Final state effects on superfluid 4^{\bf 4}He in the deep inelastic regime

A study of Final State Effects (FSE) on the dynamic structure function of superfluid $^4$He in the Gersch--Rodriguez formalism is presented. The main ingredients needed in the calculation are the momentum distribution and the semidiagonal two--body density matrix. The influence of these ground state quantities on the FSE is analyzed. A variational form of $\rho_2$ is used, even though simpler forms turn out to give accurate results if properly chosen. Comparison to the experimental response at high momentum transfer is performed. The predicted response is quite sensitive to slight variations on the value of the condensate fraction, the best agreement with experiment being obtained with $n_0=0.082$. Sum rules of the FSE broadening function are also derived and commented. Finally, it is shown that Gersch--Rodriguez theory produces results as accurate as those coming from other more recent FSE theories.Comment: 20 pages, RevTex 3.0, 11 figures available upon request, to be appear in Phys. Rev.

vrAIn: a deep learning approach tailoring computing and radio resources in virtualized RANs

Proceeding of: 25th Annual International Conference on Mobile Computing and Networking (MobiCom'19), October 21-25, 2019, Los Cabos, Mexico.The virtualization of radio access networks (vRAN) is the last milestone in the NFV revolution. However, the complex dependencies between computing and radio resources make vRAN resource control particularly daunting. We present vrAIn, a dynamic resource controller for vRANs based on deep reinforcement learning. First, we use an autoencoder to project high-dimensional context data (traffic and signal quality patterns) into a latent representation. Then, we use a deep deterministic policy gradient (DDPG) algorithm based on an actor-critic neural network structure and a classifier to map (encoded) contexts into resource control decisions. We have implemented vrAIn using an open-source LTE stack over different platforms. Our results show that vrAIn successfully derives appropriate compute and radio control actions irrespective of the platform and context: (i) it provides savings in computational capacity of up to 30% over CPU-unaware methods; (ii) it improves the probability of meeting QoS targets by 25% over static allocation policies using similar CPU resources in average; (iii) upon CPU capacity shortage, it improves throughput performance by 25% over state-of-the-art schemes; and (iv) it performs close to optimal policies resulting from an offline oracle. To the best of our knowledge, this is the first work that thoroughly studies the computational behavior of vRANs, and the first approach to a model-free solution that does not need to assume any particular vRAN platform or system conditions.The work of University Carlos III of Madrid was supported by H2020 5GMoNArch project (grant agreement no. 761445) and H2020 5G-TOURS project (grant agreement no. 856950). The work of NEC Laboratories Europe was supported by H2020 5GTRANSFORMER project (grant agreement no. 761536) and 5GROWTH project (grant agreement no. 856709). The work of University of Cartagena was supported by Grant AEI/FEDER TEC2016-76465-C2-1-R (AIM) and Grant FPU14/03701.Publicad

Frustration induced Raman scattering in CuGeO_3

We present experimental data for the Raman intensity in the spin-Peierls compound CuGeO_3 and theoretical calculations from a one-dimensional frustrated spin model. The theory is based on (a) exact diagonalization and (b) a recently developed solitonic mean field theory. We find good agreement between the 1D-theory in the homogeneous phase and evidence for a novel dimerization of the Raman operator in the spin-Peierls state. Finally we present evidence for a coupling between the interchain exchange, the spin-Peierls order parameter and the magnetic excitations along the chains.Comment: Phys. Rev. B, Rapid Comm, in Pres

High-momentum dynamic structure function of liquid 3He-4He mixtures: a microscopic approach

The high-momentum dynamic structure function of liquid 3He-4He mixtures has been studied introducing final state effects. Corrections to the impulse approximation have been included using a generalized Gersch-Rodriguez theory that properly takes into account the Fermi statistics of 3He atoms. The microscopic inputs, as the momentum distributions and the two-body density matrices, correspond to a variational (fermi)-hypernetted chain calculation. The agreement with experimental data obtained at $q=23.1$ \AA$^{-1}$ is not completely satisfactory, the comparison being difficult due to inconsistencies present in the scattering measurements. The significant differences between the experimental determinations of the 4He condensate fraction and the 3He kinetic energy, and the theoretical results, still remain unsolved.Comment: 18 pages, 11 figures, to appear in Phys. Rev.

Critical role of endothelial Notch1 signaling in postnatal angiogenesis

Notch receptors are important mediators of cell fate during embryogenesis, but their role in adult physiology, particularly in postnatal angiogenesis, remains unknown. Of the Notch receptors, only Notch1 and Notch4 are expressed in vascular endothelial cells. Here we show that blood flow recovery and postnatal neovascularization in response to hindlimb ischemia in haploinsufficient global or endothelial-specific Notch1(+/-) mice, but not Notch4(-/-) mice, were impaired compared with wild-type mice. The expression of vascular endothelial growth factor (VEGF) in response to ischemia was comparable between wild-type and Notch mutant mice, suggesting that Notch1 is downstream of VEGF signaling. Treatment of endothelial cells with VEGF increases presenilin proteolytic processing, gamma-secretase activity, Notch1 cleavage, and Hes-1 (hairy enhancer of split homolog-1) expression, all of which were blocked by treating endothelial cells with inhibitors of phosphatidylinositol 3-kinase/protein kinase Akt or infecting endothelial cells with a dominant-negative Akt mutant. Indeed, inhibition of gamma-secretase activity leads to decreased angiogenesis and inhibits VEGF-induced endothelial cell proliferation, migration, and survival. Overexpression of the active Notch1 intercellular domain rescued the inhibitory effects of gamma-secretase inhibitors on VEGF-induced angiogenesis. These findings indicate that the phosphatidylinositol 3-kinase/Akt pathway mediates gamma-secretase and Notch1 activation by VEGF and that Notch1 is critical for VEGF-induced postnatal angiogenesis. These results suggest that Notch1 may be a novel therapeutic target for improving angiogenic response and blood flow recovery in ischemic limbs

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training

We study the recently introduced stability training as a general-purpose method to increase the robustness of deep neural networks against input perturbations. In particular, we explore its use as an alternative to data augmentation and validate its performance against a number of distortion types and transformations including adversarial examples. In our image classification experiments using ImageNet data stability training performs on a par or even outperforms data augmentation for specific transformations, while consistently offering improved robustness against a broader range of distortion strengths and types unseen during training, a considerably smaller hyperparameter dependence and less potentially negative side effects compared to data augmentation.Comment: 18 pages, 25 figures; Camera-ready versio

Calculating response functions in time domain with non-orthonormal basis sets

We extend the recently proposed order-N algorithms (cond-mat/9703224) for calculating linear- and nonlinear-response functions in time domain to the systems described by nonorthonormal basis sets.Comment: 4 pages, no figure