arXiv subjects

Carlos Pedro Gonçalves

Publications and source records attributed to Carlos Pedro Gonçalves.

13 recordsLinked to original sources

arXiv2022

Quantum Neural Networks -- Computational Field Theory and Dynamics

To address Quantum Artificial Neural Networks as quantum dynamical computing systems, a formalization of quantum artificial neural networks as dynamical systems is developed, expanding the concept of unitary map to the neural computation setting and introducing a quantum computing field theory on the network. The formalism is illustrated in a simulation of a quantum recurrent neural network and the resulting field dynamics is researched upon, showing emergent neural waves with excitation and relaxation cycles at the level of the quantum neural activity field, as well as edge of chaos signatures, with the local neurons operating as far-from-equilibrium open quantum systems, exhibiting entropy fluctuations with complex dynamics including complex quasiperiodic patterns and power law signatures. The implications for quantum computer science, quantum complexity research, quantum technologies and neuroscience are also addressed.

quant-ph↗

arXiv2021

Cyberattacks on Quantum Networked Computation and Communications -- Hacking the Superdense Coding Protocol on IBM's Quantum Computers

The development of automated gate specification for quantum communications and quantum networked computation opens up the way for malware designed at corrupting the automation software, changing the automated quantum communications protocols and algorithms. We study two types of attacks on automated quantum communications protocols and simulate these attacks on the superdense coding protocol, using remote access to IBM's Quantum Computers available through IBM Q Experience to simulate these attacks on what would be a low noise quantum communications network. The first type of attack leads to a hacker-controlled bijective transformation of the final measured strings, the second type of attack is a unitary scrambling attack that modifies the automated gate specification to effectively scramble the final measurement, disrupting quantum communications and taking advantage of quantum randomness upon measurement in a way that makes it difficult to distinguish from hardware malfunction or from a sudden rise in environmental noise. We show that, due to quantum entanglement and symmetries, the second type of attack works as a way to strategically disrupt quantum communications networks and quantum networked computation in a way that makes it difficult to ascertain which node was attacked. The main findings are discussed in the wider setting of quantum cybersecurity and quantum networked computation, where ways of hacking including the role of insider threats are discussed.

quant-ph↗

arXiv2018

Financial Risk and Returns Prediction with Modular Networked Learning

An artificial agent for financial risk and returns' prediction is built with a modular cognitive system comprised of interconnected recurrent neural networks, such that the agent learns to predict the financial returns, and learns to predict the squared deviation around these predicted returns. These two expectations are used to build a volatility-sensitive interval prediction for financial returns, which is evaluated on three major financial indices and shown to be able to predict financial returns with higher than 80% success rate in interval prediction in both training and testing, raising into question the Efficient Market Hypothesis. The agent is introduced as an example of a class of artificial intelligent systems that are equipped with a Modular Networked Learning cognitive system, defined as an integrated networked system of machine learning modules, where each module constitutes a functional unit that is trained for a given specific task that solves a subproblem of a complex main problem expressed as a network of linked subproblems. In the case of neural networks, these systems function as a form of an "artificial brain", where each module is like a specialized brain region comprised of a neural network with a specific architecture.

cs.LG↗

arXiv2016

Quantum Neural Machine Learning - Backpropagation and Dynamics

The current work addresses quantum machine learning in the context of Quantum Artificial Neural Networks such that the networks' processing is divided in two stages: the learning stage, where the network converges to a specific quantum circuit, and the backpropagation stage where the network effectively works as a self-programing quantum computing system that selects the quantum circuits to solve computing problems. The results are extended to general architectures including recurrent networks that interact with an environment, coupling with it in the neural links' activation order, and self-organizing in a dynamical regime that intermixes patterns of dynamical stochasticity and persistent quasiperiodic dynamics, making emerge a form of noise resilient dynamical record.

cs.NE↗

arXiv2015

Financial Market Modeling with Quantum Neural Networks

Econophysics has developed as a research field that applies the formalism of Statistical Mechanics and Quantum Mechanics to address Economics and Finance problems. The branch of Econophysics that applies of Quantum Theory to Economics and Finance is called Quantum Econophysics. In Finance, Quantum Econophysics' contributions have ranged from option pricing to market dynamics modeling, behavioral finance and applications of Game Theory, integrating the empirical finding, from human decision analysis, that shows that nonlinear update rules in probabilities, leading to non-additive decision weights, can be computationally approached from quantum computation, with resulting quantum interference terms explaining the non-additive probabilities. The current work draws on these results to introduce new tools from Quantum Artificial Intelligence, namely Quantum Artificial Neural Networks as a way to build and simulate financial market models with adaptive selection of trading rules, leading to turbulence and excess kurtosis in the returns distributions for a wide range of parameters.

q-fin.CP↗

arXiv2014

Quantum Cybernetics and Complex Quantum Systems Science - A Quantum Connectionist Exploration

Quantum cybernetics and its connections to complex quantum systems science is addressed from the perspective of complex quantum computing systems. In this way, the notion of an autonomous quantum computing system is introduced in regards to quantum artificial intelligence, and applied to quantum artificial neural networks, considered as autonomous quantum computing systems, which leads to a quantum connectionist framework within quantum cybernetics for complex quantum computing systems. Several examples of quantum feedforward neural networks are addressed in regards to Boolean functions' computation, multilayer quantum computation dynamics, entanglement and quantum complementarity. The examples provide a framework for a reflection on the role of quantum artificial neural networks as a general framework for addressing complex quantum systems that perform network-based quantum computation, possible consequences are drawn regarding quantum technologies, as well as fundamental research in complex quantum systems science and quantum biology.

cs.NE↗

arXiv2014

Emotional Responses in Artificial Agent-Based Systems: Reflexivity and Adaptation in Artificial Life

The current work addresses a virtual environment with self-replicating agents whose decisions are based on a form of "somatic computation" (soma - body) in which basic emotional responses, taken in parallelism to actual living organisms, are introduced as a way to provide the agents with greater reflexive abilities. The work provides a contribution to the field of Artificial Intelligence (AI) and Artificial Life (ALife) in connection to a neurobiology-based cognitive framework for artificial systems and virtual environments' simulations. The performance of the agents capable of emotional responses is compared with that of self-replicating automata, and the implications of research on emotions and AI, in connection to both virtual agents as well as robots, is addressed regarding possible future directions and applications.

cs.AI↗

arXiv2012

Risk Mathematics and Quantum Games on Quantum Risk Structures - A Nuclear War Scenario Game

Quantum game theory is combined with risk mathematics' formalism to provide an approach to evolutionary scenario analysis. The formalism is addressed in its general form and is then applied to an extreme risks modelling case, to model a coevolving dynamical web of systemic situations representing the evolution of the regional tensions between two countries with nuclear weapons. The model's results are addressed regarding the potential for regional nuclear conflict to take place, and how evolutionary scenario analysis may contribute to nuclear war threat assessment and dynamical risk analysis. A final discussion is provided in what regards risk mathematics based on the evolutionary approach to risk assessement resulting from the combination of quantum game theory, morphic web representations and scenario analysis.

physics.soc-ph↗

arXiv2012

Quantum Chaos and Quantum Computing Structures

A system of quantum computing structures is introduced and proven capable of making emerge, on average, the orbits of classical bounded nonlinear maps on \mathbb{C} through the iterative action of path-dependent quantum gates. The effects of emerging nonlinear dynamics and chaos upon the quantum averages of relevant observables and quantum probabilities are exemplified for a version of Chirikov's standard map on \mathbb{C} . Both the individual orbits and ensemble properties are addressed so that the Poincaré map for Chirikov's standard map, in the current quantum setting, is reinterpreted in terms of a quantum ensemble which is then formally introduced within the formalized system of quantum computing structures, in terms of quantum register machines, revealing three phases of quantum ensemble dynamics: the regular, the chaotic and an intermediate phase called complex quantum stochastic phase which shares similarities to the edge of chaos notion from classical cellular automata and classical random boolean networks' evolutionary computation.

nlin.CD↗

arXiv2012

Chaos and Nonlinear Dynamics in a Quantum Artificial Economy

Chaos and nonlinear economic dynamics are addressed for a quantum coupled map lattice model of an artificial economy, with quantized supply and demand equilibrium conditions. The measure theoretic properties and the patterns that emerge in both the economic business volume dynamics' diagrams as well as in the quantum mean field averages are addressed and conclusions are drawn in regards to the application of quantum chaos theory to address signatures of chaotic dynamics in relevant discrete economic state variables.

nlin.CD↗

arXiv2012

Quantum Financial Economics of Games of Strategy and Financial Decisions

A quantum financial approach to finite games of strategy is addressed, with an extension of Nash's theorem to the quantum financial setting, allowing for an entanglement of games of strategy with two-period financial allocation problems that are expressed in terms of: the consumption plans' optimization problem in pure exchange economies and the finite-state securities market optimization problem, thus addressing, within the financial setting, the interplay between companies' business games and financial agents' behavior. A complete set of quantum Arrow-Debreu prices, resulting from the game of strategy's quantum Nash equilibrium, is shown to hold, even in the absence of securities' market completeness, such that Pareto optimal results are obtained without having to assume the completeness condition that the rank of the securities' payoff matrix is equal to the number of alternative lottery states.

q-fin.GN↗

arXiv2012

Quantum Financial Economics - Risk and Returns

Financial volatility risk and its relation to a business cycle-related intrinsic time is addressed through a multiple round evolutionary quantum game equilibrium leading to turbulence and multifractal signatures in the financial returns and in the risk dynamics. The model is simulated and the results are compared with actual financial volatility data.

q-fin.RM↗

arXiv2010

Chaos in Binary Category Computation

Category computation theory deals with a web-based systemic processing that underlies the morphic webs, which constitute the basis of categorial logical calculus. It is proven that, for these structures, algorithmically incompressible binary patterns can be morphically compressed, with respect to the local connectivities, in a binary morphic program. From the local connectivites, there emerges a global morphic connection that can be characterized by a low length binary string, leading to the identification of chaotic categorial dynamics, underlying the algorithmically random pattern. The work focuses on infinite binary chains of C2, which is a category that implements an X-OR-based categorial logical calculus.

math.CT↗