Swapping Networks Research Articles

Application and Challenges of Battery Swapping Technology in the Development of New Energy Vehicle

Abstract: With the rapid growth of the new energy vehicle market, the construction of battery swapping stations has become an effective solution to the problem of insufficient charging facilities. Battery swapping technology can improve energy replenishment efficiency, alleviate pressure on the power grid, reduce charging costs through overnight charging, and increase battery utilization and profitability. However, battery swapping technology faces issues such as standardization, high costs, technical and safety challenges, and low market acceptance. It is suggested to promote standardization, government policy support, technological innovation and safety enhancement, the construction of a widespread battery swapping network, as well as innovation in business models and market promotion to promote the development of battery swapping technology.

Financial development and central bank bilateral currency swaps: Is there trade effect?

Purpose ― This paper aims to empirically investigate the impact of currency swaps on international trade, given China's differential level of financial development and its currency swap partners. Methods ― The study employes an empirical structural gravity model using datasets encompassing financial development, trade, and intuitive gravity equation variables for 27 countries from 1980 to 2013. The level of financial development and swaps was captured by the interaction term of the disaggregated measure of financial development, such as access, depth, and efficiency, each interacting with currency swaps.Findings ― The findings suggest that currency swaps are essential for trade and exhibit a large trade effect, especially for countries with relatively low levels of financial development. The paper substantiates empirical evidence indicating disparities in financial development across countries, and such differences are important in determining trade patterns. Implication ― Strong financial systems promote trade in advanced economies, whereas the opposite holds true for developing countries. The examination of the influence of financial systems on trade through empirical tests remains important on the research agenda of policymakers and researchers, especially those looking at industry-level import and export data.Originality ― The study delves into the nexus between financial development and trade within the framework of the Central Bank bilateral currency swap network by highlighting the role of financial institutions and market size (depth), activity (access), and efficiency. In addition, it addresses the drawbacks of previous empirical research that largely focuses on the private credit-to-GDP ratio as a key proxy for financial development.

Central bank swaps and foreign reserves: From the perspective of a global network

Central bank swaps have flourished since the 2008 financial crisis and the intertwining swap lines have formed a typically complex network, in which bilateral swap relationships have been deeply embedded. This paper constructs a global swap network of central banks and then utilises network indices to measure the network positions and resources of swap central banks. From the perspective of the global swap network, it employs the Spatial Durbin Model to empirically estimate both direct and indirect effects of swap positions on foreign reserves and then further explores the applicability of these effects. The findings confirm a negative impact of network positions on foreign reserves. Besides, swaps can significantly substitute for foreign reserves of relevant banks by back-up rescue and demonstration mechanisms. The fact that spatial spill-over effects are much larger than direct effects justifies the necessity to assess swap performance from a spatial perspective. Applicability tests show that the substitution effect is larger in less developed countries and those with lower foreign exchange stability and financial openness. The conclusions have important policy implications for the construction of a global financial safety net and the coordination of counter-measures to cope with crises.

Central Bankers in Crisis: Interpersonal Trust, Cooperation, and the Creation of the Fed Swap Network during the 2008 Global Financial Crisis

Abstract How do policymakers respond to global crises? I argue that interpersonal trust enables policymakers to engage in ad hoc cooperation, in conditions of crisis and uncertainty. Leaders’ differentiated ties by degree—of stronger, looser, or absent—interpersonal trust influenced economies’ access to Federal Reserve swap lines over costlier unilateral and multilateral alternatives during the 2008 Global Financial Crisis. Using this framework, I re-examine the emergence of the Fed swap network. I triangulate evidence from elite interviews with central bankers in office during the crisis, and transcripts of Fed meetings. My findings highlight the role of interpersonal trust as an operating variable in shaping patterns of international cooperation and problematize the politics of technocratic governance. While necessary and successful, these crisis management policies reinforce global hierarchies and exacerbate the democratic deficit in central banking. This article thus draws attention to the contentious and undemocratic foundations of the global financial safety net.

Optimising product swaps in an urban retail network with uncertainty

City Logistics aims to achieve higher levels of consolidation in vehicles that typically requires exchanging loads at intermediate locations. Swapping goods between retail stores in urban areas due to stock shortages is a common problem arising in for example, omni-channel logistics. This study develops a two-stage stochastic program for designing a product swap network. The upper stage of the program deals with the strategic decision of locating transhipment nodes, while the lower stage finds the optimal operational vehicle routing solution. Uncertainties in demand, traffic conditions, and vehicle loading efficiency are considered. Numerical studies evaluate various solution procedures and demonstrate the importance of considering stochasticity and the value of the two-stage model.

FlowFace: Semantic Flow-Guided Shape-Aware Face Swapping

In this work, we propose a semantic flow-guided two-stage framework for shape-aware face swapping, namely FlowFace. Unlike most previous methods that focus on transferring the source inner facial features but neglect facial contours, our FlowFace can transfer both of them to a target face, thus leading to more realistic face swapping. Concretely, our FlowFace consists of a face reshaping network and a face swapping network. The face reshaping network addresses the shape outline differences between the source and target faces. It first estimates a semantic flow (i.e. face shape differences) between the source and the target face, and then explicitly warps the target face shape with the estimated semantic flow. After reshaping, the face swapping network generates inner facial features that exhibit the identity of the source face. We employ a pre-trained face masked autoencoder (MAE) to extract facial features from both the source face and the target face. In contrast to previous methods that use identity embedding to preserve identity information, the features extracted by our encoder can better capture facial appearances and identity information. Then, we develop a cross-attention fusion module to adaptively fuse inner facial features from the source face with the target facial attributes, thus leading to better identity preservation. Extensive quantitative and qualitative experiments on in-the-wild faces demonstrate that our FlowFace outperforms the state-of-the-art significantly.

Resource estimations for the Hamiltonian simulation in correlated electron materials

Correlated electron materials, such as superconductors and magnetic materials, are regarded as fascinating targets in quantum computing. However, the quantitative resources, specifically the number of quantum gates and qubits, required to perform a quantum algorithm to simulate correlated electron materials remain unclear. In this study, we estimate the resources required for the Hamiltonian simulation algorithm for correlated electron materials, specifically for organic superconductors, iron-based superconductors, binary transition-metal oxides, and perovskite oxides, using the fermionic swap network. The effective Hamiltonian derived using the ab initio downfolding method is adopted for the Hamiltonian simulation, and a procedure for the resource estimation by using the fermionic swap network for the effective Hamiltonians including the exchange interactions is proposed. For example, in the system for the ${10}^{2}$ unit cells, the estimated numbers of gates per Trotter step and qubits are approximately ${10}^{7}$ and ${10}^{3}$, respectively, on average for the correlated electron materials. Furthermore, our results show that the number of interaction terms in the effective Hamiltonian, especially for the Coulomb interaction terms, is dominant in the gate resources when the number of unit cells constituting the whole system is up to ${10}^{2}$, whereas the number of fermionic swap operations is dominant when the number of unit cells is more than ${10}^{3}$.

Optimized SWAP networks with equivalent circuit averaging for QAOA

The SWAP network is a qubit routing sequence that can be used to efficiently execute the Quantum Approximate Optimization Algorithm (QAOA). Even with a minimally connected topology on an $n$-qubit processor, this routing sequence enables $\mathcal{O}({n}^{2})$ operations to execute in $\mathcal{O}(n)$ steps. In this work, we optimize the execution of SWAP networks for QAOA through two techniques. First, we take advantage of an overcomplete set of native hardware operations [including 150-ns controlled-$\frac{\ensuremath{\pi}}{2}$ phase gates with up to 99.67(1)% fidelity] to decompose the relevant quantum gates and SWAP networks in a manner which minimizes circuit depth and maximizes gate cancellation. Second, we introduce equivalent circuit averaging, which randomizes over degrees of freedom in the quantum circuit compilation to reduce the impact of systematic coherent errors. Our techniques are experimentally validated at the Advanced Quantum Testbed through the execution of QAOA circuits for finding the ground state of two- and four-node Sherrington-Kirkpatrick spin-glass models with various randomly sampled parameters. We observe a $\ensuremath{\sim}60%$ average reduction in error (total variation distance) for QAOA of depth $p=1$ on four transmon qubits on a superconducting quantum processor.

Quantum simulation of fermionic systems using hybrid digital–analog quantum computing approach

We consider a hybrid digital–analog quantum computing approach, which allows implementing any quantum algorithm without standard two-qubit gates. This approach is based on the always-on interaction between qubits, which can provide an alternative to such gates. We show how digital–analog approach can be applied to simulate the dynamics of fermionic systems, in particular, the Fermi–Hubbard model, using fermionic SWAP network and refocusing technique. We concentrate on the effects of connectivity topology, the spread of interaction constants as well as on errors of entangling operations. We find that an optimal connectivity topology of qubits for the digital–analog simulation of fermionic systems of arbitrary dimensionality is a chain for spinless fermions and a ladder for spin 1/2 particles. Such a simple connectivity topology makes digital–analog approach attractive for the simulation of quantum materials and molecules.

The network structure of overnight index swap rates

Graph theoretical techniques are utilized to examine the centrality structure of overnight index swap (OIS) networks. Correlation based graphs are constructed to encode pairwise relationships between distinct OIS rates. Multiple notions of graph centrality are considered, and the time evolution of these measures is studied. A principal component analysis based centrality measure is constructed to examine comovements between full OIS curves. Numerical examples demonstrating these ideas are provided.

International spillover of central bank swap lines - Evidence from the COVID-19 experience of Korea

Dollar funding cost rose significantly worldwide during the early stage of the COVID-19 pandemic. Against the dollar shortage, the Fed provided liquidity to 14 other central banks through central bank swap lines. I find significant liquidity spillover into Korea by comparing foreign banks from the swap network countries with banks from the other regions in their borrowing from parent banks. The spillover amounts to 11 billion dollars, half of the maximum amount Korea has drawn from the swap line. The result highlights the broad effects of the swap lines via cross-border spillover and foreign banks’ pivotal role in international shock transmission.

Monetary Policy Cooperation/Coordination and Global Financial Crises in Historical Perspective

The Covid 19 pandemic spawned a global liquidity crisis in March 2020. The global liquidity crisis was alleviated by the Federal Reserve and other advanced country central banks cooperating by extending the swap lines they developed in the Global Financial Crisis 2007–2008. Central bank cooperation in 2020 evolved from a two-century history across several monetary regimes that is surveyed in this paper. I find that in monetary regimes which are rules-based cooperation was most successful. International currency swaps developed to manage exchange rates during the Bretton Woods era have evolved into the leading tool to manage international liquidity crises. The swap network can be viewed as a step in the direction of a global financial safety net.

The Network Structure of Overnight Index Swap Rates

Graph theoretical techniques are utilized to examine the network centrality structure of overnight index swap (OIS) networks. Correlation based graphs are constructed to encode pairwise relationships between distinct OIS rates. Multiple notions of graph centrality are considered, and the time evolution of these measures is studied. A principal component analysis based centrality measure is constructed to examine comovements between full OIS curves. Numerical examples demonstrating these ideas are provided.

Delivery drone route planning over a battery swapping network

Many enterprises invest on drone delivery research and development to drop off packages at consumers’ doorsteps in a matter of minutes. We study delivery drone route planning over a battery swapping network allowing farther reach by penetrating current battery capacity constraints. A mixed-integer nonlinear programming model is created to plan efficient drone routing over the swapping machines by minimizing the delivery lead time. We develop an exact solution method, evaluate its performance, and compare it with a straightforward nonlinear solver application. A case study highlights the applicability of the model. Data and source code to the solver are publicly shared.

Detection of genuine tripartite entanglement in quantum network scenario

Experimental demonstration of entanglement needs to have a precise control of experimentalist over the system on which the measurements are performed as prescribed by an appropriate entanglement witness. To avoid such trust problem, recently, device-independent entanglement witnesses (DIEWs) for genuine tripartite entanglement have been proposed where witnesses are capable of testing genuine entanglement without precise description of Hilbert space dimension and measured operators i.e. apparatus are treated as black boxes. Here, we design a protocol for enhancing the possibility of identifying genuine tripartite entanglement in a device independent manner. We consider three mixed tripartite quantum states none of whose genuine entanglement can be detected by applying certain DIEWs, but their genuine tripartite entanglement can be detected by applying the same when distributed in some suitable entanglement swapping network.

Systemic Risk in Networks with a Central Node

We examine the effects on a financial network of clearing all contracts though a central node (CN) thereby transforming the original network into a star-shaped one. The CN is capitalized with external equity and a guaranty fund. We introduce a structural systemic risk measure that captures the shortfall of end users. We show that it is possible to simultaneously improve the expected surplus of the banks and the CN as well as decrease the shortfall of end users. We determine the CN's equity and guaranty fund policies as a Nash bargaining solution. We illustrate our findings on simulated Credit Default Swap networks compatible with aggregate market data.

Systemic Risk in Networks with a Central Node

We examine the effects on a financial network of clearing all contracts though a central node (CN), thereby transforming the original network into a star-shaped one. The CN is capitalized with external equity and a guaranty fund. We introduce a structural systemic risk measure that captures the shortfall of end users. We show that it is possible to simultaneously improve the expected surplus of the banks and the CN as well as decrease the shortfall of end users. We determine the CN's equity and guaranty fund policies as a Nash bargaining solution. We illustrate our findings on simulated credit default swap networks compatible with aggregate market data.

Quantum Simulation of Electronic Structure with Linear Depth and Connectivity.

As physical implementations of quantum architectures emerge, it is increasingly important to consider the cost of algorithms for practical connectivities between qubits. We show that by using an arrangement of gates that we term the fermionic swap network, we can simulate a Trotter step of the electronic structure Hamiltonian in exactly N depth and with N^{2}/2 two-qubit entangling gates, and prepare arbitrary Slater determinants in at most N/2 depth, all assuming only a minimal, linearly connected architecture. We conjecture that no explicit Trotter step of the electronic structure Hamiltonian is possible with fewer entangling gates, even with arbitrary connectivities. These results represent significant practical improvements on the cost of most Trotter-based algorithms for both variational and phase-estimation-based simulation of quantum chemistry.

Nontrilocality: Exploiting nonlocality from three-particle systems

In Phys. Rev. Lett. \textbf{104},170401 (2010), Branciard \textit{e.t al.} first characterized the correlations arising in an entanglement swapping network under the assumption that the sources generating the initially uncorrelated quantum systems are independent. Precisely speaking, in Phys. Rev. Lett. \textbf{104},170401 (2010) and later in Phys. Rev. A \textbf{85},032119 (2012) the authors analyzed the importance of \textit{bilocal}(source independence) assumption to lower down the restrictions over correlations for revealing quantumness in the network where each of two sources generates a bipartite entangled state. In this context one may find interest to characterize correlations in a network involving independent sources which can correlate more than two initially uncorrelated multipartite entangled quantum systems. Our present topic of discussion basically analyzes such a network scenario. Specifically we introduce \textit{trilocal network scenario} where each of three sources independently generates a tripartite entangled quantum system thereby exploring the role of source independence assumption to exploit nonlocality in a network involving multipartite entanglement analogous to bilocal assumption in a network where only bipartite entanglement was considered. Interestingly, genuine entanglement content did not turn out to be an essential requirement for exploiting nonlocality in such a scenario. Moreover it is interesting to explore whether such a scenario can be generalized so as to characterize correlations arising in a network involving $n$ number of $n$ partite systems for any finite value of $n\geq4$ under source independence assumption.

An Iterative Interpolation Deconvolution Algorithm for Superresolution Land Cover Mapping

Superresolution mapping (SRM) is a method to produce a fine-spatial-resolution land cover map from coarse-spatial-resolution remotely sensed imagery. A popular approach for SRM is a two-step algorithm, which first increases the spatial resolution of coarse fraction images by interpolation and then determines class labels of fine-resolution pixels using the maximum a posteriori (MAP) principle. By constructing a new image formation process that establishes the relationship between the observed coarse-resolution fraction images and the latent fine-resolution land cover map, it is found that the MAP principle only matches with area-to-point interpolation algorithms and should be replaced by deconvolution if an area-to-area interpolation algorithm is to be applied. A novel iterative interpolation deconvolution (IID) SRM algorithm is proposed. The IID algorithm first interpolates coarse-resolution fraction images with an area-to-area interpolation algorithm and produces an initial fine-resolution land cover map by deconvolution. The fine-spatial-resolution land cover map is then updated by reconvolution, back-projection, and deconvolution iteratively until the final result is produced. The IID algorithm was evaluated with simulated shapes, simulated multispectral images, and degraded Landsat images, including comparison against three widely used SRM algorithms: pixel swapping, bilinear interpolation, and Hopfield neural network. Results show that the IID algorithm can reduce the impact of fraction errors and can preserve the patch continuity and the patch boundary smoothness simultaneously. Moreover, the IID algorithm produced fine-resolution land cover maps with higher accuracies than those produced by other SRM algorithms.