Stochastic Wave-Function Simulation of Irreversible Emission Processes for Open Quantum Systems in a Non-Markovian Environment

When conducting the numerical simulation of quantum transport, the main obstacle is a rapid growth of the dimension of entangled Hilbert subspace. The Quantum Monte Carlo simulation techniques, while being capable of treating the problems of high dimension, are hindered by the so-called "sign problem". In the quantum transport, we have fundamental asymmetry between the processes of emission and absorption of environment excitations: the emitted excitations are rapidly and irreversibly scattered away. Whereas only a small part of these excitations is absorbed back by the open subsystem, thus exercising the non-Markovian self-action of the subsystem onto itself. We were able to devise a method for the exact simulation of the dominant quantum emission processes, while taking into account the small backaction effects in an approximate self-consistent way. Such an approach allows us to efficiently conduct simulations of real-time dynamics of small quantum subsystems immersed in non-Markovian bath for large times, reaching the quasistationary regime. As an example we calculate the spatial quench dynamics of Kondo cloud for a bozonized Kodno impurity model.Comment: 7 pages, 3 figures, ICQT2017 Conference Proceedings; corrected a few typos; accepted for publication in the AIP Conference Proceedings journa

Armenia’s trade performance in 1995-2002 and the effect of closed borders: a cross-country perspective

The paper deals with two issues. First, it focuses on the analysis of Armenia’s trade performance based on the utilization of standard statistical models and develops comparative estimates of this performance relative to the peer countries. The comparison is undertaken in terms of trade openness, diversification, and composition. The main finding is that Armenia has been lagging in its export development relative to most CIS countries. The recent improvements in exports helped somewhat to reduce the gap. The second part of the paper provides for re-estimation of the “costs of blockade” effect. Armenia’s trade under-performance cannot be explained in terms of distorted government policies, because Armenia is recognized as a reform leader in the CIS.Armenia, trade, costs of blockade, gravity model, trade openness

Changing trade patterns after conflict resolution in the South Caucasus

Since the breakup of the USSR, the South Caucasus region has experienced a range of political conflicts, resulting in a number of hot and cold wars and border closures. The author analyzes the probably short-term impacts of peace in the region as a result of a resolution of the conflict between Armenia and Azerbaijan over the Nagorney Karabakh region and an end to the associated trade blockades, with an emphasis on Armenia, Azerbaijan, and Georgia. The conflict has seriously distorted trade flows in the region, disrupted transport routes, and stifled export and import opportunities for Armenia and Azerbaijan. Georgia has enjoyed higher-than-normal transit through its territory. Trade has stopped in gas (from Azerbaijan to Armenia) and electricity (from Armenia to Turkey). Transport tariffs are unusually high, aggravated by government-imposed transit fees (taxes). Over time, trade restrictions have eased and trading partners have found ways to conduct trade despite closed borders and blockades--but at a cost. Applying a gravity model to regional trade, the author concludes that South Caucasus countries trade enough with the CIS countries and politically friendly neighbors, but too little with the European Union, the United States, and hostile neighbors. Lifting the blockades would alleviate trade distortions and bring about short-term improvements, including: 1) More rational trade flows; 2) A resumption of (or an increase in) regional trade in major commodities such as energy; and 3) Lower prices or higher profit margins (or both) on some important consumption and production goods. With peace, Armenia could more than double its exports if Azerbaijani and Turkish markets open, which could reduce Armenia's trade deficit by a third to a half and increase its GDP by 30 percent. Improving transport routes would produce immediate savings and relieve pressure on domestic prices, especially for energy. Azerbaijan could increase its exports by $100 million, or 11 percent of 1999 levels, reducing its trade deficit by a quarter and raising its GDP by 5 percent. Its exports and imports would benefit from transport savings. Transit through Georgia might decline, but probably not by more than a quarter of the freight service surplus.Economic Theory&Research,Common Carriers Industry,Environmental Economics&Policies,Trade Policy,Transport and Trade Logistics,TF054105-DONOR FUNDED OPERATION ADMINISTRATION FEE INCOME AND EXPENSE ACCOUNT,Economic Theory&Research,Environmental Economics&Policies,Trade Policy,Transport and Trade Logistics

Probing quantum chaos with the entropy of decoherent histories

Quantum chaos, a phenomenon that began to be studied in the last century, still does not have a rigorous understanding. By virtue of the correspondence principle, the properties of the system that lead to chaotic dynamics at the classical level must also be present in the underlying quantum system. In the classical case, the exponential divergence of nearby trajectories in time is described in terms of the Lyapunov exponent. However, in the quantum case, a similar description of chaos is strictly speaking impossible due to absence of trajectories. There are different approaches to remedy this situation, but the universal criterium of quantum chaos is absent. We propose the quantum chaos definition in the manner similar to classical one using decoherent histories as a quantum analog of trajectories. For this purpose we consider the model of open quantum kicked top interacting with environment, which is bosonic bath and illustrate this idea on it. Here environment plays the role of trajectory recording device. For kicked top model on classical level depending on the kick strength there is crossover between integrable and chaotic regimes. We show that for such a model the production of entropy of decoherent histories is radically different in the integrable and chaotic regimes. Thus, the entropy of an ensemble of quantum trajectories can be used as a signature of quantum chaos.Comment: 11 pages, 9 figure

Landscape-dynamic aspects of soil formation in the Lena River Delta

This article provides data on the study of pedodiversity and pecularities of soils and their spatial distribution in the territory of the Lena River Delta (Siberia, Russia). Special reference to geogenic factors of soil formation in the pedoenvironment are made. The main patterns of soil distribution in different geomorphic positions for Samoilovsky, Arga-Belir-Aryta, Kurungnakh and Hardang islands are discussed. The soil catenas of the 4 investigated islands are given as a reliable representation of the formation of soils and the development of soil-forming processes in various types of relief and geomorphological features. Soils are represented mainly by the following groups: Fluvisols, Umbrisols, Podzols, Cryosols, Histosols, Gleysols, which are closely related to the geomorphic terraces of the delta

Evaluation of stabilization rate of high and low molecular organic matter in cryoconite holes from the Arctic, Antarctic and Caucasus mountain ecosystems by 13C–NMR spectroscopy

Cryoconite holes are considered as a place of accumulation of organomineral matter, including black carbon. It is formed as a result of incomplete combustion of carboncontaining fragments of natural and anthropogenic origin. Such material is transported by the wind and participates in the formation of cryoconite on the ice surface. The accumulation of organic matter in cryoconite can significantly affect the climate of our planet. To assess the processes of resistance to biodegradation of organic matter in cryoconite, molecular methods of analysis were used. This work presents the qualitative and quantitative evaluation of composition of humic acids, formed in selected cryoconite holes of various geographical regions. To identify them, the 13C–NMR spectroscopy method was used, which makes it possible to reveal trends in the accumulation of specific structural fragments and the rate of stabilization of cryoconite organic matter. The analysis of the elemental composition revealed that the most condensed macromolecules of humic acids accumulate in cryoconite holes on Mount Elbrus. In the molecules of humic acids, the accumulation of aliphatic structural fragments up to 71-73% occurs to a greater extent, while the composition of the aliphatic fragments depended on local precursors of humification. In the Arctic and Antarctic ecosystems, humic acids with relatively homogeneous composition are formed. These ecosystems are characterized by the domination of moss-lichen communities, which are characterized by a predominance of lipids and carbohydrates in the chemical composition. Black carbon is an important part of the planetary carbon cycle. Under the conditions of active deglaciation, cryoconite material can enter the periglacial zone, and under the action of soil microorganisms, it can become an additional source of greenhouse gases in the atmosphere

Processing Images from Multiple IACTs in the TAIGA Experiment with Convolutional Neural Networks

Extensive air showers created by high-energy particles interacting with the Earth atmosphere can be detected using imaging atmospheric Cherenkov telescopes (IACTs). The IACT images can be analyzed to distinguish between the events caused by gamma rays and by hadrons and to infer the parameters of the event such as the energy of the primary particle. We use convolutional neural networks (CNNs) to analyze Monte Carlo-simulated images from the telescopes of the TAIGA experiment. The analysis includes selection of the images corresponding to the showers caused by gamma rays and estimating the energy of the gamma rays. We compare performance of the CNNs using images from a single telescope and the CNNs using images from two telescopes as inputs.Comment: In Proceedings of 5th International Workshop on Deep Learning in Computational Physics (DLCP2021), 28-29 June, 2021, Moscow, Russi