scholarly journals The progress of High-Energy Physics in Atmosphere achieved with the implementation of particle physics and nuclear spectroscopy methods

2021 ◽  
Author(s):  
Ashot Chilingarian
2021 ◽  
Vol 9 ◽  
Author(s):  
N. Demaria

The High Luminosity Large Hadron Collider (HL-LHC) at CERN will constitute a new frontier for the particle physics after the year 2027. Experiments will undertake a major upgrade in order to stand this challenge: the use of innovative sensors and electronics will have a main role in this. This paper describes the recent developments in 65 nm CMOS technology for readout ASIC chips in future High Energy Physics (HEP) experiments. These allow unprecedented performance in terms of speed, noise, power consumption and granularity of the tracking detectors.


2019 ◽  
Vol 214 ◽  
pp. 02019
Author(s):  
V. Daniel Elvira

Detector simulation has become fundamental to the success of modern high-energy physics (HEP) experiments. For example, the Geant4-based simulation applications developed by the ATLAS and CMS experiments played a major role for them to produce physics measurements of unprecedented quality and precision with faster turnaround, from data taking to journal submission, than any previous hadron collider experiment. The material presented here contains highlights of a recent review on the impact of detector simulation in particle physics collider experiments published in Ref. [1]. It includes examples of applications to detector design and optimization, software development and testing of computing infrastructure, and modeling of physics objects and their kinematics. The cost and economic impact of simulation in the CMS experiment is also presented. A discussion on future detector simulation needs, challenges and potential solutions to address them is included at the end.


Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3569
Author(s):  
Simone Cammarata ◽  
Gabriele Ciarpi ◽  
Stefano Faralli ◽  
Philippe Velha ◽  
Guido Magazzù ◽  
...  

Optical links are rapidly becoming pervasive in the readout chains of particle physics detector systems. Silicon photonics (SiPh) stands as an attractive candidate to sustain the radiation levels foreseen in the next-generation experiments, while guaranteeing, at the same time, multi-Gb/s and energy-efficient data transmission. Integrated electronic drivers are needed to enable SiPh modulators’ deployment in compact on-detector front-end modules. A current-mode logic-based driver harnessing a pseudo-differential output stage is proposed in this work to drive different types of SiPh devices by means of the same circuit topology. The proposed driver, realized in a 65 nm bulk technology and already tested to behave properly up to an 8 MGy total ionizing dose, is hybridly integrated in this work with a lumped-element Mach–Zehnder modulator (MZM) and a ring modulator (RM), both fabricated in a 130 nm silicon-on-insulator (SOI) process. Bit-error-rate (BER) performances confirm the applicability of the selected architecture to either differential and single-ended loads. A 5 Gb/s data rate, in line with the current high energy physics requirements, is achieved in the RM case, while a packaging-related performance degradation is captured in the MZM-based system, confirming the importance of interconnection modeling.


2016 ◽  
Vol 3 (2) ◽  
pp. 252-256 ◽  
Author(s):  
Ling Wang ◽  
Mu-ming Poo

Abstract On 8 March 2012, Yifang Wang, co-spokesperson of the Daya Bay Experiment and Director of Institute of High Energy Physics, Chinese Academy of Sciences, announced the discovery of a new type of neutrino oscillation with a surprisingly large mixing angle (θ13), signifying ‘a milestone in neutrino research’. Now his team is heading for a new goal—to determine the neutrino mass hierarchy and to precisely measure oscillation parameters using the Jiangmen Underground Neutrino Observatory, which is due for completion in 2020. Neutrinos are fundamental particles that play important roles in both microscopic particle physics and macroscopic universe evolution. The studies on neutrinos, for example, may answer the question why our universe consists of much more matter than antimatter. But this is not an easy task. Though they are one of the most numerous particles in the universe and zip through our planet and bodies all the time, these tiny particles are like ‘ghost’, difficult to be captured. There are three flavors of neutrinos, known as electron neutrino (νe), muon neutrino (νμ), and tau neutrino (ντ), and their flavors could change as they travel through space via quantum interference. This phenomenon is known as neutrino oscillation or neutrino mixing. To determine the absolute mass of each type of neutrino and find out how they mix is very challenging. In a recent interview with NSR in Beijing, Yifang Wang explained how the Daya Bay Experiment on neutrino oscillation not only addressed the frontier problem in particle physics, but also harnessed the talents and existing technology in Chinese physics community. This achievement, Wang reckons, will not be an exception in Chinese high energy physics, when appropriate funding and organization for big science projects could be efficiently realized in the future.


2020 ◽  
Vol 35 (18) ◽  
pp. 2030006 ◽  
Author(s):  
Goran Senjanović

I reflect on some of the basic aspects of present day Beyond the Standard Model particle physics, focusing mostly on the issues of naturalness, in particular on the so-called hierarchy problem. To all of us, physics as natural science emerged with Galileo and Newton, and led to centuries of unparalleled success in explaining and often predicting new phenomena of nature. I argue here that the long-standing obsession with the hierarchy problem as a guiding principle for the future of our field has had the tragic consequence of deviating high energy physics from its origins as natural philosophy, and turning it into a philosophy of naturalness.


1998 ◽  
Vol 13 (06) ◽  
pp. 863-886 ◽  
Author(s):  
FRANK WILCZEK

In the first part of the paper, I give a low-resolution overview of the current state of particle physics — the triumph of the Standard Model and its discontents. I review and re-endorse the remarkably direct and (to me) compelling argument that existing data, properly interpreted, point toward a unified theory of fundamental particle interactions and toward low-energy supersymmetry as the near-term future of high energy physics as a natural science. I then attempt, as requested, some more "visionary" — i.e. even lower resolution — comments about the farther future. In that spirit, I emphasize the continuing importance of condensed matter physics as a source of inspiration and potential application, in particular for expansion of symmetry concepts, and of cosmology as a source of problems, applications, and perhaps ultimately limitations.


2019 ◽  
Vol 35 (07) ◽  
pp. 2050030
Author(s):  
Qiu-He Peng ◽  
Jing-Jing Liu ◽  
Chi-Kang Chou

There are some particle physics theories that go beyond the so-called “standard cosmological model” to predict the existence of magnetic monopoles (MMs). The discovery of MMs would be an incredible breakthrough in high-energy physics. The existence of MMs in the early Universe has been speculated and anticipated from Grand Unified Theory. If MMs exist, the inverse powers of the unification mass will not suppress the baryon number violating effects of grand unified gauge theories. Therefore, MM catalyzing nucleon decay is a typical strong interaction. This phenomenon is due to the boundary conditions that must be imposed on the core of MM fermion fields. We present a possible mechanism to explain the formation of the Hot Big Bang Cosmology. The main ingredient in our model is nucleon decay catalyzed by MMs (i.e. the Rubakov–Callan effect). It is shown that Hot Big Bang developed naturally because the luminosity due to the Rubakov–Callan effect is much greater than the Eddington luminosity (i.e. [Formula: see text]).


2020 ◽  
pp. 2030024
Author(s):  
Kapil K. Sharma

This paper reveals the future prospects of quantum algorithms in high energy physics (HEP). Particle identification, knowing their properties and characteristics is a challenging problem in experimental HEP. The key technique to solve these problems is pattern recognition, which is an important application of machine learning and unconditionally used for HEP problems. To execute pattern recognition task for track and vertex reconstruction, the particle physics community vastly use statistical machine learning methods. These methods vary from detector-to-detector geometry and magnetic field used in the experiment. Here, in this paper, we deliver the future possibilities for the lucid application of quantum computation and quantum machine learning in HEP, rather than focusing on deep mathematical structures of techniques arising in this domain.


2013 ◽  
Vol 28 (35) ◽  
pp. 1330032 ◽  
Author(s):  
ALBERTO ACCARDI

I discuss how global QCD fits of parton distribution functions (PDFs) can make the somewhat separated fields of high-energy particle physics and lower energy hadronic and nuclear physics interact to the benefit of both. I review specific examples of this interplay from recent works of the CTEQ-Jefferson Lab collaboration, including hadron structure at large parton momentum and gauge boson production at colliders. I devote particular attention to quantifying theoretical uncertainties arising in the treatment of large partonic momentum contributions to deep inelastic scattering (DIS) observables, and to discussing the experimental progress needed to reduce these.


1993 ◽  
Vol 04 (02) ◽  
pp. 95-108 ◽  
Author(s):  
AMIR A. HANDZEL ◽  
T. GROSSMAN ◽  
E. DOMANY ◽  
S. TAREM ◽  
E. DUCHOVNI

A classification problem in high energy physics has been solved on simulated data using a simple multilayer perceptron comprising binary units which was trained with the CHIR algorithm. The unstable training of such a network on a nonseparable set has been overcome by selecting those weight vectors with good performance while providing a flexible choice of the two types of classification errors. Specific features of the problem have been exploited in order to simplify and optimize the solution which has been compared to the popular backpropagation algorithm and found to perform on a similar level. Additional aspects of this work are the use of the CHIR algorithm on continuous input and incorporating the classic idea of a Φ-machine in a multilayer perceptron.


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