Over the past decade, gravitational-wave astronomy has opened a new window onto the extreme states of matter inside compact stars. At some point during the inspiral of a binary system, each star starts to experience adiabatic tides, characterized by tidal deformabilities. The dominant tidal deformability, first measured with the GW170817 event, has already constrained the dense-matter equation of state. With the advent of third-generation detectors, tidal deformabilities are expected to be inferred with much higher precision, potentially revealing subleading tidal contributions. This motivates the development of more accurate compact-star models that incorporate richer microphysics. With this in mind, we move beyond the commonly adopted perfect-fluid approximation and model compact stars through a multifluid framework. In this work, we present the fully general-relativistic description of adiabatic tidal deformations of compact stars composed of an arbitrary number of interacting fluids, using Carter's multifluid variational formalism. A distinctive feature of this approach is the presence of nondissipative mutual entrainment between fluid species. We derive the hydrostatic equilibrium equations for multifluid configurations, along with the perturbed equations governing stationary gravitoelectric and gravitomagnetic tidal responses of arbitrary order. We then investigate how entrainment modifies the corresponding tidal deformabilities. Using an analytical representation of the multifluid equation of state, we show that entrainment leaves adiabatic tidal responses unchanged and therefore produces no measurable effect on the gravitational-wave signal emitted during the inspiral long before the excitation of internal mode resonances. We subsequently discuss two specific applications: superfluid neutron stars and dark matter admixed compact stars. less

We present Q-Transform Amplitude Modulation (QTAM), a novel, fully invertible implementation of the Constant-Q Transform algorithm, designed to enable robust signal denoising and the disentanglement of overlapping transient events in current and next generation gravitational wave (GW) observatories. Time-frequency (TF) analysis faces a fundamental dichotomy: critically sampled transforms are computationally efficient but lack time-shift invariance, limiting their efficacy for robust pattern recognition and Deep Learning applications. While alternative approaches such as the Dual-Tree Complex Wavelet Transform provide efficient approximate shift-invariance, their wavelet constructions remain tied to dyadic scale frequency tilings that are poorly matched to the simultaneous representation of GW chirps and instrumental glitches. Conversely, overcomplete transforms provide the necessary shift-invariance and tunable frequency resolution, but their implementations generate highly redundant data volumes that are prohibitive for low-latency (LL) processing. Furthermore, standard attempts to compress these dense representations rely on lossy interpolation, destroying the phase coherence required to reconstruct the signal. QTAM bridges this gap by employing a methodology inspired by Amplitude Modulation radio broadcasting. By modeling the Q-transform output as a slowly varying complex envelope carried by a deterministic high-frequency term, we achieve lossless data decimation via spectral shifting to baseband. We demonstrate that QTAM is linear and fully invertible, allowing exact reconstruction of the original signal with machine precision while retaining the shift-invariance of dense spectrograms. Leveraging native GPU acceleration, QTAM enables TF pipelines to operate within LL O(1s) bounds. We validate the method's potential for denoising and disentanglement on GW data and signal injections. less

We investigate the connection between black hole shadow and quasinormal mode (QNM) spectra in the context of scalar--tensor--vector gravity (STVG) coupled to perfect fluid dark matter (PFDM), characterized by the MOG parameter $α$ and the dark matter intensity $λ$. Employing complementary methods -- namely the sixth-order WKB approximation, Padé resummation, and time-domain numerical integration -- we compute QNM frequencies for scalar ($s=0$), electromagnetic ($s=1$), and axial gravitational ($s=2$) perturbations. Both the real part of the QNM frequencies and the peak height of the effective potential display a consistent parametric dependence: they increase with $λ$ yet decrease with growing $α$. In the eikonal limit ($l \gg 1$), we derive an exact analytical link between the shadow radius $R_{\mathrm{sh}}$ and the QNM frequency $ω_R$. Noting that $R_{\mathrm{sh}}$ is determined by the critical impact parameter $b_c = r_{\mathrm{ph}}/\sqrt{f(r_{\mathrm{ph}})}$, while $ω_R = Ωl$ with photon angular velocity $Ω= \sqrt{f(r_{\mathrm{ph}})}/r_{\mathrm{ph}}$, we obtain the precise relation $ω_R = l / b_c$, identifying $R_{\mathrm{sh}} \equiv b_c$ for an asymptotically flat observer. This prediction is robustly validated by numerical results across all three computational approaches at large multipole numbers. Our findings reveal that the black hole shadow and gravitational ringdown are not independent phenomena, but dual observational signatures of the same underlying structure -- the unstable photon orbit -- thereby offering a unified multi-messenger framework to simultaneously constrain modified gravity and dark matter in the strong-field regime. less

The Sourlas-Lechner-Hauke-Zoller (SLHZ) scheme for quantum annealing uses the parity to encode logical variables and has several advantages, but it has not been implemented for large-scale quantum annealers. If the SLHZ-based approach can be implemented on currently available quantum annealers, we can evaluate its performance. An efficient method to embed the parity-encoded model into the hardware graphs of available quantum annealers is one of the key elements for this approach. We propose a qubit-efficient embedding scheme for parity-encoded Hamiltonians on quantum annealers with the Zephyr connectivity. We give an explicit constructive embedding of the interaction graph of an intermediate Hamiltonian, which contains only one- and two-body interactions, into the Zephyr graph. Our embedding maps each spin to a two-qubit chain using systematic chain-assignment rules. Its validity is verified via the resulting chain-to-chain connectivity. Our embedding also offers practical flexibility. Chains assigned to ancillary spins allow reduction to a single physical qubit, leading to options to avoid inactive qubits. The number of required qubits per spin in the parity Hamiltonian is three, which is fewer than that for a known embedding scheme for the Pegasus graph. less

Quantum metric learning enhances machine learning by mapping classical data to a quantum Hilbert space with maximal separation between classes. However, on current NISQ hardware, this mapping process itself is prone to errors and could be fundamentally incorrect. Verifying that a quantum embedding model successfully achieves its promised separation is essential to ensure the correctness and reliability. In this paper, we propose a practical black-box verification protocol to audit the performance of quantum metric learning models. We define a setting with two parties: a powerful but untrusted prover, who claims to have a parameterized unitary circuit that embeds classical data from different groups with a guaranteed angular separation, and a limited verifier, whose quantum capabilities are restricted to performing only basic measurements. The verifier has no knowledge of the implementation of the prover, including the structure of the model, its parameters, or the details of the prover measurement setup. To verify the separation between different data groups, the proposed algorithm must overcome two key challenges. First, the verifier is ignorant of the prover's implementation details, such as the optimization cost function and measurement setup. Consequently, the verifier lacks any prior information about the expected quantum embedding states for each group. Second, the destructive nature of quantum measurements prevents direct estimation of the separation angles. Our algorithm successfully overcomes these challenges, enabling the verifier to accurately estimate the true separation angles between the different groups. We implemented the proposed protocol and deployed it to verify the QAOAEmbedding models. The results from both theoretical analysis and practical implementation show that our proposal effectively assesses embedding quality and remains robust in adversarial settings. less

Trotter decomposition provides a simple approach to simulating open quantum systems by decomposing the Lindbladian into a sum of individual terms. While it is established that Trotter errors in Hamiltonian simulation depend on nested commutators of the summands, such a relationship remains poorly understood for Lindbladian dynamics. In this Letter, we derive commutator-based Trotter error bounds for Lindbladian simulation, yielding an $O(\sqrt{N})$ scaling in the number of Trotter steps for locally interacting systems on $N$ sites. When estimating observable averages, we apply Richardson extrapolation to achieve polylogarithmic precision while maintaining the commutator scaling. To bound the extrapolation remainder, we develop a general truncation bound for the Baker-Campbell-Hausdorff expansion that bypasses common convergence issues in physically relevant systems. For local Lindbladians, our results demonstrate that the Trotter-based methods outperform prior simulation techniques in system-size scaling while requiring only $O(1)$ ancillas. Numerical simulations further validate the predicted system-size and precision scaling. less

We introduce Exchange Quantum Polynomial Time (XQP) circuits, which comprise quantum computation using only computational basis SPAM and the isotropic Heisenberg exchange interaction. Structurally, this sub-universal model captures decoherence-free subspace computation without access to singlet states. We show that XQP occupies an intermediate position between BPP and BQP, as its efficient multiplicative-error simulation would collapse the polynomial hierarchy to its third level. We further provide evidence that additive-error simulation of XQP would enable efficient additive-error simulation of arbitrary BQP computations. Remarkably, the restricted family of XQP circuits consisting solely of $\sqrt{\mathrm{SWAP}}$ gates remains hard to simulate to multiplicative error. We additionally prove that circuits generated by $\sqrt{\mathrm{SWAP}}$ gates are semi-universal, generate $t$-designs for the uniform distribution over $SU(2)$-invariant unitaries, and maximise the entangling power within XQP. Finally, we derive structural results linking computational basis states in XQP to the Gelfand-Tsetlin basis of the symmetric group, and expressing XQP output probabilities as partition functions of the six-vertex and Potts models. Our findings indicate that XQP circuits are naturally suited to near-term hardware and provide a promising platform for experimental demonstrations of quantum computational advantage. less

Quantum computers have the potential to perform computational tasks beyond the reach of classical machines. A prominent example is Shor's algorithm for integer factorization and discrete logarithms, which is of both fundamental importance and practical relevance to cryptography. However, due to the high overhead of quantum error correction, optimized resource estimates for cryptographically relevant instances of Shor's algorithm require millions of physical qubits. Here, by leveraging advances in high-rate quantum error-correcting codes, efficient logical instruction sets, and circuit design, we show that Shor's algorithm can be executed at cryptographically relevant scales with as few as 10,000 reconfigurable atomic qubits. Increasing the number of physical qubits improves time efficiency by enabling greater parallelism; under plausible assumptions, the runtime for discrete logarithms on the P-256 elliptic curve could be just a few days for a system with 26,000 physical qubits, while the runtime for factoring RSA-2048 integers is one to two orders of magnitude longer. Recent neutral-atom experiments have demonstrated universal fault-tolerant operations below the error-correction threshold, computation on arrays of hundreds of qubits, and trapping arrays with more than 6,000 highly coherent qubits. Although substantial engineering challenges remain, our theoretical analysis indicates that an appropriately designed neutral-atom architecture could support quantum computation at cryptographically relevant scales. More broadly, these results highlight the capability of neutral atoms for fault-tolerant quantum computing with wide-ranging scientific and technological applications. less