Fault-tolerant quantum computing is required to execute many of the most promising quantum applications. In recent years, numerous error correcting codes, such as the surface code, have emerged which are well suited for current and future limited connectivity 2-D devices. We find quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5-D architecture, can efficiently implement surface codes with around 20× fewer transmons via this work. We virtualize 2-D memory addresses by storing the code in layers of qubit memories connected to each transmon. Distributing logical qubits across many memories has minimal impact on fault tolerance and results in substantially more efficient logical operations. Virtualized logical qubit (VLQ) systems can achieve fault tolerance comparable to conventional 2-D transmon-only architectures while putting within reach a proof-of-concept experimental demonstration of around ten logical qubits, requiring only 11 transmons and 9 attached cavities.
Fault-tolerant quantum computing is required to execute many of the most promising quantum applications. In recent years, numerous error correcting codes, such as the surface code, have emerged which are well suited for current and future limited connectivity 2-D devices. We find quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5-D architecture, can efficiently implement surface codes with around 20× fewer transmons via this work. We virtualize 2-D memory addresses by storing the code in layers of qubit memories connected to each transmon. Distributing logical qubits across many memories has minimal impact on fault tolerance and results in substantially more efficient logical operations. Virtualized logical qubit (VLQ) systems can achieve fault tolerance comparable to conventional 2-D transmon-only architectures while putting within reach a proof-of-concept experimental demonstration of around ten logical qubits, requiring only 11 transmons and 9 attached cavities.
Current, near-term quantum devices have shown great progress in the last several years culminating recently with a demonstration of quantum supremacy. In the medium-term, however, quantum machines will need to transition to greater reliability through error correction, likely through promising techniques like surface codes which are well suited for near-term devices with limited qubit connectivity. We discover quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5D architecture, can efficiently implement surface codes with substantial hardware savings and performance/fidelity gains. Specifically, we virtualize logical qubits by storing them in layers of qubit memories connected to each transmon. Surprisingly, distributing each logical qubit across many memories has a minimal impact on fault tolerance and results in substantially more efficient operations. Our design permits fast transversal application of CNOT operations between logical qubits sharing the same physical address (same set of cavities) which are 6x faster than standard lattice surgery CNOTs. We develop a novel embedding which saves approximately 10x in transmons with another 2x savings from an additional optimization for compactness. Although qubit virtualization pays a 10x penalty in serialization, advantages in the transversal CNOT and in area efficiency result in fault-tolerance and performance comparable to conventional 2D transmon-only architectures. Our simulations show our system can achieve fault tolerance comparable to conventional two-dimensional grids while saving substantial hardware. Furthermore, our architecture can produce magic states at 1.22x the baseline rate given a fixed number of transmon qubits. This is a critical benchmark for future fault-tolerant quantum computers as magic states are essential and machines will spend the majority of their resources continuously producing them. This architecture substantially reduces the hardware requirements for fault-tolerant quantum computing and puts within reach a proof-of-concept experimental demonstration of around 10 logical qubits, requiring only 11 transmons and 9 attached cavities in total.
In this short review, I draw attention to new developments in the theory of fault tolerance in quantum computation that may give concrete direction to future work in the development of superconducting qubit systems. The basics of quantum error-correction codes, which I will briefly review, have not significantly changed since their introduction 15 years ago. But an interesting picture has emerged of an efficient use of these codes that may put fault-tolerant operation within reach. It is now understood that two-dimensional surface codes, close relatives of the original toric code of Kitaev, can be adapted as shown by Raussendorf and Harrington to effectively perform logical gate operations in a very simple planar architecture, with error thresholds for fault-tolerant operation simulated to be 0.75%. This architecture uses topological ideas in its functioning, but it is not 'topological quantum computation'—there are no non-abelian anyons in sight. I offer some speculations on the crucial pieces of superconducting hardware that could be demonstrated in the next couple of years that would be clear stepping stones towards this surface-code architecture.
It is well understood that a two-dimensional grid of locally interacting qubits is a promising platform for achieving fault-tolerant quantum computing. However in the near future, it may prove less challenging to develop lower-dimensional structures. In this paper, we show that such constrained architectures can also support fault tolerance; specifically we explore a 2 × N array of qubits where the interactions between non-neighboring qubits are enabled by shuttling the logical information along the rows of the array. Despite the apparent constraints of this setup, we demonstrate that error correction is possible and identify the classes of codes that are naturally suited to this platform. Focusing on silicon spin qubits as a practical example of qubits believed to meet our requirements, we provide a protocol for achieving full universal quantum computation with the surface code, while also addressing the additional constraints that are specific to a silicon spin-qubit device. Through numerical simulations, we evaluate the performance of this architecture using a realistic noise model, demonstrating that both surface code and more complex quantum low-density parity-check codes efficiently suppress gate and shuttling noise to a level that allows for the execution of quantum algorithms within the classically intractable regime. This work thus brings us one step closer to the execution of quantum algorithms that outperform classical machines. Published by the American Physical Society 2024
Quantum computers are far more error-prone than their classical counterparts. Therefore, to build a quantum computer capable of running large-scale quantum algorithms, we must use the techniques of quantum error correction to ensure that the computer produces the correct output even when its components are unreliable. However, the resource requirements of building such a fault-tolerant quantum computer are currently prohibitive. Here, we examine the utility of using three-dimensional (3D) surface codes in a fault-tolerant quantum computer. This family of topological error-correcting codes is a generalization of the well-known 2D surface code to three spatial dimensions. We show that certain 3D surface codes have a transversal logical non-Clifford gate. In a quantum computing architecture, a non-Clifford gate is required to achieve computational universality. Transversal gates do not entangle qubits in different codes, so they are naturally fault tolerant because they do not spread errors. Next, we consider the problem of decoding 3D surface codes. In a quantum error-correcting code, we cannot observe the qubits directly, so we measure parity-check operators to gain information about the state of the code. Decoding is the problem of estimating what error has occurred given a list of unsatisfied parity checks. We observe that 3D surface codes offer asymmetric protection against bit-flip and phase-flip errors, but in both cases, we find that a threshold error rate exists below which we can suppress logical errors by increasing the size of the code. We use our results about logical gates and decoding to propose two fault-tolerant quantum computing architectures that utilize 3D surface codes. Finally, we compare the resource requirements of our architectures with the requirements of leading quantum computing architectures based on topological codes. We find that one of our architectures may be competitive with the leading architectures, depending on the properties of the physical systems used to build the qubits.
Quantum computation holds the promise of solving certain complex problems exponentially faster than classical computers. However, the high prevalent noise in current quantum devices impedes the accurate execution of even basic algorithms. This can be remedied by protecting quantum information with a quantum error-correcting code, where the logical information of an algorithmic qubit is spread across multiple physical qubits. Individual quantum errors are then located and corrected by the fault-tolerant measurement of multi-qubit stabilizer operators (parity checks). Unfortunately, error correction and fault tolerance both impose large demands on the qubit overhead: hundreds to thousands of physical qubits per logical qubit.
We reduce the spacetime cost of fault tolerance by redesigning key building blocks of an error-corrected quantum computer. First, we develop a combinatorial proof with flag fault tolerance that exponentially reduces the extra qubits needed to measure a stabilizer of any size, while tolerating one fault. We leverage these proofs to then design state preparation circuits for the Steane and Golay codes with 100% yield. Next, we improve error correction on a planar layout by showing that a distance-four code encoding six logical qubits protects information as well as the distance-five surface code, using one-tenth as many physical qubits. Finally, we optimize the time overhead of logical gates in surface code quantum computers by protecting measurement results with a classical code, cutting computation time by a factor of two to six. Our hardware-agnostic optimizations of fault tolerance overheads thus suggest new routes to advance the timeline of error-free quantum computing.
Quantum bits have technological imperfections. Additionally, the capacity of a component that can be implemented feasibly is limited. Therefore, distributed quantum computation is required to scale up quantum computers. This dissertation presents a new quantum computer architecture which takes into account imperfections, aimed to realize distributed computation by connecting quantum computers each of which consists of multiple quantum CPUs and memories. Quantum CPUs employ a quantum error correcting code which has faster logical gates and quantum memories employ a code which is superior in space resource requirements. This dissertation focuses on quantum error correcting codes, giving a practical, concrete method for tolerating static losses such as faulty devices for the surface code. Numerical simulation with practical assumptions showed that a yield of functional qubits of 90% is marginally capable of building large-scale systems, by culling the poorer 50% of lattices during post-fabrication testing. Yield 80% is not usable even when culling 90% of generated lattices. For internal connections in a quantum computer and for connections between quantum computers, this dissertation gives a fault-tolerant method that bridges heterogeneous quantum error correcting codes. Numerical simulation showed that the scheme, which discards any quantum state in which any error is detected, always achieves an adequate logical error rate regardless of physical error rates in exchange for increased resource consumption. This dissertation gives a new extension of the surface code suitable for memories. This code is shown to require fewer physical qubits to encode a logical qubit than conventional codes. This code achieves the reduction of 50% physical qubits per a logical qubit. Collectively, the elements to propose the distributed quantum computer architecture are brought together.