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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.26198 |
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| _version_ | 1866908916894400512 |
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| author | Qi, Haoran Xi, Guohao Zhou, Yuan-Biao Liu, Xinrong Mao, Yifu Yang, Jian Chen, Jun Hu, Kuojuei Gao, Weiwei Zhang, Shuai Gao, Xiaoqin Wan, Jianguo Zhou, Da-Wei An, Junhong Wang, Xuefeng Zhan, De-Chuan Zhang, Minhao Wang, Cong ji, Wei Tan, Yuan-Zhi Xie, Su-Yuan Song, Fengqi |
| author_facet | Qi, Haoran Xi, Guohao Zhou, Yuan-Biao Liu, Xinrong Mao, Yifu Yang, Jian Chen, Jun Hu, Kuojuei Gao, Weiwei Zhang, Shuai Gao, Xiaoqin Wan, Jianguo Zhou, Da-Wei An, Junhong Wang, Xuefeng Zhan, De-Chuan Zhang, Minhao Wang, Cong ji, Wei Tan, Yuan-Zhi Xie, Su-Yuan Song, Fengqi |
| contents | Information units are progressively approaching the fundamental physical limits of the integration density, including in terms of extremely small sizes, multistates and probabilistic traversal. However, simultaneously encompassing all of these characteristics in a unit remains elusive. Here, via real-time in situ electrical monitoring, we clearly observed stochastic alterations of multiple conductance states in Sc2C2@C88. The true random bit sequence generated exhibited an autocorrelation function whose confidence interval fell within \pm 0.02, demonstrating high-quality randomness. The alterations of multiple conductance states are controllable, that is, whose probability distributions could traverse from 0 to 1, enabling us to factorize 551 into its prime factors. Furthermore, we proposed a matrix-chain multiplication scheme and experimentally verified the multiplication of two 4 \times 4 state-transition matrices with a small maximum error < 0.05. Combined with theoretical calculations, the stochastic but controllable multistates are probably attributed to the rich energy landscape, which could be stepwise changed by the electric field. Our findings reveal extremely small multi-level probabilistic bit for matrix multiplication, which pave the way for ultracompact intelligent electronic devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_26198 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Sc2C2@C88 cluster based ultra-compact multi-level probabilistic bit for matrix multiplication Qi, Haoran Xi, Guohao Zhou, Yuan-Biao Liu, Xinrong Mao, Yifu Yang, Jian Chen, Jun Hu, Kuojuei Gao, Weiwei Zhang, Shuai Gao, Xiaoqin Wan, Jianguo Zhou, Da-Wei An, Junhong Wang, Xuefeng Zhan, De-Chuan Zhang, Minhao Wang, Cong ji, Wei Tan, Yuan-Zhi Xie, Su-Yuan Song, Fengqi Materials Science Information units are progressively approaching the fundamental physical limits of the integration density, including in terms of extremely small sizes, multistates and probabilistic traversal. However, simultaneously encompassing all of these characteristics in a unit remains elusive. Here, via real-time in situ electrical monitoring, we clearly observed stochastic alterations of multiple conductance states in Sc2C2@C88. The true random bit sequence generated exhibited an autocorrelation function whose confidence interval fell within \pm 0.02, demonstrating high-quality randomness. The alterations of multiple conductance states are controllable, that is, whose probability distributions could traverse from 0 to 1, enabling us to factorize 551 into its prime factors. Furthermore, we proposed a matrix-chain multiplication scheme and experimentally verified the multiplication of two 4 \times 4 state-transition matrices with a small maximum error < 0.05. Combined with theoretical calculations, the stochastic but controllable multistates are probably attributed to the rich energy landscape, which could be stepwise changed by the electric field. Our findings reveal extremely small multi-level probabilistic bit for matrix multiplication, which pave the way for ultracompact intelligent electronic devices. |
| title | A Sc2C2@C88 cluster based ultra-compact multi-level probabilistic bit for matrix multiplication |
| topic | Materials Science |
| url | https://arxiv.org/abs/2603.26198 |