arXiv subjects

Shenggang Ying

Publications and source records attributed to Shenggang Ying.

At least 19 recordsLinked to original sources

arXiv2026

Oracle Synthesis Based on X-Map Decision Diagrams

Quantum oracles act as reversible black-box operators that encode classical Boolean functions into quantum states, enabling efficient function evaluation in quantum superposition. The resource efficiency of oracle implementation is critical to the performance of numerous quantum algorithms. Most state-of-the-art oracle synthesis approaches rely on compact Boolean function representations such as exclusive-sum-of-products (ESOP), yet still suffer from excessive $T$-count and $CX$-count for large-scale functions. In this paper, we propose a novel compact representation named X-Map decision diagram (XMDD) for Boolean functions, which integrates local invertible maps and complement edges to achieve higher compression efficiency. Based on XMDD, we further develop an optimized quantum oracle synthesis algorithm. Extensive experimental results demonstrate that, for Boolean functions with more than seven input variables, our method outperforms the state-of-the-art ESOP-based approach and Qiskit in nearly all test cases, achieving simultaneous reduction in both $T$-count and $CX$-count without an obvious trade-off. Moreover, we show that the performance can be further boosted by employing more optimal variable orderings. The proposed XMDD-based framework provides a scalable and resource-efficient solution for practical oracle synthesis in near-term and fault-tolerant quantum computing.

quant-ph↗

arXiv2026

Hamiltonian-Aware ADAPT Variational Quantum Eigensolver for Molecular Ground-State Simulation

Designing compact ansätze in Variational Quantum Eigensolver (VQE) is crucial for solving energetic problems of practical molecules on near-term quantum devices. However, existing Adaptive Derivative-Assembled Pseudo-Trotter (ADAPT) ansätze face two challenges: improper operator selection and accumulation of degraded operators. In this paper, we propose the Hamiltonian-Aware (HA) ADAPT-VQE algorithm to address these issues. First, we establish a novel excitation operator selection criterion. It breaks the local constraint of existing criteria by incorporating Hamiltonian information, prioritizes physically meaningful excitation operators, and incurs no extra classical or quantum computational overhead. Furthermore, we develop a problem-adaptive method for discriminating and pruning redundant excitation operators stemming from improper selection and inevitable degradation. This method balances redundant operator pruning and convergence guarantee, and is applicable to ansätze with arbitrary scales. Systematic numerical experiments on typical strongly correlated molecular systems demonstrate that our HA-ADAPT-VQE avoids energy plateaus and outperforms baseline algorithms in terms of energy error, ansatz size, and measurement cost. This work offers an efficient, robust ansatz construction paradigm, facilitating the development and practical deployment of large-scale VQE in quantum chemistry.

quant-ph↗

arXiv2026

Constructing Compact ADAPT Unitary Coupled-Cluster Ansatz with Parameter-Based Criterion

The adaptive derivative-assembled pseudo-trotter variational quantum eigensolver (ADAPT-VQE) is a promising hybrid quantum-classical algorithm for molecular ground state energy calculation, yet its practical scalability is hampered by redundant excitation operators and excessive measurement costs. To address these challenges, we propose Param-ADAPT-VQE, a novel improved algorithm that selects excitation operators based on a parameter-based criterion instead of the traditional gradient-based metric. This strategy effectively eludes redundant operators. We further develop a sub-Hamiltonian technique and integrate a hot-start VQE optimization strategy, achieving a significant reduction in measurement costs. Numerical experiments on typical molecular systems demonstrate that Param-ADAPT-VQE outperforms the original ADAPT-VQE in computational accuracy, ansatz size, and measurement costs. Furthermore, our scheme retains the fundamental framework of ADAPT-VQE and is thus fully compatible with its various modified versions, enabling further performance improvements in specific aspects. This work presents an efficient and scalable enhancement to ADAPT-VQE, mitigating the core obstacles that impede its practical implementation in the field of molecular quantum chemistry.

quant-ph↗

arXiv2025

SOFT: a high-performance simulator for universal fault-tolerant quantum circuits

Circuit simulation tools are critical for developing and assessing quantum-error-correcting and fault-tolerant strategies. In this work, we present SOFT, a high-performance SimulatOr for universal Fault-Tolerant quantum circuits. Integrating the generalized stabilizer formalism and highly optimized GPU parallelization, SOFT enables the simulation of noisy quantum circuits containing non-Clifford gates at a scale not accessible with existing tools. To provide a concrete demonstration, we simulate the state-of-the-art magic state cultivation (MSC) protocol at code distance $d=5$, involving 42 qubits, 72 $T$ / $T^\dagger$ gates, and mid-circuit measurements. Using only modest GPU resources, SOFT performs over 200 billion shots and achieves the first ground-truth simulation of the cultivation protocol at a non-trivial scale. This endeavor not only certifies the MSC's effectiveness for generating high-fidelity logical $T$-states, but also reveals a large discrepancy between the actual logical error rate and the previously reported values. Our work demonstrates the importance of reliable simulation tools for fault-tolerant architecture design, advancing the field from simulating quantum memory to simulating a universal quantum computer.

quant-ph↗

arXiv2025

Hamiltonian-Informed Point Group Symmetry-Respecting Ansatz for Variational Quantum Eigensolver

Solving molecular energy levels via the Variational Quantum Eigensolver (VQE) algorithm represents one of the most promising applications for demonstrating practically meaningful quantum advantage in the noisy intermediate-scale quantum (NISQ) era. To strike a balance between ansatz complexity and computational stability in VQE calculations, we propose the HiUCCSD, a novel symmetry-respecting ansatz engineered from the intrinsic information of the Hamiltonian. We theoretically prove the effectiveness of HiUCCSD within the scope of Abelian point groups. Furthermore, we compare the performance of HiUCCSD and the established SymUCCSD via VQE and Adaptive Derivative-Assembled Pseudo-Trotter (ADAPT)-VQE numerical experiments on ten molecules with distinct point groups. The results show that HiUCCSD achieves equivalent performance to SymUCCSD for Abelian point group molecules, while avoiding the potential performance failure of SymUCCSD in the case of non-Abelian point group molecules. Across the studied molecular systems, HiUCCSD cuts the parameter count by 18%-83% for VQE and reduces the excitation operator pool size by 27%-84% for ADAPT-VQE, as compared with the UCCSD ansatz. With enhanced robustness and broader applicability, HiUCCSD offers a new ansatz option for advancing large-scale molecular VQE implementation.

physics.chem-ph↗

arXiv2025

Utilizing Quantum Processor for the Analysis of Strongly Correlated Materials

This study introduces a systematic approach for analyzing strongly correlated systems by adapting the conventional quantum cluster method to a quantum circuit model. We have developed a more concise formula for calculating the cluster's Green's function, requiring only real-number computations on the quantum circuit instead of complex ones. This approach is inherently more suited to quantum circuits, which primarily yield statistical probabilities. As an illustrative example, we explored the Hubbard model on a 2D lattice. The ground state is determined utilizing Xiaohong, a superconducting quantum processor equipped with 66 qubits, supplied by QuantumCTek Co., Ltd. Subsequently, we employed the circuit model to compute the real-time retarded Green's function for the cluster, which is then used to determine the lattice Green's function. We conducted an examination of the band structure in the insulator phase of the lattice system. This preliminary investigation lays the groundwork for exploring a wealth of innovative physics within the field of condensed matter physics.

quant-ph↗

arXiv2025

Advancing Quantum State Preparation Using Decision Diagram with Local Invertible Maps

Quantum state preparation (QSP) is a fundamental task in quantum computing and quantum information processing. It is critical to the execution of many quantum algorithms, including those in quantum machine learning. In this paper, we propose a family of efficient QSP algorithms tailored to different numbers of available ancilla qubits - ranging from no ancilla qubits, to a single ancilla qubit, to a sufficiently large number of ancilla qubits. Our approach exploits the power of Local Invertible Map Tensor Decision Diagrams (LimTDDs) - a highly compact representation of quantum states that combines tensor networks and decision diagrams to reduce quantum circuit complexity. Extensive experiments demonstrate that our methods significantly outperform existing approaches and exhibit better scalability for large-scale quantum states, both in terms of runtime and gate complexity. Furthermore, our method shows exponential improvement in best-case scenarios.

cs.DS↗

arXiv2025

Quantum State Preparation Based on LimTDD

Quantum state preparation is a fundamental task in quantum computing and quantum information processing. With the rapid advancement of quantum technologies, efficient quantum state preparation has become increasingly important. This paper proposes a novel approach for quantum state preparation based on the Local Invertible Map Tensor Decision Diagram (LimTDD). LimTDD combines the advantages of tensor networks and decision diagrams, enabling efficient representation and manipulation of quantum states. Compared with the state-of-the-art quantum state preparation method, LimTDD demonstrates substantial improvements in efficiency when dealing with complex quantum states, while also reducing the complexity of quantum circuits. Examples indicate that, in the best-case scenario, our method can achieve exponential efficiency gains over existing methods. This study not only highlights the potential of LimTDD in quantum state preparation but also provides a robust theoretical and practical foundation for the future development of quantum computing technologies.

quant-ph↗

arXiv2025

Gradient-Based Excitation Filter for Molecular Ground-State Simulation

Molecular ground-state simulation is one of the most promising fields for demonstrating practical quantum advantage on near-term quantum computers. However, the Variational Quantum Eigensolver (VQE), a leading algorithm for this task, still faces significant challenges due to excessive circuit depth. This paper introduces a method to efficiently simplify the Unitary Coupled-Cluster with Single and Double Excitations (UCCSD) ansatz on classical computers. We propose to estimate the correlation energy contributions of excitations using their gradients at Hartree-Fock state, supported by a theoretical proof. For molecular systems with $K$ orbitals, these gradients can be obtained with complexity only $O(K^8)$, which can be efficiently implemented on classical computers, especially in parallel. By sorting and truncating the excitations based on these gradients, the simplified ansatz can be obtained immediately, avoiding the challenging task of optimizing ansatz structure on a quantum computer. Furthermore, we introduce a strategy to indirectly identify critical excitations through spin-adapted constraints, reducing gradient computations by $60\%$. Numerical experiments on prototype molecular systems (H${_4}$, HF, H${_2}$O, BeH${_2}$ and NH$_3$) demonstrate that our approach achieves up to $46\%$ parameter decrease, $60\%$ circuit depth reduction and $678\times$ runtime speedup compared to the state-of-the-art ADAPT-VQE algorithm, enabling significantly more compact quantum circuits with enhanced near-term feasibility.

quant-ph↗

arXiv2025

Optimal Compilation Strategies for QFT Circuits in Neutral-Atom Quantum Computing

Neutral-atom quantum computing (NAQC) offers distinct advantages such as dynamic qubit reconfigurability, long coherence times, and high gate fidelities, making it a promising platform for scalable quantum computing. Despite these strengths, efficiently implementing quantum circuits like the Quantum Fourier Transform (QFT) remains a significant challenge due to atom movement overheads and connectivity constraints. This paper introduces optimal compilation strategies tailored to QFT circuits and NAQC systems, addressing these challenges for both linear and grid-like architectures. By minimizing atom movements, the proposed methods achieve theoretical lower bounds in atom movements while preserving high circuit fidelity. Comparative evaluations against state-of-the-art compilers demonstrate the superior performance of the proposed methods. These methods could serve as benchmarks for evaluating the performance of NAQC compilers.

quant-ph↗

arXiv2025

Digital quantum simulation of squeezed states via enhanced bosonic encoding in a superconducting quantum processor

We present a fully digital approach for simulating single-mode squeezed states on a superconducting quantum processor using an enhanced bosonic encoding strategy. By mapping up to 2^{n} photonic Fock states onto n qubits, our framework leverages Gray-code-based encodings to reduce gate overhead compared to conventional one-hot or binary mappings. We further optimize resource usage by restricting the simulation on Fock states with even number of photons only, effectively doubling the range of photon numbers that can be represented for a given number of qubits. To overcome noise and finite coherence in current hardware, we employ a variational quantum simulation protocol, which adapts shallow, parameterized circuits through iterative optimization. Implemented on the Zuchongzhi-2 superconducting platform, our method demonstrates squeezed-state dynamics across a parameter sweep from vacuum state preparation (r=0) to squeezing levels exceeding the Fock space truncation limit (r>1.63). Experimental results, corroborated by quantum state tomography and Wigner-function analysis, confirm high-fidelity state preparation and demonstrate the potential of Gray-code-inspired techniques for realizing continuous-variable physics on near-term, qubit-based quantum processors.

quant-ph↗

arXiv2025

RH: An Architecture for Redesigning Quantum Circuits on Quantum Hardware Devices

In this paper we present an architecture that enables the redesign of large-scale quantum circuits on quantum hardware based on the entangling quantum generative adversarial network (EQ-GAN). Specifically, by prepending a random quantum circuit module to the standard EQ-GAN framework, we extend its capability from quantum state learning to unitary transformation learning. The completeness of this architecture is theoretically proved. Moreover, an efficient local random circuit is proposed, which significantly enhances the practicality of our architecture. For concreteness, we apply this architecture to three crucial applications in circuit optimization, including the equivalence checking of (non-) parameterized circuits, as well as the variational reconstruction of quantum circuits. The feasibility of our approach is demonstrated by excellent results in both classical and noisy intermediate-scale quantum (NISQ) hardware implementations. We believe our work will facilitate the implementation and validation of the advantages of quantum algorithms.

quant-ph↗

arXiv2025

Image Computation for Quantum Transition Systems

With the rapid progress in quantum hardware and software, the need for verification of quantum systems becomes increasingly crucial. While model checking is a dominant and very successful technique for verifying classical systems, its application to quantum systems is still an underdeveloped research area. This paper advances the development of model checking quantum systems by providing efficient image computation algorithms for quantum transition systems, which play a fundamental role in model checking. In our approach, we represent quantum circuits as tensor networks and design algorithms by leveraging the properties of tensor networks and tensor decision diagrams. Our experiments demonstrate that our contraction partition-based algorithm can greatly improve the efficiency of image computation for quantum transition systems.

cs.DS↗

arXiv2025

DasAtom: A Divide-and-Shuttle Atom Approach to Quantum Circuit Transformation

Neutral atom (NA) quantum systems are emerging as a leading platform for quantum computation, offering superior or competitive qubit count and gate fidelity compared to superconducting circuits and ion traps. However, the unique features of NA devices, such as long-range interactions, long qubit coherence time, and the ability to physically move qubits, present distinct challenges for quantum circuit compilation. In this paper, we introduce DasAtom, a novel divide-and-shuttle atom approach designed to optimise quantum circuit transformation for NA devices by leveraging these capabilities. DasAtom partitions circuits into subcircuits, each associated with a qubit mapping that allows all gates within the subcircuit to be directly executed. The algorithm then shuttles atoms to transition seamlessly from one mapping to the next, enhancing both execution efficiency and overall fidelity. For a 30-qubit Quantum Fourier Transform (QFT), DasAtom achieves a 414x improvement in fidelity over the move-based algorithm Enola and a 10.6x improvement over the SWAP-based algorithm Tetris. Notably, this improvement is expected to increase exponentially with the number of qubits, positioning DasAtom as a highly promising solution for scaling quantum computation on NA platforms.

quant-ph↗

arXiv2023

isQ: Towards a Practical Software Stack for Quantum Programming

We introduce isQ, a new software stack for quantum programming in an imperative programming language, also named isQ. The aim of isQ is to make the programmers write quantum programs as conveniently as possible. In particular: 1) The isQ language and its compiler contain many features, including some not well supported by (most) other quantum programming platforms, e.g. classical control flow such as recursion; decomposition of selfdefined unitary gates; and oracle programming and its circuit realization. 2) To make it flexible, an isQ program can be compiled into several kinds of intermediate representation, including OpenQASM 3.0, QIR and QCIS (specially tailored for the superconducting quantum hardware at USTC). 3) Besides interfacing isQ with true superconducting hardware, a QIR simulator is also developed for demonstration and testing of isQ programs.

quant-ph↗

arXiv2019

Quantum Earth mover's distance, No-go Quantum Kantorovich-Rubinstein theorem, and Quantum Marginal Problem

The earth mover's distance is a measure of the distance between two probabilistic measures. It plays a fundamental role in mathematics and computer science. The Kantorovich-Rubinstein theorem provides a formula for the earth mover's distance on the space of regular probability Borel measures on a compact metric space. In this paper, we investigate the quantum earth mover's distance. We show a no-go Kantorovich-Rubinstein theorem in the quantum setting. More precisely, we show that the trace distance between two quantum states can not be determined by their earth mover's distance. The technique here is to track the bipartite quantum marginal problem. Then we provide inequality to describe the structure of quantum coupling, which can be regarded as quantum generalization of Kantorovich-Rubinstein theorem. After that, we generalize it to obtain into the tripartite version, and build a new class of necessary criteria for the tripartite marginal problem.

quant-ph↗

arXiv2018

A Logic for Recursive Quantum Programs

Most modern (classical) programming languages support recursion. Recursion has also been successfully applied to the design of several quantum algorithms and introduced in a couple of quantum programming languages. So, it can be expected that recursion will become one of the fundamental paradigms of quantum programming. Several program logics have been developed for verification of non-recursive quantum programs. However, there are as yet no general methods for reasoning about recursive procedures in quantum computing. We fill the gap in this paper by presenting a logic for recursive quantum programs. This logic is an extension of quantum Hoare logic for quantum While-programs. The (relative) completeness of the logic is proved, and its effectiveness is shown by a running example: fixed-point Grover's search.

cs.LO↗

arXiv2018

Quantum Coupling and Strassen Theorem

We introduce a quantum generalisation of the notion of coupling in probability theory. Several interesting examples and basic properties of quantum couplings are presented. In particular, we prove a quantum extension of Strassen theorem for probabilistic couplings, a fundamental theorem in probability theory that can be used to bound the probability of an event in a distribution by the probability of an event in another distribution coupled with the first.

quant-ph↗