Modern high-performance computing and Internet-of-Things deployments increasingly generate large volumes of signal data that must be compressed efficiently on resource-constrained acquisition devices and decompressed at scale on centralized servers. Lossy compression is widely adopted to minimize storage and transmission costs on low-power hardware sensors, yet existing methods rarely optimize for both reconstruction quality and decompression throughput simultaneously, nor do they apply methods that generalize across signal domains. In this work, we introduce FPTC, a high-throughput asymmetric signal codec that pairs a lightweight sequential encoder with a massively parallel GPU decoder designed for server-side batch decompression. FPTC applies a windowed discrete cosine transform (DCT) to exploit frequency-domain sparsity, quantizes spectral coefficients with a hybrid three-zone mapping, and entropy codes the result using Huffman coding with a novel packing scheme. The pipeline used in FPTC is designed to be throughput oriented on the GPU, maximizing performance without sacrificing reconstruction quality. We evaluate FPTC on ten datasets spanning four signal domains: biomedical diagnostic, seismic reflections, power-grid production metrics, and meteorological recordings. Our results demonstrate that FPTC outperforms existing frameworks in compression ratio while maintaining competitive throughput, achieving multiplicative compression performance of 3.6x (power), 3.1x (meteorological), 1.5x (biomedical), and 1.2x (seismic) over existing frameworks.

Isospin-breaking corrections to the HVP are among the leading sources of uncertainty in the Standard Model prediction of the muon $g-2$. In recent work by the RC$^{\star}$ collaboration, we compute the intermediate window contribution for a flavour non-singlet current using two strategies to include isospin-breaking corrections: the RM123 approach and a fully non-perturbative dynamical QCD+QED simulation. In both computations, we use $C$-periodic spatial boundary conditions to ensure that locality, gauge invariance, and translational invariance are preserved throughout the calculation. At fixed lattice spacing and volume with $N_f =1+2+1$ dynamical fermions, and fully including sea-quark effects in both computations, we find that simulating the full QCD+QED distribution yields smaller uncertainties for a fixed statistics. We summarize the comparison of the two approaches and discuss the implications for future lattice QCD+QED computations.

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are a promising therapy for regenerating myocardium after infarction, but their use is limited by graft-related arrhythmias that frequently occur shortly after transplantation. Experimental studies indicate that these arrhythmias can originate within the graft, which may act as an ectopic pacemaker, yet the mechanisms governing successful excitation of host tissue remain poorly understood. In particular, the role of electrical coupling at the graft-host interface is important, but difficult to measure directly or control. Computer modelling can help here. Here, we present a computational framework that enables systematic investigation of graft-host electrical interactions using a physiologically interpretable parameterisation. We model the graft-host interface as an internal boundary with a defined specific conductance, allowing direct control over coupling strength in units that correspond to measurable tissue properties. We formulate the governing equations and implement the computations using both finite-difference and finite-element discretisations in established cardiac modelling platforms. Using representative anatomical and physiological configurations, we demonstrate how variations in interface conductance influence the ability of spontaneous graft activity to initiate propagating excitation in host tissue. This framework provides a reproducible, mechanistically transparent tool for studying graft-related arrhythmogenesis and lays a foundation for evaluating strategies to mitigate arrhythmic risk in cardiac cell therapy.

Product-to-sum identities for trigonometric functions play a fundamental role in function theory and numerous applications. In this spirit, we present convolution-to-sum identities for Mittag-Leffler type functions. Using a Laplace domain analysis of fractional operators, we identify a family of Mittag-Leffler type functions that encapsulates the eigenfunctions of Riemann-Liouville and Caputo fractional derivatives. We work with two closely-related parameterizations of this class, $R_{α,v}$ and $P_{α,w}$. The convolution of two such functions can be expressed as a series of them. Moreover, if the functions share the same order $α$, the convolution can be reduced to a sum of two $P/R$ functions through a partial-fraction decomposition in the Laplace domain. Furthermore, $R$ and $P$ functions satisfy a generalization of Euler's identity, which expands the scope of the previous result to convolutions of $P/R$ functions whose orders $α_1,α_2$ are related by a rational factor. For $\frac{α_1}{α_2} = \frac{n}{m}$, the resulting sum has $n+m$ terms. The foundational results and methods developed here are illustrated by their application to forced subdiffusion and to a fractionally attenuated wave equation (the Caputo-Wismer-Kelvin, or the fractional Kelvin-Voigt model).

An analysis of the kinematics of open star clusters (OSCs) using their characteristics from the new Hunt and Reffert catalog was conducted. Based on 4003 OSCs younger than 200 million years, the following values for the angular velocity of the Galaxy's rotation were found: $Ω_0 = 28.99\pm0.11$ km/s/kpc, $Ω^{'}_0 = -3.909\pm0.026$ km/s/kpc$^{2}$ and $Ω^{''}_0 = 0.5662\pm0.018$ km/s/kpc$^{3}$, where $V_0=234.8\pm3.0$ km/s for $R_0=8.1\pm0.1$ kpc. It was found that periodicity in the radial velocities of OSCs is manifested in clusters younger than 600 Myr, while a wave in residual tangential velocities is observed only in the youngest ones, younger than 40 Myr. A spectral Fourier analysis of the radial velocities of three OSC samples with average ages of 18, 72, and 143 Myr was used to obtain the following values of the wavelength $λ$ and the velocity perturbation amplitude $f_R$: $λ=2.0$ kpc and $f_R=4.3$ km/s, $λ=2.2$ kpc and $f_R=8.2$ km/s, $λ=2.1$ kpc and $f_R=9.6$ km/s, respectively. A systematic change in the positions of the maxima and minima of the waves in the radial velocities of OSCs was found depending on the age of the sample. From the analysis of these shifts, the value of the absolute value of the difference $|ΔΩ|$ between the angular velocity of rotation of the spiral pattern $Ω_p$ and the rotation velocity of the Galaxy was found, $|ΔΩ|=2.0\pm0.5_{stat}\pm2.3_{syst}$ km/s/kpc. Based on this, an estimate of two possible values of the corotation radius was obtained: $8.6\pm0.2$ kpc and $7.6\pm0.2$ kpc, which indicates that the Sun is very close to the corotation.

We study a graded vector space of polynomials associated to a square matrix, defined by a finite difference condition along the rows. We show this space coincides with one defined by directional derivatives, and prove it is finite-dimensional precisely when all principal minors are nonzero. In that case, its dimension in each degree equals a binomial coefficient, giving total dimension a power of two. For Cartan matrices of irreducible root systems, we construct an explicit basis of volume polynomials of faces of the associated permutohedra, yielding an elementary criterion, which we call geometricity, for expressing a polynomial as a linear combination of these volume polynomials.

We study the stability of minimizers of weighted $p$-area functionals associated with prescribed $p$-mean curvature surfaces in the Heisenberg group. While existence and uniqueness results are well established, quantitative stability with respect to perturbations of the mean curvature $H$ remains largely unexplored in the nonzero-$H$ regime. Using a Rockafellar--Fenchel duality framework, we identify a unique underlying vector field associated with each minimizer and prove its stability under perturbations of $H$. This yields quantitative control of the direction field of the horizontal gradient. Building on this structure, we establish $L^1$ stability of admissible minimizers under natural geometric assumptions on level sets. In dimensions two and three, we also derive $W^{1,1}$ stability estimates under additional regularity and structural hypotheses, with explicit rates in terms of $\|H-\tilde H\|_{L^\infty}$. Our results provide the first quantitative stability theory for $p$-area minimizing graphs with prescribed nonzero $p$-mean curvature, even in the unweighted case. Numerical simulations are included to illustrate the robustness of the theoretical results.

Ensuring the structural integrity of building tiles is important for public safety and the durability of urban infrastructure. This study proposes a controlled experimental framework to quantify the effect of Unmanned Aerial vehicle (UAV) induced dynamic perturbations on acoustic tap-testing reliability for facade inspection. This work explicitly analyzes vibration-induced degradation and introduces an energy-based signal correction method to preserve classification performance under motion disturbances. In addition, Principal Component Analysis (PCA) is applied to process and classify wirelessly acquired acoustic data, reducing dimensionality while preserving key defect related features. A Stewart platform is used to reproduce controlled oscillatory conditions derived from UAV flight characterization, enabling systematic evaluation across multiple vibration amplitudes. Results show that classification accuracy degrades significantly under increasing perturbations, but can be restored above 98% using the proposed energy-based filtering approach.

Excited-state electronic structure in strongly correlated systems remains challenging due to the exponential scaling of the many-body Hilbert space and the difficulty of constructing systematically controlled active spaces. Building on the stochastic cluster expansion (SCE) framework previously developed for ground-state correlation energies, we extend the formalism to excitation gaps by expressing energy differences directly as a hierarchy of orbital-space cluster contributions. In this formulation, excitation energies are reconstructed from reduced-rank calculations involving a minimal frontier chemical subspace (FCS), treated exactly, together with stochastic sampling of the remaining orbital environment. This approach eliminates the need for large or chemically preselected active spaces. We demonstrate the method on charge-transfer complexes and polyacenes, where accurate singlet-triplet gaps are obtained that agree with full-system results. The method converges with low-order cluster terms and provides a systematically improvable framework for excited states in correlated systems.

In this paper, we develop and analyze a nonparametric procedure for detecting a single change point in sequences of independent observations using energy distance. The asymptotic properties of the test statistic are derived under both null and alternative hypotheses. Under the null hypothesis, for any fixed candidate split point, the standardized statistic $\mathcal{Z}_{n,k}$ converges to a standard normal limit. For global detection, we use the scan statistic $T_n=\max_{k\in K_η}|\mathcal{Z}_{n,k}|$ and calibrate critical values using a permutation test, which yields valid type I error control under exchangeability. The simulation study shows that the proposed method demonstrates much better robustness across various error distributions. To handle multiple change points in practical applications, the method is combined with a binary segmentation approach. The breast cancer cell line (MDA157) from cDNA microarray CGH data is used to illustrate the detection and estimation capabilities of the proposed method for genomic sequences.

While current federated multimodal continual learning over mixture-of-experts low-rank adaptation (MoE-LoRA) is built on the unverified assumption that routing isolates task-specific knowledge into disjoint experts, we argue that routing operates per-sample, while forgetting accumulates across the task sequence, and gradient conflict persists within each expert even when routing is maximally polarized. Moreover, activation-subspace protection can also fail because, under parameter-efficient fine-tuning, it entangles tasks due to a dimension-counting bound, and federated averaging (FedAvg) disrupts client-side orthogonality. To address this, we propose PRISM (Per-expert Routing-projection Interference-informed Subspace Method), which maintains a per-expert gradient subspace basis whose orthogonality is preserved under FedAvg and reinterprets MoE routing as a capacity allocator. Our results show that, on LLaVA-1.5-7B, LLaVA-1.5-13B, and Qwen2.5-VL-7B across CoIN-6 and CoIN-Long-10, PRISM outperforms sixteen the state of the art baselines in average accuracy. Compared to the best federated multimodal baseline, the performance margin increases from +3.23 pp on CoIN-6 to +6.06 pp on CoIN-Long-10.

Chalcogenides have recently emerged as an important class of phase-change materials (PCMs) for nanophotonics, owing to their very high refractive index (RI) and low optical loss in the visible to near-infrared range. They exhibit an ultralarge RI change (> 0.7) upon phase transition, which can be triggered by multiple stimuli such as electrical bias, laser illumination or thermal heating. These properties make them highly appealing materials for flat optics and metasurface applications. Current nanophotonic implementations of chalcogenide PCMs mostly rely on two-dimensional (2D) or quasi three-dimensional (3D) thin film patterning based on the coating of chalcogenide materials from a solid-state target. This limits fast prototyping of 3D freeform micro- and nanostructures, thus restricting geometric design freedom and device functionality. Here, we demonstrate a solution-phase direct printing of chalcogenide PCMs into functional structures. The method is based on dip in two photon-induced solidification (DITPS) of a specially synthesized antimony trisulfide (Sb2S3) precursor solution. Direct printing with DITPS is simple, maskless, fast and cost effective, enabling true freeform 3D printing of photonic devices with sub micron resolution. We show direct writing of Sb2S3 helices with different wire cross section profiles on gold and ITO substrates, as well as functional planar Fresnel zone plates (FZPs) and computer generated hologram metasurfaces (CGHMs) in a single printing step. This freeform DITPS approach thus enables rapid 3D prototyping of high index metasurfaces and opens a route to integrating high-index PCMs into existing photonic architectures and device platforms.

We show that time-reversed Young interferometry reorganizes, rather than reverses, optical entropy. A fixed detector conditions the reciprocal source--detector Green function and produces a source-label probability distribution. Marginal entropies in the standard and time-reversed geometries are generally unequal; the reciprocal invariant is instead the mutual information between source and detector coordinates. Near a destructive response, the conditioned source-label entropy can decrease while Fisher information for small phase, tilt, or defocus perturbations increases. The result identifies time-reversed Young interferometry as a source-space information processor with no analogue in ordinary detector-plane fringe readout.

Organic semiconductors (OSCs) are widely explored for flexible optoelectronic technologies, with performance governed not only by molecular design, but also by solid-state packing, which can give rise to polymorphism. Dinaphthothienothiophene (DNTT) is a benchmark OSC that has long been considered monomorphic. Here, we discover, isolate, and resolve the crystal structure of a previously unrecognised bulk polymorph of DNTT, termed blue DNTT owing to its characteristic blue emission. Coexisting with the well-known (green) DNTT in commercial powders, yet previously overlooked, blue DNTT represents the thermodynamically stable form. By combining X-ray diffraction, Raman, and THz spectroscopy with simulations, we demonstrate that polymorphism in DNTT reshapes the low-frequency phonon landscape and transfer-integral network, impacting charge transport. While green DNTT exhibits two-dimensional charge transport with holes more mobile than electrons, blue DNTT shows charge transport along all crystallographic directions enabled by a distinct herringbone packing. Electron mobility along the crystallographic a and b-axes in blue DNTT exceeds twice the hole mobility in the green phase. To our knowledge, this is the first reported acene-based semiconductor exhibiting three-dimensional charge transport. Polymorphism emerges as a key lever to tune charge transport dimensionality and carrier efficiency in organic semiconductors.

We describe the atomic-level motions in caesium hydroxide monohydrate (CsOH$\cdot$H$_2$O), which is a chemical compound containing layers of water and hydroxide ions. At this composition, each oxygen is involved in three hydrogen bonds which, in the hexagonal structure, form a quasi-2D honeycomb lattice. While oxygen and caesium atoms form a typical crystal lattice, the dynamics of the hydrogen atoms are more complex. Here we show that the covalent and hydrogen bonds are continually interconverting, meaning that the water and hydroxyl are interconverting by proton exchange. The order-disorder transition of the water and hydroxyl proceeds by chemical reaction rather than rotation or diffusion of the molecules. A hydrogen can rotate out of the layer, leaving a vacant site in the 2D layer. Such a hydrogen vacancy can diffuse rapidly by single molecule rotation, leading to fast-ionic conduction. The proton exchange leads to a novel type of Raman activity combining stretch and exchange processes, for which we develop a theoretical model. This would manifest in a broad single peak associated with both H$_2$O and OH stretches and a low frequency peak appearing at elevated temperature.

Arboreal networks are multi-rooted phylogenetic networks whose underlying graph is a tree. We give an encoding of stack-free arboreal networks in terms of triplets and the novel concept of a duet. This yields a polynomial time algorithm to construct these networks from complete triplet and duet systems. The classification results show correctness and lead to a natural metric on these multi-rooted networks.

Cognitive fatigue, which transitions from focused attention to inexact responses, can cause catastrophic failures in high-stakes environments, yet current black-box assessment techniques ignore the brain's non-Markovian and time-varying interdependent properties, limiting real-time phase transition detection. We develop a fractional dynamical networks-based machine learning (FDNML) framework using coupled fractional-order differential equations to capture brain signal interdependencies and detect cognitive fatigue transitions in real-time. Multifractal properties of brain activity exhibit distinct generalized fractal dimension signatures across fatigue levels, with Wasserstein distances of 0.10, 0.13, and 0.08 between states 0-1, 1-2, and 0-2, respectively. The framework achieves 93.33% classification accuracy and 95% AUROC, enabling the prevention of performance degradation through early detection of neural state transitions.

In this paper, we propose an approach that integrates end-to-end traceability with process modelling. OurprocessmodelsrepresentMDEworkflowsthatspan platform-independent-modelling, platform-specificmodelling, andcodegenerationphases. Processexecutionisautomated using megamodels and model transformation chains. The generation of end-to-end traceability information enables global model traceability, from high-level input models to generated code, forming the basis for traceability analysis. We have built an Eclipse-based framework, ProMoTA, to support our approach. ProMoTA extends the Acceleo model transformation language, introducing local traceability support. It also includes a global traceability map generator and end-to-end traceability analysis modules, providing users with a holistic view of the entire transformation process. Our framework is demonstrated with the use of a Wireless Sensor Network-Based IoT application.

In this work, we introduce a new hardware architecture for decoding correlated errors in quantum LDPC codes. The decoder is based on message passing and exploits the structure of the detector error model obtained through the recently introduced Graph Augmentation and Rewiring for Inference (GARI) method. The proposed architecture enables flexible scaling and can, in principle, adapt to any quantum LDPC codes using the GARI framework. It leverages resource reuse while maintaining a modest degree of parallelism, thereby reducing power consumption and area requirements, while preserving low decoding latency. As a case study, the architecture was implemented on a VCU19P FPGA as an ensemble of three decoder cores targeting the [[144,12,12]] bivariate bicycle code, achieving an average latency of 596 ns per decoding round. This implementation consumes six times fewer resources than the previous GARI-based proposal, being the first reported implementation of multiple decoder cores for correlated errors on a single FPGA device. This enables better energy-conscious scaling of the quantum error correction layer on the classical side, reducing overall power consumption while meeting real-time constraints without compromising decoding accuracy under correlated errors.

We consider a simple model of one-dimensional magnetic crystal and examine the propagation of an electromagnetic wave through such a medium. Calculating the dispersion relation ${\bf k}(ω)$ allows us to illustrate how the spread of the electromagnetic wave can be controlled by an external magnetic field. Our rigorous calculations should be useful for more realistic (and less tractable mathematically) models of magnetic media.

Coherent elastic strain is an important but often neglected contribution to phase-separation thermodynamics in alloy systems where decomposed phases have appreciable lattice mismatch. We develop a thermodynamic framework that incorporates coherent elastic compatibility directly into phase-diagram calculations alongside conventional CALPHAD chemical free energies. Applied to the BCC Nb-V system, the framework shows that coherent elasticity substantially suppresses phase separation, narrows the miscibility gap, and lowers the critical temperature toward experimentally observed values. Beyond these quantitative effects, the coherent constraint qualitatively alters the interpretation of phase equilibria: the equilibrium decomposition compositions become functions of both temperature and overall alloy composition, so the two-phase boundary no longer represents unique coexistence compositions. These results establish coherent elasticity as a key thermodynamic factor in lattice-mismatched systems and provide a general framework for coherent phase-diagram modeling.

Strongly interacting fermions underpin some of the most challenging problems in condensed matter physics, such as high-temperature superconductivity. The low-energy states of these systems encode their essential microscopic properties, yet remain largely inaccessible to classical methods. Quantum simulation offers a promising path forward, and among state-preparation strategies, engineered dissipation has emerged as a particularly compelling approach. Existing cooling protocols, however, typically rely on knowledge of the quasiparticle spectrum or mappings to free-fermion limits. In this letter, we introduce a randomized, symmetry-preserving cooling algorithm that requires no spectral information, using only local coupling operators to ancilla degrees of freedom with randomly sampled energy splittings to drive generic fermionic systems toward their low-energy manifold. We benchmark the protocol on canonical correlated fermionic models relevant to high-temperature superconductors, spanning metallic, density-wave, paired, superconducting, and phase-separated phases. Across all models, we observe universal cooling behavior: monotonic energy relaxation, concentration of spectral weight at low energies, and stabilization of correlated ground-state order. Our results establish randomized dissipative cooling as a general strategy for preparing strongly correlated fermionic states on programmable quantum devices.

We present a sorry-free Lean 4/mathlib4 formalization of Stokes' theorem for smooth singular cubes in arbitrary dimension, using true differential-form pullback via the Frechet derivative. The development also includes a bridge to mathlib4's abstract extDeriv, chain-level Stokes extended by Z-linearity, d^2=0 for singular cubical chains, box Stokes for axis-aligned cubes, dimensional specializations, and a structured comparison with Harrison's HOL Light formalization.

We discuss geometric properties of covers of closed hyperbolic manifolds of dimension $n\geq 3$, branched along a totally geodesic codimension two submanifold $Σ$. The results are mostly known to the experts but hard to find in the literature in this form.

Pseudo links generalize classical links by allowing crossings with missing over/under information, called pre-crossings. While the pseudo braid framework provides an algebraic description of pseudo links via a Markov-type theorem, the construction of polynomial invariants using Hecke algebra techniques is obstructed by the presence of the pseudo Reidemeister 1 move. In this paper, we construct a HOMFLYPT-type invariant for oriented pseudo links via the pseudo Hecke algebra of type \(A\). The construction is based on a resolution homomorphism that maps each pseudo generator to a linear combination of a braid generator and its inverse, interpreting pre-crossings as algebraic superpositions of classical crossings. Composing this map with the Ocneanu trace and applying a suitable normalization yields an invariant satisfying a natural pseudo skein relation. We further show that the invariant admits a state-sum formulation as a weighted sum of classical HOMFLYPT-type invariants over all classical resolutions of the pseudo crossings, as well as a skein-theoretic characterization in terms of its values on classical links and the pseudo skein relation.

Permissionless Proof-of-Stake (PoS) economic security is predicated on the high cost of violating consensus safety or liveness. We show that liquid staking introduces additional risks that are not captured by standard PoS economic security arguments. Through an empirical study of Ethereum data, we find that the operational performance of liquid staking pools is positively associated with subsequent normalized liquid staking token (LST) returns. Motivated by this, we present a cross-layer attack: a low-stake adversary can manipulate the consensus protocol to degrade a target pool's performance and take application-layer positions that profit if the market reprices the corresponding \gls{LST} in-line with the historically observed association. To make the consensus layer manipulation concrete, we develop a deep reinforcement learning (DRL) framework to automatically discover attack strategies. Our evaluation shows that the learned strategies can recover near-optimal theoretical attacks and uncover new manipulation behaviors that significantly degrade target pool performance. We further characterize feasible application-layer monetization channels and analyze leveraged shorting in detail using Monte Carlo simulations, showing that such attacks can be profitable with over one-half probability for LSTs of major staking pools. Our findings reveal a previously overlooked attack surface in PoS systems with liquid staking and expose a gap between consensus and economic security.

Dark matter density spikes forming around adiabatically growing black holes can dramatically enhance indirect and direct detection signals. Canonical predictions, however, assume a zero-mass seed in a purely dark matter environment and do not track the long-term dynamical impact of surrounding stars. We present a semi-analytic framework that first generalizes adiabatic spike formation to include finite seed masses, stellar cusps, and non-circular orbits, and then studies the subsequent cosmic evolution by solving coupled Fokker-Planck equations for the dark matter and stellar phase-space distributions, with a heating rate modulated by the cosmic star formation rate. Starting conservatively from canonical Gondolo-Silk spikes and marginalizing over astrophysical uncertainties, we find that stellar gravitational heating drives the inner slope towards $γ_χ\simeq 1.5$ within a few Gyrs (e.g by $z \lesssim 2$ for spikes formed at $z\simeq 10$), yielding overdensities two to four orders of magnitude below canonical expectations but still well above an NFW-like cusp. We provide redshift-dependent benchmarks for the column density and $J$-factor relevant to scattering, decay and annihilation signatures. Any robust interpretation of indirect dark matter signals from galactic nuclei must account for this evolution.

We propose a generalization of the Kuramoto model of interacting oscillators in which the particles move on the surface of a $D$-dimensional torus. In contrast with the traditional one-dimensional version, this model has a first order phase transition. We establish its mean field dynamics by means of a multidimensional Ott-Antonsen ansatz, and show that synchronization arises from a saddle-node bifurcation, while the incoherent state is always stable. Our theoretical calculations are validated by numerical simulations.

The rapid growth of human activities in outer space sounds urgent alarms around ethical and philosophical issues, particularly concerning space militarization. The present international legal framework governing activities in space, the Outer Space Treaty (OST), views the peaceful exploration of space for scientific research as co-equal to other 'uses' entitled to "due regard" with respect to "potentially harmful interference" on the part of other space actors. The OST is deeply aspirational but has weak enforcement mechanisms, relying at its core on the goodwill of all involved parties as the fundamental basis for accountability. But that framework now faces unsustainable pressures from both public and private interests, and current agreements like the OST may be unable to exert timely, material protections. Terrestrial frameworks of "ethics of deterrence" versus the "ethics of agreements" are quickly expanding into cosmic environments. We argue for the legal recognition of space as an environment as the basis of any future approach to securing its integrity, and share examples of agreements grounded in peaceful cooperative stewardship of shared environments. These represent potential pathways forward that are ethical and also serve rational self-interest and self-preservation at this crucial juncture for humanity.

We assess the performance of the Quantum Flow (QFlow) algorithm employing cost-effective solvers based on the unitary coupled-cluster ansatz with single and double excitations (QFlow-SD). The resulting energies are benchmarked against those obtained with an analogous QFlow formulation defined in the same active spaces but augmented by higher-rank excitations, including triples and quadruples (QFlow-SDTQ). Across all molecular systems considered, QFlow-SD exhibits close agreement with results from the canonical unitary coupled cluster with singles and doubles framework, while requiring substantially fewer qubits than the latter. For the water molecule in the cc-pVTZ basis, we further demonstrate the performance of a composite two-step downfolding strategy. In this approach, an initial coupled-cluster downfolding based on the double unitary coupled-cluster ansatz is followed by a QFlow treatment within the resulting target space, illustrating the effectiveness of combining classical downfolding with quantum flow optimization.