Shuttling for Scalable Trapped-Ion Quantum Computers
- URL: http://arxiv.org/abs/2402.14065v1
- Date: Wed, 21 Feb 2024 19:00:04 GMT
- Title: Shuttling for Scalable Trapped-Ion Quantum Computers
- Authors: Daniel Schoenberger, Stefan Hillmich, Matthias Brandl, Robert Wille
- Abstract summary: Trapped-ion quantum computers exhibit promising potential to provide platforms for high-quality qubits and reliable quantum computation.
This paper proposes an efficient shuttling schedule, which orchestrates the movement operations within the device.
Even for large-scale QCCD devices, the empirical evaluation shows promising results with respect to the quality of the solution as well as performance.
- Score: 3.1066111470235462
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Trapped-ion quantum computers exhibit promising potential to provide
platforms for high-quality qubits and reliable quantum computation. 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,
e.g., a memory zone for storage and a processing zone for the actual
computation. 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. In this paper, we propose a
heuristic approach to finding an efficient shuttling schedule, which
orchestrates the movement operations within the device. Given a quantum
algorithm and a device architecture, the proposed algorithm produces shuttling
schedules with a close-to-minimal amount of time steps for small-size QCCD
architectures. Furthermore, even for large-scale QCCD devices, the empirical
evaluation shows promising results with respect to the quality of the solution
as well as performance.
Related papers
- Distributed Quantum Computing for Chemical Applications [10.679753825744964]
distributed quantum computing (DQC) aims at increasing compute power by spreading the compute processes across many devices.
DQC aims at increasing compute power by spreading the compute processes across many devices, with the goal to minimize the noise and circuit depth required by quantum devices.
arXiv Detail & Related papers (2024-08-09T21:42:51Z) - Subspace-Based Local Compilation of Variational Quantum Circuits for Large-Scale Quantum Many-Body Simulation [0.0]
This paper proposes a hybrid quantum-classical algorithm for compiling the time-evolution operator.
It achieves a 95% reduction in circuit depth compared to Trotterization while maintaining accuracy.
We estimate the gate count needed to execute the quantum simulations using the LSVQC on near-term quantum computing architectures.
arXiv Detail & Related papers (2024-07-19T09:50:01Z) - Mixed-Dimensional Qudit State Preparation Using Edge-Weighted Decision Diagrams [3.393749500700096]
Quantum computers have the potential to solve intractable problems.
One key element to exploiting this potential is the capability to efficiently prepare quantum states for multi-valued, or qudit, systems.
In this paper, we investigate quantum state preparation with a focus on mixed-dimensional systems.
arXiv Detail & Related papers (2024-06-05T18:00:01Z) - Parallel Quantum Computing Simulations via Quantum Accelerator Platform Virtualization [44.99833362998488]
We present a model for parallelizing simulation of quantum circuit executions.
The model can take advantage of its backend-agnostic features, enabling parallel quantum circuit execution over any target backend.
arXiv Detail & Related papers (2024-06-05T17:16:07Z) - On Reducing the Execution Latency of Superconducting Quantum Processors via Quantum Program Scheduling [48.142860424323395]
We introduce the Quantum Program Scheduling Problem (QPSP) to improve the utility efficiency of quantum resources.
Specifically, a quantum program scheduling method concerning the circuit width, number of measurement shots, and submission time of quantum programs is proposed to reduce the execution latency.
arXiv Detail & Related papers (2024-04-11T16:12:01Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum
Circuits [82.50620782471485]
QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits.
It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness.
Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
arXiv Detail & Related papers (2024-01-10T22:33:00Z) - Using Boolean Satisfiability for Exact Shuttling in Trapped-Ion Quantum
Computers [3.1066111470235462]
Trapped ions are a promising technology for building scalable quantum computers.
We propose a formalization of the possible movements in ion traps via Boolean satisfiability.
This formalization allows for determining the minimal number of time steps needed for a given quantum algorithm and device architecture.
arXiv Detail & Related papers (2023-11-06T19:00:22Z) - Iterative Qubits Management for Quantum Index Searching in a Hybrid
System [56.39703478198019]
IQuCS aims at index searching and counting in a quantum-classical hybrid system.
We implement IQuCS with Qiskit and conduct intensive experiments.
Results demonstrate that it reduces qubits consumption by up to 66.2%.
arXiv Detail & Related papers (2022-09-22T21:54:28Z) - Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources.
The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
arXiv Detail & Related papers (2022-09-16T02:37:32Z) - Field-deployable Quantum Memory for Quantum Networking [62.72060057360206]
We present a quantum memory engineered to meet real-world deployment and scaling challenges.
The memory technology utilizes a warm rubidium vapor as the storage medium, and operates at room temperature.
We demonstrate performance specifications of high-fidelity retrieval (95%) and low operation error $(10-2)$ at a storage time of 160 $mu s$ for single-photon level quantum memory operations.
arXiv Detail & Related papers (2022-05-26T00:33:13Z) - Cutting Quantum Circuits to Run on Quantum and Classical Platforms [25.18520278107402]
CutQC is a scalable hybrid computing approach that distributes a large quantum circuit onto quantum (QPU) and classical platforms ( CPU or GPU) for co-processing.
It achieves much higher quantum circuit evaluation fidelity than the large NISQ devices achieve in real-system runs.
arXiv Detail & Related papers (2022-05-12T02:09:38Z) - Hardware-Efficient, Fault-Tolerant Quantum Computation with Rydberg
Atoms [55.41644538483948]
We provide the first complete characterization of sources of error in a neutral-atom quantum computer.
We develop a novel and distinctly efficient method to address the most important errors associated with the decay of atomic qubits to states outside of the computational subspace.
Our protocols can be implemented in the near-term using state-of-the-art neutral atom platforms with qubits encoded in both alkali and alkaline-earth atoms.
arXiv Detail & Related papers (2021-05-27T23:29:53Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.