The recent discovery of gravitational-wave events has offered us unique test beds of gravity in the strong and dynamical field regime. One possible modification to General Relativity is the gravitational parity violation that arises naturally from quantum gravity. Such parity violation gives rise to the so-called amplitude birefringence in gravitational waves, in which one of the circularly polarized modes is amplified while the other one is suppressed during their propagation. In this paper, we study how well one can measure gravitational parity violation via the amplitude birefringence effect of gravitational waves sourced by stellar-mass black hole binaries. We choose Chern-Simons gravity as an example and work within an effective field theory formalism to ensure that the approximate theory is well posed. We consider gravitational waves from both individual sources and stochastic gravitational-wave backgrounds. Regarding bounds from individual sources, we estimate such bounds using a Fisher analysis and carry out Monte Carlo simulations by randomly distributing sources over their sky location and binary orientation. We find that the bounds on the scalar field evolution in Chern-Simons gravity from the recently discovered gravitational-wave events are too weak to satisfy the weak Chern-Simons approximation, while aLIGO with its design sensitivity can place meaningful bounds. Regarding bounds from stochastic gravitational-wave backgrounds, we set the threshold signal-to-noise ratio for detection of the parity-violation mode as 5 and estimate projected bounds with future detectors assuming that signals are consistent with no parity violation. In an ideal situation in which all the source parameters and binary black hole merger-rate history are known a priori, we find that a network of two third-generation detectors is able to place bounds that are comparable to or slightly stronger than binary pulsar bounds. In a more realistic situation in which one does not have
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Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.
Eigenstate-preserving multi-qubit parity measurements lie at the heart of stabilizer quantum error correction, which is a promising approach to mitigate the problem of decoherence in quantum computers. In this work we explore a high-fidelity, eigenstate-preserving parity readout for superconducting qubits dispersively coupled to a microwave resonator, where the parity bit is encoded in the amplitude of a coherent state of the resonator. Detecting photons emitted by the resonator via a current biased Josephson junction yields information about the parity bit. We analyze theoretically the measurement back action in the limit of a strongly coupled fast detector and show that in general such a parity measurement, while approximately quantum nondemolition is not eigenstate preserving. To remediate this shortcoming we propose a simple dynamical decoupling technique during photon detection, which greatly reduces decoherence within a given parity subspace. Furthermore, by applying a sequence of fast displacement operations interleaved with the dynamical decoupling pulses, the natural bias of this binary detector can be efficiently suppressed. Finally, we introduce the concept of a heralded parity measurement, where a detector click guarantees successful multi-qubit parity detection even for finite detection efficiency.
This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations. PMID:25421737
This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations. 2ff7e9595c
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