Hasil untuk "Physics"

R. A. Khalek, A. Accardi, J. Adam et al.

This report describes the physics case, the resulting detector requirements, and the evolving detector concepts for the experimental program at the Electron-Ion Collider (EIC). The EIC will be a powerful new high-luminosity facility in the United States with the capability to collide high-energy electron beams with high-energy proton and ion beams, providing access to those regions in the nucleon and nuclei where their structure is dominated by gluons. Moreover, polarized beams in the EIC will give unprecedented access to the spatial and spin structure of the proton, neutron, and light ions. The studies leading to this document were commissioned and organized by the EIC User Group with the objective of advancing the state and detail of the physics program and developing detector concepts that meet the emerging requirements in preparation for the realization of the EIC. The effort aims to provide the basis for further development of concepts for experimental equipment best suited for the science needs, including the importance of two complementary detectors and interaction regions. This report consists of three volumes. Volume I is an executive summary of our findings and developed concepts. In Volume II we describe studies of a wide range of physics measurements and the emerging requirements on detector acceptance and performance. Volume III discusses general-purpose detector concepts and the underlying technologies to meet the physics requirements. These considerations will form the basis for a world-class experimental program that aims to increase our understanding of the fundamental structure of all visible matter

Pankaj Mehta, M. Bukov, Ching-Hao Wang et al.

Machine Learning (ML) is one of the most exciting and dynamic areas of modern research and application. The purpose of this review is to provide an introduction to the core concepts and tools of machine learning in a manner easily understood and intuitive to physicists. The review begins by covering fundamental concepts in ML and modern statistics such as the bias-variance tradeoff, overfitting, regularization, generalization, and gradient descent before moving on to more advanced topics in both supervised and unsupervised learning. Topics covered in the review include ensemble models, deep learning and neural networks, clustering and data visualization, energy-based models (including MaxEnt models and Restricted Boltzmann Machines), and variational methods. Throughout, we emphasize the many natural connections between ML and statistical physics. A notable aspect of the review is the use of Python Jupyter notebooks to introduce modern ML/statistical packages to readers using physics-inspired datasets (the Ising Model and Monte-Carlo simulations of supersymmetric decays of proton-proton collisions). We conclude with an extended outlook discussing possible uses of machine learning for furthering our understanding of the physical world as well as open problems in ML where physicists may be able to contribute.

Sai Vinjanampathy, J. Anders

Quantum thermodynamics is an emerging research field aiming to extend standard thermodynamics and non-equilibrium statistical physics to ensembles of sizes well below the thermodynamic limit, in non-equilibrium situations and with the full inclusion of quantum effects. Fuelled by experimental advances and the potential of future nanoscale applications, this research effort is pursued by scientists with different backgrounds, including statistical physics, many-body theory, mesoscopic physics and quantum information theory, who bring various tools and methods to the field. A multitude of theoretical questions are being addressed ranging from issues of thermalisation of quantum systems and various definitions of ‘work’ to the efficiency and power of quantum engines. This overview provides a perspective on a selection of these current trends accessible to postgraduate students and researchers alike.

A.K. Geim, I. V. Grigorieva

Research on graphene and other two-dimensional atomic crystals is intense and is likely to remain one of the leading topics in condensed matter physics and materials science for many years. Looking beyond this field, isolated atomic planes can also be reassembled into designer heterostructures made layer by layer in a precisely chosen sequence. The first, already remarkably complex, such heterostructures (often referred to as ‘van der Waals’) have recently been fabricated and investigated, revealing unusual properties and new phenomena. Here we review this emerging research area and identify possible future directions. With steady improvement in fabrication techniques and using graphene’s springboard, van der Waals heterostructures should develop into a large field of their own.

M. Polanyi

R. Glowinski, J. Oden

Shang‐keng Ma

H. Griem

C. Rovelli, C. Rovelli

T. G. Pickavance

N. Fletcher, J. Hasted

R. Vanselow, R. Howe

S. I. Braginskii

Y. Choquet-bruhat, C. DeWitt-Morette, A. Wightman

Nicolas Page, Alireza Gholami, Qian Zhang

In response to the global challenge of climate change, financial institutions are increasingly called upon to assess and disclose their carbon emissions. Various global carbon quantification and reporting standards were developed, such as the Greenhouse Gas (GHG) Protocol, Task Force on Climate-related Financial Disclosures (TCFD), Partnership for Carbon Accounting Financials (PCAF) and others. Unfortunately, the now diverse landscape of standards increases the complexity for institutions seeking to develop voluntary carbon quantification and reporting. This study addresses the complexity issue by developing a criteria-based tool that summarizes the various components and requirements of the carbon standards. We propose eight criteria that summarize the standards’ key elements, requirements and relevance to the financial industry. We analyze seven major carbon quantification and reporting standards, systematically evaluating them against our tool. By doing so, we provide financial institutions with valuable insights in selecting appropriate standards to inform their emissions quantification and reporting decisions.

Isomiddin Nishonov, Javlon Rayimbaev, Saeed Ullah Khan et al.

Abstract Testing dark matter effects on gravity around black holes in the framework of gravity theories through observational data is an essential task of relativistic astrophysical studies. In this work, we first obtain a new spacetime solution for a black hole surrounded by perfect fluid dark matter (PFDM) in modified gravity (MOG). The MOG field is assumed to be a gravitational vector field. We investigate the vector fields with combined effects of PFDM on spacetime properties: event horizon radius, scalar invariants such as the Ricci scalar, the square of the Ricci tensor, and Kretchman scalars. We investigate the circular motion of test particles in the spacetime of the black hole, taking into account the MOG field interaction on the particle geodesics. The energy and angular momentum of the particles corresponding to circular orbits are studied. In addition, we explore how the PFDM and MOG fields change the position of innermost stable circular orbits (ISCOs) and their corresponding energy and angular momentum values. Moreover, we study the energy efficiency rate around the black hole in the Novikov and Thorns thin accretion disc model. We analyze collisional cases of the particles near the black hole and study the effects of the fields on the critical angular momentum in which particles can collide near the black hole and the center-of-mass energy of the colliding particles.

Bakul Akter, Silvia Aishee, Abdullah Hridoy et al.

Etoricoxib (ETC), a selective cyclooxygenase enzyme (COX-2) inhibitor, is widely utilized to manage pain and inflammation. Nevertheless, its therapeutic efficacy is limited by poor aqueous solubility, low bioavailability, and significant cardiovascular risks, including increased blood pressure, thrombosis, and the potential for myocardial infarction. This study aimed to address these limitations through structural modifications of etoricoxib. A total of 21 derivatives were designed by introducing various functioning sets at the R3, R2, and R1 sites of ETC. Quantum chemical calculations were performed to assess alterations in physicochemical properties, such as HOMO–LUMO energy gaps, electrostatic potential, enthalpy, and dipole moments. Notably, most of the derivatives showed improved binding affinities, particularly ETC9 and ETC19, demonstrating the highest binding interactions in molecular docking studies (-10.1 and -10.8 kcal/mol, respectively). Furthermore, molecular dynamics (MD) simulations accomplished by exploiting the YASARA dynamics software program with the AMBER14 energy field throughout 100 ns revealed that the ETC9 and ETC19 derivatives exhibited enhanced stability and flexibility profiles compared to the parent drug, ETC. ADMET and PASS predictions confirmed the drug-like properties of most derivatives, particularly ETC19 and ETC9, which also showed improved absorption, better blood-brain barrier penetration, and reduced toxicity. These outcomes underscore the prospect of the de novo-designed etoricoxib analogues as safer and more effective alternatives, effectively addressing the pharmacological limitations and safety concerns associated with the parent drug.

Peter A. Bennett

At Arizona State University we have built the first and only fully online Bachelor of Science degree in Physics, with a complete curriculum, including labs. The upper division Advanced Lab courses present a special challenge for online delivery. We address that using a set of custom-built simulator modules that replicate all the imperfections (noise, background, etc) inherent in real-world data. The set of experiments duplicates those of the in-person classes. In this paper, we present an overview of these labs and discuss the advantages and challenges of delivering them online. We assert that these labs provide a valid and rigorous component for the fully online degree. The entire set of labs is available as Open Source Supplemental Materials and is shared for others to use in part or in whole, with suitable attribution.

Joel Wagner, Siew Ann Cheong, Viola Priesemann

Asset exchange models (AEMs) provide a physics-inspired framework for studying wealth formation. These models capture wealth distribution dynamics via pairwise money exchanges, yielding steady-state distributions from exponential to heavy-tailed power laws. However, empirical validation remains limited due to scarce real-world transaction data. Here, we bridge this gap by analyzing spectral properties of Markov transition matrices from both AEMs and Ethereum blockchain data, enabling quantitative comparison of model and empirical exchange dynamics. We assess thermodynamic equilibrium in exchange processes - specifically, detailed balance - and derive steady-state wealth distributions from transition matrices. We find that equilibrium systems' spectra contain only real eigenvalues and link Ethereum price changes to spectral shifts. We also investigate external factors (e.g., taxes), showing that advantages for richer individuals make wealth evolution path-dependent on initial distributions. Our work establishes a quantitative framework for validating AEMs with real data, advancing economic modeling and understanding of wealth formation.

J. Larkin, J. McDermott, Dorothea P. Simon et al.