A Stability Contract for Scalable Hybrid Computing: Minimal Sufficient Control of Component-Observable Hardware
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Abstract
Digital computation enforces stability physically, by thresholded restoration at every gate. Analog and wave computation executes directly in its substrate, so stability must instead be supplied informationally, through acquisition, identification and correction. We treat that obligation as a stability contract and establish its resource requirements. For independent Gaussian drift, holding n channels at a fixed mean-square distortion below the innovation variance requires feedback at order n bits per cycle, so a modality whose useful feedback capacity stays bounded fails beyond a computable channel count, whereas component-resolved observation delivers that information in one parallel acquisition. Information rate is not sequential depth. Maintenance separates into acquisition depth, feedback information and traffic, and host arithmetic and state. Within the declared class, a projected heavy-ball law driven by measured residuals achieves constant acquisition depth together with the linear information and arithmetic floors, at order-one auxiliary state per channel, reaching tolerance in four to five acquisitions on the tested monitor families. A routing-closure condition follows: a physical accelerator stays in the workload’s scaling class only when maintenance traffic does not cross the host boundary at a higher asymptotic rate than the workload interface. Evidence spans photonic, in-memory, large-scale simulation and quantum loop-closure studies.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22967716.
This paper studies how analog and wave-based hardware can be kept stable as the number of components increases. It argues that parallel, component-level feedback can provide the information needed for control without increasing sequential acquisition depth. The proposed controller reaches the target tolerance in four to five acquisitions on the tested systems.
The paper also does a good job of being clear about what is simulated versus physically tested.
Major issues
Most large scale results are based on simulations or modeled hardware rather than fabricated devices. Real hardware testing would make the claims stronger.
Minor issues
Some of the assumptions behind the theoretical …
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22967716.
This paper studies how analog and wave-based hardware can be kept stable as the number of components increases. It argues that parallel, component-level feedback can provide the information needed for control without increasing sequential acquisition depth. The proposed controller reaches the target tolerance in four to five acquisitions on the tested systems.
The paper also does a good job of being clear about what is simulated versus physically tested.
Major issues
Most large scale results are based on simulations or modeled hardware rather than fabricated devices. Real hardware testing would make the claims stronger.
Minor issues
Some of the assumptions behind the theoretical results, such as the drift model and component observability, are quite specific. A short example showing where these assumptions may not apply would make the scope clearer.
The paper has a lot of technical detail, so a shorter overview of the main takeaway before the mathematical sections would make it easier to follow.
Competing interests
The author declares that they have no competing interests.
Use of Artificial Intelligence (AI)
The author declares that they did not use generative AI to come up with new ideas for their review.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22967765.
This paper studies how analog and wave-based hardware can be kept stable as the number of components increases. It argues that parallel, component-level feedback can provide the information needed for control without increasing sequential acquisition depth. The proposed controller reaches the target tolerance in four to five acquisitions on the tested systems.
The paper also does a good job of being clear about what is simulated versus physically tested.
Major issues
Most large scale results are based on simulations or modeled hardware rather than fabricated devices. Real hardware testing would make the claims stronger.
Minor issues
Some of the assumptions behind the theoretical …
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22967765.
This paper studies how analog and wave-based hardware can be kept stable as the number of components increases. It argues that parallel, component-level feedback can provide the information needed for control without increasing sequential acquisition depth. The proposed controller reaches the target tolerance in four to five acquisitions on the tested systems.
The paper also does a good job of being clear about what is simulated versus physically tested.
Major issues
Most large scale results are based on simulations or modeled hardware rather than fabricated devices. Real hardware testing would make the claims stronger.
Minor issues
Some of the assumptions behind the theoretical results, such as the drift model and component observability, are quite specific. A short example showing where these assumptions may not apply would make the scope clearer.
The paper has a lot of technical detail, so a shorter overview of the main takeaway before the mathematical sections would make it easier to follow.
Competing interests
The author declares that they have no competing interests.
Use of Artificial Intelligence (AI)
The author declares that they did not use generative AI to come up with new ideas for their review.
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