Papers

Additive friction stir deposition (AFSD) involves coupled thermal and material-flow fields governed by frictional heating, plastic deformation, and tool-imposed boundary conditions. High-fidelity finite-volume methods (FVMs) can resolve these fields but are computationally expensive, while constant-property approximations can distort the predicted thermo-mechanical response. This work develops a steady-state multi-task coupled physics-informed neural network (MCoPINN) to predict three-dimensional temperature and material-flow fields while reconstructing temperature-dependent thermal conductivity, density, and specific heat from sparse property measurements. A theoretical analysis decomposes prediction error into property reconstruction and neural field-solver contributions and characterizes the discrepancy associated with constant-property models. A controlled one-dimensional nonlinear-conduction study evaluates property reconstruction under sparse measurements. The framework is then evaluated for AFSD against a temperature-dependent FVM benchmark and experimental thermocouple measurements. MCoPINN reproduces the reference thermal and material-flow fields and reduces average temperature root-mean-square error from 50.13 K for the constant-property CoPINN to 30.28 K across four traverse speeds. MCoPINN requires approximately 8.5 hours of training per condition, compared with 52 hours for the FVM benchmark. These results demonstrate computationally efficient, physics-coupled prediction with temperature-dependent material properties.

General circulation models (GCMs) are the primary tool for simulating planetary atmospheres. They play a vital role in understanding Mars's atmosphere, as forecasting its unique weather is mission-critical for operations such as entry, descent, and landing. Mars poses unusual challenges for these models, as observations are sparse compared to Earth. In addition, a thin \co{} atmosphere alongside a radiatively active dust cycle creates a volatile atmosphere with large diurnal temperature swings and no true terrestrial analog for validation. Existing Mars GCMs, including the LMD PCM, the NASA Ames Mars GCM, and PlanetWRF, are mature and physically detailed but are implemented in legacy Fortran with finite-difference or finite-volume solvers, and they do not expose gradients for calibration or machine learning. Here we present AEGIS, a modular differentiable Mars climate model that couples Mars's unique atmospheric physics to the Dinosaur dynamical core, with interfaces for neural closures. We showcase stable ten-Mars-year simulations that reproduce the seasonal \co{} cycle while conserving the total \co{} inventory, capture realistic large-scale surface-temperature structure, and produce surface pressure that follows Mars Orbiter Laser Altimeter (MOLA) topography. Gradients through coupled trajectories agree with finite differences and support physical calibration and neural training. We compare with conventional GCMs, highlighting the framework's computational efficiency and differentiability.

Understanding quantum interactions in van der Waals magnets are critical to realizing their potential for next-generation magnetic, electronic, and spintronic applications. In this study, we investigated the evolution of exchange and dipole-dipole interactions in van der Waals magnet CrCl3 using multifrequency broadband (1-16 GHz) magnetic resonance on a bulk single-crystal CrCl3 sample. We found that the dipolar-broadened low-field resonance linewidth narrows due to exchange narrowing at higher resonance fields. Our findings show that the exchange interaction evolves exponentially as we lower the sample temperature from room temperature to 50 K. However, we found that the dipole-dipole interaction remains constant in the same temperature range. We have also detected the half-field magnetic resonance transition at room temperature, indicating a robust dipole-dipole interaction among spins. The measured inter-spin distance is 2.4(3) A at room temperature. The evolution of dipole interactions, the observation of half-field magnetic resonance, and the strong exchange interaction indicate short-range ordering/correlation in CrCl3 at temperatures far above the magnetic global ordering temperature. This study also demonstrates the significance and sensitivity of the multifrequency electron spin resonance technique for understanding quantum interactions and magnetic correlations in van der Waals magnetic materials.

Simulating open-system dynamics on gate-based quantum computers offers a route to exploring dissipative quantum phenomena through programmable quantum processing. Collision models provide a direct and flexible framework by representing the environment through sequential system–ancilla collisions. At finite temperatures, however, they typically require repeated preparation of thermal ancillas, adding circuit overhead and gate errors. Here, we show that, for a broad class of $U(1)$-symmetric system–ancilla interactions, finite-temperature dynamics can instead be reconstructed from simulations with pure ancillas in orthogonal basis states. The target temperature enters only through classical post-processing of the resulting pure-branch data, allowing the same data to be reused for different temperatures without additional quantum processing. Bypassing explicit thermal-state preparation reduces ancilla-preparation overhead and preparation-induced errors.

Neutral atom-based quantum computers have the ability to dynamically reshape the qubit register geometry between experimental runs. This capability enables different types of problems to be mapped directly onto the hardware, significantly enhancing the efficiency of solving, for instance, complex optimization and machine learning use-cases. However, this flexibility requires finding atom positions to implement target pairwise interactions, inducing a difficult nonconvex optimization for setting up the quantum machine. In this work, we introduce a new force-directed method that targets interactions to encode the input problem on the quantum computer. Numerical results show that our new method can improve embedding feasibility and solution quality by orders of magnitude, and remains reliable on the largest instances.

We investigate line defect Coulomb and Higgs indices in 3d $\mathcal{N}\ge 4$ supersymmetric gauge theories. The normalized line defect indices defined by ratios of the decorated defect indices to the ordinary indices yield well-defined integer values, the line defect Witten indices in the unit R-charge fugacity limit. We propose general formulae for these Witten indices in both Coulomb and Higgs limits for the theories without Chern-Simons terms, and we show that both count the states invariant under the residual gauge group left unbroken at a generic point of the branch, which we read off from the vacuum equations. Furthermore, we find powerful algebraic recursion relations for Wilson line defect Coulomb indices in the 3d SCFTs describing M2-branes, including ADHM-type theories and ABJ(M) theories. These relations imply that higher rank line defect indices are recursively determined by lower rank data across $U(N)$, $USp(2N)$, $SO(2N)$ and $SO(2N+1)$ ADHM-type theories and ABJ(M) theories.

A small excitation gap makes a quantum dot a sensitive probe of a weak electric field, but the charge detector that reads the probe can also excite it. We ask how much of this gap enhancement survives continuous readout, for two interacting electrons tuned through a confinement-driven crossover in a gate-defined quantum dot, using a weak-coupling, stationary two-level model. The answer depends on the energy structure of the detector, not only on its noise. A quantum point contact measures more strongly at higher bias, but once the bias energy exceeds the gap it also excites the probe. When this back-action dominates the probe's own relaxation, the optimised mean-current information rate grows only as the inverse of the gap. A sensor quantum dot with a narrow level instead reaches full measurement strength at a bias below the gap, where, for a non-interacting detector and to second order in the coupling, it cannot excite the probe at zero temperature. This energy-filtered readout keeps the inverse-square gap dependence of the quantum Fisher information, down to a gap set by the detector's level width and the electron temperature. Through such a detector the interacting pair gives about three times the information rate of a single electron with the same gap and detector, compared with 1.6-1.7 in the quantum Fisher information, for both contact and Coulomb-type interactions. These different gap dependences, and the different optimal biases of the two detectors, can be tested by bias and gate sweeps on suitably tuned charge-sensed double dots.

Standard radiation spectra modeling of active galactic nuclei like Seyfert galaxies typically involves tuning the relative contributions from an optically thick disc, optically thin corona, dust torus, and outflow by hand to match observations. The physics that quantifies this relative partitioning is not precisely understood. Here we make progress toward improving this understanding by testing the implications of a conceptual paradigm that the corona is supplied from below only by magnetic fields whose scales are large enough to escape turbulent shredding on their buoyant rise time. We use a generalized mean field accretion disc theory that includes both local radial angular momentum transport and angular momentum transport into a corona. We then use previous numerical simulations of magnetized turbulent accretion disc energy spectra to connect the fraction of disc magnetic energy that would escape to the fraction of coronal to total luminosity. Without explicitly calculating detailed particle acceleration and radiative processes, we assume that the disc radiation spectrum is thermal and the coronal radiation spectrum is a power law. We then show that the aforementioned paradigm for corona formation constrains the allowed x-ray power law index to a narrow range which agrees with observations. For the three AGNs studied here the predicted mean photon index is $\overline{\Gamma}=1.76$, consistent with the mean observed value of $\overline{\Gamma}_{\rm obs}=1.73$, bolstering confidence in the paradigm.

We present ab initio calculations of atomic ionization by bare ions and antiprotons within the continuum distorted-wave eikonal initial-state (CDW-EIS) model. The dataset covers atomic targets from H to Kr, impacted by bare ions over a broad range of projectile charges and by antiprotons. Particular attention is given to elements in periods 3 and 4 of the periodic table, which are relevant to pigment analysis and technologically important materials. The resulting subshell-resolved total ionization cross sections are made openly available through an online repository covering a broad range of projectile–target systems, occupied initial subshells, and projectile velocities. We analyze systematic trends in the cross sections, including their dependence on projectile charge and velocity, binding-energy scaling, and charge-sign effects in proton and antiproton impact. To extend the practical coverage of the database, we also develop a neural-network surrogate, CDWEIS-NN, trained on the subset of the database with projectile charge $|Z_\mathrm{P}|\leq 8$. The network interpolates the CDW-EIS results to additional projectile–target systems and impact energies, reproducing both held-out CDW-EIS calculations and the experimental benchmarks considered in this work with satisfactory accuracy.

In this paper we use machine learning methods to predict radiation damage in the lead tungstate crystals of the CMS electromagnetic calorimeter at the Large Hadron Collider. We analyze LHC Open Data collected from 2016 to 2018 and study the time evolution of the crystal optical transparency. We apply deep neural network models to predict its behavior over different future time intervals, and find that encoder-decoder sequence-to-sequence architectures can effectively describe crystal aging.

Measuring the age and composition of interstellar objects is necessary to understand their origins. However, existing methods for measuring the age are either imprecise or require an unusually bright target, while the composition is confounded by the effects of Galactic cosmic rays, which drive chemical reactions in the cometary matrix. As the Vera C. Rubin Observatory expands the census of interstellar objects, measuring these properties will be critical to understanding the overall population. In this work, I derive a new methodology for simultaneously estimating the age and initial composition of an interstellar object from time-series observations of the coma. Measurements of both the composition and its gradient versus depth into the nucleus are shown to fully constrain both properties in most circumstances. A simple model using only CO and CO$_2$ is discussed and used to demonstrate the properties of this inference process. When applied to 3I/ATLAS, this simple model indicates that this object is at least 0.6 Gyr old and has an initial CO/CO$_2$ ratio of 1.5, supporting a formation outside the CO ice line. Further refinement of the chemical network and improved observational strategies will improve the precision and accuracy of these measurements, enabling a deeper understanding of the interstellar object population and extrasolar planet formation.

We test the hypothesis that Newton's gravitational constant underwent a rapid transition approximately $73$-$130\,{\rm Myr}$ ago, as proposed in some resolutions of the Hubble tension. Fully convective red dwarf stars with masses below $\sim0.35\,M_\odot$ have thermal timescales comparable to the proposed transition look-back times, so an appreciable present-day memory can remain. We show that a rapid step in $G$ induces measurable changes in their radii and confront these predictions with mass-radius measurements of eight red dwarfs in detached eclipsing binaries. We find that the $G$-step models proposed to resolve the Hubble tension, corresponding to a $4\%$ change in $G$ at a look-back time of $73\,{\rm Myr}$ and an $11\%$ change at $130\,{\rm Myr}$, are excluded at significances of $3.1\sigma$ and $4.0\sigma$, respectively.

We develop a quantum input-output theory for open photonic systems based on macroscopic quantum electrodynamics using the first-order electromagnetic Green's function. Quantum fields enter and leave the photonic system through waveguide ports, while the electromagnetic Green's function propagates the fields through the arbitrary interior of the photonic system, which may be dispersive and absorbing. The resulting relation contains a port-to-port scattering matrix and a Langevin-noise contribution from material absorption that together preserve the bosonic output commutation relations. For embedded emitters, the low-saturation and single-excitation scattering response is determined by Green's functions connecting the ports and emitters while retaining the non-Markovianity of the photonic environment. Using finite-difference time-domain simulation, we calculate the emitter-modified transmission for a nanophotonic cavity and inverse-designed coupler, providing a direct route from computed electromagnetic response to a quantum input-output model.

The article contains exact results for the behavior of the Casimir force of Ising chain of $N$ atoms containing an impurity atom. The force is considered as a function of $N$ and on both the temperature $T$ and the external magnetic field $h$. The interactions between nearest neighbors within the chain are supposed to be of a ferromagnetic short-ranged type $J>0$. The impurity atom interacts with constants $J_{ia}$ with its nearest neighbors, where $J_{ia}$ can be both of ferromagnetic type, i.e., $J_{ia}>0$, as well as of antiferromagnetic type, i.e., $J_{ia}<0$. It turns out that the Casimir force can be both attractive or repulsive, depending on the sign and the magnitude of the ratio $J_{ia}/J$.

The stress in a flowing complex fluid such as a solution of polymers, surfactants and/or colloidal particles is a fundamental dynamic property of the material. It reflects the evolution of the fluid microstructure under deformation and determines the motion of the fluid. While spatially resolved measurements of flow (via velocimetry) and microstructure (e.g.~via scattering) can be made, neither of these individually can uniquely determine the stress. In particular, due to the degenerate nature of the relationship between the stress tensor and the net force exerted by the microstructure on the fluid, the stress tensor is hidden from direct observation. We show that integrating velocity and microstructure measurements with principles of continuum mechanics can break this degeneracy, unveiling the stress tensor. The approach has two stages. In the first, velocity information is used along with the momentum and mass conservation equations to infer the force density exerted by the microstructure on the fluid using a data assimilation framework. In the second, the equation relating force density to stress is solved. This equation has a nontrivial nullspace, introducing a homogeneous solution whose structure must be found to uniquely determine the stress. We do so by using microstructural data and a general model between microstructure and stress, the parameters of which are determined, along with the nullspace solution, by solving a least-squares problem. The approach is illustrated using synthetic velocity and microstructural data from simulation of a flowing polymer solution, demonstrating its validity and robustness.

Extreme values of a physical system are rare by definition, yet they can govern some of its most consequential and anomalous behavior. Their sparsity makes them particularly costly to identify in large data sets. Quantum computation offers a potential way to reduce this cost. The challenge is that quantum amplitudes cannot simply be read, copied, compared, or marked using conventional search oracles. Here we introduce an algorithm for searching amplitude-encoded quantum signals that exploits their underlying structure. Through a nonlinear amplitude transformation, the algorithm identifies and certifies a global extremum while exponentially reducing the effective search space for structured signals. We establish a polylogarithmic query complexity in the data size $N$, together with global completeness, efficient classical verification, and a measurable criterion for quantifying exploitable structure. We demonstrate the framework using computational turbulence data. Applied to line cuts of velocity gradients from a $1024^3$ simulation containing more than one billion grid points, the algorithm consistently isolates the extreme tail and reduces the median search space to $O(\log N)$. The clustered structure characteristic of turbulence further accelerates the search. These results establish a direct connection between physical structure and quantum advantage in extreme-value search. For accessibility, the main text emphasizes the central ideas and results, while the theoretical derivations are provided in the Appendices.

We introduce and study multi-indexed Schatten spaces which lift the commutative $\ell_{q_1}\![\ell_{q_2}\![\ell_{q_3}\![\dots]]]$ -spaces to the quantum toolbox. They extend Pisier's operator-valued Schatten norms and the recently introduced two-indexed Schatten quasi-norms. For every ordered tuple $\mathcal{Q}=(q_1,\dots,q_n)$ of non-zero indices we define a quasi-norm (for positive indices) or an anti-norm (for negative indices) on operators on an $n$-fold tensor product of Hilbert spaces. We do this for indices of the same sign satisfying the mutual compatibility condition $|\frac{1}{q_i}-\frac{1}{q_j}|\leq1$. Beyond establishing desirable properties of these quasi- and anti-norms via factorization formulas that combine operator space and matrix-analytic techniques, we lift several central tools and results of the seminal [Devetak, Junge, King, Ruskai, CMP 2006] to the multi-indexed and quasi-normed setting. These include a general non-commutative Minkowski inequality relating swapped systems and two identity-removal equalities. As a consequence, complete hypercontractivity and complete reverse hypercontractivity tensorize for all compatible indices, including negative ones. Concerning quantum information theory we prove that the completely bounded minimal and the maximal output conditional entropies are additive under tensor products of quantum channels for all $\alpha\geq\frac12$. This extends the case $\alpha>1$ of [Fawzi, Kochanowski, Rouzé, Van Himbeeck, CMP 2026] and the unconditional results of [Devetak, Junge, King, Ruskai, CMP 2006]. Beyond tensor products, we establish chain rules for $\tilde H^\uparrow_\alpha$, $\alpha\in[\frac12,1)$, for compositions of possibly signaling channels, extending upon the smooth max-entropy chain rule used in device-independent entanglement certification to the whole interval $\alpha\in[1/2,1)$.

We present an analysis of active interrogation in space with the goal to verify the absence of nuclear weapons hidden in a large constellation of satellites. We propose a 16 MeV photon beam generated by advanced laser wakefield accelerators and the detection of fission neutrons using segmented organic scintillators. We use Starlink as a real-world example for the constellation and solve the inspector routing problem against this set of 7,852 satellites over a 5-year mission period. We perform detailed simulation of the nuclear and orbit physics: signal generation and detection with GEANT4 against an orbit-resolved neutron and gamma background, routes flown with Orekit including the effects from the Earth's oblateness, and detection decided by a likelihood ratio test. We identify different encounter types and fleet designs based on a range of inspector platforms. The radiation dose to target satellites from the beam can be kept to about 1% or less of the 5-year space environment dose. We find that a small number of inspection platforms, 20-70 depending on the accelerator assumptions, can serve inspections to the full constellation with a detection probability of 90% against a single deployed warhead. A 10% random sample of the whole fleet can be inspected by 2-20 platforms providing a 37% detection probability against 5 deployed warheads.

Neutron stars (NSs) receive natal kicks during supernovae that affect their survival in binaries and motion through the Galaxy. The global distribution of these kick velocities across the NS population remains uncertain. Here, we combine the orbital properties and birth rates of Gaia NS and Be+NS binaries with velocity constraints from young isolated pulsars to construct a concordance model of NS natal kicks. We find that all three populations can be jointly described by a shared bimodal kick distribution. The low-velocity component follows a lognormal distribution with $\mu_{\ln v}=1.87^{+0.65}_{-0.53}$ and $\sigma_{\ln v}=0.55^{+0.85}_{-0.44}$, corresponding to a median speed of $6.5^{+5.9}_{-2.7}~{\rm km~s^{-1}}$. The high-velocity component is consistent with the distribution inferred from young pulsars, which peaks near $200~{\rm km~s^{-1}}$. The low-velocity component contributes only $\sim10\%$ of all NS births, but produces most Gaia NS binaries and roughly half of Be+NS binaries. The same model predicts systemic recoil velocities consistent with the observed kinematics of Gaia NSs, Be+NS binaries, and NS low-mass X-ray binaries. For Gaia NSs, whose formation history remains unknown, we use this kick distribution to constrain their progenitors. We favor pre-supernova binaries containing intermediate-mass stripped stars with $\sim1~{\rm M_\odot}$ companions in au-scale orbits, and predict $\sim300$ such binaries in the Milky Way today, $\sim40$ in the LMC, and $\sim30$ in the SMC. Finally, we consider the implications of these kicks for NSs in hierarchical triples. We find that 2-10$\%$ of Gaia NS triples and 3-23$\%$ of Be+NS triples retain their tertiary after the supernova. Overall, our results suggest that a shared natal kick law can account for isolated pulsars and surviving NS binaries, where most NSs receive large kicks and low kicks are common among surviving binaries.

In this work we provide the complete classification of all non-zero finite-dimensional complex Lie subalgebras of the universal enveloping algebra of the special linear Lie algebra $\mathfrak{sl}(2,\mathbb{C})$. That is, we show that every such nilpotent Lie subalgebra is abelian and every non-solvable Lie subalgebra is reductive, with semisimple component isomorphic to $\mathfrak{sl}(2,\mathbb{C})$ itself. Every non-nilpotent solvable Lie subalgebra is the direct sum of an abelian center and a member of the family of solvable Lie algebras $\mathfrak{r}(\boldsymbol{d},\boldsymbol{m})$, parameterized by a vector $\boldsymbol{d}$ whose entries are strictly increasing positive integers that have greatest common divisor one together with a positive integer vector $\boldsymbol{m}$ of the same length recording their multiplicities. Moreover, we discuss the corresponding classification in a real skew-hermitian setting and its relation to the realizations in the single- and two-mode Weyl algebras.

The millisecond pulsar PSR J0435+3233, discovered by FAST, exhibits an unusually large apparent spin-down rate, potentially reflecting line-of-sight acceleration from a distant companion. Recent investigations reveal a hierarchical triple consisting of an inner pulsar-helium white dwarf binary with an orbital period of ~8 days, orbited by a G-type subgiant tertiary on an eccentric ~74 yr orbit. The current timing description admits two distinct geometrical solutions. We develop a singly averaged (SA) formulation that averages over the inner orbit while retaining the instantaneous phase of the eccentric outer orbit, thereby capturing the time-dependent quadrupolar perturbations induced by the tertiary. We show how this physical three-body description can be incorporated naturally into pulsar-timing analyses and use it to forward-propagate the two currently viable configurations, Tv1 and Tv2, to forecast when their timing signatures become distinguishable with FAST. The SA evolution predicts that the two configurations will become distinguishable in the coming years, with the effective projected semi-major axis, $x_{1,\mathrm{eff}}$, providing the earliest discriminating observable. We further extend the framework to predict the tertiary's spectroscopic radial-velocity and astrometric evolution, linking FAST timing with LAMOST time-domain spectroscopy and Gaia astrometry. This multi-band framework has the potential to establish PSR J0435+3233 as an exceptionally well-constrained laboratory for three-body dynamics, compact-binary and stellar evolution, and gravitational physics.

We present ToF-PAX-RIXS, a compact instrument that combines time-of-flight momentum-microscopy angle-resolved photoemission spectroscopy (ARPES) with resonant inelastic X-ray scattering (RIXS). The latter is based on photoelectron spectrometry for analysis of X-rays (PAX). The two techniques are implemented with a single multimode electron-optical column, allowing measurements to be performed sequentially on the same sample under identical experimental conditions. In ARPES mode, the instrument records the photoemission intensity as a function of kinetic energy and two in-plane momentum components. In PAX-RIXS mode, scattered soft X-ray photons are absorbed in a thin metallic converter, and the generated photoelectrons are analyzed in energy and position of emission on the converter. The electron kinetic energy retains the spectral information of the scattered photons, while the position is related to the scattering angle and therefore to the momentum transfer, enabling simultaneous access to a finite momentum-transfer interval. We describe the mechanical design, converter assembly, scattering geometry, and multimode electron optics of the instrument. Its PAX-RIXS performance is benchmarked at the Cu $L_3$ edge using CaCuO$_2$, with Au, Ag, and Pt converters. The measured spectra reproduce the principal features obtained with a conventional grating RIXS spectrometer, and deconvolution yields an effective reconstructed energy resolution better than $120$~meV under the present conditions. Finally, combined ARPES and PAX-RIXS measurements on the same Ca-doped YBa$_2$Cu$_3$O$_{6.45}$ sample demonstrate the capability of the instrument to correlate electronic structure and collective excitations within a common compact platform.

Algorithms which prepare states via the variational principle assume that closeness in energy implies closeness in state; we formalise how this assumption can fail by showing that a ground-state energy estimate converged to within $\epsilon$ of the true value is compatible with observable expectation values in error by up to $\sqrt{2\epsilon\chi_O}$ at leading order, where $\chi_O$ is the static susceptibility of the observable. As a result, the observable error can be orders of magnitude larger than the energy error, a mechanism we call non-linear error amplification, and because a variational algorithm cannot guarantee the correctness of these properties from energy alone, energy does not necessarily certify an observable. In light of our findings, we examine three algorithms: the variational quantum eigensolver on the transverse-field Ising chain, the density-matrix renormalisation group on a pair of weakly coupled hydrogen chains, and Krylov quantum diagonalisation on lithium fluoride. In each case we demonstrate that a well-converged energy can leave observables uncertified.

Satellite populations provide sensitive tests of the galaxy-halo connection, but studies have largely focused on Milky Way (MW)-mass host galaxies or a small number of nearby dwarf galaxy hosts. Here we present a statistical census of bright, star-forming satellite galaxies around sub-MW-mass hosts using the first data release of the Merian Survey. Our sample consists of 357 hosts with stellar mass $10^{9.5}<M_{\star,\text{host}}<10^{10.5} \ \text{M}_\odot$ at redshifts $0.07<z<0.09$, all selected to be central galaxies. Merian's medium-band imaging isolates H$\alpha$ and [O iii] emission lines for galaxies in this redshift range, enabling efficient selection of star-forming satellites down to $M_{\star,\text{sat}}\gtrsim 10^{7.5} \,\text{M}_\odot$. We identify 471 satellite candidates within the projected virial radii of these hosts. After statistically subtracting the contribution from foreground and background galaxies, we find $148\pm 7$ satellite candidates associated with the host sample. We find that $\mathord{\sim} 60\%$ of hosts have $N_{\rm sat}< 1$ massive satellites within their virial radii, $\mathord{\sim} 22\%$ have $1\leq N_{\rm sat}< 2$, $\mathord{\sim} 10\%$ have $2\leq N_{\rm sat}< 3$, and $\mathord{\sim} 8\%$ have $N_{\rm sat} > 3$. Satellite abundance increases with host stellar mass across the sub-MW regime, extending the observed trend from dwarf to MW-mass galaxies and broadly agreeing with predictions from the TNG50 simulation. The radial distribution of satellites around sub-MW-mass hosts is similar to that around MW-mass hosts and broadly consistent with TNG50. Together, these results extend our empirical view of satellite populations across the previously sparsely sampled transition between dwarf and MW-mass hosts.

Despite its remarkable empirical success and predictive power, quantum theory is riddled with mysteries. One such conceptual puzzle is the measurement problem: why do quantum systems in superposition collapse to a single-valued outcome upon being measured? The scenario of Wigner's friend illustrates this tension, with recent extensions deriving strong no-go results for the nature of reality. Another fundamental puzzle arises at the interface of quantum theory and general relativity—the black hole information paradox. This thesis further explores these two foundational paradoxes. Part I of this thesis focuses on extensions of the Wigner's friend scenario. We introduce several novel extended Wigner's friend arguments, and establish connections with notions of nonclassicality, i.e. the study of quantum phenomena that evade classical explanation. Key results are a refined version of the Frauchiger–Renner paradox, new extended Wigner's friend scenarios based on contextuality, and an argument against the absoluteness of free choices based on the Pusey–Barrett–Rudolph theorem. The latter result complements the Local Friendliness no-go theorem, which challenged the absoluteness of experimentally obtained measurement outcomes. In Part II of this thesis, we turn to black hole puzzles and the interplay of quantum theory and gravity. We present a paradox that unifies extended Wigner's friend arguments with black hole puzzles, strengthening the cloning and firewall paradoxes. After discussing subtleties in these paradoxes, we next present an analysis combining elements of quantum theory with gravity, analyzing the detector response near a superposed black hole using elements of quantum reference frames.

We examine the dc driven transport of particles with Yukawa interactions through an assembly of chiral active particles undergoing circular motion. The driven particles exhibit a jammed phase, a nonlinear disordered or plastic regime where there is a finite Hall effect produced by interactions with the active chiral particles, and a high drive linear regime where the driven and nondriven particles phase separate and the Hall effect nearly disappears. The chiral particles experience strong drag and Hall effects from the driven particles, and these effects vary monotonically with changing thermal fluctuations or chiral motion parameters. The different dynamical phases are correlated with features in the longitudinal and transverse transport curves, and we map out the phases as a function of active orbit size, thermal fluctuations, and particle density.

To discover and characterize debris disks, one must obtain high-quality photometry in order to accurately fit photosphere models for the host stars. Since the $K$ band always falls on the Rayleigh-Jeans side of a star's spectral energy distribution (SED), its reliability is particularly important for uncovering mid-infrared excess emission from dust. While Two Micron All Sky Survey (2MASS) photometry is the near-infrared benchmark for most stars that host debris disks discovered by Spitzer and the Wide Field Infrared Survey Explorer (WISE), the brightest stars ($K_s < 5$) saturated the 2MASS detectors. To accurately model debris disks that orbit the nearest, brightest stars, we construct new photosphere models by replacing saturated 2MASS data with $JHK$ photometry from the NASA Catalog of Infrared Observations, archival $R_C I_C$ photometry, and saturation-corrected WISE W1 photometry. We estimate the dust temperature and minimum distance from the star by fitting blackbody and modified blackbody models to infrared photometry from WISE, Spitzer, and Herschel. Our models allow us to identify disks that subtend large angles on the sky; these disks are candidates for follow-up with ground-based angular differential imaging, the Space Telescope Imaging Spectrograph (STIS) on the Hubble Space Telescope (HST), and NIRCam on JWST. Finally, we find that the disk surrounding $\gamma$~Tri likely has warm dust that could be resolvable with JWST's MIRI instrument at $23$ or $25.5 \micron$. Multiwavelength observations provide benchmarks for collisional cascade models and may reveal planet–disk interactions.

Amorphous materials are statistical ensembles rather than definitive structures, and conventional density-functional (DFT) and machine-learned-potential simulations sample only a small part of that ensemble. We present an $SE(3)$-equivariant denoising-diffusion model that learns the configurational distribution of amorphous oxides, so the model itself is the structure database. The learning is data efficient. A model trained on $1{,}781$ DFT configurations suffices to reproduce partial radial distribution functions, coordination statistics and bond-angle distributions, and to generate models of over $3\times10^{5}$ atoms at a cost comparable to that of the cheapest classical pair potentials. The trained model can propose amorphous atomic structures for first-principles relaxation to explore the configuration space. For example, it locates an amorphous Zr-Ta-O structure $36$ meV/atom below the previously known minimum. Generation can also extend beyond trained conditions to non-stoichiometric compositions, other mass densities, interfaces, and doping. First-principles verification confirms that generation can be steered to a requested energy, and shows that the denoising training loss does not rank generative quality, because the two measure different things.

Ising machines have emerged as promising hardware accelerators for intractable optimization and sampling problems, yet their practical impact increasingly hinges on the co-design of algorithms and hardware, where algorithmic demands shape new architectures and new hardware capabilities inspire entirely new algorithms. In this Review, we survey probabilistic algorithms designed for portability across diverse Ising platforms, advocating a top-down perspective that prioritizes principled methods with provable guarantees. We cover foundational methods such as simulated annealing and parallel tempering, including two-dimensional extensions that natively encode hard constraints, and examine approaches that expand the scale of solvable problems from cluster mean-field methods to variational samplers. We highlight the Probabilistic Approximate Optimization Algorithm (PAOA), a classical analog of QAOA that emerged directly from probabilistic hardware development, and explore how generative AI and Ising machines might reinforce each other: learned models propose global moves to accelerate optimization, while probabilistic techniques improve inference in large language models. Much as quantum computing has seen algorithms co-evolve with hardware, probabilistic and Ising computing stand at a similar inflection point. We outline a co-design framework for accelerating the capabilities and adoption of next-generation Ising machines.

Coherent microwave-to-optical transduction is essential for hybrid quantum networks. Typical transducers, however, have bandwidths set by fixed device parameters and face efficiency-bandwidth tradeoffs. We propose a cavity-based microwave-to-optical transducer mediated by a collective Rydberg excitation, where external driving fields tune the conversion bandwidth in situ from narrowband, spectrally selective operation to broadband operation without modifying cavity parameters. Under impedance-matching conditions, the system operates as a continuous-wave phase-preserving linear transducer, maintaining both near-unit efficiency and quantum-limited added noise throughout the tunable bandwidth range.