Long term experimental verification of a single chip quantum random number generator fabricated on the InP platform

This work presents the results from the experimental evaluation of a quantum random number generator circuit over a period of 300 minutes based on a single chip fabricated on the InP platform. The circuit layout contains a gain switched laser diode (LD), followed by a balanced Mach Zehnder Interferometer for proper light power distribution to the two arms of an unbalanced MZI incorporating a 65.4 mm long spiral waveguide that translates the random phase fluctuations to power variations. The LD was gain-switched at 1.3 GHz and the chip delivered a min-entropy of 0.5875 per bit after removal of the classical noise, resulting a total aggregate bit rate of 6.11 Gbps. The recoded data set successfully passed the 15-battery test NIST statistical test suite for all data sets.

Robustness of quantum reinforcement learning under hardware errors

Variational quantum machine learning algorithms have become the focus of recent research on how to utilize near-term quantum devices for machine learning tasks. They are considered suitable for this as the circuits that are run can be tailored to the device, and a big part of the computation is delegated to the classical optimizer. It has also been hypothesized that they may be more robust to hardware noise than conventional algorithms due to their hybrid nature. However, the effect of training quantum machine learning models under the influence of hardware-induced noise has not yet been extensively studied. In this work, we address this question for a specific type of learning, namely variational reinforcement learning, by studying its performance in the presence of various noise sources: shot noise, coherent and incoherent errors. We analytically and empirically investigate how the presence of noise during training and evaluation of variational quantum reinforcement learning algorithms affect the performance of the agents and robustness of the learned policies. Furthermore, we provide a method to reduce the number of measurements required to train Q-learning agents, using the inherent structure of the algorithm.

Polarization compensation method based on the wave plate group in phase mismatch for free-space quantum key distribution

Maintaining the polarization state in communication terminals is vital for polarization-encoding free-space quantum key distribution (QKD). Wave plate group phase mismatch caused by manufacturing errors, complex environmental effects, and the working wavelength deviation can reduce the polarization compensation effect. We found in theoretical analysis, that increasing phase mismatch of wave plates leads to the compensation method failure and reduces robustness. We propose a complementary polarization compensation method, which can effectively improve the robustness. Experimental results show that this method can improve the compensation effect by 50% at a slight phase mismatch, and realize a polarization extinction ratio exceeding 250:1 at the ergodic area even if the phase deviates to 0.27π. This method is beneficial to the high-stability design of free-space QKD systems and has the potential to be applied to QKD systems operating at multiple wavelengths.

Origin of the elements

What is the origin of the oxygen we breathe, the hydrogen and oxygen (in form of water H2O) in rivers and oceans, the carbon in all organic compounds, the silicon in electronic hardware, the calcium in our bones, the iron in steel, silver and gold in jewels, the rare earths utilized, e.g. in magnets or lasers, lead or lithium in batteries, and also of naturally occurring uranium and plutonium? The answer lies in the skies. Astrophysical environments from the Big Bang to stars and stellar explosions are the cauldrons where all these elements are made. The papers by Burbidge (Rev Mod Phys 29:547–650, 1957) and Cameron (Publ Astron Soc Pac 69:201, 1957), as well as precursors by Bethe, von Weizsäcker, Hoyle, Gamow, and Suess and Urey provided a very basic understanding of the nucleosynthesis processes responsible for their production, combined with nuclear physics input and required environment conditions such as temperature, density and the overall neutron/proton ratio in seed material. Since then a steady stream of nuclear experiments and nuclear structure theory, astrophysical models of the early universe as well as stars and stellar explosions in single and binary stellar systems has led to a deeper understanding. This involved improvements in stellar models, the composition of stellar wind ejecta, the mechanism of core-collapse supernovae as final fate of massive stars, and the transition (as a function of initial stellar mass) from core-collapse supernovae to hypernovae and long duration gamma-ray bursts (accompanied by the formation of a black hole) in case of single star progenitors. Binary stellar systems give rise to nova explosions, X-ray bursts, type Ia supernovae, neutron star, and neutron star–black hole mergers. All of these events (possibly with the exception of X-ray bursts) eject material with an abundance composition unique to the specific event and lead over time to the evolution of elemental (and isotopic) abundances in the galactic gas and their imprint on the next generation of stars. In the present review, we want to give a modern overview of the nucleosynthesis processes involved, their astrophysical sites, and their impact on the evolution of galaxies.

More simple, efficient and accurate food research promoted by intermolecular interaction approaches: A review

The investigation of intermolecular interactions has become increasingly important in many studies, mainly by combining different analytical approaches to reveal the molecular mechanisms behind specific experimental phenomena. From spectroscopic analysis to sophisticated molecular simulation techniques like molecular docking, molecular dynamics (MD) simulation, and quantum chemical calculations (QCC), the mechanisms of intermolecular interactions are gradually being characterized more clearly and accurately, leading to revolutionary advances. This article aims to review the progression in the main techniques involving intermolecular interactions in food research and the corresponding experimental results. Finally, we discuss the significant impact that cutting-edge molecular simulation technologies may have on the future of conducting deeper exploration. Applications of molecular simulation technology may revolutionize the food research, making it possible to design new future foods with precise nutrition and desired properties.

Unraveling the atomic-level vacancy modulation in Cu(9)S(5) for NIR-driven efficient inhibition of drug-resistant bacteria: Key role of Cu vacancy position

Cu₉S₅ possesses high hole concentration and potential superior electrical conductivity as a novel p-type semiconductor, whose biological applications remain largely unexploited. Encouraged by our recent work that Cu₉S₅ has enzyme-like antibacterial activity in the absence of light, which may further enhance the near infrared (NIR) antibacterial performance. Moreover, vacancy engineering can modulate the electronic structure of the nanomaterials and thus optimize their photocatalytic antibacterial activities. Here, we designed two different atomic arrangements with same V_CuSCu vacancies of Cu₉S₅ nanomaterials (CSC-4 and CSC-3) determined by positron annihilation lifetime spectroscopy (PALS). Aiming at CSC-4 and CSC-3 as a model system, for the first time, we investigated the key role of different copper (Cu) vacancies positions in vacancy engineering toward optimizing the photocatalytic antibacterial properties of the nanomaterials. Combined with the experimental and theoretical approach, CSC-3 exhibited stronger absorption energy of surface adsorbate (LPS and H₂O), longer lifetime of photogenerated charge carriers (4.29 ns), and lower reaction active energy (0.76 eV) than those of CSC-4, leading to the generation of abundant ·OH for attaining rapid drug-resistant bacteria killed and wound healed under NIR light irradiation. This work provided a novel insight for the effective inhibition of drug-resistant bacteria infection via vacancy engineering at the atomic-level modulation.

Exploring the structural, photophysical and optoelectronic properties of a diaryl heptanoid curcumin derivative and identification as a SARS-CoV-2 inhibitor

Developing modifiable natural products those having antiviral activities against SARS-CoV-2 is a key research area which is popular in current scenario of COVID pandemic. A diaryl heptanoid curcumin and its derivatives are already presenting promising candidates for anti-viral drug development. We have synthesized single crystals of a dimethylamino derivative of natural curcumin and structural characterization was done by single crystal XRD analysis. Using steady-state absorption and emission spectra and guided by complimentary ab initio calculations, we unraveled the solvent effects on the photophysical properties of the dimethyl amino curcumin derivative. Chemical reactivity of the compound has investigated using frontier molecular orbitals and molecular electrostatic potential surface. High stability of the curcumin derivative in water environment has evaluated by Radial Distributions Functions (RDF) calculated via Molecular Dynamics (MD) simulations. The inhibitory activity of the title compound was evaluated by in silico methods and the stability of the protein-ligand complexes were studied using Molecular Dynamics simulations and MM-PBSA analysis. With this detailed study, we hope to motivate scientific community to develop new curcumin derivatives against SARS-CoV-2 virus.