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| 2. |
- Ahdida, C., et al.
(author)
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Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks
- 2019
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In: Journal of Instrumentation. - : IOP PUBLISHING LTD. - 1748-0221. ; 14
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Journal article (peer-reviewed)abstract
- 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 dump and which travel distances between fifty metres and tens of kilometers. The SHiP detector needs to operate under ultra-low background conditions and requires large simulated samples of muon induced background processes. Through the use of Generative Adversarial Networks it is possible to emulate the simulation of the interaction of 400 GeV/c proton beams with the SHiP target, an otherwise computationally intensive process. For the simulation requirements of the SHiP experiment, generative networks are capable of approximating the full simulation of the dense fixed target, offering a speed increase by a factor of O(10(6)). To evaluate the performance of such an approach, comparisons of the distributions of reconstructed muon momenta in SHiP's spectrometer between samples using the full simulation and samples produced through generative models are presented. The methods discussed in this paper can be generalised and applied to modelling any non-discrete multi-dimensional distribution.
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| 3. |
- Ahdida, C., et al.
(author)
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Sensitivity of the SHiP experiment to Heavy Neutral Leptons
- 2019
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In: Journal of High Energy Physics (JHEP). - 1126-6708 .- 1029-8479. ; :4
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Journal article (peer-reviewed)abstract
- Heavy Neutral Leptons (HNLs) are hypothetical particles predicted by many extensions of the Standard Model. These particles can, among other things, explain the origin of neutrino masses, generate the observed matter-antimatter asymmetry in the Universe and provide a dark matter candidate. The SHiP experiment will be able to search for HNLs produced in decays of heavy mesons and travelling distances ranging between O(50 m) and tens of kilometers before decaying. We present the sensitivity of the SHiP experiment to a number of HNL's benchmark models and provide a way to calculate the SHiP's sensitivity to HNLs for arbitrary patterns of flavour mixings. The corresponding tools and data files are also made publicly available.
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| 4. |
- Ahdida, C., et al.
(author)
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The experimental facility for the Search for Hidden Particles at the CERN SPS
- 2019
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In: Journal of Instrumentation. - : Institute of Physics Publishing (IOPP). - 1748-0221. ; 14
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Journal article (peer-reviewed)abstract
- The Search for Hidden Particles (SHiP) Collaboration has shown that the CERN SPS accelerator with its 400 GeV/c proton beam offers a unique opportunity to explore the Hidden Sector [1-3]. The proposed experiment is an intensity frontier experiment which is capable of searching for hidden particles through both visible decays and through scattering signatures from recoil of electrons or nuclei. The high-intensity experimental facility developed by the SHiP Collaboration is based on a number of key features and developments which provide the possibility of probing a large part of the parameter space for a wide range of models with light long-lived super-weakly interacting particles with masses up to O(10) GeV/c(2) in an environment of extremely clean background conditions. This paper describes the proposal for the experimental facility together with the most important feasibility studies. The paper focuses on the challenging new ideas behind the beam extraction and beam delivery, the proton beam dump, and the suppression of beam-induced background.
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| 5. |
- Menden, MP, et al.
(author)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Journal article (peer-reviewed)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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| 6. |
- Milstead, David A., et al.
(author)
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The active muon shield in the SHiP experiment
- 2017
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In: Journal of Instrumentation. - 1748-0221. ; 12
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Journal article (peer-reviewed)abstract
- The SHiP experiment is designed to search for very weakly interacting particles beyond the Standard Model which are produced in a 400 GeV/c proton beam dump at the CERN SPS. An essential task for the experiment is to keep the Standard Model background level to less than 0.1 event after 2 x 10(20) protons on target. In the beam dump, around 10(11) muons will be produced per second. The muon rate in the spectrometer has to be reduced by at least four orders of magnitude to avoid muon-induced combinatorial background. A novel active muon shield is used to magnetically deflect the muons out of the acceptance of the spectrometer. This paper describes the basic principle of such a shield, its optimization and its performance.
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| 8. |
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| 9. |
- Donges, Jonathan F., et al.
(author)
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Unified functional network and nonlinear time series analysis for complex systems science : The pyunicorn package
- 2015
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In: Chaos. - : AIP Publishing. - 1054-1500 .- 1089-7682. ; 25:11
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Journal article (peer-reviewed)abstract
- We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni-and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.
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| 10. |
- Ferreira, David, et al.
(author)
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Atlantic-Pacific Asymmetry in Deep Water Formation
- 2018
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In: Annual Review of Earth and Planetary Science. - : Annual Reviews. - 0084-6597 .- 1545-4495. ; 46, s. 327-352
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Research review (peer-reviewed)abstract
- While the Atlantic Ocean is ventilated by high-latitude deep water formation and exhibits a pole-to-pole overturning circulation, the Pacific Ocean does not. This asymmetric global overturning pattern has persisted for the past 2-3 million years, with evidence for different ventilation modes in the deeper past. In the current climate, the Atlantic-Pacific asymmetry occurs because the Atlantic is more saline, enabling deep convection. To what extent the salinity contrast between the two basins is dominated by atmospheric processes (larger net evaporation over the Atlantic) or oceanic processes (salinity transport into the Atlantic) remains an outstanding question. Numerical simulations have provided support for both mechanisms; observations of the present climate support a strong role for atmospheric processes as well as some modulation by oceanic processes. A major avenue for future work is the quantification of the various processes at play to identify which mechanisms are primary in different climate states.
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