![]() The first three kinds of ADC have larger circuit scales and higher power dissipation compared with SAR ADC under the same performance. The most commonly used ADCs are Flash ADC, Pipeline ADC, Sigma-Delta ADC and SAR ADC. Nevertheless, a practical quantum computer needs more than thousands of qubits, which means that this method is impractical due to the complexity and reliability of the system. ![]() For example, the readout and control module of a 72-qubit superconducting quantum processor requires 168 long and lossy coax paths from 300 K to 4 K and 168 superconducting coax from 4 K to 10 mK. The state-of-art quantum computers possess only a few qubits which can be controlled and read out by room-temperature (RT) electronics which are connected to the cryogenic qubits through only a few coaxial cables. Typically, the quantum processor operates down to cryogenic temperature to maintain the fidelity of quantum bits. ![]() Although the quantum computer has shown great computing potential in specific problems, it also has some difficulties such as the readout and control of quantum bits. The overall power dissipation of the quantum computer system is about tens of kilowatts, which is only a few hundredths of that of classical supercomputers. The classical computational cost of simulating the state-of-art quantum processor’s sample task is estimated to be 6 orders of magnitude higher than that of the most complex tasks on the “Sycamore”. Additionally, a state-of-art quantum processor named “zuchongzhi 2.1” made the random quantum circuit sampling with a system scale up to 60 qubits and 24 cycles. ![]() The processor can sample an instance of quantum circuit for 1 million times in 200 s, which has incomparable advantages over classical supercomputers for the same task. The researchers from Google developed a programmable superconducting quantum processor “Sycamore” containing 53 available qubits in 2019. ![]() Relevant research shows that quantum computers are overwhelming faster than conventional supercomputers in solving specific problems. ![]()
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