Recently it was shown that the resources required to implement unitary operations on a quantum computer can be reduced by using probabilistic quantum circuits called repeat-until-success (RUS) circuits. However, the previously best-known algorithm to synthesize a RUS circuit for a given target unitary requires exponential classical runtime. We present a probabilistically polynomial-time algorithm to synthesize a RUS circuit to approximate any given single-qubit unitary to precision ϵ over the Clifford+T basis. Surprisingly, the T count of the synthesized RUS circuit surpasses the theoretical lower bound of 3 log_{2}(1/ϵ) that holds for purely unitary single-qubit circuit decomposition. By taking advantage of measurement and an ancilla qubit, RUS circuits achieve an expected T count of 1.15 log_{2}(1/ϵ) for single-qubit z rotations. Our method leverages the fact that the set of unitaries implementable by RUS protocols has a higher density in the space of all unitaries compared to the density of purely unitary implementations.
Recently it was shown that the resources required to implement unitary operations on a quantum computer can be reduced by using probabilistic quantum circuits called repeat-until-success (RUS) circuits. However, the previously best-known algorithm to synthesize a RUS circuit for a given target unitary requires exponential classical runtime. We present a probabilistically polynomial-time algorithm to synthesize a RUS circuit to approximate any given single-qubit unitary to precision ϵ over the Clifford+T basis. Surprisingly, the T count of the synthesized RUS circuit surpasses the theoretical lower bound of 3 log_{2}(1/ϵ) that holds for purely unitary single-qubit circuit decomposition. By taking advantage of measurement and an ancilla qubit, RUS circuits achieve an expected T count of 1.15 log_{2}(1/ϵ) for single-qubit z rotations. Our method leverages the fact that the set of unitaries implementable by RUS protocols has a higher density in the space of all unitaries compared to the density of purely unitary implementations.
Repeat-until-success (RUS) circuits can approximate a given single-qubit unitary with an expected number of T gates of about 31 of what is required by optimal, deterministic, ancilla-free decompositions over the Clifford + T gate set. In this work, we introduce a more general and conceptually simpler circuit decomposition method that allows for synthesis into protocols that probabilistically implement quantum circuits over several universal gate sets including, but not restricted to, the Clifford + T gate set. The protocol, which we call probabilistic quantum circuits with fallback (PQF), implements a walk on a discrete Markov chain in which the target unitary is an absorbing state and in which transitions are induced by multiqubit unitaries followed by measurements. In contrast to RUS protocols, the presented PQF protocols are guaranteed to terminate after a finite number of steps. Specifically, we apply our method to the Clifford + T, Clifford + V, and Clifford + $\ensuremath{\pi}/12$ gate sets to achieve decompositions with expected gate counts of ${log}_{b}(1/\ensuremath{\varepsilon})+O{ln[ln(1/\ensuremath{\varepsilon})]}$, where b is a quantity related to the expansion property of the underlying universal gate set.
We present a decomposition technique that uses non-deterministic circuits to approximate an arbitrary single-qubit unitary to within distance ε and requires significantly fewer non-Clifford gates than existing techniques. We develop "Repeat-Until-Success" (RUS) circuits and characterize unitaries that can be exactly represented as an RUS circuit. Our RUS circuits operate by conditioning on a given measurement outcome and using only a small number of non-Clifford gates and ancilla qubits. We construct an algorithm based on RUS circuits that approximates an arbitrary single-qubit Z-axis rotation to within distance ε, where the number of T gates scales as 1.26log2(1/ε)−3.53, an improvement of roughly three-fold over state-of-the-art techniques. We then extend our algorithm and show that a scaling of 2.4log2(1/ε)−3.28 can be achieved for arbitrary unitaries and a small range of ε, which is roughly twice as good as optimal deterministic decomposition methods.
We present a decomposition technique that uses non-deterministic circuits to approximate an arbitrary single-qubit unitary to within distance ϵ and requires significantly fewer non-Clifford gates than existing techniques. We develop ``Repeat-Until-Success" (RUS) circuits and characterize unitaries that can be exactly represented as an RUS circuit. Our RUS circuits operate by conditioning on a given measurement outcome and using only a small number of non-Clifford gates and ancilla qubits. We construct an algorithm based on RUS circuits that approximates an arbitrary single-qubit Z-axis rotation to within distance ϵ, where the number of T gates scales as 1.26log2(1/ϵ)−3.53, an improvement of roughly three-fold over state-of-the-art techniques. We then extend our algorithm and show that a scaling of 2.4log2(1/ϵ)−3.28 can be achieved for arbitrary unitaries and a small range of ϵ, which is roughly twice as good as optimal deterministic decomposition methods.
Approximate synthesis of general single-qubit unitaries over the Clifford+T gate set
For the standard Clifford+T gate set, deterministic, ancilla-free synthesis now attains the minimal T-count for general single-qubit unitaries (Morisaki et al., arXiv:2510.05816). The T gate rotates by half the angle of T, generating a finer lattice of implementable operations. Access to this magic state is expected to lower the cost of deterministic and ancilla-free synthesis of general single-qubit unitaries (Kliuchnikov et al., arXiv:2203.10064), but no direct Clifford+T algorithm existed for this case. We provide one by extending the integer lattice-point enumeration method of Morisaki et al. We adopt a resource state cost model based on the magic-state catalysis approach of Gidney and Fowler (arXiv:1812.01238). On Haar-random targets synthesized to precisions ranging from ε=10−3 to 10−8, the cost of Clifford+T circuits scales as 2.4log2(1/ε) compared to 3.0log2(1/ε) for T-count-optimal Clifford+T circuits. Once a one-time catalyst state is amortized, the Clifford+T circuits are never costlier than their Clifford+T counterparts.
We develop a method for approximate synthesis of single-qubit rotations of the form e−if(φ1,...,φk)X that is based on the Repeat-Until-Success (RUS) framework for quantum circuit synthesis. We demonstrate how smooth computable functions f can be synthesized from two basic primitives. This synthesis approach constitutes a manifestly quantum form of arithmetic that differs greatly from the approaches commonly used in quantum algorithms. The key advantage of our approach is that it requires far fewer qubits than existing approaches: as a case in point, we show that using as few as 3 ancilla qubits, one can obtain RUS circuits for approximate multiplication and reciprocals. We also analyze the costs of performing multiplication and inversion on a quantum computer using conventional approaches and find that they can require too many qubits to execute on a small quantum computer, unlike our approach.
We propose two Clifford+T synthesis algorithms that are optimal with respect to T-count. The first algorithm, called deterministic synthesis, approximates any single-qubit unitary by a single-qubit Clifford+T circuit with the minimum T-count. The second algorithm, called probabilistic synthesis, approximates any single-qubit unitary by a probabilistic mixture of single-qubit Clifford+T circuits with the minimum T-count. For most of single-qubit unitaries, the runtimes of deterministic synthesis and probabilistic synthesis are ε−1/2−o(1) and ε−1/4−o(1), respectively, for an approximation error ε. Although this complexity is exponential in the input size, we demonstrate that our algorithms run in practical time at ε≈10−15 and ε≈10−22, respectively. Furthermore, we show that, for most single-qubit unitaries, the deterministic synthesis algorithm requires at most 3log2(1/ε)+o(log2(1/ε))T-gates, and the probabilistic synthesis algorithm requires at most 1.5log2(1/ε)+o(log2(1/ε))T-gates. Remarkably, complexity analyses in this work do not rely on any numerical or number-theoretic conjectures.