Quantum Computers Model Particle Scattering

Courtesy of LLNL

Scattering takes place across the universe at large and miniscule scales. Billiard balls clank off each other in bars, the nuclei of atoms collide to power the stars and create heavy elements, and even sound waves deviate from their original trajectory when they hit particles in the air.

Understanding such scattering can lead to discoveries about the forces that govern the universe. In a recent publication in Physical Review C, researchers from Lawrence Livermore National Laboratory (LLNL), the InQubator for Quantum Simulations and the University of Trento developed an algorithm for a quantum computer that accurately simulates scattering.

"Scattering experiments help us probe fundamental particles and their interactions," said LLNL scientist Sofia Quaglioni. "The scattering of particles in matter [materials, atoms, molecules, nuclei] helps us understand how that matter is organized at a microscopic level."

The work examines nonrelativistic elastic scattering, in which the speed of the particle is much slower than the speed of light and the projectile particle bounces off a stationary target particle without losing any of its energy.

Including more particles in a simulation increases the required computational resources exponentially. Classical computers often struggle to keep up, but quantum computers can encode and process a larger amount of information.

"Quantum computers are naturally good at realizing the time evolution of two interacting particles, which is directly connected to the scattering of the particles," said Quaglioni.

"High-performance computing simulations based on microscopic physics for nuclei relevant to stellar explosions would require a moon-scale supercomputer," added LLNL scientist Kyle Wendt.

The team's algorithm takes in the initial state of the particle system (describing the projectile particle and the target particle traveling toward each other), as well as information about the interactions between the two. From there, it plays the scattering forward in time in steps and tracks the impact of the collision using a detector and a variational "trick."

In quantum mechanics, particles also behave likes waves. When particles scatter, it shifts the position of their wave within its cycle. At each step, the algorithm measures this shift by creating and varying a detector wave until it matches the particles' wave.

To test the algorithm, the researchers emulated it on a classical computer. Once the reliability was confirmed, they performed simulations on IBM quantum processors. The variational trick employed to measure the shift in the wave of scattered particles proved to be resilient against the noise sources that challenge current advancements in quantum computing hardware.

The proposed quantum algorithm's robustness against quantum hardware noise, coupled with its scaling primarily driven by the dynamics of real-time evolution, represents a significant advancement in the field of quantum simulations.

While this method was demonstrated on the simplest scattering process in the simplest scenario, it can be extended to more complex processes that presently escape classical high-performance computing for all but the smallest number of particles.

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