Tensionless Strings from Worldsheet Symmetries

We revisit the construction of the tensionless limit of closed bosonic string theory in the covariant formulation in the light of Galilean conformal symmetry that rises as the residual gauge symmetry on the tensionless worldsheet. We relate the analysis of the fundamentally tensionless theory to the tensionless limit that is viewed as a contraction of worldsheet coordinates. Analysis of the quantum regime uncovers interesting physics. The degrees of freedom that appear in the tensionless string are fundamentally different from the usual string states. Through a Bogoliubov transformation on the worldsheet, we link the tensionless vacuum to the usual tensile vacuum. As an application, we show that our analysis can be used to understand physics of strings at very high temperatures and propose that these new degrees of freedom are naturally connected with the long-string picture of the Hagedorn phase of free string theory. We also show that tensionless closed strings behave like open strings.Comment: 40 pages; v2: references added, minor text edit

Tensionless Superstrings: View from the Worldsheet

In this brief note, we show that the residual symmetries that arise in the analysis of the tensionless superstrings in the equivalent of the conformal gauge is (a trivial extension of) the recently discovered 3d Super Bondi-Metzner-Sachs algebra, discussed in the context of asymptotic symmetries of 3d Supergravity in flat-spacetimes. This helps us uncover a limiting approach to the construction of the tensionless superstring from the point of view of the worldsheet, analogous to the one we had adopted earlier for the closed tensionless bosonic string.Comment: 23 page

Inhomogeneous Tensionless Superstrings

We construct a novel tensionless limit of Superstring theory that realises the Inhomogeneous Super Galilean Conformal Algebra (SGCA$_I$) as the residual symmetries in the analogue of the conformal gauge, as opposed to previous constructions of the tensionless superstring, where a smaller symmetry algebra called the Homogeneous SGCA emerged as the residual gauge symmetry on the worldsheet. We obtain various features of the new tensionless theory intrinsically as well as from a systematic limit of the corresponding features of the tensile theory. We discuss why it is desirable and also natural to work with this new tensionless limit and the larger algebra.Comment: 34 page

DRIVE: A Digital Network Oracle for Cooperative Intelligent Transportation Systems

In a world where Artificial Intelligence revolutionizes inference, prediction and decision-making tasks, Digital Twins emerge as game-changing tools. A case in point is the development and optimization of Cooperative Intelligent Transportation Systems (C-ITSs): a confluence of cyber-physical digital infrastructure and (semi)automated mobility. Herein we introduce Digital Twin for self-dRiving Intelligent VEhicles (DRIVE). The developed framework tackles shortcomings of traditional vehicular and network simulators. It provides a flexible, modular, and scalable implementation to ensure large-scale, city-wide experimentation with a moderate computational cost. The defining feature of our Digital Twin is a unique architecture allowing for submission of sequential queries, to which the Digital Twin provides instantaneous responses with the "state of the world", and hence is an Oracle. With such bidirectional interaction with external intelligent agents and realistic mobility traces, DRIVE provides the environment for development, training and optimization of Machine Learning based C-ITS solutions.Comment: Accepted for publication at IEEE ISCC 202

RLOps:Development Life-cycle of Reinforcement Learning Aided Open RAN

Radio access network (RAN) technologies continue to witness massive growth, with Open RAN gaining the most recent momentum. In the O-RAN specifications, the RAN intelligent controller (RIC) serves as an automation host. This article introduces principles for machine learning (ML), in particular, reinforcement learning (RL) relevant for the O-RAN stack. Furthermore, we review state-of-the-art research in wireless networks and cast it onto the RAN framework and the hierarchy of the O-RAN architecture. We provide a taxonomy of the challenges faced by ML/RL models throughout the development life-cycle: from the system specification to production deployment (data acquisition, model design, testing and management, etc.). To address the challenges, we integrate a set of existing MLOps principles with unique characteristics when RL agents are considered. This paper discusses a systematic life-cycle model development, testing and validation pipeline, termed: RLOps. We discuss all fundamental parts of RLOps, which include: model specification, development and distillation, production environment serving, operations monitoring, safety/security and data engineering platform. Based on these principles, we propose the best practices for RLOps to achieve an automated and reproducible model development process.Comment: 17 pages, 6 figrue

Industry-Academia Research toward Future Network Intelligence:The NG-CDI Prosperity Partnership

Ever since the first automation provided by the introduction of the Strowger telephone exchange in the late 19th century, networks have been increas- ingly automated. Fast forward to 2022, and the challenge facing network providers is scaling up this level of automation considering massive increases in complexity, new levels of agility to operate ser- vices, and rising demand from customers within the modern telecommunications ecosystem. This article describes a significant new industry-academia part- nership to address these challenges: Next Gener- ation Converged Digital Infrastructure (NG-CDI) is creating a vision for the building and operation of a future-proof network infrastructure and its autonomic management. In this article, we high- light three exemplar activities within the NG-CDI research program that illustrate the benefits of tak- ing a highly collaborative interdisciplinary approach and show how academia and industry working closely together have delivered a range of direct and positive impacts on business