Abstract

In this article we derive the exact dynamics of a two qubit (spin 1/2) system interacting centrally with separate fermionic baths composed of qubits in thermal state. Further, each spin of a bath is coupled to every other spin of the same bath. The corresponding dynamical map is constructed. It is used to analyse the non-Markovian nature of the two qubit central spin dynamics. We further observe the evolution of quantum correlations like entanglement and discord under the influence of the environmental interaction. Moreover, we demonstrate the comparison between this exact two qubit dynamics and the locally acting fermionic central spin model. This work is a stepping stone towards the realization of non-Markovian heat engines and other quantum thermal devices.

Abstract

The design and implementation of parallel algorithms for dynamic graph problems is attracting significant research attention in the recent years, driven by numerous applications to social network analysis, neuroscience, and protein interaction networks. One such problem is the computation of PageRank values of vertices in a directed graph. This paper presents two new parallel algorithms for recomputing the PageRank values of vertices in a dynamic graph. Our techniques require the recomputation of the PageRank of only the vertices affected by the insertion/deletion of a batch of edges. We conduct detailed experimental studies of our algorithm on a set of 11 realworld graphs. Our results on Intel Xeon Silver 4116 CPU and NVIDIA Tesla V100 PCIe 16GB GPU indicate that our algorithms outperform static and dynamic update algorithms by 6.1×and 8.6×on the CPU, and by 9.8×and 9.3×on the GPU respectively. We also compare the performance of the algorithms in batched mode to cumulative single-edge updates.

Abstract

Finding the biconnected components of a graph has a large number of applications in many other graph problems including planarity testing, computing the centrality metrics, finding the (weighted) vertex cover, coloring, and the like. Recent years saw the design of efficient algorithms for this problem across sequential and parallel computational models. However, current algorithms do not work in the setting where the underlying graph changes over time in a dynamic manner via the insertion or deletion of edges. Dynamic algorithms in the sequential setting that obtain the biconnected components of a graph upon insertion or deletion of a single edge are known from over two decades ago. Parallel algorithms for this problem are not heavily studied. In this paper, we design shared-memory parallel algorithms that obtain the biconnected components of a graph subsequent to the insertion or deletion of a batch of edges

Abstract

Linear n-local networks are compatible with quantum repeaters based entanglement distribution protocols. Different sources of imperfections such as error in entanglement generation, communication over noisy quantum channels and imperfections in measurements result in decay of quantumness across such networks. From practical perspectives it becomes imperative to analyze non classicality of quantum network correlations in presence of different types of noise. Present discussion provides a formal characterization of non n-local feature of quantum correlations in noisy network scenario. In this context, persistency of non n-locality has been introduced. Such a notion helps in analyzing decay of non n-local feature of network correlations with increasing length of the linear network in presence of one or more causes of imperfections.

Abstract

urpose: Melanin is a major contributor to the intensity and width of the retinal pigment epithelium (RPE) on optical coherence tomography (OCT). It is hypothesized, high melanin concentrations cause scattering making the RPE appear as a thick band and obscures adjacent layers. A split band appearance of the outermost hyperreflective band has been demonstrated in Albinism, meaning the RPE and Bruch’s Membrane appear as two separate bands. We performed a cross-sectional observational study to test the hypothesis that a reduction in melanin causes an increased ability to differentiate the hyperreflective bands seen on OCT images of the outer retina. Methods: Using the UK Biobank dataset, we generated a randomised sample of 300 participants with specific inclusion and exclusion criteria. Inclusion criteria was an age between 40 to 65, visual acuity better than 0.60 logMAR, no ocular pathology, and

Abstract

Electric vehicles (EVs) represent the long-term green substitute for traditional fuel-based vehicles. To encourage EV adoption, the trust of the end-users must be assured. In this work, we focus on a recently emerging privacy threat of profiling and identifying EVs via the analog electrical data exchanged during the EV charging process. The core focus of our work is to investigate the feasibility of such a threat at scale. To this end, we first propose an improved EV profiling approach that outperforms the state-of-the-art EV profiling techniques. Next, we exhaustively evaluate the performance of our improved approach to profile EVs in real-world settings. In our evaluations, we conduct a series of experiments including 25032 charging sessions from 530 real EVs, sub-sampled datasets with different data distributions, etc. Our results show that even with our improved approach, profiling and individually identifying the growing number of EVs appear extremely difficult in practice; at least with the analog charging data utilized throughout the literature. We believe that our findings from this work will further foster the trust of potential users in the EV ecosystem, and consequently, encourage EV adoption.

Abstract

After the success of the Bitcoin blockchain, came several cryptocurrencies and blockchain solutions in the last decade. Nonetheless, Blockchain-based systems still suffer from low transaction rates and high transaction processing latencies, which hinder blockchains’ scalability. An entire class of solutions, called Layer-1 scalability solutions, have attempted to incrementally improve such limitations by adding/modifying fundamental blockchain attributes. Recently, a completely different class of works, called Layer-2 protocols, have emerged to tackle the blockchain scalability issues using unconventional approaches. Layer-2 protocols improve transaction processing rates, periods, and fees by minimizing the use of underlying slow and costly blockchains. In fact, the main chain acts just as an instrument for trust establishment and dispute resolution among Layer2 participants, where only a few transactions are dispatched to the main chain. Thus, Layer-2 blockchain protocols have the potential to transform the domain. However, rapid and discrete developments have resulted in diverse branches of Layer2 protocols. In this work, we systematically create a broad taxonomy of such protocols and implementations. We discuss each Layer-2 protocol class in detail and also elucidate their respective approaches, salient features, requirements, etc. Moreover, we outline the issues related to these protocols along with a comparative discussion. Our thorough study will help further systematize the knowledge dispersed in the domain and help the readers to better understand the field of Layer-2 protocols. Index Terms—Blockchain, Layer-2, Off-chain, Scalability.

Abstract

Decentralized Finance (DeFi) promises to transform the traditional financial systems into fair and transparent protocols that do not require trusted third parties. To circumvent the high volatility of crypto-assets, DeFi protocols advocate collateralizing their assets against conventional financial instruments. To do so, these protocols require access to external or off-chain data, such as asset exchange rates. DeFi protocols rely on oracles to access such information. Importing external data onto the chain via oracles consists of multiple data processing and aggregation stages. Thus, it is critical to minimize errors or deviations while the ground truth data moves through these stages. In this paper, we investigate the degree of price deviations at different levels between the data source and the final output rendered to an on-chain requester. In particular, we focus on Chainlink’s oracle network for ETH-USD pricing. Our results …

Abstract

In this paper, we present the design of a complete system for recording electrophysiology signals from patients and also present the recordings. We observe the signals from relaxed and fatigued muscles as well as from heart (ECG) signals. We designed the complete integrated circuit for flexible substrates using basic ICs. The system captures, amplifies, and filters using analog circuits. The instrumentation amplifier (AD623) in the first step amplifies (gain = 100), a combination of Bessel low- pass filter (2nd-order active low-pass filter with LM741 op-amp in Sallen-Key topology) cut-off = 500 Hz, HPF (1st-order active high-pass filter with LM741) cut-off = 0.03, and twin-T active Notch filter with LM741 filters the input. Design, analysis, and data from the prototype and packing (flexible) plan for this customized new system are presented in this paper. Index Terms—Electromyography, Instrumentation amplifier, Wearable Systems, Bio instrumentation, Analog circuit design, Second order filters

Abstract

This paper presents a low cost, easy to fabricate, thin-film sensor. We used three different methods to make the thin film using two different base (film) materials: carbon and graphite. We briefly summarize the method and outcome of multi-layer thin film fabrication using spray coating, spin-coating, and drop-casting. The quality of the thin films is compared, and electrical resistance is characterized. The fabricated thin film is used to measure humidity and is characterized against a commercial humidity sensor (DHT22). The experimental details and results of humidity measurement are discussed. We were able to achieve resistance range of 5k - 1.5k ohms for 40 - 80 % RH, respectively. Plans to further optimize the sensitivity of the sensor, in future is discussed.