In-Cryostat Error Correction using Hybrid SFQ-NPU and Topological Quantum Qubits

In this article, I propose a new way to build a quantum computer.

The most recent quantum chips are Majorana 1 by Microsoft and Willow by Google.

The proposed way to build a quantum computer is to combine a TPU(Tensor Processing Unit) and a Willow or Majorana 1 or any other type of quantum chip.

The problem with this design is temperature differences.
The TPU runs on high temperatures, while the average quantum computer runs on ~-273° C, near absolute zero.

Luckily, there is a chip called SFQ-NPU(Single-Flux Quantum Neural Processing Unit).
This chip can run in temperatures like those experienced by quantum computers.

So in theory, combining these chips will result in a single QPU-TPU chip.

A promising way to combine these chips into 1 is 3D Flip-Chip Bonding, this technique uses microscopic Indium Bumps to connect the chips together.

Since SFQ-NPU speaks in Digital(pulses), and the quantum chip speaks in Analog(waves), we can treat the SFQ-NPU  like a Digital-to-Analog Converter (DAC).
The SQU-NPU will fire its pulses rapidly and in some specific pattern that it’s waves will look like one specific wave.

There are no changes for the one writing the code!
For example, to rotate a qubit in python, qubit.rotate_X().

Due to temperature requirements, the full SFQ-NPU-QPU chip will still unfortunately have to stay in a dilution refrigerator.

I hope that these changes will accelerate AI production speed and allow large-scale simulations and specific data to be found.