Papers

We apply the combined technique of postselected amplification and photon-recycling to an optical setup of magnetic field precision measurement. We propose two recycling schemes and carry out analytic expressions for the amplified signal and measurement sensitivity. The results show significant improvement of performance over conventional measurement. The underlying reason is twofold. On one aspect, introducing the technique of recycling eliminates the shortcoming of data discarding in postselection, thus maintains similar noise level of conventional measurement (without postselection). On the other aspect, performing intentional postselection within the recycling framework, which was originally proposed in the context of gravitational wave detection, can amplify the signal. Thus, the measurement signal-to-noise ratio is enhanced.

Decoded Quantum Interferometry (DQI) defines a duality that pairs decoding problems with optimization problems. The original work on DQI considered Reed-Solomon decoding, whose dual optimization problem, called Optimal Polynomial Intersection (OPI), is a polynomial regression problem over a finite field. Here, we consider a class of algebraic geometry codes called Hermitian codes, which achieve block length $q^3$ using alphabet $\mathbb{F}_{q^2}$ compared to Reed-Solomon's limitation to block length $q$ over $\mathbb{F}_q$, requiring approximately one-third fewer qubits per field element for quantum implementations. We show that the dual optimization problem, which we call Hermitian Optimal Polynomial Intersection (HOPI), is a polynomial regression problem over a Hermitian curve, and because the dual to a Hermitian code is another Hermitian code, the HOPI problem can also be viewed as approximate list recovery for Hermitian codes. By comparing to Prange's algorithm, simulated annealing, and algebraic list recovery algorithms, we find a large parameter regime in which DQI efficiently achieves a better approximation than these classical algorithms, suggesting that the apparent quantum speedup offered by DQI extends beyond Reed-Solomon codes to a broader class of polynomial regression problems on algebraic varieties.

We study the existence and limitations of hyperinvariant tensor networks incorporating a local SU(2) symmetry. As discrete implementations of the anti de-Sitter/conformal field theory (AdS/CFT) correspondence, such networks have created bridges between the fields of quantum information theory and quantum gravity. Adding SU(2) symmetry to the tensor network allows a direct connection to spin network states, a basis of the kinematic Hilbert space of loop quantum gravity (LQG). We consider a particular situation where the states can be interpreted as kinematic quantum states for three-dimensional quantum gravity. We show that important aspects of the AdS/CFT correspondence are realized in certain quantum states of the gravitational field in LQG, thus justifying, from first principles, a class of models introduced by [F. Pastawski et al., JHEP 06, 149 (2015)]. We provide examples of hyperinvariant tensor networks, but also prove constraints on their existence in the form of no-go theorems that exclude absolutely maximally entangled states as well as general holographic codes from local SU(2)-invariance. We calculate surface areas as expectation values of the LQG area operator and discuss further possible constraints as a consequence of a decay of correlations on the boundary.

Recent research on excitonic insulator has progressed mainly based on narrow bandgap semiconductor or semimetal. Herein, we realize excitonic insulator based on two-dimensional (2D) wide band gap diamond with transition temperature as high as 220K. The resistance rises dramatically by more than three orders, which can be explained by the Bose-Einstein condensation (BEC) of excitons. While cooling down below transition temperature, the wavelength of the bound excitons caused by boron and nitrogen centers becomes highly overlapped, leading to BEC process. Furthermore, the variable range hopping mechanism is used to simulate the resistance as a function of temperature, which reveals the formation of excitonic insulator. When temperature drops down further, a sudden drop of resistance over three orders was observed around 60K, possibly due to the formation of non-equilibrium excitonic superfluid resulting from highly overlap of wavelength of the large density bound excitons at lower temperature. This study provides evidences for excitonic insulator and possible superfluid phase based on wide bandgap semiconductor.

Accurate prediction of bond dissociation energies (BDEs) underpins mechanistic insight and the rational design of molecules and materials. We present a systematic, reproducible benchmark comparing quantum and classical machine learning models for BDE prediction using a chemically curated feature set encompassing atomic properties (atomic numbers, hybridization), bond characteristics (bond order, type), and local environmental descriptors. Our quantum framework, implemented in Qiskit Aer on six qubits, employs ZZFeatureMap encodings with variational ansatz (RealAmplitudes) across multiple architectures Variational Quantum Regressors (VQR), Quantum Support Vector Regressors (QSVR), Quantum Neural Networks (QNN), Quantum Convolutional Neural Networks (QCNN), and Quantum Random Forests (QRF). These are rigorously benchmarked against strong classical baselines, including Support Vector Regression (SVR), Random Forests (RF), and Multi-Layer Perceptrons (MLP). Comprehensive evaluation spanning absolute and relative error metrics, threshold accuracies, and error distributions shows that top-performing quantum models (QCNN, QRF) match the predictive accuracy and robustness of classical ensembles and deep networks, particularly within the chemically prevalent mid-range BDE regime. These findings establish a transparent baseline for quantum-enhanced molecular property prediction and outline a practical foundation for advancing quantum computational chemistry toward near chemical accuracy.

Symmetries and their anomalies are powerful tools to understand quantum matter. In this work, for quantum spin chains, we define twisted locality-preserving automorphisms and their Gross-Nesme-Vogts-Werner indices, which provide a unified framework to describe both unitary and anti-unitary symmetries, on-site and non-on-site symmetries, and internal and translation symmetries. For a symmetry $G$ with actions given by twisted locality-preserving automorphisms, we give a microscopic definition of its anomaly index, which is an element in $H^3_\varphi(G; U(1))$, where the subscript $\varphi$ means that anti-unitary elements of $G$ act on $U(1)$ by complex conjugation. We show that an anomalous symmetry leads to multiple Lieb-Schultz-Matttis-type theorems. In particular, any state with an anomalous symmetry must either have long-range correlation or violate the entanglement area law. Based on this theorem, we further deduce that any state with an anomalous symmetry must have long-range entanglement, and any Hamiltonian that has an anomalous symmetry cannot have a unique gapped symmetric ground state, as long as the interactions in the Hamiltonian decay fast enough as the range of the interaction increases. For Hamiltonians with only two-spin interactions, the last theorem holds if the interactions decay faster than $1/r^2$, where $r$ is the distance between the two interacting spins. We demonstrate these general theorems in various concrete examples.

Filtering is commonly used in quantum optics to reject noise photons, and also to enable interference between independent photons. However, filtering the joint spectrum of photon pairs can reduce the inherent coincidence probability or loss-independent heralding efficiency. Here, we investigate filtering for multiphoton applications based on entanglement and interference (e.g., quantum teleportation). We multiplex C-band entangled photons and C-band classical communications into the same long-distance fibers, which enables scalable low-loss quantum networking but requires filtering of spontaneous Raman scattering noise from classical light. Using tunable-bandwidth filters, low-jitter detectors, and polarization filters, we co-propagate time-bin-entangled photons at wavelengths compatible with erbium-ion quantum memories (1536.5 nm) and 10-Gbps C-band classical data over 25 km/25 km of standard fiber. Narrow filtering enables mW-level C-band power, which exceeds comparable studies by roughly an order of magnitude and could feasibly support Tbps classical rates. We evaluate how performance depends on pump and filter bandwidths, multipair emission, filter shapes, loss, phase matching, and how quantum information is measured. We find a trade-off between improving noise impact and single-mode purity and discuss mitigation methods toward optimal multiphoton applications. Importantly, these results apply to noise in free space and in quantum devices (sources, frequency converters, switches, detectors, etc.) and provide insight on filter-induced degradation of single-photon purity and rates even in noise-free environments.

Quantum compute is scaling fast, from cloud QPUs to high throughput GPU simulators, making it timely to prototype quantum NLP beyond toy tasks. However, devices remain qubit limited and depth limited, training can be unstable, and classical attention is compute and memory heavy. This motivates compact, phase aware quantum token mixers that stabilize amplitudes and scale to long sequences. We present CLAQS, a compact, fully quantum token mixer for text classification that jointly learns complex-valued mixing and nonlinear transformations within a unified quantum circuit. To enable stable end-to-end optimization, we apply l1 normalization to regulate amplitude scaling and introduce a two-stage parameterized quantum architecture that decouples shared token embeddings from a window-level quantum feed-forward module. Operating under a sliding-window regime with document-level aggregation, CLAQS requires only eight data qubits and shallow circuits, yet achieves 91.64% accuracy on SST-2 and 87.08% on IMDB, outperforming both classical Transformer baselines and strong hybrid quantum-classical counterparts.

The minimum weight matching (MWM) and maximum likelihood decoding (MLD) are two widely used and distinct decoding strategies for quantum error correction. For a given syndrome, the MWM decoder finds the most probable physical error corresponding to the MWM of the decoding graph, whereas MLD aims to find the most probable logical error. Although MLD is the optimal error correction strategy, it is typically more computationally expensive compared to the MWM decoder. In this work, we introduce an algorithm that approximates MLD with $K$ MWMs from the decoding graph. Taking the surface code subject to graphlike errors as an example, we show that it is possible to efficiently find the first $K$ MWMs by systematically modifying the original decoding graph followed by finding the MWMs of the modified graphs. For the case where the $X$ and $Z$ errors are correlated, despite the MWM of the decoding hypergraph cannot be found efficiently, we present a heuristic approach to approximate the MLD by finding the $K$ MWMs in the $X$ and $Z$ subgraphs. We benchmark the efficacy of our algorithm for the surface code subject to graphlike errors, the surface-square Gottesman-Kitaev-Preskill (GKP) code and surface-hexagonal GKP code subject to the Gaussian random displacement errors, showing that the fidelity approaches that of the exact MLD (for the first two cases) or the tensor-network decoder (for the last case) as $K$ increases.

Multiple-input multiple-output (MIMO) is critical for 6G communication, offering improved spectral efficiency and reliability. However, conventional fully digital designs face significant challenges due to high hardware complexity and power consumption. Low-bit MIMO architectures, such as those employing b-bit quantized phase shifters, provide a cost-effective alternative but introduce NP-hard combinatorial problems in the pre- and post-coding design. This paper explores the use of the Quantum Approximate Optimization Algorithm (QAOA) and alternating optimization to address the problem of b-bit quantized phase shifters both at the transmitter and the receiver. We demonstrate that the structure of this quantized beamforming problem aligns naturally with hybrid-classical methods like QAOA, as the phase shifts used in beamforming can be directly mapped to rotation gates in a quantum circuit. Notably, this paper is the first to show that theoretical connection. Then, the Hamiltonian derivation analysis for the b-bit case is presented, which could have applications in different fields, such as integrated sensing and communication, and emerging quantum algorithms such as quantum machine learning. In addition, a warm-start QAOA approach is studied which improves computational efficiency. Numerical results highlight the effectiveness of the proposed methods in achieving an improved quantized beamforming gain over their classical optimization benchmarks from the literature.

Quantum computing is rapidly emerging as one of the most transformative technologies of our time. With the potential to tackle problems that remain intractable for even the most powerful classical supercomputers, quantum hardware has advanced at an extraordinary pace. Today, major platforms such as IBM Quantum, Amazon Braket, and Microsoft Azure provide cloud-based access to quantum processors, making them more widely available than ever before. While a promising technology, quantum computing is not magically immune to security threats. Much research has been done on post-quantum cryptography, which addresses how to protect classical computers from attackers using quantum computers. This article meanwhile introduces the dual idea of quantum computer security: how to protect quantum computers from security attacks.

We prove several new results concerning the pure quantum polynomial hierarchy (pureQPH). First, we show that QMA(2) is contained in pureQSigma2, that is, two unentangled existential provers can be simulated by competing existential and universal provers. We further prove that pureQSigma2 is contained in QSigma3, which in turn is contained in NEXP. Second, we give an error reduction result for pureQPH, and, as a consequence, prove that pureQPH = QPH. A key ingredient in this result is an improved dimension-independent disentangler. Finally, we initiate the study of quantified Hamiltonian complexity, the quantum analogue of quantified Boolean formulae. We prove that the quantified pure sparse Hamiltonian problem is pureQSigma-complete. By contrast, other natural variants (pure/local, mixed/local, and mixed/sparse) admit nontrivial containments but fail to be complete under known techniques. For example, we show that the exists-forall mixed local Hamiltonian problem lies in NP^QMA \cap coNP^QMA.

We develop a model for non-Gaussian state generation via spontaneous parametric down-conversion (SPDC) in InGaP microring resonators. The nonlinear Hamiltonian is written in terms of the asymptotic fields for the system, which includes a phantom channel to handle scattering loss. The full ket for the system is written as a Gaussian unitary acting on a residual non-Gaussian ket, which is vacuum initially and evolves according to a non-Gaussian Hamiltonian. We show that for realistic parameters we can access the pump depletion regime, where the Wigner function for the residual non-Gaussian ket has negativity. But we find that the non-Gaussian features for the full ket could be unobservable due to the large amount of squeezing required to lead to pump depletion. We show that a potential solution in the low-loss regime is to implement an inverse Gaussian unitary on the accessible modes to remove most of the squeezing and reveal the non-Gaussian features. This work provides a foundation for modeling pump-depleted SPDC in integrated lossy microring resonators, opening a path toward a scalable on-chip non-Gaussian source.

Qudits offer significant advantages over qubit-based architectures, including more efficient gate compilation, reduced resource requirements, improved error-correction primitives, and enhanced capabilities for quantum communication and cryptography. Yet, one of the most promising families of quantum error correction codes, namely quantum low-density parity-check (LDPC) codes, have so far been mostly restricted to qubits. Here, we generalize recent advancements in LDPC codes from qubits to qudits. We introduce a general framework for finding qudit LDPC codes and apply our formalism to several promising types of LDPC codes. We generalize bivariate bicycle codes, including their coprime variant; hypergraph product codes, including the recently proposed La-cross codes; subsystem hypergraph product (SHYPS) codes; high-dimensional expander codes, which make use of Ramanujan complexes; and fiber bundle codes. Using the qudit generalization formalism, we then numerically search for and decode several novel qudit codes compatible with near-term hardware. Our results highlight the potential of qudit LDPC codes as a versatile and hardware-compatible pathway toward scalable quantum error correction.

We express the probabilistic character associated to the wave function by treating it as a stochastic variable. This is accomplished by means of a stochastic equation for the wave function whose noise changes the phase of the wave function but not its absolute value, so that the norm of the wave function is strictly conserved along a stochastic trajectory. We show that the density matrix that obeys the quantum Liouville equation is the covariance matrix associated to the stochastic wave function.

Interfacing light with quantum systems is an integral part of quantum technology, with the most essential building block being single-photon emitters. Although various platforms exist, each with its individual strengths, molecular emitters boast a unique advantage – namely the flexibility to tailor their design to fit the requirements of a specific task. However, the characteristics of the vast space of possible molecular configurations are challenging to understand and explore. Here, we present a theoretical and computational framework to initiate exploration of this vast potential by integrating database analysis with microscopic predictions. Using a model system of dibenzoterrylene in an anthracene host as benchmark, our approach identifies promising new candidates, among them a chiral molecular emitter. Future extensions of our approach integrated with machine learning routines hold the promise of ultimately unlocking the full potential of molecular quantum light-matter interfaces.

We introduce the novel concept of mereological quantum phase transition (m-QPTs). Our framework is based on a variational family of operator algebras defining generalized tensor product structures (g-TPS), a parameter-dependent Hamiltonian, and a quantum scrambling functional. By minimizing the scrambling functional, one selects a g-TPS, enabling a pullback of the natural information-geometric metric on the g-TPS manifold to the parameter space. The singularities of this induced metric – so-called algebra susceptibility – in the thermodynamic limit characterize the m-QPTs. We illustrate this framework through analytical examples involving quantum coherence and operator entanglement. Moreover, spin-chains numerical simulations show susceptibility sharp responses at an integrability point and strong growth across disorder-induced localization, suggesting critical reorganizations of emergent subsystem structure aligned with those transitions.

Quantum computing promises exponential speedups for certain problems, yet fully universal quantum computers remain out of reach and near-term devices are inherently noisy. Motivated by this, we study noisy quantum algorithms and the landscape between $\mathsf{BQP}$ and $\mathsf{BPP}$. We build on a powerful technique to differentiate quantum and classical algorithms called the level-$\ell$ Fourier growth (the sum of absolute values of Fourier coefficients of sets of size $\ell$) and show that it can also be used to differentiate quantum algorithms based on the types of resources used. We show that noise acting on a quantum algorithm dampens its Fourier growth in ways intricately linked to the type of noise. Concretely, we study noisy models of quantum computation where highly mixed states are prevalent, namely: $\mathsf{DQC}_k$ algorithms, where $k$ qubits are clean and the rest are maximally mixed, and $\frac{1}{2}\mathsf {BQP}$ algorithms, where the initial state is maximally mixed, but the algorithm is given knowledge of the initial state at the end of the computation. We establish upper bounds on the Fourier growth of $\mathsf{DQC}_k$, $\frac{1}{2}\mathsf{BQP}$ and $\mathsf{BQP}$ algorithms and leverage the differences between these bounds to derive oracle separations between these models. In particular, we show that 2-Forrelation and 3-Forrelation require $N^{\Omega(1)}$ queries in the $\mathsf{DQC}_1$ and $\frac{1}{2}\mathsf{BQP}$ models respectively. Our results are proved using a new matrix decomposition lemma that might be of independent interest.

Quantum hardware increasingly relies on energy reserves that can later be converted into useful work; yet, most battery-like proposals demand coherent drives or engineered non-equilibrium resources, limiting practicality in noisy settings. We develop an autonomous charging paradigm in which an ensemble of identical two-level units, collectively coupled to a thermal environment, acquires work capacity without any external control. The common bath mediates interference between emission and absorption pathways, steering the many-body state away from passivity and into a steady regime with nonzero extractable work. The full charging dynamics and closed-form expressions are obtained for the steady-state, showing favorable scaling with the number of cells that approach the many-body optimum. We show that the mechanism is robust to local noise: under a convex mixture of collective and local dissipation, non-zero steady-state ergotropy persists, exhibits counterintuitive finite-temperature optima, and remains operative when the collective channel is comparable to or stronger than the local one. We show that environmental fluctuations can be harnessed to realize drive-free, scalable quantum batteries compatible with circuit- and cavity-QED platforms. Used as local work buffers, such batteries could potentially enable rapid ancilla reset, bias dissipative stabilizer pumps, and reduce syndrome-extraction overhead in fault-tolerant quantum computing.

We examine the behavior of sequences of states in the large $N$ limit of AdS/CFT duality in cases in which the bulk duals involve baby universes or black holes. Such sequences generally fail to converge as pure states. Under suitable conditions, such as diverging coarse-grained entropy, they can converge to mixed states for the large $N$ algebra, as in the case of black holes. For Euclidean preparations that produce baby universes, the sequences do not converge, due to wormhole contributions, and so these states cannot admit large $N$ limits. Nevertheless, appropriate averaging over $N$ can lead to convergence to a mixed state. The associated algebras have nontrivial commutants, which can possibly be interpreted as operators in the baby universe.

Estimating extensive combinations of local parameters in distributed quantum systems is a central problem in quantum sensing, with applications ranging from magnetometry to timekeeping. While optimal strategies are known for sensing non-interacting Hamiltonians in quantum sensor networks, fundamental limits in the presence of uncontrolled interactions remain unclear. Here, we establish optimal bounds and protocols for estimating a linear combination of local parameters of Hamiltonians with arbitrary, unknown interactions. In the process, we more generally establish bounds for learning any linear combination of Hamiltonian coefficients for arbitrary, commuting terms. Our results unify and extend existing bounds for non-interacting qubits and multimode interferometers, providing a general framework for distributed sensing and Hamiltonian learning in realistic many-body systems.

Quantum circuits with a constant rate of depolarizing noise per qubit per time step are known to converge to the uniform distribution at depth $\omega(p^{-1}\log n)$, and hence become trivially classically simulable by uniform sampling. We show that under the physically natural constraint of geometric locality, noisy circuits become classically simulable at shallower depths by substantially more structured classical algorithms. We consider arbitrary geometrically local quantum circuits on $n$ qubits, initialized in an arbitrary product state, with nearest-neighbor gates in $O(1)$ spatial dimensions and interspersed depolarizing noise of any constant strength $p$. Our first result is that when the depth exceeds a threshold $d^*=\Theta(p^{-1}\log n)$, the output distribution can be approximately sampled in quasipolynomial time. This gives a worst-case simulability result for noisy geometrically local circuits, and matches in its $n$-dependence the best previously known results for noisy random circuits. The proof is based on new information-theoretic bounds showing that in geometrically local noisy circuits, local regions lose correlations and independently converge to maximally mixed strictly before the entire system converges to the uniform distribution. We further prove structural results suggesting a sharper transition at depth $\tilde{\Theta}(p^{-1})$: after coarse-graining the lattice, Pauli weight supported on long connected paths can be truncated with exponentially small error. These results provide evidence for a percolation-like mechanism behind classical simulability at constant depth, and motivate our conjecture that all noisy geometrically local circuits admit quasipolynomial-time approximate sampling once circuit depth exceeds $\tilde{\Theta}(p^{-1})$.

Given a sequence of random variables $X^n=X_1,\ldots, X_n$, discriminating between two hypotheses on the underlying probability distribution is a key task in statistics and information theory. Of interest here is the Stein exponent, i.e. the largest rate of decay (in $n$) of the type II error probability for a vanishingly small type I error probability. When the hypotheses are simple and i.i.d., the Chernoff-Stein lemma states that this is given by the relative entropy between the single-copy probability distributions. Generalisations of this result exist in the case of composite hypotheses, but mostly to settings where the probability distribution of $X^n$ is not genuinely correlated, but rather, e.g., a convex combination of product distributions with components taken from a base set. Here, we establish a general Chernoff-Stein lemma that applies to the setting where both hypotheses are composite and genuinely correlated, satisfying only generic assumptions such as convexity (on both hypotheses) and some weak form of permutational symmetry (on either hypothesis). Our result, which strictly subsumes most prior work, is proved using a refinement of the blurring technique developed in the context of the generalised quantum Stein's lemma [Lami, IEEE Trans. Inf. Theory 2025]. In this refined form, blurring is applied symbol by symbol, which makes it both stronger and applicable also in the absence of permutational symmetry. The second part of the work is devoted to applications: we provide a single-letter formula for the Stein exponent characterising the discrimination of broad families of null hypotheses vs a composite i.i.d. or an arbitrarily varying alternative hypothesis, and establish a 'constrained de Finetti reduction' statement that covers a wide family of convex constraints. Applications to quantum hypothesis testing are explored in a related paper [Lami, arXiv:today].

Given two families of quantum states $A$ and $B$, called the null and the alternative hypotheses, quantum hypothesis testing is the task of determining whether an unknown quantum state belongs to $A$ or $B$. Mistaking $A$ for $B$ is a type I error, and vice versa for the type II error. In quantum Shannon theory, a fundamental role is played by the Stein exponent, i.e. the asymptotic rate of decay of the type II error probability for a given threshold on the type I error probability. Stein exponents have been thoroughly investigated – and, sometimes, calculated. However, most currently available solutions apply to settings where the hypotheses simple (i.e. composed of a single state), or else the families $A$ and $B$ need to satisfy stringent constraints that exclude physically important sets of states, such as separable states or stabiliser states. In this work, we establish a general formula for the Stein exponent where both hypotheses are allowed to be composite: the alternative hypothesis $B$ is assumed to be either composite i.i.d. or arbitrarily varying, with components taken from a known base set, while the null hypothesis $A$ is fully general, and required to satisfy only weak compatibility assumptions that are met in most physically relevant cases – for instance, by the sets of separable or stabiliser states. Our result extends and subsumes the findings of [BBH, CMP 385:55, 2021] (that we also simplify), as well as the 'generalised quantum Sanov theorem' of [LBR, arXiv:2408.07067]. The proof relies on a careful quantum-to-classical reduction via measurements, followed by an application of the results on classical Stein exponents obtained in [Lami, arXiv:today]. We also devise new purely quantum techniques to analyse the resulting asymptotic expressions.

We establish a novel mechanism for topological transitions in non-Hermitian systems that are controlled by the system size. Based on a new paradigm known as exceptional-bound (EB) band engineering, its mechanism hinges on the unique critical scaling behavior near an exceptional point, totally unrelated to the well-known non-Hermitian skin effect. Through a series of ansatz models, we analytically derive and numerically demonstrate how topological transitions depend on the system size with increasingly sophisticated topological phase boundaries. Our approach can be generically applied to design scaling-dependent bands in multi-dimensional lattices, gapped or gapless, challenging established critical and entanglement behavior. It can be experimentally demonstrated in any non-Hermitian platform with versatile couplings or multi-orbital unit cells, such as photonic crystals, as well as classical and quantum circuits. The identification of this new EB band mechanism provides new design principles for engineering band structures through scaling-dependent phenomena unique to non-Hermitian systems.

A robust definition of quantum runtime is essential for assessing the performance of quantum algorithms and claims of quantum advantage. While for most classical hardware the total runtime is well approximated by computation plus a weakly varying constant, on current quantum hardware a clean experimental separation between "pure computation" and "overhead" is often not justified. Consequently, conventional quantum runtime analyses excluding substantial system-level overheads can lead to biased performance assessments. In this work we introduce experimentally grounded, end-to-end definitions of quantum runtime for digital and analogue quantum computers, together with a methodology for selecting strong classical baselines for quantum-classical runtime comparisons. Within this framework, we evaluate recent claims of quantum advantage in annealing and gate-based algorithms. We examine three representative case studies. First, we revisit annealing for approximate QUBO problems PRL 134, 160601 (2025), which employs a well-motivated time-to-$\epsilon$ metric but effectively uses annealing time as a proxy for runtime. Second, we analyze a restricted implementation of Simon's problem PRX 15, 021082 (2025), where the favorable scaling in oracle calls is undisputed; however, we show that the estimated runtime of the quantum experiment is approximately two orders of magnitude slower than a tuned classical baseline at the tested sizes. Finally, we find that the runtime advantage of the BF-DCQO hybrid algorithm arXiv:2505.08663 is not observed under more comprehensive benchmarking. Therefore, on current NISQ hardware, runtime-based quantum advantage has not yet been demonstrated under experimentally grounded performance metrics, and credible claims require careful time accounting, appropriate performance measures, and properly chosen classical reference implementations, as discussed in this work.

In quantum many-body systems with kinetically constrained dynamics, the Hilbert space can split into exponentially many disconnected subsectors, a phenomenon known as Hilbert-space fragmentation. We study the interplay of such fragmentation with symmetries, focusing on charge conserving systems with charge conjugation and translation symmetries as a concrete example. The non-Abelian algebra of these symmetries and the projectors onto the fragmented subsectors leads to the emergence of exponentially many logical qubits encoded in degenerate pairs of eigenstates, which can be highly entangled. This algebra also provides necessary conditions for experimental signatures of Hilbert-space fragmentation, such as the persistence of density imbalances at late times.

We study the classical simulability of noisy random quantum circuits under general noise models. While various classical algorithms for simulating noisy random circuits have been proposed, many of them rely on the anticoncentration property, which can fail when the circuit depth is small or under realistic noise models. We propose a new approach based on the exponential decay of conditional mutual information (CMI), a measure of tripartite correlations. We prove that exponential CMI decay enables a classical algorithm to sample from noisy random circuits – in polynomial time for one dimension and quasi-polynomial time for higher dimensions – even when anticoncentration breaks down. To this end, we show that exponential CMI decay makes the circuit depth effectively shallow, and it enables efficient classical simulation for sampling. We further provide extensive numerical evidence that exponential CMI decay is a universal feature of noisy random circuits across a wide range of noise models. Our results establish CMI decay, rather than anticoncentration, as the fundamental criterion for classical simulability, and delineate the boundary of quantum advantage in noisy devices.

Networks of sensors are a promising scheme to deliver the benefits of quantum technologies in coming years, offering enhanced precision and accuracy for distributed metrology through the use of large entangled states. Recent work has additionally explored the privacy of these schemes, meaning that local parameters can be kept secret while a joint function of these is estimated by the network. In this work, we use the abstract cryptography framework to relate the two proposed definitions of quasi-privacy, showing that both are composable, which enables the protocol to be securely included as a sub-routine to other schemes. We give an explicit example that estimating the mean of a set of parameters using GHZ states is composably fully secure.

While quantum computing can accomplish tasks that are classically intractable, the presence of noise may destroy this advantage in the absence of fault tolerance. In this work, we present a classical algorithm that runs in $n^{\rm{polylog}(n)}$ time for simulating quantum circuits under local depolarizing noise, thereby ruling out their quantum advantage in these settings. Our algorithm leverages a property called approximate Markovianity to sequentially sample from the measurement outcome distribution of noisy circuits. We establish approximate Markovianity in a broad range of circuits: (1) we prove that it holds for any circuit when the noise rate exceeds a constant threshold, and (2) we provide strong analytical and numerical evidence that it holds for random quantum circuits subject to any constant noise rate. These regimes include previously known classically simulable cases as well as new ones, such as shallow random circuits without anticoncentration, where prior algorithms fail. Taken together, our results significantly extend the boundary of classical simulability and suggest that noise generically enforces approximate Markovianity and classical simulability, thereby highlighting the limitation of noisy quantum circuits in demonstrating quantum advantage.