Papers

High-fidelity universal two-qubit gates are critical for building fault-tolerant quantum computers. In scalable superconducting processors, shortened coherence times introduce more incoherent errors in gate operations. With a constrained error budget, there is reduced tolerance for coherent errors stemming from parameter deviations. In this work, we develop a closed-loop workflow to enhance the CZ gate calibration precision. Utilizing the echoed leakage error amplification (ELEA) and the repurposed context-aware fidelity estimation (CAFE) circuits, we suppress the population leakage to non-computational states, and, for the first time, demonstrate a CZ gate fidelity exceeding $99.9\%$ on an 84-qubit processor, with coherent error suppressed to $0.007\%$. Meanwhile, we obtain a median fidelity of $99.25\%$ among 72 CZ gates, demonstrating that the workflow can be generalized to the calibration of parallel CZ gates. Finally, we realize automated calibration and observe enhanced stability of the CZ gate throughout 9-hour comparative monitoring experiments. Our results, realized on a completely domestic platform, establish an efficient and automated route to quantum computation with superconducting quantum systems.

In the presence of very intense electromagnetic fields, the refractive index of vacuum is modified such that light velocity is less than $c$ and ultrarelativistic charged particles can be faster than light and can induce Cherenkov radiation. We present the comparison of the Cherenkov radiation produced by the Euler-Heisenberg theory for critical and supercritical magnetic fields. We also make the comparison between the Cherenkov and the synchrotron radiation produced by the charged particles.

We compute the matching of QCD quark-antiquark currents onto the set of the two-particle and three-particle two-jet operators in soft-collinear effective theory (SCET) at next-to-leading order (NLO) in the perturbative QCD series, including for the first time operators up to second order in the power expansion in the transverse momentum over energy. These results contribute to the ongoing programme of computing power corrections and summing power-suppressed logarithmically enhanced terms for event shapes in the two-jet region and deep-inelastic scattering in the Bjorken-$x\to 1$ limit. The three-particle operators depend on the partonic momentum fractions of two partons moving into the same direction. When one of the momentum fractions approaches zero, the coefficient functions are shown to satisfy endpoint factorization relations, which allow for a consistent cancellation of endpoint singularities among various terms in the complete factorization formula for power corrections.

In this work, we focus our analysis of Fractional-Dimension Gravity (FDG) on our home galaxy, the Milky Way (MW), by using the latest Gaia DR3 data as well as previous rotation curve (RC) data for this galaxy. FDG is an alternative gravitational model (previously known as Newtonian Fractional-Dimension Gravity - NFDG) which does not require the dark matter (DM) paradigm. The MW is studied here with the methods of FDG and its observed rotation curves are successfully reproduced by using a variable fractional dimension $D\left (R\right)$, following previous studies of several other galaxies which were analyzed with the same methodology. An alternative dimension function $D_{m}\left(R \right)$, based on the mass-dimension field equation, was also used and yielded less accurate fits to the experimental data. In addition, we also considered possible implications of the FDG metric, based on the presence of additional weights, on the structure of Special Relativity (SR) for spacetimes with fractional dimension. One notable, but very speculative outcome of this analysis is the possibility of an effective superluminal motion in galactic regions where the space dimension is $D<3$.

Many structure-property relations in amorphous materials are encoded not only in the mean structure, but in the prevalence, correlations and spatial organisation of minority environments across length scales. Yet atomistic models are commonly validated against bulk averages and a nominal number of structures, without establishing whether the finite population resolves the motifs invoked to explain material behaviour. We present an auditable framework, implemented in the Vitriflow software package, that connects calibrated melt-quench generation to explicit populations and quantity-specific uncertainty. This approach is demonstrated on three distinct benchmark systems. In a-SiO$_2$, strain is followed from intra-tetrahedral deformation through compressed Si–O–Si bridges to primitive 3-ring topology, showing that the lower angular tail is an organised medium-range population rather than undifferentiated variation about the network mean. In matched a-Si$_3$N$_4$ refinements, DFT redistributes density and first-neighbour length scale, sharpens the force-field first shell and repairs marginal contacts, while the two DFT descendants retain essentially the same first-neighbour topology. In a-Sm$_2$O$_3$, the amount and connectivity of partially ordered domains are quantified as they emerge from the disordered parent population, while the mixed coordination characteristic of the amorphous oxide remains robust. Mean structure, distribution tails, inherited topology and connected order are therefore distinct materials variables with distinct uncertainties. There is no universal ensemble size: the Vitriflow package records what was generated, which population was analysed and what that finite population establishes, providing a reproducible route from amorphous structure datasets to quantitatively supported structure-property hypotheses.

We present a laser system referenced to a room-temperature ultrastable cavity employing crystalline AlGaAs coatings. We demonstrate a fractional frequency instability of $4.2 \times 10^{-17}$, which is one of the lowest for room temperature systems and surpasses the limit imposed by Brownian noise if dielectric coatings were employed. For the first time in a room temperature system we identified the spontaneous fluctuations of the coating birefringence as a leading contribution to frequency instability. At optimized conditions we achieve an ultrastable cavity with an eigenfrequency that is highly immune to power fluctuations. As acceleration noise is the main noise contribution, we demonstrated that a feed-forward method can reduce the influence of accelerations on the cavity-stabilized laser frequency by a factor of four.

We derive the distribution of the first passage time $t_{fp}$ for the position $x$ of an underdamped harmonic oscillator to overcome a threshold $x_B$. As the $t_{fp}$ distribution depends on the oscillator quality factor $Q$ different approaches are used. At very large quality factor ($Q\gg 100$) and intermediate and long $t_{fp}$ the proof is based on an energy diffusion model, whereas at medium quality factor ($Q\sim 10$) the proof is based on the study of the eigenvalues of the Kramers linear differential operator with absorbing boundary conditions. For all $Q$ and short $t_{fp}$ we use a Hamiltonian approximation. The theoretical predictions are in excellent agreement with direct numerical simulations of underdamped oscillator dynamics. Finally we show that the mean of the trajectories ending at $t_{fp}$ presents a particular shape driven by a specific noise pattern.

The distribution of the first passage time $t_{fp}$ for the position $x$ to overcome a threshold $x_B$ is calculated in an underdamped harmonic oscillator. The proof combines several approaches based on the determination of the eigenvalues of the Kramers differential operator for the intermediate and long time regimes and on a Hamiltonian approximation for the short times. The theoretical predictions are in excellent agreement with the results of an experiment on an underdamped micro-cantilever. The knowledge of the $t_{fp}$ distribution opens the way to several applications, among them the precise estimation of the power of information engines, which we have also experimentally checked.

Under the assumption that dark matter is a coherently oscillating pseudoscalar field coupled to electromagnetism by the usual Chern-Simons term, we study the production of secondary photons from dark matter fluctuations coupled to a pre-existing magnetic field, taking into account the spectral distribution of the magnetic field. Specifically, we apply the formalism to the case of a large-scale magnetic field generated previously via a parametric resonance instability due to the same Chern-Simons coupling. However, our analysis is applicable to any spectrum of cosmological scale magnetic field fluctuations present at the time of recombination. We show that obtaining a sufficiently large flux of photons in the Lyman-Werner frequency range is consistent with constraints from CMB and X-ray observations.

Ultrafast experiments have uncovered inertial magnetization dynamics in ferromagnets, but their microscopic origin remains elusive. Using a non-Markovian quantum master equation we show that inertial dynamics arise from coherent interactions with optical phonons in the lattice. The fast optical frequency explains the nutation observed on picosecond timescales and accounts for variations between experiments through substrate-dependent phonon damping. By establishing magnon{phonon coupling as the microscopic basis of inertial magnetization, our results open new pathways for tailoring ultrafast spin dynamics and controlling magnetic states at terahertz frequencies.

This paper explores the selective suppression of Laguerre-Gaussian modes that are most vulnerable to atmospheric turbulence. Decomposing these modes into an orthogonal Zernike polynomial basis reveals significant differences in stability depending on the radial and azimuthal indices. We demonstrate that modes with a higher radial index exhibit minimal distortion of the transverse beam profile, providing a clear criterion for filtering out less resilient modes in turbulent media. Furthermore, we derive an analytical expression relating the required receiver aperture to the radial and azimuthal indices.

Several approaches to quantum gravity suggest the emergence of a fundamental minimal length at the Planck scale. In quantum mechanics, this feature is naturally encoded through deformations of the Heisenberg algebra, leading to the Generalized Uncertainty Principle (GUP). While the phenomenological implications of GUP have been extensively explored, a consistent characterization of coherent states in minimal-length quantum mechanics remains elusive. In this work, we present a systematic analysis of coherent states for the one-dimensional harmonic oscillator. We show that the canonical equivalence among their standard characterizations - as eigenstates of the annihilation operator, displaced vacuum states and minimum-uncertainty wave packets - is generically lost in the presence of a minimal length. We then investigate the dynamical and semiclassical consequences of this inequivalence by comparing the evolution of generalized coherent states with that of states saturating the GUP. In particular, we demonstrate that minimal-length effects induce nontrivial deformations of phase-space trajectories and give rise to an intrinsic squeezing mechanism with no counterpart in ordinary quantum mechanics. These results establish a unified framework for coherence in GUP-based quantum theories and identify distinctive semiclassical signatures of minimal-length physics, opening a new avenue for probing quantum-gravitational effects.

We investigate the electromagnetic interactions of dipole dark matter (DM) within an effective field theory framework, considering both standard and non-standard cosmological scenarios. We first study the prospects of DM production via both the freeze-out and freeze-in mechanisms within the standard radiation-domination. We then investigate how the viable DM parameter space is modified in a non-standard cosmological scenario due to entropy dilution during reheating. Existing constraints on the parameter space are discussed, and we highlight the discovery potential of future direct detection experiments to probe these scenarios. We further investigate the implications of neutron star heating for dipole DM. Due to the momentum-dependent nature of the interaction, dipole DM is captured efficiently by neutron stars, thereby making neutron star heating a sensitive probe of the dipole DM parameter space.

We present the first application of Fourier-space coherence analysis between the lensing-reconstructed projected mass distribution and the X-ray-emitting intracluster medium to a sample of 49 observed galaxy clusters. Using publicly available HST convergence maps from the Hubble Frontier Fields, CLASH, and RELICS programs, together with Chandra X-ray imaging, we measure the scale-dependent coherence between the dark-matter-dominated surface mass density and the hot baryonic gas. We use the coherence length, l_CR, defined as the scale above which the two maps remain at least 90% coherent, as a diagnostic of cluster dynamical state. Across the sample, dynamically relaxed systems exhibit high coherence over a broad range of scales and small l_CR/r500, while disturbed and merging systems show a loss of coherence on intermediate and small scales, yielding larger l_CR/r500. The inferred coherence lengths show sensitivity to lens-model assumptions and to the heterogeneous extent of the available convergence maps. Nevertheless, the coherence signal remains physically interpretable and provides a stringent measure of dark-matter-gas alignment. Applying a conservative threshold, l_CR/r500 < 0.2, we find that only 16% of the sample is relaxed; this fraction rises to 41% for a more permissive threshold of l_CR/r500 < 0.4. Relative to previous X-ray and morphological classifications, we find a 24% disagreement, with the coherence method identifying more systems as dynamically disturbed. These results demonstrate that lensing-X-ray coherence provides a complementary, scale-resolved probe of cluster dynamical state, while highlighting the need for homogeneous, wide-field weak-lensing maps to control reconstruction and field-of-view systematics.

We present a canonical quantization of Jackiw–Teitelboim gravity with finite Dirichlet boundary conditions, using the geodesic length between the two boundaries and its conjugate momentum as reduced phase space variables. The dynamics is recast as the scattering problem of a nonrelativistic particle in a repulsive Pöschl-Teller potential, naturally embedded within a hyperbolic reduction of the $\mathfrak{sl}(2,\mathbb{R})$ Casimir. We obtain exact wavefunctions of the universe and the disk partition function, interpreted as a transition matrix element between states of vanishing bare length. In the asymptotic limit, the theory reduces to Liouville quantum mechanics and reproduces the standard Schwarzian spectral density. At finite cutoff, however, the spectral measure exhibits genuinely nonperturbative corrections, absent in existing $T\bar T$ approaches. These contributions admit an interpretation in terms of pinched disk geometries and are responsible for a controlled violation of the Wheeler-DeWitt equation. We also obtain closed form expressions for thermal two-point functions in terms of Wilson functions and propose diagrammatic rules for time- and out-of-time-ordered four-point functions. We further address the issue of the branch cut singularity of the quasi-local energy and propose a UV completion of the model in which the Brown-York charge is extended beyond the black hole horizon. This extension naturally generalizes the scattering problem to configurations that foliate the black hole interior.

Polymeric stresses in viscoelastic flows arise from the deformation of polymer chains and are commonly computed using Eulerian constitutive models, in which the conformation tensor is evolved as a transported field over the entire domain. This approach is computationally intensive, prone to numerical instabilities, and not directly applicable to experimentally measured velocity fields. In this work, we develop a Lagrangian integration scheme that reconstructs the polymeric stress field from the deformation-gradient history along fluid element trajectories in a known, steady velocity field. This approach avoids solving the full Eulerian constitutive transport equation, which we develop for the nonlinear FENE-P model as well as the Oldroyd-B model as a reference case. After validation on unidirectional, canonical flows, the scheme is applied to non-trivial channel flows past circular obstacles using velocity fields quantified from both numerical simulations and microfluidic experiments. The reconstructed stress fields across both experiments and simulations are in agreement with traditional Eulerian reference solutions. Not only does this new Lagrangian scheme enable the quantification of stress fields directly from experimental velocity field data, but it also enables partial or whole-field mapping of stresses without solving fully-coupled viscoelastic constitutive equations.

Autonomous quantum error correction (QEC) stabilizes a logical manifold through dissipative events that emit into output channels, which are typically accessible to measurement. These signals are often discarded, and whether they contain useful information about logical failures remains generally unclear. Using quantum trajectories, we show that in dissipatively stabilized cat qubits bit flips are not silent logical errors: each flip is accompanied by a strong, time-localized photon burst from the dissipative buffer. Photon counting and homodyne monitoring can therefore herald the loss of logical information without interrupting the autonomous stabilization: bit flips in dissipative cat qubits are erasures. More broadly, our results show that the emitted signals of engineered reservoirs can act as built-in failure monitors for autonomous QEC, turning rare logical faults into erasures available to a decoder and reducing fault-tolerance overhead. To this end, we develop a general framework, based on past quantum states and number-resolved master equations, to quantify the detectability of such logical failures in autonomous QEC from the emitted signal.

We present new and improved calculations of Stark-broadened profiles for ionized helium, a key ingredient in the spectroscopic analysis of helium-atmosphere DO white dwarfs. Our approach builds upon the computer simulation framework previously developed for neutral helium, which fully accounts for the dynamical interactions of both ions and electrons with the emitting helium atom. We extend this theoretical formalism by relaxing the assumption of straight-line trajectories for the perturbing particles (electrons and ionized helium) and adopting the hyperbolic trajectories appropriate for their interaction with a charged emitter, thereby accounting for their dynamical influence on the line-broadening process. In this exploratory study, we focus on the He II 4686 line, the strongest absorption feature observed in the spectra of DO white dwarfs. We present the resulting Stark profiles and perform a detailed comparison with those available in the literature.

Gravitational Waves (GWs) represent the newest window of astronomy, furthering our understanding of compact objects like black holes and neutron stars in the Universe. The signal from two merging neutron stars is especially interesting since it brings the prospect of concordant electromagnetic and neutrino emissions. Such multi-messenger observations have a transformational impact on fundamental physics, nuclear matter, astrophysics, and gravity. It was first witnessed in 2017 with the detection of the binary neutron star (BNS) merger GW170817. However, searching for BNS signals in real-time in the LIGO-Virgo-KAGRA (LVK) GW detectors presents a computational challenge, as the data streaming out must be matched against $\sim$ million reference waveforms, which requires up to a thousand CPU cores. We present a different approach using neural networks to learn the presence of a signal in the data. Our algorithm, called Aframe, was deployed in the LVK's fourth observing run and was the first artificial intelligence (AI)-enabled search to detect multiple binary black holes (BBHs) live. In this work, we demonstrate that the approach extends to the lower-mass BNS regime, and is the first AI-enabled search that achieves sensitivity comparable to matched-filter pipelines at lower computational and latency costs. The challenge of the longer-duration BNS signals is addressed by heterodyning the data, following which the network architecture used for BBHs is sufficient to distinguish signal versus background. We also show that this analysis requires a single non-flagship GPU for online deployment. Furthermore, the design and adoption of inference-as-a-service tools allow rapid offline analysis using a distributed pool of GPU resources. Hence, aside from the use case of rapid online data analysis, we also establish the use of Aframe for efficient archival data analysis.

Fast Radio Bursts (FRBs) exhibit diverse spectro-temporal characteristics, which can probe vital propagation and source physics via Stokes polarimetry. We investigate whether the circular polarization (Stokes $V$) observed in some bursts is produced by Faraday conversion in the near-source wind of magnetars rather than being intrinsic to the source. Our calculation includes the increase in the effective mass of $e^\pm$ in the presence of the FRB wave. We find that Faraday conversion in the magnetar wind can explain the broad range of observed circular polarization in FRBs, including its frequent non-detection. Observationally derived upper limits on $V$ provide stringent constraints on the wind luminosity, magnetization, bulk Lorentz factor, and effective particle mass when ions are present. When available, frequency resolved Stokes spectra offer direct estimates of the wind environment. The Stokes parameters can undergo rapid oscillations with frequency in the high-wind/low-FRB-luminosity regime, resulting in Stokes-V depolarization. Bursts with significantly lower luminosities than typical FRBs can also develop measurable circular polarization, within the model framework. Additionally, separate zones are favored for significant circular polarization and rotation measure, when the model is applicable. The model constrains instantaneous wind parameters for several sources, including FRB 20201124A, FRB 20180301A, and SGR 1935+2154. This work represents the first instance in which properties of winds from compact objects associated with FRBs are inferred from polarization data.

We investigate properties of toric codes under realistic damping error channels, which include squeezing, thermal and non-Markovian effects. First, we map the decohered toric code under the generalized amplitude-damping (GAD) and the squeezed generalized amplitude-damping (SGAD) channels to the statistical-mechanical models using the double Hilbert-space formalism. Second, we map the action of the GAD and SGAD channels on the toric code to stochastic Pauli-type errors via Pauli twirling, yielding asymmetric depolarizing channels, and obtain the logical failure probabilities as a function of temperature and squeezing. In both cases, we relate the channel parameters of the GAD and SGAD channels to the spin-coupling constants of the statistical-mechanical model.

Quantum mechanical (QM) cluster models provide an effective framework for mechanistic studies of enzymatic reactions but remain computationally demanding. Neural network potentials (NNPs) offer a promising route to reduce this cost, but enzymes present challenges beyond small molecules, including large system sizes, implicit-solvent environments, substantial polarization, and charge transfer. Here, we present an integrated software framework for efficient NNP training for mechanistic studies of enzymes, demonstrated on QM cluster models of S-adenosyl-L-methionine-dependent methyltransferases (MTases). Our Enerzyme code introduces modular electrostatics-aware NNP architectures and combines automated QM-cluster construction with reactive dataset generation. The Enerzymette subpackage automates reaction pathway exploration at both NNP and DFT levels. We show that iterative flexible scans and nudged elastic band calculations impose stricter requirements on NNPs than conventional dataset metrics. Nevertheless, NNPs trained on fewer than 1,000 system-specific datapoints reproduce reaction energetics and transition-state structures for MTase clusters containing up to 545 atoms with near-chemical accuracy. Direct supervision of atomic charges and consistent dielectric screening substantially improve simulation stability and accuracy, while multitask-learned atomic charges capture charge transfer and polarization trends and provide chemically meaningful descriptors of reactivity. Finally, transferability across chemically diverse catechol O-methyltransferase substrates indicates that NNPs learn generalizable reactivity patterns as training data expand across multiple enzymes. Together, these results establish a foundation for accelerating enzyme mechanistic studies and guide future NNP development for biomolecular reactivity.

We present a low-cost laboratory for investigating the dynamics of a vertical mass-spring oscillator using real-time computer vision. The proposed system automatically tracks the motion of the oscillating mass with a smartphone camera, displays the displacement in real time, and exports the recorded data for further analysis. Representative experiments include damped oscillations, oscillation period measurements, spectral analysis, and phase-space reconstruction. The system also enables the investigation of nonlinear phenomena, including harmonic generation, frequency mixing, and energy exchange between coupled oscillation modes. Owing to its low cost, ease of construction, and automated data acquisition, the proposed apparatus extends the traditional mass-spring experiment to include topics in nonlinear dynamics that are rarely explored in undergraduate laboratories.

X-ray polarimetry has opened a new window into understanding the physics around magnetized compact objects. IXPE detection of linear polarization from such systems has prompted a new spurt of theoretical modeling. Our study is based on the dominant paradigm that the observed polarization arises from the scattering of photons around highly magnetized systems. Our main focus is the dependence of the polarization of the scattered light on properties of the incoming light, i.e., geometry and the polarization state, and the determination of the spectral shape of the polarized light for a wide range of magnetic field strengths. We also analyze the impact of vacuum birefringence on photon polarization. We show that, generically, we expect a higher linear degree of polarization from magnetars as compared to normal pulsars, which is in agreement with IXPE observations. Under some conditions, our study helps to understand the observed degree of polarization from normal pulsars and low-magnetized neutron stars and their spectral dependence. However, we cannot conclusively explain the spectral shape of the observed polarization for magnetars using only a single component emission from scattering in a strong magnetic field. This probably points to the system being more complex, e.g., multi-component, than our study allows for. Upcoming X-ray polarimeters with broader energy coverage could probe some of our other predictions, e.g., the spectral shape of the polarized light close to the resonance frequency.

Neural network surrogates for LHC scattering amplitudes require trustworthy uncertainty estimates, a challenging task given the non-Gaussian systematics. We target it using conformal prediction, a distribution-free post-processing to complement trained surrogates with calibrated uncertainties. We find that standard conformal predictions struggle to provide locally calibrated uncertainties. This leads us to introduce FALCON, a novel conformal prediction method that learns locally calibrated confidence intervals. Our simple examples illustrate the power of distribution-free uncertainty quantification for ultra-fast event generation at the LHC.

We propose that the Krylov basis gives a semiclassical representation of dynamics in general large-$N$, complex, many-body systems. As a probe of this semiclassicality, we study the growth of Wigner negativity – a measure of the complexity of classical simulation – under time evolution in Krylov space in several solvable models. We begin with 2d CFTs, initially in either the vacuum or the thermofield double state on a line excited by a primary operator. In both cases, Wigner negativity remains an $O(1)$ constant and does not grow at late times, indicating approximately classical dynamics in the Krylov basis. We then study random matrix theory with the maximally entangled state between two copies as the initial state. For general one-cut matrix models, we argue that Wigner negativity in the Krylov basis grows as $t^{1/2}$ at large $O(1)$ times but does not scale with the Hilbert space dimension, thus indicating semiclassical dynamics in Krylov space. Finally, in the double-scaled SYK model, we find an approximately classical phase (constant negativity) at early times and a semiclassical phase ($t^{1/2}$ growth) at late times. In all these examples, Wigner negativity either remains constant or grows slowly, demonstrating emergent semiclassicality of dynamics in Krylov space.

A direct proof based on commuting finite-dimensional flows and local polynomial invariants is given for a sharp upper bound on the amplitudes of finite-gap solutions of the modified Korteweg-de Vries (mKdV) equation. The maximal amplitude is the sum of the imaginary parts of the upper-half-plane square roots of the roots of the invariant polynomial of the finite-gap solution of the focusing mKdV equation. An analogous formula is established for a bounded class of solutions of the defocusing mKdV equation. The upper bounds are sharp and are explicitly attained by suitable initial data.

This paper presents a new hybrid MC/deterministic method for solving the one-group steady-state Boltzmann transport equation based on decomposition of solution in macro and micro components. The macro component captures the large-scale structure of the solution. It is represented by angular moments of the high-order transport solution. The $P_1$ approximation is applied to define the macro component. The first two angular moments are obtained as a solution of hybrid low-order moment equations with exact closures. The equation for the micro component is solved using a MC simulation. The hybrid two-level system of equations for macro and micro components is solved by fixed-point iteration scheme. Numerical results are presented to demonstrate variance reduction of stochastic numerical solution and improvement in computational efficiency.

We investigate analytically and numerically the tunneling-induced hybridization and coherent dynamics of Jackiw-Rebbi zero modes in a modified Su-Schrieffer-Heeger (SSH) model. Unlike the conventional SSH model, this modified system possess two bulk gap-closing points, namely the quadratic-type gap-closing point at momenta $k_0=0$ and the Dirac-type gap-closing points at $k_0=\pm\pi/4a$. Although the quadratic point does not support a topological domain wall due to the absence of mass inversion, the low-energy Dirac theory around $k_0=\pm\pi/4a$ predicts an effective mass that changes sign at two spatially separated domain walls under a kink profile, generating a pair of JR bound states with each states localized at one of those domain walls. We show that the finite spatial overlap between the JR zero modes lifts the zero-energy degeneracy through quantum tunneling, producing symmetric-antisymmetric hybridized states. Using an effective two-level description, we demonstrate that hybridized JR modes undergo coherent tunneling oscillations between the two domain walls, accompanied by periodic transfer of sublattice polarization between the (A,C) and (B,D) sectors. Our results establish a unified framework connecting JR zero modes, quantum tunneling, and coherent dynamics in modified SSH systems, offering a promising platform for controllable topological quantum-state transfer in engineered lattice structures.

Multi-gate teleportation (MGT) packages $n$ remote gates into a single ebit via a 1-ebit fan-out quantum circuit, saving $n{-}1$ entangled pairs relative to sequential gate teleportation. The cost is a correlated failure mode: a single network fault propagates through the fan-out tree, injecting a weight-$n$ Pauli error on the target register (weight $n{+}1$ including the control). We establish a design rule for fault-tolerant packet sizes in rotated surface codes of odd distance~$d$: a rigorous decoder-independent floor $\lfloor d/2 \rfloor$, extended to $\lceil d/2 \rceil$ by a local weight argument confirmed by simulation when the decoder is correlation-aware. Simulation with PyMatching shows the standard MWPM decoder built from the packet circuit's detector error model (DEM) naturally corrects the correlated error: at $n=\lfloor d/2\rfloor$ the packet matches or surpasses the per-link sequential LER for moderate-to-high $\gamma$, with the crossover $\gamma^\star$ decreasing as $d$ grows (from $\gamma^\star{\approx}17$ at $d{=}5$ to $\gamma^\star{<}1$ at $d{=}9$, extrapolated), whilst reducing the entanglement cost from $n$ ebits to~$1$. Packetisation wins when the network is the bottleneck ($\gamma \gg 1$); at $\gamma \approx 1$ the packet is marginally worse ($\leq1.13\times$ at $d\in\{5,7\}$, reversing by $d{=}9$) as the $n{-}1$ extra local fan-out gates offset the network savings. No custom decoding algorithm is required: the standard MWPM decoder, built from the packet circuit's DEM, already encodes the correlation.