Non-equilibrium thermodynamics of quantum bipartite system

In quantum information and quantum computation, a bipartite system provides a basic few-body framework for investigating significant properties of thermodynamics and statistical mechanics. A Hamiltonian model for a bipartite system is introduced to analyze the important role of interaction between bipartite subsystems in quantum non-equilibrium thermodynamics. We illustrate discrimination between such quantum thermodynamics and classical few-body non-equilibrium thermodynamics. By proposing a detailed balance condition of the bipartite system, we generally investigate the properties of the entropy and heat of our model, as well as the relation between them.

Constrained dynamics of maximally entangled bipartite system

The classical and quantum dynamics of two particles constrained on $$S^1$$ S 1 is discussed via Dirac’s approach. We show that when state is maximally entangled between two subsystems, the product of dispersion in the measurement reduces. We also quantify the upper bound on the external field $$\vec {B}$$ B → such that $$\vec {B}\ge \vec {B}_{upper }$$ B → ≥ B → upper implies no reduction in the product of dispersion pertaining to one subsystem. Further, we report on the cut-off value of the external field $$\vec {B}_{cutoff }$$ B → cutoff , above which the bipartite entanglement is lost and there exists a direct relationship between uncertainty of the composite system and the external field. We note that, in this framework it is possible to tune the external field for entanglement/unentanglement of a bipartite system. Finally, we show that the additional terms arising in the quantum Hamiltonian, due to the requirement of Hermiticity of operators, produce a shift in the energy of the system.

Measuring countries' progress in sustainable development through network theory

<p>The Agenda 2030 of sustainable development introduced in 2015 by the United Nations is a call for action to address the major challenges the world faces [1]. To tackle these challenges, the Agenda defines the 17 Sustainable Development Goals (SDGs), which have been conceived with respect to five pillars (planet, people, prosperity, peace and partnership), thus creating synergies and trade-offs among the Goals. The Agenda also addresses the need for more targeted policy implementations, totaling 169 targets across the Goals. Moreover, indicators have been defined to measure progresses in each target, and so, Goal.</p><p>To create aggregated scores of such countries’ performance indicators is a recurrent and crucial issue within the SDGs framework, where several methodologies have been proposed to create a ranking of countries which can provide insights about the fulfillment of all of the Agenda’s objectives and principles (see, e.g., Sachs et. al. [2] and Biggeri et al. [3]). In light of the complex nature of the Agenda (as pointed out by LeBlanc [4]), we argue that the use of multidisciplinary tools is essential to help shed light on how to address efforts in global sustainable development. In particular, network theory can be used to create several aggregated scores that can actually account for the complex nature of the Agenda, the synergies and trade-offs among the Goals and, no less, of the role of countries toward the achievement of SDGs.</p><p>In this work, we recast the data concerning the performances of countries in each Goal’s indicators as the incidence matrix of a bipartite system constituted of two sets: countries and Goals, connected by the performances of countries within each Goal. We exemplify our framework using the data taken from the 2020 SDG Index and Dashboard by Sachs et al. [2]. We show that, framed within network science, the SDG Index coincides with measuring the degree centrality of countries within this bipartite system and that such measure neglects the heterogeneity of countries in tackling the Goals and their responsibilities at the global scale. More informative centrality measures, and so, aggregated scores, can be obtained by the adoption of the economic complexity theory, in particular, the GENEPY framework [5]. The GENEPY rationale defines a data-driven weighting scheme in which relative countries’ performances of all SDGs are considered to define a more comprehensive ranking of countries.</p><p>References:</p><p>[1] Transforming our world: the 2030 Agenda for Sustainable Development. Division for Sustainable Development Goals: New York, NY, USA, 2015.</p><p>[2] Sachs, J., et al. . 2020. The Sustainable Development Goals and COVID-19. Sustainable Development Report 2020. Cambridge: Cambridge University Press.</p><p>[3] Biggeri, M., et al. (2019). Tracking the SDGs in an ‘integrated’ manner: A proposal for a new index to capture synergies and trade-offs between and within goals. World Development, 122, 628-647.</p><p>[4] Le Blanc, D. (2015). Towards integration at last? The sustainable development goals as a network of targets. Sustainable Development, 23(3), 176-187.</p><p>[5] Sciarra, C., et al. (2020). Reconciling contrasting views on economic complexity. Nature Communications, 11(1), 1-10.</p>

Ideological conflicts between Bolsheviks and Left Social Revolutionaries in the regional government branches

This article examines the interaction between the representatives of Bolsheviks and Left Social Revolutionaries in the regional government branches during the first half of 1918. The subject of this research is the ideological conflicts that emerged between the members of the Communist Party of the Soviet Union and the Left Social Revolutionaries in their joint activity. Considerable attention is given to classification of the ideological conflicts, as well as to identification of their causes and consequences for interaction of the representatives of both parties on the local level. These conflicts were an integral part of the Soviet bipartite system. Their manifestation began since dissolution of the government coalition of Bolsheviks and Left Social Revolutionaries. Based on the analysis of archival documents and published sources, the author describes the interaction between Bolsheviks and Left Social Revolutionaries in the local soviets. The novelty consists in classification of the conflicts between Bolsheviks and Left Social Revolutionaries, as well as in introduction into the scientific discourse of certain archival documents. The conclusion is made that despite the joint activity of the two parties aimed at strengthening of the Soviet regime, the ideological conflicts demonstrated a different perspective of Bolsheviks and Left Social Revolutionaries upon the political course of the country, as well as the methods of local governance. The escalating antagonism between the two Soviet parties eventually led to instability in the bipartite system and its collapse.

Wave–Particle–Entanglement–Ignorance Complementarity for General Bipartite Systems

Wave–particle duality as the defining characteristic of quantum objects is a typical example of the principle of complementarity. The wave–particle–entanglement (WPE) complementarity, initially developed for two-qubit systems, is an extended form of complementarity that combines wave–particle duality with a previously missing ingredient, quantum entanglement. For two-qubit systems in mixed states, the WPE complementarity was further completed by adding yet another piece that characterizes ignorance, forming the wave–particle–entanglement–ignorance (WPEI) complementarity. A general formulation of the WPEI complementarity can not only shed new light on fundamental problems in quantum mechanics, but can also have a wide range of experimental and practical applications in quantum-mechanical settings. The purpose of this study is to establish the WPEI complementarity for general multi-dimensional bipartite systems in pure or mixed states, and extend its range of applications to incorporate hierarchical and infinite-dimensional bipartite systems. The general formulation is facilitated by well-motivated generalizations of the relevant quantities. When faced with different directions of extensions to take, our guiding principle is that the formulated complementarity should be as simple and powerful as possible. We find that the generalized form of the WPEI complementarity contains unequal-weight averages reflecting the difference in the subsystem dimensions, and that the tangle, instead of the squared concurrence, serves as a more suitable entanglement measure in the general scenario. Two examples, a finite-dimensional bipartite system in mixed states and an infinite-dimensional bipartite system in pure states, are studied in detail to illustrate the general formalism. We also discuss our results in connection with some previous work. The WPEI complementarity for general finite-dimensional bipartite systems may be tested in multi-beam interference experiments, while the second example we studied may facilitate future experimental investigations on complementarity in infinite-dimensional bipartite systems.

Extraction of Work via a Thermalization Protocol

This extended abstract contains an outline of the work reported at the conference IQIS2018. We show that it is possible to exploit a thermalization process to extract work from a resource system R to a bipartite system S. To do this, we propose a simple protocol in a general setting in the presence of a single bath at temperature T and then examine it when S is described by the quantum Rabi model at T = 0 . We find the theoretical bounds of the protocol in the general case and we show that when applied to the Rabi model it gives rise to a satisfactory extraction of work and efficiency.