arXiv subjects

Zhengwei Liu

Publications and source records attributed to Zhengwei Liu.

At least 37 records · Page 2Linked to original sources

arXiv2026

Quantum Derivative Pricing for SPDEs via BDSDE Representation

We study quantum speedups of derivative pricing for stochastic partial differential equation (SPDE) models through their backward doubly stochastic differential equation (BDSDE) representations. We develop conditional and nested quantum-accelerated multilevel Monte Carlo (QA-MLMC) methods for estimating the resulting conditional and nested expectations, improving the sampling complexity of classical Monte Carlo methods from $\widetilde{O}(ε^{-2})$ to $\widetilde{O}(ε^{-1})$ within additive error $ε$. We apply the framework to derivative pricing and sensitivity analysis, providing quantum-accelerated estimators for prices as well as first-order and second-order Greeks, likelihood-ratio and Malliavin-weight representations for Greeks, and Heston-type stochastic-volatility models. To enable efficient multilevel coupling, we construct a family of Forward--Backward Taylor discretization schemes for the stochastic integrals arising in the BDSDE representations and establish global strong-error order one convergence for pricing and Greek estimators. Numerical experiments showcase our schemes for first-order and second-order Greeks can reach the required orders for the full quadratic quantum speedups.

quant-ph↗

arXiv2026

Elemental Abundances from Off-center Carbon Burning in Accreting CO White Dwarfs: Implications for SN 2021yfj-like events

SN 2021yfj is a recently discovered interacting supernova that exhibits narrow emission lines of Si, S, and Ar, indicating the presence of circumstellar material (CSM) enriched with these elements surrounding the progenitor prior to the explosion. The origin of SN 2021yfj-like events remains uncertain. Recent work proposed that the SN 2021yfj-like events may stem from the double WD merger scenario, in which the merger of a Si-rich WD with a more massive ONe WD tidally strips about 0.3Msun of Si-rich material to form the CSM. If the merger subsequently triggers a supernova explosion, the interaction between the ejecta and the CSM can reproduce the observed light curve of SN 2021yfj. In this scenario, the progenitor system is a CO WD + He star binary, in which the CO WD accretes He-rich material from the He star. The accumulated material can trigger off-center carbon burning, potentially leading to the formation of a Si-rich WD. However, it remains unclear whether such off-center carbon burning can produce Si, S, and Ar in amounts comparable to those inferred for the CSM of SN 2021yfj. In this work, we simulate the evolution of a CO WD accreting He-rich material using time-dependent mass-accretion rates. Our results show that off-center carbon burning in the accreting CO WD can produce significant amounts of Si and S. We further found that the resulting elemental abundances are strongly affected by the initial carbon abundance of the WD. Based on our results, we suggest that the double WD merger scenario may provide a viable progenitor channel for SN 2021yfj-like events.

astro-ph.SR↗

arXiv2026

Unraveling the mysteries of supernovae with SKA+VLBI

Supernovae (SNe) drive cosmic chemical enrichment and shape galactic feedback, yet the link between progenitors and explosion outcomes remains poorly constrained because the earliest phases are rarely resolved. Radio emission traces synchrotron radiation where the fastest ejecta interact with the circumstellar medium (CSM), providing a uniquely penetrating probe of these phases. SKA-Mid phased into global VLBI will move from simple detections to routine interferometric imaging of nearby extragalactic SNe. Sub-$μ$Jy sensitivity and mas-scale SKA+VLBI imaging, complemented by visibility-domain model fitting for sub-beam radius measurements at 5-15 GHz will allow us to follow the expanding shocks of stripped-envelope SNe out to $\sim$25 Mpc, measure deceleration indices ($m$) and axial ratios to $\approx 5-10\%$, and directly test jet-assisted versus neutrino-driven explosion mechanisms. For interacting SNe (Type IIn/Ibn), SKA+VLBI will resolve clumpy and toroidal CSM on progenitor scales, constraining the timing and geometry of eruptive pre-explosion mass loss. Deep limits on Type Ia SNe will tightly restrict the allowed single-degenerate parameter space, while late-time imaging will search for nascent compact remnants and pulsar wind nebulae. In synergy with optical, X-ray and gravitational wave facilities, SKA+VLBI will turn nearby SNe into laboratories for time-resolved shock physics and progenitor mapping.

astro-ph.HE↗

arXiv2026

Characterizing Pauli Propagation via Operator Complexity

Pauli-propagation simulation represents observables in the Pauli basis and evolves their coefficients in the Heisenberg picture. Its efficiency depends on whether the evolving operator can be accurately compressed by retaining only a limited number of Pauli terms. In this work, we bridge operator complexity and the resource cost of Pauli-propagation methods by proving that the truncation error is governed by the Operator Stabilizer Rényi entropy (OSE) $\mathcal{S}^α(O)$. Our a priori bounds quantify how OSE controls the compressibility of the evolving operator and give explicit prescriptions for the Top-$K$ budget required to achieve a target accuracy. As an analytic test case, we prove that for the 1D Heisenberg model at $J_z=0$, the number of non-zero Pauli coefficients generated from a local operator grows at most quadratically with the number of Trotter steps. We then benchmark the Top-$K$ Pauli propagation on XXZ Heisenberg chains. The numerical results show high accuracy with a small truncation number $K$ in the free regime ($J_z=0$) and competitive performance against tensor-network methods, such as TDVP, in the interacting case ($J_z=0.5$). These results position OSE as a resource measure for Pauli-propagation methods.

quant-ph↗

arXiv2026

Complexity of tensor network simulation for noisy quantum circuits

We aim to rigorously address how local noise affects classical simulability of quantum dynamics benchmarked by tensor-network methods. Using operator entanglement entropy (OEE), we prove the following: (1) For single-qubit depolarizing noise on arbitrary circuits, tensor networks with $\mathrm{poly}(n)$ bond dimension suffice for fixed absolute Hilbert-Schmidt error after $\order{1}$ depth, while relative error demands $\order{\log n}$ depth; and this bound is optimal. (2) For single-qubit depolarizing noise on 1D local circuits, the existence of whole-trajectory error-bounded matrix product operator (MPO) of $\mathrm{poly}(n)$ bond dimension at all depths. (3) For general single-qubit noise in 1D brickwall circuits, random two-design gates with contraction coefficient $c<1/3$ yield an $\order{1}$ OEE plateau with probability $1-Te^{-Ω(n)}$, while arbitrary gates with $c<1/48$ give $\order{\log n}$ OEE in the worst case. (4) In higher dimensions, these bounds yield uniform-in-depth $\mathrm{poly}(n)$ average boundary-bond dimensions for projected entangled pair operators~(PEPO) across every cut -- under depolarizing noise at either absolute or relative accuracy, and under general noise with strong contraction at absolute accuracy. Our results establish a rigorous connection between certain noise models, circuit types, and their classical simulability.

cond-mat.str-el↗

arXiv2026

Asteroseismic rotation rates of hot subdwarf B stars hint at transient accretion from leftover common envelope matter

Asteroseismology enabled measuring the rotation rate in the deep stellar interiors of stars across several evolutionary phases, advancing the theory of angular momentum transport in single stars from the main sequence to the white dwarf phase. However, binary stellar evolution products have not yet been studied in the context of angular momentum transport constrained by asteroseismology. Hot subdwarf B (sdB) stars can pulsate in non-radial modes, enabling probing of their internal rotation. Those in binary systems form through mass transfer, thus they can be used to probe theories of internal rotation in post-mass transfer stars. Here, we interpret observed asteroseismic core and envelope rotation rates of sdB stars in unsynchronised binary systems that formed through the common-envelope channel, using stellar evolution models of rotating sdB stars with internal magnetic fields. We find that when sdB stars form with the angular momentum content of red giant cores prior to common-envelope ejection, their predicted core rotation rates are two to ten times lower than measured asteroseismic rotation rates, and their envelope rotation rates are lower by two to five orders of magnitude. This suggests that the angular momentum content of sdB stars increases during their formation. Since sdB stars in close binary systems may host circumstellar matter from a past common-envelope ejection, we show that if they accrete a small amount of matter, the combination of internal magnetic fields with angular momentum transfer through accretion spins up both the core and envelope to match their measured asteroseismic rotation rates.

astro-ph.SR↗

arXiv2026

SN2024abfl: A Low-Luminosity Type IIP Supernova at the Low-Mass End of Core Collapse

We present optical photometric and spectroscopic observations of the low-luminosity (LL) Type IIP supernova SN\,2024abfl. The distance to its host galaxy is highly uncertain, with independent estimates of $9.5^{+2.3}_{-2.4}$ Mpc and $15.0^{+8.9}_{-1.9}$ Mpc. Even adopting the larger distance, the inferred plateau luminosity is only $\sim 10^{41}\rm erg\,s^{-1}$, placing SN 2024abfl at the extreme faint end of SNe IIP population. Its light curve exhibits a long-lasting plateau of approximately 110 days. The spectra show exceptionally low expansion velocities, with the \FeII\, velocity of $\sim1200\,\rm km\,s^{-1}$ at 50 days after the explosion, significantly lower than the typical values of $\sim2000-5500\,\rm km\,s^{-1}$ observed in SNe IIP, placing SN\,2024abfl among the slowest-expanding LL SNe IIP. Bolometric modeling yields a synthesized $^{56}$Ni mass of $\sim0.002-0.004\,\rm M_\odot$, though this estimate remains subject to significant uncertainty owing to the poorly constrained distance. Considering the plateau color and duration, the magnitude drop from plateau to tail, and the progenitor luminosity, we favor a low-mass core-collapse origin for SN\,2024abfl.

astro-ph.SR↗

arXiv2026

An efficient method of posterior sampling for Poisson INGARCH models

We develop an efficient posterior sampling scheme for the Poisson INGARCH models. The proposed method is based on the approximation of the posterior density that exploits the Poisson limit of the negative binomial distribution. It allows us to rewrite the model in a form amenable to Pólya-Gamma data augmentation scheme, which yields simple conditionally Gaussian updates for the autoregressive coefficients. Sampling from the approximate posterior is straightforward via Gibbs-type iterations and remains numerically stable even under strong temporal dependence. Using this sampler as a proposal distribution will enhance the efficiency in Metropolis-Hastings algorithm and adaptive importance sampling. Numerical simulations indicate accurate posterior estimates, high effective sample sizes, and rapidly mixing chains.

stat.ME↗

arXiv2026

Diagnosing Quantum Circuits: Noise Robustness, Trainability, and Expressibility

Achieving practical quantum advantage on near-term noisy hardware is a central goal of quantum computation. However, without efficient pre-execution diagnostics, circuit design and scheme selection often rely on costly hardware-in-the-loop trial-and-error, inflating experimental overhead and impeding progress. To address this challenge, we introduce 2MC-OBPPP, a polynomial-time classical estimator that, for parameterized quantum circuits, jointly estimates trainability, expressibility, and robustness to noise. For example, our approach visually demonstrates that moderate amplitude damping alleviates barren plateaus (improving trainability) while decreasing expressibility. Moreover, the method produces a spatiotemporal ``noise-hotspot" map that pinpoints the most noise-sensitive qubits/gates, enabling targeted noise suppression. In a representative circuit, interventions on fewer than $2\%$ qubits reduce the error up to $90\%$. Together, before execution, our approach provides an efficient diagnostic benchmark for circuit/scheme design, and in deployment, guides for targeted interventions that substantially reduce the cost of error suppression.

quant-ph↗

arXiv2026

Phase Group Categories of Bimodule Quantum Channels

In this paper, we study the quantum channel on a von Neuamnn algebra $\mathcal{M}$ preserving a von Neumann subalgebra $\mathcal{N}$, namely an $\mathcal{N}$-$\mathcal{N}$-bimodule unital completely positive map. By introducing the relative irreducibility of a bimodule quantum channel, we show that its eigenvalues with modulus 1 form a finite cyclic group, called its phase group. Moreover, the corresponding eigenspaces are invertible $\mathcal{N}$-$\mathcal{N}$-bimodules, which encode a categorification of the phase group. When $\mathcal{N}\subset \mathcal{M}$ is a finite-index irreducible subfactor of type II$_1$, we prove that any bimodule quantum channel is relatively irreducible for the intermediate subfactor of its fixed points. In addition, we can reformulate and prove these results intrinsically in subfactor planar algebras without referring to the subfactor using the methods of quantum Fourier analysis.

math.OA↗

arXiv2026

A binary merger product as the direct progenitor of a Type II-P supernova

Type II-P supernovae (SNe II-P) are the most common class of core-collapse SNe in the local Universe and play critical roles in many aspects of astrophysics. Since decades ago theorists have predicted that SNe II-P may originate not only from single stars but also from interacting binaries. While ~20 SNII-P progenitors have been directly detected on pre-explosion images, observational evidence still remains scarce for this speculated binary progenitor channel. In this work, we report the discovery of a red supergiant progenitor for the Type II-P SN 2018gj. While the progenitor resembles those of other SNe II-P in terms of effective temperature and luminosity, it is located in a very old environment and SN 2018gj has an abnormally short plateau in the light curve. With state-of-the-art binary evolution simulations, we find these characteristics can only be explained if the progenitor of SN 2018gj is the merger product of a close binary system, which developed a different interior structure and evolved over a longer timescale compared with single-star evolution. This work provides the first compelling evidence for the long-sought binary progenitor channel toward SNe II-P, and our methodology serves as an innovative and pragmatic tool to motivate further investigations into this previously hidden population of SNe II-P from binaries.

astro-ph.HE↗

arXiv2026

Taming Barren Plateaus in Arbitrary Parameterized Quantum Circuits without Sacrificing Expressibility

Quantum algorithms based on parameterized quantum circuits (PQCs) have enabled a wide range of applications on near-term quantum devices. However, existing PQC architectures face several challenges, among which the ``barren plateaus" phenomenon is particularly prominent. In such cases, the loss function concentrates exponentially with increasing system size, thereby hindering effective parameter optimization. To address this challenge, we propose a general and hardware-efficient method for eliminating barren plateaus in an arbitrary PQC. Specifically, our approach achieves this by inserting a layer of easily implementable quantum channels into the original PQC, each channel requiring only one ancilla qubit and four additional gates, yielding a modified PQC (MPQC) that is provably at least as expressive as the original PQC and, under mild assumptions, is guaranteed to be free from barren plateaus. Furthermore, by appropriately adjusting the structure of MPQCs, we rigorously prove that any parameter in the original PQC can be made trainable. Importantly, the absence of barren plateaus in MPQCs is robust against realistic noise, making our approach directly applicable to near-term quantum hardware. Numerical simulations demonstrate that MPQC effectively eliminates barren plateaus in PQCs for preparing thermal states of systems with up to 100 qubits and 2400 layers. Furthermore, in end-to-end simulations, MPQC significantly outperforms PQC in finding the ground-state energy of a complex Hamiltonian.

quant-ph↗

arXiv2026

A Unified Frequency Principle for Quantum and Classical Machine Learning

Quantum neural networks constitute a key class of near-term quantum learning models, yet their training dynamics remain not fully understood. Here, we present a unified theoretical framework for the frequency principle (F-principle) that characterizes the training dynamics of both classical and quantum neural networks. Within this framework, we prove that quantum neural networks exhibit a spectral bias toward learning low-frequency components of target functions, mirroring the behavior observed in classical deep networks. We further analyze the impact of noise and show that, when single-qubit noise is applied after encoding-layer rotations and modeled as a Pauli channel aligned with the rotation axis, the Fourier component labeled by $\boldsymbolω$ is suppressed by a factor $(1-2γ)^{\|\boldsymbolω\|_1}$. This leads to exponential attenuation of high-frequency terms while preserving the learnability of low-frequency structure. In the same setting, we establish that the resulting noisy circuits admit efficient classical simulation up to average-case error. Numerical experiments corroborate our theoretical predictions: Quantum neural networks primarily learn low-frequency features during early optimization and maintain robustness against dephasing and depolarizing noise acting on the encoding layer. Our results provide a frequency-domain lens that unifies classical and quantum learning dynamics, clarifies the role of noise in shaping trainability, and guides the design of noise-resilient quantum neural networks.

quant-ph↗

arXiv2025

Triangular Prism Equations and Categorification

We introduce the triangular prism equations (TPE) for fusion categories, obtained by evaluating triangular prisms in terms of tetrahedra. Using an oriented graphical calculus, we show that the geometric symmetries of the regular tetrahedron are preserved. In the spherical case, we prove that the TPE are equivalent to the pentagon equations after a suitable change of basis. These equations provide new insight for managing complexity via localization. As a consequence, and using the Fuchs-Runkel-Schweigert theorem on the second Frobenius-Schur indicator, we obtain new categorification criteria. As an application, we solve all remaining open cases to complete the classification of unitary 1-Frobenius simple integral fusion categories up to rank 8 and up to Frobenius-Perron dimension 20000.

math.QA↗

arXiv2025

BELT: Block Encoding of Linear Transformation on Density Matrices

Linear maps that are not completely positive play a crucial role in the study of quantum information, yet their non-completely positive nature renders them challenging to realize physically. The core difficulty lies in the fact that when acting such a map $\mathcal{N}$ on a state $ρ$, $\mathcal{N}(ρ)$ may not correspond to a valid density matrix, making it difficult to prepare directly in a physical system. We introduce Block Encoding of Linear Transformation (BELT), a systematic protocol that simulates arbitrary linear maps by embedding the output $\mathcal{N}(ρ)$ into a block of a unitary operator. BELT enables the manipulation and extraction of information about $\mathcal{N}(ρ)$ through coherent quantum evolution. Notably, BELT accommodates maps that fall outside the scope of quantum singular value transformation, such as the transpose map. BELT finds applications in entanglement detection, quantum channel inversion, and simulating pseudo-differential operators, and demonstrates improved sample complexity compared to protocols based on Hermitian-preserving map exponentiation.

quant-ph↗

arXiv2025

Quon Classical Simulation: Unifying Cliffords, Matchgates and Entanglement

We propose a new framework of topological complexity to study the computational complexity of quantum circuits and tensor networks. Within this framework, we establish the Quon Classical Simulation (QCS) for hybrid Clifford-Matchgate circuits, which is efficient for both Clifford circuits and Matchgate circuits, therefore answering a long standing open question on unifying efficient classical simulations. This framework is built upon the Quon language, a 2+1D topological quantum field theory with space-time boundary and defects. Its exponential computation complexity is captured by Magic holes, a topological feature capturing the global long-range entanglement. Both Clifford circuits and Matchgate circuits are free of Magic holes. Efficient classical simulations of Cliffords and Matchgates are implemented by two parallel operations, generalized surgery theory of 3-manifolds and Yang-Baxter relations on the 2D boundary respectively, with additional binary arithmetic properties.

quant-ph↗

arXiv2025

Millisecond Pulsars in M2: New discoveries and a detailed timing analysis

Globular clusters (GCs) offer a unique environment for discovering and studying millisecond pulsars. In this paper, we present a multi-epoch search and detailed timing analysis of millisecond pulsars in the GC M2, using the Five-hundred-meter Aperture Spherical Telescope. We have discovered two new binary millisecond pulsars in M2, designated M2F and M2G, respectively. We provide measurements of the emission properties of all known pulsars in M2, including their polarization profiles, rotation measures, flux densities, scintillation characteristics, and so forth. In particular, we report the first rotation measure at the distance and direction of this cluster. Additionally, we report the first phase-coherent timing solutions for the M2 pulsars. From our Bayesian timing analysis, we have measured their spin and orbital parameters with high precision, including the advance of periastron for M2A and M2E indicating total system masses of 1.75(13) and 1.80(5) solar masses respectively. Using archival data from the Hubble Space Telescope, we have identified an optical counterpart of M2C, which is likely the white dwarf companion of the pulsar. By combining results from optical and radio observations, we have reconstructed the binary evolution track of this system and estimated the cooling age of the companion to be approximately 10\,Myr, making it the youngest white dwarf in any known GC binary pulsars. Furthermore, using the spin period derivatives of M2 pulsars, we have investigated the gravitational potential of the cluster and found that our results strongly support the latest central-stellar-velocity dispersion measurement in M2.

astro-ph.HE↗

arXiv2025

SEDONA-GesaRaT: an AI-Accelerated Radiative Transfer Program for 3-D Supernova Simulations

We present SEDONA-GesaRaT, a rapid code for supernova radiative transfer simulation developed based on the Monte-Carlo radiative transfer code SEDONA. We use a set of atomic physics neural networks (APNN), an artificial intelligence (AI) solver for the non-local thermodynamic equilibrium (NLTE) atomic physics level population calculation, which is trained and validated on 119 1-D type Ia supernova (SN Ia) radiative transfer simulation results showing great computation speed and accuracy. SEDONA-GesaRaT has been applied to the 3-D SN Ia explosion model N100 to perform a 3-D NLTE radiative transfer calculation. The spatially resolved linear polarization data cubes of the N100 model are successfully retrieved with a high signal-to-noise ratio using the integral-based technique (IBT). The overall computation cost of a 3-D NLTE spectropolarimetry simulation using SEDONA-GesaRaT is only $\sim$3000 core-hours, while the previous codes could only finish 1-D NLTE simulation, or 3-D local thermodynamic equilibrium (LTE) simulation, with similar computation resources. The excellent computing efficiency allows SEDONA-GesaRaT for future large-scale simulations that systematically study the internal structures of supernovae.

astro-ph.HE↗