Decoherence jeopardizes the entanglement of fragile quantum states, and is among the foremost challenges towards engineering scalable quantum computers. Realizing quantum circuit implementation with small qubit count and shallow circuit depth is necessary due to the linear scaling of decoherence rate with qubit count and circuit depth. Conversely, reasonable correction of small unitary errors can be achieved by using surface codes along with a transversal gate set to protect quantum information from decoherence. In this paper, we analyze and report the upper bound of non-Clifford phase-depth for different mapping schemes and synthesis approaches. We introduce a synthesis methodology based on lookup-table (LUT) networks, wherein the Boolean logic translates into fault-tolerant quantum logic using Clifford+ Z N group with zero ancillary cost. We also present fault-tolerant synthesis techniques for k -LUT network using additional ancillary lines with exponential phase-count and unit phase-depth.
Decoherence jeopardizes the entanglement of fragile quantum states, and is among the foremost challenges towards engineering scalable quantum computers. Realizing quantum circuit implementation with small qubit count and shallow circuit depth is necessary due to the linear scaling of decoherence rate with qubit count and circuit depth. Conversely, reasonable correction of small unitary errors can be achieved by using surface codes along with a transversal gate set to protect quantum information from decoherence. In this paper, we analyze and report the upper bound of non-Clifford phase-depth for different mapping schemes and synthesis approaches. We introduce a synthesis methodology based on lookup-table (LUT) networks, wherein the Boolean logic translates into fault-tolerant quantum logic using Clifford+ Z N group with zero ancillary cost. We also present fault-tolerant synthesis techniques for k -LUT network using additional ancillary lines with exponential phase-count and unit phase-depth.
Lookup Table (LUT) based synthesis methods have recently been proposed as a way to synthesize quantum Boolean circuits in a qubit-constrained environment. Other recent research papers have demonstrated the possibility of using relative phase quantum circuits when compute/uncompute logic is used in tandem, reducing T-count in quantum Boolean circuits in the fault-tolerant quantum computing paradigm. Because LUT-based synthesis methods use compute/uncompute pairs on ancilla qubits, this suggests that implementing the arbitrary Boolean logic that make up the individual Boolean logic network nodes in a relative phase manner could reduce the T-count. To generate such arbitrary Boolean functions, we utilize Shannon’s decomposition, Davio expansions, as well as alternating balanced and unbalanced relative phase circuits. Experimental results demonstrate that our method can reduce the T-count to an average of 24% of the existing method.
To achieve large-scale fault-tolerant quantum computation, it may be easier to combine many small sets of qubits than to construct a single large set. For example via quantum error correction with block codes, or distributed quantum processors utilizing shared entanglement. In these regimes, the time or error budget of the overall quantum computation may be dominated by non-local operations. Hence, it is worthwhile to minimize the number of these operations. We consider the case where both non-local and local connectivity may be arbitrarily restricted, and give an asymptotically optimal synthesis method for distributed CNOT and Clifford circuits, based on block-matrix Gaussian elimination. We extend this to all Clifford+RZ circuits by generalizing the Pauli exponential circuit representation; this naturally integrates with existing methods for optimizing T-count. As an application, we show how to implement CNOT circuits in a CSS code encoding n logical qubits in k blocks using O(nk) inter-block transversal CNOTs and intra-block Pauli measurements.
The inseparable coupling of a quantum system with its environment adds noise at resonant frequencies, causing energy fluctuations and losses entanglement of the fragile quantum state, informally known as decoherence. By truncating Fourier wiggles with the fault-tolerant features, a robust quantum Fourier transform (QFT) scheme can mitigate the decoherence effect. However, a low qubit-count and circuit-depth-based quantum circuit is desirable because of decoherence rate scale up linearly with qubit-count, shortening the coherence time of a fragile quantum state. Indeed, due to the high latency of 1-qubit phase-gates, phase-depth becomes a more dominant factor in circuit-depth and pays a high price for scalability. The above issues are addressed in this manuscript by implementing a fault-tolerant approximate quantum Fourier-transform (AQFT) in linear phase-depth with zero ancillary cost and O(nlogn) phase-count using the Clifford+ ZN -group. By truncating lower rotated phase operators, a robust fault-tolerant AQFT is achieved with linear phase-depth and zero ancillary cost, as well as 75%, 87.6%, 94.22%, and 26.99% average improvements in phase-depth, phase-count, CNOT-count, and ancillary cost respectively over the present-state-of-the-arts 1 . The proposed AQFT maintains polynomially small approximation error, achieving a strong balance between accuracy and efficiency that makes it practical for most algorithms and well suited for NISQ hardware.
Quantum Circuit Pre-Synthesis: Learning Local Edits to Reduce T-count
Compiling quantum circuits into Clifford+T gates is a central task for fault-tolerant quantum computing using stabilizer codes. In the near term, T gates will dominate the cost of fault tolerant implementations, and any reduction in the number of such expensive gates could mean the difference between being able to run a circuit or not. While exact synthesis is exponentially hard in the number of qubits, local synthesis approaches are commonly used to compile large circuits by decomposing them into substructures. However, composing local methods leads to suboptimal compilations in key metrics such as T-count or circuit depth, and their performance strongly depends on circuit representation. In this work, we address this challenge by proposing \textsc{Q-PreSyn}, a strategy that, given a set of local edits preserving circuit equivalence, uses a RL agent to identify effective sequences of such actions and thereby obtain circuit representations that yield a reduced T-count upon synthesis. Experimental results of our proposed strategy, applied on top of well-known synthesis algorithms, show up to a 20% reduction in T-count on circuits with up to 25 qubits, without introducing any additional approximation error prior to synthesis.
LUT-based synthesis methods have recently been proposed as a way to synthesize quantum Boolean circuits in a qubit constrained environment. Other results have also shown that allowing a relative phase when implementing quantum Boolean circuits yields an advantage in T-count without additional ancilla qubits, which is advantageous in the fault-tolerant quantum computing paradigm. We propose a method that utilizes both LUT-based synthesis and relative phase quantum Boolean circuits which minimize the T-count while minimizing the ancilla required to implement them. We leverage recent results regarding relative phase versions of Boolean functions and Shannon's decomposition to propose a novel method to synthesize arbitrary Boolean functions up to a relative phase. We then utilize this method to synthesize Boolean logic inside each LUT as a relative phase quantum Boolean circuit and show that the resulting quantum circuit has a clear advantage in T-count over more naive methods.
Preparing arbitrary logical states is a central primitive for universal fault-tolerant quantum computation and the cost of encoded-state preparation contributes directly to the overall resource overhead. This makes the synthesis of efficient general-state encoding circuits an important problem, particularly with respect to two-qubit gate count and circuit depth. Yet the synthesis of such encoders has been studied less extensively than general Clifford circuit synthesis or the preparation of specific logical Pauli-eigenstates. In this work, we develop methods for synthesizing efficient encoders for arbitrary stabilizer codes. We formulate encoder synthesis as a search over stabilizer tableaus and introduce greedy and rollout-based algorithms that exploit the freedom among stabilizer-equivalent realizations of the same encoding isometry. For code families with a modular structure, such as generalized concatenated and holographic codes, we show how large encoders can be assembled from optimized local constituent encoders, and we use SMT-based exact synthesis to obtain optimal local circuits for small instances. We further evaluate the proposed methods on a broad set of stabilizer codes, including holographic and quantum low-density parity-check (qLDPC) codes, and compare them against recent encoder-synthesis methods and existing constructions from the literature, obtaining improvements of up to 43% in two-qubit gate count and up to 70% in depth. Our results support the optimization of encoded-state preparation in several fault-tolerant quantum-computing schemes, and all methods are openly available as part of the Munich Quantum Toolkit.