--- title: Quantum Machine-Learning Design Targets Training And... description: A theoretical quantum machine-learning framework proposes two scalable quantum circuit architectures — a unitary brick-wall circuit and a unitary butterfly... canonical: https://daily.dev/posts/quantum-machine-learning-design-targets-training-and-scaling-barriers-3jn5x6sdg twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Quantum Machine-Learning Design Targets Training And Scaling Barriers | daily.dev og:description: A theoretical quantum machine-learning framework proposes two scalable quantum circuit architectures — a unitary brick-wall circuit and a unitary butterfly... og:url: https://daily.dev/posts/quantum-machine-learning-design-targets-training-and-scaling-barriers-3jn5x6sdg og:image: https://api.daily.dev/og/posts/3jn5X6sDG.png og:image:alt: Quantum Machine-Learning Design Targets Training And Scaling Barriers 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. # Quantum Machine-Learning Design Targets Training And Scaling Barriers **[The Quantum Insider](https://daily.dev/sources/thequantuminsider)** · 10 min read · 0 upvotes · 0 comments ## Summary A theoretical quantum machine-learning framework proposes two scalable quantum circuit architectures — a unitary brick-wall circuit and a unitary butterfly circuit — designed to address key barriers in training large quantum neural networks. The framework mathematically avoids exponential barren plateaus (vanishing gradient signals) while introducing a parallel parameter-shift rule that reduces the number of quantum circuit evaluations needed for gradient calculations by roughly a factor proportional to the number of qubits. In a 1,024-qubit example, the butterfly circuit requires ~600 evaluations versus ~30,720 under the standard approach. The framework also proposes a data-encoding method using non-Gaussian magic states that aims to preserve classical hardness of simulation. Significant caveats remain: the work is a preprint with no large-scale hardware validation, no demonstrated advantage over classical ML models, and the classical hardness claims could be undermined by future algorithmic advances. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Quantum advantage for learning shallow neural networks with natural data distributions](https://daily.dev/posts/quantum-advantage-for-learning-shallow-neural-networks-with-natural-data-distributions-ypd2cvswe) · Nature · 0 upvotes · 0 comments - [Unleashing the Advantage of Quantum AI](https://daily.dev/posts/unleashing-the-advantage-of-quantum-ai-sg4k7mzhe) · Quantum Frontiers · 0 upvotes · 0 comments - [The Hidden Bottleneck in Quantum Machine Learning: Getting Data into a Quantum Computer](https://daily.dev/posts/the-hidden-bottleneck-in-quantum-machine-learning-getting-data-into-a-quantum-computer-q1hccsqf5) · Towards Data Science · 2 upvotes · 0 comments - [Quantum Machine Learning Is Emerging as a Practical Tool for Drug Discovery](https://daily.dev/posts/quantum-machine-learning-is-emerging-as-a-practical-tool-for-drug-discovery-gepd5819i) · The Quantum Insider · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#quantum-computing](https://daily.dev/tags/quantum-computing) [View this post on daily.dev](https://daily.dev/posts/quantum-machine-learning-design-targets-training-and-scaling-barriers-3jn5x6sdg) ```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":"Quantum Machine-Learning Design Targets Training And Scaling Barriers","url":"https://daily.dev/posts/quantum-machine-learning-design-targets-training-and-scaling-barriers-3jn5x6sdg","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/quantum-machine-learning-design-targets-training-and-scaling-barriers-3jn5x6sdg"},"datePublished":"2026-07-28T14:05:20.192Z","dateModified":"2026-07-28T14:18:46.757Z","description":"A theoretical quantum machine-learning framework proposes two scalable quantum circuit architectures — a unitary brick-wall circuit and a unitary butterfly...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/0656e0862e18eb9381d44dee800a2af3?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/0656e0862e18eb9381d44dee800a2af3?_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/quantum-machine-learning-design-targets-training-and-scaling-barriers-3jn5x6sdg","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"machine-learning,quantum-computing","timeRequired":"PT10M"} {"@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":"Quantum Machine-Learning Design Targets Training And Scaling Barriers"}]} ```