Papers

We develop a theory of approximate quantum error correction (QEC) based on the error-set model, complemented by general methods for code construction. Exact QEC has a powerful error-set structure: by the Knill-Laflamme conditions, a code correcting a given error set automatically protects against every channel whose Kraus operators lie in their linear span. This linearity gives rise to code distance, the equivalence between erasures and general errors, and a theory of asymptotically good codes. A longstanding view has been that these features do not extend to AQEC, leaving the theory essentially channel-by-channel. We show instead that, although full Knill–Laflamme linearity fails, a restricted form survives and suffices to extend all three structural features to the approximate setting. Specifically, a common error-set criterion governs families of channels whose Kraus operators are linear combinations of a given error set and whose coefficient matrices satisfy a spectral constraint. Using the Bény-Oreshkov worst-case and Petz average-case frameworks, we derive uniform fidelity guarantees for these families in terms of two new code parameters–the environment-leakage distance, controlling worst-case performance, and the Knill-Laflamme Hellinger distance, characterizing the average-case performance of Petz recovery. To demonstrate the scope of this model, we develop partition-based constructions across diverse quantum systems and geometries, placing exact and approximate correction on equal footing. These constructions lead to a metric–error alignment hierarchy for Hilbert spaces, metrics, and error families, which in turn characterizes the resulting recovery guarantees. They yield the first known asymptotically good code families for fermionic systems, one-dimensional Rydberg-blockaded systems, and deletion errors, and extend to other physical platforms.

The controllability of phonon thermal transport is fundamental for numerous technologies, from cooling high-performance chips to managing heat in quantum computing. Despite extensive efforts, on-demand, real-time control of phonon heat flow remains elusive, being fundamentally constrained by the temperature gradient. Here we achieve this long-sought phonon heat transport by introducing a novel mechanism using quantum squeezing in a cavity optomechanical system. We find that phonon squeezing of near-ground-state mechanical resonators via an optomechanically induced parametric process breaks the continuous U(1) rotation symmetry in phase space, and consequently the symmetry in the heat current structure. We reveal that heat flow under a constant temperature gradient can be deterministically amplified, reduced, or even reversed, a capability previously unattainable. With phonon squeezing, we achieve over twentyfold amplification of heat flow and reversal within 30 milliseconds. Importantly, quantum discord analysis reveals a direct connection between heat flow reversal and quantum correlation. Our results establish quantum squeezing as a versatile platform for on-demand phononic thermal control, opening avenues for active heat management in quantum devices and thermal logic circuits.

We develop a systematic framework for quantum mechanics on a finite graph-resolved class of second-countable, T1, non-Hausdorff one-manifolds. The central problem is that local differential expressions do not by themselves determine the quantum theory: non-Hausdorff incidence, bundle transport, smooth extension, and analytic completion can impose additional global constraints on the operator domain. We formulate these constraints using transported jets, Whitney realisability, Sobolev traces, and formal return holonomy, obtaining exact closure results for finite smooth graph resolutions. At first Sobolev order, scalar dynamics reduce to a weighted quantum graph whose edge weights arise from a marked resolving presentation, leading naturally to weighted Kirchhoff Hamiltonians. Multiple-origin lines and circles, branching junctions, finite trees, and split-and-rejoin geometries then yield explicit deficiency indices, reflection and transmission laws, interference conditions, compact dark states, and embedded cavity modes. For finite-rank Hermitian bundles, unitary gluing selects a transmitting fixed subspace, so scattering becomes projection onto the invariant sector of the subgroup generated by the gluing matrices. Compact-group representations therefore turn non-Hausdorff incidence into an invariant-sector selection mechanism; connected compact semisimple groups require at most two relative gluing matrices for full invariant completion, with explicit SU(3) examples. The resulting theory separates topological non-Hausdorff data from the analytic and representation-theoretic structures that remain detectable by quantum dynamics.

We derive a closed-form analytical expression for the expectation values of a damped Kerr nonlinear oscillator initialized in a coherent state. Starting from the exact Liouville-space solution of the Lindblad master equation, we specialize to coherent-state initial conditions, obtaining explicit time-dependent expressions for arbitrary normally ordered expectation values. The resulting expressions depend only on the system parameters and the initial coherent-state amplitude, requiring neither numerical integration nor evolution in a truncated Fock space. We verify the analytical expressions against master-equation simulations over a range of nonlinear interaction strengths. The closed-form solution provides an efficient alternative to numerical simulation while remaining free of Fock-space truncation error. Finally, we note an extension of the underlying Lie-algebraic structure that may provide a useful starting point for obtaining exact solutions to a broader class of open quantum optical systems.

We introduce a discrete difference operator D_k to study the one-dimensional quantum random walk (QRW) with the Hadamard coin. Explicit combinatorial expressions are obtained for the probability amplitudes a(n,k) and b(n,k), which encode the final step direction and carry alternating signs that reflect the merging of leftward steps. Removing these signs and the coin-state distinction recovers the classical binomial distribution. The symmetric and antisymmetric combinations $a\pm b$ are shown to coincide with diagonal and sub-diagonal entries of the Krawtchouk matrix. Using cross identities among Krawtchouk matrix elements, we prove by induction that the amplitudes satisfy a Parseval identity sum (a^2+b^2)=2^n-1, establishing probability conservation in the Krawtchouk formulation. The operator D_k acts as a discrete Hermite polynomial generator: the ratios h_m = (n choose k)^{-1} D_k^m (n choose k) admit explicit closed forms and converge to Hermite polynomials in the continuous limit. At the discrete level, D_k connects successive Krawtchouk matrices and acts as a coherence generator and a raising operator. The h_m quantify the position-dependent degree of quantum interference on both halves of the distribution, either individually (for x >= 0) or through an inverse-Pascal combination of several h_m (for x < 0), and the ballistic O(n^2) scaling of the variance emerges from the superposition of all excited states. Numerical illustrations for n=6 and n=10 corroborate the analytical results.

The Unruh effect predicts that an accelerating observer perceives the Minkowski vacuum as a thermal bath, yet direct detection remains experimentally inaccessible. Its timelike counterpart, arising from the entanglement of massless fields between the future and past light cones, offers a more feasible route but requires a detector whose transition frequency follows a specific conformal-time scaling. We propose and analyze a practical implementation of such a detector using superconducting fluxonium circuits, which naturally provide two quasi-degenerate ground states and a tunable excited state, forming an effective $\Lambda$-system. By modulating the excited-state transition frequency in Minkowski time, the detector accumulates a geometric phase associated with the timelike Unruh effect. Open-system simulations predict $\sim 10\%$ shift in the ground-state population within $530$ ns, representing a three-order-of-magnitude sensitivity enhancement over two-level Unruh-DeWitt detectors. These results establish a realistic quantum-circuit platform for experimentally probing the timelike Unruh effect and, more broadly, for testing fundamental nature of quantum fields using engineered quantum systems.

We show that integrable and non-integrable dynamics can coexist in the same Rydberg-atom chain, depending on the initial state in which the system is prepared. In the setting we consider, Rydberg atoms mainly experience an effective dipolar interaction and, within the nearest-neighbor approximation, their dynamics can be mapped onto an effective integrable Fermi gas with ballistic transport. The inclusion of longer-range couplings, however, is essential for the theory to be predictive; those terms break the conservation laws associated with integrability, enabling, in particular, the emergence of genuine diffusive transport. We study the dynamics generated by a bipartition protocol and reveal a sharp qualitative change in behavior as the particle density is varied, suggesting the possibility of accessing weaker and stronger integrability breaking dynamics in the same Hamiltonian depending on the relevance of local interactions. We propose a theoretical mechanism that accounts for the differences. Our findings provide clear and concrete evidence that integrability breaking is not solely a property of the Hamiltonian and of the magnitude of the couplings that break integrability, but also of the state in which the system is prepared.

Variational ansätze are a cornerstone of quantum many-body physics, providing compact approximations to complex ground states using finite resources. Recent quantum-technology advances have introduced a new class based on layered parameterized evolutions. Assessing whether they can represent critical ground states is challenging: correlations span all length scales, while finite circuit depth limits how far they extend. Building on finite-resource scaling from tensor networks, we assign each ansatz an emergent correlation length $\xi_D$, the longest range over which it faithfully captures critical correlations. Its growth with refinement parameter $D$, $\xi_D \propto D^\kappa$, defines an exponent $\kappa$ measuring how efficiently an architecture converts resources into long-distance correlations. Applying this framework to the critical transverse-field Ising model, with $D$ the circuit depth of parameterized evolutions, we compare ansätze with nearest-neighbor and long-range generators, and layers where generators act separately or combined. All ansätze are compatible with algebraic growth, but fitted exponents range from $\kappa\simeq1$ to $\kappa\simeq3$. Exponential interactions give the largest exponents, while power-law interactions stay close to nearest-neighbor behavior, showing long-range support alone gives no scaling advantage. Combined-generator layers generally outperform separable ones, so layer organization matters alongside interaction range. Finally, a quasiparticle analysis shows finite depth leaves an unresolved window of width $\xi_D^{-1}$ around the low-energy modes responsible for long-distance correlations. The emergent correlation length thus acts as an infrared resolution scale, providing a benchmark for critical-state preparation and a guide for designing resource-efficient variational architectures.

We show how finite-difference time-domain (FDTD) simulations can be extended to model ultrafast nonlinear microscopy, enabling the prediction of spatially-resolved pump–probe signals in arbitrary electromagnetic environments. Focusing on polariton transport in strongly coupled light–matter systems, we develop a perturbative framework to study the ultrafast propagation of hybrid light–matter excitations in nanophotonic structures. We first apply the framework to a standard distributed Bragg reflector (DBR) cavity, reproducing established results for polariton transport from a multimode Tavis–Cummings model. We then consider the full modal landscape of the same cavity, including guided modes below the light line that are typically neglected in single-mode-family descriptions. Exploiting these modes, we design compact mode converters that transfer radiative cavity polaritons into photon-like guided polaritons and back, utilizing the guided modes for low-loss propagation. Despite molecular dephasing, this enables transport of molecular excitation over a millimeter, an order of magnitude beyond current transport experiments. We further compute the pump–probe differential transmission signal, providing an experimental signature of the mechanism. Our results show that the modal landscape of a photonic cavity can be engineered to bypass limitations commonly assumed to be intrinsic to the transport of molecular polaritons.

In this paper, we focus on a scheme in which three high-quality-factor mechanical modes of a hexagonal boron nitride (hBN) membrane monolayer are coupled to a common optically addressable spin defect present in the membrane via magnetic field interaction. We show that this coupling induces an effective phonon-phonon interaction in the dispersive regime and under appropriate magnetic field and microwave modulation. We derive the Langevin-Heisenberg equations of motion for vibrational modes to analyze optimal parameter regimes for reaching a physically stable system. We also investigate the effect of coupling strength on purity and entanglement. Our results demonstrate that bipartite and genuinely tripartite steady-state entanglement between different vibrational modes of hBN may be achieved in a broad spectrum of experimental parameters. This study has the potential to enable scalability to be implemented for the generation of two-dimensional continuous-variable cluster states for universal quantum computation.

In this work, we investigate the application of Machine Learning (ML) algorithms to the identification and quantitative characterization of quantum entanglement in polarization-entangled photon pairs. The analysis is based on simulated symmetric, informationally complete, positive operator-valued measure (SIC-POVM) measurement data, where each two-qubit state is represented by a 16-dimensional measurement vector corresponding to experimentally accessible coincidence counts. The generated SIC-POVM measurement data include Poissonian shot noise. Several supervised ML algorithms, including Logistic Regression, k-Nearest Neighbors, Decision Trees, Support Vector Machines, and Random Forests, are applied to the classification of separable and entangled states directly from raw measurement data, without explicit density matrix reconstruction or the use of conventional separability criteria. The study additionally explores clustering methods and nonlinear regression techniques for estimating continuous entanglement measures. The obtained results demonstrate that ML methods can achieve very high classification accuracy, even under extremely limited training conditions. These findings indicate that ML may provide an efficient alternative to conventional quantum-state analysis under simulated Poissonian noise conditions.

Cat qubits can exhibit strong noise bias due to their exponentially enhanced bit-flip times and only polynomially reduced phase-flip times with increasing photon number, which makes them attractive candidates for hardware-efficient quantum error correction. However, it is difficult to maintain this strong noise bias in logical operations such as CNOT gates between cats. Here, we propose a coherent CNOT gate scheme between two dissipative cats that preserves the exponential noise bias. The proposed gate relies only on unitary operations, which avoids the non-idealities associated with many existing gate schemes that rely on engineered dissipations. Assuming good component lifetimes and precise nonlinearity engineering, the proposed gate can enable logical memory in the megaquop regime (logical error rates < 10^-6) with a distance-7 repetition code consisting of 13 cat qubits.

Quantum-centric workflows are a promising route to improving the accuracy of property predictions in computational chemistry and materials science. By integrating quantum sampling algorithms with classical solvers, electronic structure calculations have recently demonstrated their potential even on noisy intermediate-scale quantum devices. In principle, the method of Vibrational Configuration Interaction (VCI) is suitable for integration with quantum sampling algorithms as well. However, demonstrations of computational workflows for quantum-centric, vibrational property predictions are still lacking. Here, we introduce a methodology for performing anharmonic vibrational structure calculations that can be deployed in a hybrid, quantum-classical mode. Starting from a quartic force field, the approach combines a Vibrational Self-Consistent Field (VSCF) with VCI in either Full, Selected (S-VCI), or Symmetry-Adapted (SA-VCI) mode. In S-VCI, an Epstein-Nesbet perturbative screening significantly reduces the configuration space while retaining high predictive accuracy. A state-list input enables the integration of externally generated vibrational configurations as a seed space. As a proof-of-concept, we demonstrate a hybrid, quantum-classical computational workflow, in which a quantum sampling algorithm provides the seed. Our vibrational wave function analysis package ViBra, equipped with a graphical interface, is available at https://github.com/raphafe96/ViBra.

Strongly correlated quantum matter is fundamentally defined by the tension between non-commuting quantum operators. Hamiltonians exhibiting macroscopic degeneracies are of general interest in this field because they imply an infinite susceptibility to any non-commuting perturbation. In moiré heterostructures, engineering such extensive degeneracies in the kinetic Hamiltonian creates a fertile garden for exotic strongly correlated phases of matter to emerge from the resulting flat bands. Here, we introduce a prescription to construct an infinite family of exact flat band Hamiltonians supported on the faces of arbitrary graphs. We demonstrate this algorithm on the faces of four Bravais lattices. Using a discrete graph generalization of the Atiyah-Singer index theorem, we prove that the extensive degeneracies of such face-graph Hamiltonians are protected by the local topology of the face-graph connectivity. The resulting macroscopic null spaces yield compact localised states that remain localised over time due to frustration in hopping pathways. We discuss the broad implications of such non-dispersing quantum modes in diverse settings, from arrested dynamics in quantum networks and quantum machine learning algorithms to Majorana-free topological quantum computation.

We introduce a new class of fully-quantum Metropolis walks in which both the proposal and acceptance steps are intrinsically quantum. Unlike standard quantum walks obtained by quantizing classically efficient Markov chains, our algorithm employs Hamiltonian simulation as a quantum-native proposal mechanism, enlarging the class of quantum walks beyond classical counterparts. We target the problem of sampling from the low-temperature Gibbs distribution of classical dense Ising models, within a fixed error in total variation distance. This approach achieves about a cubic polynomial asymptotic advantage over previous quantum-walks, resulting in a total sixth-degree polynomial queries speedup compared to the best classical walk. This shows that speedups beyond the widely assumed quadratic limit are possible within the quantum walk formalism. We perform a complete fault-tolerant compilation of all algorithmic primitives and benchmark against CPU, GPU, and FPGA implementations of the best classical Markov chain. Under identical hardware assumptions, the resulting advantage runtime crossover is reduced from approximately $10^3$ years for conventional quantum walks to less than one day. These results identify fully-quantum Markov chains as a promising route toward practical quantum advantage.

Quasiprobability distributions for systems endowed with SU(1,1) dynamical symmetry have received surprisingly little attention, despite the central role of this symmetry in two-photon physics, squeezed states, and nonlinear interferometry. Here, we fill this gap by constructing a full covariant family of $s$-ordered quasiprobability distributions defined on the two-sheeted hyperboloid, or equivalently, on the Poincaré unit disk via stereographic projection. A key result is that the Wigner function is strictly positive for all Perelomov SU(1,1) coherent states, in sharp contrast to the SU(2) case. This positivity endows Wigner negativity with an unambiguous operational meaning: any negative volume is a direct signature of genuinely quantum behavior. We further examine the stellar rank of SU(1,1) states, defined through the zeros of the Husimi $Q$-function, and show how it compares with Wigner negativity as a geometry-adapted witness of nonclassicality in this setting. We further introduce a hierarchy of generalized multipoles through a harmonic expansion of the density operator on the hyperboloid, providing a complementary framework for probing quantumness. This offers a comprehensive toolkit for characterizing and quantifying quantum resources in SU(1,1) systems.

Conventional membrane-in-the-middle (MIM) optomechanical systems offer limited control over the optical linewidth, which can limit their performance when operating in the unresolved-sideband regime. We investigate cavity optomechanics with a photonic-crystal Fano membrane placed at the center of a Fabry-Pérot (FP) cavity. In contrast to a conventional dielectric membrane, the photonic-crystal membrane supports a localized optical resonance, which hybridizes with the cavity field and enables spectral engineering of the relevant optical modes. Besides the usual dispersive optomechanical coupling associated with cavity-length changes, the membrane motion also modifies the Fano-mode resonance and its hybridization with the cavity field. We consider two limits set by the membrane reflectivity: a transparent-membrane regime with a single FP-like mode, and a reflective-membrane regime with two coupled subcavity modes. In the latter case, only the symmetric cavity mode hybridizes with the Fano mode, while the antisymmetric mode remains decoupled. Using quantum Langevin equations together with a transfer-matrix description of the optical scattering problem, we show that the Fano-induced hybridization can generate narrow optical normal modes that remain efficiently accessible to the external drive for experimentally realistic parameters. These modes can provide effective sideband resolution and enable ground-state cooling of the membrane motion even when the bare cavity is in the unresolved-sideband regime. Our results establish Fano MIM systems as a promising platform for spectral and optomechanical engineering.

Motzkin spin chains are paradigmatic frustration-free one-dimensional quantum systems whose ground states feature exactly solvable combinatorial structures and exotic, area-law-violating entanglement scaling. Specifically, colorless Motzkin states exhibit critical logarithmic entanglement divergence \(\log N\) with system size \(N\), while their colorful counterparts host supercritical sublinear \(\sqrt{N}\) entanglement growth. Such unconventional entanglement behaviors place these states well beyond the expressive capability of standard matrix product states, which are fundamentally constrained by the entanglement area law. Here, we systematically construct exact, training-free neural-network representations for both colorless and colorful Motzkin states across four mainstream architectures, including recurrent, feedforward, convolutional, and transformer networks. Our core design leverages a causal prefix-sum module, implementable via recurrent updates, feedforward mappings, or masked attention layers, combined with position-selective rectified linear gates that enforce the Motzkin height constraints. For the colorful states, we further introduce a dedicated causal stack module that explicitly encodes the last-in-first-out color-matching rule. Our results demonstrate that neural architectures can accurately capture highly non-trivial entanglement features inaccessible to conventional tensor networks, providing prototypic examples for benchmarking and a constructive design framework for future neural-network quantum state developments targeting strongly entangled quantum systems.

Feedback locking of a probe frequency to a spin resonance is the standard operating mode of precision quantum sensors. Here we deliberately operate such a lock outside its stable regime: a continuous-wave nitrogen-vacancy (NV) ensemble magnetometer, frequency-modulation (FM) locked to one flank of its optically detected magnetic resonance (ODMR), is driven through the flip (period-doubling) bifurcation of its discrete feedback map by raising the software loop gain $G$. Beyond a critical gain $\Gc$ the lock becomes a self-sustained oscillator whose limit cycle is generated by the loop itself. We derive the threshold condition $\Gc = 2\,\Dcal/\Dtrue$, which identifies the measurable content of the threshold: the ratio of the transduction slope of the ODMR lock-in signal at calibration time $D_{cal}$ to its value at present $D_{true}$. We present an identifiability analysis showing which physical parameters this single scalar can and cannot distinguish, characterize the estimators of $\Gc$ under realistic noise, and report measurements on our current setup: an experimental bifurcation diagram with onset at $\Gc \approx 2$ as predicted for a self-calibrated loop, sub-threshold critical fluctuations following the predicted $\sqrt{G/(2-G)}$ divergence.

A central design principle in modern machine learning and artificial intelligence is to align a model's inductive bias with the structure of its input data. For matrix-valued inputs, relevant matrix-level relationships can be characterised through spectral values and spectral subspaces; however, common coordinate-wise rotation-gate data-encoding unitaries used in most quantum machine learning models do not explicitly construct such a matrix-level representation. We introduce Quantum Spectral Models (QSMs), in which we construct the generator of the data-encoding unitary directly from each input matrix. We study three QSM variants based on symmetric, global block, and non-overlapping patch-local block Hamiltonians. Their outputs admit truncated Fourier representations in which input-dependent spectral gaps supply candidate phase carriers, while spectral subspaces help determine their coefficients. We evaluate the QSMs and comparison quantum models on two matrix representations of Pendigits and two controlled synthetic tasks defined by spectral statistics. At the largest evaluated circuit depth, QSM variants lead the tested quantum models in mean test accuracy across all four benchmarks. The patch-local QSM leads on Pendigits, whereas the global block-Hamiltonian QSM leads on the controlled spectral tasks. Ablations show a task-dependent reversal: subspace-preserving controls perform better on Pendigits, whereas spectral-value-only controls lead among the tested ablations on the synthetic tasks. Together, these results shed new light on quantum machine-learning model design by showing how input-conditioned spectral representations can provide an analysable inductive bias, while offering a broader perspective on structure-aware model design in machine learning and artificial intelligence.

Coherent errors in stabilizer codes are often correlated across qubits and QEC cycles. Having a general analytical treatment of such noise would thus be extremely valuable. We derive here the exact logical channel induced by repeated QEC cycles under correlated coherent $Z$ noise, and develop a broadly general cumulant-expansion framework that yields a tractable expression for the noise-averaged logical infidelity. Crucially, this expression is non-perturbative in the noise, and applies to arbitrary stabilizer codes and correlation structures. It reveals a feature with no analogue in standard stochastic Pauli error models: the induced channel depends on which stabilizer eigenspace is chosen as the codespace. Exploiting this, we introduce protected stabilizer eigenspace (PROSE) encoding, an error-suppression strategy that selects the optimal codespace. We show that this eigenspace can be efficiently identified in many relevant situations. Further, when combined with logical Pauli twirling, PROSE matches or outperforms standard error suppression techniques (dynamical decoupling, Pauli twirling of physical qubits). We also show that noise correlations, usually assumed to be harmful to QEC, can instead be a resource: with the right encoding, even positive correlations reduce the logical infidelity below the uncorrelated baseline. Our results offer a new, broadly applicable lens on correlated coherent noise in stabilizer codes.

Post-selected stabilizer state preparation is a necessary subroutine in fault-tolerant quantum computation, both for initialization of logical qubits, and for logical-ancilla-based error correction gadgets (e.g. Steane and Knill). Therefore, reducing the number of gates needed to prepare a stabilizer state fault-tolerantly can simultaneously reduce time-to-solution and increase reliability. For small, low-distance codes such as the [[7, 1, 3]] Steane code, circuits with low gate counts can be found by inspection. This becomes impractical for larger codes, necessitating automation. There are two state-of-the-art methods for automated fault-tolerant state preparation, SAT-based stabilizer measurement and flag-at-origin. In this work, we optimize state preparation circuits using the circuit gauge operator formalism to express the construction of flag circuits as an integer linear program. This allows the construction of circuits with equal or lower gate count than the state of the art, while detecting up to three errors. We use this technique to derive a Steane error correction gadget for the [[24, 10, 4]] two-block group algebra code, and test it on Quantinuum's System Model H2 quantum computer with 10,000 shots, resulting in a logical block error rate ~0.00014 (~0.000014 per logical qubit), with ~1.6% of the shots post-selected due to weight-two errors.

Diagrammatic languages such as ZX-calculus provide compact and intuitive descriptions of quantum processes and have become established tools for circuit simplification, verification, and compilation. However, their potential as a framework for constructing many-body states and the Hamiltonians that host them remains largely unexplored. Here, we introduce families of fractal many-body states obtained from ZX-diagrams based on the Sierpiński triangle and Sierpiński carpet. By construction, the underlying graph connectivity imposes atypical subvolume-law minimum-cut upper bounds on entanglement: at most logarithmic scaling for the triangle family and sublinear power-law for the carpet family. By adjusting the free parameters of the ZX-diagram construction, we can tune the actual entanglement scaling: we demonstrate both area-law and logarithmic scaling for the triangle, and both log law and power-law for the carpet. Additionally, their local observables retain fractal-like spatial structure, identifying these states as natural candidates for atypical eigenstates in otherwise thermalizing systems. For the triangle family, we combine parent-Hamiltonian methods, insights from ZX-calculus, and local ZX identities that certify exact annihilation of the target state, producing frustration-free Hamiltonians whose terms admit simple representations in the same diagrammatic language as the states themselves. We then construct a local deformation that produces chaotic level statistics while embedding the fractal ZX state in the bulk of the energy spectrum as an exact quantum many-body scar. Our results demonstrate, through this explicit construction, that ZX-calculus can serve as a framework for Hamiltonian inverse design, in which quantum many-body scars, their local annihilators, and the chaotic Hamiltonians embedding them can be constructed and related through a set of graphical identities.

Quantum state preparation is a key component of many quantum algorithms. Performing this step efficiently is essential for realizing practical quantum advantage in quantum chemistry applications. Iterative algorithms like ADAPT-VQE can produce shallow ground-state preparation circuits, but become computationally prohibitive for the larger molecules relevant to materials science and pharmaceutical development. Here, we introduce ADAPT-GQE, a generative AI framework that learns to synthesize ground-state preparation circuits for electronic structure calculations. We first use ADAPT-VQE to generate high-quality reference circuits, which are then used as targets for training models for circuit generation. Once trained, the model can efficiently propose and score circuits, enabling reinforcement learning (RL) to drive circuit generation accuracy beyond the accuracy of the ADAPT-VQE training data. This pipeline achieves order-of-magnitude reductions in circuit generation time relative to ADAPT-VQE while maintaining comparable or improved state-preparation accuracy. We demonstrate ADAPT-GQE on imipramine, a well-established tricyclic antidepressant that serves as a representative, challenging target for computational modelling in drug stability protocols. We execute generated circuits on Quantinuum Helios-1, representing a milestone for AI-generated quantum chemistry circuits on state-of-the-art quantum hardware. These results establish a pathway toward automated quantum circuit synthesis for utility-scale quantum computational chemistry.

Collective Rydberg excitations offer strong and controllable interactions for quantum information processing, sensing, and nonlinear quantum optics, but their integration with temporally or spectrally multiplexed schemes, such as the Gradient Echo Memory (GEM) protocol, is hindered by rapid motional dephasing caused by the large spinwave wavevector. We demonstrate a new type of multi-photon addressing and interfacing scheme (with levels following the shape of the letter Ń) that allows us to generate collective Rydberg excitations with near-zero momentum transfer, extending the Rydberg spinwave lifetime almost tenfold. The scheme relies on two additional off-resonant driving fields arranged at a magic angle, forming a closed wavevector loop while remaining compatible with GEM-induced inhomogeneous broadening. This enables storage and manipulation of long-lived Rydberg spinwaves in a multimode quantum memory. Using microwave coupling between neighboring Rydberg states, we can control the attenuation between stored excitation modes by interaction-induced decay and demonstrate interaction-controlled diffraction of a retrieved optical signal. Our results reestablish compatibility between Rydberg excitations and GEM, providing a route toward multimode quantum memories with controllable long-range interactions and applications in quantum networking, sensing, and quantum information processing.

Tiger codes form a family of multimode bosonic quantum codes that unify several previously known constructions, including cat, paircat, and the two-mode binomial code. In this work, we give a rigorous algebraic treatment of these codes. Starting from a kernel definition of the codespace, we prove that the annihilation-type constraints admit a finite generating set, construct an explicit orthonormal basis, and show that the logical structure of the code is governed by the homology of an underlying chain complex, as expected in the original work on Tiger codes of Xu et al. We then develop a Fourier transform over the codespace to prove that the span of phase-rotated projected coherent states is dense therein, and to yield dual $X$- and $Z$-type descriptions of the code. We further extend the framework to non-linear number constraints, encompassing codes such as the four-legged cat or the repetition cat code. Finally, we investigate the implementation of logical operations. We first generalise the construction of logical Pauli operators proposed by Xu et al. to arbitrary logical spaces, and then construct non-Clifford gates using physical polynomial phase rotations of the form $e^{iP(\hat{\boldsymbol{n}})}$. We derive criteria on the real polynomial $P$ which, for positive single-logical-qubit Tiger codes satisfying an additional sign assumption, such as the paircat code, characterise the polynomials $P$ that preserve the codespace by decomposing them into a family of univariate polynomials. Through this decomposition, we relate the degrees of the resulting components to the induced logical action in the Clifford hierarchy. These results establish Tiger codes as a mathematically robust framework for describing a broad class of bosonic encodings.

Entanglement through interfaces has attracted considerable attention in 2d conformal field theory (CFT). However, it is known that field-theoretic predictions based on the existing framework are in general incompatible with numerical results [1-4]. A new framework for entanglement through topological defects was recently proposed in [5]. It provides a general description of entanglement through topological defects and successfully reproduces the numerical results for the Ising model in all tested cases and regimes. The key insight is that the relevant quantum correlations are encoded in twisted states, allowing for the construction of the full reduced density matrix (RDM). In this work we pursue two objectives. First, we provide new examples by studying defects in the free boson CFT. Second, we extend the framework to topological interfaces connecting two, possibly distinct, CFTs. Of particular interest are interfaces relating dual theories. We show that the reduced density matrix for a duality interface is the projection of the vacuum reduced density matrix onto a single symmetry sector, closely paralleling the framework of symmetry resolution. Unlike symmetry resolution, however, the projection is imposed by the physical interface itself, demonstrating that duality interfaces reflect quantum correlations back into the entangling interval. We establish this mechanism for diagonal and non-diagonal rational CFTs as well as the free boson CFT. Relative entropy allows us to quantify the distinguishability of the duality interface RDM from the vacuum RDM.

Quantum networks promise secure communication, distributed sensing and modular quantum computing by interconnecting distant quantum nodes through photonic links. Extending such networks beyond metropolitan distances requires quantum repeaters to overcome the exponential attenuation of photons in optical fiber. Across all architectures, a key requirement is the indistinguishability of single photons, which directly impacts the fidelity of photonic operations based on two-photon interference, such as Bell-state measurements and fusion gates. Here, we demonstrate generation of highly indistinguishable single photons from a coherently excited tin-vacancy center in diamond, achieving raw Hong-Ou-Mandel interference visibilities exceeding 0.95. By separating intrinsic emitter properties from technical imperfections, we show that decoherence plays a negligible role and that the remaining limitations are predominantly technical in nature, arriving at an intrinsic indistinguishability of up to 0.999. We further show that quantum frequency conversion to the telecom C-band preserves the photon indistinguishability. In combination with the long-lived electron and nuclear spin coherence times, these results establish tin-vacancy centers in diamond as a competitive platform for long-distance quantum networks and photonic quantum information processing. We further substantiate this potential through Monte Carlo simulations of a quantum-repeater link, demonstrating that the SnV-center platform surpasses the bound set by direct transmission.

This is a short study of an approach offering high tolerance to damage (i.e. defects or 'drop outs') in solid state fault-tolerant quantum computing. Our method is primarily aimed at semiconductor electron spin-qubit systems, which have been shown to support fast and high-fidelity shuttling along pre-defined paths. We adapt the recent CAbLECAR method of Chadwick and Chong: stabilisers are performed by ancillas which each follow a bespoke pre-programmed path. We consider the simple surface code but we damage the physical lattice, and rely on route-solving software to find efficient pathways under constraints enforcing stabiliser commutation and hook error avoidance. Solutions are then converted to detector error models for Stim and logical error rates are obtained. We express our results by gauging the logical performance against that of a pristine lattice, using the notion of a reduced equivalent surface-code distance; for reasonable underlying error rates we find that $10\%$ damage leaves roughly half of the pristine equivalent distance ($d_\text{equiv}\approx0.48\,d_\text{pristine}$ in the large-array limit, rising to $\approx0.60$ for our smallest array). This suggests that one can tolerate substantial damage by building oversized arrays. We note that investigating damage tolerance of other qLDPC codes is a straightforward generalisation, and potentially one could adapt to damage emerging at runtime.

The biharmonic equation is a prototypical fourth-order partial differential equation whose high-dimensional discretization suffers from rapidly growing degrees of freedom and severe ill-conditioning. We develop QSVT–VTAA quantum linear-system algorithms by constructing explicit block-encodings tailored to periodic, simply supported, and Dirichlet–Neumann boundary conditions. For periodic and simply supported problems, Fourier and sine-transform diagonalizations yield augmented Poisson systems with the condition-number scaling of a second-order operator. For Dirichlet–Neumann problems, we introduce a second-order boundary-corrected finite-difference discretization, establish mesh-independent stability, and construct an explicit block-encoding of the resulting nonsymmetric matrix. We also formulate a coupled-Laplace system with additional boundary unknowns and characterize its complexity in terms of the condition number of the complete augmented matrix. The analysis covers discretization error, block-encoding normalization, gate complexity, and solution extraction under an amplitude-input and quantum-state-output model. Numerical experiments validate the proposed discretizations and the corresponding linear solves.