Papers

Local quantum interactions generate dynamics in an exponentially large Hilbert space, yet locality and entanglement restrict the information that can spread and accumulate. Bounds on propagation and entanglement growth, together with tensor networks, exploit these restrictions to discard information unnecessary for describing the evolution. This leads to a sharper question: how much information must any low-rank representation retain? Here we determine these limits, up to logarithmic factors, for short-range interactions. For time-independent evolution, the optimal rank obeys $\log D=\widetilde O(t+\sqrt{\log(1/\epsilon)})$, with matching lower bounds fixing the accuracy exponent $1/2$; for arbitrary driving, matching fixed-time bounds instead give $2/3$. Correspondingly, the corresponding dynamical entanglement spectra exhibit distinct small-$\alpha$ Rényi laws, $\alpha^{-1}$ and $\alpha^{-2}$. In one dimension, the static limit is constructively attained by an explicit MPO algorithm, with an analogous extension to Liouvillian dynamics. Together, these results determine the irreducible information required to represent local quantum evolution and uncover distinct entanglement structures in static and driven dynamics.

The training efficiency of Variational Quantum Algorithms (VQAs) is dictated by the geometry of their loss landscapes, which can be formally analysed by mapping these functions to random fields on manifolds. Instead of VQAs, we can then directly study the corresponding random fields, in our case, the Wishart Hypertoroidal Random Fields (WHRFs). We are mostly interested in the distribution of critical points (especially local minima) of WHRFs. For this purpose, the Kac-Rice formula is presented, reformulated, and simulated. The findings identify a phase transition in the distribution of local minima. Beyond a specific threshold, local minima concentrate near the global minimum in function value, meaning that even local minima are good approximators of the global one. The threshold is governed by the ratio between the problem Hamiltonian degrees of freedom and by the number of independent parameters in the VQA. Since the degrees of freedom parameter scales exponentially, we propose symmetry reduction operations to lower the degrees of freedom. This mathematically reduces the dimension, scaling down the required parameter threshold and enabling to solve bigger problems.

Real-time waveform generation supports dynamic quantum circuits without pre-storing complete waveforms for every execution path. However, long-lived distortions in flux-control lines degrade gate fidelity, requiring compensation to account for the actual pulse history. A frequency-domain inversion and time-domain fitting method is proposed for resource-efficient real-time flux distortion compensation. The method fits the reconstructed compensation impulse response with a compact hybrid infinite impulse response (IIR) and finite impulse response (FIR) filter. Look-ahead parallelization enables this filter to process synthesized waveforms at 1.2GSa/s on a field-programmable gate array (FPGA). Two-qubit cross-entropy benchmarking shows that real-time IIR filtering achieves a median controlled-Z Pauli fidelity close to the software-reference value of 99.57%. Numerical analysis and FPGA synthesis indicate approximately logarithmic growth in hardware resource use with compensation timescale. Extending compensation from microsecond to hundred-microsecond timescales increases look-up table (LUT) and digital signal processing (DSP) resource use by only about 14% and 4%, respectively, while maintaining a relative arithmetic error below $10^{-4}$. This work provides a scalable hardware foundation for high-fidelity flux control in dynamic superconducting quantum circuits.

Numerous quantum devices require lasers strictly locked to atomic transitions. Atom-filtered lasers (AFLs) are considered a leading candidate for quantum device laser sources due to their ability to self-align to atomic transitions. However, the sub-GHz sharp transmission spectra of conventional atomic filters impose constraints on both laser miniaturization and output stability. Herein, we demonstrate a micro Faraday anomalous dispersion optical filter ({\mu}FADOF) operating within the extreme hyperfine Paschen-Back regime, generating a 7.5 GHz flat-top transmission window. By integrating this filter, the miniaturization bottleneck of the AFLs is overcome, achieving a 30-fold volume reduction to a compact package volume of 75 mL. Simultaneously, investigations into the optical self-feedback characteristics of the {\mu}FADOF reveal a stable operating regime, where the optical self-feedback of the atomic filter acts as a stabilizing mechanism, enabling the laser to achieve a power instability of 9 x 10^-6 at 1 s and 3.2 x 10^-5 at 8400 s. The optical frequency standard based on this 75-mL AFL achieves a further improvement in long-term frequency stability to 3 x 10^-13 at 10000 s and maintains turn-key operation under environmental shocks, highlighting the critical role of this laser in the development of deployable quantum devices.

Quantum cloud computing, delivered through the quantum-as-a-service (QaaS) model, provides access to quantum computing resources. However, applying uniform time-based pricing across fundamentally heterogeneous quantum resources significantly complicates task orchestration, particularly when addressing the tradeoff between execution costs and system performance. While heuristic methods rely on predefined scheduling rules, classical deep reinforcement learning (DRL) models may require more trainable parameters in this setting. Motivated by the potential of parameterised quantum circuits (PQCs) as compact function approximators, we propose QRLQ, a cost-delay-aware quantum cloud scheduling framework integrating PQCs with a dueling double deep Q-network (D3QN) to dynamically account for both cost and delay. Our simulation results show that QRLQ achieves lower mean cost and delay than the heuristic baselines, achieving a 5-11% lower mean cost relative to availability-based and rotation-based heuristics and reducing mean delay by 17% and 82% relative to the strongest and weakest heuristic baselines, respectively, while retaining execution fidelity within 2% of a fidelity-greedy policy. Compared with the classical DRL baseline, QRLQ achieves comparable scheduling performance while using 72% fewer trainable parameters. This work explores the feasibility of using QRL for task orchestration in quantum cloud environments and demonstrates its potential for cost-delay-aware quantum resource management.

Blockade, a phenomenon in which one particle hinders the transport of another, constitutes a core research topic in mesoscopic and microscopic physics. Benefiting from the unique single-particle characteristics, it underpins versatile applications spanning from quantum computation to quantum metrology. Nevertheless, in the context of quantum energy?storage devices, i.e., quantum batteries (QBs), blockade triggered by the intrinsic level splitting is in turn detrimental to energy accumulation. Here we propose an antiblockade charging protocol enabled by deliberately engineering a bright-dark interaction. Rooted in a manifold of equally-spaced dressed-dark states, this elaborate configuration opens up a new charging channel facilitating an antiblockade energy flow and outperforms the Rabi-split blockade design with at least a 20-fold enhancement in energy storage. Additionally, we further illustrate the achievement of superextensive (quadratic) charging characteristic by operating the system in the bad-cavity limit. In view of its inherent generality, our scheme offers a universal and feasible pathway toward high-performance quantum energy architectures.

Long-range interacting quantum systems exhibit interesting phenomena beyond the nearest-neighbours regime. Such interactions can reach further separated particles and change the behaviour of many-body correlations. Here, we analyse their structure in the antiferromagnetic long-range interaction transverse field Ising model with power-law interactions decaying as $1/r^{\alpha}$. We examine the spatial behaviour of basis-independent total multipartite correlations, called sector lengths $S_k$, of its ground state in the vicinity of critical points for different interaction exponents $\alpha$ and fixed system size. These correlation functions were shown to indicate entanglement and the existence of local realistic models, allowing us to make claims about the Bell nonlocality and entanglement in the system. We further investigate them in the context of non-stabiliserness, often referred to as quantum magic, which holds information on their classical simulability and usefulness for quantum computation. We evaluate Rényi stabiliser entropy near and outside the criticality and show that cumulative magic, up to the critical point, increases with $\alpha$ for all of the examined system sizes. Our results provide new insights into the interplay between the long-range interactions, observable non-classical phenomena and their classical simulability.

Absorption spectroscopy identifies molecules by detecting frequency-dependent optical loss, and its fundamental limit is a quantum channel-discrimination problem. In this work, we develop a general framework for characterizing the ultimate quantum limit of molecular absorption spectroscopy without collective measurements: we formulate it as an asymmetric quantum hypothesis testing task between different absorption channels. Using a semidefinite-programming formulation, we construct optimal probe states and compare them with coherent-state photon counting, Fock states, and two-mode squeezed vacuum probes. We introduce a random-loss channel model for imperfectly known background transmission, reflecting the fact that a blank experiment need not return all incident photons due to scattering, solvent absorption, or collection losses. Our results show that optimized non-classical probes can substantially outperform conventional laser spectroscopy, and that the advantage is robust to realistic baseline random loss. % In multi-frequency spectroscopy, the optimization also determines how photons should be allocated across absorption lines, revealing an additional resource-allocation advantage beyond single-mode state engineering. We illustrate our framework using infrared detection of 4-nitrophenol against chemically relevant comparison molecules, showing how quantum channel-discrimination methods provide constructive performance limits for molecular spectroscopy under realistic photon constraints.

We provide an equitable partition that gives an exact, minimal representation for the graph Cartesian product formed from quantum-like bits that preserves the relevant spectral and topological properties. We show that this result follows from the fact that the operations of taking the Cartesian product of graphs and constructing equitable partition of the graphs commute. Numerical simulations illustrate the preserved emergent eigenstates in the reduced structures. Additionally, we provide a construction of the minimal structure without passing through the Cartesian product. Finally, we frame quantum-like structures in the language of topology and fibrations.

Cryogenic capacity is a key bottleneck in the scaling of superconducting quantum processors, critically impacted by control wiring. Currently, wiring architectures are often designed following a small set of "best-practice" heuristics, little changed since they emerged for early, small-scale systems, and not rigorously evaluated for wider contexts. Here, we adopt a whole-system numerical modelling approach and present a systematic optimisation for the coaxial wiring design of a superconducting quantum processor. We identify optimised configurations that substantively outperform conventional designs in device temperature, noise burden, qubit capacity and other practical metrics. Importantly, our analysis delivers varied outcomes for different system contexts and operating regimes, illustrating the benefits of a systematic approach when there is no universal solution. Our results evaluate and sometimes challenge conventional wisdom in relation to design factors such as the utility of 0dB attenuators. We also use a wide exploration of cable configurations—directly enabled by our holistic and flexible numerical modelling approach—to develop more rigorously supported general principles for future cryogenic system design, based on a new conceptual framework to describe attenuator cascades that draws on analogies to low-noise amplifier chains. Our approach, design outcomes, and generalised analyses should also be readily applicable to other cryogenic quantum computing platforms. Finally, we support ready adoption of this approach through a web-based graphical tool which streamlines the analysis of the proposed framework under different contexts. Our results illustrate how our approach can help maximise the available computational resources of quantum processors at all system scales.

We establish the quantum channel Stein lemma at every fixed type-I error tolerance in $(0,1)$ and prove an exponential strong converse under arbitrary adaptive strategies. For any finite-dimensional channel pair, the optimal type-II exponent equals the regularized channel relative entropy and is attained by parallel strategies. When this divergence is finite, every strictly larger type-II rate forces the probability of accepting the null hypothesis to decay exponentially, uniformly over strategies and quantum memories. The proof rests on a uniform Stinespring approximation: tensor powers of the null dilation are approximated by tensor powers of the alternative dilation after applying an auxiliary linear map to the environment. The operator-norm error is exponentially small under a squared-norm bound at any rate above the regularized relative entropy. We construct the approximation from a weak testing bound by iterative rate reduction and a fixed-block tensor expansion with an exact residual. It implies right continuity at order one of the regularized sandwiched Rényi channel divergence, which yields the adaptive converse through the channel chain rule. We also obtain a sharp hockey-stick threshold and a subchannel smoothing asymptotic equipartition property for fixed and subexponentially vanishing diamond-norm errors.

Learning an interacting many-body Hamiltonian at the Heisenberg limit generally requires control that preserves local information for evolution times of order $1/\varepsilon$ to attain $\varepsilon$ precision. To achieve this, existing protocols often rely on trusted many-qubit operations or increasingly rapid control pulses, creating a precision barrier when gates involve unknown multi-qubit interaction or have finite duration. We show that neither resource is necessary for geometrically local Hamiltonians. Our protocol applies only static single-qubit fields, whose strength is independent of system size and grows polylogarithmically with $1/\varepsilon$. These fields generate emergent prethermal symmetries that suppress thermalization for the entire learning experiment while retaining informative symmetry-preserving dynamics. On a $d$-dimensional lattice of $n$ qubits, this enables learning every coefficient to accuracy $\varepsilon$, with failure probability at most $\delta$, using total evolution time $\mathcal{O}(\log^d(1/\varepsilon)\log^2(n/\delta)/\varepsilon).$ Thus, our learning protocol attains the information-theoretically optimal \(1/\varepsilon\) dependence up to polylogarithmic factors using product-state preparation, single-qubit measurements, and non-adaptive experiments. More broadly, our results establish emergent prethermal symmetries as a resource for quantum learning, opening a route to Heisenberg-limited characterization of many-body systems where fast or trusted many-qubit control is unavailable.

Full tomography of a generic many-qubit quantum state requires exponentially many copies, while suitable structural constraints can make reconstruction sample-efficient. Existing approaches exploit, for example, limited entanglement structure, low magic, or constrained state-preparation circuits. Here we consider a class of mixed states that can simultaneously exhibit extensive entanglement and extensive magic. Specifically, we introduce Clifford-encoded block-product (CEBP) states, obtained by applying an unknown global Clifford unitary to a tensor product of arbitrary mixed states supported on unknown blocks of bounded size. We show that, for a fixed block size, CEBP states can be reconstructed using polynomially many copies by exploiting Clifford-preserved Pauli correlations to recover the latent structure and reduce the remaining problem to local tomography. Our result demonstrates that sample-efficient tomography can arise from bounded complexity in a latent frame even when the physical state is highly entangled, highly magical, and mixed, and suggests complexity modulo structured transformations as a broader organizing principle for quantum-state learnability.

Weak, non-covalent interactions such as electrostatics, induction, and dispersion are commonly treated as distinct physical mechanisms, often using separate models and approximations. Here, we present a unified quantum-electrodynamical framework in which all weak interactions between neutral or charged subsystems emerge from a single interaction Hamiltonian and are expressed entirely in terms of electromagnetic Green functions. Starting from macroscopic QED in arbitrary linear environments, we derive compact master formulas that generate permanent electrostatic, mixed induction, and fully induced (dispersion) interactions on equal footing. Monopoles, dipoles, and quadrupoles are treated consistently within the same multipole expansion, leading to a common structural form in which all interaction channels are obtained from contractions of multipole moments and response functions with Green tensors. Environmental effects enter universally through dressed Green functions. The standard non-retarded free-space limits, including Keesom, Debye, and London/van der Waals interactions, are recovered as a consistency check of the formalism. Beyond this validation, the formulation shows that once the general expressions are established, different physical scenarios, such as interfaces, confinement, or polarisable continua, can be treated by direct substitution of the corresponding Green function, without reformulating the interaction for each case. This elevates Green functions to a universal organising principle for weak interactions in complex environments.

We prove quantum soundness of the total-degree diagonal line-vs-point test using the individual-degree soundness theorem of Ji, Natarajan, Vidick, Wright, and Yuen. A random change of coordinates yields projective polynomial decoders of total degree at most $md$. The uniform-line slice of the test bounds the weight of outcomes of degree greater than $d$, which are removed by a common relabeling. This reduction does not yield a dimension-independent soundness bound: the $\operatorname{poly}(m)$ dependence of the individual-degree theorem persists, as discussed in Section 1.2 of arXiv:2009.12982.

Clifford circuits acting on product magic states provide a compact ansatz exhibiting extensive magic, volume-law entanglement, and even classically hard sampling under standard complexity assumptions. Here, we efficiently recover its hidden product subsystems from two-copy Bell sampling. Quadratic relations between Bell samples determine the irreducible blocks after removing Pauli stabilizers, and binary linear algebra constructs a Clifford disentangler. For logarithmic-size blocks, approximate learning of the full state is efficient whenever the state remains inverse-polynomially separated from acquiring additional Pauli stabilizers. We efficiently learn $n$-qubit states prepared by random $T$-doped Clifford circuits with $T$-gate density below one via $O(n^2)$ Bell samples, and disentangle hidden product blocks in Clifford-augmented matrix product states. For unitary learning, we exactly learn $T$-depth-one circuits using $O(n^2)$ queries. Finally, we rule out pseudorandom states and unitaries with a product bipartition hidden by Clifford circuits.

Many inference problems are constrained from two sides: forward information and a second constraint on outcomes. Dual Boundary Condition Inference (DBCI) multiplies them and renormalises. The rule is not new: it is the product-of-experts form and the unit-exponent member of the logarithmic-pooling family. The paper contributes a classification and reducibility characterisation. The algebra does not fix the exponent at which the inputs combine: given the statistic log p_fwd + log p_bwd, which already builds in the product form, maximum entropy supplies the family (p_fwd p_bwd)^lambda and selects no member. If the inputs are read as two equally weighted opinions, three requirements select lambda = 1/2: unanimity preservation, consistency under a common Bayesian update, and minimal symmetric Kullback-Leibler divergence. If they are read as separately applied factors, two requirements select lambda = 1: a neutral second input must leave the first unchanged, and an update to one input must pass through unchanged. For a rank-one intermediate projective measurement, the Aharonov-Bergmann-Lebowitz (ABL) rule realises this form with no extra parameter. Every positive exponent orders outcomes identically, so the choice is invisible to picking the likeliest outcome, but not to scoring a class by total mass. Under the relevant identifications, the same product form gives Bayes' rule, while a final effect proportional to the identity returns the ordinary forward Born probabilities. The second result is a Two-Boundary Reducibility Criterion: DBCI factors through the forward boundary exactly when the effective backward boundary, up to positive rescaling, does. So a fixed prior or model-fixed structural constraint adds no distinctions between cases sharing the same forward boundary, though it may encode substantial information and still materially affect the result.

We consider the dynamic Schrödinger bridge problem on a finite state space and exploit its Markov structure to decompose the problem into an endpoint coupling and a collection of conditional Markov bridges. To sample from the conditional bridges, we develop a quantum Gibbs sampler based on quantum walks on the bridge path space. Under uniformly positive transition probabilities, we derive a spectral-gap bound and provide an explicit procedure for preparing the initial state. Compared with the update bounds of the corresponding classical Gibbs sampler, our quantum walk-query complexity improves the dependence on the time horizon $T$ from quadratic to linear. For the endpoint coupling, we adapt a quantum box-constrained Newton method to compute the Schrödinger potentials, improving the matrix-scaling complexity, at fixed accuracy, from quadratic to $N^{3/2}$ in the state-space size $N$. Finally, we show that exponential reweighting extends both the Schrödinger bridge formulation and the Gibbs spectral-gap estimate to models with additive running costs.

We report the first experimental observation of resonantly enhanced propagating phonon transport induced by magnon pumping in a ferromagnetic/piezoelectric bilayer. Surface acoustic waves (SAWs) generated in a 128$^{\circ}$ Y-cut LiNbO$_3$ delay-line device resonantly excite magnetization dynamics in an adjacent Co film through magnetoelastic coupling. The enhancement of the transmitted acoustic signal occurs exclusively when the SAW frequency satisfies the ferromagnetic resonance condition predicted by the Kittel dispersion, providing a direct experimental fingerprint of resonant magnon-phonon coupling. A systematic comparison between the Co/LiNbO$_3$ bilayer and the bare LiNbO$_3$ substrate demonstrates that the observed transmission enhancement originates solely from the dynamic interaction between propagating phonons and coherent magnetization precession. Furthermore, measurements performed at different SAW harmonics reveal that only the harmonic satisfying the FMR condition produces a measurable enhancement, confirming the frequency-selective nature of the phenomenon. These findings establish an efficient mechanism for transferring energy from magnons to propagating phonons and provide a new strategy for actively controlling coherent acoustic transport in hybrid spintronic, straintronic, and quantum phononic platforms.

Due to progressing miniaturization, material fatigue is expected to gain importance on microscopic scales. Nevertheless, most non-destructive testing techniques are optimized for macroscopic scales. Therefore, new approaches applicable to miniaturized samples need to be explored. High spatial resolution imaging of a material's magnetic stray field enables sensitive detection of microstructural changes due to the local interplay of magnetic properties, strain, and defects. Up to now, this approach has rarely been used for materials testing since high-resolution magnetic sensing is traditionally challenging. Novel quantum sensing techniques offer the potential to close this gap. One of the most prominent quantum sensors, the nitrogen vacancy center in diamond, is investigated for non-destructive testing applications within the scope of this work. An experimental system based on a widefield sensing approach was developed to image magnetic stray field distributions within seconds to minutes over areas up to 1 x 1 $mm^2$. Magnetic sensitivities below 10 $\mu$T/$\sqrt{\text{Hz}}$ and a spatial resolution of 1-2 $\mu$m were achieved. The technique offers high mechanical stability, which is crucial for non-destructive testing applications. Comparison with magneto-optical Kerr effect measurements showed that the magnetic field maps are strongly correlated with the material's surface domains while containing additional information from deeper inside the sample. Characteristic changes in the magnetic stray field distribution were detected in an electrical steel sample after cyclic loading. A potential marker for early fatigue damage was deduced from the splitting gradient distribution, while 2D Fourier transform analysis provided additional insight.

Reservoir computing requires not only long memory, but also memory distributed over the timescales relevant to a given task. In most quantum reservoir computing architectures, however, the memory profile emerges from intrinsic dynamics and cannot be directly engineered. Here we introduce a waveguide-QED quantum reservoir in which coherent memory return is controlled by the coupling geometry. The reservoir consists of a driven Kerr-nonlinear resonator coupled to a one-dimensional waveguide at spatially separated points. An unmeasured propagating field carries information about past inputs and coherently returns it to the resonator after a finite propagation time, forming a non-Markovian feedback channel without intermediate measurement or classical reinjection. Delay-resolved memory benchmarks reveal two complementary functions: waveguide propagation determines when past information returns, whereas Kerr dynamics convert the returned field into nonlinear temporal features accessible through a linear readout. NARMA-$n$ prediction shows that the optimal feedback delay shifts systematically with task order and approximately tracks the explicit input-product lag. These results establish coherent delayed feedback as a mechanism for engineering task-relevant memory in quantum reservoir computing.

We investigate how particle-hole symmetry, quantum interference, and tunnel barriers shape thermodynamic uncertainty relations in chaotic Andreev billiards. Using random-matrix theory and the Mahaux-Weidenmüller scattering approach, we study charge conductance and shot noise across the four Altland-Zirnbauer symmetry classes, from the single-channel extreme quantum limit to the multichannel semiclassical regime and from ideal to opaque contacts. We characterize thermodynamic precision through two complementary ensemble observables: either by averaging the sample-resolved noise-to-conductance ratio, or from the separately averaging noise and conductance. Their pronounced discrepancy in the extreme quantum regime reveals the non-self-averaging character of mesoscopic transport and persists over a broad range of barrier transparencies. For ideal contacts, the first provides a sensitive fingerprint of the Altland-Zirnbauer symmetry class. In the opaque regime, this hierarchy changes. Despite these strong symmetry- and barrier-dependent effects, the standard thermodynamic uncertainty relation remains satisfied throughout all regimes investigated. Our results establish thermodynamic uncertainty as a symmetry-sensitive probe of universal transport in chaotic normal-superconducting systems.

Employing problem-specific non-universal Variational Quantum Circuits aligned with a suitable state preparation has become a standard approach to counter the difficulty in training universal ansätze. However, due to their non-universality, diagnosing their reachability and trainability remains reference-state-specific. In this work, we establish the equivalence of maximal reachability and generic reachability over arbitrary reference states as a consequence of the principal orbit-type theorem. Thereafter, assuming that the global minimum of the cost function is achieved on a subset that can be described as the image of a smooth function, we derive necessary and sufficient conditions for non-zero probability of reachability under generically sampled reference states. Furthermore, when the solution set is assumed to be realised through a real analytic map that embeds a solution manifold, we show that local surjectivity is generically obtained on the entire solution manifold if it is attained at a single point. As a practical design rule, the need for local surjectivity automatically translates to a necessary dimensional criterion: reachability requires the target set's topological dimension to be at least as large as the co-dimension of the generic orbit. Numerical simulations show that finite-depth optimisation consistently fails when the dimensional obstruction applies, while unobstructed cases show improved convergence.

Quantisation is considered as an action of classical point operators on field states at the Planck scale of the phase space. Emphasis is placed on the sequence of physical variables. A "state language/Dirac notation" for classical mechanics is introduced; in many cases, it replaces the principle of stationary action for conservative systems. Observed classical and quantum dynamics are considered as different vectorisations of the free semigroup contribution of time. There is a dream of describing classical dynamics as complex transformations of state vectors over such a free semigroup, rather than solving differential equations. The transition from the alphabet to states, from states to state functions, and from state functions to measurable quantities is managed by projectors. An attempt is made to provide a derivation of the Legendre transformation. The trivial multiplication of the potential energy by the wave function in the coordinate representation and its non-trivial operator action in the momentum representation are obtained without a Fourier transform nor the Planck scale. The quantisation procedure is divided into two stages: first, the action of point-like classical operators on field functions; and second, accounting for the physically finite scale of the Planck length against the backdrop of the possible infinitesimality in the classical phase space. The concept of an angle between states is introduced, defining the measure of "quantumness". The free semigroup time contribution is studied in the context of the Born rule.

In complex systems theory, there are different ways to describe a system in terms of information, such as emergence (Shannon entropy), self-organization, and com- plexity. These measures provide information about the dynamic behavior of a complex system. We study the differences in entropy and complexity for many-body systems undergoing a transition from a regular to a chaotic regime. To do this, we analyze the eigenvectors of the 48 Ca nucleus for different quadrupole-type two-body interactions. We obtain the eigenvectors by diagonalizing the two-body Hamiltonian for 48 Ca us- ing the Antoine code. We then calculate the entropy and complexity for the different quadrupole-type interactions. The differences found in information entropy and com- plexity are clear when comparing a regular system with a chaotic one. We find that the complexity of the regular and chaotic states of 48 Ca shows differences associated with its internal interactions.

A central problem for surgery with quantum Low-Density Parity Check (LDPC) codes is the design of auxiliary systems which measure large sets of logical operators in parallel, while preserving sparsity and fault distance. We introduce a very general method for designing surgery gadgets which are 'high rate', meaning that the number of operators measured in parallel is large in comparison to the size of the auxiliary system. Given an arbitrary initial $[[ n, k, d ]]$ quantum LDPC Calderbank-Shor-Steane (CSS) code, and an arbitrary subcode of size $\mu \leq n$ that contains $t \leq k$ logical qubits, the method produces a sparse high-rate surgery gadget with size $\mu (\log\mu)^{O(\log\log \mu)}=\mu^{1+o(1)}$ which measures all $t$ logicals in the subcode. The space overhead is asymptotically optimal up to subpolynomial factors, as the lower bound is $\Omega(\mu)$. This gadget is produced in time polynomial in $\mu$. When logical measurement is performed using these surgery gadgets, the phenomenological fault distance is at least $d$ when performed for $d$ rounds. Our main result comes from relating surgery gadgets with relative cosystolic expansion to linear Probabilistically Checkable Proofs of Proximity (PCPPs), which allow a randomised verifier to probabilistically verify the input to a linear circuit, using only oracle access to the input and a claimed proof.

The decoder is a critical component of a fault-tolerant quantum computer, computing corrections based on parity-check measurements performed throughout the computation. A soft decoder supplements its output with a confidence score which, when used alongside post-selection, can substantially improve logical performance. We introduce a soft beam search decoder for quantum low-density parity-check codes that uses internal decoder data as a confidence metric, removing the need for extra computation. We perform circuit-level simulations of five quantum LDPC codes relevant for superconducting and trapped ion architectures equipped with our global soft decoder and we obtain up to $580\times$ logical-error suppression at a physical error rate of $10^{-3}$ while rejecting only $0.1\%$ of shots. Then, we simulate an error detected measurement, which is a core logical operation of the walking cat architecture, using a streaming version of soft beam decoder and we achieve up to $210\times$ error suppression while increasing the rejection probability by only $0.5$ percentage points. Finally, we revisit recent quantum LDPC code memory experiments on trapped ions, demonstrating that our soft decoder doubles the logical qubit lifetimes at the price of a mean rejection rate of $2.6\%$–$5.6\%$ per syndrome round, bringing all five codes into the beyond-breakeven regime.

Non-Poissonian photon statistics are usually traced to nonlinear interactions, nonclassical states, or engineered reservoirs. Here we show that measurement-based feedback can be alternatively deployed to control the Poissonian character of the measurement statistics in an externally-driven linear cavity. Each photon detection triggers a weak displacement operation whose phase determines how the feedback interferes with the coherent cavity field, resulting in a significant cavity response. Full counting statistics and two-time photon correlations show that the feedback phase controls the sign and strength of the induced correlations, continuously tuning the emission statistics between super- and sub-Poissonian regimes. At generic phases, the Mandel parameter responds linearly to the feedback amplitude, whereas at specific phases, the leading response becomes quadratic. The same phase dependence is also found in higher-order cumulants of the emission statistics. These results establish measurement-based feedback as a route to controlling photon statistics in otherwise linear driven-dissipative systems.

Quantum error-correcting codes require that the environment cannot distinguish relevant error processes acting on different codewords. In practice, residual Zeeman, Stark, or anharmonic interactions shift the underlying states, making errors distinguishable and weakening the conditions for perfect recovery. We study this effect with an analytically solvable four-level model and a canonical spontaneous-emission noise model for atoms and molecules. Distinguishability raises the effective Kraus rank of the noise channel, lowers the recovered fidelity, and sets an operational checking time that shortens as the frequency separation between the emitted photons increases. We find that rapid syndrome checking suppresses the buildup of distinguishability and quantify how fast one needs to check to restore near-perfect recovery. Error distinguishability is thus a practical limitation of monolithic error correction, and our analysis identifies fast syndrome extraction as a route to mitigating it.

We study measurement-only dynamics in an interacting spin-1 chain, using forced, normalized local projections rather than Born-rule-sampled measurement outcomes. Starting from the nearest-neighbor (NN) Affleck-Kennedy-Lieb-Tasaki (AKLT) Haldane symmetry-protected topological state, we show that competing local projectors drive this order toward three distinct dynamical phases: a featureless topologically trivial product state, an explicitly dimerized valence-bond-solid state, and a topologically trivial next-nearest-neighbor (NNN) AKLT state consisting of two interwoven Haldane chains. Using matrix product state and exact statevector simulations, we identify continuous transitions among these phases and characterize them using nonlocal string order parameters, local dimer order, and entanglement scaling. For the NN-NNN AKLT model, finite-size signatures are consistent with an intervening extended critical regime rather than a single direct transition. These results extend studies of monitored topology to a bosonic SPT and show that local projections can control both topological and valence-bond-solid order.