Papers

We define a relative $\mathbb{Z}_2$-index $\mathcal{N}(\omega_1,\omega_2)$ for locally-comparable, parity-invariant pure states on a unital $C^*$-algebra. We prove that the index is well-defined, multiplicative, invariant under parity-preserving automorphisms, and locally constant in the norm topology. For the one-dimensional self-dual CAR algebra, we apply this construction to the half-chain automorphism $\sigma$ and define the many-body Majorana number $\mathcal{N}\sigma(\omega):=\mathcal{N}(\omega,\omega\circ\sigma)$ for parity-invariant $\sigma$-local pure states. In the quasi-free Hilbert–Schmidt regime, this index agrees with the usual single-body Majorana number. We then introduce symmetric local automorphism paths and prove that $\mathcal{N}_\sigma$ completely classifies the resulting automorphic-path-components. This automorphic-path equivalence retains the bulk Majorana number but may forget a relative zero-dimensional parity obstruction.

Quantum computers offer the potential to directly probe the dynamics of strongly coupled quantum field theories. As a step towards reaching this potential, local Krylov-based truncations of a pure SU(2) lattice gauge theory on a triangular lattice are constructed. Adjoint strings connected to dynamical gluons are constructed in this truncated theory, and the resonances dominating the long-term dynamics at a large value of the gauge coupling are determined. Local operators are constructed to identify string oscillations and breakings. This is used to perform a quantum simulation of adjoint string breaking on an $8\times8$ and $16\times8$-site lattice with ibm_boston using all 156 qubits. Quantitative agreement with tensor network simulations is obtained for circuits with 7,634 CZ gates with a two-qubit gate depth of 218. In this simulation, the rates of oscillations and glueball production are identified with a distinctly non-Abelian signature of the underlying gauge group.

We introduce determinant quantum-quantum Monte Carlo (DQ$^2$MC), a quantum algorithm that lifts the auxiliary-field sampling and averaging at the operational core of determinant quantum Monte Carlo onto a quantum computer. A determinant oracle synthesizes the DQMC amplitudes directly from a block encoding of the single-particle action matrix via quantum singular value transformations, so that the exponentially many Hubbard-Stratonovich weights are never enumerated, precomputed, or stored. Since the fermions are free for fixed auxiliary fields, the construction operates entirely at the single-particle level, requiring $O(\log N_{\mathrm{st}})$ system qubits and no Jordan-Wigner or Bravyi-Kitaev encoding, where $N_{\mathrm{st}}$ is the space-time volume. A full-quantum protocol makes observables interference amplitudes, eliminating the Markov chain and its autocorrelation time altogether; a hybrid quantum-classical protocol retains a constant-size active block of qubits and replaces the Metropolis-Hastings acceptance step with an exact heat-bath draw, so that cluster updates of any size are rejection-free, and passes only classical information between updates, admitting parallel tempering and distributed execution across quantum processors. The circuit-depth scales more favorably with spatial volume than classical DQMC, at the price of a post-selection overhead determined exactly by the largest target probability — polynomial for smooth distributions, exponential for sharply peaked ones. Finally, the reweighting estimator underlying the fermion sign problem maps exactly onto a quantum weak value, placing the exponential cost of sign-problematic DQMC in precise correspondence with the post-selection overhead of weak-value extraction.

We study the nonequilibrium response of a one-dimensional Bose-Hubbard medium to a two-magnon bound state propagating along an attractive XXZ chain. A Holstein-type displacement coupling makes the magnon density act both as a local chemical-potential perturbation and as a source of bosons. We derive a long-wavelength hydrodynamic description of the density and phase fluctuations and test it against matrix-product-state simulations of the full coupled dynamics. The theory predicts a comoving near-field deformation together with retarded density waves confined to a sound cone. In the Mott regime, the deformation remains localized around the moving pair. In the compressible regime, two counterpropagating fronts detach and approach the semiclassical sound velocity, recovered from the equilibrium density with no fitted parameters. The coupling also induces a dynamical backreaction that slows the bound state and broadens its magnon-density profile. The comparison delimits where hydrodynamics stays quantitative once the probe reacts back on the medium.

Exponentially decaying long-range hoppings are ubiquitous in realistic tight-binding models and are often truncated to obtain a finite-range description. We show that this approximation can fail dramatically in non-Hermitian systems under open boundary conditions: an infinitesimal long-range hopping can nonperturbatively reconstruct the spectrum and eigenstates of a short-range non-Hermitian system. The mechanism is controlled by a competition between the decay length of infinitesimal long-range hoppings and the localization length of non-Hermitian skin modes, leading to a sharp transition as the decay rate is tuned. In one dimension, we show that a squeezed generalized Brillouin zone (GBZ) replaces the original GBZ of the short-ranged Hamiltonian, yielding the reconstructed open-boundary spectrum. In two or higher dimensions, we formulate a squeezed amoeba formulation describing the reconstructed spectral density. We further show that long-range hoppings can qualitatively reshape Green's function, which can be readily detected in experiments.

Leading eigenvalues of the truncated propagator, known as Ruelle-Pollicott (RP) resonances, are an elegant way of addressing the dynamics of unitary many-body systems. We study unitary propagators in their canonical form, known in the mathematical literature as the CMV matrices, and obtain a number of exact results for RP resonances and the associated norm-diverging eigenvectors. For the simplest CMV class describing a unilateral shift with an impurity, motivated by operator dynamics in dual-unitary circuits, we obtain closed-form results and in particular show that the three independent ways of obtaining RP resonances – the truncated propagator, analytic continuation of the resolvent, and the rigged Hilbert space approach – all give the same results. In more realistic CMV matrices, in which shift-like operator dynamics characteristic of chaotic systems is only asymptotic, we rely on the rich theory of orthogonal polynomials on the unit circle and identify two phases. In the first phase, relaxation occurs due to local operators effectively evolving into increasingly nonlocal ones with negligible backflow. Especially interesting is the second phase, which, surprisingly, exhibits faster relaxation because of contributions from the backflow of large operators. Additionally, in the second phase, RP resonances are not equal to the eigenvalues of the truncated propagator, instead, they are “hidden” within a ring of ill-conditioned eigenvalues.

Quantum Fourier transforms (QFTs) are essential primitives in quantum algorithms. While abelian groups admit efficient QFT circuits, with circuit size polynomial in the logarithm of the group order, efficient constructions are known for relatively few non-abelian families. We develop two new approaches to QFT circuit construction, based on Mackey theory and Clifford theory, respectively, and use them to show exponential improvement in circuit cost for specific group families. Using the Mackey-theoretic approach, we obtain explicit quantum circuits for the QFT over $\mathrm{GL}_2(F_q)$ that scale polynomially in $\log q$, rather than polynomially in $q$. Using the Clifford-theoretic approach, we obtain QFT circuits for wreath products $F\wr S_n$, whose cost depends on the cost of a QFT over $F$ and the size of its representation registers. This removes the restriction $|F|=\operatorname{poly}(n)$ required by previous generic constructions and can yield exponential improvements when $F$ itself has an efficient QFT. Together, these methods provide new systematic tools to construct QFTs for broad classes of finite groups.

We introduce a neural message-passing framework for decoding general concatenated stabilizer codes. Soft beliefs propagate bidirectionally across concatenation levels, and lightweight neural networks learn only to aggregate incoming messages. For the concatenated $[[15,7,3]]$ quantum Hamming code, the resulting decoder achieves substantially higher thresholds than the state-of-the-art bidirectional hard-decision decoder under both bit-flip and depolarizing noise. In particular, the depolarizing pseudo-threshold nearly doubles, from $6.5\%$ to $12.3\%$. For many-hypercube codes, a decoder fine-tuned on circuit-level errors in Knill's teleportation-based error correction can achieve lower logical-CNOT failure rates than their dedicated decoder, using a fixed number of message-passing iterations instead of extensive combinatorial search. Our framework provides a generic decoding tool for exploring the design space of concatenated codes, including non-CSS constructions, toward low-overhead fault tolerance.

Quantum Fourier transforms (QFT) for general groups were recognized to be fundamental already early in the field. A canonical example of non-abelian QFT for the symmetric group was outlined by Beals (1997). Later, a more detailed analysis of this algorithm was carried out by Kawano and Sekigawa (2016). In this paper, we revisit that construction. After a careful analysis, we revise their gate complexity to $\widetilde{\mathcal{O}}(n^{3.5})$ and circuit depth to $\widetilde{\mathcal{O}}(n^3)$. Moreover, we observe that their construction is not optimal in the choice of transversal elements, so we propose simpler realization of the symmetric group QFT.

Magic, or nonstabilizerness, is the resource that lifts Clifford circuits to universal quantum computation and has become a standard diagnostic of many-body states. For a state shared between two parties, however, a basic question has remained open: how much of the magic resides in the correlations between the parties rather than in their local bases? Isolating this nonlocal magic requires minimizing over all local bases, an optimization that has so far resisted exact solution. Here we solve it for the stabilizer fidelity: the nonlocal magic of every pure multiqubit state is the distance of its entanglement spectrum from the closest spectrum of Bell pairs. The same quantity governs an apparently unrelated task: a family of states universally embezzles entanglement under local operations and classical communication if and only if its nonlocal magic diverges. The deciding property is not the amount of entanglement but the way the entanglement spectrum spreads its weight across factor-of-two windows of rank, so that critical chains and random-singlet states, with identical logarithmic entanglement scaling, carry unbounded and vanishing nonlocal magic, respectively. Nonlocal magic thereby becomes an operationally meaningful property of quantum correlations, directly accessible to tensor-network simulations and, through entanglement spectroscopy, to experiments.

We experimentally study error mitigation and finite-shot sampling on superconducting quantum hardware under a constrained execution budget. The study combines calibration-aware qubit selection, circuit-depth scaling, zero-noise extrapolation, dynamical decoupling, readout-error mitigation, and repeated-shot estimation on an IBM Quantum processor. Experiments are organized across ideal simulation, noise-model simulation, and physical-device execution to separate sampling uncertainty from device-induced error. We investigate how mitigation performance changes with circuit depth, effective noise scale, qubit connectivity, and measurement budget, and quantify accuracy using expectation-value error, mean-squared error, statistical uncertainty, and mitigation gain. A fixed hardware-execution budget is used to evaluate shot allocation strategies and repeated measurements without relying on unlimited sampling. The resulting analysis provides a hardware-aware characterization of when mitigation improves expectation-value estimation and when finite-shot fluctuations offset the benefit of additional mitigation overhead. The implementation uses contemporary Qiskit and IBM Quantum Runtime workflows and is designed to provide reproducible experimental evidence for error-mitigation studies on current quantum processors.

In the field of cavity quantum materials, vacuum fluctuations of optical cavities are used for modifying ground-state properties of quantum materials without external driving. Here, one example is the van der Waals (vdW)/dispersion interaction in layered 2D vdW materials, where non-additive long-range correlations can dominate the interlayer binding. While cavity-induced changes of such interactions have been predicted and described using ab initio methods for molecular systems, no efficient description exists yet for extended materials. In this Letter, we close this gap by introducing a periodic formulation of the photon many-body dispersion (pMBD) functional within quantum electrodynamical density-functional theory (QEDFT). Applying this method with efficient $\textbf{q}$-point sampling to bilayer hBN and graphene, we predict cavity-modified stacking, increased equilibrium interlayer distances, and softened layer breathing modes with increasing light-matter coupling strength. Our results establish cavity vacuum fluctuations as a tuning knob for the structural properties of vdW materials.

Quantum sensors are specified by a headline sensitivity, yet applications also demand accuracy and reliability. The dominant limiter of one metric is often known, but no method resolves how interacting mechanisms combine into a signed, per-mechanism budget for each metric. We introduce a framework that computes a sensor's sensitivity, accuracy, and robustness from one open-system simulation and attributes each to its limiting mechanism. For a nitrogen-vacancy diamond ensemble the attribution inverts across metrics: dephasing limits sensitivity, the thermal ground-state shift limits accuracy, and optical leakage limits robustness. At identical sensitivity the recovered-field bias spans $8$ to $1500$\,nT, so tuning to sensitivity alone can miss the accuracy target by two orders of magnitude. The same modeling transfers to a cesium optically pumped magnetometer recording a human magnetocardiogram. As a digital twin, it predicts the gain from addressing each limiter, so sensors can be designed to the required metrics.

We prove recovery theorems for $\alpha$-$z$ Rényi divergences under normal unital positive maps between von Neumann algebras. Previous results in this setting required 2-positivity, while recent finite dimensional work showed that this assumption can be relaxed to mere positivity. Our proof uses sufficiency for JW*-subalgebras and $L^p$-spaces over them to characterize equality in the data processing inequality. As a further application of our methods, we solve a problem discussed by Haagerup and Stormer: Every conditional expectation of a von Neumann algebra onto a JW*-subalgebra factors through a conditional expectation onto the generated von Neumann subalgebra.

Phase-space methods are powerful tools for the treatment of Markovian open quantum systems: they map the reduced dynamics of a system S, in interaction with an environment E, exactly onto Langevin equations for c-number stochastic variables, as opposed to Heisenberg-Langevin equations for operators. Langevin equations provide analytical insight in key regimes and excel at handling strong nonlinearities and couplings, where other methods often falter. Extending phase-space methods to non-Markovian dynamics, however, has remained a long-standing challenge. Here we address this gap by applying phase-space representations to the full S+E system; integrating out the environmental degrees of freedom then yields a general Langevin framework for S that incorporates both deterministic and stochastic contributions from E. Normally ordered representations, such as the Glauber-Sudarshan P representation and its positive variant due to Drummond and Gardiner, lead to Langevin equations in which (i) non-Markovian effects emerge exclusively in the deterministic terms, via a memory kernel, and (ii) noise contributions vanish when E is initially in the vacuum state. To demonstrate the power of this framework, we address the paradigmatic problem of delayed coherent feedback, in which the system is driven by its own past state, and study its impact on the laser linewidth: we recover the narrowing observed well above threshold and predict an enhanced narrowing just above it. Crucially, the number of stochastic variables scales linearly with the system size, making the framework suitable for problems ranging from a few degrees of freedom to genuinely many-body systems. This opens the way to the systematic study of non-Markovian driven-dissipative quantum systems using the same analytical and numerical tools that have long made phase-space methods so successful in the Markovian regime.

We study classical string commitment over quantum channels with limited preshared entanglement. For noninteractive protocols, we determine the commitment capacity of a class of channels with input dimension $d$ that, at each use, sample a pair of classical random variables $(F,Z)$, apply one of the $d^2$ Heisenberg–Weyl operators indexed by $Z$ to the input, and deliver the transformed quantum system together with $F$ to the receiver. If $E$ is the available entanglement rate in bits per channel use, then the capacity is $\min\{H(Z|F),\log_2d+E\}$. This class of channels encompasses quantum erasure and depolarizing channels, as well as families of Pauli channels. Additionally, for interactive protocols, we show that the commitment rate cannot exceed $\log_2d+E$ bits per channel use, so that when $H(Z|F)\geq\log_2d+E$, interactive communication does not increase the capacity. As a consequence, for interactive protocols, we determine the capacity of the quantum erasure channel.

Nanoelectromechanical actuators operating at sub-100-nm gaps collapse through a pull-in instability set by competing electrostatic and Casimir forces. The quasi-static fold that bounds their safe operating range has been known in closed form for three decades, together with the Casimir ceiling above which no static equilibrium survives, which fixes the smallest gap a given stiffness and area can hold open against the quantum vacuum. That fold does not give the threshold reached from rest, its dependence on damping, or the design sensitivities of either. We train a physics-informed neural network in a rapidity coordinate that maps the movable pull-in pole to infinity, which keeps the residual bounded across the collapse threshold where fixed-step Runge-Kutta integration steps into unphysical states. Differentiating the trained surrogate returns pull-in-voltage sensitivities that match the closed-form fold to a relative error of $3\times10^{-6}$ and inverts a device specification to a gap of 97.036 nm at a target actuation voltage. Applied to the from-rest boundary, which carries no closed form once the damping is finite, it supplies the same sensitivities where no analytic root exists. We prove that this boundary is bracketed by two closed-form curves, that it is nondecreasing in the damping ratio, that it merges with the fold once the damping ratio exceeds $2^{-1/4}$, and that the gap closes as $(\tau_*-\tau)^{2/5}$. Numerically the merger already occurs at $0.396$, and the growth of the collapse time changes there from logarithmic to inverse square root. The classical-limit bound on the thermal Lifshitz derating is at the percent level, and the physical shift at these gaps lies orders of magnitude below it.

Resource-theoretic approaches to thermodynamics provide powerful, model-independent bounds on the efficiency of physical processes, because they do not rely on microscopic details of the environment. Whether such bounds can be approached by realistic dynamics generated by explicit system-environment interactions remains an open question. Photoisomerization, a fundamental molecular photoreaction, offers a concrete setting to examine this issue. We introduce a tunable microscopic model of a molecular photoswitch coupled to a structured vibrational environment, which interpolates continuously between Markovian and non-Markovian regimes. Resource-theoretic analysis predicts in particular that Markovian Thermal Operations achieve strictly lower yields than general Thermal Operations. We show that environmental memory lifts dynamical restrictions associated with Markovian thermal evolutions, thereby enlarging the set of transformations accessible to the microscopic dynamics. Approaching the thermal operation bound, however, depends on the microscopic coupling structure that generates this memory and directs the resulting dynamics towards the target transformation.

The Swing-UP of the quantum EmitteR population (SUPER) two-color pulsed excitation scheme allows for robust and close to 100% excitation of a two-level quantum emitter using only red detuned light. We analyze the underlying counterintuitive dynamics using a full quantum input-output description of the in- and outgoing light pulses for the case of two coherent free-space input pulses at realistic photon numbers. At the microscopic level, the SUPER mechanism exhibits its nonlinear three-photon Raman-type character, leading to a net photon-number change of $-2$ in one mode and $+1$ in the other, as was first guessed from cavity-enhanced model descriptions at low photon numbers. We confirm that in free space, a sufficiently high pulse photon number, much larger than one, is required to achieve high-fidelity inversion. To treat the large coherent-state amplitudes (photon numbers) relevant for SUPER, we extend the quantum input-output formalism to include a cumulant expansion approach. With an interaction-picture formulation, the few exchanged photons that govern the nontrivial dynamics enable direct full-quantum calculations in truncated Hilbert spaces, including treatments in a displacement frame and for initial Fock-state pulses.

We present a flip-chip-based sensing scheme to measure effective microwave losses associated with target materials for quantum technologies, without requiring any device fabrication on the material under test. Using this approach, we quantify the microwave losses of a strain-engineered Ge/SiGe quantum well heterostructure and investigate losses arising from its Ge substrate and intermediate layers. The quality factors of the fabricated microwave resonators agree with the losses of dielectric materials independently extracted from flip-chip sensing measurements. We further study the superconductor platinum silicon germanide (PtSiGe) prepared by thermal reaction with a deposited Pt film, finding high microwave losses that limit the suitability of the films studied here as the sole superconductor for high-quality resonator applications. By coating Pt with Nb prior to the reaction, we observe a substantial reduction in microwave loss and a nearly three-fold enhancement of the transport critical temperature. The temperature dependence of the microwave loss is consistent with gap inhomogeneity in both superconducting films. These results identify constraints on material choices, provide design guidance for microwave circuits on planar Ge heterostructures, and demonstrate a fast-turnaround testing method for new materials for superconducting quantum circuits.

Markovian open-system dynamics have widespread applications throughout quantum information science, including algorithmic state preparation. Their convergence is commonly quantified using the worst case global trace distance between the evolving and stationary states. However, this criterion can be unnecessarily stringent when only physically relevant observables are of interest. Here we introduce and study observable-specific mixing times. We prove that, for quasi-local, rapidly mixing Lindbladians, sums of geometrically local observables equilibrate in a time independent of system size, in contrast to the logarithmic dependence of global state mixing. This separation reduces the runtime of dissipative quantum algorithms, including quantum Gibbs samplers, for estimating quantities such as the Gibbs state energy and local order parameters, yielding an overall scaling that is linear in system size. Complementing this quantum result, we develop a quantum-inspired classical algorithm for estimating the same quantities. Its runtime is likewise linear in system size, but scaling exponentially in $\mathcal{O}\big(\log(1/\epsilon)^D\big)$, where $D$ denotes the spatial dimension of the lattice. We further analyse non-interacting Lindbladians over qudits, fermions, and bosons, demonstrating that locality of observables is not always necessary for a qualitatively faster mixing. Small-scale simulations of quantum Gibbs samplers reveal no large hidden constants in our asymptotic analysis and show that the theoretical predictions closely capture the finite-size dynamics.

Quantum Reservoir Computing (QRC) processes temporal data by retaining a memory of past inputs in the recurrent state of a quantum system, whereas a Quantum Extreme-Learning Machine (QELM) discards that memory, resetting the system at every step so that only the most recent input shapes the response. The two are usually treated as separate computational paradigms. We show that they are the two limits of a single architecture, connected by the input-encoding length, that is, the number of qubits overwritten with fresh data at each step. When a single qubit is re-encoded the system operates as a standard QRC, when the whole register is re-encoded it operates as a QELM, and intermediate lengths interpolate between them. The overwritten qubits hold the recent past in an explicit register, while the remaining qubits are never reset and carry older inputs forward in their evolving quantum state, so the encoding length redistributes memory between explicit and recurrent storage at fixed system size. Tuning the reservoir Hamiltonian and the evolution time with Bayesian optimization at each encoding length, we find that recurrent quantum memory is essential when a task must reach far into the past, and dispensable when the relevant history is short, where the memoryless reset limit already suffices. For every task the best reservoirs operate at the edge of chaos, where they perform as well as a densely connected reservoir with random all-to-all couplings of the same size, indicating that what temporal processing requires is the dynamical regime rather than the connectivity.

Nonlinear microwave resonators are a versatile tool in quantum information processing, enabling parametric amplification, continuous variable quantum computing, and engineered mode interactions. Many of these applications especially benefit from cubic nonlinearities enabling three-wave mixing; at the same time, they are limited by quartic nonlinearities giving rise to undesired Kerr effects. A recurrent challenge is therefore to engineer resonators with a finite cubic nonlinearity while suppressing quartic terms. Here, we investigate a superconducting resonator hosting two weak links fabricated from an aluminum-capped indium arsenide nanowire. We characterize the Kerr nonlinearity as a function of magnetic flux and gate bias, showing that it can be tuned to zero with either control parameter. Furthermore, we experimentally demonstrate three-wave mixing in a semiconductor-superconductor hybrid device, establishing nonzero cubic nonlinearity. An effective model based on Andreev bound states qualitatively captures the observed trends. Our results validate semiconductor-superconductor hybrid devices as a promising platform for tunable nonlinear superconducting circuits, with applications in parametric amplification, quantum control of bosonic modes, and engineering interactions between microwave modes.

Atom interferometers are among the most sensitive inertial sensors, yet deployment outside the laboratory is limited by vibration noise, conventionally mitigated by external sensors or bulky isolation. Here we demonstrate a hybrid inertial sensor which fuses an optomechanical resonator and an atom interferometer by exploiting the resonator's test mass as the interferometer's reference mirror. This allows for better correlation than with two separate sensors, whose unknown transfer function is replaced by the static response of one mechanical element. The resonator achieves a displacement sensitivity of $8.6\cdot 10^{-15}$ m/$\sqrt{\mathrm{Hz}}$ with suppressed 1/f noise and yields a minimum acceleration sensitivity of $1.1\cdot10^{-6}$ m/s$^2$/$\sqrt{\mathrm{Hz}}$ over a bandwidth extending from sub-Hertz to 2.5 kHz. Under ambient laboratory conditions the integrated system removes vibration-induced phase ambiguity for accelerations up to $50\cdot 10^{-3}$ m/s$^2$ and reaches the interferometer's technical noise limit, which a commercial force-balance accelerometer does not. Because the resonance-tracking readout is largely independent of the mechanical design, the architecture transfers directly to other precision sensing platforms.

The Energy Internet (EI) is a new concept aimed at enhancing the integration of renewable energy sources with the energy grid. Energy-efficient path selection in EI is NP-hard. This research presents an innovative Quadratic Unconstrained Binary Optimization (QUBO) and Ising Hamiltonian formulation for energy routing. The validation and scalability of the proposed formulation were evaluated by applying quantum-inspired annealing and quantum gate optimization to two case studies, a 9-node and a 30-node EI network. A comparative analysis was presented between classical optimization using the Dijkstra algorithm, optimization-based methods, and QAOA using the Qiskit Sampler Primitive, NumpyEigenSolver, and quantum-inspired annealing using the Ocean exact Solver, D-Wave Tabu Sampler, and D-Wave Simulated Annealing. Simulation results based on the proposed formulation agree with the exact solution, while the runtime of classical approaches is less than that of quantum approaches. However, the Simulated Annealing sampler offers the shortest runtime among all quantum methods.

We study the quantum transport of Dirac electrons in graphene subjected to a polyadic Cantor-structured electrostatic potential. Using the superperiodic potential formalism, we obtain a closed-form expression for the transmission probability. As the Cantor stage increases, the transmission spectrum evolves from a sparse set of superlattice resonances to a near-transparent regime, with the polyadic order setting the rate of this evolution. The angular response depends on the doping configuration, showing distinct behavior in the $n$–$n$–$n$, $n$–$p$–$n$, and Dirac-point cases. In the near-transparent regime, the transmission follows double-logarithmic scaling laws with respect to four independent control parameters: the Cantor stage, the potential height, the initiator length, and the angle of incidence. By combining these individual scaling relations, we establish a unified scaling law governing quantum transport. These results show that the hierarchical self-similarity of the potential governs the transport properties of such systems.

Changing a many-body system by one constituent is normally expected to produce only a vanishing correction to an intensive observable. Here we show that, above a critical dissipation imbalance, adding or removing one spin at fixed intensive controls switches the steady state of a dissipative collective spin between a phase-averaged ring and a south-polar fixed point. Unlike previous one-spin sensing through dark-state interference, parity here determines whether the Dicke ladder samples an interior zero of the nonlinear jump amplitude. The integer-spin ladder samples this zero, making Dicke states with m<0 transient, whereas the half-integer ladder misses it and remains a single recurrent class. Exact finite-size steady states show that exponential competition between stationary weights amplifies this microscopic connectivity difference, yielding a first-order dissipative phase transition confined to the odd-N sequence. Multisector one-spin loading and state-unresolved removal confirm the switch, while the exponentially increasing switching time reflects the metastable isolation of the competing macroscopic basins. Our results establish representation-lattice sampling as a route to phase control, suggesting parity-based detection of single-spin addition or removal.

Quantum federated learning enables collaborative model training across quantum devices without sharing raw data, and it faces the data and hardware heterogeneity inherent to noisy quantum devices. Utilizing the quantum geometric tensor is a natural remedy, yet pure-state approaches and diagonal approximations discard the correlations that encode parameter incompatibility. To address this, we extend the parameter-space geometry to the mixed states that noisy clients actually prepare. The real part of the resulting mixed-state geometric tensor is the Bures metric, which measures how fast the physical state changes under parameter variation, and the imaginary part is the mean Uhlmann curvature, which quantifies the incompatibility of estimating multiple parameters simultaneously. Accordingly, we employ the Bures metric as a local preconditioner and use the mean Uhlmann curvature to develop an achievable-precision aggregation rule that dynamically down-weights unreliable clients. Furthermore, we establish theoretical guarantees by proving a convergence theorem and a variance-dominance proposition. Empirical evaluations on a trapped-ion quantum emulator demonstrate that the proposed method maintains high accuracy across diverse device-heterogeneity conditions and outperforms standard federated averaging, whose accuracy degrades under strong noise.

In this work, we develop a variational imaginary-time evolution (ITE) framework based on polynomial filtering, derived from an operator-level action principle, which yields an optimized non-unitary projector expressed as a polynomial in the Hamiltonian. Starting from a single-ancilla, first-order imaginary-time update defined by a Taylor expansion and Trotter-Suzuki (TS) decompositions, we show that replacing these approximations with alternative variational formulas substantially improves both accuracy and stability at larger time steps, leading to up to an order-of-magnitude enhancement in the final success probability. We further derive rigorous error bounds that depend only on static properties of the Hamiltonian, providing practical guidance for selecting the simulation time step. Benchmarks on the transverse-field Ising model demonstrate faster convergence to the ground-state energy and improved robustness compared to standard TS–Taylor ITE, highlighting variational polynomial filtering as a practical route to higher-fidelity ground-state preparation on near-term quantum devices.

Crystal-phase quantum dots (CPQDs)$\unicode{x2014}$quantum dots in nanowires defined by crystal structure rather than material composition$\unicode{x2014}$constitute the only platform capable of fabricating quantum-dot arrays with the ultimate precision of a single atomic layer. This intrinsic control yields perfectly aligned quantum dots with atomically sharp interfaces, providing a unique pathway toward scalable quantum-dot-based photonic quantum technologies. To date, CPQDs have been studied primarily in binary semiconductors, such as InP and GaAs, where their emission linewidths are typically in the meV range, thereby limiting their technological potential. Here, we report, for the first time, CPQDs in AlGaAs nanowires and show bright single-photon emission with linewidths as narrow as 61 $\mu eV$ and low background emission, demonstrating optical quality well beyond typical CPQDs. We attribute this performance to a type-I band alignment, as suggested by an exciton lifetime of 1 ns, significantly shorter than that typically observed in type-II CPQDs. Additionally, we observe an exciton fine-structure splitting and a Zeeman splitting, as commonly observed in standard type-I self-assembled quantum dots.