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  1. Article ; Online: Analysis-Specific Fast Simulation at the LHC with Deep Learning.

    Chen, C / Cerri, O / Nguyen, T Q / Vlimant, J R / Pierini, M

    Computing and software for big science

    2021  Volume 5, Issue 1, Page(s) 15

    Abstract: We present a fast-simulation application based on a deep neural network, designed to create large analysis-specific datasets. Taking as an example the generation ... ...

    Abstract We present a fast-simulation application based on a deep neural network, designed to create large analysis-specific datasets. Taking as an example the generation of
    Language English
    Publishing date 2021-06-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2908677-2
    ISSN 2510-2044 ; 2510-2036
    ISSN (online) 2510-2044
    ISSN 2510-2036
    DOI 10.1007/s41781-021-00060-4
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  2. Book ; Online: Adversarially Learned Anomaly Detection on CMS Open Data

    Knapp, Oliver / Dissertori, Guenther / Cerri, Olmo / Nguyen, Thong Q. / Vlimant, Jean-Roch / Pierini, Maurizio

    re-discovering the top quark

    2020  

    Abstract: We apply an Adversarially Learned Anomaly Detection (ALAD) algorithm to the problem of detecting new physics processes in proton-proton collisions at the Large Hadron Collider. Anomaly detection based on ALAD matches performances reached by Variational ... ...

    Abstract We apply an Adversarially Learned Anomaly Detection (ALAD) algorithm to the problem of detecting new physics processes in proton-proton collisions at the Large Hadron Collider. Anomaly detection based on ALAD matches performances reached by Variational Autoencoders, with a substantial improvement in some cases. Training the ALAD algorithm on 4.4 fb-1 of 8 TeV CMS Open Data, we show how a data-driven anomaly detection and characterization would work in real life, re-discovering the top quark by identifying the main features of the t-tbar experimental signature at the LHC.

    Comment: 16 pages, 9 figures
    Keywords High Energy Physics - Experiment ; Computer Science - Machine Learning ; High Energy Physics - Phenomenology
    Publishing date 2020-05-04
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning

    Chen, Cheng / Cerri, Olmo / Nguyen, Thong Q. / Vlimant, Jean-Roch / Pierini, Maurizio

    2020  

    Abstract: We present a fast simulation application based on a Deep Neural Network, designed to create large analysis-specific datasets. Taking as an example the generation of W+jet events produced in sqrt(s)= 13 TeV proton-proton collisions, we train a neural ... ...

    Abstract We present a fast simulation application based on a Deep Neural Network, designed to create large analysis-specific datasets. Taking as an example the generation of W+jet events produced in sqrt(s)= 13 TeV proton-proton collisions, we train a neural network to model detector resolution effects as a transfer function acting on an analysis-specific set of relevant features, computed at generation level, i.e., in absence of detector effects. Based on this model, we propose a novel fast-simulation workflow that starts from a large amount of generator-level events to deliver large analysis-specific samples. The adoption of this approach would result in about an order-of-magnitude reduction in computing and storage requirements for the collision simulation workflow. This strategy could help the high energy physics community to face the computing challenges of the future High-Luminosity LHC.

    Comment: 15 pages, 12 figures
    Keywords Physics - Computational Physics ; Computer Science - Machine Learning ; High Energy Physics - Experiment ; High Energy Physics - Phenomenology
    Subject code 006
    Publishing date 2020-10-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Pileup mitigation at the Large Hadron Collider with Graph Neural Networks

    Martinez, Jesus Arjona / Cerri, Olmo / Pierini, Maurizio / Spiropulu, Maria / Vlimant, Jean-Roch

    2018  

    Abstract: At the Large Hadron Collider, the high transverse-momentum events studied by experimental collaborations occur in coincidence with parasitic low transverse-momentum collisions, usually referred to as pileup. Pileup mitigation is a key ingredient of the ... ...

    Abstract At the Large Hadron Collider, the high transverse-momentum events studied by experimental collaborations occur in coincidence with parasitic low transverse-momentum collisions, usually referred to as pileup. Pileup mitigation is a key ingredient of the online and offline event reconstruction as pileup affects the reconstruction accuracy of many physics observables. We present a classifier based on Graph Neural Networks, trained to retain particles coming from high-transverse-momentum collisions, while rejecting those coming from pileup collisions. This model is designed as a refinement of the PUPPI algorithm, employed in many LHC data analyses since 2015. Thanks to an extended basis of input information and the learning capabilities of the considered network architecture, we show an improvement in pileup-rejection performances with respect to state-of-the-art solutions.

    Comment: 12 pages, 11 figures
    Keywords High Energy Physics - Phenomenology ; Computer Science - Machine Learning ; High Energy Physics - Experiment
    Subject code 006
    Publishing date 2018-10-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: Variational Autoencoders for New Physics Mining at the Large Hadron Collider

    Cerri, Olmo / Nguyen, Thong Q. / Pierini, Maurizio / Spiropulu, Maria / Vlimant, Jean-Roch

    2018  

    Abstract: Using variational autoencoders trained on known physics processes, we develop a one-sided threshold test to isolate previously unseen processes as outlier events. Since the autoencoder training does not depend on any specific new physics signature, the ... ...

    Abstract Using variational autoencoders trained on known physics processes, we develop a one-sided threshold test to isolate previously unseen processes as outlier events. Since the autoencoder training does not depend on any specific new physics signature, the proposed procedure doesn't make specific assumptions on the nature of new physics. An event selection based on this algorithm would be complementary to classic LHC searches, typically based on model-dependent hypothesis testing. Such an algorithm would deliver a list of anomalous events, that the experimental collaborations could further scrutinize and even release as a catalog, similarly to what is typically done in other scientific domains. Event topologies repeating in this dataset could inspire new-physics model building and new experimental searches. Running in the trigger system of the LHC experiments, such an application could identify anomalous events that would be otherwise lost, extending the scientific reach of the LHC.

    Comment: 29 pages, 12 figures, 5 tables
    Keywords High Energy Physics - Experiment ; Computer Science - Machine Learning ; High Energy Physics - Phenomenology
    Subject code 190
    Publishing date 2018-11-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article: Determinazione di composti organici con sodio ipoclorito. Nota II - Determinazione spettrofotometrica, colorimetrica e volumetrica di meprobamato e mebutamato

    Cerri, O

    Bollettino chimico farmaceutico

    1975  Volume 114, Issue 8, Page(s) 478–480

    Title translation Determination of organic compounds by means of sodium hypochlorite. II. Spectrophotometric, colorimetric and volumetric determination of meprobamate and mebutamate.
    MeSH term(s) Carbamates/analysis ; Colorimetry ; Meprobamate/analysis ; Sodium Hypochlorite ; Spectrophotometry, Ultraviolet
    Chemical Substances Carbamates ; Meprobamate (9I7LNY769Q) ; Sodium Hypochlorite (DY38VHM5OD)
    Language Italian
    Publishing date 1975-08
    Publishing country Italy
    Document type English Abstract ; Journal Article
    ZDB-ID 603071-3
    ISSN 0006-6648
    ISSN 0006-6648
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 627: Show issues Location:
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  7. Article: Sulla purezza dei principi attivi di origine estrattiva

    Cerri, O

    Bollettino chimico farmaceutico

    1974  Volume 113, Issue 5, Page(s) 277–279

    Title translation Purity of active principles of the extractive origin.
    MeSH term(s) Alkaloids/isolation & purification ; Chromatography, Thin Layer ; Spectrophotometry, Ultraviolet
    Chemical Substances Alkaloids
    Language Italian
    Publishing date 1974-05
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 603071-3
    ISSN 0006-6648
    ISSN 0006-6648
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  8. Article: Determinazione spettrofotometrica all'U.V. della nitroglicerina.

    Cerri, O

    Bollettino chimico farmaceutico

    1971  Volume 110, Issue 3, Page(s) 170–171

    Title translation Spectrophotometric U.V. determination of nitroglyceryin.
    MeSH term(s) Chemistry, Pharmaceutical ; Methods ; Nitroglycerin/analysis ; Spectrophotometry ; Ultraviolet Rays
    Chemical Substances Nitroglycerin (G59M7S0WS3)
    Language Italian
    Publishing date 1971-03
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 603071-3
    ISSN 0006-6648
    ISSN 0006-6648
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 627: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
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  9. Article: Sul dosaggio dei farmaci ad azione beta-bloccante.

    Cerri, O

    Bollettino chimico farmaceutico

    1970  Volume 109, Issue 5, Page(s) 338–343

    Title translation Determination of beta-blocking agents.
    MeSH term(s) Adrenergic beta-Antagonists/analysis ; Chemistry, Pharmaceutical ; Methods ; Sympatholytics/analysis
    Chemical Substances Adrenergic beta-Antagonists ; Sympatholytics
    Language Italian
    Publishing date 1970-05
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 603071-3
    ISSN 0006-6648
    ISSN 0006-6648
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 627: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
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  10. Article: Metodo gas-cromatografico di determinazione del meprobamato.

    Cerri, O

    Bollettino chimico farmaceutico

    1969  Volume 108, Issue 4, Page(s) 217–222

    Title translation Gas chromatographic determination of meprobamate.
    MeSH term(s) Chromatography, Gas ; Meprobamate/analysis
    Chemical Substances Meprobamate (9I7LNY769Q)
    Language Italian
    Publishing date 1969-04
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 603071-3
    ISSN 0006-6648
    ISSN 0006-6648
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 627: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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