From scheduling flights to planning delivery routes or arranging phone networks, many everyday challenges come down to what scientists call combinatorial optimization problems.
These are puzzles with countless possible solutions, where the goal is to find the most efficient one.
While today’s computers are powerful, they often struggle with these kinds of problems because of physical limits on how much processing power can be squeezed into a chip.
On top of that, training advanced artificial intelligence models consumes enormous amounts of energy.
Now, researchers at UCLA and UC Riverside have created a new type of computer architecture that could change the game.
Instead of relying on digital bits like traditional machines, their design processes information through a network of oscillators—tiny systems that move back and forth at steady rhythms or frequencies.
When all the oscillators sync up, the system has effectively solved the optimization problem.
This approach is known as an Ising machine, a physics-inspired computer model that uses parallel computing.
Parallel computing means it can handle many calculations at the same time, making it especially powerful for complex tasks. The researchers demonstrated that this method allows optimization problems to be solved faster and more efficiently than traditional digital approaches.
What makes this discovery stand out is that their device operates at room temperature.
Many other physics-based or quantum computing systems require ultra-cold environments to work properly, which makes them difficult and expensive to use. In contrast, the UCLA–UC Riverside team’s system is based on a special “quantum material” that links electrical activity with vibrations inside the material itself.
This connection bridges the strange world of quantum mechanics with the more familiar rules of everyday physics.
Their prototype uses a form of tantalum sulfide, which allows switching between electrical and vibrational phases. This property makes it ideal for creating the coupled oscillators that power the machine. Because it works at room temperature, the design avoids one of the biggest obstacles in developing quantum-inspired hardware.
Professor Alexander Balandin, the lead researcher, explained that this new kind of computing doesn’t just mimic traditional digital operations—it actually uses the laws of physics to perform the calculations directly. That’s why it can be much faster and more energy-efficient than current methods.
Another promising feature of this design is that it could integrate with existing silicon technology, the foundation of nearly all modern electronics. “Any new physics-based hardware has to work with standard digital silicon technology to make an impact,” Balandin said. The material they chose makes that integration possible, opening the door to real-world applications.
The prototype was built at UCLA’s Nanofabrication Laboratory and tested in their Phonon Optimized Engineered Materials lab.
While still early in development, this research hints at a future where physics-inspired computers could help us solve some of the most complex challenges in science, engineering, and daily life—all while using far less energy than current technologies.
