HASLab - Indexed Articles in Journals

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Browsing HASLab - Indexed Articles in Journals by Author "5603"
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    Coalgebra for the working software engineer
    ( 2022) Luís Soares Barbosa ; 5603
    Often referred to as ‘the mathematics of dynamical, state-based systems’, Coalgebra claims to provide a compositional and uniform framework to specify, analyse and reason about state and behaviour in computing. This paper addresses this claim by discussing why Coalgebra matters for the design of models and logics for computational phenomena. To a great extent, in this domain one is interested in properties that are preserved along the system’s evolution, the so-called ‘business rules’ or system’s invariants, as well as in liveness requirements, stating that e.g. some desirable outcome will be eventually produced. Both classes are examples of modal assertions, i.e. properties that are to be interpreted across a transition system capturing the system’s dynamics. The relevance of modal reasoning in computing is witnessed by the fact that most university syllabi in the area include some incursion into modal logic, in particular in its temporal variants. The novelty is that, as it happens with the notions of transition, behaviour, or observational equivalence, modalities in Coalgebra acquire a shape. That is, they become parametric on whatever type of behaviour, and corresponding coinduction scheme, seems appropriate for addressing the problem at hand. In this context, the paper revisits Coalgebra from a computational perspective, focussing on three topics central to software design: how systems are modelled, how models are composed, and finally, how properties of their behaviours can be expressed and verified. © 2022, College Publications. All rights reserved.
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    A component-based framework for certification of components in a cloud of HPC services
    ( 2020) de Carvalho Junior,FH ; de Oliveira Dantas,ABD ; Luís Soares Barbosa ; 5603
    HPC Shelf is a proposal of a cloud computing platform to provide component-oriented services for High Performance Computing (HPC) applications. This paper presents a Verification-as-a-Service (VaaS) framework for component certification on HPC Shelf. Certification is aimed at providing higher confidence that components of parallel computing systems of HPC Shelf behave as expected according to one or more requirements expressed in their contracts. To this end, new abstractions are introduced, starting with certifier components. They are designed to inspect other components and verify them for different types of functional, non-functional and behavioral requirements. The certification framework is naturally based on parallel computing techniques to speed up verification tasks. © 2019
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    Data governance: Organizing data for trustworthy Artificial Intelligence
    ( 2020) Brous,P ; Janssen,M ; Janowski,T ; Luís Soares Barbosa ; Estevez,E ; 5603
    The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements. However, they all rely on data which is not only big, open and linked but varied, dynamic and streamed at high speeds in real-time. Managing such data is challenging. To overcome such challenges and utilize opportunities for BDAS, organizations are increasingly developing advanced data governance capabilities. This paper reviews challenges and approaches to data governance for such systems, and proposes a framework for data governance for trustworthy BDAS. The framework promotes the stewardship of data, processes and algorithms, the controlled opening of data and algorithms to enable external scrutiny, trusted information sharing within and between organizations, risk-based governance, system-level controls, and data control through shared ownership and self-sovereign identities. The framework is based on 13 design principles and is proposed incrementally, for a single organization and multiple networked organizations.
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    Digital quantum simulation of non-perturbative dynamics of open systems with orthogonal polynomials
    ( 2024) Luís Soares Barbosa ; 5603
    Classical non-perturbative simulations of open quantum systems' dynamics face several scalability problems, namely, exponential scaling of the computational effort as a function of either the time length of the simulation or the size of the open system. In this work, we propose the use of the Time Evolving Density operator with Orthogonal Polynomials Algorithm (TEDOPA) on a quantum computer, which we term as Quantum TEDOPA (Q-TEDOPA), to simulate nonperturbative dynamics of open quantum systems linearly coupled to a bosonic environment (continuous phonon bath). By performing a change of basis of the Hamiltonian, the TEDOPA yields a chain of harmonic oscillators with only local nearestneighbour interactions, making this algorithm suitable for implementation on quantum devices with limited qubit connectivity such as superconducting quantum processors. We analyse in detail the implementation of the TEDOPA on a quantum device and show that exponential scalings of computational resources can potentially be avoided for time-evolution simulations of the systems considered in this work. We applied the proposed method to the simulation of the exciton transport between two light-harvesting molecules in the regime of moderate coupling strength to a non-Markovian harmonic oscillator environment on an IBMQ device. Applications of the Q-TEDOPA span problems which can not be solved by perturbation techniques belonging to different areas, such as the dynamics of quantum biological systems and strongly correlated condensed matter systems.
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    Digital quantum simulation of non-perturbative dynamics of open systems with orthogonal polynomials
    ( 2024) Luís Soares Barbosa ; 5603
    Classical non-perturbative simulations of open quantum systems' dynamics face several scalability problems, namely, exponential scaling of the computational effort as a function of either the time length of the simulation or the size of the open system. In this work, we propose the use of the Time Evolving Density operator with Orthogonal Polynomials Algorithm (TEDOPA) on a quantum computer, which we term as Quantum TEDOPA (Q-TEDOPA), to simulate nonperturbative dynamics of open quantum systems linearly coupled to a bosonic environment (continuous phonon bath). By performing a change of basis of the Hamiltonian, the TEDOPA yields a chain of harmonic oscillators with only local nearestneighbour interactions, making this algorithm suitable for implementation on quantum devices with limited qubit connectivity such as superconducting quantum processors. We analyse in detail the implementation of the TEDOPA on a quantum device and show that exponential scalings of computational resources can potentially be avoided for time-evolution simulations of the systems considered in this work. We applied the proposed method to the simulation of the exciton transport between two light-harvesting molecules in the regime of moderate coupling strength to a non-Markovian harmonic oscillator environment on an IBMQ device. Applications of the Q-TEDOPA span problems which can not be solved by perturbation techniques belonging to different areas, such as the dynamics of quantum biological systems and strongly correlated condensed matter systems.
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    Generalising KAT to Verify Weighted Computations
    ( 2019) HASLab INESC TEC,Universidade do Minho,R. da Universidade,4710-057 Braga,Portugal, ; CIDMA,Universidade de Aveiro,Campus Universitario de Santiago,3810-193 Aveiro,Portugal, ; Luís Soares Barbosa ; Madeira,A ; Leandro Rafael Gomes ; Universidade do Minho,R. da Universidade,4710-057 Braga,Portugal & Quantum Software Engineering Group,INL, ; 6759 ; 5603
    Kleene algebra with tests (KAT) was introduced as an algebraic structure to model and reason about classic imperative programs, i.e. sequences of discrete transitions guarded by Boolean tests. This paper introduces two generalisations of this structure able to express programs as weighted transitions and tests with outcomes in non necessarily bivalent truth spaces: graded Kleene algebra with tests (GKAT) and a variant where tests are also idempotent (I-GKAT). In this context, and in analogy to Kozen's encoding of Propositional Hoare Logic (PHL) in KAT we discuss the encoding of a graded PHL in I-GKAT and of its while-free fragment in GKAT. Moreover, to establish semantics for these structures four new algebras are defined: FSET(T), FREL(K,T) and FLANG(K,T) over complete residuated lattices K and T, and M (n, A) over a GKAT or I-GKAT A. As a final exercise, the paper discusses some program equivalence proofs in a graded context.
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    Hierarchical Hybrid Logic
    ( 2018) Renato Jorge Neves ; Luís Soares Barbosa ; Martins,MA ; Alexandre Castro Madeira ; 5603 ; 5620 ; 6181
    We introduce HHL, a hierarchical variant of hybrid logic. We study first order correspondence results and prove a Hennessy-Milner like theorem relating (hierarchical) bisimulation and modal equivalence for HHL. Combining hierarchical transition structures with the ability to refer to specific states at different levels, this logic seems suitable to express and verify properties of hierarchical transition systems, a pervasive semantic structure in Computer Science.
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    Languages and models for hybrid automata: A coalgebraic perspective
    ( 2018) Luís Soares Barbosa ; Renato Jorge Neves ; 6181 ; 5603
    We study hybrid automata from a coalgebraic point of view. We show that such a perspective supports a generic theory of hybrid automata with a rich palette of definitions and results. This includes, among other things, notions of bisimulation and behaviour, state minimisation techniques, and regular expression languages.
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    On Quantum Natural Policy Gradients
    ( 2024) Luís Paulo Santos ; Luís Soares Barbosa ; 6969 ; 5603
    This article delves into the role of the quantum Fisher information matrix (FIM) in enhancing the performance of parameterized quantum circuit (PQC)-based reinforcement learning agents. While previous studies have highlighted the effectiveness of PQC-based policies preconditioned with the quantum FIM in contextual bandits, its impact in broader reinforcement learning contexts, such as Markov decision processes, is less clear. Through a detailed analysis of L & ouml;wner inequalities between quantum and classical FIMs, this study uncovers the nuanced distinctions and implications of using each type of FIM. Our results indicate that a PQC-based agent using the quantum FIM without additional insights typically incurs a larger approximation error and does not guarantee improved performance compared to the classical FIM. Empirical evaluations in classic control benchmarks suggest even though quantum FIM preconditioning outperforms standard gradient ascent, in general, it is not superior to classical FIM preconditioning.
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    Policy gradients using variational quantum circuits
    ( 2023) Luís Soares Barbosa ; Luís Paulo Santos ; 5603 ; 6969
    Variational quantum circuits are being used as versatile quantum machine learning models. Some empirical results exhibit an advantage in supervised and generative learning tasks. However, when applied to reinforcement learning, less is known. In this work, we considered a variational quantum circuit composed of a low-depth hardware-efficient ansatz as the parameterized policy of a reinforcement learning agent. We show that an epsilon-approximation of the policy gradient can be obtained using a logarithmic number of samples concerning the total number of parameters. We empirically verify that such quantum models behave similarly to typical classical neural networks used in standard benchmarking environments and quantum control, using only a fraction of the parameters. Moreover, we study the barren plateau phenomenon in quantum policy gradients using the Fisher information matrix spectrum.
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    Quantum advantage in temporally flat measurement-based quantum computation
    ( 2024) Luís Soares Barbosa ; 5603
    Several classes of quantum circuits have been shown to provide a quantum computational advantage under certain assumptions. The study of ever more restricted classes of quantum circuits capable of quantum advantage is motivated by possible simplifications in experimental demonstrations. In this paper we study the efficiency of measurement-based quantum computation with a completely flat temporal ordering of measurements. We propose new constructions for the deterministic computation of arbitrary Boolean functions, drawing on correlations present in multi-qubit Greenberger, Horne, and Zeilinger (GHZ) states. We characterize the necessary measurement complexity using the Clifford hierarchy, and also generally decrease the number of qubits needed with respect to previous constructions. In particular, we identify a family of Boolean functions for which deterministic evaluation using non-adaptive MBQC is possible, featuring quantum advantage in width and number of gates with respect to classical circuits.
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    Quantum privacy-preserving service for secure lane change in vehicular networks
    ( 2023) Luís Soares Barbosa ; 5603
    Secure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks. However, classical SMC implementations suffer from efficiency and security challenges. To address this problem, two quantum communication technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution were utilised. These technologies supply symmetric and oblivious keys respectively, allowing fast and secure inter-vehicular communications. These quantum technologies are integrated with the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to form a Quantum Secure Multiparty Computation (QSMC) platform. A lane change service is implemented in which vehicles broadcast private information about their intention to exit the highway. The proposed QSMC approach provides unconditional security even against quantum computer attacks. Moreover, the communication cost of the quantum approach for the lane change use case has decreased by 97% when compared to the classical implementation. However, the computation cost has increased by 42%. For open space scenarios, the reduction in communication cost is especially important, because it conserves bandwidth in the free-space radio channel, outweighing the increase in computation cost. A Quantum Secure Multiparty Computation (QSMC) solution for lane change service in vehicular networks that uses two quantum technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution (QOKD) is proposed. This quantum-based approach is resistant to quantum computer attacks and requires less communication resources compared to classical methods.image
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    Simulation of Nonradiative Energy Transfer in Photosynthetic Systems Using a Quantum Computer
    ( 2020) Carlos Eduardo Tavares ; Guimaraes,JD ; Luís Soares Barbosa ; Vasilevskiy,MI ; 4852 ; 5603
    Photosynthesis is an important and complex physical process in nature, whose comprehensive understanding would have many relevant industrial applications, for instance, in the field of energy production. In this paper, we propose a quantum algorithm for the simulation of the excitonic transport of energy, occurring in the first stage of the process of photosynthesis. The algorithm takes in account the quantum and environmental effects (pure dephasing), influencing the quantum transport. We performed quantum simulations of such phenomena, for a proof of concept scenario, in an actual quantum computer, IBM Q, of 5 qubits. We validate the results with the Haken-Ströbl model and discuss the influence of environmental parameters on the efficiency of the energy transport.
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    A taxonomy for planning and designing smart mobility services
    ( 2018) Estevez,E ; Guillermina Cledou ; Luís Soares Barbosa ; 5603 ; 6193
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    Trainability issues in quantum policy gradients
    ( 2024) Luís Paulo Santos ; Luís Soares Barbosa ; 6969 ; 5603
    This research explores the trainability of Parameterized Quantum Circuit-based policies in Reinforcement Learning, an area that has recently seen a surge in empirical exploration. While some studies suggest improved sample complexity using quantum gradient estimation, the efficient trainability of these policies remains an open question. Our findings reveal significant challenges, including standard Barren Plateaus with exponentially small gradients and gradient explosion. These phenomena depend on the type of basis-state partitioning and the mapping of these partitions onto actions. For a polynomial number of actions, a trainable window can be ensured with a polynomial number of measurements if a contiguous-like partitioning of basis-states is employed. These results are empirically validated in a multi-armed bandit environment.