IBM Quantum Computers: Evolution, Performance, and Future Directions

TL;DR

The paper surveys IBM Quantum's evolution from early cloud-access experiments to large-scale superconducting processors, detailing hardware generations (Canary to Condor), performance metrics, and the software stack (Qiskit) that enables scaling to hundreds of qubits. It highlights innovations in qubit layouts (heavy-hex), modular System Two, and substantial milestones such as Condor's 1,121-qubit processor and Heron's 133–156 qubits, underpinned by performance metrics like coherence times and gate fidelities. The work also covers practical pathways toward usable quantum computing, including a roadmap to quantum-centric supercomputing and quantum-safe cryptography, along with demonstrations that parallelism and dynamic circuits can push beyond brute-force classical simulations. These insights illuminate IBM Quantum's trajectory toward utility-scale quantum computation and its potential impact on science, industry, and cybersecurity, while underscoring the need for continued collaboration and investment. The narrative emphasizes concrete hardware progress, software tooling, and a forward-looking agenda to achieve fault-tolerant, scalable quantum computing with practical applications.

Abstract

Quantum computers represent a transformative frontier in computational technology, promising exponential speedups beyond classical computing limits. IBM Quantum has led significant advancements in both hardware and software, providing access to quantum hardware via IBM Cloud since 2016, achieving a milestone with the world's first accessible quantum computer. This article explores IBM's quantum computing journey, focusing on the development of practical quantum computers. We summarize the evolution and advancements of IBM Quantum's processors across generations, including their recent breakthrough surpassing the 1,000-qubit barrier. The paper reviews detailed performance metrics across various hardware, tracing their evolution over time and highlighting IBM Quantum's transition from the noisy intermediate-scale quantum (NISQ) computing era towards fault-tolerant quantum computing capabilities.

Figures (8)

• Figure 1: IBM's latest quantum processor Condor, unveiled in 2023, features 1,121 superconducting qubits arranged in a honeycomb configuration. (Credit: Ryan Lavine, IBM).
• Figure 2: IBM Quantum System Two, unveiled at the IBM Quantum Summit 2023, represents IBM’s first modular quantum computer and serves as a foundational element in IBM’s quantum-centric supercomputing architecture. (Image source: IBM Quantum).
• Figure 3: IBM Quantum's Eagle processors family configuration. These processors utilize a heavy-hexagonal qubit layout, where qubits connect with two or three neighboring qubits resembling edges and corners of tessellated hexagons. This design reduces errors caused by interactions between adjacent qubits, thereby improving processor reliability and functionality while maintaining high performance.
• Figure 4: Readout error map and layout of the ibm_sherbrooke quantum computer. This quantum system is based on an Eagle r3 quantum processor, featuring 127 superconducting transmon qubits. Key performance metrics include median ECR error: $7.571 \times 10^{-3}$, median SX error: $2.411 \times 10^{-4}$ median readout error: $1.350 \times 10^{-2}$ median T1: 262.69 $\mu$s, and median T2: 176.67 $\mu$s, as of August 1, 2024.
• Figure 5: Qiskit's software architecture: The quantum info module links circuits to quantum information mathematics. The transpiler optimizes circuits via a pass manager, considering ISA and constraints. Primitives run circuits on simulators or hardware, evaluating results. Visualization tools and serialization with OpenQASM QCQiskit31 and QPY format are also included QCQiskit54. Regenerated under a Creative Commons license ( https://creativecommons.org/licenses/by/4.0/) from QCQiskit.