The analysis of vast amounts of data constitutes a major challenge in modern high energy physics experiments. Machine learning (ML) methods, typically trained on simulated data, are often employed to facilitate this task. Several choices need to be made by the user when training the ML algorithm. In addition to deciding which ML algorithm to use and choosing suitable observables as inputs, users typically need to choose among a plethora of algorithm-specific parameters. We refer to parameters that need to be chosen by the user as hyperparameters. These are to be distinguished from parameters that the ML algorithm learns autonomously during the training, without intervention by the user. The choice of hyperparameters is conventionally done manually by the user and often has a significant impact on the performance of the ML algorithm. In this paper, we explore two evolutionary algorithms: particle swarm optimization and genetic algorithm, for the purposes of performing the choice of optimal hyperparameter values in an autonomous manner. Both of these algorithms will be tested on different datasets and compared to alternative methods.

Estonia

Laurits Tani

Diana Rand

Christian Veelken

Mario Kadastik

Evolutionary algorithms for hyperparameter optimization in machine learning for application in high energy physics

We present a new color decomposition for QCD amplitudes at one-loop level as a generalization of the Del Duca-Dixon-Maltoni and Johansson-Ochirov decomposition at tree level. Starting from a minimal basis of planar primitive amplitudes we write down a color decomposition that is free of linear dependencies among appearing primitive amplitudes or color factors. The conjectured decomposition applies to any number of quark flavors and is independent of the choice of gauge group and matter representation. The results also hold for higher-dimensional or supersymmetric extensions of QCD. We provide expressions for any number of external quark-antiquark pairs and gluons.

Sweden

Gregor Kälin

Cyclic Mario worlds — color-decomposition for one-loop QCD

A dedicated search is presented for new phenomena in inclusive 8- and 10-jet final states with low missing transverse momentum, with and without identification of jets originating from b quarks. The analysis is based on data from proton–proton collisions corresponding to an integrated luminosity of 19.7fb−1 collected with the CMS detector at the LHC at s=8TeV . The dominant multijet background expectations are obtained from low jet multiplicity control samples. Data agree well with the standard model background predictions, and limits are set in several benchmark models. Colorons (axigluons) with masses between 0.6 and 0.75 (up to 1.15) TeV are excluded at 95% confidence level. Similar exclusion limits for gluinos in R -parity violating supersymmetric scenarios are from 0.6 up to 1.1 TeV. These results comprise the first experimental probe of the coloron and axigluon models in multijet final states.

Armenia

Vardan Khachatryan

Albert M Sirunyan

Armen Tumasyan

Austria

Wolfgang Adam

Ece Aşılar

Thomas Bergauer

Johannes Brandstetter

Erica Brondolin

Marko Dragicevic

Janos Erö

Martin Flechl

Markus Friedl

Rudolf Fruehwirth

Vasile Mihai Ghete

Christian Hartl

Natascha Hörmann

Josef Hrubec

Manfred Jeitler

Axel König

Ilse Krätschmer

Dietrich Liko

Takashi Matsushita

Ivan Mikulec

Dinyar Rabady

Navid Rad

Babak Rahbaran

Herbert Rohringer

Jochen Schieck

Josef Strauss

Wolfgang Treberer-Treberspurg

Wolfgang Waltenberger

Claudia-Elisabeth Wulz

Belarus

Vladimir Mossolov

Nikolai Shumeiko

Juan Suarez Gonzalez

Belgium

Sara Alderweireldt

Eddi A De Wolf

Xavier Janssen

Jasper Lauwers

Merijn Van De Klundert

Hans Van Haevermaet

Pierre Van Mechelen

Nick Van Remortel

Alex Van Spilbeeck

Shimaa Abu Zeid

Freya Blekman

Jorgen D'Hondt

Nadir Daci

Isabelle De Bruyn

Kevin Deroover

Natalie Heracleous

Steven Lowette

Seth Moortgat

Lieselotte Moreels

Annik Olbrechts

Quentin Python

Stefaan Tavernier

Walter Van Doninck

Petra Van Mulders

Isis Van Parijs

Hugues Brun

Cécile Caillol

Barbara Clerbaux

Gilles De Lentdecker

Hugo Delannoy

Giuseppe Fasanella

Laurent Favart

Reza Goldouzian

Anastasia Grebenyuk

Georgia Karapostoli

Thomas Lenzi

Alexandre Léonard

Jelena Luetic

Thierry Maerschalk

Andrey Marinov

Aidan Randle-conde

Tomislav Seva

Catherine Vander Velde

Pascal Vanlaer

Ryo Yonamine

Florian Zenoni

China

Fengwangdong Zhang

Anna Cimmino

Tom Cornelis

Didar Dobur

Alexis Fagot

Guillaume Garcia

Muhammad Gul

Deniz Poyraz

Sinem Salva Diblen

Robert Schöfbeck

Michael Tytgat

Ward Van Driessche

Efe Yazgan

Nicolas Zaganidis

Hamed Bakhshiansohi

France

Camille Beluffi

Olivier Bondu

Sébastien Brochet

Giacomo Bruno

Search for new phenomena in events with high jet multiplicity and low missing transverse momentum in proton–proton collisions at s=8TeV