--- title: IonQ Researchers Run MegaQuOp-Scale Quantum Error... description: IonQ researchers demonstrated an end-to-end quantum error decoder capable of handling MegaQuOp-scale simulated workloads—up to 408 logical qubits and over 1... canonical: https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: IonQ Researchers Run MegaQuOp-Scale Quantum Error Decoder on a MacBook Pro | daily.dev og:description: IonQ researchers demonstrated an end-to-end quantum error decoder capable of handling MegaQuOp-scale simulated workloads—up to 408 logical qubits and over 1... og:url: https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc og:image: https://api.daily.dev/og/posts/SJ17HK8sC.png og:image:alt: IonQ Researchers Run MegaQuOp-Scale Quantum Error Decoder on a MacBook Pro og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # IonQ Researchers Run MegaQuOp-Scale Quantum Error Decoder on a MacBook Pro **[The Quantum Insider](https://daily.dev/sources/thequantuminsider)** · 9 min read · 0 upvotes · 0 comments ## Summary IonQ researchers demonstrated an end-to-end quantum error decoder capable of handling MegaQuOp-scale simulated workloads—up to 408 logical qubits and over 1 million quantum operations—running entirely on a single Apple M4 Max MacBook Pro CPU, using 12 of its 16 cores. The decoder added less than 0.3% overhead at a two-qubit gate error rate of 0.01%, and under 12% at a 0.05% error rate. The test modeled IonQ's proposed 'walking cat' trapped-ion architecture using quantum LDPC codes, simulating error streams rather than running on real MegaQuOp hardware, which does not yet exist. Techniques included incremental error-model updates and reduced memory footprint to allow concurrent decoding processes. The researchers note the results are architecture-specific and based on circuit-level noise simulation rather than real hardware data, with rare decoder convergence failures possible. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Can a MacBook Pro handle quantum error decoding for a large-scale fault-tolerant quantum computer? Yes, in simulation. IonQ researchers ran an end-to-end decoder for a simulated MegaQuOp-scale workload—up to 408 logical qubits and over 1 million quantum operations—on a single Apple M4 Max processor, using 12 of its 16 CPU cores. Decoding added under 0.3% overhead at a 0.01% two-qubit gate error rate and under 12% at a 0.05% error rate. _Following how classical hardware keeps pace with quantum error correction gets easier with daily.dev's research tracking._ ### What is IonQ's walking cat architecture for trapped-ion quantum computing? It is a proposed fault-tolerant trapped-ion design that stores logical qubits in quantum low-density parity-check (LDPC) codes, using separate magic-state factories to supply resources for T gates. It tracks many logical operations in software without physically merging or reshaping error-correcting blocks, and was the architecture modeled in a decoder benchmark using 68 memory blocks, 20 magic-state factories, 11,680 physical qubits, and 408 logical qubits. _Engineers evaluating fault-tolerant quantum designs can follow architecture developments like this on daily.dev._ ### How much time overhead does classical error decoding add to a fault-tolerant quantum computation? At a two-qubit gate error rate of 0.01%, decoding added as little as 0.02% to 0.24% extra computation time across tested workloads; at a 0.05% error rate, overhead ranged from 0.72% up to 11.53%, depending on the benchmark and assumed syndrome-extraction cycle time (1ms or 5ms). These figures come from simulations of IonQ's walking-cat trapped-ion architecture, not from a running quantum computer. _Tracking realistic performance benchmarks like this helps quantum developers gauge decoder feasibility on daily.dev._ ## Similar posts on daily.dev - [Demonstrating real-time and low-latency quantum error correction with superconducting qubits](https://daily.dev/posts/demonstrating-real-time-and-low-latency-quantum-error-correction-with-superconducting-qubits-rhwsq5rei) · Nature · 0 upvotes · 0 comments - [IonQ Achieves 99.99% Two-Qubit Gate Performance](https://daily.dev/posts/ionq-achieves-99-99-two-qubit-gate-performance-0lq49upqp) · The Quantum Insider · 0 upvotes · 0 comments - [A new ion-based quantum computer makes error correction simpler](https://daily.dev/posts/a-new-ion-based-quantum-computer-makes-error-correction-simpler-nf3k08gdx) · MIT Technology Review · 0 upvotes · 0 comments --- Tags: [#quantum-computing](https://daily.dev/tags/quantum-computing) [View this post on daily.dev](https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"IonQ Researchers Run MegaQuOp-Scale Quantum Error Decoder on a MacBook Pro","url":"https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc"},"datePublished":"2026-08-31T12:41:38.889Z","dateModified":"2026-08-31T12:42:03.943Z","description":"IonQ researchers demonstrated an end-to-end quantum error decoder capable of handling MegaQuOp-scale simulated workloads—up to 408 logical qubits and over 1...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/578c1e363248f1bb81dcc644cfb1f9ae?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/578c1e363248f1bb81dcc644cfb1f9ae?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"The Quantum Insider","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"The Quantum Insider","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/7b14a6b34c1b464c9e8a88d9a0dac951","url":"https://daily.dev/sources/thequantuminsider"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"quantum-computing","timeRequired":"PT9M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"The Quantum Insider","item":"https://daily.dev/sources/thequantuminsider"},{"@type":"ListItem","position":3,"name":"IonQ Researchers Run MegaQuOp-Scale Quantum Error Decoder on a MacBook Pro"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/ionq-researchers-run-megaquop-scale-quantum-error-decoder-on-a-macbook-pro-sj17hk8sc#faq","mainEntity":[{"@type":"Question","name":"Can a MacBook Pro handle quantum error decoding for a large-scale fault-tolerant quantum computer?","acceptedAnswer":{"@type":"Answer","text":"Yes, in simulation. IonQ researchers ran an end-to-end decoder for a simulated MegaQuOp-scale workload—up to 408 logical qubits and over 1 million quantum operations—on a single Apple M4 Max processor, using 12 of its 16 CPU cores. Decoding added under 0.3% overhead at a 0.01% two-qubit gate error rate and under 12% at a 0.05% error rate. Following how classical hardware keeps pace with quantum error correction gets easier with daily.dev's research tracking."}},{"@type":"Question","name":"What is IonQ's walking cat architecture for trapped-ion quantum computing?","acceptedAnswer":{"@type":"Answer","text":"It is a proposed fault-tolerant trapped-ion design that stores logical qubits in quantum low-density parity-check (LDPC) codes, using separate magic-state factories to supply resources for T gates. It tracks many logical operations in software without physically merging or reshaping error-correcting blocks, and was the architecture modeled in a decoder benchmark using 68 memory blocks, 20 magic-state factories, 11,680 physical qubits, and 408 logical qubits. Engineers evaluating fault-tolerant quantum designs can follow architecture developments like this on daily.dev."}},{"@type":"Question","name":"How much time overhead does classical error decoding add to a fault-tolerant quantum computation?","acceptedAnswer":{"@type":"Answer","text":"At a two-qubit gate error rate of 0.01%, decoding added as little as 0.02% to 0.24% extra computation time across tested workloads; at a 0.05% error rate, overhead ranged from 0.72% up to 11.53%, depending on the benchmark and assumed syndrome-extraction cycle time (1ms or 5ms). These figures come from simulations of IonQ's walking-cat trapped-ion architecture, not from a running quantum computer. Tracking realistic performance benchmarks like this helps quantum developers gauge decoder feasibility on daily.dev."}}]} ```