Floppy Qubit Tunneling Rate Tuning for Quantum Annealing Degeneracy
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Solution Overview
Problem
Quantum processors face challenges with degeneracy, leading to reduced optimality of solutions in hard optimization problems due to differences in tunneling rates among qubits, resulting in issues like small-gap avoided level crossings and Landau-Zener transitions.
Innovation Solution
The method involves mitigating degeneracy by tuning tunneling rates, either directly or indirectly, through techniques such as advancing or retarding 'floppy' qubits and adjusting magnetic susceptibility-based offsets to synchronize freeze-out times and reduce the incidence of avoided level crossings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If quantum processors use standard quantum annealing without degeneracy mitigation, then the system is simpler to operate, but the optimality of solutions deteriorates due to degeneracy-related issues
Solution Approach 1:
The system performs preliminary identification of floppy qubits and calculation of offsets before the main quantum annealing computation. This advance preparation allows the system to pre-establish correction strategies for degeneracy-prone qubits, improving solution optimality without adding complexity during the actual computation phase.
Solution Approach 2:
The patent applies degeneracy mitigation selectively to specific qubits identified as 'floppy' rather than uniformly to all qubits. By calculating individual offsets only for qubits that exhibit degeneracy-prone behavior, the system improves solution optimality while minimizing the additional complexity introduced by mitigation techniques.
2Reliability
If quantum processors advance or retard floppy qubits to synchronize freeze-out times, then the incidence of avoided level crossings is reduced, but the control mechanism becomes more complex
Solution Approach 1:
The system uses feedback by monitoring the freeze-out times of qubits during quantum annealing and dynamically adjusting the tunneling rates of floppy qubits accordingly. This feedback mechanism automatically synchronizes qubit behavior, reducing avoided level crossings while maintaining operational simplicity through self-regulation.
Solution Approach 2:
The patent changes the tunneling rate parameter of specific qubits (floppy qubits) to advance or retard their freeze-out times. By modifying this physical parameter selectively, the system achieves better synchronization and reduces degeneracy-related issues without requiring fundamental changes to the quantum processor architecture or operation.
3Reliability
If quantum processors use uniform tunneling rates for all qubits, then the control system is simpler, but the synchronicity of freeze-out times deteriorates leading to more degeneracy issues
Solution Approach 1:
The system applies different tunneling rates to different qubits based on their individual characteristics, particularly identifying 'floppy' qubits that require adjustment. This localized approach improves freeze-out synchronicity by tailoring control parameters to specific qubit needs rather than applying uniform control to all qubits.
Solution Approach 2:
The system performs preliminary identification and characterization of qubits to determine which ones are floppy and require offset adjustments. This advance analysis allows the system to establish individualized tunneling rate schedules before computation begins, improving synchronicity without adding complexity during runtime.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly boosts hardware performance on degeneracy-prone problems by improving the synchronicity of qubit freeze-out times, enhancing the optimality of generated solutions and reducing the incidence of degeneracy-related issues.
Implementation Method 1
quantum annealing may use quantum effects, such as quantum tunneling, as a source of delocalization to reach an energy minimum more accurately and/or more quickly than classical annealing
Implementation Method 2
A quantum computer is a system that makes direct use of at least one quantum-mechanical phenomenon, such as, superposition, tunneling, and entanglement, to perform operations on data
Implementation Method 3
A particular example is realized by an implementation of superconducting qubits
Data Source
AI summary
Degeneracy in analog processor (e.g., quantum processor) operation is mitigated via use of floppy qubits or domains of floppy qubits (i.e., qubit(s) for which the state can be flipped with no change in energy), which can significantly boost hardware performance on certain problems, as well as improve hardware performance for more general problem sets. Samples are drawn from an analog processor, and devices comprising the analog processor evaluated for floppiness. A normalized floppiness metric is calculated, and an offset added to advance the device in annealing. Degeneracy in a hybrid computing system that comprises a quantum processor is mitigated by determining a magnetic susceptibility of a qubit, and tuning a tunneling rate for the qubit based on a tunneling rate offset determined based on the magnetic susceptibility. Quantum annealing evolution is controlled by causing the evolution to pause for a determined pause duration.