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Sengthai Heng

Publications and source records attributed to Sengthai Heng.

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Enhancing the Yield of Bucket Brigade Quantum Random Access Memory using Redundancy Repair

Quantum Random Access Memory (qRAM) is an essential computing element for running oracle-based quantum algorithms. qRAM exploits quantum superposition to access all data stored in the memory cells simultaneously and guarantees the superior performance of quantum algorithms. A qRAM memory cell comprises logical qubits encoded through quantum error correction technology for successful operation against various quantum noises. In addition to quantum noise, the low-technology nodes based on silicon technology can increase the qubit density and may introduce defective qubits. As qRAM comprises many qubits, its yield will be reduced by defective qubits; these qubits must be handled using QEC scheme. However, the QEC scheme requires numerous physical qubits, which burdens resource overhead. In this paper, to resolve this overhead problem, we propose a novel quantum memory architecture that compensates for defective qubits by introducing redundant qubits. We also analyze the yield improvement offered by our proposed quantum memory architecture by varying the ideal fabrication error rate from 0.5% to 1% for different numbers of logical qubits in the qRAM. We demonstrate that for the qRAM comprising 1,024 logical qubits, eight redundant logical qubits improved the yield by 95.92% from that of qRAM not employing the redundant repair scheme.

quant-ph

Context-Aware Coupler Reconfiguration for Tunable Coupler-Based Superconducting Quantum Computers

We address interconnection challenges in limited-qubit superconducting quantum computers (SQC), which often face crosstalk errors due to expanded qubit interactions during operations. Existing mitigation methods carry trade-offs, like hardware couplers or software-based gate scheduling. Our innovation, the Context-Aware COupler REconfiguration (CA-CORE) compilation method, aligns with application-specific design principles. It optimizes the qubit connections for improved SQC performance, leveraging tunable couplers. Through contextual analysis of qubit correlations, we configure an efficient coupling map considering SQC constraints. Our method reduces depth and SWAP operations by up to 18.84% and 42.47%, respectively. It also enhances circuit fidelity by 40% compared to IBM and Google's topologies. Notably, our method compiles a 33-qubit circuit in less than 1 second.

quant-ph