Papers

For a collection of states indexed by $[n]={1,\ldots,n}$, let $F(H)$ denote the optimal unnormalized minimum discrimination error for each nonempty subfamily $H\subseteq[n]$. We call $F$ the discrimination profile and characterize exactly which profiles can arise in a general probabilistic theory (GPT). For fixed $n$, the GPT region $\mathfrak{G}_n$ is a bounded rational polytope, giving a hierarchy $\mathfrak{C}_n\subseteq\mathfrak{Q}_n\subseteq\mathfrak{G}_n$ of classical, quantum, and GPT profiles, analogous to the local–quantum–no-signalling hierarchy in Bell theory. For $n=3$ we determine the classical and GPT polytopes explicitly. Within $\mathfrak{G}_3$, the classical region is characterized by $\beta:=F(123)-F(12)-F(13)-F(23)\le0$, while the GPT maximum is $1$. For qubit triples, the maximal value is attained by the trine, $\beta_{\mathrm{tr}}=3\sqrt3/2-2$, and we prove the dimension-independent quantum bound $\beta_{\mathrm Q}\le2/3$, with a slight further improvement. Hence $0=\beta_{\mathrm C}<3\sqrt3/2-2\le\beta_{\mathrm Q}\le2/3<1=\beta_{\mathrm{GPT}}$. We conjecture $\beta_{\mathrm Q}=\beta_{\mathrm{tr}}$ and prove this for arbitrary pure-state triples, together with further supporting evidence. For arbitrary $n$, every classical facet admitting a GPT violation already admits a quantum violation in dimension at most $3$. A four-state qubit example shows that quantum success profiles need not be submodular, unlike for $n=3$. Finally, we exhibit a four-dimensional quantum triple whose discrete profile is classical for all subfamilies but becomes nonclassical when unequal priors are allowed.

Divergent series arising in the computation of Casimir energies admit two seemingly different treatments: a physically motivated regularization and subtraction procedure, and formal analytic continuation methods that assign finite values directly to divergent expressions. The agreement between these approaches for the Casimir energy between parallel plates is well known, but its origin is often left implicit. In this work, we provide a unified framework that makes this equivalence transparent. Building on Tao's theory of smoothed sums, we show that the introduction of a smooth cutoff leads to an asymptotic expansion whose finite, regulator-independent part is universally determined by the analytic continuation of the associated Dirichlet series. This identification follows from a Mellin-transform representation, in which divergences and finite contributions are encoded in the pole structure of the integrand. We extend this approach to a class of series relevant to Casimir problems. In this setting, we show that logarithmic divergences arise from pole coincidences, and we obtain a natural decomposition of the result into universal and cutoff-dependent terms, mirroring the structure of renormalization in quantum field theory.

Precision measurements with molecules require molecular beams with high flux and narrow divergence. Here we present the design, implementation, and characterization of an electrostatic quadrupole lens (EQL) for focusing a cryogenic beam of $^{205}$TlF molecules. The EQL consists of four electrodes operated at spatially alternating potentials up to $\pm 30$ kV. This configuration generates a transverse restoring force that focuses molecules prepared in selected manifold of hyperfine states. At the optimal applied voltage, the EQL increases the detected molecular signal by a factor of $14.4(4)$ at the current detection position. The measured lens gain, transverse Doppler spectra, and transverse spatial profiles are all reproduced by trajectory simulations using independently measured beam parameters as input. Based on this agreement, we project a gain of $16.5(8)$ for the full $7.9~\mathrm{m}$ CeNTREX beamline. These results establish the EQL as a key component for increasing sensitivity in precision experiments using cryogenic beams of polar molecules.

We develop an effective stochastic and semiclassical framework for dynamical thin-shell wormholes connecting two asymptotic spacetime regions. The Israel junction geometry is separated from the phenomenological open-system description: stochastic dynamics is formulated in the radial phase space $(a,\dot a)$, whereas $\sigma$, $P$, and the effective temperature scales are induced observables. A one-dimensional Langevin–Fokker–Planck model is obtained only after an explicit overdamped/adiabatic approximation. Local acceleration scales are interpreted as reservoir temperatures only under additional KMS and detailed-balance assumptions. For a symmetric Schwarzschild–Schwarzschild wormhole, the transparent conservative shell defines the reference potential and restoring frequency, while dissipation and noise are introduced as open-system corrections. The stable linear response is closed by the constitutive slope $\beta_0^2=(dP/d\sigma)_0$. For $2M<a_0<3M$, stability requires a lower bound on $\beta_0^2$ that diverges as $a_0\to2M^+$. Moreover, the derivative along the family of static configurations equals the marginal-stability slope and must not be identified with the constitutive derivative of a stable stochastic shell. The reduced model determines stationary distributions, fluctuations, correlations, Markovian and non-Markovian spectra, and entropy production. Near the horizon, the junction conditions yield $T_{\rm stress}=T_{\rm acc}+O(\hbar\gamma/a)$, with equality at leading order under a specified dominance condition. A peeling temperature participates only if the ray-tracing map satisfies generalized Unruh/peeling and adiabaticity conditions. Thus, the three-temperature correspondence is conditional, while the stochastic coefficients remain phenomenological pending a microscopic shell–reservoir model.

Brown dwarfs are common as free-floating objects but rare as close companions to Sun-like stars, a disparity known as the "brown-dwarf desert". Host-star metallicity can constrain whether these companions form mainly through metal-sensitive core accretion or through less metal-dependent disc or cloud fragmentation. We extend our homogeneous spectroscopic analysis of directly imaged planet hosts into the brown-dwarf regime and compare their metallicities with those of planet hosts and close-in brown-dwarf hosts. We compiled 54 unique directly imaged brown-dwarf systems selected over an inclusive 13-80 M_Jup interval and projected separations from about 5 au to several thousand au. Objects near the model-dependent 70-75 M_Jup hydrogen-burning boundary may instead be very-low-mass stars. For 31 hosts with archival high-resolution spectra, we derived atmospheric parameters and metallicities using Bayesian spectral synthesis. Literature companion masses and projected separations are heterogeneous and are used only for demographic context. Galactic velocities were calculated for 46 hosts solely to characterise the youth-biased imaging sample. The host stars have a broadly solar metallicity distribution, with a median [Fe/H] of +0.06 dex and a median absolute deviation of 0.11 dex, and show no strong metal-rich bias. No statistically significant metallicity difference is detected between the lower- and higher-mass directly imaged subsamples. The hosts are kinematically cold, as expected from the youth-biased selection of direct-imaging surveys. The absence of a strong metal-rich bias suggests that classical core accretion does not dominate the wide-orbit brown-dwarf population. Disc instability and cloud fragmentation remain plausible, but the current sample and heterogeneous companion properties do not permit object-by-object discrimination between these channels.

We present a theoretical study of a semiconductor photon-pair source based on a radiative cascade enabled by a permanent exciton dipole. The source consists of a GaAs quantum dot placed between a metal nanoparticle and a mirror. The dot exciton and the localized electromagnetic mode mix to form upper and lower polaritons. Without a permanent dipole, a symmetry separating states with even and odd excitation numbers forbids photon emission between the polaritons. Separation of the mean electron and hole positions gives the exciton a permanent dipole and breaks this symmetry. The upper polariton can then emit an idler photon as it decays to the lower polariton. The lower polariton can emit a signal photon as the system returns to its ground state. Using an effective model, we calculate the probability that a prepared upper polariton emits both photons through the metal antenna. We also analyze fluctuations in the emitted photon counts and correlations between the two emission channels. The calculation establishes an operating principle for assumed values of the coupling strength, emitter properties and optical loss rates. Whether the device can be built and its photon correlations measured remains open.

How much does the noisy measurement add to learned quantum error mitigation? An accuracy table cannot say, because a model handed circuit structure can score well without reading the measurement at all. QEMScore adds the comparison that can. Each simulated circuit carries an exact ideal answer. The learned mitigator is scored beside a capacity-matched control, a model just as flexible that reads the same circuit description but never the measurement. Each method's measurement spend is accounted and not equalized. We run a controlled campaign on simulated circuits and reanalyze two published learned mitigators, Q-LEAR and QRAFT, from their released hardware data. Three findings stand out. First, under familiar within-family conditions (S0) evaluated across two spin-chain families and three seeds, continuous couplings identify the target, and the control that never reads the measurement matches 87.7 to 100.5 percent of the mitigator's gain over an affine fit to the circuit description. A plain polynomial in the coupling parameters, fitted after the campaign, beats the mitigator on all six evaluations, reflecting the selected learners' capacity. Second, for these selected learners, matching most of the gain is not matching the accuracy: on five of six evaluations the mitigator removes 19.5 to 74.5 percent of the error the capacity-matched control leaves, a learner-specific gap rather than a measurement requirement. Third, on released hardware data where descriptors only partially identify queries, the findings differ: flexible models of the descriptors show negligible mean gain over affine fits in Q-LEAR, and measurement inputs carry predictive gains in both Q-LEAR and QRAFT. These comparisons reflect representation- and protocol-specific behavior rather than an isolated cross-regime difference. A learned mitigator's accuracy should therefore be reported beside such controls.

Calculating disequilibrium chemistry in exoplanet atmospheres remains a significant computational bottleneck in atmospheric retrievals. The increasing observational precision from facilities such as JWST and the Ariel mission requires including disequilibrium chemistry in these analyses. Previous studies have demonstrated that neural networks can emulate kinetic chemistry, although their spatial inductive bias does not align with the topology of chemical reaction networks. This study introduces a graph neural network surrogate that represents chemical species as nodes and temperature-dependent reaction rates as edges, thereby enabling information propagation along physically meaningful chemical pathways. The model is trained on atmospheres generated using the Venot+2020 chemical scheme and Guillot temperature-pressure profiles. The GNN accurately reconstructs disequilibrium abundances across the sampled parameter space and reduces the mean abundance error by a factor of approximately 3 compared to the previous U-Net model. When applied to transmission spectra, most predictions fall within the observational precision expected for JWST and Ariel, with only about 7% of test atmospheres exceeding a 20 ppm mean spectral error. Performance variations are primarily observed in chemically transitional regimes near a carbon-to-oxygen ratio of one and at low temperatures. An evaluation of the boundary-case planet WASP-39b demonstrates effective performance under a moderate domain shift. Perturbation analysis indicates that disturbances propagate along chemical connectivity rather than spatial adjacency, confirming that the architecture captures the structure of reaction networks. These results suggest that GNN surrogates provide accurate, computationally efficient predictions of disequilibrium chemistry, facilitating integration into the atmospheric retrieval pipeline.

Gas–grain astrochemical models predict that a substantial fraction of elemental nitrogen in dense cores and protoplanetary disks is locked in molecular nitrogen (N$_2$), in the gas or ice phase, although interstellar N$_2$ ice has not been directly identified. Rosetta measurements at comet 67P/Churyumov–Gerasimenko showed strong N$_2$ depletion relative to CO, while NH$_3$ was the dominant detected nitrogen-bearing ice. We experimentally quantify the conversion of NH$_3$ ice into N$_2$ and N$_2$H$_4$ under astronomically relevant conditions by studying its temperature- and fluence-dependent VUV photochemistry. Experiments were performed under ultra-high vacuum using 40-monolayer NH$_3$ ice at 15, 25, and 70 K irradiated at 115–170 nm to a total fluence of $3.8\times10^{18}$ photons cm$^{-2}$. Laser desorption with post-ionization reflection time-of-flight mass spectrometry (ReTOF-MS) was used to monitor N$_2$ and N$_2$H$_4$ simultaneously. VUV photolysis efficiently forms both products, with formation kinetics and product ratios depending on temperature and photon fluence. Initial-growth fits gave the highest apparent ice-retained N$_2$ formation yield at 15 K, approximately an order of magnitude above those at 25 and 70 K. The N$_2$/NH$_3$ column-density ratio was determined as a function of fluence and compared with astronomical constraints. These results suggest that NH$_3$ ice photochemistry may provide an additional pathway to N$_2$ ice in cold outer planetary environments.

The surface chemistry of additively manufactured aluminum alloys plays a critical role in corrosion resistance and joining with external materials. In this work, the near-surface elemental composition of a laser powder bed fusion (PBF-LB/M) processed Al-Mg-Si-Zr alloy was characterized by glow discharge optical emission spectroscopy GDOES depth profiling. The measurements reveal pronounced Mg enrichment within the near-surface region extending to approximately 10 {\mu}m, consistent with the characteristic scale of surface roughness, together with an increase in oxygen concentration, whereas Al, Si, and Zr approach stable bulk-like levels at greater depths. To understand this observation on the atomic scale, first-principles calculations based on density functional theory (DFT) were performed on low-index Al surfaces. The calculated results show a strong thermodynamic driving force for Mg surface segregation, with diffusion energy differences ranging from approximately -0.30 eV to -0.41 eV, while Zr exhibits a pronounced preference for remaining in the bulk matrix. Vacancy migration calculations further demonstrate that full structural relaxation substantially reduces the migration barrier for Mg to below that of Si, which makes Mg diffusion kinetically highly favorable. Moreover, the presence of adsorbed surface oxygen dramatically promotes the tendency of Mg to diffuse toward the surface, which lowers the diffusion energy difference of Mg to as much as -3.0 eV. This promotes the formation of a locally reconstructed Mg-O-Al coordinated precursor structure accompanied by localized electron transfer shown by an electron localization function analysis.

In 2014, we introduced a new experimental approach to study the UV photo-processing of cryogenic ices of astrophysical interest using laser ablation in combination with ionization and time-of-flight mass spectrometry (ToF-MS). The setup, MATRI$^2$CES (Mass Analytical Tool to Research Interstellar ICES), allowed us to detect newly formed species at low abundances. However, we found that with increasing molecular complexity, the detection of larger photoproducts was hindered by the dynamic range of the detector. Here, we introduce a method to overcome this issue that we expect to be useful for similar applications in other research fields. The concept is based on a precisely controlled high-energy pulser that regulates the voltage across the deflection plates of the ToF-MS to deflect the most abundant species and prevent them from reaching the detector. In this way, the detector sensitivity can be increased from an operating voltage of 2500~V up to 3000~V. The applicability is first illustrated using an argon matrix, in which $^{40}$Ar$^+$ ions are deflected to increase the detection sensitivity for $^{40}$Ar$^{2+}$ at $m/z=20$ and $^{40}$Ar$_2^+$ at $m/z=80$ by a factor of 30. Similarly, we show that substantially larger complex organic molecules can be measured in UV-irradiated methanol ice.

We examine the different methods of extracting the anomalous Hall conductivity using SrRuO$_3$ and GdAlSi. For SrRuO$_3$, where the ordinary Hall background is well defined and the magnetoconductance is small, subtracting the ordinary Hall contribution either before or after conversion from resistivity to conductivity yields nearly identical anomalous Hall conductivities. In GdAlSi, in contrast, the transverse response does not exhibit clear saturation, and both low- and high-field regions can appear approximately linear. We show that different interpretations of these linear regions as the ordinary Hall background, together with the treatment of the measured longitudinal resistance in the resistivity-to-conductivity conversion, can produce completely different estimates of the anomalous Hall conductivity. We also examine whether the nonlinear Hall response can instead be described within an ordinary Hall framework without invoking an anomalous contribution. Our analysis provides practical cautions for extracting excess Hall contributions in quantum materials.

Spatial and temporal correlations in quantum noise challenge the local Markovian models commonly used in quantum information processing. We develop a unified operational framework for quantifying temporal, spatial, and total spatiotemporal correlations in general quantum processes. Using process tensors, we define these quantities through optimal distinguishability from Markovian, spatially local, and fully uncorrelated processes. Optimization over admissible probing combs ensures monotonicity under every superprocess that preserves the corresponding free set, while Choi-state functionals and restricted probes provide accessible lower bounds. We establish hierarchy and interpolation relations among the correlation measures and derive dimension-dependent upper bounds on temporal correlations transmitted by quantum memories, with tighter bounds for classical memory, together with universal ceilings imposed by the system dimension. These bounds turn certified lower estimates into witnesses of minimum memory dimension, nonclassicality under a memory-dimension constraint, and inconsistencies in the assumed process model. We illustrate the results with effective superconducting-qubit models featuring \(ZZ\) and \(XY\) interactions, exhibiting saturation of classical-memory, quantum-memory, and system-dimension ceilings. These results pave the way toward practical approaches to characterizing and addressing spatiotemporally correlated errors in quantum devices.

Acetylene (C$_2$H$_2$) is commonly observed in star-forming regions, young stellar objects, and the Solar System. Laboratory and theoretical studies have linked this simplest alkyne to volatile hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) through UV- or cosmic-ray-driven chemistry, but it remains unclear whether refractory material can efficiently form through solid-state reactions of C$_2$H$_2$ on dust grains. We experimentally investigate the chemical complexity induced by UV irradiation of pure C$_2$H$_2$ ice and characterize both volatile and nonvolatile photoproducts. Experiments were performed with MATRI$^2$CES under ultra-high-vacuum conditions at 15 K using 7.2–10.2 eV photons. UV-processed ices were monitored in situ by laser desorption post-ionization reflection time-of-flight mass spectrometry (LDPI ReTOF-MS) combined with pulsed ion deflection (PID). Volatile and refractory products were measured in situ at 15 and 300 K, respectively. After a fluence of $3 \times 10^{17}$ photons cm$^{-2}$, corresponding to about $10^6$ years in dense clouds, large saturated and unsaturated hydrocarbons containing up to 13 carbon atoms are formed. After sublimation of the volatile products, the 300 K residue shows a rich and distinct mass spectrum consistent with refractory material containing conjugated triple (-C$\equiv$C-) and double (-C=C-) bonds. These results demonstrate that UV processing of pure C$_2$H$_2$ ice can produce substantial molecular complexity and refractory hydrocarbons under astronomically relevant conditions, with possible implications for unidentified infrared emission bands.

The systematic generalisation of the well-established $S$-matrix positivity and bootstrap bounds from $2 \to 2$ scattering processes to higher-point amplitudes has, to date, remained elusive. To address this, we consider a large class of tree-level UV-completions of a single-scalar EFT. Specifically, we consider the most general renormalisable $N$-scalar theory in $D=4$. By explicitly computing tree-level amplitudes for four-, five- and six-point scattering and expanding at low energies, we can search for positivity relations among the expansion coefficients. We find that quite generally positivity bounds are unavailable due to contamination from a specific class of Feynman diagrams that are linear in sign-indefinite cubic couplings. However, by isolating a sector of the full crossing-symmetric low-energy amplitude that is unaffected by these sign-indefinite cubic couplings, we find that selected six-, five- and four-point Wilson coefficients organise into positive semi-definite matrices. While a violation of these positivity statements only implies that a given EFT is inconsistent with our class of UV completions, the result helps to guide towards what more general positivity bounds for higher-point interactions could, and could not, look like.

Effective infrared two-sheeted descriptions of fermion mixing between braneworlds have emerged in several distinct realizations and lead to testable matter-swapping effects, motivating low-energy searches and cosmological applications. The recurrence of the same low-energy fermion operator motivates asking whether this structure can also arise from a D-brane mechanism. We construct a local Type IIB D3$_+$-D7-D3$_-$/E3 realization in which direct interbrane mixing is perturbatively forbidden but generated non-perturbatively by a suitable E3 instanton sector. The resulting low-energy interaction reproduces the characteristic pseudoscalar structure of the two-sheeted fermion operator, together with its scalar companion, while D7 Wilson transport provides the required gauge-invariant relative connection. The construction therefore provides a local string realization of the same operator structure, subject to the stated instanton and zero-mode conditions. The analysis further provides a concrete model-building roadmap toward a compact phenomenological realization: the compactification must achieve electromagnetic sequestering of the two fermion sectors and support a sufficiently light non-uniform D7 gauge mode capable of mediating a long-range relative interaction. In such a complete compactification, the mixing parameter $g$ would in principle become computable from microscopic string data and directly testable against low-energy constraints.

We present an updated strong lensing model for the galaxy cluster RXJ0437.1+0043 (z=0.285) using new JWST NIRCam imaging in four pass-bands. The cluster field notably displays at least three separate gravitationally lensed galaxies in hyperbolic-umbilic (H-U) configurations, which in the JWST imaging show exquisitely resolved stellar clumps at scales as small as 0.04”. We identify 13 new systems of multiply-imaged lensed galaxies and determine the redshifts for two sources based on archival spectroscopic observations. We also identify over 50 individually resolved substructure clumps in the multiple images of eight galaxies and add them into the lens model, for a total of 275 positional lensing constraints between all 26 lensed sources used in the model. We investigate the impact of different modeling choices on our results. In the final lens model, we reproduce the observed multiple images with a precision of 0.23” , and achieve 0.13” specifically for the H-U systems. We estimate a total enclosed mass in the cluster's strong lensing regime of M(<110 kpc) ~ 8.2 x 10^13 Msun, reconstruct the source images of the most highly magnified galaxies, and measure time delays in the most magnified, morphologically detailed systems. The isotropic lensing effect from the H-U configurations enables future detailed studies of the properties of their source galaxies, and the number and spatial density of additional constraints improve the model's ability to detect dark matter substructures within the cluster core.

This study investigates the impact of fermionic dark matter (DM) on the structural and tidal properties of white dwarfs (WDs). Using a two-fluid general relativistic framework, we model stars with fixed DM mass fractions (${\rm MF}=M_{\rm DM}/M_{\rm NM} $), ranging from 0% to 8%, with zero representing the no DM scenario. Our results indicate that DM accumulation leads to a significant compactification of the star, reflected in increased surface gravity and compactness. Furthermore, we calculate the second-order tidal Love number $k_2$ and the dimensionless tidal deformability $\Lambda$. For some total mass range, we find that the presence of DM significantly reduces $\Lambda$, suggesting that DM-admixed WDs (DMWDs) are less susceptible to tidal deformations. These structural shifts alter the gravitational wave signatures in binary systems, potentially providing a new window for DM detection with future instruments like LISA.

We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using the overlapping Schwarz alternating method. We consider the two-dimensional advection-diffusion equation in the advection-dominated, Peclet-number 10^6 regime. We first demonstrate that, unlike the corresponding physics-informed neural network (PINN), a monolithic NINN can be accurately trained on our model problem without domain decomposition. We then employ overlapping multiplicative Schwarz as a deployment mechanism for coupling a pre-trained, subdomain-local NINN with a neighboring FOM, with the NINN weights held fixed throughout the Schwarz iteration. We consider two training approaches for the subdomain-local NINNs: a top-down approach, in which boundary data are obtained from a coupled Schwarz solve on the full domain with a FOM on each subdomain (FOM-FOM Schwarz), and a bottom-up approach, in which boundary traces are generated synthetically on the NINN subdomain without requiring any full-domain solves. The resulting hybrid NINN-FOM solutions agree closely with the corresponding FOM-FOM Schwarz solutions, with the top-down and bottom-up training approaches yielding comparable accuracy.

Low-energy nuclear structure is encoded in a broad body of experimental information across the chart of nuclides. Learning how this information is organized across observables and nuclei can provide a data-driven empirical baseline for theoretical extrapolations and experimental design. Here, we develop held-out ensembles based on NuCLR (Nuclear Co-Learned Representations), a multi-task model of nuclear data, to study charge radii and electric-quadrupole transition strengths. Out-of-fold (OOF) validation shows that shared representation improves performance over single-task learning, yielding a charge-radius $\mathrm{RMS}$ deviation of $0.0147~{\rm fm}$ and a $\mathrm{B(E2)}$ $\mathrm{RMS}$ deviation of $0.192~e^2{\rm b}^2$ across hundreds of nuclides, competitive with state-of-the-art nuclear models. Our error bars estimate the expected prediction accuracy across the nuclear chart, highlighting regions where new data would encode information beyond the learned patterns. NuCLR thus serves as a data-driven surveyor of nuclear structure and a step toward a shared, multi-observable foundation model of the nuclear chart.

Hybrid domain decomposition methods provide a flexible framework for coupling full order models (FOMs) and reduced order models (ROMs), but typically assume the model assigned to each subdomain is fixed throughout a simulation. This is limiting for transient problems in which localized features propagate through the domain and the regions requiring high-fidelity resolution change over time. We introduce a reinforcement learning (RL)-based approach for online adaptation of FOM-ROM models coupled via the overlapping Schwarz alternating method (O-SAM), an iterative domain decomposition method that solves subdomain-local problems while exchanging solution information through transmission boundary conditions on overlapping interfaces. Deep Q-networks (DQNs) are trained offline to select among subdomain-local FOMs and pre-trained Operator Inference (OpInf) ROMs using a reward balancing accuracy, cost, and model-switching frequency. Once trained, the policies are deployed predictively on problem instances not seen during training, without requiring a reference FOM solution. We demonstrate the approach on two examples: a 1D advection-diffusion problem with a moving front, and a 3D linear elastic wave propagation problem implemented in the Norma.jl solid mechanics code. For the advection-diffusion benchmark, the learned policy dynamically allocates high-fidelity resolution as the front propagates and outperforms static FOM/ROM assignments; letting the agent also adapt the domain decomposition provides no further benefit. For the elastic wave benchmark, learned policies for two and three subdomain decompositions track the propagating wave by assigning FOMs to subdomains containing the wave and ROMs elsewhere, as expected. Our results demonstrate the potential of RL to enable predictive online adaptation of model fidelity within Schwarz-based hybrid simulations.

We study the Quantum Approximate Optimization Algorithm with a Grover mixer and independently sampled cost and mixing angles. Under a lattice condition on the cost values carried by the initial state, we prove a depth-independent lower bound for the variance of the loss at every depth, together with the same bound for the derivative with respect to the final mixing angle. The estimate is instance-dependent and, for fixed locality, is inverse polynomial in the number of qubits for integer-valued local objective functions with uniformly bounded local terms, in particular for MaxCut. We also establish Grover-type reachability bounds showing that the depth required to approximate a prescribed carried eigenspace is bounded below by a constant multiple of the inverse square root of its initial probability.

By using the Dirac and symplectic formalisms, the analysis of the Holst action in the $G \rightarrow 0$ limit is performed. We study the theory's full canonical structure and symmetries. In particular, we focus on the cases $\gamma = i$ and $\gamma \neq i$, aiming to obtain Smolin's auto-self-dual model in terms of the Ashtekar variables and a Barbero-type formulation. We then perform the symplectic analysis and discuss the principal insight of these formalisms.

Proto-planetary nebulae are considered to be the evolutionary link between AGB stars and planetary nebulae. They possess many of the physical characteristics expected of such a link and provide valuable information about the evolutionary process in these objects. One important characteristic of proto-planetary nebulae is the prevalence of very strong bipolar and point-symmetric morphologies. In planetary nebulae, these shapes are widely considered to be the result of shaping by a binary companion. Indeed, a number of studies have shown links between strong axial or point-symmetry in planetary nebulae and close binary central star systems that have gone through a common envelope phase. Here, we explore whether the observed proto-planetary nebulae may be the progenitors of planetary nebulae with close binary central stars. We find that despite the strong shaping of proto-planetary nebulae this is unlikely to be the case. We also discuss options for evolution to close binaries and the alternatives.

Understanding how instrumental and mission parameters affect the ability to measure faint astrophysical signals is a key challenge in the design of future experiments. This is particularly relevant for CMB spectral distortions, whose weak signals are affected by both instrumental effects and astrophysical foregrounds. We develop a method to explore and optimise the multidimensional parameter space of an astronomical instrument, and apply it to CMB spectral distortion measurements using the FOSSIL mission concept. We combine a dedicated sky model with a realistic instrument model and use Fisher forecasts to assess measurement capabilities of the simulated instrument. Decision-tree-based regression models are then used to learn the non-linear mapping between instrumental parameters and the predicted signal-to-noise ratios of the sky observables. Random Forest and gradient boosting models accurately reproduce the forecasted measurement performance. SHAP values are used to interpret the impact of instrumental parameters on the measurement. The temperature of the warmest instrumental component is found to be the dominant parameter for all three observables, highlighting the importance of limiting internal emission and operating the instrument at cryogenic temperatures. Frequency coverage is also highly influential, revealing a trade-off between spectral coverage and instrumental sensitivity. The proposed optimisation method provides a fast and interpretable approach to explore high-dimensional instrumental parameter spaces and identify parameters that most strongly influence the scientific performance of an experiment. To the best of our knowledge, this work represents the first application of machine-learning methods to the global optimisation of an astronomical instrument and can readily be extended to other astronomical instruments and mission concepts.

Matrix models express partition functions of random surfaces with prescribed boundary lengths through string equations. We give a probabilistic realization of this structure in Liouville quantum gravity (LQG). For $\gamma^2\in(8/3,4)$, we construct the quantum $n$-hole sphere from a quantum disk decorated by an independent conformal loop ensemble (CLE) and compute its area Laplace transform at fixed boundary lengths. The transform depends only on the total boundary length apart from a simple prefactor and is determined by a hypergeometric string equation. We derive this equation from stable Lévy excursions using LQG/CLE coupling. The conformal welding equation yields symmetric polynomials that represent integrated LQG/CLE coupling observables. These polynomials converge to Weil–Petersson volumes of spheres with $n$ geodesic boundaries as $\gamma\downarrow0$.

Many proteins function through transitions between conformational states, yet rare states are rarely sampled by diffusion models trained on an equilibrium ensemble, demanding better sampling methods. We introduce METALICA, which implements Metadynamics on a pretrained diffusion model via Replica Exchange. It accumulates a bias potential along a Collective Variable, repels new samples from previous ones through biased sampling, and reweights samples onto the unbiased distribution. METALICA holds one replica per diffusion level, forming a Markov Chain that evolves through inter-replica communication and is refined in place as the bias grows. METALICA is the dual of sequential control, in which Sequential Monte Carlo parallelizes the sampler over a batch of particles. Parallelism over the levels of the diffusion-time schedule instead allows METALICA to generate samples from long chains, essential for the discovery of rare events, with accuracy set by run length rather than by the memory available. We validate on a bimodal target with known free energies, then apply METALICA to the unfolding of a protein. At a budget for which sequential control yields no unfolded structure, METALICA populates the basin and resolves a second free energy minimum.

Bolometers transduce incident electromagnetic radiation into measurable electrical signals via radiation-induced heating in thermo-resistive materials. They are uniquely capable of detecting low-energy photons without cryogenic cooling, and are widely deployed for uncooled long-wave infrared (LWIR) radiation detection and thermal imaging. Although their fundamental detection limit is set by the thermodynamic fluctuations, state-of-the-art uncooled bolometers still operate well above this limit due to the presence of Johnson noise, 1/f noise and noises from the readout circuits. Here, we address this challenge by introducing a new uncooled LWIR bolometer concept—the silicon avalanche transition edge (SATE) bolometer. Operating near the steep current transition edge associated with avalanche breakdown, the device exhibits an ultra-high, positive temperature coefficient of resistance (TCR) of 330 %/K, greatly suppressing the impacts of other noise sources. Even without any thermal insulation structures, the SATE bolometer delivers a high room-temperature responsivity up to 160 mA/W for 9.5 $\mu$m radiation, a noise equivalent power of 370 pW/$\sqrt{\mathrm{Hz}}$, and a strong electro-thermal feedback enlarged bandwidth of 77 kHz—performance unattainable with conventional bolometer materials with a TCR of $-1\sim-3\%$/K. Our work establishes a promising thermo-electric transduction mechanism toward high-sensitivity, high-speed room-temperature thermal imaging and infrared spectroscopy using CMOS technology.

Determining which microscopic states remain thermally active when tunneling and interactions compete is a central question in Hubbard physics. Here we develop an entropy measurement protocol for a double quantum dot, extending the charge-based approach established for a single dot, and measure the total entropy of a tunable two-site Hubbard molecule realized in a GaAs double dot. By shifting both dot levels together at fixed detuning, the entropy is correctly probed with only a single charge sensor. As interdot tunneling increases, the system evolves from two atomic-like dots through hybridized molecular states to a merged single dot. Across this evolution, the entropy decreases as tunnel-induced energy splitting exceeds the thermal energy and suppresses the occupation of higher-energy states. The measurements resolve the diminishing contribution of antibonding states and the changing thermal contributions of hybridized singlet and triplet states, in quantitative agreement with a two-site Hubbard model. By distinguishing states with the same charge configuration but different orbital and spin content, entropy reveals how tunneling and interactions determine the thermally active states of the minimal Hubbard system.

We perform 3D radiation magneto-hydrodynamic (RMHD) shearing-box simulations of local patches of optically thick accretion disks, applicable to sub-Eddington active galactic nuclei (AGN) at $\sim 1000$ gravitational radii around a supermassive black hole (SMBH) of $10^7-10^8M_\odot$. In particular, we set up zero-net-vertical-flux (ZNVF) simulations with strong net azimuthal fields ($B_y$) characterized by initial gas-to-magnetic pressure ratio $\beta_0$. We find that $\beta_0 \sim 1$ simulations relax to the classical MRI state with steady-state $\beta\sim 10-20$ and slow periodic reversals of the mean azimuthal field (dynamo cycles), losing memory of their initial $B_y$ configuration. The outcome of simulations starting from $\beta_0=0.1$ (superthermal magnetic pressures) depends upon the numerical resolution as quantified by the number of grid cells per thermal scale height $H_\mathrm{th}$. Resolved simulations ($\Delta z\le H_\mathrm{th}/5$) settle into final states similar to the larger-$\beta_0$ runs, exhibiting thermally dominated midplanes heated by MRI turbulence and undergoing dynamo cycles. In contrast, lower resolution $\beta_0 = 0.1$ runs evolve towards states dominated by a coherent mean field, similar to what is observed in recent isothermal MHD simulations. However, those disks fail to sustain sufficient turbulent heating near the midplane and undergo runaway cooling and contraction. While such states might be sustained in global models with even lower initial $\beta_0$ and/or continuous $B_y$ injection, our results indicate that they could arise purely from under-resolving the midplane MRI dynamo that would otherwise be able to generate and emanate randomized fields. We highlight the need to resolve a fraction of the thermal scale height (the classical MRI wavelengths) for strongly magnetized initial conditions to obtain converged outcomes in RMHD simulations.