arXiv subjects

Jin Lin

Publications and source records attributed to Jin Lin.

At least 19 recordsLinked to original sources

arXiv2026

High fidelity control of superconducting qubits with optical transmitted signal

Superconducting circuits exhibit remarkable potential for constructing large-scale quantum simulation and computation systems, featuring numerous qubits, extended coherence time, and precise control. Nevertheless, the growing number of signal cables poses a challenge in dilution refrigerators due to space and heat load constraints. To overcome this issue, we experimentally implemented an optically-assisted transmission line as an alternative to coaxial cables. By modulating microwave signals on laser intensities at room temperature and regenerating the signals at a cryogenic plate within the dilution refrigerator, we demonstrated full control of superconducting qubits using photocurrent. We demonstrate and benchmark both single-qubit and two-qubit gates on frequency tunable transmon qubits, achieving fidelities of 99.915% $\pm$ 0.005% and 99.676% $\pm$ 0.041%, respectively, which have reached the requirement of the surface code.

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arXiv2026

Generalized Mermin Inequalities for Benchmarking Large-Scale GHZ States

Multipartite Bell tests provide a correlation-only route to benchmarking quantum processors, but their application at large scales is hindered by the rapid decay of many-body correlators under noise and exponentially many terms in conventional Bell expressions. Here we address these scalability obstacles by introducing a finite-setting generalized Mermin family of state-tailored Bell inequalities with analytic certification bounds, in which the measurement-setting number $m$ provides an additional certification dimension complementary to the system size $n$. We show that, for the powers-of-two setting choices considered here, increasing $m$ leaves the ideal normalized multipartite quantum value unchanged while lowering the relevant classical bounds, thereby strengthening the Bell-violation ratios and yielding an improved noise-robustness scaling compared to the standard Mermin inequality. We test this construction experimentally on a programmable superconducting processor by preparing Greenberger-Horne-Zeilinger (GHZ) states of up to 80 qubits. Using randomized sampling for direct Bell-operator estimation, we observe Bell ratios that grow exponentially with system size, certify a nonlocality depth of 14, and show that increasing $m$ strengthens both the Bell ratio and depth certification. All results are obtained solely from measured correlators and analytical bounds, without readout correction, tomography, or model-based mitigation. Generalized Mermin inequalities therefore provide a sharper Bell benchmark for noisy large-scale GHZ states.

quant-ph↗

arXiv2026

Surface code logical operations on a superconducting quantum processor

Fault-tolerant quantum computation requires logical operations that manipulate encoded information while preserving quantum error-correction protection. In planar surface-code architectures, code deformation and lattice surgery provide a local, measurement-based route to such operations. Here we experimentally realize key elements of patch-based surface-code logical processing on a 107-qubit superconducting quantum processor. We first implement a reusable primitive layer comprising merge and split, patch expansion and shrinkage, and deformations mediated by domain walls and twist defects. We then compose these primitives to realize logical state routing, the logical controlled-NOT gate, and the single-qubit Hadamard and phase gates, which together form a Clifford-generating set. All operations are implemented on distance-three rotated surface-code patches with multi-round syndrome extraction and neural-network decoding, without post-selection. Our results advance superconducting surface-code experiments from protected logical memory to active, patch-based fault-tolerant logical operations.

quant-ph↗

arXiv2025

Black-Start Power Capacity Sizing and Control Strategy for an Islanded DFIG Wind-to-Hydrogen System

This paper proposes a black-start method for an off-grid wind-to-hydrogen (W2H) system comprising a wind farm based on Doubly-Fed Induction Generators (DFIGs), proton exchange membrane fuel cells (PEMFCs) serving as the black-start power source, and a hydrogen production industry. The PEMFC is installed within the hydrogen industry to facilitate direct access to hydrogen fuel. Based on the microgrid topology and black-start scheme, this study innovatively sizes the rated capacity of the PEMFC through power flow analysis. The capacity must be sufficient to charge passive components such as transmission lines and transformers, provide rotor excitation, and supply wind turbine (WT) and electrolyzer (ELZ) auxiliaries during startup. The proposed system integrates wind-hydrogen coordinated control (WHCC) and hydrogen-storage coordinated control (HSCC). Under maximum power point tracking (MPPT) of the WTs, the ELZ follows power fluctuations to absorb wind output, ensuring stable voltage and frequency. Fixed-frequency control applied to either the DFIG or PEMFC converters enables DFIGs to retain conventional grid-following (GFL) operation, reducing converter development costs. For both control modes, this paper establishes the black-start sequence and formulates a comprehensive coordinated control strategy for the entire system. The entire control system is validated through simulations in MATLAB/Simulink. Results confirm that the calculated PEMFC capacity supports reliable black-start, while the black-start control strategy ensures smooth system self-startup. Furthermore, the coordinated control strategy maintains stable frequency and voltage under fluctuating wind power, demonstrating the practicality and robustness of the proposed approach.

eess.SY↗

arXiv2025

Algorithmic Quantum Simulations of Quantum Thermodynamics

Characterizing quantum phases-of-matter at finite-temperature is essential for understanding complex materials and large-scale thermodynamic phenomena. Here, we develop algorithmic protocols for simulating quantum thermodynamics on quantum hardware through quantum kernel function expansion (QKFE), producing the free energy as an analytic function of temperature with uniform convergence. These protocols are demonstrated by simulating transverse field Ising and XY models with superconducting qubits. In both analogue and digital implementations of the QKFE algorithms, we exhibit quantitative agreement of our quantum simulation experiments with the exact results. Our approach provides a general framework for computing thermodynamic potentials on programmable quantum devices, granting access to key thermodynamic properties such as entropy, heat capacity and criticality, with far-reaching implications for material design and drug development.

quant-ph↗

arXiv2025

Distributed-HISQ: A Distributed Quantum Control Architecture

The design of a scalable Quantum Control Architecture (QCA) faces two primary challenges. First, the continuous growth in qubit counts has rendered distributed QCA inevitable, yet the nondeterministic latencies inherent in feedback loops demand cycleaccurate synchronization across multiple controllers. Existing synchronization strategies -- whether lock-step or demand-driven -- introduce significant performance penalties. Second, existing quantum instruction set architectures are polarized, being either too abstract or too granular. This lack of a unifying design necessitates recurrent hardware customization for each new control requirement, which limits the system's reconfigurability and impedes the path toward a scalable and unified digital microarchitecture. Addressing these challenges, we propose Distributed-HISQ, featuring: (i) HISQ, A universal instruction set that redefines quantum control with a hardware-agnostic design. By decoupling from quantum operation semantics, HISQ provides a unified language for control sequences, enabling a single microarchitecture to support various control methods and enhancing system reconfigurability. (ii) BISP, a booking-based synchronization protocol that can potentially achieve zero-cycle synchronization overhead. The feasibility and adaptability of Distributed-HISQ are validated through its implementation on a commercial quantum control system targeting superconducting qubits. We performed a comprehensive evaluation using a customized quantum software stack. Our results show that BISP effectively synchronizes multiple control boards, leading to a 22.8% reduction in average program execution time and a $\sim$5$\times$ reduction in infidelity when compared to an existing lock-step synchronization scheme.

quant-ph↗

arXiv2025

Generation of 95-qubit genuine entanglement and verification of symmetry-protected topological phases

Symmetry-protected topological (SPT) phases are fundamental features of cluster states, serving as key resources for measurement-based quantum computation (MBQC). Generating large-scale cluster states and verifying their SPT phases are essential steps toward practical MBQC, which however still presents significant experimental challenges. In this work, we address these challenges by utilizing advanced superconducting hardware with optimized gate operations, enhanced readout fidelity, and error mitigation techniques. We successfully generate and verify 95-qubit one-dimensional and 72-qubit two-dimensional genuine entangled cluster states, achieving fidelities of $0.5603 \pm 0.0084$ and $0.5519 \pm 0.0054$, respectively. Leveraging these high-fidelity cluster states, we investigate SPT phases through quantum teleportation across all 95 qubits and demonstrate input-state-dependent robustness against symmetry-breaking perturbations, highlighting the practicality and intrinsic robustness of MBQC enabled by the SPT order. Our results represent a significant advancement in large-scale entanglement generation and topological phase simulation, laying the foundation for scalable and practical MBQC using superconducting quantum systems.

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arXiv2025

Free-Space Twin-Field Quantum Key Distribution

Twin-field quantum key distribution (TF-QKD) elevates the secure key rate from a linear to a square-root dependence on channel loss while preserving measurement-device-independent security. This protocol is uniquely positioned to enable global-scale quantum networks, even under extreme channel loss. While fiber-based TF-QKD implementations have advanced rapidly since its proposal, free-space realizations have remained elusive due to atmospheric turbulence-induced phase distortions. Here, we report the first experimental demonstration of free-space TF-QKD over 14.2 km urban atmospheric channels, surpassing the effective atmospheric thickness -- a critical threshold for satellite compatibility. We achieve a secret key rate exceeding the repeaterless capacity bound, a milestone for practical quantum communication. Our approach eliminates the need for an auxiliary channel to stabilize a closed interferometer, instead leveraging open-channel time and phase control of optical pulses. This work represents a pivotal advance toward satellite-based global quantum networks, combining high-speed key distribution with inherent resistance to real-world channel fluctuations.

quant-ph↗

arXiv2025

Achieving Stability and Optimality: Control Strategy for a Wind Turbine Supplying an Electrolyzer in the Islanded Storage-less Microgrid

Wind power generation supplying electrolyzers in islanded microgrids is an essential technical pathway for green hydrogen production, attracting growing attention in the transition towards net zero carbon emissions. Both academia and industry widely recognize that islanded AC microgrids normally rely on battery energy storage systems (BESSs) for grid-forming functions. However, the high cost of BESS significantly increases the levelized cost of hydrogen (LCOH), compromising economic feasibility. To address this challenge and reduce the LCOH, this paper focuses on a wind turbine (WT) supplying an electrolyzer in a storage-less microgrid and identifies a unique characteristic that challenges the conventional understanding of this microgrid: active power is coupled with microgrid voltage rather than frequency, the latter being entirely decoupled from active power balance. Based on this unique characteristic, this paper develops a new control strategy that maintains power balance, stabilizes the voltage and frequency, and maximizes hydrogen production. The effectiveness of the control strategy is validated through case studies conducted in Matlab/Simulink, especially its capability to maintain stability while maximizing hydrogen production under various conditions.

eess.SY↗

arXiv2024

Establishing a New Benchmark in Quantum Computational Advantage with 105-qubit Zuchongzhi 3.0 Processor

In the relentless pursuit of quantum computational advantage, we present a significant advancement with the development of Zuchongzhi 3.0. This superconducting quantum computer prototype, comprising 105 qubits, achieves high operational fidelities, with single-qubit gates, two-qubit gates, and readout fidelity at 99.90%, 99.62% and 99.18%, respectively. Our experiments with an 83-qubit, 32-cycle random circuit sampling on Zuchongzhi 3.0 highlight its superior performance, achieving one million samples in just a few hundred seconds. This task is estimated to be infeasible on the most powerful classical supercomputers, Frontier, which would require approximately $6.4\times 10^9$ years to replicate the task. This leap in processing power places the classical simulation cost six orders of magnitude beyond Google's SYC-67 and SYC-70 experiments [Nature 634, 328(2024)], firmly establishing a new benchmark in quantum computational advantage. Our work not only advances the frontiers of quantum computing but also lays the groundwork for a new era where quantum processors play an essential role in tackling sophisticated real-world challenges.

quant-ph↗

arXiv2024

Exploring the Optimal Size of Grid-forming Energy Storage in an Off-grid Renewable P2H System under Multi-timescale Energy Management

Utility-scale off-grid renewable power-to-hydrogen systems (OReP2HS), typically comprising photovoltaic plants, wind turbines, electrolyzers (ELs), and battery energy storage system (BESS), requires at least one component, generally the BESS, working with grid-forming ability to provide frequency and voltage references and regulate them through transient power support. However, existing designs of OReP2HS based on the energy management strategies (EMSs) with 5-min or hourly resolution fail to capture fast transients and may underestimate the BESS size required to ensure adequate grid-forming ability. This paper first proposes a framework of multi-timescale EMS covers from those for power system transient behaviors to second-level EL load adjustments and minute-level intra-day scheduling to coordinate renewable power, BESS, and ELs. Then, an iterative search procedure based on high-fidelity simulation is employed to determine the cost-effective BESS size that satisfies grid-forming, long-term energy balancing over 8760 hours, and emergency support requirements. Case studies based on a planned OReP2HS project in Inner Mongolia, China, show that the proposed EMS yields a base-case LCOH of 33.212 CNY/kg, with CAPEX of BESS accounting for 17.83% of total investment. The optimal BESS capacity represents 13.6% of the rated hourly renewable output and shows a yearly degradation of 4.87%. Sensitivity analysis reveals that reducing the electrolytic load adjustment time step from 90 to 5 seconds and increasing its ramping limit from 1% to 10% rated power per second, the BESS size decreases by 53.57%, and the LCOH decreases to 25.458 CNY/kg. Considering the cost of designing and manufacturing utility-scale ELs with fast load regulation capability, a load adjustment time step of 5 to 10 seconds and a ramping limit of 4-6% rated power per second are recommended.

math.OC↗

arXiv2024

In situ Qubit Frequency Tuning Circuit for Scalable Superconducting Quantum Computing: Scheme and Experiment

Frequency tunable qubit plays a significant role for scalable superconducting quantum processors. The state-of-the-art room-temperature electronics for tuning qubit frequency suffers from unscalable limit, such as heating problem, linear growth of control cables, etc. Here we propose a scalable scheme to tune the qubit frequency by using in situ superconducting circuit, which is based on radio frequency superconducting quantum interference device (rf-SQUID). We demonstrate both theoretically and experimentally that the qubit frequency could be modulated by inputting several single pulses into rf-SQUID. Compared with the traditional scheme, our scheme not only solves the heating problem, but also provides the potential to exponentially reduce the number of cables inside the dilute refrigerator and the room-temperature electronics resource for tuning qubit frequency, which is achieved by a time-division-multiplex (TDM) scheme combining rf-SQUID with switch arrays. With such TDM scheme, the number of cables could be reduced from the usual $\sim 3n$ to $\sim \log_2{(3n)} + 1$ for two-dimensional quantum processors comprising $n$ qubits and $\sim 2n$ couplers. Our work paves the way for large-scale control of superconducting quantum processor.

quant-ph↗

arXiv2023

Coordinated Active-Reactive Power Management of ReP2H Systems with Multiple Electrolyzers

Utility-scale renewable power-to-hydrogen (ReP2H) production typically uses thyristor rectifiers (TRs) to supply power to multiple electrolyzers (ELZs). They exhibit a nonlinear and non-decouplable relation between active and reactive power. The on-off scheduling and load allocation of multiple ELZs simultaneously impact energy conversion efficiency and AC-side active and reactive power flow. Improper scheduling may result in excessive reactive power demand, causing voltage violations and increased network losses, compromising safety and economy. To address these challenges, this paper first explores trade-offs between the efficiency and the reactive load of the electrolyzers. Subsequently, we propose a coordinated approach for scheduling the active and reactive power in the ReP2H system. A mixed-integer second-order cone programming (MISOCP) is established to jointly optimize active and reactive power by coordinating the ELZs, renewable energy sources, energy storage (ES), and var compensations. Case studies demonstrate that the proposed method reduces losses by 3.06% in an off-grid ReP2H system while increasing hydrogen production by 5.27% in average.

math.OC↗

arXiv2023

Multi-Stage Expansion Planning for Decarbonizing Thermal Generation Supported Renewable Power Systems Using Hydrogen and Ammonia Storage

Large-scale centralized development of wind and solar energy and peer-to-grid transmission of renewable energy source (RES) via high voltage direct current (HVDC) has been regarded as one of the most promising ways to achieve goals of peak carbon and carbon neutrality in China. Traditionally, large-scale thermal generation is needed to economically support the load demand of HVDC with a given profile, which in turn raises concerns about carbon emissions. To address the issues above, hydrogen energy storage system (HESS) and ammonia energy storage system (AESS) are introduced to gradually replace thermal generation, which is represented as a multi-stage expansion planning (MSEP) problem. Specifically, first, HESS and AESS are established in the MSEP model with carbon emission reduction constraints, and yearly data with hourly time resolution are utilized for each stage to well describe the intermittence of RES. Then, a combined Dantzig-Wolfe decomposition (DWD) and column generation (CG) solution approach is proposed to efficiently solve the large-scale MSEP model. Finally, a real-life system in China is studied. The results indicate that HESS and AESS have the potential to handle the intermittence of RES, as well as the monthly imbalance between RES and load demand. Especially under the goal of carbon neutrality, the contribution of HESS and AESS in reducing levelized cost of energy (LCOE) reaches 12.28% and 14.59%, respectively, which finally leads to a LCOE of 0.4324 RMB/kWh.

eess.SY↗

arXiv2023

Logical Magic State Preparation with Fidelity Beyond the Distillation Threshold on a Superconducting Quantum Processor

Fault-tolerant quantum computing based on surface code has emerged as an attractive candidate for practical large-scale quantum computers to achieve robust noise resistance. To achieve universality, magic states preparation is a commonly approach for introducing non-Clifford gates. Here, we present a hardware-efficient and scalable protocol for arbitrary logical state preparation for the rotated surface code, and further experimentally implement it on the \textit{Zuchongzhi} 2.1 superconducting quantum processor. An average of \hhl{$0.8983 \pm 0.0002$} logical fidelity at different logical states with distance-three is achieved, \hhl{taking into account both state preparation and measurement errors.} In particular, \hhl{the magic states $|A^{\pi/4}\rangle_L$, $|H\rangle_L$, and $|T\rangle_L$ are prepared non-destructively with logical fidelities of $0.8771 \pm 0.0009 $, $0.9090 \pm 0.0009 $, and $0.8890 \pm 0.0010$, respectively, which are higher than the state distillation protocol threshold, 0.859 (for H-type magic state) and 0.827 (for T -type magic state).} Our work provides a viable and efficient avenue for generating high-fidelity raw logical magic states, which is essential for realizing non-Clifford logical gates in the surface code.

quant-ph↗

arXiv2023

Optimal Sizing of Isolated Renewable Power Systems with Ammonia Synthesis: Model and Solution Approach

Isolated renewable power to ammonia (IRePtA) has been recognized as a promising way to decarbonize the chemical industry. Optimal sizing of the renewable power system is significant to improve the techno-economic of IRePtA since the investment of power sources exceeds 80\% of the total investment. However, multi-timescale electricity, hydrogen, and ammonia storages, minimum power supply for system safety, and the multi-year uncertainty of renewable generation lead to difficulties in planning. To address the issues above, an IGDT-MILFP model is proposed. First, the levelized cost of ammonia (LCOA) is directly formulated as the objective, rendering a mixed integer linear fractional programming (MILFP) problem. Information gap decision theory (IGDT) is utilized to handle the multi-year uncertainty of renewable generation. Second, a combined Charnes-Cooper (C&C) transformation and Branch-and-Bound (B&B) method is proposed to efficiently solve the large-scale IGDT-MILFP model, giving robust and opportunistic planning results. Then, Markov Chain Monte Carlo (MCMC) sampling-based posteriori analysis is leveraged to quantify the long-run performance. Finally, a real-life system in Inner Mongolia, China, is studied. The results indicate that the proposed methods could reduce the computational burden by orders of magnitude for solving a large-scale MILFP problem. Moreover, the proposed IGDT-MILFP model is necessary and accurate to obtain an optimal capacity allocation with the lowest expected LCOA (3610 RMB/t) in long-run simulations.

eess.SY↗

arXiv2023

Multi-timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets

Renewable power to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on the electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified framework. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC\&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of an RePtA VPP joining multiple markets over conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor's flexibility.

eess.SY↗

arXiv2023

Extended Load Flexibility of Utility-Scale P2H Plants: Optimal Production Scheduling Considering Dynamic Thermal and HTO Impurity Effects

In the conversion toward a clear and sustainable energy system, the flexibility of power-to-hydrogen (P2H) production enables the admittance of volatile renewable energies on a utility scale and provides the connected electrical power system with ancillary services. To extend the load flexibility and thus improve the profitability of green hydrogen production, this paper presents an optimal production scheduling approach for utility-scale P2H plants composed of multiple alkaline electrolyzers. Unlike existing works, this work discards the conservative constant steady-state constraints and first leverages the dynamic thermal and hydrogen-to-oxygen (HTO) impurity crossover processes of electrolyzers. Doing this optimizes their effects on the loading range and energy conversion efficiency, therefore improving the load flexibility of P2H production. The proposed multiphysics-aware scheduling model is formulated as mixed-integer linear programming (MILP). It coordinates the electrolyzers' operation state transitions and load allocation subject to comprehensive thermodynamic and mass transfer constraints. A decomposition-based solution method, SDM-GS-ALM, is followingly adopted to address the scalability issue for scheduling large-scale P2H plants composed of tens of electrolyzers. With an experiment-verified dynamic electrolyzer model, case studies up to 22 electrolyzers show that the proposed method remarkably improves the hydrogen output and profit of P2H production powered by either solar or wind energy compared to the existing scheduling approach.

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