Adaptive sparse sampling for quasiparticle interference imaging

Area of Science:

• Condensed Matter Physics
• Materials Science
• Surface Science

Background:

• Quasiparticle interference imaging (QPI) reveals quantum material band structures via Fourier transforms of local density of states (LDOS).
• Traditional QPI requires extensive scanning tunneling microscopy (STM) measurements, often taking days.
• Sparse sampling techniques have been proposed to reduce QPI measurement time.

Purpose of the Study:

• To introduce and validate an adaptive sparse sampling (ASS) approach for efficient QPI.
• To enable controllable interruption and resumption of QPI measurements.
• To improve the quality and reduce the time required for QPI data acquisition.

Main Methods:

• Implemented an adaptive sparse sampling (ASS) strategy using compressive sensing recovery.
• Gradually accumulated sparsely sampled LDOS measurements until a target quality was achieved.
• Interleaved LDOS measurements with topographic images for registry, drift correction, and resuming measurements.

Main Results:

• Demonstrated a method to achieve high-quality QPI images with significantly reduced measurement time.
• Showcased the ability to interrupt and resume QPI measurements without data loss.
• Validated the effectiveness of scattering wave conserving background subtractions.

Conclusions:

• The adaptive sparse sampling (ASS) approach offers a practical and efficient extension to QPI.
• ASS removes hesitations in implementing sparse sampling for QPI, facilitating faster quantum material characterization.
• This method enhances the feasibility of studying complex band structures through reduced experimental effort.