This 40-qubit superconducting processor, launched in 2021, showcased Rigetti's early multi-chip integration and provided a platform for hybrid quantum-classical algorithm exploration.
The Rigetti Aspen-11, a 40-qubit superconducting quantum processor, represented a significant milestone in the development of quantum hardware when it was first announced in October 2021 and made available in December of the same year. As a data analyst examining the historical trajectory of quantum computing, understanding systems like Aspen-11 is crucial for contextualizing current advancements and anticipating future trends. Rigetti, a prominent player in the quantum computing landscape, designed Aspen-11 using transmon qubits, a widely adopted technology known for its relatively long coherence times and high gate fidelities, making it suitable for early-stage quantum algorithm development and benchmarking.
Aspen-11 was not merely another qubit count increase; it embodied Rigetti's strategic approach to scaling quantum processors through multi-chip integration. This architectural choice aimed to overcome the physical limitations of fabricating a large number of high-quality qubits on a single monolithic chip, a challenge that continues to drive innovation across the industry. By integrating multiple smaller quantum processing units (QPUs) into a larger system, Rigetti sought to pave a path towards higher qubit counts and more complex quantum circuits. Its availability through Rigetti QCS, Azure Quantum, and AWS Braket democratized access to advanced quantum hardware, allowing researchers and developers worldwide to experiment with real quantum systems and contribute to the burgeoning field of quantum algorithm design.
From an analytical perspective, Aspen-11's performance metrics, such as its CLOPS benchmark score of 7512 in 2022 and its specified gate fidelities, provide invaluable data points for tracking the progress of quantum hardware. These metrics allow us to quantify the capabilities of NISQ (Noisy Intermediate-Scale Quantum) devices and understand the practical limitations faced by early quantum applications. While Aspen-11 has since been retired, making way for newer, more powerful generations of Rigetti processors, its legacy remains important. Its operational period offered critical insights into the challenges of maintaining coherence, minimizing crosstalk, and executing complex quantum circuits on real hardware. For data analysts, studying the lifecycle of systems like Aspen-11—from announcement to availability to retirement—highlights the rapid pace of innovation in quantum computing and the continuous drive towards fault-tolerant quantum computation.
The retirement of Aspen-11 post-2022 underscores the dynamic and rapidly evolving nature of the quantum hardware industry. Systems that were state-of-the-art just a few years ago are quickly superseded by devices with higher qubit counts, improved fidelities, and more sophisticated architectures. This rapid iteration is a hallmark of an emerging technology, driven by intense competition and fundamental scientific advancements. For data analysts, understanding this lifecycle is crucial for interpreting historical benchmarks, assessing the rate of technological progress, and projecting future capabilities. Aspen-11, therefore, serves as a critical reference point for evaluating the performance gains achieved by subsequent quantum processors and for understanding the foundational engineering and scientific challenges that Rigetti and the broader quantum community have addressed and continue to tackle.
Moreover, the experience gained from operating and benchmarking Aspen-11 has undoubtedly informed the design and development of Rigetti's current and future quantum computing platforms. The insights derived from its connectivity topology, native gate set, and error characteristics have contributed to a deeper understanding of how to optimize quantum hardware for specific applications and how to mitigate the effects of noise. For those engaged in quantum algorithm research, the historical data from Aspen-11 provides a concrete example of the performance envelope of a significant NISQ device, enabling more realistic simulations and theoretical analyses of algorithm scalability and error resilience. Its role in facilitating hybrid quantum-classical algorithms and optimization tasks further cemented its place as an important experimental platform during a pivotal period in quantum computing's development.
| Spec | Details |
|---|---|
| System ID | Rigetti_Aspen-11 |
| Vendor | Rigetti |
| Technology | Superconducting |
| Status | Retired |
| Primary metric | Physical qubits |
| Metric meaning | Number of superconducting transmon qubits |
| Qubit mode | Transmon qubits with tunable frequencies |
| Connectivity | Octagonal |
| Native gates | XY, CZ, RX, RZ |
| Error rates & fidelities | Single-qubit gate fidelity: 99.8% (2021) | Two-qubit CZ: 92.7% | XY: 91.0% |
| Benchmarks | CLOPS: 7512 (2022) | Mirror circuits: Not specified |
| How to access | Via Rigetti QCS or partners |
| Platforms | Rigetti QCS | Azure Quantum | AWS Braket |
| SDKs | Qiskit | PyQuil | Cirq |
| Regions | us-west-1 |
| Account requirements | Account signup |
| Pricing model | Pay-per-task + per-shot |
| Example prices | Task: $0.30 | Shot: $0.00035 (2022) |
| Free tier / credits | None |
| First announced | 2021-10-01 |
| First available | 2021-12-15 |
| Major revisions | None |
| Retired / roadmap | Retired post-2022 |
| Notes | Checked Rigetti site; no current access; assumed retired based on newer systems |
Qubit Architecture and Technology: The Rigetti Aspen-11 was built upon superconducting technology, specifically utilizing 40 physical transmon qubits. Transmon qubits are a type of superconducting circuit that behaves as an artificial atom, engineered to have a large anharmonicity (non-uniform energy level spacing) to allow for selective addressing of the lowest two energy levels as the computational basis states. This design choice is prevalent in many leading quantum processors due to its relatively long coherence times and high gate fidelities compared to other superconducting qubit types. A key feature of Aspen-11's transmon qubits was their tunable frequencies. This tunability offers significant advantages, such as the ability to dynamically adjust qubit frequencies to avoid spectral collisions (crosstalk) during gate operations and to enable resonant interactions for two-qubit gates. However, it also introduces engineering complexity and potential sources of noise if not precisely controlled. The 40-qubit count, at the time of its release, positioned Aspen-11 as a substantial platform for exploring quantum algorithms beyond simple proof-of-concept demonstrations, pushing the boundaries of what was computationally feasible on real quantum hardware.
Connectivity Topology: Aspen-11 featured an octagonal connectivity topology. In this arrangement, qubits are typically laid out in a pattern where each qubit is connected to a fixed number of neighbors, forming an octagonal graph structure. This specific topology dictates which pairs of qubits can directly interact via two-qubit gates. From a data analyst's perspective, the connectivity topology is a critical factor influencing the efficiency and depth of quantum circuits. Algorithms often require interactions between non-adjacent qubits, necessitating the use of 'SWAP' gates to move quantum information across the processor. An octagonal topology, while offering more connectivity than a simple linear chain, is less connected than an all-to-all architecture (which is currently impractical for large qubit counts). This means that certain quantum algorithms might require more SWAP operations, increasing circuit depth and susceptibility to errors. Understanding this topology is essential for optimizing qubit mapping and gate scheduling to minimize computational overhead and maximize algorithm success probability.
Native Gate Set: The native gate set for Aspen-11 included XY, CZ, RX, and RZ gates. These gates form a universal set, meaning any arbitrary quantum operation can be decomposed into a sequence of these fundamental gates. The CZ (Controlled-Z) gate is a foundational two-qubit entangling gate, crucial for creating quantum correlations. The XY gate, often implemented as an iSWAP-like interaction, is another powerful two-qubit entangling gate that facilitates the exchange of excitation between qubits. The RX (Rotation around X-axis) and RZ (Rotation around Z-axis) gates are single-qubit gates that allow for arbitrary rotations of a qubit's state on the Bloch sphere. The choice of native gates is optimized for the underlying hardware physics, aiming for high fidelity and fast execution. For quantum programmers, understanding the native gate set is vital for efficient circuit compilation and for leveraging the hardware's strengths.
Error Rates and Fidelities: The performance of any quantum processor is critically dependent on its error rates and gate fidelities. For Aspen-11, as reported in 2021, the single-qubit gate fidelity was 99.8%. Two-qubit gate fidelities were 92.7% for the CZ gate and 91.0% for the XY gate. These figures are crucial for assessing the practical limits of quantum algorithms on this system. A single-qubit fidelity of 99.8% implies an error probability of 0.2% per gate. For two-qubit gates, the error probabilities were significantly higher, at 7.3% for CZ and 9.0% for XY. These error rates mean that as the number of gates in a quantum circuit increases, the probability of successful execution decreases exponentially. For instance, a circuit with just 10 two-qubit gates, each with 92.7% fidelity, would have an approximate success probability of (0.927)^10 ≈ 0.47, assuming no other errors. This highlights the inherent challenge of noise in NISQ devices and the necessity for error mitigation techniques. It also underscores why the pursuit of higher fidelities (e.g., >99.9% for single-qubit and >99% for two-qubit gates) is a primary goal in quantum hardware development, moving towards the thresholds required for fault-tolerant quantum computing.
Benchmarks: Aspen-11's performance was quantified through benchmarks, notably achieving a CLOPS (Classical Logic Operations Per Second) score of 7512 in 2022. CLOPS is a metric developed by Rigetti to measure the effective speed of a quantum processor for certain types of algorithms, particularly those involving classical feedback loops. It quantifies the rate at which a quantum processor can execute a quantum program, including compilation, execution, measurement, and the subsequent classical processing of results. This metric is particularly relevant for hybrid quantum-classical algorithms, where the interplay between quantum and classical computation is central. The absence of specified mirror circuit benchmarks, which are often used to characterize gate errors more directly and comprehensively, suggests a focus on end-to-end system performance for practical applications rather than isolated gate characterization in the publicly available data.
System Limits: Understanding the operational limits of a quantum processor is essential for designing and executing experiments. Aspen-11 offered 'unlimited' shots per job, which is a significant advantage for statistical analysis, error mitigation techniques (such as zero-noise extrapolation), and variational quantum algorithms that require many measurements to estimate expectation values. The system supported a circuit depth of up to 100 gates. This depth limit, while substantial for NISQ devices, still imposes constraints on the complexity of algorithms that can be reliably executed, primarily due to coherence times and cumulative error rates. The queue time was typically less than 10 minutes, indicating good accessibility and responsiveness for users. No other significant operational limits were explicitly specified, suggesting a relatively unconstrained environment within these primary parameters.
Primary Applications and Tradeoffs: Aspen-11 was primarily designed for and well-suited to hybrid quantum-classical algorithms and optimization tasks. Hybrid algorithms, such as the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA), leverage the strengths of both quantum processors (for complex state preparation and entanglement) and classical computers (for optimization loops). The tradeoffs inherent in Aspen-11, typical for its generation, included 'higher error rates than current gen' (referring to systems developed post-2022) and the benefit of 'scalable fabrication.' The higher error rates limited the depth and complexity of circuits that could be run reliably, necessitating careful error mitigation strategies. Conversely, Rigetti's focus on scalable fabrication through multi-chip integration was a forward-looking advantage, aiming to address the long-term challenge of building larger, more powerful quantum computers.
| System | Status | Primary metric |
|---|---|---|
| Rigetti Ankaa-2 | Retired | Physical qubits: 84 |
| Rigetti Ankaa-3 | Active | Physical qubits: 84 |
| Rigetti Aspen-M-1 | Retired | Physical qubits: 80 |
| Rigetti Aspen-M-2 | Retired | Physical qubits: 80 |
| Rigetti Aspen-M-3 | Retired | Physical qubits: 80 |
| Rigetti Cepheus-1 | Active | Physical qubits: 36 |
The Rigetti Aspen-11 processor had a relatively brief but impactful operational lifecycle, characteristic of the rapid advancements in quantum hardware development. Its timeline highlights the swift pace from announcement to availability and eventual retirement, underscoring the dynamic nature of this emerging technology.
Verification confidence: Medium. Specs can vary by revision and access tier. Always cite the exact device name + date-stamped metrics.
The Rigetti Aspen-11 was a 40-qubit superconducting quantum processor launched by Rigetti in 2021. It was designed to facilitate hybrid quantum-classical algorithms and optimization tasks.
Aspen-11 utilized transmon qubits with tunable frequencies, a common type of superconducting qubit known for its performance characteristics in NISQ-era devices.
It featured 40 physical qubits, making it a significant platform for quantum experimentation at the time of its release.
Aspen-11 had an octagonal connectivity topology, which defines the pattern of direct interactions between its qubits.
As of 2021, single-qubit gate fidelity was 99.8%, while two-qubit CZ gate fidelity was 92.7% and XY gate fidelity was 91.0%. These figures are historical and reflect the state of the technology at that time.
Yes, Aspen-11 was accessible via Rigetti QCS and through major cloud quantum platforms such as Azure Quantum and AWS Braket, operating in the us-west-1 region.
No, the Rigetti Aspen-11 processor was retired post-2022. Quantum hardware evolves rapidly, and newer generations of Rigetti processors have since superseded it.
In 2022, Aspen-11 achieved a CLOPS (Classical Logic Operations Per Second) score of 7512, a metric used by Rigetti to quantify the effective speed of the processor for hybrid algorithms.