Gravitational ultrarelativistic interaction of classical particles in the context of unification of interactions

The response of the ultrarelativistic particle with spin in a Schwarzschild field to the gravitomagnetic components as measured by the comoving observer is investigated. The dependence of the particle's spin-orbit acceleration on the Lorentz \gamma - factor and the spin orientation is studied. The concrete circular ultrarelativistic orbit of radius r=3m is considered as a partial solution of the Mathisson-Papapetrou equations and as the corresponding high-energy quantum state of the Dirac particle. Numerical estimates for protons and electrons near black holes are given. A tendency of gravitational and electromagnetic interactions to approach in quantitative terms at ultrarelativistic velocities is discussedComment: 16 page

Quasifree Knockout Of Deuterons In The ⁶Li(α,αd)⁴He Reaction At 23.6 MeV

α−d correlations in quasi-elastic scattering of 23.6-MeV α particles on the deuteron cluster of the ⁶Li target were measured in and off the principal reaction plane. Despite the low c.m. energy of 14.2 MeV, the impulse approximation provides a reasonable description of the quasifree process. Computations were based on the asymptotic α−d S-state wave function and on the cluster-model wave function of ⁶Li. Insensitivity of the fits to the details of the ⁶Li cluster-model wave function indicates an extreme surface reaction mechanism. The full width at half-maximum of the spectator momentum distribution was found to be 48±6 MeV/c. By comparing the experimental cross section for the quasifree process at the maximum of the angular correlation ((d2σ/dΩddΩ)=68±9 mb/sr² at θ=25°,θ(d)=45°) with the corresponding cross section for the free process, the probability of finding ⁶Li as an α−d cluster was evaluated

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding

Learning long-term dependencies in extended temporal sequences requires credit assignment to events far back in the past. The most common method for training recurrent neural networks, back-propagation through time (BPTT), requires credit information to be propagated backwards through every single step of the forward computation, potentially over thousands or millions of time steps. This becomes computationally expensive or even infeasible when used with long sequences. Importantly, biological brains are unlikely to perform such detailed reverse replay over very long sequences of internal states (consider days, months, or years.) However, humans are often reminded of past memories or mental states which are associated with the current mental state. We consider the hypothesis that such memory associations between past and present could be used for credit assignment through arbitrarily long sequences, propagating the credit assigned to the current state to the associated past state. Based on this principle, we study a novel algorithm which only back-propagates through a few of these temporal skip connections, realized by a learned attention mechanism that associates current states with relevant past states. We demonstrate in experiments that our method matches or outperforms regular BPTT and truncated BPTT in tasks involving particularly long-term dependencies, but without requiring the biologically implausible backward replay through the whole history of states. Additionally, we demonstrate that the proposed method transfers to longer sequences significantly better than LSTMs trained with BPTT and LSTMs trained with full self-attention.Comment: To appear as a Spotlight presentation at NIPS 201

Deep Complex Networks

At present, the vast majority of building blocks, techniques, and architectures for deep learning are based on real-valued operations and representations. However, recent work on recurrent neural networks and older fundamental theoretical analysis suggests that complex numbers could have a richer representational capacity and could also facilitate noise-robust memory retrieval mechanisms. Despite their attractive properties and potential for opening up entirely new neural architectures, complex-valued deep neural networks have been marginalized due to the absence of the building blocks required to design such models. In this work, we provide the key atomic components for complex-valued deep neural networks and apply them to convolutional feed-forward networks and convolutional LSTMs. More precisely, we rely on complex convolutions and present algorithms for complex batch-normalization, complex weight initialization strategies for complex-valued neural nets and we use them in experiments with end-to-end training schemes. We demonstrate that such complex-valued models are competitive with their real-valued counterparts. We test deep complex models on several computer vision tasks, on music transcription using the MusicNet dataset and on Speech Spectrum Prediction using the TIMIT dataset. We achieve state-of-the-art performance on these audio-related tasks

Localizability of Tachyonic Particles and Neutrinoless Double Beta Decay

The quantum field theory of superluminal (tachyonic) particles is plagued with a number of problems, which include the Lorentz non-invariance of the vacuum state, the ambiguous separation of the field operator into creation and annihilation operators under Lorentz transformations, and the necessity of a complex reinterpretation principle for quantum processes. Another unsolved question concerns the treatment of subluminal components of a tachyonic wave packets in the field-theoretical formalism, and the calculation of the time-ordered propagator. After a brief discussion on related problems, we conclude that rather painful choices have to be made in order to incorporate tachyonic spin-1/2 particles into field theory. We argue that the field theory needs to be formulated such as to allow for localizable tachyonic particles, even if that means that a slight unitarity violation is introduced into the S matrix, and we write down field operators with unrestricted momenta. We find that once these choices have been made, the propagator for the neutrino field can be given in a compact form, and the left-handedness of the neutrino as well as the right-handedness of the antineutrino follow naturally. Consequences for neutrinoless double beta decay and superluminal propagation of neutrinos are briefly discussed.Comment: 12 pages, 5 figure

Neutrino Mass^2 Inferred from the Cosmic Ray Spectrum and Tritium Beta Decay

An earlier prediction of a cosmic ray neutron line right at the energy of the knee of the cosmic ray spectrum was based on the speculation that the electron neutrino is a tachyon whose mass is reciprocally related to the energy of the knee, $E_k$. Given the large uncertainty in $E_k$, the values of ${m_\nu}^2$ corresponding to it are consistent with values recently reported in tritium beta decay experiments.Comment: Published as Phys. Lett. B 493 (2000) 1-

Superluminal Signals: Causal Loop Paradoxes Revisited

Recent results demonstrating superluminal group velocities and tachyonic dispersion relations reopen the question of superluminal signals and causal loop paradoxes. The sense in which superluminal signals are permitted is explained in terms of pulse reshaping, and the self-consistent behavior which prevents causal loop paradoxes is illustrated by an explicit example.Comment: 6 pages, 3 figure

Gravitational and electromagnetic fields of a charged tachyon

An axially symmetric exact solution of the Einstein-Maxwell equations is obtained and is interpreted to give the gravitational and electromagnetic fields of a charged tachyon. Switching off the charge parameter yields the solution for the uncharged tachyon which was earlier obtained by Vaidya. The null surfaces for the charged tachyon are discussed.Comment: 8 pages, LaTex, To appear in Pramana- J. Physic