves, the Cosmic Microwave Background and the 21-cm signal from the Cosmic […]


Continue.. Removing the fat from your posterior samples with margarine

Marginal Post Processing of Bayesian Inference Products with Normalizing Flows and Kernel Density Estimators

Posted by klaurent Cambridge

Kavli Affiliate: George Efstathiou | First 5 Authors: Harry T. J. Bevins, William J. Handley, Pablo Lemos, Peter H. Sims, Eloy de Lera Acedo | Summary: Bayesian analysis has become an indispensable tool across many different cosmological fields including the study of gravitational waves, the Cosmic Microwave Background and the 21-cm signal from the Cosmic […]


Continue.. Marginal Post Processing of Bayesian Inference Products with Normalizing Flows and Kernel Density Estimators

Giant enhancement of third-harmonic generation in graphene-metal heterostructures

Posted by klaurent UCAS

Kavli Affiliate: Cheng Peng | First 5 Authors: Irati Alonso Calafell, Lee A. Rozema, David Alcaraz Iranzo, Alessandro Trenti, Joel D. Cox | Summary: Nonlinear nanophotonics leverages engineered nanostructures to funnel light into small volumes and intensify nonlinear optical processes with spectral and spatial control. Due to its intrinsically large and electrically tunable nonlinear optical […]


Continue.. Giant enhancement of third-harmonic generation in graphene-metal heterostructures