A Finite State Automaton for the Tsetlin Machine Using High-Capacity Resettable D Flip-Flop Cells

Read full text
Authors: Zeyu Han, Nobuyuki Yoshikawa, Yuki Yamanashi
Cited by: 0
References: 26

Abstract

Single Flux Quantum (SFQ) circuits provide ultrafast operation and low power consumption, making them attractive candidates for machine learning accelerators. The Tsetlin Machine (TM) is a low-complexity and highly interpretable architecture, organized as a voting system of propositional clauses. In the TM, an ensemble of finite-state automata (FSAs), called Tsetlin automata, independently decides whether to include or exclude specific literals. The chosen literals are assembled into propositional clauses that collectively form the voting system, while each FSA updates its state based on rewards or penalties determined by the prediction outcome. However, existing FSA designs for TM based on SFQ circuits still suffer from either a narrow margin or excessive circuit area. To achieve compact and stable state transitions using SFQ circuits, we designed High-Capacity Resettable D Flip-Flop (HC-RDFF) cells by cascading storage loops. The proposed FSA was implemented using two HC-RDFFs to store the include and exclude states, respectively. The FSA with 16 states requires only 395 Josephson junctions with a static power of approximately 128 μW, exhibiting a bias margin of −21% to +25% at low speed and a maximum operating frequency of 20 GHz in simulation. We fabricated the HC-RDFF and the FSA using a 10 kA/cm² Nb four-layer superconducting process and verified their correct operation through low-speed measurements. The number of FSA states can be increased simply by extending the cascaded storage loops in the HC-RDFFs. We expect the proposed FSA to be suitable for constructing stable TM systems based on SFQ circuits with reduced hardware costs.

Fields of Study & Subjects

Superconducting and THz Device Technology Advanced Memory and Neural Computing Quantum Information and Cryptography

Publication details

Journal / source
IEEE Transactions on Applied Superconductivity
Volume
36
Issue
5
Pages
1–6
Publication date
27 January 2026
Language
EN