Infleqtion entangles 30 logical qubits on Sqale using 80 physical qubits, not an industry record
Technically, the significance lies not only in the number of logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. but in entangling all 30 within a single circuit and executing about 1,000 physical operations. Reducing the number of physical gates helps suppress errors that accumulate per gate and is an enabler for scaling to longer computations. However, signal strength relative to noise alone does not allow one to judge overall logical error rates or computational accuracy.
From a business perspective, servicing three customers with logical-qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. circuits indicates progress in application development. Still, customer identities in full, specific commercial performance, and demonstration of quantum advantagequantum advantage量子優位性 / Quantum Advantage / Quantum Computational AdvantageFor a particular problem, a quantum computer demonstrates a practical advantage over classical computation in terms of speed, accuracy, cost, etc.QI NoteNot necessarily synonymous with "quantum supremacy"; the term is often used to include practical usefulness. When evaluating claims, check the classical methods used for comparison and the evaluation metrics. are not provided, so this result alone does not establish commercial maturity.
What to watch next
The next focus will be whether Infleqtion publishes details on logical operation error rates and atom loss, and whether independent comparisons with prior approaches become possible. It will be important to see if the connectivity and gate-reduction benefits hold when scaling to 100 logical qubits. Also critical is whether work with the three customers yields concrete use cases and performance evaluations, and whether intermediate milestones toward the 2028 and 2030 roadmaps are published.
✍️ Quantum Index Analysis
Infleqtion ran a circuit on hardware that operated 30 logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. in a jointly related fashion. This capability is important for eventually tackling larger problems on quantum computers. However, entangling 30 logical qubits is neither a first nor the largest demonstration in the industry. Comparing this result with prior work from other companies and research teams clarifies its position.
| Company / research team | Logical qubits | Experiment |
|---|---|---|
| Harvard / QuEra, etc. | Up to 96 | 2025: Experimented with cluster states connecting multiple logical qubits across space and time |
| Quantinuum | 94 | 2025: Created a GHZ stateGHZ stateGreenberger–Horne–Zeilinger State / GHZ StateAn entangled quantum state of three or more qubits that is a superposition of the state in which all qubits are 0 and the state in which all qubits are 1. It is used as a representative indicator to verify entanglement spanning multiple qubits.QI NoteThe scale at which GHZ states can be generated is one indicator of a quantum computer’s multi-qubit control performance. A fidelity exceeding 0.5 constitutes evidence of genuine multipartite entanglement, but this does not directly demonstrate practical performance in quantum computation or quantum advantage. with error-detecting logical qubits, excluding detected results |
| Harvard / QuEra, etc. | 48 | 2023: Executed a quantum circuitquantum circuit量子回路 / Quantum CircuitA representation of the computation procedure executed on a quantum computer, listing in order operations such as qubit initialization, quantum gate operations, and measurements.QI NoteEven for the same algorithm, the number of qubits used, circuit depth, and number of gates vary depending on the implementation. When comparing real-device performance, also check the circuit scale and the conditions after compilation. connecting 48 qubitsqubitsQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. |
| Infleqtion | 30 | This work: executed a circuit connecting 30 logical qubits on Sqale |
| Atom Computing / Microsoft | 24 | 2024: Reported an entangled state of 24 qubits |
Note: The created states, circuits, and error-handling methods differ, so this table is not a ranking of performance by count alone.
It is also important to note not to interpret these “30 logical qubits” as immediately usable, fault-tolerant logical qubits. Infleqtion uses an encoding that maps 8 physical qubitsphysical qubitsPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. to 3 logical qubits; in practice, the circuits allow error detection and mitigation of atom loss, but they are not the same as logical qubits that continuously correct general quantum errors as assumed in full FTQCFTQCFault-Tolerant Quantum Computing / FTQCA method for future large-scale quantum computing that uses quantum error correction to allow correct computation to continue even when physical errors occur.QI NoteA demonstration of quantum error correction is not the same as realizing FTQC. Logical error rates, the number of physical qubits required, logical gate performance, and so on are important.. Therefore, the high ratio of 30 logical qubits from 80 physical qubits is not directly comparable to other companies’ FTQC-targeted logical-qubit counts.
Still, the advance here is meaningful: Infleqtion expanded the scale on its own Sqale platform from 12 logical qubits demonstrated last year to 30 logical qubits and ran a circuit spanning all 30 on hardware. It is significant that the company obtained a clear signal from a state spanning the whole set, not merely prepared 30 qubits. Also, they report reducing the number of physical gates required for key logical operations by half through improved operations connecting qubits. In quantum computing, fewer operations generally mean fewer potential errors, so implementing the same function with fewer operations is important for scaling circuits.
However, figures such as “1 KiloQuOp” and “about 1,000 times the noise” alone do not show whether logical error rates improved or whether accuracy is maintained for even longer circuits. This result neither demonstrates higher computational performance than other groups reporting 48, 94, or 96 qubits, nor does it realize fault-tolerant quantum computing. A more accurate characterization is that Infleqtion’s design philosophy—creating many encoded qubits from relatively few physical qubits and operating them together—was extended to the 30-logical-qubit scale.
Also note that Sqale is not a single machine model but a product family that Infleqtion plans to scale. Separating current results from next-generation plans gives the picture below.
| Sqale stage | Logical qubits | Status |
|---|---|---|
| 2025 experiment | 12 | Achieved |
| This experiment | 30 | Achieved |
| Next-generation Sqale product spec | 50+ | Planned |
| 2028 target | 100 | Future target |
| 2030 target | 1,000 | Future target |
Therefore, it is reasonable to view this announcement as not an industry record for “30 qubits,” but as a demonstration that advances Sqale’s roadmap while showing a working design that handles many encoded qubits with low physical-qubit overhead. The next evaluations should focus less on the raw logical-qubit count and more on whether this low overhead can be maintained as codes are strengthened and whether logical error rates can be driven below physical error rates while running long computations.
NETWORKSee the industry network around Infleqtion →Related articles
- QuEra and HPE consider on-premises integration of fault-tolerant quantum computers with HPC on a Cray foundation
- Xanadu targets over 1,000 logical qubits by 2031 with FTQC and manufacturing roadmap
- IonQ validates error decoding for error correction on a single CPU, envisioned for 408 logical qubits, hardware not yet available
Source
Read the announcement from Infleqtion
Infleqtion announced that it entangled 30 logical qubits into a single quantum statequantum stateQuantum State / Quantum StateRepresents the state of a quantum system and determines quantities such as the probabilities of outcomes obtained when the system is measured.QI NoteA quantum state is not the simple "0 or 1" value of a qubit. It includes superpositions and mixed states, and how the state was prepared and measured is also important. on its neutral-atom quantum computer Sqale, using 80 physical qubits. The company says the circuit executed corresponded to roughly 1,000 physical operations through co-design of hardware and software.
✍️ Quantum Index Analysis
Explains the technical and commercial significance behind the announcement and highlights evaluation points that numbers and headlines alone can obscure. Read our independent analysis ↓
Overview
In this experiment, Infleqtion formed 30 logical qubits from 80 physical qubits on Sqale and entangled all logical qubits into a single coherent quantum state. The circuit size corresponded to about 1,000 physical operations—what the company calls a “1 KiloQuOp”—and Infleqtion reports that the signal demonstrating the result was roughly 1,000 times the background noise. Sqale is a neutral-atom system that combines per-qubit control with dynamically reconfigurable atom arrays. The design aims to maintain all-to-all connectivity between qubits while limiting error accumulation from atom movement, atom loss, and increased processing time. The result used co-design between Sqale hardware and the quantum software stack Superstaq. Infleqtion also says it used GPT 5.6 Sol to discover a new entangling operation between logical qubits that halved the number of physical gates required for key logical operations compared with previous approaches. According to Infleqtion, there are three customers using logical-qubit circuits on Sqale. One customer is the Wellcome Leap Quantum for Bio program, which previously demonstrated a quantum neural network on hardware using 12 logical qubits. The company has targets of 100 logical qubits by 2028 and 1,000 logical qubits by 2030.
Key points
- Using 80 physical qubits, Infleqtion encoded 30 logical qubits and entangled them into a single state.
- The circuit ran the equivalent of about 1,000 physical operations, and the reported signal was roughly 1,000 times the baseline noise.
- An AI-assisted discovered operation between logical qubits halved the number of physical gates needed for main logical operations.
- Combines per-qubit control and reconfigurable atom arrays through co-design with Superstaq.
- Infleqtion says three customers are using logical-qubit circuits; it targets 100 logical qubits by 2028 and 1,000 by 2030.
Technical and business implications
Technically, the significance lies not only in the number of logical qubits but in entangling all 30 within a single circuit and executing about 1,000 physical operations. Reducing the number of physical gates helps suppress errors that accumulate per gate and is an enabler for scaling to longer computations. However, signal strength relative to noise alone does not allow one to judge overall logical error rates or computational accuracy.
From a business perspective, servicing three customers with logical-qubit circuits indicates progress in application development. Still, customer identities in full, specific commercial performance, and demonstration of quantum advantagequantum advantage量子優位性 / Quantum Advantage / Quantum Computational AdvantageFor a particular problem, a quantum computer demonstrates a practical advantage over classical computation in terms of speed, accuracy, cost, etc.QI NoteNot necessarily synonymous with "quantum supremacy"; the term is often used to include practical usefulness. When evaluating claims, check the classical methods used for comparison and the evaluation metrics. are not provided, so this result alone does not establish commercial maturity.
What to watch next
The next focus will be whether Infleqtion publishes details on logical operation error rates and atom loss, and whether independent comparisons with prior approaches become possible. It will be important to see if the connectivity and gate-reduction benefits hold when scaling to 100 logical qubits. Also critical is whether work with the three customers yields concrete use cases and performance evaluations, and whether intermediate milestones toward the 2028 and 2030 roadmaps are published.
✍️ Quantum Index Analysis
Infleqtion ran a circuit on hardware that operated 30 logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. in a jointly related fashion. This capability is important for eventually tackling larger problems on quantum computers. However, entangling 30 logical qubits is neither a first nor the largest demonstration in the industry. Comparing this result with prior work from other companies and research teams clarifies its position.
| Company / research team | Logical qubits | Experiment |
|---|---|---|
| Harvard / QuEra, etc. | Up to 96 | 2025: Experimented with cluster states connecting multiple logical qubits across space and time |
| Quantinuum | 94 | 2025: Created a GHZ stateGHZ stateGreenberger–Horne–Zeilinger State / GHZ StateAn entangled quantum state of three or more qubits that is a superposition of the state in which all qubits are 0 and the state in which all qubits are 1. It is used as a representative indicator to verify entanglement spanning multiple qubits.QI NoteThe scale at which GHZ states can be generated is one indicator of a quantum computer’s multi-qubit control performance. A fidelity exceeding 0.5 constitutes evidence of genuine multipartite entanglement, but this does not directly demonstrate practical performance in quantum computation or quantum advantage. with error-detecting logical qubits, excluding detected results |
| Harvard / QuEra, etc. | 48 | 2023: Executed a quantum circuitquantum circuit量子回路 / Quantum CircuitA representation of the computation procedure executed on a quantum computer, listing in order operations such as qubit initialization, quantum gate operations, and measurements.QI NoteEven for the same algorithm, the number of qubits used, circuit depth, and number of gates vary depending on the implementation. When comparing real-device performance, also check the circuit scale and the conditions after compilation. connecting 48 qubitsqubitsQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. |
| Infleqtion | 30 | This work: executed a circuit connecting 30 logical qubits on Sqale |
| Atom Computing / Microsoft | 24 | 2024: Reported an entangled state of 24 qubits |
Note: The created states, circuits, and error-handling methods differ, so this table is not a ranking of performance by count alone.
It is also important to note not to interpret these “30 logical qubits” as immediately usable, fault-tolerant logical qubits. Infleqtion uses an encoding that maps 8 physical qubitsphysical qubitsPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. to 3 logical qubits; in practice, the circuits allow error detection and mitigation of atom loss, but they are not the same as logical qubits that continuously correct general quantum errors as assumed in full FTQCFTQCFault-Tolerant Quantum Computing / FTQCA method for future large-scale quantum computing that uses quantum error correction to allow correct computation to continue even when physical errors occur.QI NoteA demonstration of quantum error correction is not the same as realizing FTQC. Logical error rates, the number of physical qubits required, logical gate performance, and so on are important.. Therefore, the high ratio of 30 logical qubits from 80 physical qubits is not directly comparable to other companies’ FTQC-targeted logical-qubit counts.
Still, the advance here is meaningful: Infleqtion expanded the scale on its own Sqale platform from 12 logical qubits demonstrated last year to 30 logical qubits and ran a circuit spanning all 30 on hardware. It is significant that the company obtained a clear signal from a state spanning the whole set, not merely prepared 30 qubits. Also, they report reducing the number of physical gates required for key logical operations by half through improved operations connecting qubits. In quantum computing, fewer operations generally mean fewer potential errors, so implementing the same function with fewer operations is important for scaling circuits.
However, figures such as “1 KiloQuOp” and “about 1,000 times the noise” alone do not show whether logical error rates improved or whether accuracy is maintained for even longer circuits. This result neither demonstrates higher computational performance than other groups reporting 48, 94, or 96 qubits, nor does it realize fault-tolerant quantum computing. A more accurate characterization is that Infleqtion’s design philosophy—creating many encoded qubits from relatively few physical qubits and operating them together—was extended to the 30-logical-qubit scale.
Also note that Sqale is not a single machine model but a product family that Infleqtion plans to scale. Separating current results from next-generation plans gives the picture below.
| Sqale stage | Logical qubits | Status |
|---|---|---|
| 2025 experiment | 12 | Achieved |
| This experiment | 30 | Achieved |
| Next-generation Sqale product spec | 50+ | Planned |
| 2028 target | 100 | Future target |
| 2030 target | 1,000 | Future target |
Therefore, it is reasonable to view this announcement as not an industry record for “30 qubits,” but as a demonstration that advances Sqale’s roadmap while showing a working design that handles many encoded qubits with low physical-qubit overhead. The next evaluations should focus less on the raw logical-qubit count and more on whether this low overhead can be maintained as codes are strengthened and whether logical error rates can be driven below physical error rates while running long computations.
NETWORKSee the industry network around Infleqtion →Related articles
- QuEra and HPE consider on-premises integration of fault-tolerant quantum computers with HPC on a Cray foundation
- Xanadu targets over 1,000 logical qubits by 2031 with FTQC and manufacturing roadmap
- IonQ validates error decoding for error correction on a single CPU, envisioned for 408 logical qubits, hardware not yet available
