A general framework to define quantum circuit architecture witnesses, which certify the incompatibility of a unitary transformation with a specified quantum circuit architecture, and exploit the stabiliser formalism to reduce the construction to linear programming.
Abstract
Determining whether a target unitary can be implemented within a prescribed quantum circuit architecture is a fundamental problem in quantum information, with direct implications for optimisation and compilation of quantum circuits, and hardware-efficient quantum computation. While existing synthesis and compilation methods are primarily constructive, they generally do not provide rigorous certificates that a unitary cannot be realised using given implementation resources. Here we introduce a general framework to define quantum circuit architecture witnesses, which certify the incompatibility of a unitary transformation with a specified quantum circuit architecture. We formulate the witness construction as a semidefinite program by maximising the fidelity between the Choi state of the target unitary and those of tested circuits. The resulting witnesses provide practical and quantitative certificates of incompatibility, implying lower bounds on implementation resources such as the gate count or circuit depth, and can also be used experimentally to benchmark quantum devices by certifying that an implemented unitary channel goes beyond the capabilities of a given circuit architecture. For Clifford unitaries, we exploit the stabiliser formalism to reduce the construction to linear programming, enabling both more efficient numerical certification for circuits containing on the order of seven two-qubit gates, and analytical witnesses for some families of architectures made of an arbitrary number of gates.
Here it is shown that minimized expressions retain algebraic structure minimization cannot reach, arising from containment and complementary-polarity relationships among their terms, and that extracting it yields circuits cheaper to execute despite having more operations.
Mehul A. Shah, Robert Fiszer, M. Perkowski· 0 citations
This paper presents an algorithm that converts a circuit containing a sequence of CNOT gates into a form that is suitable for arbitrary quantum computer architectures, and demonstrates the algorithm only in the context of quantum fingerprinting.
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A Clifford+T quantum circuit construction that approximately implements any classically specified unitary to within error $\epsilon$ and achieves a worst-case $T$-count with leading exponential scaling of $2^{5n/4}$ whenever $\log(1/\epsilon)=\operatorname{poly}(n)$.
Dynamic quantum circuits (DQCs) provide a hardware-efficient route to quantum computing by reducing physical-qubit overhead and compressing circuit topology through mid-circuit measurements, qubit reset and reuse, and classical feed-forward control. Here, we demonstrate the advantages of DQCs on a single hybrid superconducting qubit-cavity processor by implementing a hierarchy of algorithms with increasing complexity. This hybrid architecture consists of a high-dimensional cavity qudit serving as the computational register and a dispersively coupled superconducting transmon ancilla that is repeatedly measured, reset, and reused to enable dynamic control. Using this device, we implement a 10-bit Bernstein-Vazirani algorithm with an average success probability of 82%, surpassing state-of-the-art dynamic and static implementations in both scale and performance; an 8-bit quantum phase-estimation protocol with estimation errors below 10-3; and the first dynamic-circuit implementation of Shor's algorithm on a superconducting platform, factoring 15 over all coprime bases with squared statistical overlap values above 99.8%. These results provide concrete benchmarks for future DQC implementations and highlight the versatile advantages of DQCs with the hybrid qubit-qudit architecture, establishing it as a promising route toward scalable, programmable quantum computation.
Hongbo Wu, Ling Hu, Jiasheng Mai et al.· 0 citations
Encoding classical data into quantum systems is a foundational step in the execution of nearly all quantum algorithms, and a critical bottleneck in realizing practical quantum advantage. This review provides a comprehensive account of the concepts, algorithms, and practical considerations associated with quantum data encoding. We trace the development from its early conceptual foundations to recent advances, considering commonly used access models, such as quantum state preparation, unitary synthesis, QRAM and block encoding. We survey the circuit size, depth, space-time tradeoffs, as well as non-Clifford resources required for fault-tolerant implementation. We also discuss the roles of different access models in quantum algorithms. Special attention is given to structured data, such as sparse data, Boolean functions and data represented by tensor networks. This review bridges theory and applications, serving both as a pedagogical guide for newcomers and as a reference for active researchers. We also highlight the pivotal role of quantum data encoding in quantum computing and provide insights into future directions that will enable quantum advantage.
Xiao-Ming Zhang, Arthur G. Rattew, Bu-Jiao Wu et al.· 1 citation
Current quantum programs are mainly designed at the level of quantum gates acting on individual qubits; on a large scale and for complex problems this may involve a high cognitive load on the programmer, making the program specification nontrivial and error-prone. In this context, providing quantum programming with higher abstraction mechanisms will assist in making this task more manageable and robust against design errors. In this work, a conceptual framework is addressed following the notion of the whole quantum computation as a structure composed of quantum registers representing each an undivided entity. Thus, computation progresses through semantically well-defined transformations that act on, or entangle, quantum registers, thereby modifying the global state. Ultimately, the program reaches the desired state by following a specific composition strategy. With this in mind, high-level syntax is presented through an algebraic formalism that bridges them with their low-level semantics. Proposed syntax is based on certain well-know operations used on quantum algorithms that apply phase shifts upon logical condition satisfaction or leverage on parallel evaluation. Based solely on the formalized operations, a quantum satisfiability modulo theories (SMT) solver can be designed. At its core, this work contributes to establishing some methodological principles towards realizing a high-level quantum structured programming.
David Chamizo, José García-Alonso, J. M. Murillo· 0 citations
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