29.3 A Cryo-CMOS Receiver with 15K Noise Temperature Achieving 9.8dB SNR in 10μs Integration Time for Spin Qubit Readout.

IEEE International Solid-State Circuits Conference(2024)

引用 0|浏览1
暂无评分
摘要
Continuous rounds of quantum error correction (QEC) are essential to achieve fault-tolerant quantum computers (QCs). In each QEC cycle, thousands of ancilla quantum bits (qubits) must be read out faster than the qubits’ decoherence time $(\gg \mathrm{T}_{2} * \sim 120 \mu \mathrm{s}$ for spin qubits). To address this urgent need, several CMOS receivers operating at cryogenic temperatures (cryo-CMOS RXs) have recently been introduced for gate-based [1] and RF reflectometry [2] readout of spin qubits, as well as transmons’ dispersive readout [3]. However, they have a few shortcomings. First, due to the temperature-independent shot noise of transistors in nanometer CMOS technology [4], their measured noise temperature $(\mathrm{T}_{{\mathrm {N}}})$ is limited to 40K, thus degrading qubit readout fidelity. Second, due to their large T N , prior art showed either only the electrical performance of their chips by applying a relatively large (i.e., -85dBm [2]) modulated signal directly to the RX input [2, 3] or offered limited qubit measurements by exploiting a HEMT amplifier prior to the RX [1]. Those issues hinder future monolithic integration between solid-state qubits and readout electronics. This work advances the prior art by (1) introducing a wideband passive amplification circuit at the RX front-end to minimize the shot noise contribution of the active devices, lowering prior art T N by $\sim 2.7\mathrm{x}$; (2) demonstrating the RX performance in an RF-reflectometry qubit readout scheme without using off-the-shelf LNA prior to the RX.
更多
查看译文
关键词
Integration Time,Noise Temperature,Qubit Readout,Random Noise,Inverter,Operating Frequency,Thermal Noise,Bit Error Rate,Active Devices,Bit Error,Shot Noise,Parasitic Capacitance,Cryogenic Temperatures,Prior Art,Qubit State,Operating Frequency Range,Quantum Error Correction,Passive Network,Dilution Refrigerator
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要