We study in detail the dynamics of unstable two-level quantum systems by adopting the Bloch-vector representation. We identify a novel class of critical scenarios in which the so-called energy-level and decay-width vectors, ${\bf E}$ and ${\bfΓ}$, are orthogonal to one another, and the parameter $r = |{\bf Γ}|/(2|{\bf E}|)$ is less than~1. Most remarkably, we find that critical unstable qubit systems exhibit atypical behaviours like coherence--decoherence oscillations when analysed in an appropriately defined co-decaying frame of the system. By making use of a Fourier series decomposition, we define anharmonicity observables that quantify the degree of non-sinusoidal oscillation of a CUQ. We apply the results of our formalism to the neutral-meson systems and derive generic upper limits on these new observables. In particular, we provide a compilation table of all well-explored meson--antimeson two-level systems in terms of Bloch-sphere parameters.

Knotted proteins embed a physical (i.e., open) knot within their native structures. For decades, significant effort has been devoted to elucidating the functional role of knots in proteins, yet no consensus has been reached. Here, using extensive Monte Carlo off-lattice simulations of a simple structure-based model, we isolate the effect of topology by comparing simulations that preserve the linear topology of the chain with simulations that allow chain crossings. This controlled framework enables us to isolate topological effects from sequence, structure and energetic contributions. We show that protein kinetic stability, defined as resistance to unfolding at a fixed temperature, is higher in knotted proteins. Additionally, kinetic stability increases significantly with knot depth, whereas foldability (or folding efficiency) is comparatively less affected. By considering a simple model of protein evolution in which amino-acid alphabet size is used as a proxy for evolutionary time, we find that increasing primary-sequence complexity through the addition of biotic amino acids predominantly enhances kinetic stability. Taken together, these results indicate that kinetic stability is a functional advantage conferred by protein knots and suggest that evolutionary pressure for kinetic stability could contribute to the persistence of knotted proteins.

The classic pivot based clustering algorithm of Ailon, Charikar and Chawla [JACM'08] is factor 3, but all concrete examples showing that it is no better than 3 are based on some very good clusters, e.g., a complete graph minus a matching. By removing all good clusters before we make each pivot step, we show that this improves the approximation ratio to $2.9991$. To aid in this, we also show how our proposed algorithm performs on synthetic datasets, where the algorithm performs remarkably well, and shows improvements over both the algorithm for locating good clusters and the classic pivot algorithm.

A search for long-lived particles in events with significant missing transverse momentum and at least one displaced vertex is presented. This analysis is performed using 137 $\text{fb}^{-1}$ of $pp$ collision data collected between 2016--2018 during Run 2 of the Large Hadron Collider by the ATLAS detector. Displaced vertices are identified using two different secondary vertexing algorithms, including a novel ``fuzzy'' vertexing algorithm optimized for identifying displaced decays of heavy quarks. Separate searches are performed using each algorithm, and the expected Standard Model background is independently estimated for each search using a data-driven procedure. No significant excess is observed over the background in either case. The results are used to set 95% confidence-level limits on potential beyond-the-Standard Model physics that could produce this final state. Results are interpreted in the context of four models: long-lived gluinos that form $R$-hadrons before decaying, neutralinos decaying via Higgs-mediated channels in the Bino-Wino coannihilation model, long-lived Higgsinos decaying to axinos, and an exotic Higgs portal model predicting displaced decays of light pseudoscalars.

We show that the observable category of q-tame multiparameter persistence modules satisfies good metric and algebraic properties: it forms a complete metric space with respect to the interleaving distance, and it is Krull--Schmidt in the sense that every object admits an essentially unique decomposition into indecomposables. Moreover, we show that these metric and algebraic structures are compatible: two objects are at distance zero if and only if they are isomorphic. We argue that the observable category of q-tame multiparameter persistence modules is the right setup for multiparameter persistence by showing that many of the categories already considered in the literature form full subcategory of this category. We also characterize precompact sets in terms of finite representation type of certain discretizations, and show that the image of several of the main constructions in multiparameter persistence is precompact.

Deploying complex, distributed scientific workflows across diverse HPC sites is often hindered by site-specific dependencies and complex build environments. This paper investigates the design and performance of portable HPC container images capable of encapsulating MPI- and CUDA-enabled software stacks without sacrificing bare-metal performance. This work is part of recent work performed within the EBRAINS Research Infrastructure, to evaluate the implementation of portable HPC (Apptainer-based) container images targeting the EBRAINS Software Distribution (ESD) -- a Spack-based software ecosystem comprising approximately 80 top-level packages (and 800 dependencies). We evaluate a hybrid, PMIx-based containerization strategy using Apptainer that seamlessly bypasses the need for site-specific builds by dynamically leveraging host-level specialized hardware, such as network interfaces and GPUs, on two production HPC clusters: Karolina and Jureca-DC. We demonstrate the feasibility of building portable, MPI- and CUDA-enabled scientific software into container images that correctly leverage site-installed drivers and hardware to reproduce bare-metal communication behavior. Using communication microbenchmarks (e.g., OSU and NCCL) alongside performance metrics of applications from neuroscience, we measure and verify their performance against bare-metal deployments. Crucially, our verification approach extends beyond top-level runtime measurements; we highlight the analysis of underlying debug logs to actively detect misbehavior and misconfigurations, such as suboptimal transport pathways. Ultimately, this investigation demonstrates the feasibility of a simple and reproducible methodology for decoupling software environments from underlying infrastructures, paving the way for automated pipelines that ensure optimized, performance-verified execution across varied HPC architectures.

One-axis twisting (OAT) interaction is a pivotal resource for manipulating quantum states of atomic ensembles, enabling spin squeezing, atomic-cat-state generation, and weak-phase amplification. Current implementations of OAT dynamics predominantly rely on the Tavis-Cummings model of light-atoms coupling; however, this approach inevitably introduces an additional Stark term that entangles the light with the atoms, which compromises the unitarity of OAT evolution and thereby degrades the OAT-based control precision. Here we propose a scheme based on a driven Tavis-Cummings model to achieve near-unitary OAT evolution. We demonstrate that both constant and time-varying driving of an atoms-cavity hybrid system can realize near-unitary OAT evolution, albeit with distinct coupling strength. Furthermore, when atomic dissipation is taken into account, we find that the time-varying-driving scheme exhibits superior resistance to decoherence. Our approach is broadly applicable to a variety of atomic platforms, including cold atoms, trapped ions, and nitrogen-vacancy centers.

As transistors continue to scale down, device reliability has become a critical concern. In order to accurately simulate defect-induced reliability degradation in MOSFET based logic, memory and power devices, we develop RASP (Reliability Ab initio Simulation Package), which implements the all-state model for reliability simulation. Unlike conventional two-state and four-state models that consider only two and four defect configurations respectively, the all-state model systematically considers all possible defect configurations in amorphous gate dielectrics and all nonradiative multiphonon (NMP) and thermal transition pathways among them. With defect parameters obtained from ab initio calculations as input, RASP enables accurate simulation of threshold voltage shifts caused by defects. Using RASP to simulate oxygen vacancies in a-SiO$_2$, we find that they are a non-negligible source of negative bias temperature instability (NBTI).

We study a kinetic multi-agent framework coupling opinion dynamics with epidemic spreading, where individual social behaviour both affects and is affected by disease transmission. Each agent is characterised by an epidemiological state and a continuous opinion variable measuring compliance with non-pharmaceutical interventions. The key mechanism of the model is an asymmetric opinion update driven by epidemic encounters: infection events induce more cautious attitudes, while failed transmissions push individuals toward more extreme opinions. We focus on a prototypical SIS setting, for which we derive a macroscopic kinetic description and, in a fast social-interaction regime, a reduced system of differential equations capturing the feedback between epidemic prevalence and opinion evolution. Convergence of the reduced model is rigorously quantified through a modified Wasserstein distance. Numerical simulations highlight how infection-induced awareness and non-infection-driven extremization jointly shape collective epidemic-opinion dynamics.

The first 100 days of Donald Trump second presidential term (January 20th - April 30th, 2025) featured policy actions with potential market repercussions, constituting a well-suited case study of a concentrated policy scenario. Here, we provide a first look at this period, rooted in the information theory, by analyzing major stock indices across the Americas, Europe as well as Asia and Oceania. Our approach jointly examines dispersion (standard deviation) and information complexity (entropy), but also employs a sliding window cumulative entropy to localize extreme events. We find a notable decoupling between the first two measures, indicating that entropy is not merely a proxy for amplitude but reflects the diversity of populated outcomes. As such, they allow us to capture both market volatility and narrative constraints, signaling large and coherent moves driven by policy changes. In turn, the cumulative entropy is found to notably increase during regional episodes with high information density, providing effective signatures of such events. We argue that the obtained results indicate short-term globally coupled, yet regionally modulated, market impacts with clear connection to introduced policies. In what follows, the presented entropic framework emerges as an efficient complement to standard methods for characterizing markets under turbulent conditions, with potential to enhance forecasting strategies such as the stochastic modeling.

We consider the global optimization of a non-convex potential $U : \mathbb{R}^d \to \mathbb{R}$ and extend the controlled simulated annealing framework introduced by Molin et al. (2026) to the class of swarm gradient dynamics, a family of Langevin-type mean-field diffusions whose noise intensity depends locally on the marginal density of the process. Building on the time-homogeneous model of Huang and Malik (2025), we first analyze its invariant probability density and show that, as the inverse temperature parameter tends to infinity, it converges weakly to a probability measure supported on the set of global minimizers of $U$. This result justifies using this family of invariant measures as an annealing curve in a controlled swarm setting. Given an arbitrary non-decreasing cooling schedule, we then prove the existence of a velocity field solving the continuity equation associated with the curve of invariant densities. Superimposing this field onto the swarm gradient dynamics yields a well-posed controlled process whose marginal law follows exactly the prescribed annealing curve. As a consequence, the controlled swarm dynamics converges toward global minimizers with, in principle, arbitrarily fast convergence rates, entirely dictated by the choice of the cooling schedule. Finally, we discuss an algorithmic implementation of the controlled dynamics and compare its performance with controlled simulated annealing, highlighting some numerical limitations.

We discuss that conventional Technicolour dynamics can be revitalized within the Dark Technicolour paradigm by invoking the Extended Most Attractive Channel hypothesis. In this framework, Standard Model fermions acquire masses via multifermion chiral condensates arising from new strong dynamics. The model incorporates three confining gauge sectors, Technicolour, Dark Technicolour, and an intermediate QCD-like sector, linked through extended gauge symmetries. The Extended Most Attractive Channel hypothesis reveals a hierarchical structure of condensates, where channels with higher net chirality become increasingly attractive. At low energies, the Dark Technicolour paradigm naturally reduces to the Froggatt-Nielsen or Standard Hierarchical Vacuum Expectation Value model, governed by residual discrete symmetries, offering a compelling resolution to the Standard Model Flavor Problem.

Gravitational waves (GW) emitted by binary systems allow us to perform precision tests of general relativity in the strong field regime. Ringdown signals allow for probing black hole mass and spin with high precision in GW astronomy. With improvements in current and next-generation GW detectors, developing likelihood-free parameter inference methods is crucial. This is especially important when facing challenges such as non-standard noise, partial data, or incomplete signal models that prevent the use of analytical likelihood functions. In this work, we propose an amortized simulation-based inference strategy to estimate ringdown parameters directly. Specifically, our method is based on amortized neural posterior estimation, which trains a neural density estimator of the posterior for all data segments within the prior range. The results show that our trained amortized network achieves statistically consistent parameter estimates with valid confidence coverage compared to established Markov-chain methods, while offering inference speeds that are orders of magnitude faster. Furthermore, we evaluate the robustness of the method against transient noise contamination. Our analysis reveals that the timing of glitch injection has a decisive impact on estimation bias, particularly during the tail of a signal with sparse information. Glitch strength is positively correlated with estimation error, but has limited effect at low signal-to-noise ratios. Mass and spin parameters are most sensitive to noise. This study not only provides an efficient and accurate inference framework for ringdown analysis but also lays a foundation for developing robust data-processing pipelines for future GW astronomy in realistic noise environments.

We show the existence of weak solutions to the fluid-structure interaction problem of a largely deforming viscoelastic bulk solid with a viscous fluid governed by the incompressible Navier-Stokes equations. In contrast to previous works, the fluid is allowed to slip along the solid boundary; namely, the so called Navier-slip boundary conditions are considered. Such boundary conditions naturally involve the time-changing outer normal of the fluid domain. Hence, their dependence on the varying geometry is one degree higher than in the previously considered no-slip case, which makes it necessary to adjust the concept of weak coupled solutions. Two classes of test functions are introduced: test functions that are continuous over the fluid-solid domain, and fluid-only test functions with nonzero tangential component at the boundary. The weak equations are established until the point of contact, and moreover, compatibility with the strong formulation is shown.

This paper studies the existence of solutions and, in particular, the well-posedness of a class of boundary control systems. Our main result provides explicit and verifiable conditions on the system data that guarantee continuous dependence of solutions on the initial data and $L^p$-inputs. The proof relies on a new boundedness estimate for the input/output maps of linear time-invariant infinite-dimensional systems with unbounded control and observation operators. The developed technique is applied to derive specific conditions for the exponential input-to-state stability of boundary-coupled heat equations with boundary disturbances and time-delays.

In this article, we discuss gradient robust discretizations for the simulation of non-linear incompressible Navier-Stokes problem and the optimal control of such flow. We consider several formulations of the flow problem that are equivalent for the continuous non-linear forward problem and compare their gradient robust discretization. We will then discuss the influence of the chosen formulation on the adjoint equations needed for gradient computation in the solution of the optimal control problem.

In Earth observation (EO) missions with Low Earth orbit (LEO) satellites, high-resolution image acquisition generates a massive data volume that poses a significant challenge for transmission under the limited satellite power budget, while LEO movement introduces dynamic systems. To enable efficient image transmission, this paper employs semantic communication (SemCom) with joint source-channel coding (JSCC), which focuses on transmitting meaningful information to reduce power consumption. Under a quality-of-service (QoS) requirement defined by image reconstruction quality, this work aims to minimize the total transmit power by jointly optimizing the JSCC encoder-decoder parameters and resource allocation. However, the implicit relationship among JSCC parameters, link quality, and image quality, coupled with the presence of mixed integer-continuous variables, makes the problem difficult to solve directly. To address this, a curve-fitting model is proposed to approximate the JSCC compression-SNR-quality relationship. Then, the joint compression ratio-resource allocation (JCRRA) algorithm is proposed to address the underlying problem. Numerical results demonstrate that the proposed method achieves substantial power savings compared to both greedy algorithms and conventional transmission paradigms.

Certifying that quantum randomness generated by untrusted devices is unpredictable to an attacker (say, Eve) is crucial for device-independent security. Bipartite protocols where only one of the parties is trusted are termed one-sided device-independent (1SDI) or steering-based protocols, where the untrusted party (say, Alice) performs measurements on her part of a bipartite entangled state to steer the subsystem of the trusted party (say, Bob) into different ensembles (collectively, an assemblage) of quantum states. Recent work has shown that an assemblage has certified randomness if and only if it is realizable by a set of measurements that are star-incompatible, i.e., the measurement setting of interest for the guessing probability of Eve is incompatible with at least one of the remaining measurement settings of Alice. However, it remains conceivable that there exist star-incompatible measurements that cannot certify steering-based randomness, just like there exist incompatible measurements that cannot certify bipartite Bell nonlocality. Here we prove that any set of star-incompatible measurements can generate steering-based randomness, thereby establishing an equivalence between the two notions. We further introduce a weight-based measure of star-incompatibility and lower bound the amount required to certify a given randomness, capturing the qualitative and quantitative interplay between the quantum resources of star-incompatibility and steering-based randomness.

We investigate the emergence of altermagnetic (AM) phases on the square-kagome lattice. Our analysis reveals that matrix element effects due to an orthogonal sublattice weight decomposition of Fermi level eigenstates known as sublattice interference enable decoupled magnetic ordering tendencies on distinct sublattices. Depending on which sublattice undergoes a magnetic instability, we identify a $d_{xy}$-type AM phase and a $d_{x^{2}-y^{2}}$-type AM phase originating from different sublattice polarization patterns. Using the Kotliar-Ruckenstein slave boson formalism we explore the stability of these AM phases as a function of interaction strength. Our findings demonstrate that sublattice-selective magnetic instabilities provide a versatile route to engineer the nature of AM order.

An anisotropic elastic material is referred to as exotic when, under specific loadings, its mechanical response exhibits a higher degree of symmetry than that prescribed by its intrinsic material symmetry. Such materials, which may be regarded as lying, conceptually and functionally, between two distinct symmetry classes, are of significant practical relevance. They enable the tailored design of metamaterials capable of reconciling otherwise incompatible mechanical requirements; for example, achieving directional isotropy of the Young's modulus in an intrinsically anisotropic medium. This work focuses on the systematic classification of exotic structures within the framework of three-dimensional linear elasticity. An exhaustive classification is carried out, leading to the enumeration of 18 exotic structures corresponding to symmetry classes higher than orthotropy. Representative examples of exotic elastic behaviours are analysed in detail.

With the deployment of large antenna arrays at high-frequency bands, future wireless communication systems are likely to operate in the radiative near-field (NF). Unlike far-field beam steering, NF beams can be focused on a spatial region with finite depth, enabling user multiplexing in both range and angle. In NF multiuser multiple-input multiple-output (MU-MIMO) systems, achievable rates are limited by interference arising from sidelobes in both the axial (range) and lateral (angle) dimensions. This work investigates how axial sidelobes (ASLs) vary with array geometry. Closed-form array gain expressions are derived to characterize ASLs for uniform planar arrays. Analytical results show that the uniform square array (USA) yields the lowest ASLs, followed by the uniform concentric circular array (UCCA), uniform linear array (ULA), and uniform circular array (UCA). Specifically, the USA achieves a peak sidelobe level (PSLL) of -17.6 dB versus -7.9 dB for the UCA. Numerical simulations confirm that the USA provides superior sidelobe suppression and highest sumrate performance.

We investigate the particle production in proton-antiproton ($p\bar{p}$) collisions using the PACIAE 4.0 model. The pseudorapidity density distributions ($dN_{\text{ch}}/dη$) and transverse momentum ($p_T$) spectra of charged particles from nonsingle diffractive (NSD) $p\bar{p}$ collisions agree well with the experimental data when using model parameters previously determined from nonsingle diffractive proton-proton ($pp$) collisions. Furthermore, we systematically compare results from both inelastic (INEL) and nonsingle diffractive $p\bar{p}$ and $pp$ collisions at the same energy to study the effect of the initial state (matter vs. antimatter) on the transverse momentum spectra of identified particles. Our results show that the net baryon-number difference in the initial state significantly enhances nucleon production at low collision energies, while its effect becomes negligible for high-multiplicity particles or at high collision energies, as expected. These findings further prove that the PACIAE 4.0 model is a versatile and reliable tool for studying high-energy collision physics.

Inspired by recent developments in the theory of stability results in the context of certain wave type phenomena, we discuss abstract damped hyperbolic type equations given in a block operator matrix form with regards to asymptotic behaviour of their solutions. Under mild conditions on the operators involved we provide criteria establishing strong or semi-uniform stability. In the particular case of Maxwell's equations, these criteria are implied under mild regularity conditions of the underlying domain causing spatial derivative operators satisfy certain compact embedding conditions and rather minimal assumptions on the damping conductivity. These assumptions improve on both regularity as well as on the structural requirements for the conductivity previously available in the literature.

We analyze propagation and detection of two-photon states expanded in Zernike modes through atmospheric turbulence using the extended Huygens-Fresnel formalism. For SPDC states prepared with a single Zernike pump mode, we analytically reduce the 8-dimensional continuous propagation integrals to an exact, discrete modal expansion. In the absence of turbulence, Zernike addition enforces conservation of azimuthal index and a strict radial-order bound. Turbulence relaxes these constraints, driving structured azimuthal and radial crosstalk dominated by low-order aberration modes. By explicitly removing the lowest-order terms from the discrete turbulence sum, we demonstrate that partial adaptive optics correcting only up to the sixth radial order is sufficient to heavily suppress this crosstalk and restore near-ideal spatial correlations.

We present a comprehensive multifrequency VLBI analysis of the FRII, high-excitation radio galaxy 3C 452, aiming to resolve and analyze for the first time its twin-jet structure on sub-parsec scales. Our data set comprises High Sensitivity Array (HSA) observations at 4.9, 8.4, 15.4, 23.6, and 43.2 GHz. Through fitting methods performed in both the visibility and the image plane, we trace the jet expansion from scales of a few thousand to nearly $10^5$ Schwarzschild radii ($R_S$) on both the approaching and receding jets. Additionally, we derive the core brightness temperatures and Doppler factors to constrain the jet's orientation and intrinsic speed. Our study provides the first detailed description of the twin-jet system in 3C 452 on VLBI scales, confirming it as a rare FRII source with jets detected down to millimeter wavelengths. We resolve both jet and counter-jet down to scales of a few thousand $R_S$, revealing a symmetric, parabolically expanding structure with power-law indices $k \approx 0.66$ (jet) and $k \approx 0.47$ (counter-jet). The brightness temperature analysis yields low Doppler factors ($δ\sim 0.03$-$0.83$), indicative of Doppler de-boosting due to the large viewing angle ($θ\approx 70^\circ$) and/or a magnetically dominated jet base. A spectral index analysis reveals a strongly inverted core spectrum ($α> 2$) with additional absorption at the highest frequencies, followed by a sharp steepening ($α\sim -2.5$) to optically thin values in the innermost jet. Finally, a comparison between broad- and narrow-line high-excitation radio galaxies shows that jets in narrow-line sources such as 3C 452 and Cygnus A complete collimation at $\leq 10^5 R_S$, whereas broad-line sources exhibit shape transitions at $10^6$-$10^7 R_S$, suggesting that orientation plays an important role in the observed collimation scales.

Multi-swarm systems, where two or more swarms of mobile agents occupy the same region of space with different parameters and goals, occur in a variety of biological, engineering, and defense applications. Composites of multiple swarms can produce hybrid spatiotemporal patterns, which compared to single swarming systems, are relatively unexplored. In this work, we develop a framework for studying the collision of counter-moving swarms, each with its own preferred, stable velocity before collision. We show that redirection of such swarms after collision occurs when a stable velocity synchronized state of the multi-swarm composite exists. Using a rigid-body approximation, we are able to extract how scatter-redirection transitions scale with swarm parameters in a variety of scenarios from reciprocal and non-reciprocal systems to symmetric and antagonistic parameter values. Our results compare well to simulations of both particle modeled agents and wheeled robots.

Considering a two-by-two block operator matrix system of Maxwell type, we present an elementary way of deducing exponential stability under minimal smoothness (and boundedness) requirements of the underlying domains when applications are concerned. The approach is based on resolvent estimates using block operator matrices.

This paper investigates quantum simulation algorithms for the Liouville equation in geometrical optics with partial transmission and reflection at sharp interfaces, based on the Schrödingerization method. By means of a warped phase transformation in one higher dimension, the Schrödingerization method converts linear partial differential equations into a system of Schrödinger-type equations with unitary evolution, thereby rendering them suitable for quantum simulation. In this work, the Schrödingerization method is combined with a Hamiltonian-preserving scheme that incorporates partial transmission and reflection into the numerical flux. A main difficulty is that the interface treatment in the classical scheme relies on threshold-dependent "if/else" procedures, making it highly nontrivial to reformulate the method in a matrix form suitable for quantum simulation. To overcome this difficulty, we encode the interface conditions into a partial transmission and reflection matrix prepared a priori, rather than during the time evolution. We present detailed constructions of the resulting quantum algorithms and show through complexity analysis that the proposed methods achieve polynomial quantum advantage in the precision parameter $ε$ over their classical counterparts.

We reassess the concept of transition at minimum work in classical stochastic finite-time thermodynamics, when the system dynamics is modelled by a diffusion process. We show that a well-posed formulation of the optimal control problem corresponding to the minimization of the mean work done on the system during a finite-time transition necessarily requires taking into account speed limits on control protocols. This fact has major qualitative consequences. First, it permits to discriminate between optimal swift engineered equilibration and transitions at minimum work. Second, it shows that in the limit when speed limits are removed, only transitions specified by generalized Schrödinger bridges admit a consistent physical interpretation. To illustrate these points, we focus on the simplest model problem: a levitating particle in a Gaussian moving trap.

We describe the dynamical, photometric, and spectroscopic data available for stars targeted by Spitzer and Herschel to search for cold circumstellar dust emission from debris disks, a collection that we name the Cold Debris Disk Surveys (CDDS). These data include Hipparcos and Gaia parallaxes, 0.4-1250 micron photometry, spectral types, effective temperatures, gravities, bolometric luminosities, visual extinctions, metallicities, lithium abundances, rotational periods, projected rotational velocities, the Ca~II HK and IR triplet activity indicators, and X-ray luminosities for 3675 stars. Within this sample, we investigate the frequency of stellar and planetary companions (including potential new proper motion companions); use the data to assign CDDS stars to the field or one of many moving groups, open clusters, or stellar associations; and investigate correlations between stellar activity indicators. In future papers, we plan to explore the magnitude and frequency of infrared excess emission as a function of host star properties; to search for new companions with Gaia; and to examine the evolution of infrared excesses with the ages of stars in clusters and the field.