MONTREAL, May 08, 2024 (GLOBE NEWSWIRE) -- InfinityQ Technology, a pioneer in quantum-inspired computing, proudly presented its cutting-edge research at the 2024 Optimization Days Conference. Leveraging the power of the TitanQ platform, these studies showcase unprecedented advancements in clustering, portfolio optimization, and job shop scheduling, cementing InfinityQ's position at the forefront of technological innovation.
“These presentations underscore InfinityQ's commitment to pushing the boundaries of quantum-inspired computing,” says Aurélie Hélouis, Founder and CEO of InfinityQ. "By harnessing the power of TitanQ, we are unlocking new frontiers in data analysis, financial optimization, and production scheduling, empowering industries to achieve unprecedented levels of efficiency and performance."
1. Quantum-Inspired Methods for Clustering Large Datasets
Presented by Brian Mao, Head of Algorithms at InfinityQ
Titled "Quantum-Inspired Methods for Clustering Large Datasets," Mao addresses the limitations of traditional clustering algorithms and introduces a novel approach to enhance cluster quality while accommodating real-world constraints. Key highlights include the utilization of TitanQ for solving clustering problems via distance minimization, integration of quantum-inspired techniques for large-scale problem-solving, and benchmarking against industry-standard algorithms.
2. Portfolio Optimization Driven by Quantum-Inspired Techniques
Presented by Ethan Wang, Mathematical Algorithms Developer at InfinityQ
In "Portfolio Optimization Driven by Quantum-Inspired Techniques," Wang tackles the complexities of portfolio optimization in the fast-paced world of quantitative finance. Leveraging TitanQ, the study introduces a strategy to enhance portfolio selection by mapping the subset selection problem to a Quadratic Unconstrained Binary Optimization (QUBO) formulation. Backed by historical data analysis, this approach demonstrates superior performance in expected return and risk reduction across diverse portfolios.
3. Solving the Job Shop Scheduling Problem with the TitanQ Quantum-Inspired Solver
Presented by Ali M’hammedi Alaoui, Mathematical Programming Developer at InfinityQ
Through "Solving the Job Shop Scheduling Problem with the TitanQ Quantum-Inspired Solver," M’hammedi Alaoui presents a groundbreaking approach to one of the most challenging combinatorial optimization problems. By formulating the Job Shop Scheduling Problem (JSSP) as a QUBO expression, InfinityQ pioneers a scalable solution that surpasses conventional methods. Through extensive experimentation, the study showcases unparalleled performance gains and scalability in tackling complex scheduling challenges.
InfinityQ's dedication to innovation continues to drive advancements across diverse domains, offering transformative solutions to complex real-world challenges. The opportunity to present their research at the 2024 Optimization Days Conference is a testament to InfinityQ’s commitment to collaboration and knowledge exchange within the scientific community, thereby driving collective progress toward a future enriched by quantum-inspired solutions.
About InfinityQ:
InfinityQ Technology Inc. is a Canadian, woman-founded company at the forefront of quantum-inspired technologies. InfinityQ provides simple solutions to seemingly impossible computational and optimization problems across sectors such as Last Mile Delivery, Transport & Logistics, Life Sciences, and Energy. InfinityQ’s technology outperforms classical computers in speed and surpasses existing pure-quantum technologies in accuracy, efficiency, sustainability, and cost. By unlocking the full potential of quantum-inspired computing in real-time, InfinityQ is actively shaping the future of technology and innovation. For more information, visit www.infinityq.tech.
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