Now showing 1 - 10 of 65
PublicationAutomatic generation of Grover quantum oracles for arbitrary data structures( 2023)
;Seidel, Raphael ; ; ;Tcholtchev, Nikolay Vassilev ;The steadily growing research interest in quantum computing-together with the accompanying technological advances in the realization of quantum hardware-fuels the development of meaningful real-world applications, as well as implementations for well-known quantum algorithms. One of the most prominent examples till today is Grover’s algorithm, which can be used for efficient search in unstructured databases. Quantum oracles that are frequently masked as black boxes play an important role in Grover’s algorithm. Hence, the automatic generation of oracles is of paramount importance. Moreover, the automatic generation of the corresponding circuits for a Grover quantum oracle is deeply linked to the synthesis of reversible quantum logic, which-despite numerous advances in the field-still remains a challenge till today in terms of synthesizing efficient and scalable circuits for complex Boolean functions. In this paper, we present a flexible method for automatically encoding unstructured databases into oracles, which can then be efficiently searched with Grover’s algorithm. Furthermore, we develop a tailor-made method for quantum logic synthesis, which vastly improves circuit complexity over other current approaches. Finally, we present another logic synthesis method that considers the requirements of scaling onto real world backends. We compare our method with other approaches through evaluating the oracle generation for random databases and analyzing the resulting circuit complexities using various metrics.
PublicationSemRob: Towards semantic stream reasoning for robotic operating systems( 2022)
;Nguyen-Duc, Manh ;Le-Tuan, Anh ; ;Bowden, DavidPhuoc, Danh LeStream processing and reasoning is getting considerable attention in various application domains such as IoT, Industry IoT and Smart Cities. In parallel, reasoning and knowledge-based features have attracted research into many areas of robotics, such as robotic mapping, perception and interaction. To this end, the Semantic Stream Reasoning (SSR) framework can unify the representations of symbolic/semantic streams with deep neural networks, to integrate high-dimensional data streams, such as video streams and LiDAR point clouds, with traditional graph or relational stream data. As such, this positioning and system paper will outline our approach to build a platform to facilitate semantic stream reasoning capabilities on a robotic operating system called SemRob.
PublicationDesign and specification of a privacy-preserving registration for Blockchain-based energy marketsThe challenges of climate change and the related demand to integrate non-plannable and weather-dependent renewable energy resources pose enormous challenges for the entire energy domain, e.g. in the context of grid control. These challenges reveal the need for new technical solutions and new business models while they indicate the required and inevitable transition to smart grids. Many blockchain-based solutions are being discussed in this context, ranging from peer-to-peer energy trading to grid-serving applications. However, especially in connection with public blockchains, clear security privacy challenges arise since the security and privacy of private data must be guaranteed while traceability must be avoided. Therefore, in this paper, we will specify privacy-protecting registration processes for blockchain-based flexibility markets that enable pseudonymous access to the latter. Furthermore, in collaboration with a governmental regulating institution named DGA, we will show that using an existing X.509-based PKI and RSA-based cryptographic processes, the integrity of all market participants can be guaranteed. This integrity is essential for the security-critical use of operating reserve. In addition, we will evaluate the specified processes in terms of efficiency, scalability, security, and privacy protection.
PublicationTowards building live open scientific knowledge graphs( 2022)
;Le-Tuan, Anh ;Franzreb, Carlos ;Phuoc, Danh Le ;Due to the large number and heterogeneity of data sources, it becomes increasingly difficult to follow the research output and the scientific discourse. For example, a publication listed on DBLP may be discussed on Twitter and its underlying data set may be used in a different paper published on arXiv. The scientific discourse this publication is involved in is divided among not integrated systems, and for researchers it might be very hard to follow all discourses a publication or data set may be involved in. Also, many of these data sources-DBLP, arXiv, or Twitter, to name a few-are often updated in real-time. These systems are not integrated (silos), and there is no system for users to query the content/data actively or, what would be even more beneficial, in a publish/subscribe fashion, i.e., a system would actively notify researchers of work interesting to them when such work or discussions become available. In this position paper, we introduce our concept of a live open knowledge graph which can integrate an extensible set of existing or new data sources in a streaming fashion, continuously fetching data from these heterogeneous sources, and interlinking and enriching it on-the-fly. Users can subscribe to continuously query the content/data of their interest and get notified when new content/data becomes available. We also highlight open challenges in realizing a system enabling this concept at scale.
PublicationNavigating through changes of a digital world( 2022)
;Hauk, NathalieIn this chapter, we address the question of how trust in technological development can be increased. The use of information technologies can potentially enable humanity, social justice, and the democratic process. At the same time, there are concerns that the deployment of certain technologies, e.g., AI technologies, can have unintended consequences or can even be used for malicious purposes. In this chapter, we discuss these conflicting positions.
PublicationComputer Scientist's and Programmer's View on Quantum Algorithms: Mapping Functions' APIs and Inputs to Oracles( 2022)
; ;Tcholtchev, Nikolay Vassilev ;Quantum Computing (QC) is a promising approach which is expected to boost the development of new services and applications. Specific addressable problems can be tackled through acceleration in computational time and advances with respect to the complexity of the problems, for which QC algorithms can support the solution search. However, QC currently remains a domain that is strongly dominated by a physics' perspective. Indeed, in order to bring QC to industrial grade applications we need to consider multiple perspectives, especially the one of software engineering and software application/service programming. Following this line of thought, the current paper presents our computer scientist's view on the aspect of black-box oracles, which are a key construct for the majority of currently available QC algorithms. Thereby, we observe the need for the input of API functions from the traditional world of software engineering and (web-)services to be mapped to the above mentioned black-box oracles. Hence, there is a clear requirement for automatically generating oracles for specific types of problems/algorithms based on the concrete input to the belonging APIs. In this paper, we discuss the above aspects and illustrate them on two QC algorithms, namely Deutsch-Jozsa and the Grover's algorithm.
PublicationCQELS 2.0: Towards a unified framework for semantic stream fusion( 2022)
;Le-Tuan, Anh ;Nguyen-Duc, Manh ;Le, Chien-Quang ;Tran, Trung-Kien ; ;Eiter, ThomasPhuoc, Danh LeWe present CQELS 2.0, the second version of Continuous Query Evaluation over Linked Streams. CQELS 2.0 is a platform-agnostic federated execution framework towards semantic stream fusion. In this version, we introduce a novel neuralsymbolic stream reasoning component that enables specifying deep neural network (DNN) based data fusion pipelines via logic rules with learnable probabilistic degrees as weights. As a platform-agnostic framework, CQELS 2.0 can be implemented for devices with different hardware architectures (from embedded devices to cloud infrastructures). Moreover, this version also includes an adaptive federator that allows CQELS instances on different nodes in a network to coordinate their resources to distribute processing pipelines by delegating partial workloads to their peers via subscribing continuous queries.
PublicationEnabling short-term energy flexibility markets through BlockchainClimate change has put significant pressure on energy markets. Political decisions such as the plan of the German government to shut down coal power plants by 2038 are shifting electricity production towards renewable and distributed energy resources. The share of these resources will continue to grow significantly in the coming years. This trend changes the ways how energy markets work which mandates fundamental changes in the underlying IT infrastructure. In this paper, we propose a blockchain-based solution which enables an economically viable and grid-serving integration of distributed energy resources into the existing energy system. Our blockchain-based approach targets intraday and day-ahead operating reserve markets, on which energy grid operators and operators of distributed energy resources can trade ﬂexibilities within the schedulable energy production and consumption of their resources. By utilizing these ﬂexibilities as an operating reserve, renewable and climate-friendly technologies can contribute to maintaining the grid stability and security of supply while simultaneously creating economically interesting business models for their operators. We propose to define blockchain-based short-term energy markets by utilizing the concept of general-purpose smart contracts and cryptocurrencies. This enables direct and decentralized trading of energy ﬂexibilities without any intermediary or central instance. We demonstrate the feasibility of our approach through an implementation of a prototype of the proposed markets based on the Ethereum blockchain and provide a detailed evaluation of its efficiency and scalability.
PublicationEfficient Floating Point Arithmetic for Quantum Computers( 2022)
;Seidel, Raphael ;Tcholtchev, Nikolay Vassilev ; ;One of the major promises of quantum computing is the realization of SIMD (single instruction - multiple data) operations using the phenomenon of superposition. Since the dimension of the state space grows exponentially with the number of qubits, we can easily reach situations where we pay less than a single quantum gate per data point for data-processing instructions which would be rather expensive in classical computing. Formulating such instructions in terms of quantum gates, however, still remains a challenging task. Laying out the foundational functions for more advanced data-processing is therefore a subject of paramount importance for advancing the realm of quantum computing. In this paper, we introduce the formalism of encoding so called-semi-boolean polynomials. As it turns out, arithmetic Z/2nZ ring operations can be formulated as semi-boolean polynomial evaluations, which allows convenient generation of unsigned integer arithmetic quantum circuits. For arithmetic evaluations, the resulting algorithm has been known as Fourier-arithmetic. We extend this type of algorithm with additional features, such as ancilla-free in-place multiplication and integer coefficient polynomial evaluation. Furthermore, we introduce a tailormade method for encoding signed integers succeeded by an encoding for arbitrary floating-point numbers. This representation of floating-point numbers and their processing can be applied to any quantum algorithm that performs unsigned modular integer arithmetic. We discuss some further performance enhancements of the semi boolean polynomial encoder and finally supply a complexity estimation. The application of our methods to a 32-bit unsigned integer multiplication demonstrated a 90% circuit depth reduction compared to carry-ripple approaches.
PublicationOpen 5G campus networks: key drivers for 6G innovations5G was designed to enable and unify Industrial Internet communication. Emerging 5G campus networks, in particular, provide a flexible communication infrastructure option addressing the specific needs of industry verticals regarding low latency, resilience, security, and operation models. Network Function Virtualization (NFV) and Edge Computing have paved the way for vendor-independent, customized, and scalable network designs for the past decade. Today, Open Radio Access Network (Open RAN) principles extend this architectural thinking toward an innovative and open 5G end-to-end infrastructure. 5G campus networks, in particular, might benefit from this envisaged openness. One key driver for boosting the global interest in private campus networks was the allocation of a dedicated 5G spectrum in Germany in 2019. In addition to permanent spectrum allocations for static campus network deployments, nomadic ad hoc campus network deployments using novel mechanisms, such as dynamic spectrum access and trading, also emerge. Both network types are enabled by the inherent flexibility of combining or disaggregating the desired open 5G RAN and core components in appropriate network deployments. Building upon years of experience in developing and operating 5G network cores and 5G testbeds, the authors provide an overview of the emerging global campus network market, available spectrum options, use cases for nomadic campus network deployments, and the need for open campus networks and open end-to-end technology testbeds. Utilizing the Fraunhofer FOKUS Open5GCore, the 5G Playground testbed, and the 5G+ Nomadic Node as examples, the paper sketches a blueprint for campus networks for international, applied research and development. Ending with an outlook on the evolution of campus networks, namely the transition toward higher spectrums and the integration of non-terrestrial networks, but also the adoption of more agile software principles and the deeper integration of AI/ML technologies for network control and management, it will become obvious that open campus network innovations will pave the way toward 6G.