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The security and performance of blockchain systems such as Bitcoin critically rely on the P2P network. This paper aims to investigate blockchain P2P networks. We explore the topologies, peer discovery, and data forwarding and examine the security and performance of the P2P network. Further, we formulate an optimization problem to study the theoretical limit of the performance and provide a solution to achieve optimal performance in a blockchain P2P network.

Abstract We combine infrared absorption and Raman scattering spectroscopies to explore the properties of the heavy transition metal dichalcogenide 1T-HfS 2 . We employ the LO–TO splitting of the E u vibrational mode along with a reevaluation of mode mass, unit cell volume, and dielectric constant to reveal the Born effective charge. We find $${Z}_{{\rm{B}}}^{* }$$ Z B *  = 5.3 e , in excellent agreement with complementary first-principles calculations. In addition to resolving the controversy over the nature of chemical bonding in this system, we decompose Born charge into polarizability and local charge. We find α  = 5.07 Å 3 and Z *  = 5.2 e , respectively. Polar displacement-induced charge transfer from sulfur p to hafnium d is responsible for the enhanced Born charge compared to the nominal 4+ in hafnium. 1T-HfS 2 is thus an ionic crystal with strong and dynamic covalent effects. Taken together, our work places the vibrational properties of 1T-HfS 2 on a firm foundation and opens the door to understanding the properties of tubes and sheets.

Summary In this article we develop a method based on model-X knockoffs to find conditional associations that are consistent across environments, while controlling the false discovery rate. The motivation for this problem is that large datasets may contain numerous associations that are statistically significant and yet misleading, as they are induced by confounders or sampling imperfections. However, associations replicated under different conditions may be more interesting. In fact, sometimes consistency provably leads to valid causal inferences even if conditional associations do not. Although the proposed method is widely applicable, in this paper we highlight its relevance to genome-wide association studies, in which robustness across populations with diverse ancestries mitigates confounding due to unmeasured variants. The effectiveness of this approach is demonstrated by simulations and applications to UK Biobank data.

We present our experimental results on generating photon pairs entangled in a transverse-mode Bell state in few-mode optical fiber by controlling the transverse mode of the pump to selectively excite spontaneous four-wave mixing processes.

Surface segregation is a phenomenon that depends on the delicate interplay between thermodynamic driving forces and kinetic obstacles, for which elevated temperature is often needed to enhance the atom mobility and reach equilibrium. Using the classic system of Cu3Au(100) under the non-isothermal conditions, herein we show an adatom process underlying transient surface segregation dynamics through the temperaturechange-driven creation and annihilation of thermal vacancies in the bulk and the resulting bulk/surface mass exchanges. This is demonstrated by monitoring the surface composition evolution of Cu3Au(100) with temperature changes between 250 °C and 500 °C, showing that the increase in temperature decreases monotonically the surface Au concentration as a result of the transfer of more Cu than Au from the bulk to the surface to form Cu-rich clusters of adatoms. Such a bulk thermal defect effect is expected to be universal in inducing the disparity in the bulk/surface mass exchanges of dissimilar atoms in multicomponent materials because of the inherent differences in the vacancy formation energies of the constituent atoms.