Papers

Electron-phonon interactions underpin a variety of phenomena, ranging from transport and superconductivity to polarons and ultrafast carrier dynamics. Despite being one of the most intensely studied subjects in condensed matter physics, research on electron-phonon physics mostly focused on linear, first-order couplings. Second- and higher-order nonlinear couplings are commonly ignored because their calculations are too demanding and we lack computational frameworks that can provide both diagonal and off-diagonal coupling matrix elements. In this work, we report a theory and computational method for computing nonlinear electron-phonon interactions of any order in real materials. Our approach combines the advantages of unit-cell calculations of electron wavefunctions and supercell calculations of phonon perturbations, is systematically improvable, can be used with either semilocal or nonlocal exchange-correlation functionals, and is amenable to Wannier-Fourier interpolation. As a first proof of concept, we illustrate this method by computing second-order electron-phonon coupling matrix elements in diamond, lithium fluoride, and graphite as representative nonpolar semiconductors, polar semiconductors, and metals, respectively. Furthermore, we generalize the ab initio polaron equations to second-order electron-phonon couplings, and we show that second-order couplings are essential to achieve quantitative accuracy in polaron formation energies and hopping barriers. The present methodology will find application in the study of all properties and phenomena that are currently being investigated within the linear electron-phonon coupling approximation, from phonon-mediated superconductivity to excited-states dynamics, both in harmonic and anharmonic systems.

Optical inter-satellite links (OISLs) are key enablers for high-capacity space networks and next-generation satellite constellations. However, their extreme directionality makes link reliability highly sensitive to platform-induced pointing jitter, which causes random misalignment between the transmitter and receiver beams. In this paper, we develop a tractable closed-form statistical channel model for point-to-point OISLs subject to independent pointing errors at both terminals. Accurate Gaussian main-lobe approximations are applied to the transmitter far-field pattern and receiver coupling efficiency. This transforms the diffraction-based channel response into closed-form expressions for the channel-gain distribution, outage probability, and ergodic capacity. The analytical results are validated through Monte Carlo simulations and used to study the impact of terminal stability, beam divergence, and link margin on OISL performance. The results show that outage probability is governed by the weaker terminal in terms of pointing stability, while improving only the stronger terminal provides minimal additional benefit. In contrast, the ergodic-capacity penalty depends on the combined stability of both terminals, revealing a fundamental distinction between reliability and throughput metrics. The proposed framework provides practical design guidelines for selecting beam parameters and specifying pointing and tracking requirements under varying levels of platform instability.

The high-overtone quasinormal-mode spectrum encodes the near-singularity Kasner scaling of black-hole interiors. We show that distinct structures in this spectrum independently determine the temporal and spatial Kasner grades, allowing the corresponding metric exponents to be reconstructed without imposing Kasner constraints or invoking holography. We demonstrate this independent reconstruction at the fixed Kasner point of five-dimensional asymptotically flat Schwarzschild and planar Schwarzschild–AdS$_5$, and then extend it to a continuously varying Gibbons–Maeda black-hole family. The reconstructed exponents satisfy the Kasner relation a posteriori, providing a nontrivial geometric consistency check. More generally, the high-overtone spectrum separates into global spectral data and local algebraic corrections whose fractional powers are fixed by the near-singularity Kasner geometry. These fractional corrections therefore provide a direct spectral probe of the local geometry behind the horizon.

A revision of the drift-reduced Braginskii model is presented, focusing on its practical implementation in numerical codes, and systematically analyzing the effect of several commonly-used approximations on energy conservation. As a practical example, the effect of the approximations is quantified in the GBS code. By dropping the most important approximations and related energy sinks, the simulation shows increased transport levels and a target heat flux with closer agreement to experimental observations.

Recent measurements of the distribution of galaxies by the Dark Energy Spectroscopic Instrument (DESI) are in mild tension with a standard $\Lambda$-Cold Dark Matter cosmological model inferred from the anisotropies of the Cosmic Microwave Background (CMB) when extrapolated to low redshifts. Several solutions to explain this discrepancy in terms of new physics have been put forward, notably from new dynamics in a complex Dark Sector. Here we report on a resolution to this discrepancy that postulates that the inertial and gravitational masses of dark matter particles are not the same. Our best fit to CMB data combined either with Baryon Acoustic Oscillation (BAO) and Full Shape (FS) data from DESI DR1 (Data Release 1), or with BAO DR2 data alone, suggests the presence of a new long-range force in the Dark Sector with strength of $\beta \sim 0.5\% $ relative to gravity, at the $\sim 2.5\sigma$ level. A preliminary analysis combining FS DR1 and BAO DR2 data confirms the statistical power of DR2 and raises the evidence for dark forces to $\sim 3\sigma$, albeit ignoring the not yet available cross-correlation between the two datasets.

The recent high-recoil candidate event reported by LUX-ZEPLIN (LZ) motivates dark-matter scenarios with nonstandard kinematics and momentum-dependent interactions. We study a two-state inelastic dark-matter model in which $\chi_1$ and $\chi_2$ couple off-diagonally to an axion-like particle (ALP) that also couples to gluons and photons. Unlike treatments that assume only one dark-matter state is present today, we track the cosmological evolution of both states. The excited state $\chi_2$ is sufficiently long-lived to survive to the present, with its relic fraction determined by the dark-sector conversion process $\chi_2\chi_2\leftrightarrow\chi_1\chi_1$. We find that this fraction depends strongly on the Lorentz structure of the DM–ALP interaction: scalar transition couplings efficiently deplete $\chi_2$, favoring endothermic $\chi_1 N\to\chi_2 N$ scattering, whereas pseudoscalar transition couplings preserve $f_2\simeq1/2$, yielding recoil spectra dominated by exothermic $\chi_2 N\to\chi_1 N$ down-scattering. Benchmark spectra in all four scenarios can peak near the observed recoil energy of $250\,\mathrm{keV}$. Our results demonstrate that the dominant direction of inelastic scattering in direct detection can be dynamically selected by the early-Universe evolution of the dark sector. With additional data, annual modulation measurements could distinguish these scenarios. We further show that the ALP portal can be directly probed at colliders.

A multiset of pure quantum states is said to be k-learnable if there is a measurement strategy that always narrows an unknown sample drawn from the list down to one of at most k candidates. The parameter k interpolates between distinguishability and antidistinguishability, and provides a unified framework for partial state identification. We prove two universal, and optimal, Gram-matrix criteria for k-learnability: a Frobenius-norm sufficient condition and an entrywise-$\ell_1$ necessary condition. We apply them to derive explicit learnability and copy-complexity guarantees for several well-known sets of states including SIC-POVMs, mutually unbiased bases, and stabilizer states. We further apply our results to zero-error mutation detection problems such as anomaly detection and changepoint detection.

$\mathsf{QAC}^0$ is the class of constant-depth $\mathrm{poly}(n)$-ancilla circuits obtained by extending $\mathsf{QNC}^0$, the class of local circuits, to include nonlocal interactions via arbitrary width Toffoli gates. It is believed to be weaker than its counterpart, $\mathsf{QNC}^0_f$, obtained by including arbitrary-width FANOUT gates instead ($\mathsf{QAC}^0 \subseteq \mathsf{QNC}^0_f$ [Moo99]). In this note, we show that every $O(\log n)$-qubit state can be exactly and cleanly prepared by a $\mathrm{poly}(n)$-ancilla $\mathsf{QAC}^0$ circuit. Previous known $\mathrm{poly}(n)$-ancilla circuits for arbitrary such states are only known via additional access to either FANOUT or QRAM (indexing) gates [Ros21b, GGJ26b], neither of which are known to be in $\mathsf{QAC}^0$. Equivalently, prior constructions of arbitrary $n$-qubit states in $\mathsf{QAC}^0$ require doubly exponential size and we obtain an exponential factor improvement.

It is shown how evaporative cooling in hot plasma is essentially different from evaporative cooling in other media, such as neutral gases or Bose-Einstein condensates. The fundamental difference in plasmas arises both from the large mass ratio between electrons and ions in fully ionized plasma and the unusually sensitive dependence of plasma collisionality on speed. Thus, a hot ion mode plasma ($T_e < T_i$) is shown to support a distinctive evaporative cooling regime, where a strong reduction in the ion evaporation rate appears. This new regime may have application to approaches to economical nuclear fusion, where the ion tail plays an outsized role in the fusion reaction rate.

We discuss the interpretation of an observed running Hubble constant with the redshift, in terms of the possible underlying physical scenario. Assuming, like in the $\Lambda$CDM model, that the matter and dark energy components do not directly interact, we arrive at the conclusion that the physical content of the cosmological dynamics can always be represented with an evolutionary dark energy paradigm. We discuss both the case of the power-law running Hubble constant, and that of an optimized fitting model, both studied with the binned Pantheon Sample of the Type Ia Supernovae data. These two cases turn out to be associated with a phantom-like evolutionary dark energy.

Quantifying the magnetic properties of open-shell molecules is a common task in chemistry and is increasingly performed in silico using Kohn-Sham density functional theory (KS-DFT). Previous work demonstrates that the predictive accuracy of a few functionals for one such property - hyperfine coupling constants (HFCCs) - is possible, implying that such approximations must yield accurate spin-densities at the nucleus. However, the ability of such functionals to globally predict accurate spin-densities of comparable quality to rigorous ab initio coupled cluster theory, for example, is dubious, despite this being a fundamental quantity for KS-DFT. This work intends to explore the matter by evaluating moments of the spin-density, $\langle r^n \rangle = \int \rho(r)r^n d\tau$, $n=-2,\cdots,2,3$, for second-, third-, and fourth-row atoms to compare various KS-DFT functionals against CCSD. Our results broadly indicate that the tested functionals experience significant deviations with respect to CCSD spin-densities in regions up to 1 Bohr away from the nuclei, with most errors occurring in the immediate vicinity of the nucleus. We find evidence of extreme errors by some functionals for individual $\alpha$/$\beta$ spin-densities, although several ultimately end up benefiting from significant error cancellation once the corresponding global spin-density is formed. Nevertheless, a comparison between CAM-B3LYP and the Quantum Theory Project (QTP)-family of DFT functionals based on Correlated Orbital Theory conditions across all error metrics demonstrates that QTP00 more accurately reproduces the global spin-density as well as HFCCs, generally offering results in better agreement with CCSD. In line with previous work, we also corroborate the success of PBE0 and the TPSS-family of functionals for HFCCs, further finding that both approximations generally yield spin-densities that are amongst the best.

We present a component-resolved analysis of the IR–X-ray connection in a sample of 104 spectroscopically confirmed Type~1 AGN. By combining \xmm, \swift/UVOT, and new high–angular resolution \jwst/NIRCam imaging for a subset of the sources, we constructed detailed SEDs in which the IR emission was explicitly decomposed into accretion-disk, torus, and polar-dust components. This approach enables us to isolate the intrinsic AGN-IR luminosities with minimal host-galaxy contamination, providing a clean assessment of the physical relationship between the accretion flow, circumnuclear dust, and the X-ray corona. By incorporating JWST/NIRCam observations into our SED decomposition, we significantly reduce host-galaxy contamination and isolate the nuclear infrared emission with greater fidelity, particularly at near-infrared (NIR) wavelengths. This improvement is most apparent at 1 $\mu\mathrm{m}$, where sources with JWST coverage exhibit a markedly steeper relation between $\nu$L$_{\nu}$ (2 keV) and the NIR luminosity than those without JWST data. This behavior is naturally explained by starlight dilution, whereby host-galaxy emission dominates lower-resolution measurements.

The terrestrial ionosphere is a major limitation for high angular resolution imaging at decametre wavelengths. Its rapidly varying and direction-dependent phase errors can defocus sources, reduce recovered flux densities, and produce strong field-to-field variations in image quality. We investigate these effects using three overlapping pointings from the LOFAR Decametre Sky Survey (LoDeSS), observed under different ionospheric conditions. Using phase-calibration solutions on a bright source, we derive the spatial diffractive scale, the temporal decorrelation time, and the angular scale over which direction-dependent calibration solutions can be transferred before residual phase errors become significant. These metrics are reflected in the final image quality. The field with the weakest ionospheric phase structure has the sharpest compact sources and the most reliable flux-density scale, while the field with the strongest phase structure shows substantial source broadening and flux-density loss. The comparison indicates that spatial ionospheric structure is the dominant limitation in these observations. Calibration-derived ionospheric metrics, therefore, provide a practical way to diagnose and predict image-quality variations in decametre survey data.

It is important to locate water-ice in the lunar regolith to build futuristic, sustainable bases there. But communication delays from Earth, limited bandwidth, and power constraints demand an onboard, autonomous, time-efficient decision-making framework for locating volatiles such as water-ice in the lunar regolith. In this work, we present a framework, DewTwin-Coin, that can locate potential water-ice sites in real time without drilling. Its decision-making principle is based on a find-S learning algorithm that uses surface temperature and the Hydrogen-to-Oxygen intensity ratio at a location. The core idea is a physics-based rule $-$ water-ice is stable only if the temperature is below 110 K and the Hydrogen-to-Oxygen intensity ratio is between 1.7 and 2.3. We validate DewTwin-Coin on Chandrayaan-3's 3165 laser-induced breakdown spectroscopy (LIBS) elemental data with 387 Chandra's surface thermophysical experiment (ChaSTE) data. On a 16 GB RAM system, it classified all 3165 locations within 615 seconds, yielding no strong signatures of water-ice, which matches the Chandrayaan-3 in-situ analysis. This framework is very important for future lunar and other planetary missions in which an onboard rover can autonomously determine feasible drilling locations for water-ice without issuing false drilling commands in warm terrains. Thus, the mission's onboard setup can stretch its technical limits in both power and memory capacity.

We investigate domain-wall physics in a non-Hermitian Su-Schrieffer-Heeger model featuring the non-Hermitian skin effect and its higher-dimensional extensions, focusing on analytical eigenstate solutions under open boundary conditions. By gluing two Su-Schrieffer-Heeger chains with inverted coupling ratios together, we identify two distinct interface geometries, and derive closed-form quantization conditions for the complex wave number and wave functions using symmetry-based ansatzes. Besides conventional skin modes and topological zero modes, the domain walls generate additional localized states at finite energy that detach from the bulk open-boundary-condition continuum. We validate the analytical results by exact diagonalization, and further generalize the interface construction to a two-dimensional Lieb lattice, where competing nonreciprocities produce tunable funneling regimes towards codimension-one and codimension-two interfaces.

Future near-infrared (NIR) astronomy missions dedicated to photon-starved science cases, in particular an all-sky astrometric survey extending the legacy of Gaia into the NIR, as identified within the ESA Voyage~2050 programme, require large-format detectors combining sub-electron effective read noise with very low dark current. Linear-mode avalanche photodiodes (LmAPDs) based on HgCdTe meet this need by multiplying the photo-generated charge by an avalanche gain before the readout stage, thereby reducing the relative contribution of the read noise. We report the first electro-optical characterization of an IBEX detector, a $2048\times2048$, \SI{15}{\micro\meter}-pitch HgCdTe LmAPD array developed by Leonardo with the European Space Agency and operated at \SI{80}{\kelvin} on a dedicated bench at CEA-IRFU. We first discuss the central difficulty of characterizing an APD array, the degeneracy between avalanche gain, quantum efficiency (QE), and conversion gain in the measured response, and we then separate the measurements into two categories. Among the quantities that are directly measurable without assumptions, we report a signal-to-noise ratio for a CDS measurement that exceeds that of a Euclid-type H2RG above \SI{8}{\volt} pixel bias under identical low-flux conditions, a photo-response non-uniformity stable at the $\sim$10% level, and a quantum efficiency-to-excess-noise ratio (QEFR) of \num{0.40} at \SI{10.5}{\volt}. Among the quantities derived under an explicit set of assumptions, we obtain a conversion gain corresponding to a sense-node capacitance of \SI{27}{\femto\farad}, a quantum efficiency of $46\pm12\%$ at \SI{2.5}{\volt}, and an excess noise factor $F=1.15\pm0.14$ at \SI{10.5}{\volt}. These results establish IBEX as a promising European large-format detector for future ultra-low-flux NIR instruments.

Because it offers exactly-integer topological quantities, the modified Villain discretization offers a route to correct anomaly structure at finite lattice spacing. I will present a 4-dimensional purely-bosonic modified Villain model with an ABJ-type vector-vector-axial anomaly. The model may have a direct continuous phase transition from one SSB phase to another, giving hope of yielding 4D CFT with a VVA anomaly.

Quantum batteries promise revolutionary advantages for energy storage but are fundamentally crippled by environmental decoherence, which induces self-discharge and rapid "aging." Here, we crack this critical bottleneck by exploiting the decoherence-suppression mechanism: the formation of system-environment bound states. We consider a charger-battery system embedded in a three-dimensional anisotropic photonic crystal bath and derive exact non-Markovian dynamics. Strikingly, we reveal a tunable phase diagram where modulating the atomic eigenfrequency and coupling strength switches the system between zero, one, and two bound states. In the presence of two bound states, the battery energy evolves into a persistent periodic oscillation, enabling lossless energy storage and on-demand extraction indefinitely, effectively realizing an aging-free quantum battery. Conversely, the absence of bound states leads to complete energy decay. We also demonstrate that even during self-discharge, a single bound state can stabilize extractable energy. This work establishes bound-state formation as a powerful and feasible strategy for combating decoherence, offering a clear blueprint for designing durable solid-state quantum batteries in non-Markovian photonic platforms.

Magnetars are young, isolated neutron stars that possess an exceptionally strong magnetic field, with surface dipolar strengths on the order of $10^{15}$ G. One of the plausible scenarios for generating such a strong field is an exponential amplification by a turbulent convective dynamo during the protoneutron star phase. However, the short expected duration of the convection ($\sim 10$ s) imposes a stringent constraint on the dynamo growth rate. We perform an extensive set of 82 three-dimensional convective dynamo simulations in the anelastic approximation and investigate the kinematic phase to quantify the dynamo growth rate $\gamma$. We find that $\gamma$ increases with both the magnetic Prandtl number ${\rm Pm}$ and the Rayleigh number ${\rm Ra}$, with the most unstable mode becoming highly non-axisymmetric and multipolar. We further observe a gradual transition from large-scale to small-scale dynamo as the magnetic Reynolds number ${\rm Rm}$ increases, resulting in a magnetic field that is predominantly concentrated at small scales. The trend remains unchanged when the outer magnetic boundary condition is varied. Since resolving the increasingly small scales becomes numerically impractical, we employ the theoretical small-scale Kazantsev dynamo model to explore the large ${\rm Pm}$ regime characteristic of protoneutron stars. The model qualitatively captures the growth rate behaviour observed in simulations and, upon extrapolation to the large ${\rm Pm}$ limit, indicates that $\gamma$ is only weakly dependent on the resistivity in a PNS. Under conditions relevant to the PNS, this model predicts a magnetic energy growth rate of the order of $\sim 1$ ms$^{-1}$.

Heavy-ion collisions provide unique access to the properties of QCD matter over a broad range of temperatures and baryon densities. We review recent progress in constraining the high-density phase structure of QCD, with particular emphasis on the microscopic inputs required for reliable transport modeling. We discuss cluster production, strange-particle interactions, collision dynamics at few-GeV energies, and the isospin dependence of the nuclear interaction, together with their impact on the interpretation of flow, yields, fluctuations, and possible critical signatures.

We prove a purely quasi-local positivity theorem for the Wang–Yau mass for a class of initial data whose Jang deformation, after a boundary-preserving conformal reduction to zero scalar curvature, lies in a sufficiently small transverse–traceless (TT) perturbative neighborhood of a strictly convex Euclidean fill-in.We explicitly construct a nontrivial class of physical initial data whose admissible Jang reductions realize this TT-generated sector. The argument reduces the Wang–Yau energy to the Brown–York mass of the resulting scalar-flat compact metric, together with nonnegative bulk terms determined by the Jang deformation, and establishes strict positivity by computing the second variation of the Brown–York functional at the Euclidean metric in transverse–traceless directions. The proof is entirely confined to the compact fill-in and uses neither an asymptotically flat extension nor the positive mass theorem. This gives a partial answer to a question of R. Schoen concerning a genuinely quasi-local proof of positivity for quasi-local mass.

We identify a topological constraint on extremal $\mathcal{N}=1$ AdS$_3$ spectra that is not implied by genus-one modular covariance of the three even spin structure partition functions. Assuming the expected topological modular forms divisibility of the Ramond Witten index, we show that for infinitely many odd $n$ at central charge $c=12n$, an extremal holomorphic $\mathcal{N}=1$ superconformal field theory requires an odd number of Neveu–Schwarz primaries at the BTZ threshold. Thus the strict ansatz with no threshold primaries is excluded for this infinite family.

Let $\Th(\alpha,L)=\sum_{v\in L}e^{-\pi\alpha|v|^2}$ for $\alpha>0$ and $E(L,s)=\sum_{v\in L\setminus\{0\}}|v|^{-2s}$ for $s>3/2$ be the theta and Epstein zeta functions associated to the lattice $L$, respectively. We are particularly interested in physically relevant dimension three. Fix the covolume of the lattice $L$ to $1$. Up to an orthogonal transformation, we prove that \begin{equation}\nonumber \argmin_{|L|=1}\Th(\alpha,L)= \begin{cases} \boldsymbol{\mathrm{FCC}}\;\;\mathrm{lattice},\;\;\;\;\;\;\;\;\; \;\;\;\;\;\;&\text{if}\;\; \alpha>1, \boldsymbol{\mathrm{BCC}}\;\;\mathrm{lattice}, \;\;\;\;\;\;\;\;\;\;\;\;\;\;\;&\text{if}\;\; \alpha<1, \boldsymbol{\mathrm{FCC}}\;\;\mathrm{or}\;\; \boldsymbol{\mathrm{BCC}}\;\;\mathrm{lattice},\;\;&\text{if}\;\;\alpha=1, \end{cases} \end{equation} and \begin{equation}\nonumber \argmin_{|L|=1}E(L,s)= \boldsymbol{\mathrm{FCC}}\;\;\mathrm{lattice},\;\;\;\;\;\;\;\;\; \;\;\;\;\;\;\text{if}\;\; s>3/2. \end{equation} Therefore, we prove the Sarnak–Strömbergsson conjecture \cite[Inequalities (43)–(44), Section 5]{SS}.

Inferring network structure from dynamical observations is a fundamental inverse problem in complex systems. Existing approaches have largely focused on single-layer or pairwise interaction networks, leaving the reconstructability of multiplex systems with higher-order interactions poorly understood. Here, we show that structural identifiability in such systems is jointly governed by cross-layer spreading couplings and network heterogeneity. Building on coupled awareness-behavior dynamics, we develop a multiscale inference framework that disentangles interacting spreading processes and enables the simultaneous reconstruction of microscopic simplicial interactions and macroscopic metapopulation organization. Numerical experiments on synthetic and empirical networks demonstrate high reconstruction performance, particularly in non-absorbing dynamical regimes sustained by weak inhibitory and strong facilitatory couplings. Results reveal the mechanisms governing structural identifiability in higher-order multiplex networks and provide a general route for inverse inference in multiscale complex systems.

Loading multiple quantum states in parallel into a quantum machine learning (QML) model can unlock learning tasks where key information resides in the relations between states rather than in individual states. We introduce an adaptive relational learning framework for such multi-instance quantum data that accesses pairwise and higher-order relations. Our model combines global measurements via SWAP or CYCLE tests for evaluating an $n$-state Bargmann invariant with shallow trainable transformations applied locally to each input state. We demonstrate the approach for continuous-variable (CV) photonic systems, which naturally provide access to quantum data and necessary computing operations. We solve tasks involving hidden relationship detection, geometric phase classification, and sensing in the presence of an unknown shared nuisance interaction. We benchmark the adaptive model against a non-adaptive “measure-first” approach based on continuous-variable classical shadows, and show that the cost of shadow estimation grows rapidly with $n$, while our model avoids this dependence. Already for $n=2$, we achieve perfect test accuracy $A=1.0$ with $500$ inference shots, improving average test accuracy over the shadow-based method by $\Delta A=0.15$ while using $100$ times fewer shots per data point. Our work opens routes to sensing and quantum-data applications where adaptive photonic QML can access relational features that are costly to recover with non-adaptive, measure-first models.

Independently at every vertex $x$ of a large core graph $\mathbb G$, we draw a random graph and connect $x$ to a subset of its vertices. This model of a randomly sprinkled graph captures qualitative features of commonly observed graphs; it can also be regarded as a model of quantum disorder, where disorder arises from local perturbations to the graph geometry. We show that it is naturally connected both to the Anderson model and to site percolation on $\mathbb G$ by deriving an Anderson-percolation representation for its spectrum. We characterize the support of the spectrum and derive quantitative bounds on the integrated density of states. We also analyse in detail the regime of sparse sprinkling, in particular investigating the behaviour of the density of states in the vicinity of atoms.

This work presents the spatially resolved mapping of methane decomposition chemistry in a short direct-current glow discharge, revealing segregated zones for dissociation and polymerization in an Ar-CH4 mixture at 400 mTorr. Laser-induced fluorescence (LIF), two-photon absorption LIF (TALIF), and optical emission spectroscopy (OES), are used to map the absolute number densities of atomic hydrogen (H), methylidyne (CH), and dicarbon (C2) radicals. The results reveal a segregated chemical environment driven by the non-local electron kinetics. The primary dissociation of methane is confined to the cathode sheath (< 4 mm), where the H atom density peaks at a value (). Analysis of the Halpha} line profile identifies two distinct suprathermal H atom populations with peak kinetic energies of ~110 eV and ~17.5 eV, attributed to ion-surface reflection and electron-impact dissociation, respectively. The densities of secondary radicals CH and C2 peak further from the cathode at the sheath-negative glow boundary (y=4-6 mm), identifying this region as the primary zone for polymerization, with the peak C2 density higher than that of CH by a factor of ~370. The discharge operates under strong non-equilibrium conditions, confirmed by the disparity between the low bulk gas temperature (~570 K) and the high vibrational temperature (3300-4700 K) of the emitting CH(A) radicals, the latter serving as a signature of a specific high-energy dissociative excitation pathway. This work demonstrates how the structured energy landscape of a short glow discharge spatially separates methane dissociation from subsequent polymerization. Kinetic estimates suggest that suprathermal H atoms may play a role in bulk plasma chemistry via abstraction reactions, with predicted CH4 activation rates exceeding those of the thermal H population.

We study the decoupling of branes sourcing AdS flux vacua from the asymptotic bulk using scalar-wave absorption probabilities. In a one-modulus truncation, the result depends only on the dimension of the AdS vacuum and on the asymptotic steepness of the scalar potential. We find that for any steepness and for any dimension greater than two the absorption probability vanishes in the low-energy limit, showing that the branes decouple from the bulk. We illustrate the general analysis in several scale-separated AdS vacua. For DGKT we find $P_{\rm abs}\sim\omega^{27/7}$ and an effective transverse dimension $d_{\rm eff}=20/7$. Interestingly, the scalar potential along the brane-induced moduli trajectory agrees with that obtained by compactifying a hypothetical $(4+13/7)$-dimensional gravity theory on a $13/7$-dimensional sphere threaded by flux. We also apply the analysis to scale-separated $\mathrm{AdS}_3$ examples and to the simplest one-modulus KKLT model.

Living systems compute with chemistry by mapping environmental signals onto specific internal chemical states. Despite recent advances in molecular programming, it remains unclear which physicochemical features control the computational expressivity of chemical systems. Here we inverse-design thermodynamically consistent chemical reaction networks whose steady-state response to an environmental input computes a target nonlinear function. Using implicit differentiation we train the free-energy landscape directly: standard chemical potentials, transition-state energies and thermodynamic drives. Increasingly large networks generated by elementary ligation and cleavage steps fit increasingly complex nonmonotonic polynomial functions, with expressivity scaling logarithmically with network size, predicted primarily by the number of reactions. Training individual energetic parameter classes reveals that internal thermodynamic drives, capable of breaking detailed balance, dominate trainability, with comparable performances achieved only by pairs of parameter classes. These results identify nonequilibrium drive as the most effective single resource for steady-state computational expressivity in chemical reaction networks.

I present the first implementation in MadGraph5_aMC@NLO for bound-state production, including quarkonium, leptonium, and B(c) mesons within Non-Relativistic Quantum Chromo-Dynamics (NRQCD) and Non-Relativistic Quantum Electro-Dynamics (NRQED). In these proceedings, I focus on the extension of MadGraph5_aMC@NLO to quarkonium states and describe the capabilities of the new framework for inclusive and associated S-wave quarkonium production in a wide variety of experimental environments at Leading Order (LO). These developments provide the community with a unified, automated, and efficient framework for bound-state production in QED and QCD, and establish a solid foundation for our future Next-to-Leading-Order (NLO) extension.