The Deflationary Bias of the ZLB and the FED’s Strategic Response

The paper shows, in a simple analytical framework, the existence of a deflationary bias in an economy with a low natural rate of interest, a Zero Lower Bound (ZLB) constraint on nominal interest rates and a discretionary Central Bank with an inflation mandate. The presence of the ZLB prevents the central bank from offsetting negative shocks to inflation whereas it can offset positive shocks. This asymmetry pushes average inflation below the target which in turn drags down inflation expectations and reinforces the likelihood of hitting the ZLB. We show that this deflationary bias is particularly relevant for a Central Bank with a symmetric dual mandate (i.e. minimizing deviations from inflation and employment), especially when facing demand shocks. But a strict inflation targeter cannot escape the suboptimal deflationary equilibrium either. The deflationary bias can be mitigated by targeting “shortfalls” instead of “deviations” from maximum employment and/or using flexible average inflation targeting. However, changing monetary policy strategy risks inflation expectations becoming entrenched above the target if the natural interest rate increases

Space-weighted seismic attenuation mapping of the aseismic source of Campi Flegrei 1983-84 unrest

Peer reviewedPublisher PD

Quasideterministic generation of maximally entangled states of two mesoscopic atomic ensembles by adiabatic quantum feedback

We introduce an efficient, quasideterministic scheme to generate maximally entangled states of two atomic ensembles. The scheme is based on quantum nondemolition measurements of total atomic populations and on adiabatic quantum feedback conditioned by the measurements outputs. The high efficiency of the scheme is tested and confirmed numerically for ideal photodetection as well as in the presence of losses.Comment: 7 pages, 6 figures, title changed, revised version published on Phys. Rev

Decoherence of number states in phase-sensitive reservoirs

The non-unitary evolution of initial number states in general Gaussian environments is solved analytically. Decoherence in the channels is quantified by determining explicitly the purity of the state at any time. The influence of the squeezing of the bath on decoherence is discussed. The behavior of coherent superpositions of number states is addressed as well.Comment: 5 pages, 2 figures, minor changes, references adde

Tunable non-Gaussian resources for continuous-variable quantum technologies

We introduce and discuss a set of tunable two-mode states of continuous-variable systems, as well as an efficient scheme for their experimental generation. This novel class of tunable entangled resources is defined by a general ansatz depending on two experimentally adjustable parameters. It is very ample and flexible as it encompasses Gaussian as well as non-Gaussian states. The latter include, among others, known states such as squeezed number states and de-Gaussified photon-added and photon-subtracted squeezed states, the latter being the most efficient non-Gaussian resources currently available in the laboratory. Moreover, it contains the classes of squeezed Bell states and even more general non-Gaussian resources that can be optimized according to the specific quantum technological task that needs to be realized. The proposed experimental scheme exploits linear optical operations and photon detections performed on a pair of uncorrelated two--mode Gaussian squeezed states. The desired non-Gaussian state is then realized via ancillary squeezing and conditioning. Two independent, freely tunable experimental parameters can be exploited to generate different states and to optimize the performance in implementing a given quantum protocol. As a concrete instance, we analyze in detail the performance of different states considered as resources for the realization of quantum teleportation in realistic conditions. For the fidelity of teleportation of an unknown coherent state, we show that the resources associated to the optimized parameters outperform, in a significant range of experimental values, both Gaussian twin beams and photon-subtracted squeezed states.Comment: 13 pages, 7 figure

Optimal estimation of losses at the ultimate quantum limit with non-Gaussian states

We address the estimation of the loss parameter of a bosonic channel probed by arbitrary signals. Unlike the optimal Gaussian probes, which can attain the ultimate bound on precision asymptotically either for very small or very large losses, we prove that Fock states at any fixed photon number saturate the bound unconditionally for any value of the loss. In the relevant regime of low-energy probes, we demonstrate that superpositions of the first low-lying Fock states yield an absolute improvement over any Gaussian probe. Such few-photon states can be recast quite generally as truncations of de-Gaussified photon-subtracted states.Comment: 4 pages, 3 figure

Global gyrokinetic simulations of ITG turbulence in the configuration space of the Wendelstein 7-X stellarator

We study the effect of turbulent transport in different magnetic configurations of the Weldenstein 7-X stellarator. In particular, we performed direct numerical simulations with the global gyrokinetic code GENE-3D, modeling the behavior of Ion Temperature Gradient turbulence in the Standard, High-Mirror, and Low-Mirror configurations of W7-X. We found that the Low-Mirror configuration produces more transport than both the High-Mirror and the Standard configurations. By comparison with radially local simulations, we have demonstrated the importance of performing global nonlinear simulations to predict the turbulent fluxes quantitatively

A Gaussian-Mixture based stochastic framework for the interpretation of spatial heterogeneity in multimodal fields

We provide theoretical formulations enabling characterization of spatial distributions of variables (such as, e.g., conductivity/permeability, porosity, vadose zone hydraulic parameters, and reaction rates) that are typical of hydrogeological and/or geochemical scenarios associated with randomly heterogeneous geomaterials and are organized on various scales of heterogeneity. Our approach and ensuing formulations embed the joint assessment of the probability distribution of a target variable and its associated spatial increments, DY, taken between locations separated by any given distance (or lag). The spatial distribution of Y is interpreted through a bimodal Gaussian mixture model. The modes of the latter correspond to an indicator random field which is in turn related to the occurrence of different processes and/or geomaterials within the domain of observation. The distribution of each component of the mixture is governed by a given length scale driving the strength of its spatial correlation. Our model embeds within a unique theoretical framework the main traits arising in a stochastic analysis of these systems. These include (i) a slight to moderate asymmetry in the distribution of Y and (ii) the occurrence of a dominant peak and secondary peaks in the distribution of DY whose importance changes with lag together with the moments of the distribution. This causes the probability distribution of increments to scale with lag in way that is consistent with observed experimental patterns. We analyze the main features of the modeling and parameter estimation framework through a set of synthetic scenarios. We then consider two experimental datasets associated with different processes and observation scales. We start with an original dataset comprising microscale reaction rate maps taken at various observation times. These are evaluated from AFM imaging of the surface of a calcite crystal in contact with a fluid and subject to dissolution. Such recent high resolution imaging techniques are key to enhance our knowledge of the processes driving the reaction. The second dataset is a well established collection of Darcy-scale air-permeability data acquired by Tidwell and Wilson (1999) [Water Resour Res, 35, 3375-3387] on a block of volcanic tuff through minipermeameters associated with various measurement scales

Exploring the links between cancer and placenta development

The development of metastatic cancer is a multistage process, which often requires decades to complete. Impairments in DNA damage control and DNA repair in cancer cell precursors generate genetically heterogeneous cell populations. However, despite heterogeneity most solid cancers have stereotypical behaviours, including invasiveness and suppression of immune responses that can be unleashed with immunotherapy targeting lymphocyte checkpoints. The mechanisms leading to the acquisition of stereotypical properties remain poorly understood. Reactivation of embryonic development processes in cells with unstable genomes might contribute to tumour expansion and metastasis formation. However, it is unclear whether these events are linked to immune response modulation. Tumours and embryos have non-self-components and need to avoid immune responses in their microenvironment. In mammalian embryos, neo-antigens are of paternal origin, while in tumour cells DNA mismatch repair and replication defects generate them. Inactivation of the maternal immune response towards the embryo, which occurs at the placental-maternal interface, is key to ensuring embryonic development. This regulation is accomplished by the trophoblast, which mimics several malignant cell features, including the ability to invade normal tissues and to avoid host immune responses, often adopting the same cancer immunoediting strategies. A better understanding as to whether and how genotoxic stress promotes cancer development through reactivation of programmes occurring during early stages of mammalian placentation could help to clarify resistance to drugs targeting immune checkpoint and DNA damage responses and to develop new therapeutic strategies to eradicate cancer