Local networks of neurons are nonlinear systems driven by synaptic currents elicited by its own spiking activity and the input received from other brain areas. Synaptic currents are well approximated by correlated Gaussian noise. Besides, the population dynamics of neuronal networks is often found to be multistable, allowing the noise source to induce state transitions. State changes in neuronal systems underlies the way information is encoded and transformed. The characterization of the escape time from metastable states is then a cornerstone to understand how information is processed in the brain. The effects of correlated input forcing bistable systems have been studied for over half a century, nonetheless most results are perturbative or valid only when a separation of time scales is present. Here, we present a novel and exact result holding when the correlation time of the noise source is identical to that of the neural population, hence solving in a very general setting the mean escape time problem.

Dense spin ensembles in solids present a natural platform for studying quantum many-body dynamics. Multiple-pulse coherent control can be used to manipulate the magnetic dipolar interaction between the spins to engineer their dynamics. Here, we investigate the performance of a series of well-known pulse sequences that aim to suppress interspin dipolar couplings. We use a combination of numerical simulations and solid-state nuclear magnetic resonance experiments on adamantane to evaluate and compare sequence performance. We study the role of sequence parameters like interpulse delays and resonance offsets. Disagreements between experiments and theory are typically explained by the presence of control errors and experimental nonidealities. The simulations allow us to explore the influence of factors such as finite pulse widths, rotation errors, and phase transient errors. We also investigate the role of local disorder and establish that it is, perhaps unsurprisingly, a distinguishing factor in the decoupling efficiency of spectroscopic sequences (that preserve Hamiltonian terms proportional to $S_z$) and time-suspension sequences (which refocus all terms in the internal Hamiltonian). We discuss our findings in the context of previously known analytical results from average Hamiltonian theory. Finally, we explore the ability of time-suspension sequences to protect multispin correlations in the system.

We introduce and analyze an active steering protocol designed to target multipartite entangled states. The protocol involves multiple qubits subjected to weak Bell-pair measurements with active feedback, where the feedback operations are optimized to maximize the quantum Fisher information. Our scheme efficiently reaches a genuinely entangled one-parameter state manifold. Numerical simulations for systems with up to 22 qubits suggest that the protocol is scalable and allows for high multipartite entanglement across the system.

Bremsstrahlung MeV x rays with high doses are essential for radiography of dense objects. Intense, short-pulse laser-driven MeV x-ray sources offer a promising solution, but understanding how the dose scales with laser intensity is crucial for their development. While theory predicts a square root scaling with laser intensity, experimental verification has been hindered by significant shot-to-shot variations, often exacerbated by long preplasma scale lengths from low laser contrast. Here, we demonstrate low shot-to-shot dose variation and confirm the theoretical scaling using high-contrast OMEGA EP laser interactions with millimeter-thick tantalum foils, achieving MeV x-ray doses up to 5.4 rad at 1 m for $E_{\mathrm{photon}}>$ 500 keV. Simulations reveal that the unique focal spot of the OMEGA EP laser enables efficient x-ray generation and reduced variability by facilitating deeper laser penetration into dense plasma, even with shorter preplasma scale lengths.

The investigation of methods to control and optimize the physical properties of the intrinsic magnetic topological insulator (TI) ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ is a critical challenge for the development of functional materials for quantum technologies and spintronics. The promising approach is to substitute Mn atoms with Ge, Sn, or Pb atoms in the $\left({\mathrm{Mn}}_{1-x}{A}_x^{\mathrm{IV}}\right){\mathrm{Bi}}_2{\mathrm{Te}}_4$ ($A^{\mathrm{IV}}=\mathrm{Ge},\mathrm{Sn},\mathrm{Pb}$) solid solutions. This substitution enables manageable tuning of the system's magnetic and electronic properties. In this study, we present a detailed investigation of the electronic structure evolution in $\left({\mathrm{Mn}}_{1-x}{\mathrm{Pb}}_x\right){\mathrm{Bi}}_2{\mathrm{Te}}_4$ as a function of Pb concentration, using a variety of angle-resolved photoemission spectroscopy based techniques, including photon-energy-dependent studies, spin-resolved, and circular dichroism (CD) measurements. Special emphasis was placed on identifying experimental evidence of the theoretically predicted topological phase transitions (TPTs) in $\left({\mathrm{Mn}}_{1-x}{\mathrm{Pb}}_x\right){\mathrm{Bi}}_2{\mathrm{Te}}_4$ near $x\approx 50$%. The criteria for detecting TPT include the presence or absence of topological surface states (TSS) in the electronic structure, which can be identified by their characteristic helical spin structure in spin-resolved or CD spectra, as well as the closure of the bulk band gap. Our results show that the bulk gap in the ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ -like electronic structure decreases gradually with increasing Pb concentration up to 40%, where it almost closes. From 40% to 60%, the band gap remains unchanged, and above 80%, the ${\mathrm{PbBi}}_2{\mathrm{Te}}_4$ -like electronic structure emerges, with the bulk gap reopening. Additionally, the TSS were detected in $\left({\mathrm{Mn}}_{1-x}{\mathrm{Pb}}_x\right){\mathrm{Bi}}_2{\mathrm{Te}}_4$ samples with Pb concentrations up to at least 30% and beyond 80%, correlating with the regions where the bulk gap is open. However, no TSS were observed at $x\approx 55$%, indicating that the system is in topologically distinct phase compared to ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ or ${\mathrm{PbBi}}_2{\mathrm{Te}}_4$. At this concentration, the system may be in a semimetallic state or a trivial insulator phase with a very narrow bulk gap. The demonstrated tunability of the electronic structure in $\left({\mathrm{Mn}}_{1-x}{\mathrm{Pb}}_x\right){\mathrm{Bi}}_2{\mathrm{Te}}_4$ highlights its potential for further exploration in topological and spintronic applications.

Discovering new superionic materials is essential for advancing solid-state batteries, which offer improved energy density and safety compared to traditional lithium-ion batteries with liquid electrolytes. Conventional computational methods for identifying such materials are resource-intensive and not easily scalable. Recently, universal interatomic potential models have been developed using equivariant graph neural networks. These models are trained on extensive datasets of first-principles force and energy calculations. One can achieve significant computational advantages by leveraging them as the foundation for traditional methods of assessing the ionic conductivity, such as molecular dynamics or nudged elastic band techniques. However, the generalization error from model inference on diverse atomic structures arising in such calculations can compromise the reliability of the results. In this work, we propose an approach for the quick and reliable screening of ionic conductors through the analysis of a universal interatomic potential. Our method incorporates a set of heuristic structure descriptors that effectively employ the rich knowledge of the underlying model while requiring minimal generalization capabilities. Using our descriptors, we rank lithium-containing materials in the Materials Project database according to their expected ionic conductivity. Eight out of the ten highest-ranked materials are confirmed to be superionic at room temperature in first-principles calculations. Notably, our method achieves a speed-up factor of approximately 50 compared to molecular dynamics driven by a machine-learning potential, and it is at least 3000 times faster compared to first-principles molecular dynamics.

The codespace of a quantum error-correcting code can often be identified with the degenerate ground space within a gapped phase of quantum matter. We argue that the stability of such a phase is directly related to a set of coherent error processes against which this quantum error-correcting code (QECC) is robust: such a quantum code can recover from adiabatic noise channels, corresponding to random adiabatic drift of code states through the phase, with asymptotically perfect fidelity in the thermodynamic limit, as long as this adiabatic evolution keeps states sufficiently “close” to the initial ground space. We further argue that when specific decoders—such as minimum-weight perfect matching—are applied to recover this information, an error-correcting threshold is generically encountered within the gapped phase. In cases where the adiabatic evolution is known, we explicitly show examples in which quantum information can be recovered by using stabilizer measurements and Pauli feedback, even up to a phase boundary, though the resulting decoding transitions are in different universality classes from the optimal decoding transitions in the presence of incoherent Pauli noise. This provides examples where nonlocal, coherent noise effectively decoheres in the presence of syndrome measurements in a stabilizer QECC.

The ability of the quantum approximate optimization algorithm (QAOA) to deliver a quantum advantage on combinatorial optimization problems is still unclear. Recently, a scaling advantage over a classical solver was postulated to exist for random 8-SAT at the satisfiability threshold. At the same time, the viability of quantum error mitigation for deep circuits on near-term devices has been put into doubt. Here we analyze the QAOA's performance on random Max-$k\text{XOR}$ as a function of $k$ and the clause-to-variable ratio. As a classical benchmark, we use the mean-field approximate optimization algorithm and find that it performs better than or equal to the QAOA on average. Still, for large $k$ and numbers of layers $p$, there may remain a window of opportunity for the QAOA. However, by extrapolating our numerical results, we find that reaching high levels of satisfaction would require extremely large $p$, which must be considered rather difficult both in the variational context and on near-term devices.

Microwave shielding is an important technique that can suppress the losses that arise from collisions of ultracold polar molecules. It has been instrumental in achieving molecular Bose-Einstein condensation (BEC) for NaCs [Nature (London) 631, 289 (2024)]. We demonstrate that microwave shielding is universal, in the sense that the two-body collision properties of different molecules are very similar when expressed in suitable reduced units of length and energy. This applies to rate coefficients for inelastic scattering and loss, to scattering lengths, and to the properties of two-molecule bound states. We also explore the small deviations from universality that arise at very large Rabi frequencies. In general, the collision properties are near-universal except when the Rabi frequency exceeds a few percent of the molecular rotational constant. The universality extends to elliptically polarized microwaves and to combinations of multiple fields. Our results indicate that the methods that have been used to achieve BEC for NaCs can be transferred directly to most other polar molecules.

The analysis of signal data plays a fundamental role across diverse scientific fields, where the high-precision estimation of peak parameters such as intensity, position, bandwidth, and area is essential for advancing scientific progress. However, understanding how these parameters are influenced by profile shape and instrumentation remains a key challenge, as these factors fundamentally determine the precision and efficiency of analytical measurements. To address this, we derive analytical solutions for the precision of Lorentzian profile peak parameters under Poisson noise constraints using the Cramér–Rao inequality and Fisher information. By comparing these precision limits with those of Gaussian profiles, we identify the peak characteristics that strongly influence parameter precision. Our results demonstrate that the profile slope and tail intensity are critical factors for estimating peak position and position differences, with Gaussian profiles exhibiting higher precision under identical conditions. Conversely, the weaker intensity–bandwidth correlation in Gaussian profiles contributes to their superior precision in intensity and bandwidth estimation. Additionally, Lorentzian profiles show a $\sqrt{3}$-fold improvement in area ratio precision over intensity ratio precision, surpassing the corresponding improvement in Gaussian profiles. This distinction arises from the larger area and stronger intensity–bandwidth correlation inherent in Lorentzian profiles. These findings highlight the significant impact of profile shape on peak parameter precision, providing essential guidance for decision-making in instrument design and analytical conditions. By integrating these analytical solutions with insights from analytical chemistry, we establish a theoretical framework linking peak parameter precision with instrument performance. This framework enables quantitative evaluation of the effects of equipment and experimental design improvements on measurement precision. As a practical application, we numerically demonstrate how enhanced instrument conditions improve the precision of isotope ratio measurements of $\mathrm{C}{\mathrm{O}}_2$ using Raman spectroscopy. Our findings provide practical guidelines for instrument optimization and budget planning, ultimately supporting high-precision analytical applications.

By generalizing Gao's approach [Phys. Rev. A 58, 1728 (1998)] for solving the Schrödinger equation for an isotropic van der Waals (vdW) potential to the systems with a multiscale anisotropic long-range interaction, we derive the solutions for the Schrödinger equation for an anisotropic dipole-dipole interaction plus an isotropic attractive vdW potential, i.e., $C_d(1-3{cos}^2\theta )/r^3-C_6/r^6$, which is projected to the subspace with angular momentum $l\le l_{\mathrm{cut}}$, with $l_{\mathrm{cut}}$ being an arbitrary angular-momentum cutoff. Here $\theta$ is the polar angle of the coordinate $\mathit{r}$ and $r=\left|\mathit{r}\right|$. The asymptotic behaviors of these solutions for $r\to 0$ and $r\to \infty$ are obtained. The generalization of our approach for the case of an anisotropic vdW potential is also discussed. These results can be used in the research of collisions and chemical reactions between ultracold polar molecules in a static electric field. Our approach to derive the solutions can be applied to the systems with a general long-range potential ${\sum }_{\lambda =2}^{{\lambda }_{\max }}{V}_{\lambda }(\theta ,\phi )/r^{\lambda }$, with $\phi$ being the azimuthal angle of $\mathit{r}$, and thus can be used in collision problems between various kinds of molecules, ions, or atoms (e.g., the collisions between ultracold dipolar atoms).

Quantum entanglement is a vital phenomenon required for realizing secure quantum networks, so much that distributed entanglement can be reimagined as a commodity which can be traded to enable and maintain these networks. We explore the idea of commercializing entanglement-based cryptography and future applications where advanced quantum memory systems support less advanced users. We design a sneakernet-based quantum communication network with a central party connecting the users through delayed choice quantum entanglement swapping, using quantum low-density-parity-check (qLDPC) encoded qubits on neutral atoms. Our analysis compares this approach with traditional surface codes, demonstrating that qLDPC codes offer superior scaling in terms of resource efficiency and logical qubit count. We show that with near-term attainable patch sizes, one can attain medium- to high-fidelity correlations, motivating further research towards the long-term realization of large-scale commercial quantum networks.

We identify the optimal protocols to achieve the minimum entropy production in finite-time information exchange processes in Langevin systems, on the basis of optimal transport theory. Our general results hold even for non-Gaussian cases, while we derive a concise expression of the minimum entropy production for Gaussian processes. In particular, we apply our results to Maxwell's demons that perform measurement and feedback, and demonstrate Gaussian and non-Gaussian models of optimal demons operating in finite time. Our results provide a general strategy for controlling Langevin systems, including colloidal particles and biomolecules, in a thermodynamically optimal manner beyond the quasistatic limit.

We introduce the concept of quantum weight as a ground-state property of quantum many-body systems that is encoded in the static structure factor and characterizes density fluctuation at long wavelengths. The quantum weight carries a wealth of information about dielectric responses and optical properties of the system and is closely related to its quantum geometry. For systems with short-range interactions or low-dimensional Coulomb systems, we show that the many-body quantum metric (which measures the change of the ground state under twisted boundary conditions) can be determined directly from the quantum weight. Notably, the quantum weight is a property of a single ground state and independent of boundary conditions in the thermodynamic limit. Our finding thus enables direct experimental measurement and numerical calculation of the many-body quantum metric. On the other hand, for three-dimensional Coulomb systems, we show that the quantum weight is distinct from the many-body quantum metric due to dielectric screening in three dimensions. We further use dielectric sum rules to derive upper and lower bounds on the quantum weight of real materials in terms of their electron density, static dielectric constant, and plasmon energy. Our work highlights quantum weight as a fundamental material parameter, which can be experimentally determined by x-ray scattering or electron-loss spectroscopy.

We consider a class of Heisenberg all-to-all coupled spin models inspired by neutrino interactions in a supernova with $N$ degrees of freedom. These models are characterized by a coupling matrix that is relatively simple in the sense that there are only a few, relative to $N$, nontrivial eigenvalues, in distinction to the classic Heisenberg spin-glass models, leading to distinct behavior in both the high-temperature and low-temperature regimes. When the momenta of the neutrinos are uniform and random in directions, we can calculate the large-$N$ partition function for the quantum Heisenberg model. In particular, the high-temperature partition function predicts a non-Gaussian density of states, providing interesting counterexamples showing the limits of general theorems on the density of states for quantum spin models. We can repeat the same argument for classical Heisenberg models, also known as rotor models, and we find the high-temperature expansion is completely controlled by the eigenvalues of the coupling matrix, and again predicts non-Gaussian behavior for the density of states as long as the number of eigenvalues does not scale linearly with $N$. Indeed, we derive the amusing fact that these thermodynamic partition functions are essentially the generating function for counting permutations in the high-temperature regime. Finally, for the case relevant to neutrinos in a supernova, we identify the low-temperature phase as a unique state with the direction of the momenta of the neutrino dictating its coherent state in flavor-space, a state we dub the “flavor-momentum-locked” state.

Verifying entanglement between parties is essential for creating secure quantum communication. However, finite statistics can lead to false positive outcomes in any tests for entanglement. Here, we introduce a one-sided device-independent protocol that corrects for apparent signaling effects in experimental probability distributions, caused by statistical fluctuations and experimental imperfections. We use semidefinite programming to identify the optimal inequality, for our experimental probability distribution, without resource-intensive tomography. Our protocol is numerically and experimentally analyzed in the context of random, misaligned measurements, correcting apparent signaling where necessary. Our results show a significantly higher probability of violation than existing state-of-the-art inequalities. This study demonstrates the power of semidefinite programming for entanglement verification and brings quantum networks closer to practical applications.