arXiv subjects

Chenxu Liu

Publications and source records attributed to Chenxu Liu.

At least 37 records · Page 2Linked to original sources

arXiv2026

Quantum Information Harvesting with the Parallel Quantum Flow Algorithm

The Quantum Flow (QFlow) algorithm provides a resource-efficient framework for describing correlated many-body systems on hybrid quantum-classical architectures. By enabling parallel utilization of quantum and classical resources, QFlow offers a scalable pathway toward simulations of realistic systems. In this Letter, we report a high-performance computing (HPC) implementation of the QFlow formalism based on a singles-and-doubles model. We demonstrate its performance for target spaces comprising 82 and 114 orbitals, where the flow includes all 6 active electrons in 6 active orbitals type active spaces. In the largest QFlow simulations, we optimize 1.17 million wave function parameters using the equivalent of 12 qubits. Despite the modest qubit requirements of the underlying active-space problems, the method recovers over $95\%$ of the total correlation energy obtained with the coupled cluster singles and doubles (CCSD) approach for systems dominated by dynamical correlation effects, which remain challenging for existing quantum algorithms. We further show that the QFlow formalism retains high accuracy in extended basis sets with diffuse functions, highlighting its potential for realistic large-scale quantum chemistry simulations.

quant-ph↗

arXiv2026

HETDEX Public Data Release 1: Source Catalog 2 and Data Cubes from ~90 sq deg of Integral-Field Optical Spectroscopy

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is a wide-field, integral-field spectroscopic survey designed to map the large-scale distribution of Lyman-alpha emitting galaxies (LAEs) at 1.88 < z < 3.52 and constrain dark energy at cosmic noon. Using the 10-m Hobby-Eberly Telescope and the Visible Integral-Field Replicable Unit (IFU) Spectrograph, HETDEX obtains >35,000 spectra per exposure over 3500-5500 Å at R~800 with ~1.8 arcsec image quality, enabling an untargeted census of emission-line galaxies across 540 sq deg. We present HETDEX Public Data Release 1 (PDR1), comprising 431,713 IFU observations covering 86.67 sq deg of noncontiguous sky in the Spring (13h, +51°) and Fall (1.5h, 0°) fields, along with legacy regions (COSMOS, GOODS-N, NEP, SA22). PDR1 includes the HETDEX Public Source Catalog 2 (HPSC2), an expanded and reprocessed version of Mentuch Cooper et al. (2023) incorporating four additional years of data, improved quality control, and new machine learning classifiers. HPSC2 contains 426,654 LAEs, 491,411 [O II] emitters, 19,457 low-z galaxies, 18,303 active galactic nuclei, and 150,608 stars, providing coordinates, redshifts or stellar velocities, and 1D spectra for each source. Because the data cubes use local sky subtraction optimized for faint emission-line detection, they are not suited for absolute surface-brightness measurements or very extended nearby galaxies. Appendix materials include the full detection catalog, the 1.6 million-candidate LAE sample, and raw detection databases. All products are publicly accessible through the HETDEX data portal (https://hetdex.org/data-results/), including access to a public JupyterLab. HPSC2 is also publicly available via Zenodo (DOI: 10.5281/zenodo.19581262).

astro-ph.GA↗

arXiv2026

Data-Driven Discovery of Unconventional Antiferromagnets

Unconventional antiferromagnets combine zero net magnetization with spin-split electronic bands, offering a distinct, important platform for spintronics. Their discovery, however, has so far depended largely on case-by-case studies and on a limited number of compounds with experimentally resolved magnetic structures. Here, we overcome these bottlenecks by resolving magnetic ground states across a broad materials database. We narrow down 37163 magnets from the Materials Project to 189 collinear antiferromagnets by combining physics-informed prescreening, high-throughput exchange calculations and Luttinger-Tisza analysis. Among these, symmetry analysis identifies 36 altermagnets and 11 Luttinger-compensated ferrimagnets (LCFs), including 22 altermagnets and 9 LCFs that have not been reported previously. The identified unconventional antiferromagnets can support nonrelativistic spin Hall effects and doping-tunable spin transport with switchable polarization and giant anisotropy. Our framework converts broad structural databases into a curated, symmetry-classified set of experimentally testable compensated spin-split magnets, establishing a scalable route for the efficient discovery of functional antiferromagnets.

cond-mat.mtrl-sci↗

arXiv2026

Transpiler-Architecture Co-Design to Curb Clifford Costs in Fault-Tolerant Quantum Computing

Quantum Error Correction (QEC) codes form the foundation of Fault-Tolerant Quantum Computing (FTQC) and predominantly use the Clifford+T gate set. Recently, Clifford operations have become the key performance bottleneck in implementing QEC. While state-of-the-art approaches like Pauli-Based Compilation (PBC) reduce Clifford overhead by transforming Clifford gates into Pauli measurements, they do so at the cost of gate-level parallelism, inflating circuit depth and execution times. To overcome these limitations, we introduce TACO, a Transpiler-Architecture Co-design framework that tackles the Clifford bottleneck through circuit and architectural optimization. TACO uses FTQC insights to guide hardware-aware Clifford gate elimination and circuit restructuring, and leverages the resulting optimized circuits to refine architectural design. TACO applies FTQC-specific transformations to aggressively reduce Clifford overhead from rotation synthesis and Toffoli decompositions, while preserving gate-level parallelism. The resulting architecture is optimized for the locality and data-movement patterns of these circuits, enabling high-throughput, resource-efficient execution. Our evaluation across diverse benchmarks shows that TACO achieves up to 21.9x (mean 4.4x) reduction in execution time compared to the state-of-the-art baseline.

quant-ph↗

arXiv2026

Benchmarking and Resource Analysis for Augmented-Lagrangian Quantum Hamiltonian Descent

Quantum Hamiltonian Descent (QHD) is a continuous optimization algorithm based on simulating a time-dependent quantum Hamiltonian whose potential energy encodes the objective function and whose kinetic energy promotes exploration through quantum interference and tunneling. While QHD is formulated for unconstrained optimization, many real-world optimization problems are constrained and highly nonconvex. In this paper, we benchmark AL-QHD, a hybrid framework that embeds QHD within the Augmented Lagrangian Method (ALM), thereby solving a sequence of unconstrained subproblems while using ALM to enforce constraints. We evaluate AL-QHD on standard nonconvex test functions and use iterative refinement to improve solution accuracy at fixed per-run qubit cost. We also perform a gate-based resource analysis on ACOPF-derived power system subproblems constructed from power-network data to estimate the quantum-computer scale required for practical applications. Resource estimates on Texas7k-derived ACOPF instances show steep hard-gate scaling, reaching $\sim 4.46 \times 10^7$ entangling gates in a NISQ-oriented model and $\sim 9.42 \times 10^8$ T gates in a fault-tolerant model at $\sim 5.3 \times 10^2$ active variables. These results suggest that AL-QHD is a useful framework for studying constrained nonconvex optimization with QHD, but that practical ACOPF-scale applications would likely require large-scale fault-tolerant quantum hardware.

quant-ph↗

arXiv2026

FTPrimitiveBench: A Benchmark Suite For Logical Computation Under Hardware-Motivated and Biased Noise Models

Fault-tolerant quantum computing requires understanding how error-correcting codes perform on diverse physical hardware. This is typically assessed via noisy stabilizer simulation of logical circuits at HPC scale, combined with a noise model that yields a logical error rate for the relevant code distances and depths. The uniform depolarizing model is the standard baseline, but its homogeneous assumptions fail to capture the heterogeneity, asymmetries, and correlations of real devices, where Pauli, measurement, and spatio-temporal errors are not weakly coupled. Yet these same structured features create opportunities for joint code-hardware co-design, motivating noise models that more faithfully reflect target hardware while remaining tractable to simulate. We introduce FTPrimitiveBench, a systematic benchmarking approach for studying how logical primitives interact with hardware-motivated noise. It supports both custom specifications and representative structured noise families: Pauli bias, measurement bias, and spatial or spatio-temporal non-uniformity -- together with generators for core surface-code Clifford primitives: logical memory, lattice surgery, transversal logical Hadamard, and the logical phase gate via lattice surgery. We find that structured noise affects these primitives in qualitatively distinct ways, with outcomes shaped by the interplay between noise model, primitive, and decoder choice. These results extend memory benchmarks to active logical computation, where the interaction between noise structure and primitive implementation matters. By standardizing the link between noise-model specification and primitive construction, FTPrimitiveBench enables reproducible comparative studies of QEC protocols and decoders, supporting hardware-aware co-design of fault-tolerant architectures. Code: https://github.com/ShuwenKan/FTPrimitiveBench.

quant-ph↗

arXiv2026

The Intermediate-Mass Black Hole Reverberation Mapping Project: Stable Optical Continuum Lags of an IMBH in the Dwarf Galaxy NGC 4395 Over Years

NGC 4395 is a nearby dwarf spiral galaxy hosting an active galactic nucleus (AGN) powered by an intermediate-mass black hole (IMBH, $M_{\rm BH} \sim 10^{4}$--$10^{5}\,M_\odot$). Recent optical continuum reverberation mapping studies have suggested potential lag variations between different epochs, offering important clues to the physical mechanisms governing variability in the vicinity of the central black hole. We present continuous intranight multi-band photometric monitoring of NGC 4395 based on five nights of observations, including three nights from the Faulkes Telescope North (two of which are archival) and two new nights from Mephisto. This represents the first systematic investigation of optical continuum lag stability in a galaxy hosting a robustly confirmed IMBH. By applying difference-imaging techniques to both the new observations and the reprocessed archival data, we detect statistically significant optical inter-band lags of $\sim 5$--15 minutes, which increase monotonically with increasing wavelength. No obvious $u$-band lag excess is observed, implying a negligible fractional contribution from diffuse continuum (DC) emission to the optical continuum, in agreement with our spectral decomposition results. The inter-band lags remain stable over multi-year baselines. We suggest that this long-term lag stability may be related to the minor DC contribution, a relatively steady disk-corona structure, and the unusually high X-ray-to-optical luminosity ratio characteristic of low-luminosity AGNs, which likely allows X-ray reprocessing to dominate over other potential variability mechanisms. Future facilities like Gemini/SCORPIO, with its simultaneous optical-to-near-infrared coverage, will be ideally suited to play an important role in advancing this field.

astro-ph.GA↗

arXiv2026

A superconducting quantum circuit single artificial atom maser

We demonstrate a circuit QED analog of an atomic micromaser that utilizes an artificial, multi level atom, pumped into a population-inverted state by a microwave tone, as the gain medium. Our demonstration is enabled by the flexibility of the circuit QED platform, which allowed us to precisely engineer the level-structure, coupling, and dissipation of the micromaser components. Our device shows rich physics and perhaps points to ways to use the recent developments in the domain of microwave quantum circuits to probe the domain of maser physics.

quant-ph↗

arXiv2026

Simultaneous Multi-band Optical Follow-up Observations of a Gamma-Ray Flare in BL Lacertae

On $2024$ October $5$, BL Lacertae ($2200+420$) experienced one of its brightest gamma-ray flares. We conducted simultaneous follow-up observations in the $u$, $v$, $g$, $r$, $i$, and $z$ bands from $2024$ October $17$ to November $21$ using the Mephisto telescope and its two $50$ cm twin auxiliary photometric telescopes of Yunnan University. Intraday variability (IDV) was detected in the $g$, $r$, $i$, and $z$ bands. The IDV duty cycle increased with observing frequency across these bands. The shortest variability time-scale, derived from auto-correlation analysis, constrains the upper limit of the black hole mass to be $M_{\bullet} \lesssim 10^{8.29} M_{\odot}$ assuming a Kerr black hole, and $M_{\bullet} \lesssim 10^{8.77} M_{\odot}$ assuming a Schwarzschild black hole. The emission region responsible for the observed variability has a size of $R \le 3.51 \times 10^{14}$ cm and is located at a distance of $R_H \le 2.83 \times 10^{15}$ cm from the central supermassive black hole. This distance is approximately three orders of magnitude smaller than the typical radius of the broad-line region, indicating that the emission region lies well within it. A general bluer-when-brighter (BWB) trend was detected on intraday time-scales, suggesting that shock-accelerated relativistic electrons enhance the high-energy particle population, leading to spectral hardening. A potential quasi-periodic oscillation (QPO) with a period of $\sim 100.77$ minutes was detected with $>99.99$ per cent confidence, consistent with predictions from the magnetic reconnection model. These observed optical intraday variabilities and colour variations of BL Lacertae can be well explained by the turbulent jet model.

astro-ph.HE↗

arXiv2026

Emission-line Variable Active Galactic Nuclei at Cosmic Noon from HETDEX

We present the first statistical census of emission-line variable active galactic nuclei (EVA) at cosmic noon by combining untargeted and deep HETDEX spectroscopy with multi-epoch spectra from SDSS, DESI, and LAMOST. Anchoring all candidates to a HETDEX spectroscopic epoch and requiring AGN classification in either the HETDEX or the external epoch(s), we identify a homogeneous sample of 100 EVA at z~1.5, including 98 newly identified. Emission-line variability is selected primarily through statistically significant line-flux changes, supplemented by extensive visual inspections using contemporaneous photometric light curves. The resulting incidence fraction is $f_{\rm EVA} \approx 0.9\%$. The rest-frame intervals between spectroscopic epochs span $\sim$1--10 yr, with brightening and dimming events exhibiting statistically indistinguishable characteristic timescales ($ΔT\sim2.2$ and $\sim2.6$ yr, respectively). A key result is the characterization of the Baldwin effect in the time domain: while many EVA follow the ensemble Baldwin effect (eBeff) between two epochs, a substantial fraction exhibit apparent anti-eBeff responses. Time-resolved spectroscopy of an individual source reveals that the intrinsic EW--luminosity relation is non-stationary, with the line-to-continuum responsivity systematically evolving from stronger to weaker across successive variability cycles; sparse two-epoch sampling of this evolving intrinsic Baldwin evolution (iBeff) naturally produces both eBeff-like and anti-eBeff behaviors. Finally, EVA show no strong preference for extreme Eddington ratios but exhibit a mild tendency toward lower $λ_{\rm Edd}$ values relative to matched control samples, driven primarily by sources observed in their dim states. Together, these results establish a coherent framework for interpreting emission-line variability in AGN at the peak epoch of cosmic black hole growth.

astro-ph.GA↗

arXiv2026

Lyα Nebulae in HETDEX: The Largest Statistical Census Bridging Lyα Halos and Blobs across Cosmic Noon

The Hobby-Eberly Dark Energy Experiment (HETDEX) is an untargeted ~540 deg^2 spectroscopic survey of Lyα emission in the 1.9 < z < 3.5 Universe. In surface brightness, this survey reaches 1σ Lyα sensitivities of approximately 2-5 x 10^-18 erg s^-1 cm^-2 arcsec^-2, allowing large samples of extended Lyα nebulae (LAN) to be studied. We selected a sample of 70,691 Lyα-emitting galaxies (LAEs) with an emission-line signal-to-noise ratio greater than 6 and modeled the Lyα emission as a point-source component with an optional exponential envelope. Half (~47.5%) of the LAE sample (33,612 objects) exhibits significant extended emission and is best fit by the two-component model. The fraction of resolved sources increases with Lyα flux and luminosity. Their isophotal areas range from 10-130 arcsec^2 (median 15 arcsec^2), with integrated Lyα fluxes from 6-2000 x 10^-17 erg s^-1 cm^-2 (median 20 x 10^-17 erg s^-1 cm^-2). Comparison between point-spread-function-weighted and isophotal flux measurements shows that the HETDEX pipeline underestimates the total Lyα flux by ~30% on average, reflecting the substantial halo contribution in extended sources. Approximately 420 LANs are found per deg^2 over 79.5 deg^2 of non-contiguous sky. About 12% of resolved sources show active galactic nuclei signatures and are bright in Lyα and continuum. The remaining 88% span a wide range of morphologies and often lack continuum counterparts. Exponential scale lengths show no strong correlation with Lyα flux or luminosity (median 11.6 +/- 1.9 kpc). Only 2.9% of the full S/N > 6 LAE population with ancillary data have radio counterparts, but 64% of those are found to be extended, with the radio fraction increasing with Lyα size.

astro-ph.GA↗

arXiv2026

An observational test of the plasma lensing effect using QSOs with and without MgII absorption

Radio wave propagation can be perturbed by compact ionized gas clumps through plasma lensing, which induces frequency dependent magnification and may distort the observed number counts of background sources. The quasar (QSO) number densities are a powerful probe for understanding the effects of intervening material. Absorption lines in QSO spectra reveal the presence of interstellar and intergalactic gas, which can change observed fluxes through dust extinction and plasma lensing. By combining observations from radio (VLASS), infrared (WISE), and optical bands (DESI), we assembled a sample of QSOs: ~4000 sources with MgII absorbers, and ~12, 000 non-absorbers. In the radio band, the MgII sample shows a moderate excess at the bright end of the flux distribution, which is broadly consistent with plasma lensing predications. In the optical, the MgII sample turns over at higher g-band fluxes and exhibits a steeper decline at the faint end than the non-MgII sample. Control samples were constructed by matching in redshift, infrared (W1), and optical (g) luminosities. In these comparisons, the radio excess becomes less prominent, suggesting that the apparent magnification may not be robust evidence for plasma lensing. Nevertheless, a weak contribution cannot be ruled out, especially given residual excess observed at the bright end relative to the non-MgII sample. Dust extinction along the line-of-sight remains a plausible alternative. Regardless of the dominant mechanism, the multi-wavelength differences offer a valuable probe of the physical state of the intervening medium.

astro-ph.CO↗

arXiv2026

QASMTrans: An End-to-End QASM Compilation Framework with Pulse Generation for Near-Term Quantum Devices

QASMTrans is a lightweight, high-performance, C++-based quantum compiler that bridges abstract quantum algorithms to device-level control and is designed for just-in-time (JIT) deployment on QPU testbeds with tightly integrated FPGAs or CPUs. We focus on achieving fast transpilation times on circuits of interest, we find more than 100x faster compilation than Qiskit in some circuits with similar circuit quality, enabling transpilation of large, high-depth circuits in seconds. Unlike existing tools, QASMTrans offers end-to-end device-pulse compilation and direct quantum control integration with QICK, closing the gap between logical circuits and hardware control enabling closed-loop optimization. QASMTrans supports latency-aware Application-tailored Gate Sets (AGS) at the pulse level, identifying high-impact gate sequences on the circuit critical path and synthesizing optimized pulse schedules using pre-defined robust circuit ansatz. Validated through integrated QuTiP pulse-level simulation, this is found to significantly reduce execution latency and can improve final-state fidelity by up to 12% in some tested circuits. QASMTrans further implements device-aware, noise-adaptive transpilation that uses device calibration data for circuit placement on high-quality qubits and can focus on the circuit critical path to reduce transpilation-pass time while maintaining comparable fidelity. Additionally, it introduces circuit space sharing via calibration-aware device partitioning, enabling concurrent execution of multiple circuits or shots on a single QPU. Moreover, QASMTrans is entirely self-contained and has no external library dependencies, making it easy for practical deployment. By combining fast compilation, pulse-level control, and noise-aware optimization, QASMTrans enables real-time adaptive algorithms such as ADAPT-VQE and ADAPT-QAOA.

quant-ph↗

arXiv2026

Calibration-Conditioned FiLM Decoders for Low-Latency Decoding of Quantum Error Correction Evaluated on IBM Repetition-Code Experiments

Real-time decoding of quantum error correction (QEC) is essential for enabling fault-tolerant quantum computation. A practical decoder must operate with high accuracy at low latency, while remaining robust to spatial and temporal variations in hardware noise. We introduce a hardware-conditioned neural decoder framework designed to exploit the natural separation of timescales in superconducting processors, where calibration drifts occur over hours while error correction requires microsecond-scale responses. By processing calibration data through a graph-based encoder and conditioning a lightweight convolutional backbone via feature-wise linear modulation (FiLM), we decouple the heavy processing of device statistics from the low-latency syndrome decoding. We evaluate this approach using the 1D repetition code as a testbed on IBM Fez, Kingston, and Pittsburgh processors, collecting over 2.7 million experimental shots spanning distances up to d = 11. We demonstrate that a single trained model generalizes to unseen qubit chains and new calibration data acquired days later without retraining. On these unseen experiments, the FiLM-conditioned decoder achieves up to an 11.1x reduction in logical error rate relative to modified minimum-weight perfect matching. We observe that by employing a network architecture that exploits the highly asynchronous nature of system calibration and decoding, hardware-conditioned neural decoding demonstrates promising, adaptive performance with negligible latency overhead relative to unconditioned baselines.

quant-ph↗

arXiv2026

Implementation of Tensor Network Simulation TN-Sim under NWQ-Sim

Large-scale tensor network simulations are crucial for developing robust complexity-theoretic bounds on classical quantum simulation, enabling circuit cutting approaches, and optimizing circuit compilation, all of which aid efficient quantum computation on limited quantum resources. Modern exascale high-performance computing platforms offer significant potential for advancing tensor network quantum circuit simulation capabilities. We implement TN-Sim, a tensor network simulator backend within the NWQ-Sim software package that utilizes the Tensor Algebra for Many-body Methods (TAMM) framework to support both distributed HPC-scale computations and local simulations with ITensor. To optimize the scale up in computation across multiple nodes we implement a task based parallelization scheme to demonstrate parallelized gate contraction for wide quantum circuits with many gates per layer. Through the integration of the TAMM framework with Matrix Product State (MPS) tensor network approaches, we deliver a simulation environment that can scale from local systems to HPC clusters. We demonstrate an MPS tensor network simulator running on the state-of-the-art Perlmutter (NVIDIA) supercomputer and discuss the potential portability of this software to HPC clusters such as Frontier (AMD) and Aurora (Intel). We also discuss future improvements including support for different tensor network topologies and enhanced computational efficiency.

quant-ph↗

arXiv2025

F2: Offline Reinforcement Learning for Hamiltonian Simulation via Free-Fermionic Subroutine Compilation

Compiling shallow and accurate quantum circuits for Hamiltonian simulation remains challenging due to hardware constraints and the combinatorial complexity of minimizing gate count and circuit depth. Existing optimization method pipelines rely on hand-engineered classical heuristics, which cannot learn input-dependent structure and therefore miss substantial opportunities for circuit reduction. We introduce F2, an offline reinforcement learning framework that exploits free-fermionic structure to efficiently compile Trotter-based Hamiltonian simulation circuits. F2 provides (i) a reinforcement-learning environment over classically simulatable free-fermionic subroutines, (ii) architectural and objective-level inductive biases that stabilize long-horizon value learning, and (iii) a reversible synthetic-trajectory generation mechanism that consistently yields abundant, guaranteed-successful offline data. Across benchmarks spanning lattice models, protein fragments, and crystalline materials (12-222 qubits), F2 reduces gate count by 47% and depth by 38% on average relative to strong baselines (Qiskit, Cirq/OpenFermion) while maintaining average errors of 10^(-7). These results show that aligning deep reinforcement learning with the algebraic structure of quantum dynamics enables substantial improvements in circuit synthesis, suggesting a promising direction for scalable, learning-based quantum compilation

quant-ph↗

arXiv2025

Exact and Efficient Stabilizer Simulation of Thermal-Relaxation Noise for Quantum Error Correction

Stabilizer-based simulation of quantum error-correcting codes typically relies on the Pauli-twirling approximation (PTA) to render non-Clifford noise classically tractable, but PTA can distort the behavior of physically relevant channels such as thermal relaxation. Physically accurate noise simulation is needed to train decoders and understand the noise suppression capabilities of quantum error correction codes. In this work, we develop an exact and stabilizer-compatible model of qubit thermal relaxation noise and show that the combined amplitude damping and dephasing channel admits a fully positive probability decomposition into Clifford operations and reset whenever $T_2 \leqslant T_1$. For $T_2 > T_1$, the resulting decomposition is negative, but allows a smaller sampling overhead versus independent channels. We further introduce an approximated error channel with reset that removes the negativity of the decomposition while achieving higher channel fidelity to the true thermal relaxation than PTA, and extend our construction to finite temperature relaxation. We apply the exact combined model to investigate large surface codes and bivariate bicycle codes on superconducting platforms with realistic thermal relaxation error. The differing logical performances across code states further indicate that noise-model-informed decoders will be essential for accurately capturing thermal-noise structure in future fault-tolerant architectures.

quant-ph↗

arXiv2025

A Quantum Network Processor Unit for Distributed Quantum Computing

As quantum computing progresses, the need for scalable solutions to address large-scale computational problems has become critical. Quantum supercomputers are the next upcoming frontier by enabling multiple quantum processors to collaborate effectively to solve large-scale computational problems. The emergence of quantum supercomputers necessitates an efficient interface to manage the quantum communication protocols between quantum processors. In this paper, we propose the Quantum Network Processing Unit (QNPU), which enables quantum applications to efficiently scale beyond the capacity of individual quantum processors, serving as a critical building block for future quantum supercomputers. The QNPU works alongside the Quantum Processing Unit (QPU) in our decoupled processing units architecture, where the QPU handles local quantum operations while the QNPU manages quantum communication between nodes. We design a comprehensive instruction set architecture (ISA) for the QNPU with high-level communication protocol abstractions, implemented via micro-operations that manage EPR resources, quantum operations, and classical communication. To facilitate programming, we introduce DistQASM, which extends OpenQASM with distributed quantum operations. We then propose a microarchitecture featuring both scalar and superscalar QNPU designs to enhance performance for communication-intensive quantum workloads. Finally, we evaluate the performance of our proposed QNPU design with distributed quantum workloads and demonstrate that the QNPU significantly improves the efficiency of communication between quantum nodes, paving the way for quantum supercomputing.

quant-ph↗