Papers

Counterdiabatic (CD) driving is a powerful technique for accelerating adiabatic quantum computing. However, it becomes self-limiting in complex optimizations like the Sherrington-Kirkpatrick model: long evolution times $T$ needed to traverse crossings force the CD strength to scale as $1/T$, causing it to vanish before convergence and wasting the quantum resources invested in its implementation. We break this trade-off with a Hybrid adaptive variational quantum dynamics simulation (HAVQDS). HAVQDS combines adaptive real-time evolution for circuit compression with imaginary-time steps that suppress excitations at no extra gate cost. For the SK model (6–14 qubits), HAVQDS achieves higher approximation ratios than adiabatic or CD approaches, while reducing CNOT counts by 1–2 orders of magnitude, enabling high-fidelity quantum optimization.

We analyze finite-sample statistics of Bohmian trajectories for single spinless and spin-1/2 particles. Equivariance ensures agreement with $|\psi|^2$ in the quantum equilibrium limit, yet experiments and simulations necessarily use finite ensembles. We show that in regular flows (e.g., wavepackets or low-mode superpositions of eigenstates of harmonic oscillators) sample means and/or variances over modest $N$ are consistent with Born-rule moments. In contrast, degenerate superpositions of 3D oscillators with nodal barriers and chaotic Bohmian dynamics exhibit sensitive dependence on initial conditions and complex flow partitioning, which can yield noticeable finite-sample deviations in the mean and variance. For the spin-1/2 particle, both convective and Pauli currents conserve $|\psi|^2$, but they are associated with different velocity fields and thus might yield different finite-sample trajectory statistics. These findings calibrate the interpretation of trajectory-based uncertainty and provide practical guidance for numerical Bohmian simulations of spin and transport, without challenging the equivalence to orthodox quantum mechanics in the quantum equilibrium ensemble.

Single-photon emitters are fundamental building blocks for quantum information processing, communication and sensing. However, unwanted interactions with bulk phonons in their host environment strongly limit their coherence and controllability. We report single color centers in nanodiamonds that are strongly and comprehensively decoupled from the bulk phononic environment. The color centers feature record-narrow linewidths down to 0.3 nm at room temperature and stable, bright emission, exceeding 10 Mcps in saturation. Notably, the bulk phonon sideband is almost entirely suppressed, revealing the presence of a single localized vibrational mode outside the diamond phonon band. Our observations and simulations point towards a unique mechanism for phonon decoupling in common wide-gap materials, based on a strongly radiative orbital transition coupled to a localized vibrational mode. The new color center enables qualitatively higher performance for applications in quantum networks and nanoscale sensing, and the exploration of new physical resources associated with vibrational states.

Optical neural networks (ONNs) have been developed to enhance processing speed and energy efficiency in machine learning by leveraging optical devices for nonlinear activation and establishing connections among neurons. In this work, we propose a quantum optical neural network (QONN) that utilizes atom-cavity neurons with controllable photon absorption and emission. These quantum neurons are designed to replace the electronic components in ONNs, which typically introduce delays and substantial energy consumption during nonlinear activation. To evaluate the performance of the QONN, we apply it to the MNIST digit classification task, considering the effects of photon absorption duration, random atom-cavity detuning, and stochastic photon loss. Additionally, we introduce a convolutional QONN to facilitate a real-world satellite image classification (SAT-6) task. Due to its compact hardware and low power consumption, the QONN offers a promising solution for real-time satellite sensing, reducing communication bandwidth with ground stations and thereby enhancing data security.

We present an algorithm to solve the Simultaneous Unitary Similarity(S.U.S) problem which is to check if there exists a Similarity transformation determined by a Unitary $U$ s.t $UA_lU^*=B_l$, $l \in \{1,...,p\}$, where $A_l$ and $B_l$ are $nxn$ complex matrices. We observe that the problem is simplest when $U$ is diagonal, where we see that the `paths' in the graph defined by non-zero elements of $A_l$ and $B_l$ determine the solution. Inspired by this we generalize this to the case when $U$ is block-diagonal to identify a form refered to as the `Solution-form' using `paths' determined by non-zero sub-matrices of $A_l,B_l$ which are non-zero multiples of Unitary. When not in Solution form we find an equivalent problem to solve by diagonalizing a Hermitian or a Normal matrix related to the sub-matrices. The problem is solved in a maximum of $n$ steps. The same idea can be extended to solve the Simultaneous Unitary Equivalence (S$.$U$.$Eq) problem where we solve for $U,V$ in $UA_lV^*=B_l$, $A_l,B_l$ being $mxn$ Complex rectangular matrices. Here we work with the 'paths' in the related bi-graph to define the Solution-form. The algorithms have a complexity of $O(pn^4)$. This work finds application in Quantum Evolution, Quantum gate design and Simulation. The salient features of each step of the algorithm can be retained as Canonical features to classify a given collection of complex matrices up to Unitary Similarity.

One of the foundational challenges in both Quantum Field Theory and the philosophy of physics lies in the traditional binary classification of entities as either real or unreal. The classical view posits that material entities are real, while mental constructs or theoretical entities are unreal. However, quantum phenomena such as virtual particles challenge this simplistic dichotomy. These unobservable entities, by influencing measurable phenomena, raise profound questions about the nature and modes of existence. To address this, we propose a four-level ontological hierarchy that spans from the quantum vacuum and the virtual level to the quantum level and phenomenal reality, providing a coherent continuum from potentiality to actualization. This framework not only clarifies the interpretation of quantum theory but also offers a unified perspective linking the unobservable with the observable. In QFT, virtual particles play a crucial role in mediating forces and in correcting the measurable properties of real particles. They arise within the mathematical structure of Feynman diagrams and, despite being unobservable, produce real, measurable effects such as the Lamb shift and the Casimir effect. Philosophically, this raises deep ontological questions: if unobservable entities affect measurable phenomena, can they truly be dismissed as unreal? Conversely, if they are real, what mode of existence do they possess? The traditional dichotomy of real versus unreal is thus insufficient for interpreting the ontological implications of quantum processes. To overcome these limitations, we propose a four-level ontological hierarchy.

Anomaly detection has a significant impact on applications such as video surveillance, medical diagnostics, and industrial monitoring, where anomalies frequently depend on context and anomaly-labeled data are limited. Quantum federated learning (QFL) overcomes these concerns by distributing model training among several quantum clients, consequently eliminating the requirement for centralized quantum storage and processing. However, in real-life quantum networks, clients frequently differ in terms of hardware capabilities, circuit designs, noise levels, and how classical data is encoded or preprocessed into quantum states. These differences create inherent heterogeneity across clients - not just in their data distributions, but also in their quantum processing behaviors. As a result, training a single global model becomes ineffective, especially when clients handle imbalanced or non-identically distributed (non-IID) data. To address this, we propose a new framework called personalized quantum federated learning (PQFL) for anomaly detection. PQFL enhances local model training at quantum clients using parameterized quantum circuits and classical optimizers, while introducing a quantum-centric personalization strategy that adapts each client's model to its own hardware characteristics and data representation. Extensive experiments show that PQFL significantly improves anomaly detection accuracy under diverse and realistic conditions. Compared to state-of-the-art methods, PQFL reduces false errors by up to 23%, and achieves gains of 24.2% in AUROC and 20.5% in AUPR, highlighting its effectiveness and scalability in practical quantum federated settings.

Quantum circuits are considered more powerful than classical circuits and require exponential resources to simulate classically. Clifford circuits are a special class of quantum circuits that can be simulated in polynomial time but still show important quantum effects such as entanglement. In this work, we present an algorithm that simulates Clifford circuits by performing Gaussian elimination on a modified adjacency matrix derived from the circuit structure. Our work builds on a ZX-calculus tensor network representation of Clifford circuits that reduces to quantum graph states. We give a concise formula of amplitudes of graph states based on the LDL decomposition of matrices over GF(2), and use it to get efficient algorithms for strong and weak simulation of Clifford circuits using a tree-decomposition-based sparse LDL algorithm. The complexity of our algorithm matches the state of the art for weak graph state simulation and improves the state of the art for strong graph state simulation by taking advantage of Strassen-like fast matrix multiplication. Our algorithm is also efficient when computing many amplitudes or samples of a Clifford circuit. Further, our amplitudes formula provides a new characterization of locally Clifford equivalent graph states as well as an efficient protocol to learn graph states with low-rank adjacency matrices.

Quantum computing relies on quantum error correction for high-fidelity logical operations, but scaling to achieve near-term quantum utility is highly resource-intensive. High-rate quantum LDPC codes can reduce error correction overhead, yet realizing high-rate fault-tolerant computation with these codes remains a central challenge. Apart of the lattice surgery approach, standard schemes for realizing logical gates have so far been restricted to performing global operations on all logical qubits at the same time. Another approach relies on low-rate code switching methods. In this work, we introduce a gate-based protocol for addressable single- and multi-qubit Clifford operations on individual logical qubits encoded within one or more quantum LDPC codes. Our scheme leverages logical transversal operations via an auxiliary Bacon-Shor code to perform logical operations with constant time overhead enabled by teleportation. We demonstrate the implementation of an overcomplete logical Clifford gate set and perform numerical simulations to evaluate the error-correction performance of our protocol. Finally, we observe that our scheme can be integrated with magic state cultivation protocols to achieve universal, gate-based, and fully addressable quantum computation.

We introduce a family of bosonic quantum error-correcting codes built as a rotation-symmetric superposition of squeezed vacuum states, which promise protection against both loss and dephasing noise channels. The robustness of these "squeezed-vacuum codes" arises from being arranged at evenly spaced angles in phase-space, and simultaneously in evenly spaced photon-number support $n \equiv {2k} \! \pmod {2m}$. We present simple preparation circuits: a two-legged code using a Hadamard-conditional-squeezing-Hadamard sequence on an ancilla qubit, and for general "$m$-legged" codewords using sequences of conditional rotations. The performance of these codes is evaluated against loss and dephasing noises using the Knill-Laflamme violation function and benchmarked against cat codes. As the number $m$ of squeezed-vacuum states in a code increases, the code exhibits improved loss tolerance at the cost of higher dephasing sensitivity. We outline implementations in circuit QED and trapped-ion platforms, where high-fidelity Gaussian operations and conditional controls are available or under active development. These results help establish squeezed-vacuum codes as practical, hardware-ready, members of the bosonic codes class.

Resolving sources beyond the diffraction limit is important in imaging, communications, and metrology. Current image-based methods of super-resolution require phase information (either of the source points or an added filter) and perfect alignment with the centroid of the object. Both inhibit the practical application of these methods, as uniform motion and/or relative jitter destroy their assumptions. Here, we show that measuring intensity in the Fourier plane enables super-resolution without any of the issues of image-based methods. We start with the shift-invariance of the Fourier transform and the observation that the two-point position problem ${x_1,x_2}$ in the near field corresponds to the single-point wavenumber problem $k\ =2\pi/(x_2-x_1)$ in the far field. We consider the full range of mutual coherence and show that for fully coherent sources, the Fourier method saturates the quantum limit, i.e. it gives the best possible measurement. Similar results hold for sub-Rayleigh constellations of $N$ sources, which can act collectively as a spatially averaged metasurface and/or individually as elements of a phased-array antenna. The theory paves the way to merge Fourier optics with super-resolution techniques, enabling experimental devices that are both simpler and more robust than previous designs.

In various physical implementations of quantum information processing, qubits are realized in a Lambda type system configuration as two stable lower energy levels coupled indirectly via an unstable higher energy level, that is, in comparison, a lot more susceptible to decoherence. We consider the quantum control problem of optimal state transfer between two isospectral density matrices, over an arbitrary finite time horizon, for the quantum Lambda system. The cost considered is a compromise between the energy of the control field and the average occupancy in the highest energy level. We apply a geometric approach that combines the use of the Pontryagin Maximum Principle, a symmetry reduction technique to reduce the number of parameters in the resulting optimization problem, and several auxiliary techniques to bound the parameter space in the search for the optimal solution. We prove several properties of the optimal control and trajectories for this problem, including their normality and smoothness. We obtain a system of differential equations that must be satisfied by the optimal pair of control and trajectory we treat in detail, with numerical simulations, and solve a case study involving a Hadamard-like transformation. Our techniques can be adapted to other contexts and promise to push to a more consequential level, the application of geometric control in quantum systems.

Heat engines convert thermal energy into mechanical work. We here report the experimental realization of a fully quantum engine that converts quantum coherence into work. A single solid-state spin in diamond is fueled by a coherent bath and cyclically stores energy in a spin quantum battery. We establish quantum-enhanced performance by showing that almost 200$\%$ more work is produced after a few cycle compared to the corresponding classical engine. We obtain concrete criteria for successful coherence-to-work conversion, and highlight the importance of a coherent motor-battery interaction. This device harnesses nonclassical features during all stages of its cycle, and demonstrates the functionality of a nanomachine whose parts are all quantum coherent.

Rapid progress in valleytronics and spintronics is limited by the scarcity of two-dimensional materials that simultaneously provide robust valley splitting and strong spin selectivity. Here we showed that a van der Waals heterostructure (VSe2/VN) built from hexagonal VSe2 and hexagonal VN addressed this gap. Using first-principles density functional theory, phonon, ab initio molecular dynamics stability tests, Bader charge analysis, and Wannier-based Berry-curvature calculations, we demonstrated an energetically and dynamically stable heterostructure that exhibited interlayer charge transfer and a work function intermediate between the constituent monolayers. The electronic structure showed small indirect PBE gap (108.9 meV), with HSE06 indicating a half-metallic tendency; a sizable conduction-band valley splitting (\Delta CKK' = 22.9 meV for spin-up and \Delta CKK' = 61.3 meV for spin-down); and pronounced spin asymmetry, where the spin-down channel showed a wide semiconducting gap (0.64 eV) while the spin-up channel was nearly gapless. These features yielded a high zero-strain spin-filter efficiency P = 75.4%, tunable to 82.5% under +4% biaxial tensile strain. The heterostructure also supported non-zero, valley-contrasting Berry curvature, and a large anomalous Hall conductivity (peak sigmaxy = 568.33 S/cm). Importantly, mean-field estimation placed the ferromagnetic Curie temperature near room temperature at zero strain (Tc = 284.04 K), while Tc decreased to 183.9 K at +4% strain, the magnetic order remained robust to cryogenic temperatures, providing a beneficial tuning knob to balance spin-filter performance with thermal stability in device-relevant regimes. These results identified VSe2/VN as a practical, strain-tunable platform for integrated valleytronic, spintronic devices, and for exploring anomalous Hall and valley-dependent transport phenomena.

The precision with which we can measure operators that do not commute with conserved quantities is limited by the need to preserve the associated global symmetries. We show how to construct a local hidden-variable model that violates Bell inequalities by interpreting this measurement error as altering the measure space of the hidden variables. This provides a physically-motivated example of a supermeasured model, where the statistical independence assumption used to form Bell inequalities is violated without there being a causal dependence of the measurement settings on the hidden variables (superdeterminism) or a causal dependence of the hidden variables on the measurement settings (retrocausality). The model also gives subtly different predictions to quantum mechanics, that could be tested experimentally.

We introduce the Spin-ZX calculus as an elevation of Penrose's diagrams and associated binor calculus to the level of a formal diagrammatic language. The power of doing so is illustrated by the variety of scientific areas we apply it to: permutational quantum computing, quantum machine learning, condensed matter physics, and quantum gravity. Respectively, we analyse permutational computing transition amplitudes, evaluate barren plateaus for SU(2) symmetric ansätze, study properties of AKLT states, and derive the minimum quantised volume in loop quantum gravity. Our starting point is the mixed-dimensional ZX calculus, a purely diagrammatic language that has been proven to be complete for finite-dimensional Hilbert spaces. That is, any equation that can be derived in the Hilbert space formalism, can also be derived in the mixed-dimensional ZX calculus. We embed the Spin-ZX calculus inside the mixed-dimensional ZX calculus, rendering it a quantum information flavoured diagrammatic language for the quantum theory of angular momentum, i.e. SU(2) representation theory. We diagrammatically derive the fundamental spin coupling objects - such as Clebsch-Gordan coefficients, symmetrising mappings between qubits and spin spaces, and spin Hamiltonians - under this embedding. Our results establish the Spin-ZX calculus as a powerful tool for representing and computing with SU(2) systems graphically, offering new insights into foundational relationships and paving the way for new diagrammatic algorithms for theoretical physics.

In this study, we propose a new approach to describing certain macroscopic objects that can arise in a quantum fluid. These objects are formed by means of quantum entanglement from the circular-shaped mesoscale and microscale vortices, and can be interpreted as a vortex filaments with any shape and size. The method is based on a quantization scheme for classical closed vortex filaments that was proposed by the author early \cite{Tal18,Tal22_1,Tal_Chaos25J}. The model we consider examines the instantaneous picture of the locations in space $\mathbb R_3$ of such filaments with a small, but non-zero, core diameter. Both energy and circulation of the studied filaments are calculated using the proposed approach. We demonstrate that the adopted concept leads to the emergence of secondary vortices around these investigated filament-like objects. We also study the specific mechanisms by which large vortex loops can disconnect and create the filament fragments . From our point of view, the proposed approach to describing vortex filaments within a vortex tangle can be seen as an important step toward understanding the appearance of quantum turbulence.

The definition of quantum states in terms of tagged vector spaces is generalized to incorporate the spatiotemporal and spin degrees of freedom. Considering a tagged vector space where the index space is a function space, representing the additional degrees of freedom, we obtained axioms for the tags that include a completeness condition expressed in terms of a functional integral with an abstract functional integration measure. Using these axioms, we derive a generating functional for the moments of this functional integration measure. These moments are then used to evaluate the functional integrals of Gaussian functionals, leading to expressions in accordance with those obtained as generalizations of equivalent integrals over a finite number of integration variables. For a Gaussian functional used as a probability distributions, we show that its moments, obtained with this functional integration measure, satisfy Carleman's condition, indicating that the measure is unique.

Quantum technologies with quantum correlated light require photodiodes with near-perfect `true' quantum efficiency, the definition of which adequately accounts for the photodiode dark noise. Future squeezed-light-enhanced gravitational wave detectors could in principle achieve higher sensitivities with a longer laser wavelength around 2 {\mu}m. Photodiodes made of extended InGaAs are available for this range, but the true quantum efficiency at room temperature and the low frequency band of gravitational waves is strongly reduced by dark noise. Here we characterize the change in performance of a commercial extended-InGaAs photodiode versus temperature. While the dark noise decreases as expected with decreasing temperature, the detection efficiency unfortunately also decreases monotonically. Our results indicate the need for a dedicated new design of photodiodes for gravitational wave detectors using 2-{\mu}m laser light.

The quantum speed limit sets a fundamental restriction on the evolution time of quantum systems. We explore the relationship between quantum imaginarity and the quantum speed limit by utilizing measures such as relative entropy, trace distance, and geometric imaginarity. These speed limits define the fundamental constraints on the minimum time necessary for quantum systems to evolve under various dynamical processes. As applications the dephasing dynamics and dissipative dynamics are analyzed in detail. The quantum speed limit in stochastic-approximate transformations is also investigated. Our quantum speed limits provide lower bounds on how fast a physical system evolves to attain or lose certain imaginarity, with potential applications in efficient quantum computation designs, quantum control and quantum sensing.

Optical systems are a main platform for quantum information processing. A main challenge is information loss due to scattering in unmonitored modes. These losses are modeled as state-independent beam-splitter interactions, with a thermal state (for all practical purposes, the vacuum) in the second input port. The perfect correction of these Gaussian lossy channels with Gaussian operations alone is known to be impossible. In this work, we investigate the Petz recovery map as an approximate recovery. For single mode losses and Gaussian reference states, the Petz map is found to use either a beam-splitter or a state-independent amplifier, depending on the parameters. Then we study the recovery performance on several examples, showing that it is near-optimal among the considered class of protocols. We also obtain more specific comparisons: Petz is always better than just re-preparing the reference state; but it is worse than doing nothing if the reference state is far from the true state. Finally, we extend our study to losses on two modes, and compare the global Petz map to the local implementation on each mode separately.

We investigate the relationships among the wave property, particle property and mixedness of quantum states based on the lp-norm coherence. By conforming that the lp-norm coherence is an appropriate measure of wave property and introducing a measure of particle property based on the differences between the maximal l2-norm coherence and the general l2-norm coherence, we present tradeoff relationships among the wave, particle and mixedness of quantum states. For 1<= p <2, we establish two kinds of tradeoffs of the wave, particle and mixedness with respect to the upper and lower bounds of the lp-norm coherence given by the l2-norm coherence. These trade relations give rise to compressive understanding of the intrinsic connections among the wave, particle and mixedness of quantum states, and cover some existing results as particular ones.

Scalable implementation of quantum networks and photonic processors require integrated photonic memories with high efficiency, yet current integrated systems have been limited to storage efficiencies below 27.8%. Here, we demonstrate highly efficient integrated quantum memories based on rare-earth-iondoped crystals coupled with impedance-matched microcavities, realized in two novel architectures: 200-micrometer-thin membranes of Eu3+:Y2SiO5 integrated with fiber-based microcavities, and waveguide-based cavities fabricated using femtosecond lasers. Our approach achieves reliable integrated quantum storage with record efficiencies of 80.3(7)% for weak coherent pulses and 69.8(1.6)% for telecom-heralded single photons, alongside the storage of 20 temporal modes with an average efficiency of 51.3(2)%. Moreover, the thin-membrane Eu3+:Y2SiO5 architecture enables spectrally tunable efficient quantum storage via variable strain, providing a flexible interface for quantum networks. By combining high efficiency, large multimode capacity, and tunability, our devices establish a versatile hardware foundation for scalable quantum repeaters and chip-scale photonic processors.

Model predictive control has shown potential to enhance the robustness of quantum control systems. In this work, we propose a tractable Stochastic Model Predictive Control (SMPC) framework for finite-dimensional quantum systems under continuous-time measurement and quantum filtering. Using the almost-sure eigenstate reduction of quantum trajectories, we prove that the infinite-horizon stochastic objective collapses to a fidelity term that is computable in closed form from the one-step averaged state. Consequently, the online SMPC step requires only deterministic propagation of the filter and a terminal fidelity evaluation. An advantage of this method is that it eliminates per-horizon Monte Carlo scenario sampling and significantly reduces computational load while retaining the essential stochastic dynamics. We establish equivalence and mean-square stability guarantees, and validate the approach on multi-level and Ising-type systems, demonstrating favorable scalability compared to sampling-based SMPC.

Continuous-variable quantum batteries provide a viable platform for microscopic energy storage, yet environmental dissipation typically degrades both their charging efficiency and extractable work (ergotropy). In this work, we investigate the charging dynamics of an open continuous-variable quantum battery modeled as coupled harmonic oscillators driven by counter-diabatic (CD) protocols in the presence of a Markovian thermal reservoir. Using Williamson's theorem to track the Gaussian state evolution, we show that CD driving significantly enhances ergotropy compared to conventional unassisted driving. Specifically, in the underdamped regime, the CD protocol boosts the peak ergotropy while suppressing thermal degradation. In the overdamped regime, where conventional unassisted charging fails due to rapid thermal dissipation, the CD protocol maintains a robust, non-zero ergotropy. Furthermore, by evaluating the temporal fluence of the auxiliary control fields, we assess the energetic cost and confirm that these thermodynamic advantages are achieved with physically realistic control overheads. These results indicate that counter-diabatic driving provides a practical route to decoherence-resilient quantum energy storage.

Biphoton states have shown promising applications in quantum information processing, including quantum communications, quantum metrology, and quantum imaging. The generation and manipulation of biphoton entanglement in topologically distinct modes paves the way in this direction. Here we present a comprehensive method for regulating the topological properties of the system by combining the nonlinearity in waveguides, i.e., nonlinearity in the waveguide coupling materials, and the waveguide lattice structure. Our method enables the generation of topological biphoton states with injected pump activation on the topologically trivial modes. This is realized through self-induced manipulation on pump-dependent nonlinear couplings on the defects, which is unable to be realized while there are no such nonlinear couplings. Specifically, by including the nonlinear gain/loss mechanism in the coupling between the nearest-neighbor waveguides and the third-order Kerr nonlinearity effect along the waveguides, the injected pump power will be the controllable parameter for the manipulation of the topology in the defect states and the generation of biphoton entanglement states. We also present an experimental proposal to realize our scheme and its generalization in the contemporaneous "active" topological photonics time-bin platforms. Our method can be used in other Su-Schrieffer-Heeger (SSH) models with various defect configurations. Our method enables the reusability and versatility of SSH lattice chips and their application for fault-tolerant quantum information processing, promoting the industrialization process of quantum technology.

The ability to preserve multipartite entanglement in noisy environments is central to advancing quantum information processing. In this work, we develop a semiclassical theoretical model of three entangled qubits exposed to local Markov noise environments with tunable statistical correlations between noise sources. We show that such correlations can significantly influence the dynamics of multipartite entanglement, in some cases slowing its decay and, under ideal conditions, even enabling full preservation. Using tripartite negativity as an entanglement measure, we derive analytical results for the GHZ and W states, demonstrating their contrasting responses to correlated and anticorrelated noise. Our analysis identifies regimes in which multipartite entanglement can be sustained despite environmental interactions, offering new insight into how noise correlations may serve as a resource for protecting quantum coherence in multi-qubit systems.

The negatively charged tin-vacancy center in diamond (SnV$^-$) is an excellent solid state qubit with optically-addressable transitions and a long electron spin coherence time at elevated ($\sim1.7$ K). However, implementing scalable quantum nodes with high-fidelity optical readout of the electron spin state requires efficient photon emission and collection from the system. In this manuscript, we report a quantum photonic interface for SnV$^-$ centers based on one-dimensional photonic crystal cavities fabricated in diamond thin films. Furthermore, we provide a rigorous description of the spontaneous emission dynamics of our system, taking into account individual contributions from both the C and D transitions of the emitter. This allows for determination of Purcell factors per transition and, by extension, the C/D branching ratio SnV$^{-}$ zero phonon line. We observe quality factors up to $\sim$6000 across this sample, and measure up to a 12-fold lifetime reduction, which translates into a Purcell factor of $F_C=26.2\pm1.5$ for a targeted C transition. By considering the cavity mode polarization alignment with the C and D transition dipole moments, we validate the C/D branching ratio to be $\eta_{\text{BR}}=0.75\pm0.01$, in line with previous theoretical and experimental findings.

A quantum error correction code is assessed over its ability to correct errors in noisy quantum circuits. This task requires extensive simulations of faulty quantum circuits, which are often made tractable by considering stochastic Pauli noise models, as they are compatible with efficient classical simulation techniques. However, such noise models do not fully capture the variety of physical error mechanisms encountered in realistic quantum platforms. In this work, we extend circuit-level noise modeling beyond the Pauli framework by estimating the threshold of the hexagonal color code under more general noise models. Specifically, we consider two representative non-Pauli error channels: a systematic $X$-rotation model that introduces coherent over-rotations, and an amplitude damping channel that captures relaxation processes. These models are incorporated at the circuit level into color code circuits using a Tree Tensor Network ansatz. Our simulations demonstrate that tensor network simulations enable accurate threshold estimation under non-Pauli noise for color codes up to distance $d=7$ (73 qubits). Comparing our results with the Pauli twirling approximations of the noise models, we find that coherent over-rotations yield systematically higher error rates, deviating from the Pauli twirling approximation as the code distance increases.

A variety of quantum computing algorithms exist for the preparation of approximate Hamiltonian ground states. A natural and important question is how these ground-state approximations can be further improved using adiabatic state preparation. Here, we present a heuristic method to carry out adiabatic state preparation starting from a generic initial wavefunction. Given a quantum circuit that prepares the initial wavefunction, and a target Hamiltonian for which one wishes to prepare the ground state, we present an algorithm to construct an adiabatic path between these two states. This method works by approximating a parent Hamiltonian for the initial wavefunction, and the quality of this approximation can be can be checked prior to running the ASP algorithm. We apply this technique to simulate the ground state of water and the lowest-lying multireference singlet state of methylene, using various initial wavefunctions as the starting point of the adiabatic path.