Hearing the Shape of the Ising Model with a Programmable Superconducting-Flux Annealer
arXiv:1307.1114 · doi:10.1038/srep05703
Abstract
Two objects can be distinguished if they have different measurable properties. Thus, distinguishability depends on the Physics of the objects. In considering graphs, we revisit the Ising model as a framework to define physically meaningful spectral invariants. In this context, we introduce a family of refinements of the classical spectrum and consider the quantum partition function. We demonstrate that the energy spectrum of the quantum Ising Hamiltonian is a stronger invariant than the classical one without refinements. For the purpose of implementing the related physical systems, we perform experiments on a programmable annealer with superconducting flux technology. Departing from the paradigm of adiabatic computation, we take advantage of a noisy evolution of the device to generate statistics of low energy states. The graphs considered in the experiments have the same classical partition functions, but different quantum spectra. The data obtained from the annealer distinguish non-isomorphic graphs via information contained in the classical refinements of the functions but not via the differences in the quantum spectra.
13 pages, 10 figures
References in corpus (2)
Cited by in corpus (17)
- What is the Computational Value of Finite Range Tunneling?
- Computational Role of Multiqubit Tunneling in a Quantum Annealer
- Consistency Tests of Classical and Quantum Models for a Quantum Annealer
- Modernizing Quantum Annealing using Local Searches
- Experimental quantum annealing: case study involving the graph isomorphism problem
- Nested Quantum Annealing Correction
- Maximum-Entropy Inference with a Programmable Annealer
- Quantum annealing correction at finite temperature: ferromagnetic -spin models
- Simulated Quantum Annealing with Two All-to-All Connectivity Schemes
- Scalable effective temperature reduction for quantum annealers via nested quantum annealing correction
- Adiabatic Quantum Optimization for Associative Memory Recall
- Fluctuation guided search in quantum annealing
- Error measurements for a quantum annealer using the one-dimensional Ising model with twisted boundaries
- Realization of Heisenberg models of spin systems with polar molecules in pendular states
- Performance Models for Split-execution Computing Systems
- Discriminating Non-Isomorphic Graphs with an Experimental Quantum Annealer
- An Overview of Approaches to Modernize Quantum Annealing Using Local Searches