The creation and exploration of new materials under extreme pressure-temperature conditions has become increasingly reliant on laser-heated diamond anvil cell (LHDAC) techniques, which provide direct access to previously unexplored regions of multinary phase diagrams. Whereas numerous high-pressure phases have been identified in situ, systematic recovery and post-synthesis physical property characterization of these materials remain significant challenges. In this work, we present the development of an integrated LHDAC synthesis and demonstrate a practical LHDAC-based synthesis workflow that enables stabilization and recovery of metastable intermetallic phases for subsequent structural and transport studies. Using this approach, we successfully achieved LHDAC synthesis of high-pressure MnSb2 and YbZn2 phases under moderate pressures. Synchrotron X-ray diffraction and spatial mapping confirm dominant formation of the targeted phases, whereas laboratory-based refinement quantifies phase fractions despite intrinsic microstrain and minor secondary phases. High-pressure transport measurements on recovered samples reveal tunable by pressure electronic instabilities in both systems. In MnSb2, pressure suppresses two high-temperature magnetic ordering anomalies, observed in transport, by 5 GPa and for higher pressures induces a new low-temperature feature that increases with further pressure increase. In hexagonal high-pressure YbZn2, an electronic reconstruction emerges at ~11 GPa, characterized by semiconducting-like behavior from ~ 30 K to 300 K and a broad low-temperature coherence crossover near 30 K. Our results establish LHDAC synthesis not only as a structural discovery tool, but also as an experimental platform for investigating correlated quantum states stabilized far from equilibrium thermodynamic conditions.

In core/shell quantum dots (QDs), the interface between semiconductors of different chemical character largely determines their optoelectronic properties. In III-V/II-VI systems, this boundary involves pronounced chemical and electronic discontinuities that can generate trap states even under complete surface passivation. Using density functional theory on atomistic models of InAs/CdSe QDs, we systematically reconstruct atomic arrangements at the surface and interface to evaluate how local coordination and interfacial dipoles influence the electronic structure. Abrupt interfaces induce charge imbalance and band-gap collapse, whereas introducing an alloyed interlayer that mixes core and shell atoms and vacancies restores energetic alignment and yields delocalized band-edge states, consistent with experimental findings. We also introduce a charge-flow analysis that quantifies charge redistribution across the QD, providing a framework for realistic modeling of interlayer formation and predictive design of defect-free interfaces in core@shell architectures.

Fast and Relaxed Vector Fitting (FRVF) is a frequency-domain system identification approach that has been widely adopted in electrical system modelling, while its application to mechanical systems has remained relatively unexplored. In this work, FRVF is reformulated for the identification of structural modal parameters of an aircraft based on Ground Vibration Test (GVT) data within a Multi-Input Multi-Output (MIMO) framework. The proposed procedure consists of three stages: (i) rational approximation of frequency response functions via an enhanced input-stacking strategy, (ii) identification of system poles from the resulting rational model, and (iii) estimation of modal parameters from the extracted poles and associated residues. The methodology is first numerically validated on a MIMO beam model, with particular emphasis on accuracy and robustness under increasing measurement noise. Subsequently, experimental validation is conducted using GVT data from the BAE Systems Hawk T1A aircraft. The results obtained demonstrate a level of performance comparable to that achieved by existing methods. Overall, the extended MIMO formulation of FRVF exhibits high accuracy and strong robustness to measurement noise, highlighting its suitability for application in GVT-based modal analysis.

Monte Carlo event generators are the central interface between theoretical calculations and experimental measurements in collider physics. Over several decades, a comprehensive and highly modular ecosystem of tools has developed around them, encompassing matrix-element calculations, parton showers, hadronisation models, and their integration with detector simulation, event-level analysis and statistical inference. While these tools are ubiquitous in modern research, the conceptual scope and technical structure of the full simulation chain can be challenging to navigate, particularly for researchers entering the field. In this primer, we provide a structured and up-to-date overview of the high-energy physics Monte Carlo ecosystem, focusing primarily on event-generator methodologies and their role within the broader collider workflow. We discuss the conceptual foundations of modern generators, the computational and organisational challenges of large-scale simulations, and the principles that enable interoperability and reproducibility across theory and experiment. We also examine the evolving computing landscape and sustainability considerations that will shape the future development of these tools. Aimed primarily at early-stage doctoral researchers while serving as a reference for the broader community, this article seeks to clarify architecture, methodology, and long-term trajectory of Monte Carlo event generation in collider physics.

We study the Sudakov form factor and the four-point scattering amplitude on the Coulomb branch of planar $\mathcal{N}=4$ SYM as functions of the Coulomb-branch parameters and kinematic invariants. This setup provides a controlled probe of the interpolation between on- and off-shell regimes of infrared-sensitive quantities in gauge theories. We identify a novel scaling limit in which both observables exhibit double-logarithmic behavior governed by a walking anomalous dimension. As the mass scales are varied, this walking anomalous dimension interpolates between the cusp anomalous dimension of the on-shell regime and the octagon anomalous dimension of the off-shell regime. Based on the explicit two-loop result and the expected all-order structure, we propose an all-loop form for the walking anomalous dimension both for the form factor and for the four-point scattering amplitude. These all-loop expressions depend on new, presently unknown functions of the 't Hooft coupling.

We consider the problem of testing the mean of high-dimensional data when the dimension may grow without explicit rate restrictions relative to the sample size. The proposed procedure is based on the statistic V_n = n||Xn||^2, which avoids inversion of the covariance matrix and is therefore suitable for high-dimensional settings.We establish asymptotic distributional results for both fixed and increasing dimension by embedding the observations into the Hilbert space l2. Furthermore, we prove the asymptotic validity of a bootstrap approximation for the distribution of the test statistic. The resulting bootstrap test yields asymptotic level-a procedures without requiring sparsity assumptions or structural conditions on the covariance matrix. In all this, a new Central Limit Theorem in l2 is proving to be an extremely useful tool.

A base for a subgroup $G$ of $\mathrm{Sym}(Ω)$ is a sequence of elements of $Ω$ with trivial pointwise stabiliser. The size of the smallest base for $G$ is denoted $b(G)$. There is a natural greedy algorithm to compute a base for $G$, and it was conjectured by Cameron in 1999 that there exists an absolute constant $c$ such that if $G$ is primitive then any base returned by this algorithm has size at most $cb(G)$. In this paper we determine the size of every base returned by the greedy algorithm when $G$ is a primitive group of diagonal type, and hence prove Cameron's conjecture for these groups. The relational complexity $\mathrm{RC}(G)$ of $G$ is a measure of the way in which the orbits of $G$ on $Ω^k$ for various $k$ determine the action of $G$ on $Ω$. Very few precise values of relational complexity are known, and in particular it is not known which primitive groups have relational complexity $3$. In this paper we prove that if $G$ is primitive of diagonal type then $\mathrm{RC}(G) \geqslant 4$, that this lower bound is attained by infinitely many such $G$, and that the relational complexity of the groups of diagonal type is unbounded.

Ventilated acoustic silencers combing sound attenuation with high ventilation are pivotal for advanced noise control. However, balancing attenuation, bandwidth, openness, and thickness remains a high-dimensional challenge. Here, we report a physics-aware machine-learning-driven inverse design framework for ultra-open acoustic silencers (UAS). By leveraging Green's function-based parameterization, we physically decouple the design space into spectral and radial parameters, ensuring physical interpretability while reducing complexity. We introduce a two-stage forward prediction architecture that captures broadband envelopes and sharp resonant features via a coarse-to-fine strategy. Coupled with a population-based, hybrid-objective parallel (PHP) inverse strategy, our framework enables rapid exploration of non-convex landscapes, identifying hundreds of optimized candidates within seconds. Crucially, this framework uncovers hidden linear design rules that govern high-performance monolithic designs, acting as geometric proxies for optimal impedance-matching. We experimentally validate a family of prototypes: UAS-2 demonstrates the monolithic limit with high ventilation ratio, while UAS-3 demonstrates versatility in multi-mode interactions. To circumvent the trade-off ceiling of single-unit resonators, a parallel-composite architecture (UAS-4) is introduced to enhance performance through spatial interference distribution. Results confirm a broadband bandwidth exceeding 830 Hz achieved with an ultra-thin profile (0.1-0.2λ) and 80% ventilation. This work establishes a data-driven paradigm for discovering design principles in functional metamaterials.

Dynamical quantum phase transitions (DQPTs) occur at times when a quantum state exhibits a nonanalytic change in its return probability. This can be viewed as the probability of collapsing the evolved state to the initial state by quantum measurement. However, the initial wave function usually has exponentially small amplitude in the late time evolved state. Here we perform statistical characterization for all the possible post-measurement states distributed according to the Born's rule, by sampling a one-dimensional quantum Ising chain after a quantum quench dynamics. The statistical ensemble can also be viewed as a mixed state when the time evolved state is subjected to maximally dephasing noise in a certain basis. We map the distribution to a statistical model and characterize its effective "energy" spectrum, and introduce the average dynamical free energy, establishing a framework for the statistical DQPTs. We show the recovering of DQPT under high-moment average and a delocalized level distribution following critical times. Through analytic continuation into the complex time plane, we demonstrate the vanishing of Yang-Lee-Fisher zeros and the emergent level crossing near critical times. Finally, we propose a measurement-based quantum computation protocol to simulate the unitary evolution via single-qubit measurements on a two-dimensional cluster state. Our results provide a way for experimentally investigating statistical DQPTs in quantum devices, shedding light on the structured circuit sampling with insights from DQPT and generalizing the understanding of mixed state due to decoherence beyond equilibrium.

A classical enumerative result states that, given a graph $G$ and a vertex $u$, the number of connected subgraphs of $G$ is equal to the number of orientations of $G$ such that every vertex can reach $u$ by a directed path. We show that this result is an instance of a much broader set of enumerative identities between subgraphs and orientations corresponding to various connectivity constraints. Namely, given two sets of pairs of vertices $A=\{(u_i,v_i), i\in[k]\}$ and $B=\{(u_i',v_i'), i\in[l]\}$, we consider the orientations $α$ of $G$ such that adding the elements of $A$ and $B$ as additional directed edges to $α$ gives an orientation $α'$ in which $v_i$ cannot reach $u_i$ for all $i\in[k]$, but $v_i'$ can reach $u_i'$ for all $i\in[l]$. We show that this set of orientations is equinumerous to a set of subgraphs satisfying the ``same" connectivity constraints defined in terms of $A$ and $B$. We also extend our results to the enumeration of equivalence classes of orientations satisfying such connectivity constraints. Precisely, we consider the equivalence classes under cycle reversal, cocycle reversal, or cycle-cocycle reversal. We show that the equivalences classes are equinumerous to some sets of subgraphs defined by connectivity and acyclicity constraints.

Expectations of multivariate functions with missing labels occur in various fields such as transfer learning and average treatment effects. Although non-parametric estimators based on nearest-neighbour matching are frequently used in this context, the existing literature assumes that the covariates live in some well-shaped compact subset of $\R^d$, with densities that are bounded away from zero. In this paper, we show that the usual rates of convergence can be achieved with minimal assumptions on the covariate supports. These assumptions are replaced with conditions on the source and target distributions, among which a measure of the tranferability between the two probability measures. We show that these conditions are general, can be applied to distributions supported on manifolds, and allow the target distribution to have a heavier tail than the source distribution. We also show that this control of the transferability is needed for any estimator to achieve good rates of convergence. Finally, applying our results to the estimation of treatment effects, we could relax the assumption that the assignment probabilities had to be bounded away from zero and one.

Starting from a thorough analysis of the conjugate $\overline{H}$ of a complex Hilbert space $H$, including its significant importance regarding a representation of the tensor product of two complex Hilbert spaces and its impact to the theorem of Fréchet-Riesz over to a revisit of applications of nuclear and absolutely $p$-summing operators in algebraic quantum field theory (AQFT) in the sense of Araki, Haag and Kastler ($p=2$) and more recently in the framework of general probabilistic spaces ($p=1$), we will outline that Banach operator ideals in the sense of Pietsch, or equivalently tensor products of Banach spaces in the sense of Grothendieck are even lurking in the foundations and philosophy of quantum physics and quantum information theory. In particular, we concentrate on their importance in AQFT (Theorem 5.27). In doing so, we revisit the role of trace-class operators in quantum theory and construct the enveloping $\tup{C}^\adj$-algebra, corresponding to an arbitrarily given normed operator ideal (Proposition 5.3 and Theorem 5.5). Applications are presented, including a purely linear algebraic description of the quantum teleportation process, thereby showing a link to quantum information theory, also due to the emergence of the Hadamard-Walsh transform and the controlled NOT gate (Example 4.18). All Hilbert spaces discussed in this paper may be nonseparable (and hence infinite-dimensional).

In recent developments, a novel set of necessary optimality conditions for mixed constrained optimal control problems, termed the asymptotic weak maximum principle, has been formulated. These novel conditions deviate from the classical ones by virtue of their sequential nature and the fact that they are satisfied regardless of the regularity conditions imposed on the mixed constraints. Furthermore, due to their asymptotic behaviour, these conditions serve as a precise tool for use as stopping criteria in numerical methods of solution. However, it should be noted that, in certain instances, these conditions may not be sufficiently robust to fully characterize optimal solutions, as they can be satisfied by processes that are not extremals. The present study proposes a novel constraint qualification, meticulously developed to address these asymptotic optimality conditions. It is demonstrated that the asymptotic weak maximum principle implies the classical weak maximum principle when the newly proposed constraint qualification is verified. It is further demonstrated that, in the smooth setting, this constraint qualification is the weakest one that possesses such a property. Additionally, this study present sufficient criteria for the validity of the newly proposed constraint qualification.

The inclusive cross sections for charm ($\mathrm{c}\overline{\mathrm{c}}$) and bottom ($\mathrm{b}\overline{\mathrm{b}}$) quark-antiquark pair production in proton-proton, proton-antiproton, and proton-nucleus collisions are studied over a wide range of center-of-mass energies, $\sqrt{s}\approx 10$ GeV--400 TeV. All existing data over $\sqrt{s}\approx 10$ GeV--14 TeV are collected and compared to calculations at next-to-next-to-leading-order (NNLO) accuracy using the new fixed-order MaunaKea open-source code for varying sets of parton distribution functions (PDFs). Relative to next-to-leading-order (NLO) predictions, the NNLO cross sections are enhanced by up to a factor of two, with the associated theoretical scale uncertainties reduced by the same amount, leading to agreement with experimental data over the full range of collision energies. The NNLO results are also compared with NLO predictions obtained within the SACOT-$m_{_\mathrm{T}}$ general-mass variable-flavour-number scheme. Despite still sizable theoretical and experimental uncertainties, $\mathrm{c}\overline{\mathrm{c}}$ cross section at multi-TeV energies can provide extra constraints on the gluon density at very small-$x$ in global PDF analyses. In the bottom sector, more precise cross section measurements at low energies, $\sqrt{s}\approx 10$--100 GeV, can help constraint the bottom-quark pole mass.

We compare the predicted phase behaviour of lead (Pb) using three different interatomic potential models, including an embedded atom method (EAM), a modified embedded atom method (MEAM), and a neural network-based machine-learned model in the form of an ephemeral data-derived potential (EDDP). Using nested sampling and replica-exchange nested sampling simulations, we computed thermodynamic and structural properties at pressures up to 60 GPa, mapping both melting behaviour and solid-phase stability. Both the EAM and MEAM models predict the face-centred cubic (FCC) phase to remain stable up to approximately 60 GPa. In contrast, the EDDP model captures the experimentally-observed FCC-to-hexagonal close-packed (HCP) transition at around 15 GPa. These results highlight the importance of training data and model flexibility in accurately describing high-pressure phase behaviour, and demonstrate the effectiveness of nested sampling as a robust framework for exploring phase stability in materials. Particularly, the combination of nested sampling with modern machine-learned interatomic potentials - delivering near ab initio accuracy at tractable cost - opens the door to truly predictive and exhaustive exploration. EDDPs trained on diverse, out-of-equilibrium configurations appear particularly well suited to this task, offering a robust and transferable framework for unbiased phase discovery.

The product formula, commonly known as Trotter decomposition, is a central tool for digital quantum simulation, whose performance depends critically on how the Hamiltonian is partitioned into tractable blocks. Standard decompositions typically rely on direct commutativity among Hamiltonian terms in a chosen operator representation, which can lead to large residual errors and deep circuits for complex, practically relevant many-body quantum systems. We address this fundamental bottleneck by introducing a new decomposition principle that goes beyond commutativity, grouping Hamiltonian terms into local three-site clusters according to the underlying SU(2) symmetry of the local dynamics. We show that three-site generators fall into at most four SU(2)-symmetry classes, each admitting an effective two-qubit SU(4) representation with exact and efficient implementations. By reducing the number of clusters, this decomposition principle substantially suppresses commutator-induced errors and circuit overhead while preserving underlying physical structures that commutativity-based decompositions may violate. We demonstrate the proposed method on several physically relevant spin-lattice models, where the reduced cluster structure can even realise the second-order product formula without doubling the circuit depth, as would be required by conventional decompositions. Numerical simulations of a Kagome Heisenberg model with triangular spin-chirality interactions show that the proposed method reduces both state infidelity and average spin-chirality bias by more than three orders of magnitude compared with conventional decompositions, while using substantially fewer gates. These results establish local symmetry as a flexible and practical design principle for product-formula simulation, opening a route to more accurate and hardware-efficient simulations of broader classes of many-body systems.

From the synthesis and evolution of the elements to the celestial nuclear processes of stellar explosions and neutron star mergers, nuclear physics is the foundation of our understanding of the universe. After more than a century of progress, the field of nuclear physics remains vibrant. The rapid advancement of laser technology has opened unprecedented avenues in nuclear physics, driven by the interdisciplinary convergence of laser physics, nuclear structure, plasma science, and quantum dynamics. This emerging field enables studies on laser-induced nuclear excitation, laser assisted nuclear decay, and precision manipulation of nuclear isomers for optical clocks. This review comprehensively examines the research achievements over the past decade regarding the influence of lasers on radioactive charged particle emissions and nuclear excitation. Regarding theoretical developments, the review details various methods used to evaluate the interactions between lasers and nuclei, including the time-dependent Schrödinger equation for $α$ decay, proton radioactivity, and two-proton radioactivity and Fermi's golden rule for nuclear excitation as well as the application and advancement of various theoretical models and approximation methods. In experimental research, the review synthesizes significant breakthroughs in laser induced nuclear excitation experiments, particularly emphasizing the excitation of the $^{229}$Th, $^{83}$Kr, and $^{45}$Sc. These achievements provide essential groundwork for future breakthroughs in both fundamental nuclear science and its broader technological applications.

BEDT-TTF-based organic conductors host a number of ground states, tuned by electron repulsion from Mott and charge ordered insulators to superconductors. Knowing charge distribution on the molecular sites in the insulating state of these materials is a key to understanding the origin of these ground states. We survey and discuss the C=C stretching modes in BEDT-TTF based molecular conductors. These molecular vibrations are extremely crucial in characterization of charge-ordered insulators, and are recently linked to superconductivity in some compounds. Focusing on the known examples of BEDT-TTF$^{+0.5}$ salts, we analyse the reliability of the C=C stretching modes for the determination of charge ordering and absolute site charge. Considering the charge-ordered states, a prominent shift in frequency of 141 cm$^{-1}$ per elementary charge $e$ for $ν_{27}(b_{1u})$ and 98 cm$^{-1}$$e$ for $ν_2$($a_g$) can be clearly realised, however, the distribution resulting from different compounds span over 20 cm$^{-1}$. For nominal BEDT-TTF$^{+0.5}$ compounds, the distribution of the resonance also extends around 20 cm$^{-1}$, yielding an unexpected large uncertainty of $Δρ~\approx~(~\pm~0.045)e$, which is presumably due to the influence of small differences in the structure. This highlights the limitations of charge-frequency relations to detect small deviations in absolute charge values on molecular lattice sites, and emphasises on the use of the relations to estimate charge-ordering, rather than absolute site charge.

A fault-tolerant quantum computer is expected to require thousands of qubits. Trapped ion architectures provide a modular approach where the quantum register is divided into multiple subregisters connected by physically moving the corresponding ions. Transporting ions at scale comes with several challenges such as the need to connect thousands of control lines to an ion trap chip. Multiplexing the required control voltages from few input signals to multiple electrodes offers a solution to this wiring challenge. Here we demonstrate a quantum processing unit that combines a surface ion trap with a time multiplexer via a sample-and-hold technique that initially charges electrodes to fixed voltages and disconnects them during qubit operations. We characterize the unit's performance by measuring motional heating rates below one phonon per second in both open and closed switch configurations. We further characterize the sample and hold process and find that sampling intervals below 50 ms are sufficient to keep expected gate errors from decaying charges during the hold phase below $10^{-4}$. Our results indicate that the multiplexing scheme is compatible with high-fidelity operations.

We consider the optimization of beyond diagonal reconfigurable intelligent surface (BD-RIS)-aided multi-user (MU) cell-free (CF)-massive multiple-input multiple-output (mMIMO) systems, where the propagation environment design achieved scattering matrix optimization is complemented by developing an efficient base station (BS) beamforming (BF) scheme that effectively exploits the latter ``engineered'' channel. In particular, we describe a fractional programming (FP) method, which based on the equivalent channel incorporating a reciprocal BD-RIS (RBD-RIS) parameterized by existing scattering matrix design methods, yielding the correspondingly optimized multiple-input multiple-output (MIMO) BF weights. The proposed approach decomposes the transmit (TX) beamformer into multiple sum-rate maximization (SRM) sub-beamformers, each satisfying an independent power-constraint, such that distributed MIMO-BF scenarios can be optimally handled. Although the proposed SRM-MIMO-BF framework is independent of the specific scattering matrix design, extending the BD-RIS-aided system model to the CF-mMIMO setting requires the design of a corresponding beamforming matrix. In this context, this work investigates the impact of beamforming in reconfigurable intelligent surface (RIS)-aided systems. Simulation results demonstrate that the proposed method for designing the MIMO-BF weights, when combined with the previously developed design of reciprocal BD-RIS (RBD-RIS) scattering matrices, outperforms existing BD-RIS-aided state-of-the-art (SotA) schemes employing existing MIMO-BF techniques, indicating that the whole contribution is more than the sum of the parts.

We establish the following result, confirming a conjecture of Jean Esterle. For each closed subset $E$ of the unit circle of Lebesgue measure zero, there exists a positive sequence $u_n\to\infty$ with the following property: if $T$ is a contraction on a Hilbert space such that $σ(T)\subset E$ and $\|T^{-n}\|=O(u_n)$ as $n\to\infty$, then $T$ is a unitary operator. A key tool used in the proof is a result generalizing the well-known fact that closed subsets $E$ of the real axis of Lebesgue measure zero are removable for bounded holomorphic functions. We show that such sets remain removable even for certain unbounded holomorphic functions of moderate growth near $E$, where the notion of `moderate' depends on $E$.

A broadcast on a connected graph is a function f that assigns each vertex v an integer f(v) with 0 <= f(v) <= ecc(v) where ecc(v) denotes the eccentricity of v. A vertex u hears a broadcasting vertex v (with f(v)>0) if u is at distance at most f(v) from v. Beyond the classical broadcast domination problem, where every vertex is required to hear at least one vertex, two variants raise intriguing combinatorial and algorithmic questions. In an independent broadcast, no broadcasting vertex hears another broadcasting vertex, while a broadcast packing requires that every vertex hears at most one broadcasting vertex. The corresponding problems Broadcast Independence and Broadcast Packing ask for broadcasts of values at least k under these constraints, where the value is the sum of the broadcast values. We initiate a systematic study of the parameterized complexity of such problems. We prove that Broadcast Independence and Broadcast Packing are FPT parameterized by the treewidth plus the diameter of G, with a family of dynamic-programming algorithms over nice tree decompositions. We obtain as a corollary that both problems are FPT parameterized by k and the treewidth of G and XP for treewidth only. The latter result shows that the known algorithm for trees (Bessy and Rautenbach, DAM 2022) can indeed be extended to bounded treewidth graphs. On the negative side, we show that Broadcast Independence is W[1]-hard parameterized by the pathwidth of G. Note that this result completes the picture for parameter k and treewidth for Broadcast Independence since it is known to be W[1]-hard for k only. We complement these results by showing that a weighted version of both problems, where the input comes with a weight function on the edges, is W[1]-hard parameterized by the vertex cover of G. Finally, we provide a constant-factor approximation algorithm parameterized by treewidth for Broadcast Independence.

Coherent perfect absorbers (CPAs) have recently attracted considerable attention due to their ability to enhance light--matter interaction. By exploiting interference, CPAs enable even weakly absorbing materials to achieve complete absorption under appropriate excitation conditions. Generalizing this concept to the simultaneous absorption of arbitrary multimode input states remains challenging, however, since conventional implementations typically operate only for a single or a very small number of input channels. Here, we propose a compact realization of a multimode coherent perfect absorber based on a gradient-index (GRIN) fiber. Using the self-imaging property of the fiber, the bulky free-space architecture of previous approaches is replaced by a monolithic waveguiding platform that supports near-degenerate rephasing of many spatial modes. We show that standard GRIN profiles optimized for minimal intermodal dispersion enable highly efficient absorption of complex multimode fields, with field-of-view reflectivities well below \(1\%\) for realistic parameters. This approach provides a practical and scalable route toward efficient multimode absorption in fiber-based and integrated photonic systems, with potential applications in light harvesting, optical control, and imaging.

We study a discounted singular stochastic control problem driven by a general Lévy process, where the objective is to minimize a cost functional composed of a running cost and a control cost that depends on the current state of the process. We first establish a Hamilton Jacobi Bellman (HJB)-type verification theorem providing sufficient conditions under which a reflecting barrier strategy is optimal and characterizing the value function. Our main contribution is to connect this control problem with an associated optimal stopping problem: we prove that the optimal reflection threshold coincides with the optimal stopping boundary of the auxiliary problem. This connection allows us to characterize the optimal strategy through probabilistic tools and leads to explicit or semi-explicit solutions in several relevant cases. We illustrate the results with several examples, including an application to pollution abatement.

In 2016, Ananyan and Hochster gave the first proof of a positive answer to Stillman's Question, which asked for a bound on the projective dimension of a graded polynomial ideal purely in terms of the number and degrees of its generators. Explicit formulas for such a bound are limited and often not optimal. In this paper, we give a nearly optimal linear upper bound on the projective dimension of height $3$ ideals generated by any number of degree $2$ homogenous polynomials.

We analyze the autonomous stabilization of remote entanglement by driving two distant qubits with the output of a correlated photon source. By treating the qubits as idealized entanglement detectors, we develop a general framework to quantify the maximum amount of entanglement that can be remotely stabilized in this way with a given photon source. We then apply this approach to evaluate the suitability of a single driven two-level system as a minimal resource for autonomous entanglement distribution schemes. While our analysis confirms the presence of distributable entanglement in the Mollow sidebands of a bare two-level system, we show that stabilizing close to maximally entangled states requires additional filter cavities that enhance the relevant correlated emission events compared to other processes. We identify optimized driving and cavity parameters and explain the achievable amount of entanglement in different regimes in terms of an effective two-mode squeezing model. These insights are particularly relevant for quantum networks based on photons or phonons in solid-state systems, where isolated spins, impurity centers, or other two-level defects are readily available, while alternative sources of correlated photons are difficult to realize.

Scaling up superconducting quantum processors remains a central challenge for realizing fault-tolerant quantum computation. Although distributed architectures based on optical photons offer a promising route to scalability, they require an efficient microwave-to-optical quantum transducer that operates at cryogenic temperatures. Existing approaches typically rely on strong optical pumping, which induces undesirable heating and degrades single-photon coherence. Here, we propose a microwave-to-optical quantum transducer based on double-resonant scattering from a single color center embedded in a diamond optomechanical resonator. We show that strong coupling between the color center and the optical cavity enables coherent conversion at extremely low pump powers on the order of 10 pW. The proposed device enables remote entanglement generation on the order of 1 kHz with a fidelity exceeding 0.9, demonstrating a viable pathway toward ultra-low-power, high-efficiency quantum transducers based on individual solid-state defects for future distributed superconducting quantum networks.

We prove the coarea formula for Lipschitz maps from the subriemannian $n$th Heisenberg group $\mathbb H_n$ to $\mathbb R^{2n}$. Our result is new even when $n=1$ and provides the simplest vector-valued instance of the coarea formula in subriemannian geometry. This answers a question left open in the works of Magnani, Kozhevnikov, Magnani--Stepanov--Trevisan, and Julia--Nicolussi Golo--Vittone. The main difficulty of the proof is that a fiber of a $C^1_{\mathrm{H}}$ map $f: \mathbb H_n\to \mathbb R^{2n}$ is typically an unrectifiable curve. Its measure depends on the symplectic area of its projection to $\mathbb R^{2n}$. A bound on this area would imply the coarea formula, but examples of Kozhevnikov show that this area can be infinite or undefined. To overcome this, we introduce an integral that we use to define both the symplectic area of $\frac{1}{2}$--Hölder curves in $\mathbb R^{2n}$ and the symplectic area of projections of vertical curves in $\mathbb H_n$. Then, we give a geometric condition for this integral to converge. This yields, in addition, new results on the existence of the signed area of $\tfrac12$--Hölder planar curves that may be of independent interest. Finally, we use $β$--number estimates from the Fässler--Orponen Dorronsoro Theorem to show that this geometric condition holds for almost every fiber.

SS 433 is a microquasar whose relativistic jets precess every ~162 days, providing a laboratory for jet-interstellar medium interactions. We present a comprehensive analysis of 16 years of Fermi Large Area Telescope data (August 2008-September 2024) of the SS 433/W50 field, using events in the 0.3-300 GeV range and employing pulsar gating to mitigate contamination from the bright nearby pulsar PSR J1907+0602. We detect the GeV source 4FGL J1913.2+0512 (TS = 45, where TS denotes the likelihood-ratio Test Statistic) with a power-law spectrum (photon index 2.61 +- 0.08) and confirm a GeV excess at the western lobe (TS = 17). The eastern lobe of SS 433 is hinted at with lower significance. One additional GeV excess, Fermi J1909.6+0552 (TS = 20; TS = 28 over 0.1-300 GeV), located outside the SS 433 / W50 system, is revealed after gating. Exposure-corrected Lomb-Scargle periodograms and precessional phase-folded light curves show a ~162-day modulation in 4FGL J1913.2+0512. This periodicity is prominent during the first 10 years of the mission (2008-2018) but disappears thereafter, with the phase-folded flux concentrated in precessional phases 0.0-0.5. Over the full 16-year dataset, the modulation remains detectable but with reduced significance, consistent with dilution by the later non-modulated epoch. These results indicate that the efficiency and/or geometry of gamma-ray production in the SS 433 environment evolves on multi-year timescales.

We introduce thermodynamic networks, a general framework for autonomous, physics-based computation using non-equilibrium steady states. These networks are modeled as a collection of finite-size reservoirs that exchange conserved quantities--such as electric charge or molecular number--while relaxing to a non-equilibrium steady state, which encodes the solution of a computational problem. We identify Negative Differential Conductance (NDC) as the critical physical property governing the computational expressivity of the thermodynamic network. While networks lacking NDC are restricted to computing monotonic functions, the presence of NDC enables universal function approximation. For the training of the network, we use protocols that take advantage of the natural tendency of the system to equilibrate. We illustrate the versatility of our approach via two different platforms: quantum dot networks and enzymatic reaction networks. Both systems can be engineered to have NDC, enabling high performance in standard benchmarks, including sine function approximation and MNIST digit classification. Overall, our work establishes a rigorous link between non-equilibrium steady states and computational expressivity.