Papers

Large-scale fault-tolerant quantum computing (FTQC) will require quantum-classical interfaces (QCIs) that orchestrate real-time decoding over thousands to millions of logical qubits simultaneously. To scale FTQC systems, complex decoding resources must be shared between logical qubits, creating resource contention bottlenecks in the QCI. Mitigating this contention via optimal resource allocation remains an open problem. Lightweight predecoding techniques can reduce decoder utilization and average latency, both of which ease contention for shared decoding resources. To date, both decoder allocation and predecoding work is limited to the surface code. As focus shifts towards general qLDPC codes, slower decoding exacerbates resource contention, while code complexity precludes manual predecoder design. To address this gap, we introduce an automated framework designed to generate predecoders for arbitrary qLDPC codes. By independently handling up to 99.98% of the decoding workload, these predecoders reduce decoder utilization up to 4,090$\times$, including up to 81.19% decrease in expensive OSD post-processing and 59.96% decrease in extra RelayBP legs. An efficient, pipelined hardware architecture enables simultaneous decoding of ~1,800 BB code logical qubits on a single FPGA, while cryogenic ASIC implementation supports ~50,000-500,000 BB code logical qubits within a 1.5 W power budget at 4 K.

Molecular spins offer promise in emerging quantum technologies such as quantum sensing and computing. At low temperatures, nuclear spin-spin interactions affect electron spin coherence lifetimes through pure dephasing. Nuclear-spin noise can originate from spin pairs within a molecule itself, pairs in a surrounding environment system, or pairs in which one spin is on the molecule and the other in the environment. Improving coherence times requires detailed knowledge of the dominant sources of dephasing. Here, we analyze the decoherence behavior of two molecular qubit candidates with various ligands and in different nuclear-spin containing solvents. We apply an electronic-structure enhanced, non-Markovian perturbative theoretical method to connect experimentally comparable dephasing times to individual spin pairs. This analysis allows the development of a computational workflow to strategically improve coherence lifetimes in spin systems where decoherence is dominated by spin-spin dephasing.

We introduce the coordination principle, which states that perfect coordination, in the form of agreement on a uniformly random output, among N parties is possible only if they share a common cause. This principle is purely causal and can be viewed as a multipartite generalization of Reichenbach's common cause principle. We prove that quantum information theory satisfy the coordination principle in any network, and derive noise-tolerant Bell-like inequalities that certify the presence of a common cause. We further show that the principle is not a consequence of no-signaling and independence alone by constructing a concrete operational probabilistic theory that obeys both principles while still allowing perfect coordination without a common cause. This possibility arises only in fully general causal scenarios with intermediate transformations between preparations and measurements. We also formulate a genuinely quantum coordination task, showing that the preparation of a multipartite GHZ state requires a quantum common cause, which can be certified by Bell-like inequalities which are experimentally testable. Finally, we discuss the open problem of finding a quantitative, noise-tolerant version of the coordination principle that constrains approximate coordination in any reasonable causal theory. This work is the extended version of the more compact letter and provides all the technical details of the proofs.

We present ffsim, an open-source software library for fast simulation of fermionic quantum circuits. ffsim exploits conservation of particle number and the z component of spin, symmetries present in a wide range of fermionic systems, to dramatically reduce memory usage and simulation time compared to general-purpose quantum circuit simulators. Compared to FQE, a library with similar functionality, ffsim differs in software design and is faster on a representative set of simulation benchmarks. Beyond state vector evolution by basic fermionic gates, ffsim offers a number of additional features including variational ansatzes, Hamiltonian time evolution via Trotter-Suzuki product formulas, efficient sampling of Slater determinants, seamless integration with Qiskit and PySCF, and comprehensive documentation. We demonstrate ffsim's capabilities on scientific applications involving quantum circuits of up to 64 qubits.

Frequency-multiplexed entangled photon pair sources with narrow bandwidths and high pair generation efficiency are a key enabling technology for quantum networking. We present a simulation-based design study of an integrated photonic racetrack resonator source for spontaneous parametric down-conversion (SPDC) that simultaneously achieves all three properties. The central result is a simulated set of 90 doubly resonant signal/idler frequency-mode pairs with an effective Schmidt number of 89.62, average bandwidths of 1.08 GHz, a mean free spectral range of 51.9 GHz, and a total internal pair-generation-rate efficiency of 1.16 GHz/mW. Under deterministic wavelength-based splitting, the accessible frequency-state Schmidt number is reduced to 44.93. To support these predictions, we derive a closed-form analytical connection between classical cavity parameters (resonant frequencies, decay rates, coupling coefficients) and the quantum joint spectral amplitude and pair generation rate, extending the dispersive-medium quantization formalism of Raymer to the nonlinear optical cavity case. We demonstrate how classical electromagnetic field simulations can be combined with this analytical framework to predict quantum figures of merit for an integrated photonic source prior to fabrication. Fabrication and experimental validation are left for future work.

We propose a novel causal principle that is a genuinely multipartite extension of Reichenbach's common cause principle, namely, the coordination principle: parties in a network can achieve perfect randomized coordination–in particular, agree on a uniformly random output–only if they all share a common cause. We show that this principle does not follow from the standard no-signaling and independence principles by providing an explicit theory satisfying all these principles while violating the coordination principle. Strikingly, we prove that the coordination principle holds, however, in quantum theory for four parties, and derive noise-tolerant Bell-like inequalities that certify a common cause. We then extend these results to a genuinely quantum coordination task, showing that the four-partite GHZ state requires a quantum common cause which can also be certified by experimentally accessible Bell-like inequalities. A companion paper generalizes these results for N parties, proving that the coordination principle is satisfied in general for quantum theory.

We present a geometric characterisation of local models in the bipartite Bell scenario with three measurement settings per site and binary outcomes, i.e. the (3,3,2,2) case. Restricting attention to indistinguishable sites, thus resulting in a `symmetric local' scenario, we introduce a three-dimensional mixed-moment space in which the mixed moments are calculated under off-diagonal measurement settings. In this reduced representation, the symmetric local region assumes the remarkably simple form of a regular tetrahedron - the 'pyramid'. We prove that only three inequalities are required to characterise the interior of this region. We call them the pyramid inequalities that separate symmetric local ($\mathcal{SL}$) models from their complement, non-symmetric local ($\mathcal{\overline{SL}}$) models. Remarkably, in this representation, the 'symmetric quantum' region forms an elliptope defined by a single inequality. We also clarify the relation between the symmetry-reduced pyramid representation and the full $(3,3,2,2)$ Bell polytope in the 36-dimensional conditional-probability space, which possesses 684 facet-defining inequalities. The reduction from 684 to three reflects normalisation, symmetry reduction, and projection to the mixed-moment space. In the pyramid representation, the hierarchy $\mathcal{SL} \subsetneq \mathcal{SQ} \subsetneq \mathcal{NS}$ appears geometrically as a tetrahedron embedded in a somewhat larger curved body of symmetric quantum models, $\mathcal{SQ}$, which in turn is embedded in a cube of no-signalling models, $\mathcal{NS}$. This provides a unified three-dimensional visualisation of symmetric local, symmetric quantum, and symmetric post-quantum correlations. The qualitative advantages of the pyramid representation over the standard one-dimensional CSHS representation of the $(2,2,2,2)$ case are also discussed.

Exchange-only (EO) spin qubits in silicon realise all-electrical qubit control through pairwise Heisenberg exchange interactions, making them attractive for scalable quantum computation. Their principal vulnerability is charge noise, which couples multiplicatively to the exchange coupling and degrades gate fidelity. We present a two-stage Physics-Informed Neural Network (PINN) framework for per-gate pulse optimisation. In Stage~I (iterations~1–100) the PINN maximises the noise-averaged gate fidelity toward a threshold of $\Fth=0.99$; the pulse duration is held fixed at its nominal hardware value. Once the threshold is crossed, Stage~II (iterations~101–250) progressively compresses the total pulse time while maintaining $F\geq\Fth$ via continuous fine-tuning of the pulse-shape parameters. The cost function is a Monte-Carlo ensemble mean-squared error (MSE) averaged over $N_{\rm real}=2000$ quasi-static Gaussian noise realisations drawn fresh at every iteration. We benchmark the framework on the single-qubit gate set $\{X,Y,Z,H\}$ and the two-qubit set $\{X,Y,Z,H,\mathrm{CX}\}$ at noise levels $\sigmaJ/J\in\{1\%,5\%,10\%\}$. All single-qubit gates cross $\Fth$ within the first 100 iterations across all noise levels; Stage~II then reduces pulse durations by 20–40% from their nominal values. The two-qubit gates follow the same two-phase behaviour, with the CX gate compressing from its nominal \SI{31}{\nano\second} to $\approx\SI{22}{\nano\second}$ at 1% noise.

We propose a novel method to calculate logical error rates in surface codes, assuming independent and identically distributed physical errors. These results fit well known scaling laws for studied physical error rates and code distances, but break down in some other regimes. Increasing the code distance still reduces logical error rates, but returns diminish quickly beyond a certain point. We show how to use our method to analyze hypothetical quantum computers with various configurations and select designs with lower error rates. Currently, this requires expensive classical simulations of quantum decoders for various distances and physical error rates or inaccurate extrapolation from minimal experimental data. Instead, we use the symmetry of the problem to count the configurations that result in a logical error with our novel software. Given a physical error rate, we can deduce the probability of a logical error to provably good accuracy quickly. We include an analysis of measurement errors to allow for a more complete comparison of different surface code implementations. We extend this counting method to a particular locally-correlated error model and another globally-correlated error model.

To what extent do individual eigenstates encode information about their parent Hamiltonian, and how does this encoding vary across the spectrum? We introduce learnability as a new framework to quantify this information, measured by the precision with which a machine learning model can reconstruct a Hamiltonian from a limited set of eigenstates. For many-body quantum systems, there is a contrast between the eigenstates near the spectral edges (low-entanglement, highly-structured states) and those far from the spectral edges (high-entanglement, near-random states). Using an encoder-decoder neural network for a non-integrable spin chain, we show that this dichotomy results in a stark difference in learnability: spectral-edge eigenstates allow for higher-accuracy Hamiltonian reconstruction using significantly fewer eigenstates, compared to mid-spectrum eigenstates. Our results provide a new lens through which to view the spectral structure of many-body systems.

We establish the conditions under which scalable spin squeezing can be achieved in interacting spin ensembles embedded in arbitrary, inhomogeneous graph geometries. We identify two different forms of squeezing: OAT-like scalable squeezing is governed solely by the universal properties of the interaction graph and is controlled by its spectral dimension. In critical squeezing, on the other hand, the value of the spectral dimension only furnishes the necessary condition for scalable metrological gain, while the sufficient condition requires the model to lie below the symmetry breaking transition. Therefore, in systems with random interaction graphs, the scaling of the spin-squeezing critical point emerges from a nontrivial interplay between xy-ferromagnetic universality and percolation universality. We apply this general theoretical framework to several experimental scenarios and discuss sharp and experimentally relevant conditions for achieving robust metrological gain on generic inhomogeneous structures, giving a unifying perspective for designing scalable quantum sensors across diverse quantum simulation platforms.

The quantum Wasserstein distances defined by Golse, Mouhot, Paul, and Caglioti and by De Palma and Trevisan coincide for qubits when a single operator appears in the cost function. As a consequence, the square of the self-distance equals the Wigner-Yanase skew information in this case. Moreover, for finite-dimensional systems of dimension $d\ge2$ and any number of operators, we show that the Golse-Mouhot-Paul-Caglioti self-distance is bounded from below by the De Palma-Trevisan self-distance.

We study the problem of constructing strong approximate unitary $k$-designs on $D$-dimensional grids (and more generally on Cartesian products of graphs), building on the work of Schuster et al. arXiv:2509.26310 which establishes strong unitary designs in 1D and in all-to-all connectivity. We provide two constructions. The first construction leverages the existing all-to-all connectivity result with general routing theory to provide flexible (but slightly suboptimal) strong $k$-designs in arbitrary connectivities. The second construction is more direct, requires no auxiliaries and has provably optimal depth (in the number of qubits $n$) for $D$-dimensional grids with constant dimension. Combining these techniques also allows us to construct strong pseudorandom unitaries on $D$-dimensional grids with provably optimal depth.

We present a general method to determine the energy minimum of spin Hamiltonians over separable states when the single-particle reduced density matrices are fixed. For ferromagnetic Ising and Ising-like models with nearest-neighbor interactions on lattices of any dimension and on a fully connected graph in an external field, this minimum is given by a compact analytic formula involving the quantum Fisher information. For the ferromagnetic Heisenberg chain of spin-1/2 particles, the minimum is expressed via the Uhlmann-Jozsa fidelity. These relations enable the direct extraction of both the quantum Fisher information and the fidelity from correlation measurements on the ground states of suitably engineered spin models.

We construct exact eigenstates of quantum many-body systems with Hamiltonians that are not frustration-free in matrix product form, based on a local error cancellation ansatz motivated by the Derrida-Evans-Hakim-Pasquier method for finding the stationary state of the asymmetric simple exclusion process. We demonstrate the approach with explicit examples in both one and two spatial dimensions.

A major promise of quantum computers is the controlled preparation of many-body quantum states beyond the reach of efficient classical computation. Among the most important targets are thermal mixed states and their thermofield double (TFD) purifications, which play central roles in quantum many-body physics and quantum gravity. For target systems with a bounded energy spectrum that obey the eigenstate thermalization hypothesis (ETH), we present a parent Hamiltonian built from two copies of the target Hamiltonian and ultra-local couplings between the copies, which we argue is gapped with a ground state that approximates a TFD state of the target Hamiltonian. By adiabatically evolving down from strong coupling, we can thus prepare a high-fidelity TFD state. We study two variants of the parent Hamiltonian using numerical methods in two classes of models: mixed field Ising models in one and two dimensions and non-local "spin Sachdev-Ye-Kitaev” models. In the simpler variant, the parent Hamiltonian ground state has high overlap with a TFD for system sizes accessible to near-term quantum devices. However, the global overlap decays exponentially with the number of qubits, with a small error per degree of freedom. The second variant introduces an additional penalty term which can be tuned to reduce or remove the decay of the overlap with system size. Together with a general ETH-based analysis, these results suggest a broadly applicable method for TFD preparation that is not limited to particular temperatures or geometric locality.

Thermal state preparation is a central challenge in the simulation of quantum many-body systems. Yet, provably efficient algorithms for this task were only introduced recently [Chen et al. Nature 646, 561 (2025)]. These algorithms are based on dissipative Lindbladian evolution which exactly fixes the thermal state. Controlled and efficient digital simulation of this evolution, although possible in principle, remains out of reach for present-day quantum hardware. Subsequent work has therefore focused on analog approximations of the proposed Lindbladians via `collision models' with relatively modest requirements – a resettable bath of ancilla qubits whose couplings to the system can be tuned in time-dependent fashion – while still admitting rigorous fixed-point error bounds. Existing rigorous approaches, however, do not exploit the fact that these constructions generically implement not only the desired Lindblad dynamics, but also an additional unitary evolution generated by the system Hamiltonian which may aid convergence to the thermal state [Lloyd and Abanin arXiv:2506.21318 (2025)]. Here, we show that this unitary contribution does indeed tighten the fixed-point error bound and demonstrate that it is rigorously controlled by the system-bath coupling strength $J$, scaling as $J^2$. This demonstrates that the effect of the spurious `Lamb shift' term generated by the system-bath interaction can be controlled by tuning $J$. We clarify the role, previously observed, of a randomized implementation in suppressing possible resonances of the drive with the many-body spectrum, and bound the additional variance that this randomization imposes on observables. Finally, we numerically study aspects of the protocol which are relevant for its practical realization, such as the mixing time.

The local-operator entanglement (LOE) measures the classical simulability of a Heisenberg operator and is conjectured to witness many-body chaos in locally interacting systems. Using tools from free probability, we analytically compute its asymptotic value for Haar random dynamics for all Rényi indices. We find that to the first two orders in large dimension, for traceless operators it exactly reproduces the Page curve for random states. In contrast to higher-order out-of-time-ordered correlators (OTOCs), which depend on more complex operator correlations via free cumulants, the leading-order LOE is independent of the initial operator. \add{We detail exactly how these higher-order correlations are encoded in the coefficients of the finite-size corrections. Therefore, guided by our Haar result, we argue that the long-time value of the LOE entropies in chaotic systems is robust: they depend only on a simple sub-sector of the hierarchy of correlations encoded by the full Eigenstate Thermalization Hypothesis. Our results therefore provide a conceptual boundary between operator simulability and higher-order scrambling diagnostics.

The linear combination of unitaries (LCU) is a fundamental quantum computing primitive used to embed non-unitary operators into larger systems via ancilla post-selection. In standard LCU implementations, only the zero-state ancilla outcome is retained, while all other measurement branches are discarded as unusable overhead. We study these discarded parts. Every computational-basis outcome of the ancilla projects the system onto a different linear combination of the target unitaries; collecting these outcome states in a matrix gives a factorization $\Phi=CX$, where $C$ is determined by the ancilla preparation and the rows of $X$ are the states $U_t|\psi\rangle$, so that $rank(\Phi)\le K$. Although this holds for any LCU circuit; to make the analysis easier, we use a simplified model circuit with Hadamard gates on the index register and a single rotation qubit in place of the coefficient preparation unitary, in which $C$ is explicit. The structure suggests two complementary applications: (i) in an explicit amplitude-access model, classical low-rank matrix completion can reconstruct the full output (including the target) from a subset of its amplitude entries, while computational basis counts provide intensities and generally require additional phase information for full complex recovery; (ii) treating $C$ as a secret key suggests a candidate quantum trapdoor function, whose security remains informal and depends on the difficulty of structured phase retrieval. The scheme thus turns the "junk" ancilla outcomes into a structured resource, possibly opening paths for further applications.

Dispersion interactions are usually derived assuming fixed internal spectra of the interacting quantum systems. Here, we relax this assumption and study how self-consistent electromagnetic backaction modifies van der Waals interactions when excitation energies and transition dipole moments are allowed to respond to the interaction itself. Within a macroscopic quantum electrodynamics framework, we formulate a self-consistent treatment that includes both self-energy corrections and mutual backaction. Using a minimal three-level model, we show that, while one-sided self-energy effects are short-ranged, fully self-consistent backaction can lead to substantial, long-ranged modifications of the effective van der Waals interaction. Our analysis demonstrates that these effects originate from the coherent accumulation of repeated photon-mediated scattering processes. The results highlight limitations of perturbative dispersion theories with fixed spectra and identify few-level systems as a clean platform for studying backaction in dispersion forces.

We demonstrate the adjusting left-handedness in the cold \(^{87}\)Rb atom by its number density, the strong coupling field and two incoherent pumping fields. The results show that more dense \(^{87}\)Rb atoms and more stronger coupling field can influence the left-handedness more greatly, while the increasing two incoherent pumping fields construct the negative magnetic response but depress the negative electric response. The left-handedness adjusted by multiple parameter in the cold \(^{87}\)Rb atomic system provides the flexibility and feasibility for the coming experiment.

Post-quantum migration in Transport Layer Security (TLS) requires evidence-aware measurements that distinguish session negotiation, endpoint capability, certificate-chain evidence, and the provenance of missing observations. This distinction is essential under TLS 1.3 encryption, resumption, mutual TLS, trace truncation, fragmentation, coalescing, active certificate retrieval, and temporal drift. We present a multi-surface framework for post-quantum TLS observability. The framework separates passive session evidence, active probing, certificate-chain evidence, and registry knowledge, and maps them onto measurement planes for session behavior, key establishment, endpoint capability, authentication, lifecycle, observability, and policy. We instantiate it as a reproducible artifact with schema-enforced observations and results, versioned registries, auditable inference rules, stress contracts, and baseline adapters. We evaluate the framework on 29 controlled scenarios spanning TLS 1.2 and TLS 1.3, classical and hybrid key establishment, mutual TLS, resumption, HelloRetryRequest, truncation, fragmentation and coalescing, temporal drift, IPv6, and chain-depth variation. Passive evidence closes session-level planes, active probing establishes capability lower bounds, and multi-surface evidence closes the full measurement object while preserving uncertainty and contradiction when required. Against an inherited TLS quantum-vulnerability analyzer, the baseline detects 2 of 29 runs and 0 of 23 TLS 1.3 runs. In a stratified public campaign over 1000 targets and 2000 fresh probes, the framework completes 1971 handshakes, collects 1368 chain artifacts, confirms hybrid capability for 310 targets, and identifies 310 cases where endpoint capability exceeds what any single classical session view reveals.

Quantum many-body Gibbs states satisfy an approximate local Markov property~\cite{chen2025GibbsMarkov}: local noise can be approximately recovered by a quasi-local recovery map, and the conditional mutual information decays for the corresponding tripartition. Recent work~\cite{bergamaschi2025structural} extends this property to approximate stationary states (metastable states) of certain master equations modeling system–bath dynamics, and proposes a strengthened post-selected recovery property requiring recovery to hold for each measurement outcome. In this note, we characterize this strong Markov property: it holds if and only if the state additionally satisfies correlation decay for suitable pairs of observables. We further prove several structural and operational consequences of the strong Markov property in the presence of an underlying master equation. First, one can estimate multiple observables from a single copy of the state via a repeated measurement–recovery protocol. Second, any two strongly Markov states must have local marginals that are either very close or well separated. Third, if a strongly Markov state can be expressed as a mixture of two strongly Markov states, then their local marginals must be nearly indistinguishable.

We introduce a real-valued functional $I(\vec{n}_1,\vec{n}_2)$ of four three-qubit correlations that turns the Greenberger-Horne-Zeilinger (GHZ) algebraic paradox into a quantitative witness of genuine tripartite entanglement. For every three-qubit state $\rho$ and every pair of directions, $|I(\vec{n}_1,\vec{n}_2;\rho)|\le 2$, with equality if and only if $\vec{n}_1\perp\vec{n}_2$ and $\rho$ is locally unitarily equivalent to the GHZ state. On the five-parameter Acín family, $I(\hat{x},\hat{y})$ depends only on $\lambda_0\lambda_4$ and is maximised by the GHZ state; for the W state $I(\hat{x},\hat{y})=0$ and $\max|I_{\mathrm{W}}|=35/27$. Maximising over independent local orthonormal frames yields a local-unitary invariant measure $\mathcal{E}_{\mathrm{GHZ}}\in[0,1]$, computable from four three-body Pauli correlators, that equals one exactly on the GHZ orbit and takes the values $35/54$ on the W state and $1/2$ on product states. We show that $\mathcal{E}_{\mathrm{GHZ}}$ is not convex: an equal mixture of three biseparable states has $\mathcal{E}_{\mathrm{GHZ}}=14/27$, larger than the average $1/2$ of its components. We also relate $\mathcal{E}_{\mathrm{GHZ}}$ to GHZ fidelity witnesses, discuss its behaviour under local operations and classical communication, and outline a generalisation to three qudits via Heisenberg-Weyl operators.

We propose a physically explicit sensing application of a time-reversed Young (TRY) interferometer: simultaneous monitoring of beam tilt and focus drift with a fixed detector. The task is relevant to compact optical relays, free-space links, fiber-coupling stages, and micro-optical alignment modules, where continuous tracking of pointing and focus is needed but downstream wavefront cameras or multiport analyzers are undesirable. Using a finite-width double-slit Fresnel model, we derive the exact local TRY response functions for tilt-like and defocus-like phase perturbations and compute the corresponding optimal upstream source codes numerically. The physical optimal codes are fringe-locked and differ qualitatively from the simple odd/even modes suggested by Gaussian toy models. Two source-coded scalar channels recover essentially all local Fisher information in the full source-resolved TRY record for the physical model considered here. Compared with downstream direct intensity sensing, TRY provides first-order access to the mixed tilt–defocus task with fixed detection; compared with ideal downstream matched-mode sorting, its advantage is architectural rather than fundamental.

By confining a Bose-Einstein condensate in a vertical lattice subjected to a gravitational potential, we analyze the quantum Fisher information to determine its scaling with respect to time, system size and particle number. Our results reveal that in the localized phase, on-site interactions $U$ amplify the quantum Fisher information by a factor with respect to resonance condition $U=mh$ where $U$ is factor of gradient field amplitude $h$. This precision enhancement can be employed in gravitational acceleration measurements with a finite number of particles trapped in optical lattices.

We identify a hierarchical symmetry structure underlying the Hilbert space of quantum systems made of identical particles. By studying the linear map between single-body and many-body spectra, we show that the resulting spectral organization admits a natural partition into sectors induced by a symmetry governed by cyclotomic fields and their Galois groups. This approach offers a new perspective on the structure of quantum many-body spectra, defining a controlled coarse-graining of the Hilbert space in which degeneracies and spectral features can be systematically organized through a set of new quantum numbers. The resulting structure induces a hierarchy of spectral resolutions following a renormalization flow, which enables information loss control. We demonstrate that this hierarchical decomposition provides an efficient route to approximate MBDoS calculations for any identical particle system, while preserving physically relevant spectral properties. This approach provides a general symmetry-based framework for organizing and approximating many-body spectra, with potential applications to quantum thermalization, spectral statistics, and large-scale quantum simulations.

Quantum error detection can produce unbiased expectation values that exponentially converge to noiseless results as the code distance is increased. Despite this, its performance as an error mitigation technique is relatively understudied on quantum hardware because of its two main drawbacks: (i) the number of samples increases exponentially in the circuit depth/noise level, and (ii) the classical processing generally grows exponentially in the code distance, though exceptions exist. Additionally, the constant (but often large) overhead of embedding the code and logical operations on hardware can make accuracy worse instead of better. In this work, we seek to provide a clear picture of these opportunities and challenges for scaling quantum error detection on hardware. We do so by performing a detailed benchmarking study on real and simulated noisy quantum computers, using the repetition code and triangular color code for memory experiments and logical computations with up to $74$ physical qubits. In addition to these benchmarks, we estimate the pseudothreshold of codes to map the frontier of error detection on current and future quantum computers. Despite the challenges, our results show strong promise for scaling quantum error detection on hardware.

Single-spin magnetic resonance spectroscopy promises to yield structural and chemical information at the level of individual atoms or molecules, in a non-invasive way. Here, we use an Er3+ paramagnetic center in a CaWO4 crystal, detected by microwave photon counting at 10 mK, as a nanoscale magnetic sensor to measure the NMR spectrum of a proximal individual nuclear-spin-9/2 93Nb impurity with Hertz spectral resolution. From these measurements, we determine the 93Nb insertion site, its position relative to the Er3+ , and its complete quadrupolar tensor. We moreover harness the high spectral resolution of our measurements to establish the presence of two previously unobserved terms in the spin Hamiltonian. The first describes a coupling between the Er3+ spin and the 93Nb nuclear quadrupole; it possibly originates from a spin-dependent electrostatic interaction between the two systems. The second is a nuclear hexadecapolar term, and may be caused by the coupling of the electric field third derivative to the 93Nb nuclear hexadecapolar moment.

Variational quantum algorithms (VQAs) are leading strategies for using near-term quantum devices, with a well-studied bottleneck being their trainability. Standard expectation-value objectives with expressive circuits frequently encounter barren plateaus in the optimization landscape during training. To address this challenge, we introduce the Quantum Tilted Loss (QTL), an operator-level generalization of classical exponential tilting designed to systematically reshape the optimization landscape. By tuning a single continuous parameter, QTL can amplify gradient signals in structured settings while preserving the problem's true global minima. We provide a theoretical foundation that unifies standard expectation minimization with popular tunable heuristics, such as Conditional Value-at-Risk (CVaR) and Gibbs formulations. Deploying this framework requires balancing the geometric benefits of a sharpened landscape against the statistical cost of estimating nonlinear gradients from finite quantum measurements. We formalize this trainability-estimability trade-off, demonstrating how aggressive tilting fundamentally shifts the optimization bottleneck from landscape flatness to sample complexity. Thus, the operational bottleneck shifts from vanishing gradients to measurement sampling variance. Finally, we exhibit through numerical simulations that ascending tilt schedules can outperform fixed-tilt training in finite-shot regimes.