arXiv subjects

Benchen Huang

Publications and source records attributed to Benchen Huang.

15 recordsLinked to original sources

arXiv2026

QMCtwin: Master-Equation Simulation of Syndrome Statistics Beyond Pauli Noise

As quantum error correction moves toward large-scale experimental implementations, decoder performance increasingly depends on how faithfully hardware noise is translated into syndrome statistics. Standard stabilizer workflows achieve scalability by replacing device dynamics with stochastic Pauli or detector-error models, but this compression can discard coherent phase information, nonunital drift, continuous-time effects of always-on couplings, and correlations generated by simultaneous Hamiltonian and dissipative evolution. Here we present QMCtwin, a sign-problem-suppressed quantum Monte Carlo framework for master-equation simulation of QEC circuits, and apply it to a full syndrome-extraction round of a distance-$7$ rotated surface code with $97$ physical qubits. The open-system model includes realistic superconducting-device noise mechanisms such as relaxation, pure dephasing, coherent gate miscalibration, residual $ZZ$ crosstalk, and drive-qubit detuning. By directly estimating syndrome observables from the QMC-generated stochastic density matrix estimator, we compare the master-equation dynamics with their Pauli-twirled Clifford simulation counterparts. QMCtwin predicts syndrome-extraction biases and correlations between syndromes and proxies of logical-string-parity that are absent or strongly suppressed in the stochastic Pauli description. We introduce information-theoretic diagnostics that further quantify how information concerning syndromes versus string-parity proxies differs between the realistic master-equation simulation and the corresponding Pauli-twirled model. These results show that QMC-based master-equation digital twins can expose noise features hidden by conventional Pauli/Clifford noise models and provide a practical path toward more accurate decoder-facing syndrome models.

quant-ph↗

arXiv2025

Elucidating the Inter-system Crossing of the Nitrogen-Vacancy Center up to Megabar Pressures

The integration of Nitrogen-Vacancy color centers into diamond anvil cells has opened the door to quantum sensing at megabar pressures. Despite a multitude of experimental demonstrations and applications ranging from quantum materials to geophysics, a detailed microscopic understanding of how stress affects the NV center remains lacking. In this work, using a combination of first principles calculations as well as high-pressure NV experiments, we develop a complete description of the NV's optical properties under general stress conditions. In particular, our ab initio calculations reveal the complex behavior of the NV's inter-system crossing rates under stresses that both preserve and break the defect's symmetry. Crucially, our proposed framework immediately resolves a number of open questions in the field, including: (i) the microscopic origin of the observed contrast-enhancement in (111)-oriented anvils, and (ii) the surprising observation of NV contrast-inversion in certain high-pressure regimes. Our work lays the foundation for optimizing the performance of NV high-pressure sensors by controlling the local stress environment, and more generally, suggests that symmetry-breaking stresses can be utilized as a novel tuning knob for generic solid-state spin defects.

quant-ph↗

arXiv2025

Quantum-Classical Auxiliary Field Quantum Monte Carlo with Matchgate Shadows on Trapped Ion Quantum Computers

We demonstrate an end-to-end workflow to model chemical reaction barriers with the quantum-classical auxiliary field quantum Monte Carlo (QC-AFQMC) algorithm with quantum tomography using matchgate shadows. The workflow operates within an accelerated quantum supercomputing environment with the IonQ Forte quantum computer and NVIDIA GPUs on Amazon Web Services. We present several algorithmic innovations and an efficient GPU-accelerated execution, which achieves a several orders of magnitude speedup over the state-of-the-art implementation of QC-AFQMC. We apply the algorithm to simulate the oxidative addition step of the nickel-catalyzed Suzuki-Miyaura reaction using 24 qubits of IonQ Forte with 16 qubits used to represent the trial state, plus 8 additional ancilla qubits for error mitigation, resulting in the largest QC-AFQMC with matchgate shadow experiments ever performed on quantum hardware. We achieve a $9\times$ speedup in collecting matchgate circuit measurements, and our distributed-parallel post-processing implementation attains a $656\times$ time-to-solution improvement over the prior state-of-the-art. Chemical reaction barriers for the model reaction evaluated with active-space QC-AFQMC are within the uncertainty interval of $\pm4$ kcal/mol from the reference CCSD(T) result when matchgates are sampled on the ideal simulator and within 10 kcal/mol from reference when measured on QPU. This work marks a step towards practical quantum chemistry simulations on quantum devices while identifying several opportunities for further development.

quant-ph↗

arXiv2025

First-Principles Framework for the Prediction of Intersystem Crossing Rates in Spin Defects: The Role of Electron Correlation

Optically active spin defects in solids are promising platforms for quantum technologies. Here, we present a first-principles framework to investigate intersystem crossing processes, which represent crucial steps in the optical spin-polarization cycle used to address spin defects. Considering the nitrogen-vacancy center in diamond as a case study, we demonstrate that our framework effectively captures electron correlation effects in the calculation of many-body electronic states and their spin-orbit coupling and electron-phonon interactions, while systematically addressing finite-size effects. We validate our predictions by carrying out measurements of fluorescence lifetimes, finding excellent agreement between theory and experiments. The framework presented here provides a versatile and robust tool for exploring the optical cycle of varied spin defects entirely from first principles.

cond-mat.mtrl-sci↗

arXiv2024

QuCLEAR: Clifford Extraction and Absorption for Quantum Circuit Optimization

Quantum computing carries significant potential for addressing practical problems. However, currently available quantum devices suffer from noisy quantum gates, which degrade the fidelity of executed quantum circuits. Therefore, quantum circuit optimization is crucial for obtaining useful results. In this paper, we present QuCLEAR, a compilation framework designed to optimize quantum circuits. QuCLEAR significantly reduces both the two-qubit gate count and the circuit depth through two novel optimization steps. First, we introduce the concept of Clifford Extraction, which extracts Clifford subcircuits to the end of the circuit while optimizing the gates. Second, since Clifford circuits are classically simulatable, we propose Clifford Absorption, which efficiently processes the extracted Clifford subcircuits classically. We demonstrate our framework on quantum simulation circuits, which have wide-ranging applications in quantum chemistry simulation, many-body physics, and combinatorial optimization problems. Near-term algorithms such as VQE and QAOA also fall within this category. Experimental results across various benchmarks show that QuCLEAR achieves up to a $77.7\%$ reduction in CNOT gate count and up to an $84.1\%$ reduction in entangling depth compared to state-of-the-art methods.

quant-ph↗

arXiv2024

Extrapolating Pauli Checks for Expectation Value Estimation on Noisy Quantum Devices

Pauli Check Sandwiching (PCS) is an error detection scheme that protects quantum circuits by inserting pairs of parity checks and discarding runs that signal errors. However, each additional check introduces noise and exponentially increases sampling costs. To address these limitations, we propose Pauli Check Extrapolation (PCE), an error mitigation technique that obtains measured expectation values from circuits with different numbers of checks and, analogous to ZNE, extrapolates to the ``maximum check'' limit -- the theoretical number of checks required for unit fidelity. We test linear and exponential ansatzes, deriving the exponential form from the Markovian error model. Benchmarking PCE against ZNE on random Clifford circuits with simulated depolarizing noise shows PCE outperforming ZNE for larger circuits. On real IBM hardware, PCE achieves an accuracy of up to 99.2% (56.2% improvement over baseline), compared to ZNE's 82% accuracy (29.1% improvement over baseline), for 4-qubit circuits. To demonstrate a practical use case, we then apply PCE towards mitigating errors in classical shadow measurements. Our results show that PCE can achieve fidelities greater than the state-of-the-art Robust Shadow estimation, while significantly reducing the number of required samples by eliminating the need for a calibration procedure. We validate these findings on both fully connected topologies and simulated IBM hardware backends.

quant-ph↗

arXiv2024

Evaluating a quantum-classical quantum Monte Carlo algorithm with Matchgate shadows

Solving the electronic structure problem of molecules and solids to high accuracy is a major challenge in quantum chemistry and condensed matter physics. The rapid emergence and development of quantum computers offer a promising route to systematically tackle this problem. Recent work by Huggins et al.[1] proposed a hybrid quantum-classical quantum Monte Carlo (QC-QMC) algorithm using Clifford shadows to determine the ground state of a Fermionic Hamiltonian. This approach displayed inherent noise resilience and the potential for improved accuracy compared to its purely classical counterpart. Nevertheless, the use of Clifford shadows introduces an exponentially scaling post-processing cost. In this work, we investigate an improved QC-QMC scheme utilizing the recently developed Matchgate shadows technique [2], which removes the aforementioned exponential bottleneck. We observe from experiments on quantum hardware that the use of Matchgate shadows in QC-QMC is inherently noise robust. We show that this noise resilience has a more subtle origin than in the case of Clifford shadows. Nevertheless, we find that classical post-processing, while asymptotically efficient, requires hours of runtime on thousands of classical CPUs for even the smallest chemical systems, presenting a major challenge to the scalability of the algorithm.

quant-ph↗

arXiv2024

Temperature dependent spin-phonon coupling of boron-vacancy centers in hexagonal boron nitride

The negatively charged boron-vacancy center ($\mathrm{V}_{\mathrm{B}}^-$) in hexagonal boron nitride (hBN) has recently emerged as a highly promising quantum sensor. Compared to the nitrogen-vacancy (NV) center in diamond, the change with temperature of the spin transition energy of $\mathrm{V}_{\mathrm{B}}^-$ is more than an order of magnitude larger, making it a potential nanoscale thermometer with superior sensitivity. However, the underlying mechanism of the observed large temperature dependence remains an open question. In this work, using isotopically purified $\mathrm{h}{}^{10}\mathrm{B}{}^{15}\mathrm{N}$, we systematically characterize the zero-field splitting, hyperfine interaction, and spin relaxation time of $\mathrm{V}_{\mathrm{B}}^-$ from 10 to 350$~$K. We carry out first-principle calculations of the $\mathrm{V}_{\mathrm{B}}^-$ spin-phonon interaction and show that a second-order effect from finite-temperature phonon excitations is responsible for the observed changes in experiments. By fitting our experimental results to a physically motivated model, we extract the dominant phonon mode which agrees well with our simulations. Finally, we investigate the dynamic nuclear spin polarization process at cryogenic temperatures. Our results provide key insights in $\mathrm{V}_{\mathrm{B}}^-$ centers and their utilization as nanoscale thermometers and phonon sensors.

quant-ph↗

arXiv2023

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

quant-ph↗

arXiv2023

Superstaq: Deep Optimization of Quantum Programs

We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster chemistry method, we find that deep optimization can improve program execution performance by at least 10x compared to prevailing state-of-the-art compilers. To highlight the versatility of our approach, we present results from several hardware platforms: superconducting qubits (AQT @ LBNL, IBM Quantum, Rigetti), trapped ions (QSCOUT), and neutral atoms (Infleqtion). Across all platforms, we demonstrate new levels of performance and new capabilities that are enabled by deeper integration between quantum programs and the device physics of hardware.

quant-ph↗

arXiv2023

Microwave-based quantum control and coherence protection of tin-vacancy spin qubits in a strain-tuned diamond membrane heterostructure

Robust spin-photon interfaces in solids are essential components in quantum networking and sensing technologies. Ideally, these interfaces combine a long-lived spin memory, coherent optical transitions, fast and high-fidelity spin manipulation, and straightforward device integration and scaling. The tin-vacancy center (SnV) in diamond is a promising spin-photon interface with desirable optical and spin properties at 1.7 K. However, the SnV spin lacks efficient microwave control and its spin coherence degrades with higher temperature. In this work, we introduce a new platform that overcomes these challenges - SnV centers in uniformly strained thin diamond membranes. The controlled generation of crystal strain introduces orbital mixing that allows microwave control of the spin state with 99.36(9) % gate fidelity and spin coherence protection beyond a millisecond. Moreover, the presence of crystal strain suppresses temperature dependent dephasing processes, leading to a considerable improvement of the coherence time up to 223(10) ${\mu}$s at 4 K, a widely accessible temperature in common cryogenic systems. Critically, the coherence of optical transitions is unaffected by the elevated temperature, exhibiting nearly lifetime-limited optical linewidths. Combined with the compatibility of diamond membranes with device integration, the demonstrated platform is an ideal spin-photon interface for future quantum technologies.

cond-mat.mes-hall↗

arXiv2023

Imaging the Meissner effect and flux trapping in a hydride superconductor at megabar pressures using a nanoscale quantum sensor

By directly altering microscopic interactions, pressure provides a powerful tuning knob for the exploration of condensed phases and geophysical phenomena. The megabar regime represents an exciting frontier, where recent discoveries include novel high-temperature superconductors, as well as structural and valence phase transitions. However, at such high pressures, many conventional measurement techniques fail. Here, we demonstrate the ability to perform local magnetometry inside of a diamond anvil cell with sub-micron spatial resolution at megabar pressures. Our approach utilizes a shallow layer of Nitrogen-Vacancy (NV) color centers implanted directly within the anvil; crucially, we choose a crystal cut compatible with the intrinsic symmetries of the NV center to enable functionality at megabar pressures. We apply our technique to characterize a recently discovered hydride superconductor, CeH$_9$. By performing simultaneous magnetometry and electrical transport measurements, we observe the dual signatures of superconductivity: local diamagnetism characteristic of the Meissner effect and a sharp drop of the resistance to near zero. By locally mapping the Meissner effect and flux trapping, we directly image the geometry of superconducting regions, revealing significant inhomogeneities at the micron scale. Our work brings quantum sensing to the megabar frontier and enables the closed loop optimization of superhydride materials synthesis.

cond-mat.supr-con↗

arXiv2022

Quantum simulations of Fermionic Hamiltonians with efficient encoding and ansatz schemes

We propose a computational protocol for quantum simulations of Fermionic Hamiltonians on a quantum computer, enabling calculations which were previously not feasible with conventional encoding and ansatses of variational quantum eigensolvers (VQE). We combine a qubit-efficient encoding scheme mapping Slater determinants onto qubits with a modified qubit-coupled cluster ansatz and noise-mitigation techniques. Our strategy leads to a substantial improvement in the scaling of circuit gate counts and to a decrease in the number of required variational parameters, thus increasing the resilience to noise. We present results for spin defects of interest for quantum technologies, going beyond minimum models for the negatively charged nitrogen vacancy center in diamond and the double vacancy in 4H silicon carbide (4H-SiC) and tackling a defect as complex as negatively charged silicon vacancy in 4H-SiC for the first time.

quant-ph↗

arXiv2022

Quantum Embedding Theories to Simulate Condensed Systems on Quantum Computers

Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties more complex than tractable at present on classical architectures. Here, we discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate scale quantum computers using embedding theories, and we give examples for a specific class of materials, i.e., spin defects in solids. These are promising systems to build future quantum technologies, e.g., computers, sensors and devices for quantum communications. Although quantum simulations on quantum architectures are in their infancy, promising results for realistic systems appear to be within reach.

quant-ph↗

arXiv2021

Simulating the electronic structure of spin defects on quantum computers

We present calculations of the ground and excited state energies of spin defects in solids carried out on a quantum computer, using a hybrid classical/quantum protocol. We focus on the negatively charged nitrogen vacancy center in diamond and on the double vacancy in 4H-SiC, which are of interest for the realization of quantum technologies. We employ a recently developed first-principle quantum embedding theory to describe point defects embedded in a periodic crystal, and to derive an effective Hamiltonian, which is then transformed to a qubit Hamiltonian by means of a parity transformation. We use the variational quantum eigensolver (VQE) and quantum subspace expansion methods to obtain the ground and excited states of spin qubits, respectively, and we propose a promising strategy for noise mitigation. We show that by combining zero-noise extrapolation techniques and constraints on electron occupation to overcome the unphysical state problem of the VQE algorithm, one can obtain reasonably accurate results on near-term-noisy architectures for ground and excited state properties of spin defects.

quant-ph↗