Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer

Ding, Yongcheng; Gonzalez-Conde, Javier; Lamata, Lucas; Martín-Guerrero, José D.; Lizaso, Enrique; Mugel, Samuel; Chen, Xi; Orús, Román; Solano, E.; Sanz, Mikel

doi:10.3390/e25020323

Cited by 10 publications

(5 citation statements)

References 41 publications

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“…It is thus a natural question whether quantum computation can enhance forecasting financial crashes [20]. This problem has already been investigated in terms of quantum annealing and also run on the D-Wave 2000 quantum annealer for a particular problem instance [39]. Here, we use the same model for a QAOA benchmark.…”

Section: The Financial Crash Problemmentioning

confidence: 99%

Parity Quantum Optimization: Benchmarks

Fellner

Ender

Roeland

et al. 2023

Quantum

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We present benchmarks of the parity transformation for the Quantum Approximate Optimization Algorithm (QAOA). We analyse the gate resources required to implement a single QAOA cycle for real-world scenarios. In particular, we consider random spin models with higher order terms, as well as the problems of predicting financial crashes and finding the ground states of electronic structure Hamiltonians. For the spin models studied our findings imply a significant advantage of the parity mapping compared to the standard gate model. In combination with full parallelizability of gates this has the potential to boost the race for demonstrating quantum advantage.

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Section: The Financial Crash Problemmentioning

confidence: 99%

Parity Quantum Optimization: Benchmarks

Fellner

Ender

Roeland

et al. 2023

Quantum

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“…Computer-based cognitive applications can be found in sociopolitical applications emerging throughout the 1990s [154,188]. The implementation of cognitive-like processes in computer-aided financial analysis has followed throughout the 20th century a comparable evolution to that of perception, decision-making and asset organisation in the military [50,179]. Arguably the most relevant of these cases is Blackrock's Aladdin financial analytics and risk management system.…”

Section: The Mental Of the Mechanicmentioning

confidence: 99%

Cognitive warfare

Pastor¹

2023

Preprint

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Military powers have consolidated in the last two decades a way to erase the boundaries between peacetime and crisis and wage a continuous war. Cognitive warfare (CW) has been proposed as the most advanced form to-date of manipulation of behaviour at mass scale to obtain strategic advantage. Instead of the corpse-ridden battlefields of kinetic warfare, the theatre of operations of CW is the human mind, and therein operations are realized on the fields of perception, emotion and memory. The goal is not termination but permanent control and exploitation. This opinion article reviews methods of CW focused on the human factors that may be manipulated not to merely control what populations think but how they think and thus how they act. It is argued that the weaponisation of sciences of brain and behaviour, combined with a distributed-computing technological millieu, can be utilised in CW to fine-tune societal and subject-level factors rendering not only all opposition infertile, but the very fact of being oppressed desirable.

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“…Furthermore, the open-source libraries for QA facilitate the specification of personalized hybrid workflows through the selection of diverse classical algorithms and embedding technologies, thus providing increased adaptability and customization. Owing to its ability to resolve intricate optimization issues, QA has found applications across various industry sectors such as finance [28][29][30], energy [31,32], transportation [33][34][35] and manufacturing [9,10]. In the context of JSSP, numerous investigations of QA have been conducted.…”

Section: 𝐻 = ∑ 𝑄mentioning

confidence: 99%

Solving flexible job shop scheduling problems in manufacturing with Quantum Annealing

Schworm

Glatt

et al. 2022

Prod. Eng. Res. Devel.

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Quantum Annealing (QA) is a metaheuristic for solving optimization problems in a time-efficient manner. Therefore, quantum mechanical effects are used to compute and evaluate many possible solutions of an optimization problem simultaneously. Recent studies have shown the potential of QA for solving such complex assignment problems within milliseconds. This also applies for the field of job shop scheduling, where the existing approaches however focus on small problem sizes. To assess the full potential of QA in this area for industry-scale problem formulations, it is necessary to consider larger problem instances and to evaluate the potentials of computing these job shop scheduling problems while finding a near-optimal solution in a time-efficient manner. Consequently, this paper presents a QA-based job shop scheduling. In particular, flexible job shop scheduling problems in various sizes are computed with QA, demonstrating the efficiency of the approach regarding scalability, solutions quality, and computing time. For the evaluation of the proposed approach, the solutions are compared in a scientific benchmark with state-of-the-art algorithms for solving flexible job shop scheduling problems. The results indicate that QA has the potential for solving flexible job shop scheduling problems in a time efficient manner. Even large problem instances can be computed within seconds, which offers the possibility for application in industry.

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Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer

Cited by 10 publications

References 41 publications

Parity Quantum Optimization: Benchmarks

Parity Quantum Optimization: Benchmarks

Cognitive warfare

Solving flexible job shop scheduling problems in manufacturing with Quantum Annealing

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