Papers

We derive a generalized fluctuation-dissipation theorem (FDT) for vector fields in rotating thermal equilibrium from an exact phase-space Kubo-Martin-Schwinger (KMS) relation. The resulting FDT contains rotation-induced tensorial contributions beyond a scalar thermal factor. In the local transport limit, we obtain a model-independent generalized Einstein relation with rotation in which, through second order in thermal vorticity, symmetric momentum diffusion depends on low-frequency spectral information beyond that encoded in the rotation-dependent dissipative drag. Remarkably, we find a new Einstein-type relation linking zero modes in the spectral function to the nonrotating drag coefficient. These zero modes underlie a new mechanism for the orbital polarization of heavy quarkonium. The same FDT constraint yields a modified detailed-balance relation whose first-order vortical correction is governed by transition polarization, without explicit dependence on the bath model. Our findings establish microscopic equilibrium constraints for studying rotating quantum matter in various fields.

Quantum key distribution (QKD) links are provisioned from security analyses of stationary channels, whereas the devices that determine the channel drift between recalibrations. Whether an eavesdropper who cannot alter the channel's own noise gains by following that drift has not been quantified. Adaptive eavesdropping is posed here as a constrained Markov decision process in which the attacker selects one circuit per round while the noise level follows an Ornstein–Uhlenbeck process and the abort condition is a budget over each block of rounds. The value of adaptation is bounded by the best fixed circuit and a dynamic-programming upper bound. The actions are learnt attacks. Whereas Decker et al. trained a parametrised circuit on a fixed gate template against a fixed channel, here the gate structure and rotation angles are searched jointly. This yields circuits compact enough to form a discrete action set, extending the construction to noise models lacking a known template, including the amplitude damping channel. On device-independent E91 under bilateral depolarising noise, a reinforcement-learning attacker raises her Holevo information from $0.135$ for the best fixed circuit to $0.348$ at zero detection, $98\%$ of the upper bound. On BB84 under a drifting bit-flip channel, she exceeds a conservative noise-indexed rule by $0.024$ in fidelity, reaching $99\%$ of the upper bound. Under stationary noise, the attacker's gain from basis asymmetry changes sign between an averaged and a per-basis error-rate constraint. The search, started from random gate sequences, recovers the analytical cloners and the collective-attack key rate, and meets the lower bound of the Winick–Lütkenhaus–Coles objective from above.

Heavy-quark spin dynamics in the quark-gluon plasma provides a potential probe of the interaction between heavy quarks and the medium. We develop a stochastic framework in which the random momentum kicks responsible for heavy-quark diffusion also induce spin rotation through Thomas precession. Starting from the Thomas-Bargmann-Michel-Telegdi equation and a Langevin equation for heavy-quark momentum, we derive a novel coupled spin-momentum Fokker-Planck equation. In the heavy-quark limit, where momentum equilibrates faster than spin, the momentum degrees of freedom can be integrated out, yielding a rotational Fokker-Planck equation for the spin orientation. This establishes a direct relation between the Thomas precession contribution to the spin-relaxation time $\tau_{s}$ and the heavy-quark momentum-diffusion coefficient $\kappa$. In the non-relativistic limit, we find $\tau_s=2\tau_p(m_Q/T)^2$, with $\tau_p$ being the momentum relaxation time. Using recent determinations of $\kappa$ from lattice QCD, strong-coupling estimates, $T$-matrix calculations, and heavy-flavor phenomenology, we obtain the corresponding Thomas precession contribution to spin relaxation times for charm and bottom quarks. Relativistic kinematics modify the result by only a modest amount over the temperature range relevant for heavy-ion collisions, while the uncertainty is dominated by that of $\kappa$. We emphasize that the result represents the Thomas precession contribution to heavy-quark spin relaxation; direct coupling to the chromomagnetic field provides an additional channel.

We discuss the triality between stochastic growth models in the KPZ universality class, the DSSYK model, and low dimensional dilaton gravity. The TASEP model, which will be our primary focus, is identified with the strong-coupling limit of two-dimensional quantum gravity. The Hamiltonian of DSSYK and the transfer matrix of ASEP coincide up to an additive constant, and we derive the exact expression for the resolvent of the corresponding transfer matrix in ASEP on a finite interval. We also mention the relation of cumulants with the Tutte polynomial $T(1,q)$ of the crossing graph dual to the chord diagram, which implies the relationship of the models considered with the $Q=0$ Potts model coupled with gravity. We further exploit the realization of all these models in terms of different versions of discrete and continuous random walks on two-dimensional manifolds, which parameterize the Hilbert spaces of the respective theories. The representation of TASEP as the growth model of heaps provides new insight into strong-coupling gravity, suggesting its interpretation as an emerging phenomenon. The new dualities between ASEP and q-TASEP models and heap models providing a useful growth interpretation have been developed.

Informational steady states (ISSs) arise when the rate at which information is gained from continuous measurements is exactly balanced by the rate at which information from earlier measurements is lost to the environment. While ISSs have been studied in Markovian settings, relatively little is known about how memory effects influence their formation and steady-state properties. In this work, we investigate non-Markovian effects on ISSs within the framework of continuously monitored collision models. We model the environment as a sequence of two-qubit ancillas and find that, for this specific model, the steady-state information gain per measurement is negatively correlated with the degree of non-Markovianity. Numerical results further characterize how the system-ancilla and ancilla-ancilla interaction parameters influence both the degree of non-Markovianity and the steady-state information gain.

The growing scale and accessibility of quantum hardware exposed new reliability and security challenges in the quantum computing workflow, such as the run-time fault injection attacks in cloud-based quantum computing platforms. However, existing works fail to identify vulnerabilities with gate-level precision or adapt to run-time environments. In this work, we formulate gate-level fault analysis as a learning-guided prioritization problem under restricted fidelity budgets. The framework uses a circuit-DAG-based GNN backbone to predict the vulnerability score of each gate to each type of injected fault, defined as the impact of the gate-fault pair on circuit fidelity. The gate-fault pairs are then ranked by their vulnerability score. Experiments on QASMbench and HamLib MaxCut show that QUFIG recovers high-impact vulnerable gate-fault pairs with fewer inspections than random and depth-based heuristics. Our results show that QUFIG can reduce the number of gates requiring inspection by 2.9–19.8% while maintaining effective fault identification, allowing quantum circuit designers to identify vulnerabilities and apply targeted defenses more efficiently.

Hidden zeros impose constraints on scattering amplitudes beyond their familiar factorization properties. We explore their structure in two related directions. We first promote hidden zeros to explicit splitting formulas that organize full amplitudes at generic kinematics. Ordered $\mathrm{Tr}(\phi^3)$ amplitudes, nonlinear sigma model (NLSM) amplitudes, and cosmological wavefunctions share the same defining exact splitting structure $\mathcal A=\sum_\alpha R_\alpha\, {\mathcal J}_{\alpha,L}{\mathcal J}_{\alpha,R} {\mathcal J}_{\alpha,\mathrm{out}}$, adapted to any hidden zero. Each prefactor $R_\alpha$ is a condition of the hidden zero locus, so this decomposition manifests the hidden vanishing term by term. The remaining factors are lower point amplitudes or currents. Using these representations, we can systematically find new zero loci beyond the usual ones. In particular, we obtain five new all-multiplicity zero families. We also find continuous families of zeros: the coefficients of their defining equations can vary continuously while the amplitude remains zero.

The entanglement-assisted Hadamard test (EHT) is a practical method for estimating a quantum phase by amplifying the phase signal. However, the feasible amplification is fundamentally limited by the accuracy of the reference phase, such that the method is inefficient in the high-precision regime. In this work, we propose an algorithm, called adaptive entanglement-assisted Hadamard test (AEHT), that iteratively refines the reference phase, enabling progressively stronger amplification as the iteration goes by. We further consider the imperfect eigenstate preparation scenario, where a systematic bias is unavoidable when estimating the quantum phase with the conventional EHT. Such a bias can be suppressed by the proposed AEHT. Moreover, taking physical implementation into consideration, we adopt device-restart count to measure the cost of quantum phase estimation, rather than shot count. The numerical experiments confirm the effectiveness of the proposed AEHT compared with conventional methods under this measure. By unlocking the full amplification power of large entangled states, this work offers an efficient method to estimate high-precision quantum phase on near-term quantum processors.

Propagating the electronic and nuclear degrees of freedom of a molecule simultaneously is a challenging task, because the number of vibronic states grows exponentially with system size. We use the adaptive time-dependent density matrix renormalization group to perform simulations of the extended Hubbard-Peierls Hamiltonian, in which both the electronic and nuclear degrees of freedom are quantized. We describe our approach, and demonstrate it through converged calculations of the nonadiabatic dynamics of hexatriene. This simulation predicts a lifetime of the `bright' $\mathrm{1B_u}$ electronic state of approximately 40 fs. Our predictions for the population of the $\mathrm{1B_u}$ electronic state are in qualitative agreement with those obtained using the linear vibronic coupling model derived from the extended Hubbard-Peierls Hamiltonian in previous work.

The exceptionally large diamagnetic susceptibility of a single-crystal graphite in the direction perpendicular to the graphene layers is caused by the Landau levels. However, there are also other contributions to the magnetic susceptibility. In particular, in metals the Pauli paramagnetism is leading, whereas in dielectrics the diamagnetic Langevin and paramagnetic Van Vleck terms are essential. These components of magnetic susceptibility are also present in graphite. In this work, we calculate the magnitudes of all these small contributions from first principles. It is found that the Pauli paramagnetism is negligible (2.3 x 10^{-9} emu/g), whereas the other diamagnetic contribution - arising from the Langevin and Van Vleck mechanisms - is comparable to the in-plane experimental diamagnetism of graphite and to the diamagnetic response of C60 and C70} fullerenes. This diamagnetic contribution proves to be slightly anisotropic (-2.93 x 10^{-7} emu/g along the x- or y-axes and -2.24 x 10^{-7} emu/g along the $z-$axis), with the averaged value -2.7 x 10^{-7} emu/g.

A-GHOST (A Global Heterogeneous Online Scouting Trigger) is an R&D effort investigating high-rate streaming readout architectures for high-energy physics (HEP) experiments. The central idea is to convert the deterministic front-end and fixed-latency processing close to the detector from a decision-making platform to an aggregation and streaming source. Compact trigger-level data are streamed to a GPU-enabled backend, where substantially more complex algorithms can run beyond the resource and latency envelope of the hardware trigger. This paper presents a proof-of-concept backend using the NVIDIA IGX Thor development kit. A software rate-controlled transmitter sends data through a QSFP interface and external loopback cable to a second QSFP interface, allowing the network-to-GPU path to be studied before integration with FPGA sources. NVIDIA DAQIRI enables reception directly into GPU-accessible memory, while a custom CUDA kernel reassembles packet payloads into persistent, contiguous TensorRT input windows without data-type conversion, which is handled by the models. Using a HEP-derived event representation consisting of the ten leading calorimeter clusters, the backend scales from 40 to 100 Gbps while sustaining a constant input rate and an inference latency of 0.118 ms at the p95 interval. The system operates for multiple hours without drops or inference errors. Generative and temporally aware neural networks demonstrate workloads beyond those normally deployed in fixed-latency FPGA trigger systems. The result establishes A-GHOST as a basis for future FPGA-to-GPU streaming readout systems.

We derive the tree-level interaction vertices of the linear sigma model with quarks in the presence of global rotation. Starting from the scalar and fermionic field solutions in a rotating background, we construct the corresponding spectral representations and use them to evaluate the mesonic self-interactions and Yukawa couplings of the model. We show that rotation modifies the usual momentum-space structure of the interaction vertices: conservation of longitudinal momentum is accompanied by angular-momentum selection rules, while the transverse dynamics is encoded in rotation-induced radial form factors involving products of Bessel functions. The resulting expressions provide a set of interaction rules adapted to the symmetries and finite geometry of the rotating system. Although derived within the linear sigma model with quarks, the structures obtained for scalar self-interactions and scalar-fermion couplings can be extended to a broader class of quantum field theories under global rotation. These results provide the building blocks for perturbative calculations and contribute toward a microscopic quantum-field-theoretical description of interacting matter in rotating environments.

The discovery of spin-density-wave (SDW) order in bilayer nickelates has intensified interest in its interplay with superconductivity. Unlike cuprates, where doping rapidly suppresses the Néel temperature, the SDW transition temperature ($T_{\mathrm{SDW}}$) in bilayer nickelates is robust against oxygen annealing and even increases under pressure. Here, we combine oxygen annealing with isovalent rare-earth ($A$-site) substitution to effectively apply $c$-axis uniaxial pressure, realizing superconducting bilayer nickelate films with $T_{\mathrm{SDW}}$ suppressed from 150 K to 70 K. Notably, while SDW order is weakened but remains, a second charge-like anisotropy order is completely eliminated in the superconducting state. Polarization-resolved O $K$-edge X-ray absorption and electronic structure calculations show that strengthened interlayer coupling reconstructs the Fermi surface and weakens the SDW. These findings, consistent with a spin-spinless stripe ground state, provide new insight into the mechanism of density wave formation and their interplay with superconductivity.

Goniopolar metals exhibit opposite thermoelectric polarities along different crystallographic directions, enabling zero-field transverse thermoelectricity but offering few means for external control. Here we show that a spatially structured Laguerre–Gaussian vector potential can programmably reconstruct the goniopolar phase space of NaSn$_2$As$_2$. First-principles-derived Wannier transport with bond-dependent Peierls coupling reveals two OAM-dependent spatial scaling laws: the radial response follows the Laguerre–Gaussian radius $r_{\max}\propto\sqrt{|\ell|}$, while calculations for $|\ell|=2$–5 yield a dominant angular harmonic $m_{\mathrm{dom}}=2|\ell|$, encoding the optical winding in a frequency-doubled thermoelectric response. Increasing $|\ell|$ simultaneously reconstructs pre-existing goniopolar windows, enhancing a representative window by approximately 17% at $|\ell|=5$. By contrast, reversing $\ell$ at fixed polarization produces only a small correction that approximately interchanges upon polarization reversal. Energy-resolved transport reveals that the structured field redistributes in-plane and cross-plane electronic velocities, shifting the directional Seebeck-zero boundaries that define the goniopolar state. These results establish vortex position and OAM magnitude as programmable control coordinates for goniopolar thermoelectricity.

In this work, we study bipartiteness and expansion testing, two canonical problems in graph property testing in the bounded-degree model through the lens of quantum query complexity. In the classical setting, it is known that $\widetilde{\Theta}(\sqrt{N})$ queries are necessary and sufficient for both these testing problems (Goldreich and Ron, 1999, 2000 & 2002), where $N$ denotes the number of vertices of the input graph. Due to their significance, (Ambainis, Childs, and Liu, 2011) initiated the study of these problems in the quantum setting and designed quantum algorithms for bipartiteness and expansion testing that perform $\widetilde{O}(N^{1/3})$ queries, showing a polynomial speedup. They also proved that $\widetilde{\Omega}(N^{1/4})$ queries are necessary for expansion testing, but the possibility of an exponential quantum advantage for bipartiteness testing remained open. Despite significant effort, there has been no improvement in these results in the last decade and a half. In this work, we prove essentially tight $\widetilde{\Omega}(N^{1/3})$ quantum query lower bounds for both bipartiteness and expansion testing, thereby completely characterizing the quantum query complexity of these problems up to polylogarithmic factors. While our proofs use the polynomial method similarly to Ambainis, Childs, and Liu, we use intermediate problems that we relate to the main problems via reductions, and perform a more precise analysis of the resulting polynomials, leading to the near-optimal lower bounds.

Heterogeneous high–performance computing architectures expose numerical algorithms to perturbations arising from the non–associativity of floating–point arithmetic. In Large–Eddy Simulation (LES), similar numerical effects may become relevant when they affect the filter–width entering the subgrid scale (SGS) model. This work investigates this mechanism for the least–squares (LSQ) based filter–width formulation, focusing on how floating–point effects are generated, transmitted, and coupled with the resolved flow. We show that, for fixed resolved kinematics, the LSQ filter–width is logarithmically non-expansive but not strictly contractive with respect to perturbations of the mesh metrics. Consequently, small disturbances may be transmitted with little attenuation through strongly directional filter-width responses. To mitigate this sensitivity, we introduce a scalar max–min compression of the directional mesh scales together with a bounded modulation based on the resolved velocity gradient. The resulting formulation reroutes floating–point perturbations through the filter-width operator, improving robustness while preserving the flow–dependent character of the original LSQ construction. The framework is assessed on heterogeneous CPU and GPU architectures for flow past a circular cylinder at Re=3900 and the Taylor–Green vortex at Re=1600. In the former, nearly one–to–one transmission of relative metric disturbances can become relevant when the transmitted perturbations interact with shear-layer transition. By contrast, on orthogonal Taylor–Green vortex grids, the accumulation pathway is structurally absent and no comparable macroscopic response develops. These results suggest floating–point sensitivity matters for LES filter–width formulations in heterogeneous computing environments.

Light-pulse atom interferometry has emerged as a promising approach for developing quantum inertial and gravity sensors for real-world applications, but achieving robust operation in dynamic environments without sacrificing sensitivity remains challenging. To mitigate performance degradations resulting from vibration-induced noise and mismatches in the spatial overlap between free-falling atoms and light pulses, we demonstrate a first-of-a-kind high-data-rate, high-sensitivity grating magneto-optical trap (GMOT)-based light-pulse atom interferometer (LPAI). This system uses a compact, rugged GMOT architecture, based on an in-vacuum microfabricated grating chip and a single laser-cooling beam, to enable high-data-rate GMOT-based cold-atom generation with sub-Doppler cooling. Our GMOT-based LPAI operates at high data rates (up to 100 Hz), while simultaneously achieving both high acceleration sensitivity (550 ng/rt-Hz at 20 Hz, 1.49 ug/rt-Hz at 45 Hz, and 6.31 ug/rt-Hz at 70 Hz) and good bias stability (71 ng). This compact, rugged architecture paves the way for field-deployable quantum inertial and gravity sensors in high dynamics and for time-multiplexed, multi-axis inertial sensing.

The origin of chirality-induced spin selectivity (CISS) remains elusive, and ultrahigh spin polarization (SP) in topologically knotted molecules is unexplained. We develop a discrete geometric spin-orbit coupling (SOC) framework for molecular junctions, resolving site-specific curvature and current-partition effects beyond continuous models. For trefoil-knot molecules, it quantifies site-resolved geometric SOC, reaching $\sim$120 meV, nearly two orders of magnitude larger than intrinsic SOC of light atoms. The substrate-coupled benzene unit, carrying the largest current and remarkable geometric SOC, dominates the CISS effect. The framework quantitatively reproduces measured SP, temperature-dependent magnetoresistance (MR) and $\Delta$MR trends, establishing discrete geometric SOC as a predictive tool for CISS in topologically knotted molecules.

We investigate how root allometry and below-ground root competition due to root overlap affect the conditions for pattern formation in non-local scalar vegetation models. We start from a spatially explicit two-component vegetation-water system in which plants acquire soil water through their laterally extended root systems, with root allometry represented by an interaction kernel whose spatial extent increases with the above-ground biomass density. In the limit of fast water dynamics, we eliminate the water variable, resulting in a non-local scalar model for the vegetation dynamics. This reduction reveals that accounting for root overlap naturally leads to a double integral structure in the scalar model, in contrast to the single convolution term commonly used to model non-local competition for resources. For the resulting scalar model, we identify two distinct mechanisms that can drive Turing instabilities. The first instability mechanism requires root growth to outpace mortality, while the second mechanism relies on the development of competitive pressure zones, in which vegetation growth is impeded by the cumulative competitive pressure exerted by neighbouring areas with higher biomass density. Root allometry promotes the occurrence of both instability mechanisms, while root overlap inhibits the emergence of competitive pressure zones. Hence, our results show that both root allometry and root overlap are important features to consider when studying vegetation pattern formation.

Conceptual density functional theory (CDFT) defines chemical reactivity descriptors as derivatives of the electronic energy with respect to the number of electrons and the external potential, or combinations thereof; in practice, however, researchers almost always replace these derivatives with finite-difference and frontier-orbital approximations, and no common software exists for their analytical evaluation. We present PyCDFT, to our knowledge, the first standardized, open-source, and scriptable code that analytically computes the descriptors of conceptual density (matrix) functional theory for ground and excited states up to second order, including the orbital hardness, the Fukui function and Fukui matrix, and the linear response function, from a single converged mean-field wavefunction imported from virtually any electronic-structure package. The descriptors are obtained from matrix-free, preconditioned Krylov-subspace solutions of the coupled-perturbed self-consistent-field equations for both spin-unpolarized and spin-polarized references, with the work distributed over MPI ranks and all data flowing through a single HDF5 checkpoint file that supports restart, post-processing, and the export of real-space descriptors as cube files for visualization. The design delegates integrals, grids, and exchange-correlation kernels to PySCF and Libxc, keeping the library compact, user-friendly, and interoperable. Worked examples on the ground state of H$_2$O and a broken-symmetry $\Delta$SCF excited state of NH$_3$ show that a complete second-order CDFT analysis requires only a few lines of user code.

Bismuth telluride (Bi2Te3) is a prototypical V-VI semiconductor of interest for both thermoelectric and topological applications; however, phase-selective synthesis and thermal stability across the bismuth-telluride homologous series remain poorly understood. We report a facile and phosphine-free colloidal synthesis approach for a phase-selective synthesis of Bi2Te3, BiTe, and Bi4Te5 nanosheets with well-defined hexagonal morphology. By controlling precursor chemistry and reaction temperature, we achieved the selective formation of different phases within the (Bi2)m(Bi2Te3)n homologous series. Based on in situ heating studies, BiTe and Bi4Te5 nanosheets transform into Bi2Te3 at about 340 degree C, followed by preferential Te sublimation under vacuum or oxidation in air at higher temperatures. We discuss plausible mechanisms for these phase transformations. EDS analysis and FFT analysis of STEM images provide direct evidence for the temperature-dependent compositional and structural changes and highlight the close thermal relationship among these phases. These results not only advance fundamental understanding of phase stability and thermal behavior in bismuth-tellurides at the nanoscale but also establish a framework for understanding structural evolution in related homologous series, providing insights into their potential future applications in thermoelectric, spintronic, and topological systems.

We report thick target yields of $^{65}{\rm Cu}(\alpha,n)^{68}{\rm Ga}$ from $\alpha$ energies $E_{\alpha}$$=$6.5–8~MeV measured via neutron-counting at the Edwards Accelerator Laboratory at Ohio University. Our results agree with prior results based on single-foil irradiations, while disagreeing with thick-target yields inferred from stacked-foil irradiations by up to an order of magnitude. Based on comparisons of our and prior measurements to Hauser-Feshbach calculations, we estimate the thick-target yield for $^{68}{\rm Ga}$ from $E_{\alpha}$=14~MeV impinging on 100%-enriched copper ($^{65}{\rm Cu}$) is 161$^{+5}_{-24}$~MBq/$\mu$Ah (for He$^{++}$), which is in agreement with the current IAEA estimate of 156~MBq/$\mu$Ah. At $E_{\alpha}$$=$8~MeV, where radioimpurity-free production of $^{68}{\rm Ga}$ could be realized with a natural copper target, our yield estimate is nearly 4$\times$ lower than the IAEA estimate. We find that the $^{65}{\rm Cu}(\alpha,n)$ cross section estimates presently employed for neutrino and dark matter detector backgrounds and the $^{65}{\rm Cu}(\alpha,n)$ astrophysical reaction rate recently recommended for nucleosynthesis calculations are in agreement with our measurement results.

Control of molecular angular momentum orientation enables state-resolved studies of molecular interactions and provides a basis for quantum information processing. Here we propose all-optical Autler-Townes state-selective adiabatic passage (ASAP) to prepare molecules in a single $|J,M\rangle$ sublevel. An Autler-Townes branch created by a strong coupling field is selectively populated and adiabatically mapped onto the target vibrational state. We resolve detuning-dependent rovibrational Autler-Townes splitting in $^{13}$CO$_2$, establishing the spectroscopic basis for the selective excitation of the target dressed branch. The density-matrix model calibrated by these spectra predicts transfer approaching 90%. The scheme can exploit millisecond vibrational radiative lifetimes within the electronic ground state and extend to polar and nonpolar molecules with infrared-active vibrational modes.

We report the synthesis and comprehensive investigation of single-crystalline Tb$_2$IrAl$_4$Ge$_2$ and Er$_2$IrAl$_4$Ge$_2$, the first Ir-based members of the $Ln_2M$Al$_4$Ge$_2$ family. Both compounds crystallize in the tetragonal Tb$_2$NiAl$_4$Ge$_2$-type structure (space group $I4/mmm$) and exhibit easy-axis magnetic anisotropy with the crystallographic $c$ axis as the preferred magnetization direction. Tb$_2$IrAl$_4$Ge$_2$ undergoes antiferromagnetic ordering below $T_N = 25$ K and develops a sequence of field-induced metamagnetic transitions accompanied by pronounced magnetotransport anomalies, including a nonlinear Hall response. In contrast, Er$_2$IrAl$_4$Ge$_2$ exhibits three successive zero-field magnetic transitions and a substantially richer low-temperature magnetic phase diagram comprising multiple competing field-induced phases confined to relatively modest magnetic fields. The differences between the Tb- and Er-based compounds demonstrate the wide range of magnetic behavior that can be realized within the \ce{Tb2NiAl4Ge2}-type structure. More broadly, the successful realization of Ir-based $Ln_2M$Al$_4$Ge$_2$ compounds considerably expands the accessible chemical space of this family and opens a route toward the exploration of related $4d$- and $5d$-based aluminogermanides.

In-context learning (ICL) enables a pretrained model to infer a task from demonstrations without updating its parameters. While much of the existing theory focuses on linear target functions, in this paper we study nonlinear cases by comparing two one-layer attention architectures on the same family of single-index tasks. A kernel learner first maps inputs through a fixed nonlinear feature map and then applies linear attention, whereas a feature learner applies attention to the original input, followed by a learned nonlinear readout. We derive predictions for their memorization and generalization errors using the replica method, retaining the effects of pretraining size, task-pool diversity, and training and inference context lengths. The resulting predictions closely match numerical experiments across a broad range of regimes. Our analysis yields phase diagrams that characterize when each architecture is advantageous as the amount of pretraining data, task diversity, and context lengths vary. We further identify qualitatively different context-length scalings for the two learners. Together, these results clarify how architectural choices interact with the dataset and govern nonlinear in-context learning.

We demonstrate the complete observation of a black-hole lightring resonance in an optical analogue. To do so, we generalize the concept of the photon sphere to non-stationnary systems by showing that the lightring is associated to a spatiotemporal caustic and that its complex frequency is determined by the propagation and divergence of this caustic. For an optical soliton acting as an analogue black-hole potential, we predict a characteristic spectral plateau whose boundaries are set by the real part of the lightring frequency, while its spectral decay is governed by the imaginary part. Using a pump-probe experiment in a 5-km-long dispersion-shifted fiber, we observe these signatures for two distinct pump wavelengths. The measured spectra agree with numerical simulations and with the predicted lightring-mode profile, providing direct access to both the oscillatory and decay properties of the resonance. Our results establish a direct experimental connection between black-hole lightrings, spacetime caustics, and quasinormal-mode spectroscopy in a dispersive analogue system.

Quantum algorithms are usually optimized for gate count or circuit depth. We find on Quantinuum System Model H2 quantum computer that for a tight-binding chain ground state preparation, there is a system size $N$ beyond which the adiabatic evolution reaches significantly lower energies than the Fermionic Fourier Transform (FFT), with the same number of gates, and with the same circuit depth. We attribute this high noise sensitivity of the FFT to its high precision, being able to distinguish momenta by $1/N$. This high resolution in momentum space requires long-range couplings in real space, which propagates errors faster. In contrast, although local and physical circuits such as the adiabatic evolution have a coarser momentum resolution, they also propagate errors more slowly. For physical applications, high momentum resolution is rarely required and is often worth trading for low noise sensitivity. We also introduce a momentum measurement scheme that although less precise than FFT, is less costly and less noisy. We show that it achieves better performance than FFT for spectral function measurement on Quantinuum System Model H2 quantum computer. Our work emphasizes the importance of reducing the noise sensitivity of quantum algorithms, beyond the number of gates or circuit depth.

We study the interplay between local stroboscopic measurements and the unitary quantum circuit dynamics of the deterministic Floquet-quantum East model. We derive exact analytical results for the probability of first detecting a subset of qubits back in their initial state. This is achieved via a renewal equation linking the first-detection probability to the subsystem Loschmidt echo, which encodes the effective open dynamics of the monitored qubits. The resulting statistics exhibit two regimes set by the competition between the measurement probing time and the relaxation timescale of the unitary circuit dynamics: while infrequent monitoring leads to geometric first-detection statistics, frequent monitoring induces correlations that manifest as deviations from this geometric behavior. These results provide a rare exact characterization of how local measurement backaction reshapes detection statistics in an interacting quantum many-body system. In our local protocol, return probabilities are controlled by the size of the monitored subregion and can therefore be accessed on digital quantum simulators via local mid-circuit measurements.

The smallness of polytropic index $\Gamma_\varepsilon \lesssim 1.75$ and near conformality of sound velocity $c_s^2 \approx 1/3$ in neutron star matter are usually referred to as signals of the emergence of quark matter. We construct a density-resolved nucleonic reference domain in the \((P/P_{\rm free},\Gamma_\varepsilon)\) plane using nucleonic EoSs jointly constrained by nuclear matter properties and neutron star mass, radius and tidal data, and found that the domain extends unambiguously below \(\Gamma_\varepsilon=1.75\). Crucially, the nucleonic domain becomes stable against the truncation order only after \(Z_0\) and \(Z_{sym}\) are included, showing that the higher-order density dependence controls the extrapolation from finite nuclei to neutron-star matter. These findings therefore provide concrete targets for finite-nucleus and heavy-ion experiments, while linking terrestrial nuclear physics directly to multimessenger observations. We compare the domain with smooth equations of state generated by neural networks without phase labels and represented by symbolic regression. Among these reconstructions, \(35.29\%\) have complete trajectories inside the nucleonic domain over \(0.5\leq n/n_0\leq8\). Within the EoS sample obtained after minimizing the multimessenger loss, the smallest value of \(\max_n c_s^2(n)\) is 0.38, above the conformal value $1/3$. In conclusion, we convert microscopic interpretation into a falsifiable, density-resolved null-hypothesis test and show quantitatively that current observations do not reject the nucleonic null over much of the admissible space of equation of state.

Exploring the world of Bell inequalities requires numerical methods that scale effectively with the number of parties, inputs, and outputs. Such methods can be used to study large-scale Bell inequalities beyond the reach of analytic methods, to design experiments for violating more complicated Bell inequalities, and to enable applications of Bell inequality violation. Such applications include randomness generation and multi-agent coordination with restricted communication. However, current general purpose optimizers such as the see-saw method struggle to handle Bell inequalities with only a dozen inputs and outputs. We introduce an optimizer for the quantum value of a Bell inequality based on batched gradient descent (BGD). More precisely, our BGD optimizer is a differentiable search over feasible quantum strategies in which states and projective measurements are generated from unconstrained variables. The Bell expression is evaluated by a direct tensor contraction without forming the prohibitively large Bell operator. This formulation makes parallel random restarts inexpensive and is thus naturally implemented by a GPU. We evaluate our optimizer against the see-saw method and find a significant speedup for a wide variety of Bell inequality families. Implemented on a GPU, our BGD optimizer can optimize Bell inequalities in our numerical experiments with more than a thousand inputs or outputs within minutes. For these large-scale Bell inequalities, we also efficiently compute the classical value by enumerating possible strategies using a GPU or expressing the optimization as a mixed-integer linear program. Our optimizers can serve as numerical evaluation tools for Bell experiments and multi-agent coordination problems modeled by Bell inequalities with many inputs and outputs, a common feature of real-world scenarios such as high frequency trading and distributed systems.