Gravitational-Wave Implications for the Parity Symmetry of Gravity at GeV Scale

Gravitational waves generated by the coalescence of compact binary open a new window to test the fundamental properties of gravity in the strong-field and dynamical regime. In this work, we focus on the parity symmetry of gravity which, if broken, can leave imprints on the waveform of gravitational wave. We construct generalized waveforms with amplitude and velocity birefringence due to parity violation in the effect field theory formalism, then analyze the open data of the ten binary black-hole merger events and the two binary neutron-star merger events detected by LIGO and Virgo collaboration. We do not find any signatures of violation of gravitational parity conservation, thereby setting the lower bound of the parity-violating energy scale to be $0.07$ GeV. This presents the first observational evidence of the parity conservation of gravity at high energy scale, about 17 orders of magnitude tighter than the constraints from the Solar system tests and binary pulsar observation. The third-generation gravitational-wave detector is capable of probing the parity-violating energy scale at $\mathcal{O}(10^2)$ GeV

Energy-Delay Tradeoffs of Virtual Base Stations With a Computational-Resource-Aware Energy Consumption Model

The next generation (5G) cellular network faces the challenges of efficiency, flexibility, and sustainability to support data traffic in the mobile Internet era. To tackle these challenges, cloud-based cellular architectures have been proposed where virtual base stations (VBSs) play a key role. VBSs bring further energy savings but also demands a new energy consumption model as well as the optimization of computational resources. This paper studies the energy-delay tradeoffs of VBSs with delay tolerant traffic. We propose a computational-resource-aware energy consumption model to capture the total energy consumption of a VBS and reflect the dynamic allocation of computational resources including the number of CPU cores and the CPU speed. Based on the model, we analyze the energy-delay tradeoffs of a VBS considering BS sleeping and state switching cost to minimize the weighted sum of power consumption and average delay. We derive the explicit form of the optimal data transmission rate and find the condition under which the energy optimal rate exists and is unique. Opportunities to reduce the average delay and achieve energy savings simultaneously are observed. We further propose an efficient algorithm to jointly optimize the data rate and the number of CPU cores. Numerical results validate our theoretical analyses and under a typical simulation setting we find more than 60% energy savings can be achieved by VBSs compared with conventional base stations under the EARTH model, which demonstrates the great potential of VBSs in 5G cellular systems.Comment: 5 pages, 3 figures, accepted by ICCS'1