A study by Cristian Micheletti and Francesco Slongo of SISSA, Philipp Hauke of the University of Trento, and Pietro Faccioli of the University of Milano-Bicocca, published in Science Advances, demonstrates how quantum computing can be used to discover new properties of polymer systems. The team used a mathematical approach called QUBO, suited for quantum computers known as “quantum annealers”, to simulate dense polymer mixtures. The method significantly improved computational performance compared to traditional techniques, even when used on conventional computers. The research, funded by NextGenerationEU and the European Union’s Horizon Europe program, could have far-reaching implications for understanding molecular systems.
“Simulation techniques known as ‘Monte Carlo’ have long been among the most powerful, elegant, and versatile methods for studying complex systems, such as synthetic polymers or biological ones, such as DNA”
Cristian Micheletti
Quantum Computing and Polymeric Materials Simulation
A recent study published in Science Advances has demonstrated how quantum computing can uncover new properties of polymer systems, which are crucial in biology and material science. Quantum computing offers new possibilities for solving problems that are currently beyond the capabilities of conventional computers, including issues in cryptography, pharmacology, and the physical and chemical properties of molecules and materials. However, the computational capabilities of current quantum computers are still relatively limited.
The research team, consisting of scientists from SISSA in Trieste, the University of Trento, and the University of Milano-Bicocca, used a mathematical approach called QUBO (Quadratic Unconstraint Binary Optimization). This approach is ideally suited for specific quantum computers, known as “quantum annealers“. The team used the QUBO approach to simulate dense polymer mixtures in a new way, resulting in a significant increase in computational performance compared to traditional techniques.
The QUBO Approach and Its Effectiveness
The QUBO approach was particularly effective, even when used on conventional computers, enabling researchers to discover surprising properties of the simulated polymer mixtures. The implications of this are potentially far-reaching, as the approach used in the study is naturally suited to be transferred to many other molecular systems.
Simulation techniques, such as ‘Monte Carlo’, have long been among the most powerful and versatile methods for studying complex systems, such as synthetic polymers or biological ones, like DNA. However, the efficiency of these methods decreases as the system density and size increase. Studying realistic systems, such as the organisation of chromosomes in the cell nucleus, requires significant computational resources. Quantum computers promise major boosts of computational performance, albeit with the inevitable limitations of novel technologies.
“Quantum computers promise major boosts of computational performance, albeit with the inevitable limitations of novel technologies. And this is where the new simulation strategy comes in, which is ideally suited to today’s pioneering quantum computers, and yet can be successfully transferred even to traditional computers.”
Francesco Slongo
Quantum Computing Inspiring New Perspectives
The new simulation strategy is ideally suited to today’s pioneering quantum computers and can be successfully transferred even to traditional computers. Quantum machines dedicated to solving QUBO already exist and can be highly effective. The research team reformulated conventional polymer models in the QUBO framework to optimally exploit such machines. Surprisingly, the QUBO reformulation also proved advantageous on traditional computers, allowing faster simulation of dense polymers than with established methods.
Implications and Future Directions of Quantum Computing
Physical models created to take full advantage of innovative computing technologies have often been transferred to different areas. The best-known case is that of lattice-based fluid models designed for 1990s supercomputers but now widely used for many other systems and types of computers. The study in Science Advances provides a further example, demonstrating how methodologies inspired by quantum computing can pave the way for exploring new materials and understanding the workings of molecular systems of biological interest.
“Currently, there already exist quantum machines dedicated to solving QUBO, and they can be highly effective. We reformulated conventional polymer models in the QUBO framework to optimally exploit such machines. Surprisingly, the QUBO reformulation also proved advantageous on traditional computers, allowing faster simulation of dense polymers than with established methods. Thanks to this, we established previously unknown properties for these systems, all using standard computers.”
Philipp Hauke and Pietro Faccioli
Summary
A recent study has demonstrated how quantum computing can be utilized to discover new properties of polymer systems, which are crucial in biology and material science. The research used a mathematical approach called QUBO, which, when applied to quantum computers, significantly boosted computational performance and revealed surprising properties of the simulated polymer mixtures.
- A new study published in Science Advances demonstrates the potential of quantum computing in discovering new properties of polymer systems, which are crucial in biology and material science.
- The research team, including Cristian Micheletti and Francesco Slongo of SISSA, Philipp Hauke of the University of Trento, and Pietro Faccioli of the University of Milano-Bicocca, used a mathematical approach called QUBO (Quadratic Unconstraint Binary Optimization) suitable for specific quantum computers known as “quantum annealers”.
- The QUBO approach was used to simulate dense polymer mixtures in a novel way, resulting in a significant increase in computational performance compared to traditional techniques.
- The QUBO approach was also effective when used on conventional computers, leading to the discovery of surprising properties of the simulated polymer mixtures.
- The approach used in the study can potentially be applied to many other molecular systems.