CERN Document Server: Presentations & Talks
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CERN Document Server latest documents in Presentations & TalksenFri, 09 Dec 2016 05:41:40 GMTInvenio 1.1.3.1106-62468cds.support@cern.ch36014963125https://cds.cern.ch/img/site_logo_rss.pngCERN Document Server
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International Beam Instrumentation Conference
https://cds.cern.ch/record/2238434
Thu, 08 Dec 2016 10:17:17 GMThttps://cds.cern.ch/record/2238434['']4th International Conference Initial Stages in High-Energy Nuclear Collisions
https://cds.cern.ch/record/2238394
Wed, 07 Dec 2016 17:56:15 GMThttps://cds.cern.ch/record/2238394['']Identification of Complex Dynamical Systems with Neural Networks (2/2)Identification of Complex Dynamical Systems with Neural Networks (2/2)
https://cds.cern.ch/record/2238350
The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character.
First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments.
Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parallel.
Third, we will move on to large closed dynamical systems with hundreds of state variables and will compare causal versus retro-causal models of the observations. The combination of these models will lead us to an implicit description of dynamical systems on manifolds.
Fourth, we will discuss the quantification of uncertainty in forecasting. In our framework the uncertainty appears as a consequence of principally unidentifiable hidden variables in the description of large systems.
Finally we will end up with a discussion on causality and predictability.
Lecturer's bio:
Dr. Hans Georg Zimmermann, studied mathematics, computer science and economics at the University of Bonn (focus on dynamical systems, control theory, PhD in game theory). He works since 1987 at Siemens, Corporate Research in Munich. Founding Member of the neural network research at Siemens (1987). Today, Senior Principal Research Scientist, scientific head of the neural network research with applications in forecasting, diagnosis and control. Member of the GOR (German Operation Research Society), DMV (German association of mathematicians), Advisor of the US National Science Foundation. Lectures and talks at universities on all continents.CERN. GenevaZimmermann, Hans-GeorgWed, 07 Dec 2016 12:34:50 GMT2016-12-06https://cds.cern.ch/record/2238350['']Electroweak Results from CMSElectroweak Results from CMS
https://cds.cern.ch/record/2238318
We present recent CMS measurements on electroweak boson production including single, double, and triple boson final states. Electroweak processes span many orders of magnitude in production cross section. Measurements of high-rate processes provide stringent tests of the standard model. In addition, rare triboson proceses and final states produced through vector boson scattering are newly accessible with the large integrated luminosity provided by the LHC. If new physics lies just beyond the reach of the LHC, its effects may manifest as enhancements to the high energy kinematics in mulitboson production. We present limits on new physics signatures using an effective field theory which models these modifications as modifications of electroweak gauge couplings. Since electroweak measurements will continue to benefit from the increasing integrated luminosity provided by the LHC, the future prospects of electroweak physics are discussed.CERN. GenevaKunkle, Joshua MiloWed, 07 Dec 2016 09:43:51 GMT2016-12-06https://cds.cern.ch/record/2238318['']58th ICFA Advanced Beam Dynamics Workshop on High Luminosity Circular e+e-Colliders
https://cds.cern.ch/record/2238273
Tue, 06 Dec 2016 16:35:58 GMThttps://cds.cern.ch/record/2238273['']HINT2016 - The international workshop on future potential of high intensity accelerators for particle and nuclear physics
https://cds.cern.ch/record/2238229
Tue, 06 Dec 2016 11:03:42 GMThttps://cds.cern.ch/record/2238229['']12th Central European Seminar on Particle Physics and Quantum Field Theory
https://cds.cern.ch/record/2238227
Tue, 06 Dec 2016 10:59:11 GMThttps://cds.cern.ch/record/2238227['']Kruger2016 - Workshop on Discovery Physics at the LHC
https://cds.cern.ch/record/2238226
Tue, 06 Dec 2016 10:57:22 GMThttps://cds.cern.ch/record/2238226['']3D PARTON DISTRIBUTIONS: PATH TO THE LHC
https://cds.cern.ch/record/2237752
Tue, 06 Dec 2016 10:12:57 GMThttps://cds.cern.ch/record/2237752['']2017 MERIT Public Session /EN presentation2017 MERIT Public Session /EN presentation
https://cds.cern.ch/record/2237751
CERN. GenevaStappers, SaraPerez Reale, ValeriaTue, 06 Dec 2016 10:08:32 GMT2016-12-06https://cds.cern.ch/record/2237751['']Identification of Complex Dynamical Systems with Neural Networks (1/2)Identification of Complex Dynamical Systems with Neural Networks (1/2)
https://cds.cern.ch/record/2237701
The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character.
First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments.
Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parallel.
Third, we will move on to large closed dynamical systems with hundreds of state variables and will compare causal versus retro-causal models of the observations. The combination of these models will lead us to an implicit description of dynamical systems on manifolds.
Fourth, we will discuss the quantification of uncertainty in forecasting. In our framework the uncertainty appears as a consequence of principally unidentifiable hidden variables in the description of large systems.
Finally we will end up with a discussion on causality and predictability.
Lecturer's bio:
Dr. Hans Georg Zimmermann, studied mathematics, computer science and economics at the University of Bonn (focus on dynamical systems, control theory, PhD in game theory). He works, since 1987 at Siemens, Corporate Research in Munich. Founding Member of the neural network research at Siemens (1987). Today, Senior Principal Research Scientist, scientific head of the neural network research with applications in forecasting, diagnosis and control. Member of the GOR (German Operation Research Society), DMV (German association of mathematicians), Advisor of the US National Science Foundation. Lectures and talks at universities on all continents.CERN. GenevaZimmermann, Hans-GeorgMon, 05 Dec 2016 16:01:00 GMT2016-12-05https://cds.cern.ch/record/2237701['']25th Russian Particle Accelerator Conference
https://cds.cern.ch/record/2237547
Mon, 05 Dec 2016 10:31:22 GMThttps://cds.cern.ch/record/2237547['']Miami Conference on Elementary Particles, Astrophysics and Cosmology
https://cds.cern.ch/record/2237494
Mon, 05 Dec 2016 02:12:36 GMThttps://cds.cern.ch/record/2237494['']10th Les Houches Workshop on Physics at TeV Colliders
https://cds.cern.ch/record/2237493
Sun, 04 Dec 2016 22:49:04 GMThttps://cds.cern.ch/record/2237493['']Parity Violation in Chiral Molecules: From Theory towards Spectroscopic Experiment and the Evolution of Biomolecular HomochiralityParity Violation in Chiral Molecules: From Theory towards Spectroscopic Experiment and the Evolution of Biomolecular Homochirality
https://cds.cern.ch/record/2237399
We shall start with an introductory discussion of three fundamental questions relating physics to molecular quantum dynamics and stereochemistry.
(i) To what extent are the fundamental symmetries and conservation laws of physics and their violations reflected in molecular quantum dynamics and spectroscopy, in general?
(ii) How important is parity violation for the quantum dynamics and spectroscopy of chiral molecules, in particular?
(iii) How important is parity violation for biomolecular homochirality, i.e. the quasi exclusive preference of L-amino acids and D-sugars in the biopolymers of life (proteins and DNA)?
The observation of biomolecular homochirality can be considered as a quasi-fossil of the evolution of life [1], the interpretation of which has been an open question for more than a century, with numerous related hypotheses, but no definitive answers. We shall briefly discuss the current status and the relation to the other two questions.
The discovery of parity violation led to important developments of physics in the 20th century and is understood within the standard model of particle physics, SMPP. For molecular stereochemistry it leads to the surprising prediction of a small energy difference D of the ground state energies of the enantiomers of chiral molecules, corresponding to a small reaction enthalpy for the stereomutation between the R and S enantiomers [2].This reaction enthalpy would be exactly zero by symmetry with exact parity conservation. Theory predicts D to be in the sub-femto eV range, typically, depending on the molecule (about D= 100 aeV for ClSSCl or CHFClBr, corresponding to a reaction enthalpy of about 10 pJ/mol). We have outlined three decades ago, how this small energy difference D might by measured by spectroscopic experiment [3], and recent progress indicates that experiment might be successful in the near future [4-8]. We shall discuss the current status of our experiments including alternatives pursued in other groups and the possible consequences for our understanding of molecular and biomolecular chirality.For background reading see [1-7].
1. M. Quack, Adv. Chem. Phys., 2014, 157, 249-290, Chapter 18.
2. M. Quack, Fundamental Symmetries and Symmetry Violations from High Resolution Spectroscopy, in Handbook of High Resolution Spectroscopy, Vol. 1, Chapt. 18, pp. 659-722 (Eds.: M. Quack, F. Merkt), Wiley, Chichester, New York, 2011
3. M. Quack, Chem. Phys. Lett., 1986, 132, 147-153.
4. P. Dietiker, E. Miloglyadov, M. Quack, A. Schneider, G. Seyfang, J. Chem. Phys., 2015, 143, 244305, (and references cited therein).
5. R.Prentner, M. Quack, J. Stohner, M. Willeke, J. Phys. Chem. A, 2015, 119, 12805-22.
6. C. Fábri, Ľ. Horný, M. Quack, ChemPhysChem, 2015, 16, 3584–3589.
7. S. Albert, I. Bolotova, Z. Chen, C. Fábri, L. Horný, M. Quack, G. Seyfang, D. Zindel, Phys. Chem. Chem. Phys., 2016, 18, 21976-21993. A.Albert, F.Arn,I.Bolotova,Z.Chen, C.Fabri, G.Grassi, P.Lerch, M.Quack, G.Seyfang, A.Wokaun, D. Zindel, J.Phys.Chem. Lett. 2016, 7, 3847-3853CERN. GenevaQuack, Martin Fri, 02 Dec 2016 14:47:20 GMT2016-12-01https://cds.cern.ch/record/2237399['']8th International Workshop on Multiple Partonic Interactions at the LHC
https://cds.cern.ch/record/2236135
Fri, 02 Dec 2016 11:02:29 GMThttps://cds.cern.ch/record/2236135['']Frontiers in physical sciences
https://cds.cern.ch/record/2236134
Fri, 02 Dec 2016 10:47:34 GMThttps://cds.cern.ch/record/2236134['']New frontiers in PDF determinationNew frontiers in PDF determination
https://cds.cern.ch/record/2236004
Parton Distribution Functions (PDFs) are a crucial input at the LHC, their uncertainty often being the limiting factor in the accuracy of theoretical predictions. At the same time the LHC is delivering a number of precise measurements that have the potential to greatly constrain these functions. I will give an overview on the theory behind and on the state of the art of PDF determination. I will then mention the new theoretical and methodological challenges in modern PDF fits and explore the precision frontiers opened by the accuracy of the LHC data.CERN. GenevaUbiali, MariaFri, 02 Dec 2016 09:37:09 GMT2016-11-30https://cds.cern.ch/record/2236004['']Practical Statistics for Particle Physics Analyses: Search for New Physics (4/4)Practical Statistics for Particle Physics Analyses: Search for New Physics (4/4)
https://cds.cern.ch/record/2235848
This will be a 4-day series of 2-hour sessions as part of CERN's Academic Training Course. Each session will consist of a 1-hour lecture followed by one hour of practical computing, which will have exercises based on that day's lecture. While it is possible to follow just the lectures or just the computing exercises, we highly recommend that, because of the way this course is designed,
participants come to both parts.
In order to follow the hands-on exercises sessions, students need to bring their own laptops. The exercises will be run on a dedicated CERN Web notebook service, SWAN (swan.cern.ch), which is open to everybody holding a CERN computing account. The requirement to use the SWAN service is to have a CERN account and to have also access to Cernbox, the shared storage service at CERN. New users of cernbox are invited to activate beforehand cernbox by simply connecting to https://cernbox.cern.ch. A basic prior knowledge of ROOT and C++ is also recommended for participation in the practical session.
Day 4: Search for New Physics
A large fraction of Particle Physics Publications are devoted to searches for New Physics. Such analyses can result in discovery (e.g. Higgs boson), exclusion (e.g. SUSY for a large range of parameters), or be ambiguous. This last talk deals with the statistical issues relevant to such analyses. Topics involved include:
* p-values: Complaints about p-values; p-values and L-ratios; Critical values.
* Blind analyses
* Upper Limits, including CLs
* The Look Elsewhere Effect
* Why 5 sigma for discovery?
The example of the Higgs discovery, and the measurement of its mass and spin-parity are discussed.CERN. GenevaMoneta, LorenzoLyons, LouisThu, 01 Dec 2016 13:36:24 GMT2016-12-01https://cds.cern.ch/record/2235848['']RF SystemsIntroduction to Accelerator Physics 2016
https://cds.cern.ch/record/2235810
CERN. GenevaTECKER, FrankThu, 01 Dec 2016 09:46:41 GMT2016-10-05https://cds.cern.ch/record/2235810['']Longitudinal Beam Dynamics in Circular Machines IIntroduction to Accelerator Physics 2016
https://cds.cern.ch/record/2235809
CERN. GenevaTECKER, FrankThu, 01 Dec 2016 09:46:36 GMT2016-10-05https://cds.cern.ch/record/2235809['']Longitudinal Beam Dynamics in Circular Beams IIIntroduction to Accelerator Physics 2016
https://cds.cern.ch/record/2235753
CERN. GenevaTECKER, FrankWed, 30 Nov 2016 15:09:27 GMT2016-10-06https://cds.cern.ch/record/2235753['']Practical Statistics for Particle Physics Analyses: Bayes and Frequentism (3/4)Practical Statistics for Particle Physics Analyses: Bayes and Frequentism (3/4)
https://cds.cern.ch/record/2235749
This will be a 4-day series of 2-hour sessions as part of CERN's Academic Training Course. Each session will consist of a 1-hour lecture followed by one hour of practical computing, which will have exercises based on that day's lecture. While it is possible to follow just the lectures or just the computing exercises, we highly recommend that, because of the way this course is designed,
participants come to both parts.
In order to follow the hands-on exercises sessions, students need to bring their own laptops. The exercises will be run on a dedicated CERN Web notebook service, SWAN (swan.cern.ch), which is open to everybody holding a CERN computing account. The requirement to use the SWAN service is to have a CERN account and to have also access to Cernbox, the shared storage service at CERN. New users of cernbox are invited to activate beforehand cernbox by simply connecting to https://cernbox.cern.ch. A basic prior knowledge of ROOT and C++ is also recommended for participation in the practical session.
Day 3: Bayes and Frequentism:
These fundamental approaches to statistics different interpretations of 'What is Probability?'
Examples are given of how they estimate ranges for parameters. and how their interpretations of these ranges are very different.CERN. GenevaLyons, LouisMoneta, LorenzoWed, 30 Nov 2016 14:32:32 GMT2016-11-30https://cds.cern.ch/record/2235749['']Transverse Linear Beam Dynamics IIIntroduction to Accelerator Physics 2016
https://cds.cern.ch/record/2235740
CERN. GenevaHOLZER, BernhardWed, 30 Nov 2016 13:17:55 GMT2016-10-05https://cds.cern.ch/record/2235740['']Practical Statistics for Particle Physics Analyses: Chi-Squared and Goodness of Fit (2/4)Practical Statistics for Particle Physics Analyses: Chi-Squared and Goodness of Fit (2/4)
https://cds.cern.ch/record/2235733
This will be a 4-day series of 2-hour sessions as part of CERN's Academic Training Course. Each session will consist of a 1-hour lecture followed by one hour of practical computing, which will have exercises based on that day's lecture. While it is possible to follow just the lectures or just the computing exercises, we highly recommend that, because of the way this course is designed,
participants come to both parts.
In order to follow the hands-on exercises sessions, students need to bring their own laptops. The exercises will be run on a dedicated CERN Web notebook service, SWAN (swan.cern.ch), which is open to everybody holding a CERN computing account. The requirement to use the SWAN service is to have a CERN account and to have also access to Cernbox, the shared storage service at CERN. New users of cernbox are invited to activate beforehand cernbox by simply connecting to https://cernbox.cern.ch. A basic prior knowledge of ROOT and C++ is also recommended for participation in the practical session.
Day 2: Chi-squared and Goodness of Fit
The chi-squared method can be used not only for estimating parameters and their
correlations, but also for providing aa measure for Goodness of Fit.Examples are given
where the number of degrees of freedeom is not what we might expect. Other Goodness of Fit techniques are discussed, that work with fewer observations than are required by
the chi-squared method.CERN. GenevaLyons, LouisMoneta, LorenzoWed, 30 Nov 2016 12:17:15 GMT2016-11-29https://cds.cern.ch/record/2235733['']