ML-Powered FPGA-based Real-Time Quantum State Discrimination Enabling Mid-circuit Measurements Article Swipe
Neel Vora
,
Yilun Xu
,
Akel Hashim
,
Neelay Fruitwala
,
Hồ Nam Nguyễn
,
Haoran Liao
,
J. Balewski
,
Abhi Rajagopala
,
Kasra Nowrouzi
,
Qing Ji
,
K. Birgitta Whaley
,
Irfan Siddiqi
,
Phuc Nguyen
,
Gang Huang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.18807
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.18807
Similar to reading the transistor state in classical computers, identifying the quantum bit (qubit) state is a fundamental operation to translate quantum information. However, identifying quantum state has been the slowest and most susceptible to errors operation on superconducting quantum processors. Most existing state discrimination algorithms have only been implemented and optimized "after the fact" - using offline data transferred from control circuits to host computers. Real-time state discrimination is not possible because a superconducting quantum state only survives for a few hundred us, which is much shorter than the communication delay between the readout circuit and the host computer (i.e., tens of ms). Mid-circuit measurement (MCM), where measurements are conducted on qubits at intermediate stages within a quantum circuit rather than solely at the end, represents an advanced technique for qubit reuse. For MCM necessitating single-shot readout, it is imperative to employ an in-situ technique for state discrimination with low latency and high accuracy. This paper introduces QubiCML, a field-programmable gate array (FPGA) based system for real-time state discrimination enabling MCM - the ability to measure the state at the control circuit before/without transferring data to a host computer. A multi-layer neural network has been designed and deployed on an FPGA to ensure accurate in-situ state discrimination. For the first time, ML-powered quantum state discrimination has been implemented on a radio frequency system-on-chip FPGA platform. The deployed lightweight network on the FPGA only takes 54 ns to complete each inference. We evaluated QubiCML's performance on superconducting quantum processors and obtained an average accuracy of 98.5% with only 500 ns readout. QubiCML has the potential to be the standard real-time state discrimination method for the quantum community.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2406.18807
- https://arxiv.org/pdf/2406.18807
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400141564
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400141564Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2406.18807Digital Object Identifier
- Title
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ML-Powered FPGA-based Real-Time Quantum State Discrimination Enabling Mid-circuit MeasurementsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-06-27Full publication date if available
- Authors
-
Neel Vora, Yilun Xu, Akel Hashim, Neelay Fruitwala, Hồ Nam Nguyễn, Haoran Liao, J. Balewski, Abhi Rajagopala, Kasra Nowrouzi, Qing Ji, K. Birgitta Whaley, Irfan Siddiqi, Phuc Nguyen, Gang HuangList of authors in order
- Landing page
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https://arxiv.org/abs/2406.18807Publisher landing page
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https://arxiv.org/pdf/2406.18807Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2406.18807Direct OA link when available
- Concepts
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Field-programmable gate array, State (computer science), Computer science, Quantum, Embedded system, Physics, Quantum mechanics, AlgorithmTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(MCM), | 106 |
| abstract_inverted_index.(i.e., | 100 |
| abstract_inverted_index.employ | 142 |
| abstract_inverted_index.ensure | 203 |
| abstract_inverted_index.errors | 35 |
| abstract_inverted_index.method | 272 |
| abstract_inverted_index.neural | 192 |
| abstract_inverted_index.qubits | 112 |
| abstract_inverted_index.rather | 120 |
| abstract_inverted_index.reuse. | 132 |
| abstract_inverted_index.solely | 122 |
| abstract_inverted_index.stages | 115 |
| abstract_inverted_index.system | 165 |
| abstract_inverted_index.within | 116 |
| abstract_inverted_index.(qubit) | 13 |
| abstract_inverted_index.QubiCML | 261 |
| abstract_inverted_index.Similar | 0 |
| abstract_inverted_index.ability | 174 |
| abstract_inverted_index.average | 252 |
| abstract_inverted_index.because | 72 |
| abstract_inverted_index.between | 92 |
| abstract_inverted_index.circuit | 95, 119, 182 |
| abstract_inverted_index.control | 61, 181 |
| abstract_inverted_index.hundred | 82 |
| abstract_inverted_index.in-situ | 144, 205 |
| abstract_inverted_index.latency | 151 |
| abstract_inverted_index.measure | 176 |
| abstract_inverted_index.network | 193, 229 |
| abstract_inverted_index.offline | 57 |
| abstract_inverted_index.quantum | 11, 21, 25, 39, 75, 118, 213, 247, 275 |
| abstract_inverted_index.reading | 2 |
| abstract_inverted_index.readout | 94 |
| abstract_inverted_index.shorter | 87 |
| abstract_inverted_index.slowest | 30 |
| abstract_inverted_index.However, | 23 |
| abstract_inverted_index.QubiCML, | 158 |
| abstract_inverted_index.accuracy | 253 |
| abstract_inverted_index.accurate | 204 |
| abstract_inverted_index.advanced | 128 |
| abstract_inverted_index.circuits | 62 |
| abstract_inverted_index.complete | 238 |
| abstract_inverted_index.computer | 99 |
| abstract_inverted_index.deployed | 198, 227 |
| abstract_inverted_index.designed | 196 |
| abstract_inverted_index.enabling | 170 |
| abstract_inverted_index.existing | 42 |
| abstract_inverted_index.obtained | 250 |
| abstract_inverted_index.possible | 71 |
| abstract_inverted_index.readout, | 137 |
| abstract_inverted_index.readout. | 260 |
| abstract_inverted_index.standard | 268 |
| abstract_inverted_index.survives | 78 |
| abstract_inverted_index.QubiCML's | 243 |
| abstract_inverted_index.Real-time | 66 |
| abstract_inverted_index.accuracy. | 154 |
| abstract_inverted_index.classical | 7 |
| abstract_inverted_index.computer. | 189 |
| abstract_inverted_index.conducted | 110 |
| abstract_inverted_index.evaluated | 242 |
| abstract_inverted_index.frequency | 222 |
| abstract_inverted_index.operation | 18, 36 |
| abstract_inverted_index.optimized | 51 |
| abstract_inverted_index.platform. | 225 |
| abstract_inverted_index.potential | 264 |
| abstract_inverted_index.real-time | 167, 269 |
| abstract_inverted_index.technique | 129, 145 |
| abstract_inverted_index.translate | 20 |
| abstract_inverted_index.ML-powered | 212 |
| abstract_inverted_index.algorithms | 45 |
| abstract_inverted_index.community. | 276 |
| abstract_inverted_index.computers, | 8 |
| abstract_inverted_index.computers. | 65 |
| abstract_inverted_index.imperative | 140 |
| abstract_inverted_index.inference. | 240 |
| abstract_inverted_index.introduces | 157 |
| abstract_inverted_index.processors | 248 |
| abstract_inverted_index.represents | 126 |
| abstract_inverted_index.transistor | 4 |
| abstract_inverted_index.Mid-circuit | 104 |
| abstract_inverted_index.fundamental | 17 |
| abstract_inverted_index.identifying | 9, 24 |
| abstract_inverted_index.implemented | 49, 218 |
| abstract_inverted_index.lightweight | 228 |
| abstract_inverted_index.measurement | 105 |
| abstract_inverted_index.multi-layer | 191 |
| abstract_inverted_index.performance | 244 |
| abstract_inverted_index.processors. | 40 |
| abstract_inverted_index.single-shot | 136 |
| abstract_inverted_index.susceptible | 33 |
| abstract_inverted_index.transferred | 59 |
| abstract_inverted_index.information. | 22 |
| abstract_inverted_index.intermediate | 114 |
| abstract_inverted_index.measurements | 108 |
| abstract_inverted_index.transferring | 184 |
| abstract_inverted_index.communication | 90 |
| abstract_inverted_index.necessitating | 135 |
| abstract_inverted_index.before/without | 183 |
| abstract_inverted_index.discrimination | 44, 68, 148, 169, 215, 271 |
| abstract_inverted_index.system-on-chip | 223 |
| abstract_inverted_index.discrimination. | 207 |
| abstract_inverted_index.superconducting | 38, 74, 246 |
| abstract_inverted_index.field-programmable | 160 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 14 |
| citation_normalized_percentile |