Trapped-Ion Quantum Computers: A Promising Solution with Quantum Charge Coupled Device?

Quantum computing, which uses quantum mechanical effects to solve complex problems, is being heavily researched by companies like IBM, Google, and Microsoft. Among the various physical technologies, trapped-ion quantum computers are seen as a promising candidate. The Quantum Charge Coupled Device (QCCD) architecture is a modular solution that enables scalable quantum computers. However, scaling these computers requires efficient movement of ions on a QCCD architecture. This paper proposes a heuristic approach to generate an efficient shuttling schedule for a given quantum circuit on a QCCD architecture. The approach has shown promising results in empirical evaluations.

What is the Potential of Trapped-Ion Quantum Computers?

Quantum computing is a new paradigm that promises to solve certain problems which are computationally intractable on classical computers. Famous examples include Shor’s algorithm to factorize integers and Grover’s search for unstructured data. Quantum computing also has potential applications in quantum chemistry. The advantage of quantum computing lies in the exploitation of quantum mechanical effects such as superposition, where a quantum state can assume a combination of basis states, and entanglement, where qubits can lose their locality and can no longer be described individually.

Several companies, including IBM, Alphabet (Google), Microsoft, Rigetti, AQT, Infineon Technologies, and IonQ, have heavily invested in research towards quantum computing. Among the possible physical technologies such as superconducting quantum computers, neutral atom quantum computers, and optical quantum computers, trapped-ion quantum computers are one of the most promising candidates to show quantum advantage in the foreseeable future.

How Does the Quantum Charge Coupled Device (QCCD) Architecture Work?

The Quantum Charge Coupled Device (QCCD) architecture offers a modular solution to enable the realization of scalable quantum computers, paving the way for practical quantum algorithms with large qubit numbers. Within these devices, ions can be shuttled (moved) throughout the trap and through different dedicated zones, such as a memory zone for storage and a processing zone for the actual computation.

The qubits are encoded into ions that are trapped by electromagnetic fields. By manipulating these fields, the ions can be moved on the architecture. However, due to the decoherence of the ions’ quantum states, the qubits lose their quantum information over time. Thus, the required time steps of shuttling operations should be minimized.

What is the Challenge in Scaling Trapped-Ion Quantum Computers?

The scaling of trapped-ion quantum computers requires corresponding tooling support to exploit the full potential. Without proper support, there is the possibility that powerful trapped-ion quantum computers will be available, but there will be no means to use that power. For ion traps in particular, efficiently moving (i.e., shuttling) the ions on a QCCD architecture is an important problem since unnecessary movement not only increases the required time but also the likelihood of errors due to decoherence.

Determining efficient schedules, also referred to as sequences of the movement, is paramount for useful computations in trapped-ion quantum computers. First solutions addressing this problem have been proposed, however, the considered architectures are comparatively simple and do not cover a large part of possible QCCD architectures.

How Can We Generate an Efficient Shuttling Schedule?

In this paper, a heuristic approach to generating an efficient shuttling schedule for a given quantum circuit to be executed on a QCCD architecture is proposed. A two-step approach is proposed. First, the logical qubits in the quantum circuit are mapped to the physical ions in ion chains, and subsequently, the sequence of chains is generated.

Second, a graph-based abstraction of the underlying physical hardware that represents linear ion traps and junctions is introduced. Based on this graph, efficient shuttling schedules without conflicts are generated by exploiting cycles in the graph representation. This enables movement on short paths without expensive backtracking to move potentially blocking ion chains out of the way.

What are the Results of the Proposed Approach?

Empirical evaluations confirm the efficacy of the proposed approach with a close-to-minimal amount of time steps for small architectures and promising results for larger ones. This includes both the resulting schedule, i.e., the number of time steps required to execute the quantum algorithm, as well as the classical generation of the schedule in the first place. An open-source implementation of the proposed approach is publicly available.

In conclusion, the proposed approach offers a promising solution to the challenge of efficiently shuttling ions in trapped-ion quantum computers, thereby paving the way for the practical application of these devices in solving complex computational problems.