English
Related papers

Related papers: Comix, a new matrix element generator

200 papers

We introduce a new efficient algorithm for phase space generation. A parton shower is used to distribute events across all of multiplicity, flavor, and phase space, and these events can then be reweighted to any desired analytic…

High Energy Physics - Phenomenology · Physics 2008-12-18 Christian W. Bauer , Frank J. Tackmann , Jesse Thaler

We introduce multilayer structures based on phase-change materials for reconfigurable structural color generation. These structures can produce multiple distinct colors within a single pixel. Specifically, we design structures that generate…

In this paper, we present an extension of MadGraph5_aMC@NLO which is able to evaluate tree-level QCD matrix-elements up to $2\to 6$ (one more particle than before). To achieve this, we implemented Berends-Giele-like recursion, and…

High Energy Physics - Phenomenology · Physics 2022-12-20 Andrew Lifson , Olivier Mattelaer

Closed-form generating functions for counting one-face rooted hypermaps with a known number of darts by number of vertices and edges is found, using matrix integral expressions relating to the reduced density operator of a bipartite quantum…

Combinatorics · Mathematics 2015-01-28 Jacob P. Dyer

A method is given that "inverts" a logic grammar and displays it from the point of view of the logical form, rather than from that of the word string. LR-compiling techniques are used to allow a recursive-descent generation algorithm to…

cmp-lg · Computer Science 2016-08-31 Christer Samuelsson

The new matrix element generator AMEGIC++ is introduced, dedicated to describe multi-particle production in high energy particle collisions. It automatically generates helicity amplitudes for the processes under consideration and constructs…

High Energy Physics - Phenomenology · Physics 2009-11-07 F. Krauss , R. Kuhn , G. Soff

New machine learning based algorithms have been developed and tested for Monte Carlo integration based on generative Boosted Decision Trees and Deep Neural Networks. Both of these algorithms exhibit substantial improvements compared to…

High Energy Physics - Phenomenology · Physics 2017-07-04 Joshua Bendavid

Procedural content generation via machine learning (PCGML) has demonstrated its usefulness as a content and game creation approach, and has been shown to be able to support human creativity. An important facet of creativity is combinational…

Machine Learning · Computer Science 2020-06-18 Sam Snodgrass , Anurag Sarkar

Matrix generators for the general and special linear groups, the symplectic groups and the general and special unitary groups over finite fields. For the most part the generators have been obtained by translating Steinberg's generators for…

Group Theory · Mathematics 2022-01-25 Donald E. Taylor

In this paper, we develop a geometric framework for matrix rank-metric codes based on generator tensors and their slice spaces. To every nondegenerate matrix rank-metric code, we associate two systems, which translate metric properties of…

Combinatorics · Mathematics 2026-05-20 Gianira N. Alfarano , Martino Borello , Alessandro Neri

After an introduction to event generators we give an overview of developments in the field of joining matrix elements with parton showers. Starting with matrix element corrections, we also discuss implementations that match LO and NLO…

High Energy Physics - Phenomenology · Physics 2007-05-23 Stefan Gieseke

The structure of events in high-energy collisions is complex and not predictable from first principles. Event generators allow the problem to be subdivided into more manageable pieces, some of which can be described from first principles,…

High Energy Physics - Phenomenology · Physics 2007-05-23 Torbjörn Sjöstrand

We describe a generating tree approach to the enumeration and exhaustive generation of k-nonnesting set partitions and permutations. Unlike previous work in the literature using the connections of these objects to Young tableaux and…

Combinatorics · Mathematics 2014-02-11 Sophie Burrill , Sergi Elizalde , Marni Mishna , Lily Yen

The characteristic identity formalism discussed in our recent articles is further utilized to derive matrix elements of type 2 unitary irreducible $gl(m|n)$ modules. In particular, we give matrix element formulae for all gl(m|n) generators,…

Mathematical Physics · Physics 2016-01-20 Jason L. Werry , Mark D. Gould , Phillip S. Isaac

We introduce an explainable generative model by applying sparse operation on the feature maps of the generator network. Meaningful hierarchical representations are obtained using the proposed generative model with sparse activations. The…

Machine Learning · Computer Science 2019-02-01 Xianglei Xing , Song-Chun Zhu , Ying Nian Wu

In real world domains, most graphs naturally exhibit a hierarchical structure. However, data-driven graph generation is yet to effectively capture such structures. To address this, we propose a novel approach that recursively generates…

Machine Learning · Computer Science 2023-06-01 Mahdi Karami , Jun Luo

In this contribution the matrix element generator AMEGIC++ will be presented. It automatically generates Feynman diagrams, helicity amplitudes, and suitable phase space mappings for processes involving multi-particle final states within the…

High Energy Physics - Phenomenology · Physics 2007-05-23 T. Gleisberg , S. Hoeche , F. Krauss , A. Schaelicke , S. Schumann , J. Winter , G. Soff

A method is given that "inverts" a logic grammar and displays it from the point of view of the logical form, rather than from that of the word string. LR-compiling techniques are used to allow a recursive-descent generation algorithm to…

cmp-lg · Computer Science 2008-02-03 Christer Samuelsson

We seek to automate the design of molecules based on specific chemical properties. In computational terms, this task involves continuous embedding and generation of molecular graphs. Our primary contribution is the direct realization of…

Machine Learning · Computer Science 2019-04-01 Wengong Jin , Regina Barzilay , Tommi Jaakkola

We introduce a new framework for manipulating and interacting with deep generative models that we call network bending. We present a comprehensive set of deterministic transformations that can be inserted as distinct layers into the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-15 Terence Broad , Frederic Fol Leymarie , Mick Grierson
‹ Prev 1 2 3 10 Next ›