Quantum-inspired optimization for wavelength assignment

Problems related to wavelength assignment (WA) in optical communications networks involve allocating transmission wavelengths for known transmission paths between nodes that minimize a certain objective function, for example, the total number of wavelengths. Playing a central role in modern telecommunications, this problem belongs to NP-complete class for a general case so that obtaining optimal solutions for industry-relevant cases is exponentially hard. In this work, we propose and develop a quantum-inspired algorithm for solving the wavelength assignment problem. We propose an advanced embedding procedure to transform this problem into the quadratic unconstrained binary optimization (QUBO) form, having a improvement in the number of iterations with price-to-pay being a slight increase in the number of variables (“spins”). Then, we compare a quantum-inspired technique for solving the corresponding QUBO form against classical heuristic and industrial combinatorial solvers. The obtained numerical results indicate on an advantage of the quantum-inspired approach in a substantial number of test cases against the industrial combinatorial solver that works in the standard setting. Our results pave the way to the use of quantum-inspired algorithms for practical problems in telecommunications and open a perspective for further analysis of the use of quantum computing devices

Potential for improving the efficiency of carbonate oil deposits waterflooding with the use of controlled salinity technology (Smart water) at fields of Tatarstan Republic

The article provides an overview of ion-modified waterflooding technology, also known as low salinity, controlled salinity, or Smart water. This technology is currently considered one of the most promising approaches in the development of oil deposits in carbonate reservoirs due to its economic efficiency and environmental safety. The article discusses the main mechanisms and processes underlying ion-modified waterflooding and presents the results of laboratory studies conducted on core samples from foreign oil deposits. It includes an analysis of several studies, including contact angle measurements and core flooding experiments on core samples from oil deposits in carbonate reservoirs on the eastern side of the Melekess depression in the Republic of Tatarstan. It is important to note that the Vereyian deposits explored in this article are not a typical example of test objects for ion-modified water injection. This is because they are characterized by a low reservoir temperature of 23 °C, which suggests that the efficiency of the technology would likely be lower compared to studies conducted abroad, where reservoir temperatures were significantly higher. For example, Darvish Sarvestani et al. studied reservoir conditions at 90 °C, Yousef et al. – reservoir temperature of 100 °C, and Austad et al. examined the Ekofisk field at 130 °C and the Volhall field at 90 °C in Norway. However, as several studies have indicated, prolonged contact between rock samples and ion-modified water contributes to significant hydrophilization of the rock surface, as confirmed by contact angle measurements. The contact angle decreases from approximately 138.3° to 53.45° after exposure to ion-modified water. Additionally, the core flooding experiment demonstrated a slight increase in the oil displacement coefficient, reaching 9.2%. These findings suggest the potential for enhanced oil recovery by injecting Smart water into the Vereyian sediments, although further research is required to confirm the underlying mechanism

DataSheet1_Quantum-inspired optimization for wavelength assignment.PDF

Problems related to wavelength assignment (WA) in optical communications networks involve allocating transmission wavelengths for known transmission paths between nodes that minimize a certain objective function, for example, the total number of wavelengths. Playing a central role in modern telecommunications, this problem belongs to NP-complete class for a general case so that obtaining optimal solutions for industry-relevant cases is exponentially hard. In this work, we propose and develop a quantum-inspired algorithm for solving the wavelength assignment problem. We propose an advanced embedding procedure to transform this problem into the quadratic unconstrained binary optimization (QUBO) form, having a improvement in the number of iterations with price-to-pay being a slight increase in the number of variables (“spins”). Then, we compare a quantum-inspired technique for solving the corresponding QUBO form against classical heuristic and industrial combinatorial solvers. The obtained numerical results indicate on an advantage of the quantum-inspired approach in a substantial number of test cases against the industrial combinatorial solver that works in the standard setting. Our results pave the way to the use of quantum-inspired algorithms for practical problems in telecommunications and open a perspective for further analysis of the use of quantum computing devices.</p