Alice & Bob estimate 22,593 physical qubits to break RSA‑2048; comparison with IonQ highlights FTQC design differences

【Article Title】 Alice & Bob estimate 22,593 physical qubits to break RSA‑2048; comparison with IonQ highlights FTQC design differences 【Article Body】 AI TRANSLATION This article is an AI-generated translation of the original Japanese article. For the authoritative version, please refer to the original. Read the original Japanese article → (https://quantumindex.jp/alice-bob-cat-qubit-rsa-2048-resource-estimate/) Alice & Bob have published an estimate that running Shor’s algorithm on fault‑tolerant superconducting cat qubitscat qubitsCat Qubit / Cat Qubit / Schrödinger Cat QubitA qubit designed to use "cat states"—superpositions of distinct quantum states—to make certain types of errors less likely.QI NoteIt may reduce the overhead required for error correction, but not all errors are automatically suppressed. Attention should also be paid to the remaining error rates. would break RSA‑2048 using 22,593 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. in 3.14 days. They estimate ECDLP‑256 would require 29,588 physical qubits and take 61.8 minutes. These primary figures assume the stringent condition that no bit‑flip errors occur during the computation. ✍️ Quantum Index Analysis The technical and commercial significance behind the announcement, and evaluation points that aren’t obvious from the numbers and headlines alone. Read our independent analysis ↓ Summary of the announcement In this study the authors concretized the operation and timing of each physical qubit for the most resource‑intensive processes, producing a chip layout and execution schedule. Rather than converting from a generic count 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., they accumulated required resources aligned with a specific physical architecture. To reduce 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. count they used cat qubits that suppress bit‑flip errors at the hardware level, the more efficient LDPC‑cat code compared with conventional concatenated codes, and adders redesigned for cat qubits. The RSA‑2048 estimate falls from a previous 49,649 physical qubits to 22,593—less than half. However, the assumed bit‑flip time underlying the estimate corresponds to roughly a century. Under an assumption of one bit‑flip roughly every hour, the required physical qubit count rises to about 45,000. These figures are resource estimates based on assumed error rates and architecture, not claims of practical cryptographic breakage on real hardware. Key points • They estimate resources to break RSA‑2048 at 22,593 physical qubits and a runtime of 3.14 days. • For ECDLP‑256 they estimate 29,588 physical qubits and 61.8 minutes. This exceeds Bitcoin’s ~10‑minute block time, so in‑flight transactions would not be targetable under this runtime. • Alice & Bob claim their RSA‑2048 physical‑qubit estimate is 1/40 of the estimate Craig Gidney published in 2025. • Using LDPC‑cat codes and redesigned adders, they reduce the RSA‑2048 physical‑qubit requirement from the previous estimate of 49,649 to less than half. • The primary estimate assumes no bit‑flip occurs during the computation; if bit‑flips occur about once per hour, the required physical qubit count rises to roughly 45,000. Technical and commercial implications Technically, the work shows that biasing error types at the hardware level with cat qubits, paired with error‑correction codes matched to that bias and algorithmic design, can potentially reduce the number of physical qubits needed for cryptographic attacks. Notably, the mapping down to physical‑qubit placement and scheduling provides a more concrete evaluation than rough logical‑qubit counts alone. From a business and societal perspective, it provides a new estimate to consider when assessing the impact of quantum computers on public‑key cryptography. However, the estimate heavily depends on the extremely long assumed bit‑flip time and does not directly indicate when practical cryptographic breakage will occur. Decisions to migrate to post‑quantum cryptography should consider this estimate alongside actual hardware performance and engineering feasibility. What to watch next Going forward it will be important to see how closely the assumed bit‑flip time and other operation fidelities can be realized on hardware. Third‑party verification of the proposed chip layout and execution schedule, and comparative evaluations under different error conditions, would be useful. It will also be important to track demonstrations of large‑scale error correction using LDPC‑cat codes and how the RSA‑2048 and ECDLP‑256 estimates evolve as hardware performance improves. ✍️ Quantum Index Analysis The noteworthy aspect of this announcement is not just the headline number of roughly 23,000 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. for RSA‑2048. It is that by leveraging error‑biasing properties of superconducting cat qubitscat qubitsCat Qubit / Cat Qubit / Schrödinger Cat QubitA qubit designed to use "cat states"—superpositions of distinct quantum states—to make certain types of errors less likely.QI NoteIt may reduce the overhead required for error correction, but not all errors are automatically suppressed. Attention should also be paid to the remaining error rates., an error‑correction scheme tailored to that bias, and algorithmic optimization, the authors substantially improved on prior resource estimates. They also concretized the quantum algorithm down to physical‑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. layout and execution scheduling, taking a step beyond purely gate‑count‑based estimates. An instructive comparison is with IonQ’s 2026 secp256k1 resource estimate (https://en.quantumindex.jp/ionq-secp256k1-fault-tolerant-resource-estimate/). Both studies target the 256‑bit elliptic‑curve discrete logarithm problem (ECDLP‑256), but IonQ adopts a trapped‑ion platform with a quantum LDPC codequantum LDPC codeQuantum Low-Density Parity-Check Code / Quantum Low-Density Parity-Check Code / Quantum LDPC Code / QLDPC CodeA type of quantum error-correcting code with a sparse structure in which each check acts on only a small number of qubits. It has the potential to correct errors efficiently with a small number of additional qubits.QI NoteWhile they are attracting attention for the possibility of reducing qubit overhead compared to the surface code, practical viability must be evaluated not only by code rate and distance but also by the required connectivity, decoders, and implementation conditions of the error-correction circuits. in a “Walking Cat” architecture, whereas Alice & Bob use superconducting cat qubits that physically suppress bit‑flip errors together with LDPC‑cat codes. Note that the “Cat” in Walking Cat refers to cat states used for logical operations and is conceptually different from Alice & Bob’s physical cat qubits. Comparison itemIonQAlice & BobHardware platformTrapped ionsSuperconducting cat qubitsError‑correction schemeWalking Cat / quantum LDPCLDPC‑catTarget problemECDLP‑256 (secp256k1)ECDLP‑256Physical qubit countabout 19,40029,588Logical qubitLogical qubitLogical 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. count1,4571,462Toffoli gate countabout 39 millionabout 58 millionEstimated runtime25.7 days61.8 minutesQubit count × runtimeabout 499,000 qubit‑daysabout 1,270 qubit‑daysCryptographic break on real hardwareNot demonstratedNot demonstrated ※Comparison based on each company’s published figures. IonQ’s runtime is a single‑run time, while Alice & Bob report expected runtime to success, so this is not a strictly like‑for‑like comparison. The product of qubit count and runtime is Quantum Index’s estimate. In this comparison Alice & Bob require roughly 1.5× more physical qubits but their estimated runtime is compressed by about 600×. Even the simple product of qubit count and runtime shows roughly a 400× difference. Of course, the gate speeds, error rates, and error‑correction procedures assumed by the two studies differ, so this should not be read as a direct measure of hardware superiority. Still, it underscores that for large‑scale 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. tasks like cryptographic attacks, reducing physical qubit count alone is insufficient; accelerating logical operations, including error‑correction overhead, is critically important. However, Alice & Bob’s estimate rests on a significant assumption. Their most efficient configuration assumes no bit‑flip error occurs during the quantum computation, which for RSA‑2048 corresponds to an extraordinarily long bit‑flip time of about 100 years per physical qubit—far beyond currently demonstrated performance. If bit‑flip time is about one hour, the required physical qubit count rises to roughly 45,000. Thus the 22,593‑qubit figure should be viewed not as the scale of presently buildable systems but as a design target for future, higher‑performance hardware. When assessing practical cryptographic risk, the ECDLP‑256 estimated runtime of about one hour is also important. Because this exceeds Bitcoin’s average ~10‑minute block interval, the estimate does not imply practical attacks on in‑flight transactions. That said, attacks on addresses whose public keys are already exposed are subject to different timing constraints. Evaluating cryptographic threat requires distinguishing required qubit counts, target scenarios, public‑key exposure, and runtimes. What IonQ and Alice & Bob share is the approach of evaluating Shor’s algorithm not as an abstract circuit but in the context of a concrete quantum hardware platform and an associated error‑correction scheme. The disparities between their estimates demonstrate that FTQC practicality depends not only on qubit count but strongly on overall architectural design. Future evaluations will hinge on how closely each team can realize their assumed physical error rates, logical operation speeds, and large‑scale error‑correction procedures on actual hardware. NETWORKSee Alice & Bob’s industry network → (/qi-network/) Related articles • Alice & Bob demonstrate higher‑order photon exchange with DC voltage, advancing four‑component cat qubits (https://en.quantumindex.jp/alice-bob-dc-voltage-cat-qubit-stabilization/) • IBM demonstrates 99% state‑transfer fidelity between quantum processors, advancing modular FTQC (https://en.quantumindex.jp/ibm-nighthawk-l-coupler-state-transfer/) • D‑Wave launches beta of gate‑model quantum simulator, ahead of dual‑rail hardware (https://en.quantumindex.jp/dwave-gate-model-simulator-beta/) Sources Read the original announcement (https://alice-bob.com/newsroom/alice-bob-sets-record-low-for-quantum-resources-required-to-break-internet-encryption/) If you found this article useful, please consider sharing it. ──────────────────── 【AI Evaluation Request】 Evaluate the following article critically, not based on the quality of its writing, but on its **original informational value as a specialist publication**. Do not give a high rating to summaries, paraphrases, explanations of technical terms, or generic observations such as "this will be worth watching" or "the timeline remains uncertain" if they could easily be produced by a general-purpose generative AI, even if they are well written. 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Alice & Bob have published an estimate that running Shor’s algorithm on fault‑tolerant superconducting cat qubitscat qubitsCat Qubit / Cat Qubit / Schrödinger Cat QubitA qubit designed to use "cat states"—superpositions of distinct quantum states—to make certain types of errors less likely.QI NoteIt may reduce the overhead required for error correction, but not all errors are automatically suppressed. Attention should also be paid to the remaining error rates. would break RSA‑2048 using 22,593 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. in 3.14 days. They estimate ECDLP‑256 would require 29,588 physical qubits and take 61.8 minutes. These primary figures assume the stringent condition that no bit‑flip errors occur during the computation.

Summary of the announcement

In this study the authors concretized the operation and timing of each physical qubit for the most resource‑intensive processes, producing a chip layout and execution schedule. Rather than converting from a generic count 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., they accumulated required resources aligned with a specific physical architecture. To reduce 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. count they used cat qubits that suppress bit‑flip errors at the hardware level, the more efficient LDPC‑cat code compared with conventional concatenated codes, and adders redesigned for cat qubits. The RSA‑2048 estimate falls from a previous 49,649 physical qubits to 22,593—less than half. However, the assumed bit‑flip time underlying the estimate corresponds to roughly a century. Under an assumption of one bit‑flip roughly every hour, the required physical qubit count rises to about 45,000. These figures are resource estimates based on assumed error rates and architecture, not claims of practical cryptographic breakage on real hardware.

Key points

• They estimate resources to break RSA‑2048 at 22,593 physical qubits and a runtime of 3.14 days.
• For ECDLP‑256 they estimate 29,588 physical qubits and 61.8 minutes. This exceeds Bitcoin’s ~10‑minute block time, so in‑flight transactions would not be targetable under this runtime.
• Alice & Bob claim their RSA‑2048 physical‑qubit estimate is 1/40 of the estimate Craig Gidney published in 2025.
• Using LDPC‑cat codes and redesigned adders, they reduce the RSA‑2048 physical‑qubit requirement from the previous estimate of 49,649 to less than half.
• The primary estimate assumes no bit‑flip occurs during the computation; if bit‑flips occur about once per hour, the required physical qubit count rises to roughly 45,000.

Technical and commercial implications

Technically, the work shows that biasing error types at the hardware level with cat qubits, paired with error‑correction codes matched to that bias and algorithmic design, can potentially reduce the number of physical qubits needed for cryptographic attacks. Notably, the mapping down to physical‑qubit placement and scheduling provides a more concrete evaluation than rough logical‑qubit counts alone. From a business and societal perspective, it provides a new estimate to consider when assessing the impact of quantum computers on public‑key cryptography. However, the estimate heavily depends on the extremely long assumed bit‑flip time and does not directly indicate when practical cryptographic breakage will occur. Decisions to migrate to post‑quantum cryptography should consider this estimate alongside actual hardware performance and engineering feasibility.

What to watch next

Going forward it will be important to see how closely the assumed bit‑flip time and other operation fidelities can be realized on hardware. Third‑party verification of the proposed chip layout and execution schedule, and comparative evaluations under different error conditions, would be useful. It will also be important to track demonstrations of large‑scale error correction using LDPC‑cat codes and how the RSA‑2048 and ECDLP‑256 estimates evolve as hardware performance improves.

✍️ Quantum Index Analysis

The noteworthy aspect of this announcement is not just the headline number of roughly 23,000 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. for RSA‑2048. It is that by leveraging error‑biasing properties of superconducting cat qubitscat qubitsCat Qubit / Cat Qubit / Schrödinger Cat QubitA qubit designed to use "cat states"—superpositions of distinct quantum states—to make certain types of errors less likely.QI NoteIt may reduce the overhead required for error correction, but not all errors are automatically suppressed. Attention should also be paid to the remaining error rates., an error‑correction scheme tailored to that bias, and algorithmic optimization, the authors substantially improved on prior resource estimates. They also concretized the quantum algorithm down to physical‑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. layout and execution scheduling, taking a step beyond purely gate‑count‑based estimates.

An instructive comparison is with IonQ’s 2026 secp256k1 resource estimate. Both studies target the 256‑bit elliptic‑curve discrete logarithm problem (ECDLP‑256), but IonQ adopts a trapped‑ion platform with a quantum LDPC codequantum LDPC codeQuantum Low-Density Parity-Check Code / Quantum Low-Density Parity-Check Code / Quantum LDPC Code / QLDPC CodeA type of quantum error-correcting code with a sparse structure in which each check acts on only a small number of qubits. It has the potential to correct errors efficiently with a small number of additional qubits.QI NoteWhile they are attracting attention for the possibility of reducing qubit overhead compared to the surface code, practical viability must be evaluated not only by code rate and distance but also by the required connectivity, decoders, and implementation conditions of the error-correction circuits. in a “Walking Cat” architecture, whereas Alice & Bob use superconducting cat qubits that physically suppress bit‑flip errors together with LDPC‑cat codes. Note that the “Cat” in Walking Cat refers to cat states used for logical operations and is conceptually different from Alice & Bob’s physical cat qubits.

Comparison item	IonQ	Alice & Bob
Hardware platform	Trapped ions	Superconducting cat qubits
Error‑correction scheme	Walking Cat / quantum LDPC	LDPC‑cat
Target problem	ECDLP‑256 (secp256k1)	ECDLP‑256
Physical qubit count	about 19,400	29,588
Logical qubitLogical qubitLogical 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. count	1,457	1,462
Toffoli gate count	about 39 million	about 58 million
Estimated runtime	25.7 days	61.8 minutes
Qubit count × runtime	about 499,000 qubit‑days	about 1,270 qubit‑days
Cryptographic break on real hardware	Not demonstrated	Not demonstrated

※Comparison based on each company’s published figures. IonQ’s runtime is a single‑run time, while Alice & Bob report expected runtime to success, so this is not a strictly like‑for‑like comparison. The product of qubit count and runtime is Quantum Index’s estimate.

In this comparison Alice & Bob require roughly 1.5× more physical qubits but their estimated runtime is compressed by about 600×. Even the simple product of qubit count and runtime shows roughly a 400× difference. Of course, the gate speeds, error rates, and error‑correction procedures assumed by the two studies differ, so this should not be read as a direct measure of hardware superiority. Still, it underscores that for large‑scale 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. tasks like cryptographic attacks, reducing physical qubit count alone is insufficient; accelerating logical operations, including error‑correction overhead, is critically important.

However, Alice & Bob’s estimate rests on a significant assumption. Their most efficient configuration assumes no bit‑flip error occurs during the quantum computation, which for RSA‑2048 corresponds to an extraordinarily long bit‑flip time of about 100 years per physical qubit—far beyond currently demonstrated performance. If bit‑flip time is about one hour, the required physical qubit count rises to roughly 45,000. Thus the 22,593‑qubit figure should be viewed not as the scale of presently buildable systems but as a design target for future, higher‑performance hardware.

When assessing practical cryptographic risk, the ECDLP‑256 estimated runtime of about one hour is also important. Because this exceeds Bitcoin’s average ~10‑minute block interval, the estimate does not imply practical attacks on in‑flight transactions. That said, attacks on addresses whose public keys are already exposed are subject to different timing constraints. Evaluating cryptographic threat requires distinguishing required qubit counts, target scenarios, public‑key exposure, and runtimes.

What IonQ and Alice & Bob share is the approach of evaluating Shor’s algorithm not as an abstract circuit but in the context of a concrete quantum hardware platform and an associated error‑correction scheme. The disparities between their estimates demonstrate that FTQC practicality depends not only on qubit count but strongly on overall architectural design. Future evaluations will hinge on how closely each team can realize their assumed physical error rates, logical operation speeds, and large‑scale error‑correction procedures on actual hardware.

NETWORKSee Alice & Bob’s industry network →

Related articles

• Alice & Bob demonstrate higher‑order photon exchange with DC voltage, advancing four‑component cat qubits
• IBM demonstrates 99% state‑transfer fidelity between quantum processors, advancing modular FTQC
• D‑Wave launches beta of gate‑model quantum simulator, ahead of dual‑rail hardware

Sources

Read the original announcement