Publications related to TurboSMARTS: Accurate microarchitecture simulation sampling in minutes

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...

2019

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Lesya Shchutska, Aurelio Bay, Guido Haefeli, Elena Graverini, Alexey Boyarsky, Alexandre Emmanuel Grandchamp, Sun Hee Kim, Federico Leo Redi, Maria Elena Stramaglia, Oleg Ruchayskiy, Nikolaos Charitonidis, Sebastian Gerlach, Jean-Loup Tastet, Ana Bárbara Rodrigues Cavalcante, Ekaterina Kuznetsova, Hans Dijkstra, Anton Petrov, Sergei Smirnov

This paper presents a fast approach to simulating muons produced in interactions of the SPS proton beams with the target of the SHiP experiment. The SHIP experiment will be able to search for new long-lived particles produced in a 400 GeV/c SPS proton beam ...

IOP PUBLISHING LTD2019

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Lesya Shchutska, Aurelio Bay, Guido Haefeli, Elena Graverini, Alexey Boyarsky, Sun Hee Kim, Federico Leo Redi, Maria Elena Stramaglia, Oleg Ruchayskiy, Nikolaos Charitonidis, Sebastian Gerlach, Inar Timiryasov, Jean-Loup Tastet, Ana Bárbara Rodrigues Cavalcante, Ekaterina Kuznetsova, Hans Dijkstra, Anton Petrov, Sergei Smirnov

This paper presents a fast approach to simulating muons produced in interactions of the SPS proton beams with the target of the SHiP experiment. The SHiP experiment will be able to search for new long-lived particles produced in a 400~GeV

/c

SPS proton be ...

2019

Sampling at unknown locations, with an application in surface retrieval

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from t ...

2017

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface

Michele Ceriotti, Gareth Aneurin Tribello, Edoardo Baldi

Interfaces between different materials and phases play a crucial role in many physical and chemical phenomena. When performing simulations of matter at the atomic scale, however, it is often not trivial to characterize these interfaces, particularly when t ...

Iop Publishing Ltd2017

On the sensitivity of buildings to climate

Parag Rastogi

Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...

EPFL2016

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

Influence of loading history on mechanical properties of biomaterials

Tom Charles Maurice Walet

It is known that the mechanical response to load or displacement of a biological tissue can highly vary from one cycle to the next. Therefore, in order to establish a reference state for repeating data measurements, tissues are subjected to a preliminary s ...

2016

Incorporating Climate Change Predictions in the Analysis of Weather-based Uncertainty

Marilyne Andersen, Parag Rastogi

This paper proposes randomly-generated synthetic time series incorporating climate change forecasts to quantify the variation in energy simulation due to weather inputs, i.e., Monte Carlo analysis for uncertainty and sensitivity quantification. The method ...

IBPSA-USA, ASHRAE2016

The population genomics of rapid adaptation: disentangling signatures of selection and demography in white sands lizards

Jeffrey David Jensen, Susanne Petra Pfeifer, Stefan Jean Laurent, Nicky Louise Ormond

Understanding the process of adaptation during rapid environmental change remains one of the central focal points of evolutionary biology. The recently formed White Sands system of southern New Mexico offers an outstanding example of rapid adaptation, with ...

Wiley-Blackwell2016

TurboSMARTS: Accurate microarchitecture simulation sampling in minutes

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Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Sampling at unknown locations, with an application in surface retrieval

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface

On the sensitivity of buildings to climate

Shapes from Pixels

Influence of loading history on mechanical properties of biomaterials

Incorporating Climate Change Predictions in the Analysis of Weather-based Uncertainty

The population genomics of rapid adaptation: disentangling signatures of selection and demography in white sands lizards

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Sampling at unknown locations, with an application in surface retrieval

On the sensitivity of buildings to climate

The population genomics of rapid adaptation: disentangling signatures of selection and demography in white sands lizards

Shapes from Pixels

Extracting the interfacial free energy and anisotropy from a smooth fluctuating dividing surface

Influence of loading history on mechanical properties of biomaterials

Incorporating Climate Change Predictions in the Analysis of Weather-based Uncertainty

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks