Fermionic quantum turbulence: Pushing the limits of high-performance computing

Area of Science:

• Quantum simulation
• Astrophysical phenomena
• Condensed matter physics

Background:

• Ultracold atoms offer a controllable platform for analog quantum simulation.
• Quantum turbulence in ultracold atoms may explain astrophysical phenomena like pulsar glitches.
• Simulating fermionic quantum turbulence presents significant computational challenges.

Purpose of the Study:

• To perform the largest simulations of fermionic quantum turbulence to date.
• To identify necessary computing technologies for advancing quantum turbulence simulations.
• To investigate dissipation and thermalization processes in fermionic quantum turbulence.

Main Methods:

• Utilized ultracold atoms as an analog quantum computing platform.
• Developed and employed improved Eigenvalue soLvers for Petaflop Applications (ESPLA) library for large-scale matrix diagonalization.
• Analyzed the internal structure of vortices as a probe for local effective temperature.

Main Results:

• Successfully executed the largest fermionic quantum turbulence simulations on record.
• Demonstrated the capability to diagonalize matrices of millions by millions.
• Quantified dissipation and thermalization by correlating vortex structure with local effective temperature.

Conclusions:

• Ultracold atom simulations are crucial for understanding quantum turbulence and astrophysical phenomena.
• Advancements in computational methods, particularly eigenvalue solvers, are essential for pushing simulation boundaries.
• The internal structure of vortices provides a novel and effective method for measuring local temperature in quantum turbulence.