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We present a complete and extensive analysis of associated chargino and neutralino production in the framework of a supersymmetric theory augmented by left-right symmetry. This model provides additional gaugino and higgsino states in both…

High Energy Physics - Phenomenology · Physics 2013-10-10 Adam Alloul , Mariana Frank , Benjamin Fuks , Michel Rausch de Traubenberg

Properties of metrics and pairs consisting of left and right connections are studied on the bimodules of differential 1-forms. Those bimodules are obtained from the derivation based calculus of an algebra of matrix valued functions, and an…

q-alg · Mathematics 2009-10-30 L. Dcabrowski , P. M. Hajac , G. Landi , P. Siniscalco

We consider the possibility to detect right-handed neutrinos, which are mostly singlets of the Standard Model gauge group, at future accelerators. Substantial mixing of these neutrinos with the active neutrinos requires a cancellation of…

High Energy Physics - Phenomenology · Physics 2008-11-26 Joern Kersten , Alexei Yu. Smirnov

In this paper, we have realized the left-right symmetric model with modular symmetry. We have used $\Gamma$(3) modular group which is isomorphic to non-abelian discrete symmetry group $A_4$. The advantage of using modular symmetry is the…

High Energy Physics - Phenomenology · Physics 2023-02-01 Ankita Kakoti , Bichitra Bijay Boruah , Mrinal Kumar Das

We present a python-based program for phenomenological investigations in particle physics using machine learning algorithms, called \verb"MLAnalysis". The program is able to convert LHE and LHCO files generated by \verb"MadGraph5_aMC@NLO"…

High Energy Physics - Phenomenology · Physics 2023-10-18 Yu-Chen Guo , Fan Feng , An Di , Shi-Qi Lu , Ji-Chong Yang

The present paper provides a method for finding partial differential equations satisfied by the Feynman integrals for diagrams of various types, using the Griffiths theorem on the reduction of poles of rational differential forms. As an…

Mathematical Physics · Physics 2017-05-16 Valentina A. Golubeva , Alexey N. Ivanov

In many extensions of the Standard Model, including a broad class of left-right symmetric and Grand Unified theories, the light neutrino mass matrix is given by the left-right symmetric seesaw formula $M_\nu = f v_L - \frac{v^2}{v_R} Y_\nu…

High Energy Physics - Phenomenology · Physics 2009-11-11 Pierre Hosteins , Stephane Lavignac , Carlos A. Savoy

Experimental limits on supersymmetry and similar theories are difficult to set because of the enormous available parameter space and difficult to generalize because of the complexity of single points. Therefore, more phenomenological,…

High Energy Physics - Experiment · Physics 2012-02-21 C. Gütschow , Z. Marshall

The Large Hadron Collider has a potential to probe the scale of left-right symmetry restoration and the associated lepton number violation. Moreover, it offers hope of measuring the right-handed leptonic mixing matrix. We show how this,…

High Energy Physics - Phenomenology · Physics 2011-04-20 Vladimir Tello , Miha Nemevsek , Fabrizio Nesti , Goran Senjanović , Francesco Vissani

We present a framework for performing a comprehensive analysis of a large class of supersymmetric models, including spectrum calculation, dark matter studies and collider phenomenology. To this end, the respective model is defined in an…

High Energy Physics - Phenomenology · Physics 2015-05-30 Florian Staub , Thorsten Ohl , Werner Porod , Christian Speckner

Advantages of the original symmetrical form of the parametrization of the lepton mixing matrix are discussed. It provides a conceptually more transparent description of neutrino oscillations and lepton number violating processes like…

High Energy Physics - Phenomenology · Physics 2011-10-27 W. Rodejohann , J. W. F. Valle

We consider the approximation of the inverse of the finite element stiffness matrix in the data sparse $\mathcal{H}$-matrix format. For a large class of shape regular but possibly non-uniform meshes including graded meshes, we prove that…

Numerical Analysis · Mathematics 2024-07-25 Niklas Angleitner , Markus Faustmann , Jens Markus Melenk

FeynGame is an open-source software tool to draw Feynman diagrams, but also to get acquainted with their structure. This article reports on a number of new features which have been added to FeynGame since its first release. These include…

High Energy Physics - Phenomenology · Physics 2024-01-24 Robert Harlander , Sven Yannick Klein , Magnus Schaaf

In particle physics, as in many areas of science, parameter inference relies on simulations to bridge the gap between theory and experiment. Recent developments in simulation-based inference have boosted the sensitivity of analyses;…

High Energy Physics - Phenomenology · Physics 2026-04-23 Ezequiel Alvarez , Sean Benevedes , Manuel Szewc , Jesse Thaler

In a supersymmetric extension of the standard model where baryon and lepton numbers are local gauge symmetries(BLMSSM), we deduce the Feynman rules for neutrinos and new neutralinos. We briey introduce the mass matrices for the particles…

High Energy Physics - Phenomenology · Physics 2016-05-30 Xing-Xing Dong , Shu-Min Zhao , Hai-Bin Zhang , Fang Wang , Tai-Fu Feng

We argue that the Mellin-Barnes representations of Feynman diagrams can be used for obtaining linear systems of homogeneous differential equations for the original Feynman diagrams with arbitrary powers of propagators without recourse to…

High Energy Physics - Theory · Physics 2015-06-05 Mikhail Yu. Kalmykov , Bernd A. Kniehl

The masses and mixing of the light left-handed neutrinos can be related to those of the heavy right-handed neutrinos in left-right symmetric theories. Properties of the light neutrinos are measured in terrestrial experiments and the…

High Energy Physics - Phenomenology · Physics 2014-11-17 A. S. Joshipura , E. A. Paschos , W. Rodejohann

Knowledge graph embedding models have gained significant attention in AI research. Recent works have shown that the inclusion of background knowledge, such as logical rules, can improve the performance of embeddings in downstream machine…

Artificial Intelligence · Computer Science 2019-08-21 Mojtaba Nayyeri , Chengjin Xu , Jens Lehmann , Hamed Shariat Yazdi