Quantum Annealing in Sherrington-Kirkpatrick Spin Glass in Presence of Time-Dependent Longitudinal Field
Atanu Rajak, Bikas K Chakrabarti

TL;DR
This paper investigates quantum annealing in the Sherrington-Kirkpatrick spin glass model with a time-dependent longitudinal field, demonstrating improved ground state probability and phase boundary effects through numerical simulations.
Contribution
It introduces a novel study of quantum annealing with both transverse and longitudinal fields, showing advantages of annealing the longitudinal field and analyzing phase transitions.
Findings
Longitudinal field annealing enhances ground state probability.
Quantum tunneling affects the Almeida-Thouless phase boundary.
Longitudinal field induces ergodicity in the quantum SK model.
Abstract
Motivated by the recent development of quantum technology using quantum annealing technique and the recent works on the static properties of the Sherrington-Kirkpatrick (SK) spin glass model, we study quantum annealing of the spin glass model by tuning both transverse and longitudinal fields. We numerically solve the time-dependent Schr\"odinger equation of the total Hamiltonian when both the fields are made time-dependent and eventually vanish at the same time. We have computed the time-evolution of the probability of finding the system in one of two degenerate ground states of the classical spin glass. At the end of annealing, using the configuration averaged probability, we have shown a clear advantage while the longitudinal field is annealed rather than keeping it constant throughout the process of quantum annealing. We further investigate the order parameter distribution of a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTheoretical and Computational Physics · Complex Network Analysis Techniques · Neural Networks and Reservoir Computing
