In this work, we compare three qubit-mapping strategies to study the structure of the nuclear ground state within the shell model description employing the Variational Quantum Eigensolver (VQE) approach. Although the initial point for different mappings is a Hamiltonian matrix in many-body particle basis or Slater determinant (SD) basis, the structure of the trial wavefunction and resource counts are different for each mapping. These three mappings are tested for a mid $p$-shell nucleus $^{10}$B and compared the quantum resources required to find the ground state for each mapping. Further, we extend the qubit-efficient mapping to study the ground state of one more mid $p$-shell nucleus $^{12}$C. We run circuits up to 26-qubits representing their ground states on a noisy simulator (IBM's FakeFez backend) and quantum hardware ($ibm\_fez$). The best post-error mitigated results from the hardware for $^{10}$B ground state is obtained following SD to qubit mapping with a percent error of 0.21 \%. The percent errors for the same state following cSD and pnSD mapping are 3.37 and 8.88 \%, respectively. On the other hand, following the cSD mapping, the post-error mitigated ground state energy of $^{12}$C is 6.82 \% away from the exact result. We further evaluate the fidelity of the VQE wavefunctions obtained from hardware with respect to the shell model wavefunctions for the cSD mapping. This cSD mapping can be useful for scaling the VQE algorithm for complex nuclei across different mass regions in terms of qubit efficiency.

The existence of a landscape of metastable vacua raises the possibility that our Universe may have undergone quantum vacuum decay at late times. This work explores how such a transition can be tested with cosmological observables, focusing on precision distance measurements and cosmic microwave background (CMB) anisotropies. A set of phenomenological models is constructed in which late-time quantum tunneling changes the vacuum energy and may convert a subcomponent of dark matter into dark radiation, possibly accompanied by domain-wall production. The resulting expansion histories are compared with DESI DR2 baryon acoustic oscillation data; supernova distance measurements from DES-Dovekie, Pantheon+, and Union3; and a compressed CMB likelihood. For quantum-tunneling models, current cosmological distance measurements still allow a 50% decrease in the total vacuum energy for a transition redshift $z_t<1$. The model with dark-matter conversion and domain-wall production provides a good fit to resolve the tension between cosmological observables and the $Λ$CDM model, with a preferred transition around $z_t \sim 7$ and about 10% of dark matter participating in the transition. Additionally, CMB anisotropy constraints from bubble nucleation and the associated domain-wall network are derived and shown to strongly restrict slow or sparse late transitions. Applied to the minimal quantum-tunneling model, these constraints allow an $\mathcal{O}(10\%)$ decrease in the total vacuum energy for a transition redshift $z_t$ of order unity. For nonminimal models, dark-matter-density-dependent tunneling can proceed rapidly enough to evade such bounds. These results demonstrate that late-time quantum vacuum decay is a testable cosmological phenomenon and provide a concrete observational handle on metastable-vacuum physics motivated by landscape scenarios.

LLMs are increasingly deployed to simulate social interactions, yet many of the existing simulators remain ad hoc and monolithic. This lack of architectural standardization prevents reproducible research and complicates downstream evaluation. We advance a rigorous science of LLM-based multi-agent simulation by modularizing core components into Environments, Agents, Simulation engines, and Evaluation metrics (EASE). We demonstrate the utility of EASE configuration by wrapping it in an experimental study schema for orchestrating workflows centered around answering explicit research questions in generated scenarios. We contribute SiliSocS, an open-source, research-ready Silicon Society Sandbox implementing a study-structured EASE configuration to enable highly configurable and reproducible LLM-based social simulations. Using SiliSocS and EASE, we present three case studies, showcasing the system's comprehensive assessment of existing questions, ability to dive deeper into complex questions, and elaboration of existing studies, respectively. Together, these case studies highlight the limitations of current modeling approaches and isolate the impacts of design choices on key results.

In this letter, we establish a complete correspondence between the Newman--Penrose and 1+1+2 semitetrad covariant formalisms by expressing all Newman--Penrose spin coefficients, Ricci scalars, and Weyl scalars in terms of the scalar, vector, and tensor variables of the 1+1+2 decomposition. This provides a direct dictionary between two widely used approaches to general relativity and gives a geometrical interpretation of Newman--Penrose quantities in terms of covariantly defined 1+1+2 variables. As an application, we derive necessary conditions for the existence of future outer trapping horizons in locally rotationally symmetric class II spacetimes, expressed in terms of the Ricci and Weyl Newman--Penrose scalars and the cosmological constant.

For a compact, connected, orientable Riemannian manifold with $b$ boundary components, we obtain geometric lower bounds for the low Steklov eigenvalues, namely $σ_k$, $1\le k\le b-1$. Our results complement earlier results, which apply only to $σ_k$ with $k\ge b$ and depend on the geometry near the boundary, by showing how the interior geometry influences the low eigenvalues. Our result also yields lower bounds for the low Steklov eigenvalues in the setting of pinched negatively curved manifolds, thus recovering similar results in that context through an alternative proof. The proof of the main result is based on the trace inequality relating the Steklov eigenvalue to the Neumann eigenvalues of the connected subdomains of the manifold containing a boundary collar. The geometric coefficient appearing in this inequality is given by an explicit formula in terms of a quantity that can be interpreted as the electrical resistance of the boundary collar.

The increasing complexity of industrial scheduling and transport routing problems motivates the study of alternative optimization formulations and computational paradigms. In this work, we study how higher-order unconstrained binary optimization (HUBO) formulations of such problems map onto quantum optimization workflows in both noisy and fault-tolerant regimes. We consider three representative logistics and manufacturing use cases and formulate each as a HUBO problem. This captures process intricacies, such as highly correlated assembly-line scheduling rules, which are difficult to express faithfully with the standard quadratic (QUBO) form, while at the same time reducing the number of binary variables required in the quantum mapping, thus lowering qubit demand. We compare the HUBO formulations with corresponding QUBO encodings, highlighting a key trade-off: while HUBO reduces qubit requirements through compact binary encoding, it introduces higher-order interaction terms that increase circuit depth, limiting feasibility on current quantum hardware. The proposed formulations are validated using classical solvers across several problem instances and benchmark small routing problem instances using bias-field digitized counterdiabatic quantum optimization in classical simulation. We complement these results with a resource and scalability analysis, focusing on the capacitated vehicle routing problem as a representative large-scale industrial use case. Our analysis indicates that while HUBO formulations offer advantages in qubit scaling compared to QUBO encodings, their practical implementation is constrained by gate fidelity, coherence, and circuit depth, making hybrid quantum-classical workflows and early fault-tolerant quantum hardware the most plausible settings for their practical use.

Efficient computation of the angular bispectrum is an essential part of modelling large-scale structure observations, but it still remains an extremely challenging task. In this work, we compute the tree-level, unequal-time angular bispectrum in both real and redshift space. By deriving full-sky results, we show that the bispectrum can be expressed as a sum of products of two angular power spectra, enabling the use of our recently developed flat-sky approximation to enhance computational efficiency significantly. This flat-sky formalism preserves key line-of-sight mode information while discarding extraneous full-sky contributions. We validate our approach by comparing it with direct full-sky integration, finding excellent agreement across a wide range of scales and redshifts for all bispectrum configurations. At redshift $z = 1$, we achieve sub-percent agreement (for multipoles $\ell \gtrsim 5$) between full-sky and flat-sky results for equilateral, squeezed, and folded configurations, using narrow Gaussian radial window functions ($σ_z = 0.01$) in both equal-time and unequal-time scenarios. On small scales, where direct full-sky integration becomes computationally prohibitive, our results align with the Limber approximation (where applicable), confirming the robustness and accuracy of our implementation. To facilitate future studies, we provide a \texttt{Python} implementation of our results, which is publicly available on \texttt{GitHub}.

We investigate transient clustering dynamics in nonlocal aggregation-diffusion systems from an energetic perspective. Starting from a stochastic interacting particle system, we study the associated macroscopic McKean-Vlasov equation on the torus and exploit its Wasserstein gradient-flow structure to analyse the thermodynamic competition between interaction-driven aggregation and entropy-driven diffusion. Through numerical experiments for locally attractive interaction kernels, we identify alternating aggregation- and diffusion-dominated transient regimes along trajectories converging to fixed equilibria. These dynamics can be interpreted as a form of non-monotone clustering behaviour. Moreover, we demonstrate that clustering observables, such as the density peak height, are only partially coupled to the underlying energetic mechanisms and therefore do not uniquely characterise the relevant macroscopic transport dynamics. Our results highlight the role of the variational structure not only for equilibrium analysis, but also as a framework for understanding transient clustering phenomena in interacting particle systems.

We explicitly account for electron-electron interactions when modeling low-dimensional helical organic molecules. We show that competition between various hopping channels, together with interaction-induced double- and superexchange mechanisms, can stabilize non-collinear helical magnetic order. The resulting single-electron bands exhibit partial spin polarization, a manifestation of $p$-wave magnetism. Using density-matrix renormalization group, cluster perturbation theory, and Monte Carlo methods, we find that even vanishingly small spin-orbit coupling triggers strong spin selectivity at temperatures significantly above the spin-orbit scale. While strong correlations are essential for this mechanism, long-range spin ordering is not required. We thus propose non-collinear spin correlations driven by Coulomb interactions as an explanation of chirality-induced spin selectivity and discuss connections to experiments.

We investigate the presence of primordial oscillatory features in measurements of CMB anisotropies through a systematic comparison of phenomenological templates. Building upon previous searches for primordial features using Planck data, we compare the full PR3 legacy release with the PR4 (NPIPE) processing to assess how the results depend on the choice of CMB maps and likelihood framework. To maximise our sensitivity to rapidly varying oscillatory signals, we employ unbinned likelihoods. We find that several previously reported indications of oscillatory structure persist across different analyses, although none attains global statistical significance. Furthermore, some anomalies reported in earlier studies are substantially reduced when updated to the new versions of the CamSpec likelihood using Planck PR4 products. For all templates considered, we identify a small number of frequencies in the range $ω\sim 10-100$ that improve the fit to the CMB data by up to $Δχ^2 \simeq -10$ to $-15$ relative to the featureless reference model. However, this improvement is not supported by a Bayesian model comparison. The inclusion of three or four additional parameters can reduces the overall predictability of the feature models and leads to an Occam penalty. Finally, after properly accounting for the look-elsewhere effect, the significance of the preferred frequencies is reduced, corresponding to a global statistical significance of at most $2.6σ$. We present forecasts for forthcoming CMB experiments, highlighting the decisive role of next-generation polarisation measurements in distinguishing genuine primordial oscillations from statistical fluctuations and modelling systematics. The upper bounds or uncertainties on the feature amplitudes, expected from the combination of SO and LiteBIRD, improve by more than one order of magnitude.

The realization of universal control in hybrid oscillator-qubit quantum processors enables the systematic design and implementation of quantum algorithms. However, the algorithmic development for such platforms remains at an early stage. While the Quantum Approximate Optimization Algorithm (QAOA) has been extensively studied in both continuous-variable (CV) and discrete-variable (DV) quantum systems, its development in the hybrid CV-DV setting remains limited. In this paper, we propose a hardware-native non-Abelian mixer for QAOA on hybrid CV-DV quantum processors and develop a corresponding hybrid ansatz for the Max-Cut problem. We evaluate the proposed ansatz on unweighted Erdős-Rényi graphs and benchmark it against the standard transverse-field mixer using the approximation ratio and optimal-solution probability. Across all graph sizes and Fock cutoffs in our simulations, the proposed non-Abelian mixer consistently improves both expected solution quality and the probability of sampling an optimal solution relative to the transverse-field mixer. These results indicate that the proposed non-Abelian mixer is a promising building block for QAOA on hybrid oscillator-qubit platforms.

We exploit the connection between quantum dot Dirac operators and $\overline\partial$-Robin Laplacians. First, we find a graphical relation between their smallest positive eigenvalues, which allows us to deduce a recipe for translating bounds (from above and below) from one to the other. As an application, we provide new upper and lower bounds for the eigenvalues of the quantum dot Dirac operators, which depend only on geometric quantities of the underlying domain. In particular, we obtain some Faber-Krahn type inequalities for convex thin domains.

We show that bright squeezed vacuum light, combined with a single-shot quadrature measurement of the post-interaction light, enables the ultrafast generation of macroscopic quantum states in matter. Although in the weak-coupling regime multiphoton quantum light leaves the unconditional matter state as a classical mixture due to light--matter entanglement, quadrature-based heralding prepares the matter in a Gaussian-weighted quantum superposition. For an ensemble of resonantly electric-dipole-coupled two-level systems, this heralding dynamics acts as a Gaussian filter with respect to the electric polarization, with brighter squeezed-vacuum light accelerating the preparation of the zero-eigenvalue Dicke state. Counter-rotating terms further drive a stroboscopic transition from this Dicke state to a cat-like state. Our results open a route to ultrafast engineering of macroscopic quantum matter with strong-field quantum light.

We prove an inversion theorem for recursive formulas satisfied by certain families of converging power series in two variables. These power series are indexed by the Harder-Narasimhan types of principal $G$-bundles of degree $d \in π_1 G$ on a smooth projective curve $X$, where $G$ is a connected complex reductive group. As an application, we obtain a closed formula for the Hodge-Poincaré series of moduli stacks of semistable principal $G$-bundles of degree $d$. We also compute the variation of Hodge structure of the moduli stack of all principal $G$-bundles over $X$, as a function of the period matrix of that curve.

This paper proposes a scenario-based framework for predictive maintenance scheduling under uncertainty in a finite planning horizon. The considered setting involves multiple assets for which maintenance decisions are informed by three heterogeneous sources of information: calendar-based overhaul intervals, usage-based limits driven by uncertain future operating cycles, and condition-monitoring outputs represented through remaining useful life (RUL) estimates with uncertainty. While these elements have been studied extensively in the maintenance literature, they are often treated separately or only partially integrated. In contrast, the proposed formulation evaluates complete maintenance schedules under simulated future scenarios and compares them using expected-cost and tail-risk criteria. The contribution is primarily conceptual and methodological: we define a unified finite-horizon decision framework that combines calendar-, usage-, and prognostics-based information within a common scheduling problem. A small synthetic computational example is used as a proof of concept. The results show that integrated scenario-based policies can substantially outperform simpler single-trigger rules, while the difference between risk-neutral and risk-aware integrated policies remains modest under the present calibration.

We study the primary constraint structure of Newer General Relativity, a gravity theory based on a torsionless teleparallel geometry. The gravitational action is built from a scalar formed by quadratic combinations of the nonmetricity tensor, with arbitrary coefficients $c_i$ in the Lagrangian. We decompose the Lagrangian and compute the canonical momenta conjugate to the metric. We characterize the primary constraints arising from these momenta by identifying when the map between velocities and momenta becomes non-invertible, and organize the outcome through a fully nonlinear decomposition into scalar, vector and tensor sectors. Comparing with previous results in the literature, we recover five and three primary constraints associated with the tensor and vector sectors, respectively. We also identify a previously unreported degeneracy in the scalar sector, which yields either one or two scalar primary constraints depending on the conditions imposed on the parameters $c_i$. Finally, we obtain the primary constraints associated with the covariant formulation of symmetric teleparallel gravity.

Noise is typically treated as the adversary of quantum information processing. For open quantum dynamics, however, dissipation is part of the target physics, creating a tension with fault-tolerant architectures designed to suppress decoherence. Here we show that logical noise can instead be turned into a calibrated resource. We treat the error-correction cycle as a programmable primitive: one fault-tolerant round induces a logical completely positive trace-preserving map, and decoder/recovery randomization generates a controllable family of logical channels whose convex mixtures realize Kraus-channel mixing. This enables direct compilation of target dissipators into effective logical dynamics without explicit ancilla qubits for encoding the bath degree of freedoms. We derive an accuracy criterion for multi-step simulation in which the code distance is chosen so that uncontrolled logical errors remain a small fraction of the intended dissipation per step, rather than being driven below an arbitrarily small closed-system tolerance. Partial quantum error correction thus repurposes fault-tolerant structure to sculpt dissipation, offering a resource-efficient route to quantum simulation of open quantum systems.

In this paper, we present HyperPrecision, a Mathematica package for high-precision numerical evaluation of general Horn-type multivariate hypergeometric functions and their Laurent expansions in a small parameter $ε$. Such functions appear widely in physics and mathematics, with applications ranging from quantum field theory and string theory to number theory and statistics. Their high-precision numerical evaluation, however, remains challenging, since their defining series converge only in restricted domains and analytic continuation beyond these domains is, in general, non-trivial. HyperPrecision addresses this problem by automatically constructing the Pfaffian system of partial differential equations for a given hypergeometric function and restricting it to a one-dimensional contour in the space of variables connecting the starting to the target point. The resulting ordinary differential equation is then solved by the Frobenius method, with boundary conditions fixed analytically by the defining series. We illustrate the use of the package by evaluating commonly occurring multivariate hypergeometric functions, including the Appell $F_1$, $F_2$, $F_3$, and $F_4$ functions, the Horn $G$- and $H$-series, and the Lauricella $F_A$, $F_B$, $F_C$, and $F_D$ functions, as well as by considering applications to angular integrals, Feynman integrals, and cosmological and holographic correlators.

Electronic identities (eIDs) are crucial in an increasingly digitalized environment. Pseudonyms, as offered by Austria's governmental sector-specific personal identifiers (bPks), can significantly improve privacy by ensuring that personal data is not universally traceable across public services and private companies. However, the current architecture comes with several challenges regarding availability, privacy, and authenticity, due to a fully centralized design. This paper proposes bPk#, a distributed architecture to address these issues, reducing reliance on the central authority, while still providing all functional requirements to the existing bPk system. In particular, users are delegated the rights to compute their own pseudonyms, thereby minimizing metadata revealed to the central authority, while (subsets of) service providers may receive the right to compute pseudonyms only within their own domain, thereby reducing the availability needs of the central authority. To the best of our knowledge, we provide the first formal framework for such delegatable pseudonym systems, together with a generic construction for which we provide formal security proofs. Furthermore, we propose a concrete instantiation of our construction, together with a reference implementation demonstrating the practical efficiency.

Chiroptical techniques for detecting and characterizing the chirality of matter and artificial nanostructures are traditionally based on their interaction with chiral light, typically circularly-polarized fields propagating in free space. More recently, these approaches have been extended to integrated photonic platforms, offering significant practical advantages. However, the generation of chiral guided light is challenging, it requires degeneracy of the fundamental modes of the integrated waveguide, which occurs at a single wavelength and limits broadband characterization. Here, we introduce and simulate numerically a new alternative integrated optical configuration inspired by the Stern-Gerlach experiment, in which a chiral sample is illuminated by a linearly polarized light beam. Such a beam exits from a dielectric waveguide that propagates the fundamental TE mode, thereby eliminating the need for circularly polarized excitation. On this basis, enantio-discrimination is achieved through a spatially resolved scheme using a symmetric arrangement of optical antennas on either side of the propagation axis. Our simulation results suggest that the selective scattering and absorption of the circular polarization component matching the chirality of the sample induces an imbalance of (spin) angular momentum of the optical field, resulting in a transverse deflection of the beam toward the corresponding side. This on-chip platform then provides a direct route to chiroptical functionalities under linearly-polarized illumination, enabling compact implementations of chiral sensing, spectroscopy, optical computing, and communication schemes.

Match-fixing undermines the integrity of sport by eroding public trust and threatening the financial sustainability of clubs and leagues. The global expansion of sports betting markets has created new incentives and opportunities for manipulation, calling for rigorous, data-driven monitoring tools. Football, which accounts for the largest share of global betting turnover, remains particularly exposed: integrity reports continue to flag several suspicious matches, with past scandals in Italy and Turkey underlining the problem's persistence. This study uses high-frequency live-betting data from the Italian Serie B (2018/19-2020/21) to explore statistical approaches for detecting abnormal betting behaviour. A state-space modelling framework is employed to describe standard betting market dynamics and to predict expected betting volumes conditional on match characteristics. Deviations from these expectations can then be analysed using outlier detection techniques to identify potentially suspicious periods. The results demonstrate how statistical modelling can contribute to the early identification of irregular betting patterns, thereby supporting integrity assurance in live sports betting markets.

A differential phase shift of a low-power spin wave (SW) induced by a high-power pumping wave co-propagating at different frequencies in perpendicularly magnetized magnetic films has been studied. We find that this effect for forward volume SWs propagating in yttrium iron garnet (YIG) films is stronger than that for surface SWs propagating in tangentially magnetized films. The results show that the induced nonlinear phase shift up to 180° takes place for pumping wave power of a few milliwatts. The phenomenon paves the way for fast and energy-efficient control of one-dimensional magnon transport.

Legal article retrieval is critical for building traceable and reliable legal AI systems, where conclusions must be grounded in specific legal articles. However, existing open-domain retrieval methods rely heavily on surface-level lexical or semantic similarity, making it difficult for them to distinguish legally relevant articles from those that are textually similar but legally inapplicable or misaligned with the user's underlying intent. To bridge this gap, we propose \textsc{LexPath}, a domain-oriented multi-path framework comprising a multi-path retrieval module and an intent-aware reranking module. The retrieval module combines two complementary legal-specific paths to collect candidate articles: an IRAC-guided sparse path that expands queries with legally informative keywords, and a structure-guided dense path trained with hard negatives derived from legal hierarchy and citation relations. Then, the reranking module further refines the candidate ranking by incorporating the intent consistency score between queries and legal articles. We evaluate \textsc{LexPath} on two publicly available benchmarks focusing on general-public queries and a self-constructed benchmark targeting domain-professional scenarios. Experimental results demonstrate that \textsc{LexPath} consistently outperforms lexical, dense, hybrid, and adaptive retrieval-augmented generation (RAG) baselines. Ablation studies further verify the effectiveness of each component.

The ground-state many-body electron momentum density, which can be probed by x-ray Compton scattering, holds insights into the electronic structure of materials. Comparisons between the measured so-called Compton profiles and the theoretical ones are invaluable in assessing the successes and failures of the methodology used to generate the theoretical ground-state electronic structure. Here, we present calculations of the Compton profiles of Li, Si, Cr, and Ni using the state-of-the-art QSGW method within the Questaal package compared with density functional theory (DFT), one-shot $GW$ ($G^0W^0$) predictions and with experiment. This comparison reveals significant differences between the QSGW and $G^0W^0$ methods which we attribute to the distinction between the single particle density provided by the QSGW method and the many-body density that we construct from the $G^0W^0$ theory; although in general the QSGW description of the electronic structure is superior to that of $G^0W^0$, we find the use of the many-body reduced density matrix is key to improving the agreement of the Compton profile with experiment.

The membership inference problem for publicly released statistics from a private dataset is well-studied. When developing and formally analyzing attack strategies, however, the focus has been on attacks that model the population using only its marginals. In practice, these attacks can perform well on various populations, however most formal analysis is for populations that follow a product distribution. These strategies may fail to leverage useful information about the population that is important for understanding a realistic privacy threat. In this work, we explore the impact of providing an attacker with additional information about the attribute dependency structure of the population, motivated by examples where multiple parties may have access to similarly structured data, for example the US Census and the IRS. To model this scenario, we re-frame the membership inference problem with respect to a population represented as a Bayesian network (BN). We develop a framework based on Bayesian decision-making which can incorporate prior information about the population to launch more effective, specialized attacks. To evaluate our framework, we introduce a specific attack instantiation which computes the Bayesian posterior using a probabilistic program, and prove its equivalence to an optimal variant of the likelihood ratio test attack for two populations with strong attribute dependency. We implement our program in the Roulette probabilistic programming language and show experimentally that it outperforms the likelihood ratio test and inner product attacks on five commonly used BNs, where the population dependency structure is too complex for the existing attacks to be manually adapted.

We construct the causal fermion system for globally hyperbolic spacetimes starting in the framework of algebraic quantum field theory. The fermionic projector is identified with the one-particle density operator of a quasi-free Hadamard state. The ultraviolet regularization is built into the fermionic projector via a chart-independent $i\varepsilon$-regularization scheme. The continuum limit analysis is developed in globally hyperbolic spacetimes. It is shown that the Euler-Lagrange equations of the causal action principle are satisfied in this setup if and only if the coupled Einstein-Dirac equations hold.

Recent literature shows that hypocoercivity properties of linear evolution equations (in particular their exponential decay and the sharp short time decay of their propagator norm) carry over to their discretization via the midpoint rule. This note discusses this connection for the (other) $θ$-methods, i.e.\ for $θ\ne\frac12$. It is shown that any implicit discretization with $θ\in (\frac12,1]$ (pertaining to a hypocoercive continuous-time evolution equation) is contractive, and not only hypocontractive -- in contrast to the midpoint rule. For a coercive continuous-time evolution equation, a discretization with $θ\in [0,\frac12)$ is contractive for time steps small enough.

Conjugated polymers exhibit unique spin-dependent phenomena arising from weak yet critical hyperfine interactions. Understanding these spin effects, particularly the spin-dependent formation and decay of correlated spin pairs, is important for advancing both organic electronics and polymer-based spintronics. Intrinsic magnetic-field responses such as magnetoresistance have primarily been investigated in diode architectures, where electrons and holes coexist. However, such systems are less suitable for probing bipolaron formation in unipolar transport, and the relationship between polymer structure and bipolaron formation in lightly doped polymers remains unclear. Here, we systematically investigate intrinsic magnetoresistance in representative conjugated polymers using field-effect transistors and observe a generally positive magnetoresistance. First-principles simulations reveal that bipolarons preferentially form on short conjugated segments associated with amorphous regions. Moreover, comparisons across these polymers show that enhanced charge trapping correlates with stronger magnetoresistance, implying promoted bipolaron formation. Bipolaron-incorporated energylevel-alignment modeling near metal/polymer interfaces suggests that charge traps can increase the bipolaron density.

Low threshold cryogenic calorimeters are a key technology for the advancement of rare-event searches. However, since a few years their sensitivity reach is challenged by the presence of a rising spectrum at low energies named low-energy excess (LEE), ascribed to an unknown background. In this work, we describe the LEE as absorber events induced by the relative thermal-contraction coefficient mismatch between the absorber and the SiO$_2$ amorphous layer underneath the transition-edge sensors (TESs), present for example in the case of CRESST detectors. The relative contraction in processes with temperature changes, such as during sensor fabrication and cooldown from room temperature to the temperature of operation, can induce surface dislocation nucleation. Other interfaced materials with thermal-expansion mismatch can also generate dislocations during temperature-variation processes. We formulate a simple elastic model to bridge this solid-state effect and the LEE observations. Double-TES modules have been designed to provide surface background rejection. We highlight that the presence of the LEE in the coincident event band of double-TES modules does not exclude the explanation given in this work. Exemplary, we discuss the role of the thermal boundary resistance between absorber and sensor as explanation for the presence of the LEE in the coincident-event band. We propose detector designs to test these hypotheses and mitigate the LEE.

We present a lattice QCD determination of the Mellin moments of the unpolarized gluon parton distribution function in the proton. The analysis is based on matrix elements of nonlocal gluon operators coupled to momentum-boosted proton states. The calculation relies on an $N_f=2+1+1$ ensemble of maximally twisted mass fermions with clover improvement and the Iwasaki-improved gauge action, at a pion mass of approximately 260 MeV. Working within the short-distance operator product expansion (OPE) of the reduced gluon Ioffe-time distribution, we extract ratios of higher-order gluon moments, $\langle x^n\rangle$ with $n>1$, to the gluon momentum fraction, $\langle x\rangle$. We investigate systematic effects associated with the truncation of the order of moment in the OPE, the choice of minimum and maximum Wilson-line separations entering the analysis, and the treatment of mixing with the quark-singlet under perturbative matching. The stability of the extracted moments is further studied under scale evolution using DGLAP equations, allowing us to assess uncertainties related to perturbative truncation by varying the scale. Our work provides a determination of the ratio $\langle x^3\rangle_g/\langle x\rangle_g$ at a scale of 2 GeV, with uncertainties that account for both statistical and the dominant theoretical systematic uncertainties.