Wire cutting is a technique for partitioning large quantum circuits into smaller subcircuits in such a way that observables for the original circuits can be estimated from measurements on the smaller subcircuits. Such techniques provide workarounds for the limited numbers of qubits that are available on near-term quantum devices. Wire cutting, however, introduces multiplicative factors in the number of times such subcircuits need to be executed in order to estimate desired quantum observables to desired levels of statistical accuracy. An optimal wire-cutting methodology has recently been reported that uses ancilla qubits to minimize the multiplicative factors involved as a function of the number of wire cuts. Until just recently, the best-known wire-cutting technique that did not employ ancillas asymptotically converged to the same multiplicative factors, but performed significantly worse for small numbers of cuts. This latter technique also requires inserting measurement and state-preparation subcircuits that are randomly sampled from Clifford 2-designs on a per-shot basis. This paper presents a modified wire-cutting approach for pairs of subcircuits that achieves the same optimal multiplicative factors as wire cutting aided by ancilla qubits, but without requiring ancillas. The paper also shows that, while unitary 2-designs provide a sufficient basis for satisfying the decomposition, 2-designs are not mathematically necessary and alternative unitary designs can be constructed for the decompositions that are substantially smaller in size than 2-designs. As this paper was just about to be released, a similar result was published, so we also include a comparison of the two approaches.
Wire cutting is a technique for partitioning large quantum circuits into smaller subcircuits in such a way that observables for the original circuits can be estimated from measurements on the smaller subcircuits. Such techniques provide workarounds for the limited numbers of qubits that are available on near-term quantum devices. Wire cutting, however, introduces multiplicative factors in the number of times such subcircuits need to be executed in order to estimate desired quantum observables to desired levels of statistical accuracy. An optimal wire-cutting methodology has recently been reported that uses ancilla qubits to minimize the multiplicative factors involved as a function of the number of wire cuts. Until just recently, the best-known wire-cutting technique that did not employ ancillas asymptotically converged to the same multiplicative factors, but performed significantly worse for small numbers of cuts. This latter technique also requires inserting measurement and state-preparation subcircuits that are randomly sampled from Clifford 2-designs on a per-shot basis. This paper presents a modified wire-cutting approach for pairs of subcircuits that achieves the same optimal multiplicative factors as wire cutting aided by ancilla qubits, but without requiring ancillas. The paper also shows that, while unitary 2-designs provide a sufficient basis for satisfying the decomposition, 2-designs are not mathematically necessary and alternative unitary designs can be constructed for the decompositions that are substantially smaller in size than 2-designs. As this paper was just about to be released, a similar result was published, so we also include a comparison of the two approaches.
A restriction in the quality and quantity of available qubits presents a substantial obstacle to the application of near-term and early fault-tolerant quantum computers in practical tasks. To confront this challenge, some techniques for effectively augmenting the system size through classical processing have been proposed; one promising approach is quantum circuit cutting. The main idea of quantum circuit cutting is to decompose an original circuit into smaller subcircuits and combine outputs from these subcircuits to recover the original output. Although this approach enables us to simulate larger quantum circuits beyond physically available circuits, it needs classical overheads quantified by two metrics: the sampling overhead in the number of measurements to reconstruct the original output, and the number of channels in the decomposition. Thus, it is crucial to devise a decomposition method that minimizes both of these metrics, thereby reducing the overall execution time. This paper studies the problem of decomposing the n -qubit identity channel, i.e., n -parallel wire cutting, into a set of local operations and classical communication; then we give an optimal wire-cutting method composed of channels based on mutually unbiased bases that achieves minimal overheads in both the sampling overhead and the number of channels, without ancilla qubits. This is in stark contrast to the existing method that achieves the optimal sampling overhead yet with ancilla qubits. Moreover, we derive a tight lower bound on the number of channels in parallel wire cutting without ancilla systems and show that only our method achieves this lower bound among the existing methods. Notably, our method shows an exponential improvement in the number of channels, compared to the aforementioned ancilla-assisted method that achieves optimal sampling overhead. Our work significantly alleviates the additional overheads for the wire-cutting method and may provide essential components for the early success of quantum computing. Published by the American Physical Society 2024
A large-scale quantum circuit can be partitioned into multiple subcircuits through circuit cutting, where each subcircuit is executed multiple times and the expectation value of the original circuit is reconstructed by classical post-processing from their measurement (sampling) results. In this process, appropriate cut locations are identified after the user-designed quantum circuit, including multi-qubit gates that act on three or more qubits, has been decomposed into single-qubit gates and two-qubit gates such as the CNOT gate. Here, we present a method for reducing the sampling overhead, which refers to the increase in the number of samples required due to the cutting process, by modifying the decomposition strategy of multi-qubit gates. Using MCX and CCCX gates as representatives of multi-qubit gates, we demonstrate that the proposed decomposition method, which introduces a small number of ancilla qubits according to the identified cut locations, effectively decreases the sampling overhead.
Current quantum devices face challenges when dealing with large circuits due to error rates as circuit size and the number of qubits increase. The circuit wire-cutting technique addresses this issue by breaking down a large circuit into smaller, more manageable subcircuits. However, the exponential increase in the number of subcircuits and the complexity of reconstruction as more cuts are made poses a great practical challenge. Inspired by ancilla-assisted quantum process tomography and the MUBs-based grouping technique for simultaneous measurement, we propose a new approach that can reduce subcircuit running overhead. The approach first uses ancillary qubits to transform all quantum input initializations into quantum output measurements. These output measurements are then organized into commuting groups for the purpose of simultaneous measurement, based on MUBs-based grouping. This approach significantly reduces the number of necessary subcircuits as well as the total number of shots. Lastly, we provide numerical experiments to demonstrate the complexity reduction.
Quantum circuit cutting enables the execution of large circuits on devices with a limited number of qubits by partitioning circuits into independent subcircuits. However, this introduces a sampling overhead, which grows exponentially with the number of cuts, rendering the choice of cut placements critical for practical circuit cutting. Determining optimal cut placements remains computationally challenging, particularly as circuits grow in size. Additionally, existing circuit cutting approaches typically treat gate and wire cuts independently. Those combining both cutting approaches, however, do not take advantage of joint cutting, i.e., identifying common gate groups and cutting them jointly for a reduced overhead. This work presents a unified framework that combines gate and wire cutting within a single partitioning strategy, enabling more efficient circuit decompositions. Moreover, our approach incorporates joint cutting via a novel gate grouping technique, further reducing sampling overhead. By formulating the cut placement problem as a scalable graph partitioning task, our method efficiently identifies near-optimal cut placements for large circuits, also providing diagnostic feedback on whether circuits are suitable for cutting.
Circuit knitting is the process of partitioning large quantum circuits into smaller subcircuits such that the result of the original circuits can be deduced by only running the subcircuits. Such techniques will be crucial for near-term and early fault-tolerant quantum computers, as the limited number of qubits is likely to be a major bottleneck for demonstrating quantum advantage. One typically distinguishes between gate cuts and wire cuts when partitioning a circuit. The cost for any circuit knitting approach scales exponentially in the number of cuts. One possibility to realize a cut is via the quasiprobability simulation technique. In fact, we argue that all existing rigorous circuit knitting techniques can be understood in this framework. Furthermore, we characterize the optimal overhead for wire cuts where the subcircuits can exchange classical information or not. We show that the optimal cost for cuttingnwires without and with classical communication between the subcircuits scales asO(16n) andO(4n), respectively.
The wire-cutting technique has been recently developed to partition a large quantum circuit into smaller subcircuits, enabling distributed computation across multiple quantum devices with limited capacity. In this work, we generalize the standard wire-cutting method—which can be interpreted as excising an identity operation—to a broader framework that allows the excision of arbitrary unitary gates. We propose a general measure-and-prepare approach to realize this extension, which allows a quantum gate to be excised from a circuit significantly more efficiently than by cutting all the wires surrounding the gate, leading to exponential savings in classical computational cost with respect to the number of wires involved. As an application, we employ this framework for the classical simulation of near-Clifford quantum circuits by excising non-Clifford gates from the circuit and efficiently simulating the remaining Clifford subcircuit in polynomial time. Experimental results demonstrate the superiority of our method over the prior wire-cutting technique in emulating near-Clifford circuits.