Papers

We examined the ratios of neutron and proton transition matrix elements, $M_n/M_p$, for the $0_{gs}^+ \rightarrow 2_1^+$ transitions in 48 even-even stable nuclei with $N>20$ for which electromagnetic matrix elements were compiled by Pritychenko et al. and for which high-quality inelastic proton scattering data were available. Several deformed rare earth nuclei have $(M_n/M_p)/(N/Z)$ values significantly below 1.0, which is not consistent with a simple liquid drop picture. However, this phenomenon can be explained using a schematic picture in which $M_p$ reaches a maximum at proton mid-shell ($Z=66$) and $M_n$ reaches its maximum at neutron mid-shell ($N=104$). Several mid-mass vibrational nuclei have $M_n/M_p$ values significantly below $N/Z$, which is not consistent with the expectation that $M_n/M_p = N/Z$ in such nuclei. A shell model investigation of these observations might yield insights about this behavior.

The microscopic origin of anomalous orbital polarization in a class of low-dimensional correlated oxides remains unresolved due to the competition among crystal-field effects, electronic correlations, and orbital-dependent dimensionality. Using dynamical mean-field theory, we investigate a two orbital Hubbard model with orbital-dependent dimensionality and reveal the mechanism for anomalous orbital polarization through orbital reconstruction beyond the bare crystal-field picture. We identify interorbital Coulomb interaction-induced charge competition as a key microscopic mechanism responsible for the orbital redistribution, which leads first to an orbital-polarized correlated metal and subsequently to an orbital-polarized Mott insulator. We further find that Hund's coupling acts as a filling-dependent regulator of orbital reconstruction. It weakens the correlation-induced orbital redistribution at quarter filling by competing with interorbital charge fluctuations, while at half filling it completely suppresses the orbital-polarized state by stabilizing high-spin orbital-balanced configurations. These results provide a unified picture of correlation driven orbital reconstruction and highlight the relevance of interorbital interactions and Hund's coupling for understanding orbital phenomena in low-dimensional transition-metal oxides.

Perfect deterministic distinguishing of nonorthogonal quantum states is forbidden by the linear and unitary structure of quantum mechanics. It has often been assumed that, if such distinguishing were available, it would be the resource enabling work extraction from a single heat bath. We show that this expectation identifies the wrong thermodynamic operation and prove such hypothetical operation increases, rather than decreases, the joint entropy of system and detector. The entropy-decreasing resource is instead the inverse operation, which we call nonorthogonal-state erasure. Reanalyzing a Peres-type Szilard engine, we show that the apparent extracted work $W_{\mathrm{ext}}=0.2766k_{\mathrm{B}}T$ for an equal mixture of an atomic ensemble with spin state $\left|\uparrow\right\rangle $ and $\left|\rightarrow\right\rangle $. Thus the apparent second-law violation is supplied not by nonorthogonal-state distinguishing, but by a nonorthogonal quantum state erasure.

MIRI, the Mid-Infrared Instrument on the James Webb Space Telescope, is the only instrument sensitive to wavelengths longward of 5 um on the observatory. In this regime, MIRI brings order-of-magnitude improvements over past instruments and missions in a wavelength range that is challenging or impossible to access from the ground. As such, MIRI occupies a unique parameter space, offering unparalleled capabilities in all areas of astrophysics, from the Solar System to the most distant galaxies in the Universe. We continue to make operational improvements to MIRI, four years into its operational lifetime, to create new observing opportunities, improve performance, and enhance its scientific return. In this paper we will describe several such improvements, and their anticipated impact on MIRI and JWST science.

We develop quantum algorithms for estimating properties of general matrix functions of Hermitian matrices, with applications to phase estimation, Green's function evaluation, and estimating measurement distributions of time-evolved states. The resulting methods exhibit commutator scaling in matrix parameters similar to that usually found for product formulae, lower circuit depth in other parameters, and require only a single ancillary qubit. Our central primitive consists of classically postprocessing randomly chosen product formulae circuits, which mathematically corresponds to an approximation of a Richardson extrapolation. Within our framework, we introduce a protocol for approximating the measurement distributions of quantum states, extending beyond standard observable estimation. We also provide tightened gate complexity bounds for practically relevant systems, including those with k-local interactions, long-tailed matrix ensembles, and conserved quantities. Finally, numerical experiments confirm that our method can achieve significantly shallower circuit depths than standard product formulae in certain parameter regimes, and highlight the potential of their heuristic application.

The capacity region of the $K$-sender discrete memoryless multiple access channel (MAC) is fully characterized when non-signaling (NS) assistance is available to all $K$ transmitters and the receiver. It is shown to have the same form as the classical capacity region of the MAC, except that the input distribution is allowed to be arbitrarily dependent across the senders. In particular, the NS-assisted capacity region matches the natural generalization to $K$ senders of an outer bound that was previously established by Fawzi and Fermé for $K=2$ senders. Additionally, we provide examples of $K$-sender MACs where the multiplicative gain in capacity from NS-assistance is arbitrarily close to $K$. Combined with an upper bound from prior work, this establishes $K$ as the extremal value of the multiplicative gain from NS-assistance across all $K$-sender MAC settings.

We apply persistent homology to a six-layer temporal network model of the Inca Empire (Tawantinsuyu), built from the Qhapaq Ñan road system ($6{,}546$ segments; $12{,}031$~km): 4,492 nodes (4,452 active; 40 isolated removed), $4{,}358$ edges, $57$ temporal snapshots (1400–1572~CE). The complete flag complex yields $\beta_1 = 32$ cycles ($26$ macro-continental, $6$ meso-regional) and $\beta_0 = 264$ components at the finest filtration, evaluated across six layers: infrastructure, Inca political control, Spanish alliance growth, Andean tribute commerce, and Spanish legal/effective administration. Five results. (i) Infrastructure entropy $H_{\mathrm{infra}}=1.486\pm0.0001$ stays constant throughout, indicating no detectable topological disruption of the Qhapaq Ñan at this resolution. (ii) Inca political entropy $H_{\mathrm{inca}}$ is stable through the Cajamarca capture (1532~CE), then collapses to zero by 1537~CE; the dominant break is at Vilcabamba ($F=120.7$), not Cajamarca ($F=11.5$). (iii) Four of six layers reach the critical regime at 1532~CE, while infrastructure stays marginally below threshold ($\mathrm{ICT}=0.495$); trade and political reach the highest values ($\mathrm{ICT}=0.976$, $0.968$), marking Cajamarca as a synchronised multi-layer phase transition. (iv) Spanish legal administration converges to the infrastructure topology by 1572~CE ($W_1=5\times10^{-6}\approx0$): Substitution Topology, infrastructure-preserving collapse via topology transfer. (v) Legal–effective divergence decays from $W_1=0.591$ (1532) to $0.002$ (1572), quantifying resolution of colonial legal fiction. Together, these results support a distinct collapse mode—Substitution Topology—differing from erosion-dominated Roman/Byzantine collapse, Han fragmentation, and Aztec military destruction.

We show that the network of quantum register states of a quantum computer (QC), coupled through residual two-body interactions between qubits, exhibits small-world properties analogous to those of complex networks found in human society. The most probable Erdős number between any two states is about 9, comparable to the six degrees of separation reported by Milgram for social networks. Using the $\mathring{A}$berg criterion, which retains only interactions exceeding the local energy spacing, we construct an effective ($\mathring{A}$berg) network and show that, above a critical coupling strength, this network percolates into a giant component spanning nearly the whole quantum register space. This percolation transition closely matches the onset of quantum chaos and dynamical thermalization established previously via costly exact diagonalization, while our approach extends the accessible system size up to $n_q=30$ qubits.

Infrasound signal period is widely used as a proxy for source energy in bolide studies, but the reliability of period-yield relations for small, high-altitude regional meteors has not been systematically evaluated. We analyze 90 infrasound detections from well-constrained regional meteoroid events (source altitudes 20-111 km, ranges 47-268 km) and demonstrate a strong, monotonic decrease in receiver dominant frequency with increasing source altitude (Spearman r_{s} = -0.629, p = 3.3 x 10^11). No detections above 80 km retain dominant frequencies exceeding 3 Hz, and 75% of detections above 100 km are dominated by sub-1 Hz content. Partial correlation analysis indicates this is primarily an altitude effect, not a propagation distance artifact. Near-source dissipation modeling using the generalized Burgers equation supports a physical mechanism: the exponential increase in kinematic viscosity with altitude drives the acoustic Reynolds number downward, imposing frequency-dependent molecular absorption that selectively attenuates high-frequency content within the first 5 km below the source. Our results suggest that this atmospheric low-pass filter systematically modulates the observed period and can bias period-based energy estimates upward by one to two orders of magnitude for sources above 80-90 km when uncorrected period-yield relations are applied. These findings are relevant to any high-altitude infrasound source, including space debris and controlled reentries.

Next-generation submillimeter instruments require gigahertz-scale readout bandwidths to support the growing detector counts of large microwave kinetic inductance detector (KID) arrays. Designed to meet the readout bandwidth and tone-capacity requirements of the CCAT Prime-Cam 850 GHz and 410 GHz instrument modules, we developed our second-generation (Gen2) KID readout system on a Xilinx ZCU111 radio frequency system-on-chip (RFSoC), based on a parallelized overlap-channel polyphase synthesis filter bank and a companion wideband receiving channelizer. This two-octave architecture reads out four independent RF networks, each with 1.024 GHz instantaneous bandwidth and up to 2048 detectors. The polyphase synthesis doubles the baseline channel count and bandwidth, and enables on-the-fly control of individual tone frequency, amplitude and phase, facilitating optimized KID biasing and providing a gateway to tone tracking. These capabilities may also be useful more broadly across Prime-Cam and in similar frequency-division multiplexed (FDM) readout systems. We present the design in DSP simulation, and measurements in RF loopback as well as with two KID test chips, one spanning the full two-octave band. Loopback measurements demonstrate comparable noise performance between the first-generation (Gen1) baseline and Gen2; preliminary on/off-resonance measurements indicate detector-noise-limited operation for the majority of channels; and the digital channel crosstalk is measured and discussed. We report FPGA resource and power utilization and assess scalability toward future large-format KID instruments.

We present the first application of simulation-based inference to resonant inelastic X-ray scattering spectroscopy. Using truncated marginal neural ratio estimation to efficiently restrict the prior and conditional flow matching as the joint density estimator, we infer full posteriors with a modest simulation budget for two Ni$^{2+}$ compounds—NiPS$_3$ as a representative covalent case and K$_2$NiF$_4$ as a more atomic one. We demonstrate that a vision transformer encoder whose tokenization matches the physical layout of the RIXS map yields better-covered and sharper posteriors than generic image encoders. Applying the validated method to experimental NiPS$_3$ and K$_2$NiF$_4$ data, we recover a joint posterior that reveals parameter correlations invisible to point estimators, and a posterior predictive distribution that closely matches the observed spectrum. The amortized posterior unlocks a class of analyses not previously available to the field such as nuisance-marginalized uncertainty quantification, multi-measurement posterior fusion and active experimental design.

We apply persistent homology and a dual-model topological pipeline to a multilayer network of the Aztec Empire (Triple Alliance, 1427–1521 CE), constructed from tribute records and geographic adjacency among 38 nodes (Tenochtitlan-Centro, 36 tribute-paying provinces, and the Tlaxcala enclave) and 208 edges. We report four main results: (i) The tribute (control) layer is a pure extraction tree ($\bettione = 0$, $H = 0.000$ at all epochs): structurally more fragile than any documented configuration in the Roman, Byzantine, or Han administrative datasets analyzed with the same pipeline. (ii) Single-node removal of Tenochtitlan-Centro collapses the giant component from 1.000 to 0.630 and eliminates 30 redundancy cycles simultaneously, a structural asymmetry ratio of $>4$:1 relative to random perturbation. (iii) The Tlaxcala–Puebla region coincides with the dominant $\bettione$ class of the imperial geographic point cloud (persistence $= 22.09$~km, versus $< 3$~km for all others), a structural void that exists identically whether Tlaxcala is modeled as absent or present in the filtration. (iv) A logistic regression confirms that commercial centrality in the geographic layer ($r = +0.462$, $p = 0.004$) is the dominant predictor of early alliance formation, while tribute burden is uncorrelated ($r = -0.033$, $p = 0.845$). These four results define a new imperial collapse mode, the void-occupied tree, in which zero topological redundancy in the control layer coincides with a dominant geometric void occupied by an autonomous enclave—a configuration not previously documented in historical network TDA.

Molecular hydrogen formation on interstellar dust grains is a key surface process, but the partitioning of recombination energy between the substrate and the nascent molecule remains poorly understood. Here, we use ring-polymer molecular dynamics (RPMD) with a machine-learning force field to investigate energy partitioning during H2 and HD formation on graphene at T=25 K, 50 K and 100 K, focusing on the chemisorbed-H recombination pathway previously identified as the dominant low-temperature channel on bare graphitic surfaces when nuclear quantum effects are included. The desorbing molecule retains approximately 84-87% of the effective released energy, with only weak variation across the three velocity-initialization temperatures under the present sampling protocol. Within the retained molecular energy, rovibrational motion dominates at 25 K, whereas center-of-mass translation becomes increasingly important at 100 K. H2 and HD show similar total energy retention, with modest isotope-dependent differences in their internal partitioning. The effective joint rovibrational distributions show a modest positive association between vibrational and rotational excitation. Purely radiative cascade calculations in the optically thin, collision-free limit yield formation-pumping spectra at all three temperatures. From 25 to 100 K, the rovibrational fraction of the emitted energy decreases from approximately 43% to 28% for H2 and from 41% to 28% for HD, while the strongest lines remain in similar wavelength regions. These results provide an energy-resolved microscopic picture of surface-mediated energy redistribution and formation pumping in H2/HD formation on graphene.

We study the static, spherically symmetric electric branch of spontaneously vectorized Einstein-vector-Gauss-Bonnet black holes close to its Schwarzschild bifurcation. A weakly nonlinear expansion is built around the fundamental vector zero mode. The critical coupling is determined independently by shooting and collocation, the second-order metric correction is checked against the unreduced covariant equations, and the corresponding ADM-mass correction is shown to vanish analytically. The leading departure of the vectorized branch from the bifurcation point follows from a third-order Fredholm solvability condition. Using the resulting metric, we calculate the leading corrections to the photon sphere, shadow scale, marginally bound orbit, innermost stable circular orbit, orbital and epicyclic frequencies, the geometric three-to-two frequency-ratio radius, the instability of the circular photon orbit, and the logarithmic strong-deflection coefficient. Near the bifurcation, the photon sphere and innermost stable orbit move outward, whereas the three-to-two radius moves inward. The photon-orbit angular frequency decreases and its Lyapunov exponent increases. These results characterize the local strong-field geometry of the electric vectorized branch. They are not intended as observational constraints or as an extrapolation to the strongly nonlinear regime.

We construct a zero-knowledge proof of knowledge for the CSIDH group action that exploits the Chinese Remainder Theorem (CRT) structure of the ideal class group, available whenever the group structure is known exactly, as for CSIDH-512. We prove perfect completeness, perfect special honest-verifier zero-knowledge, and 2-special soundness, in which the secret is recovered from two accepting transcripts by one subtraction and one modular inversion per CRT component; no rewinding loop, lattice reduction, or heuristic sampling appears in the extractor. Because each round admits exactly two responses, Unruh's transform yields a non-interactive proof with straight-line extraction in the quantum random oracle model (QROM), removing the multiplicative forking-lemma loss. We instantiate the scheme on the CSIDH-512 class group, verify the algebraic layer by machine over the exact 258-bit modulus ($10^4$ random instances, all passing), and report protocol-level simulations in the exponent model: Monte Carlo soundness rates matching the proven $2^{-t}$ bound within 95% confidence at every tested $t$, serialized signature sizes within 1.6% of the formulas, instrumented action counts, and a scaled meet-in-the-middle attack whose measured cost follows the predicted $\sqrt{q}$ law. We further prove two delimiting results: CRT decomposition cannot enlarge the per-round challenge space, and publishing the CRT hop curves lowers classical key-recovery cost from about $2^{128.6}$ to about $2^{67.3}$ group action evaluations. The construction is therefore correct and structurally complete today, but quantitatively secure only on future parameters whose class number has large prime factors. We compare against CSI-FiSh, CSI-Otter, and Tanuki; a tightly secure blind signature from this proof of knowledge is left to future work.

The Carrier–Greenspan hodograph transformation linearises the nonlinear shallow-water equations on a beach of constant slope. We extend the transformation to a moving bottom and identify the family of bottom motions that preserves the Carrier–Greenspan invariants. The bottom gradient must be uniform in space, that is, $h(x,t)=\rho(t)x+\mathcal{B}(t)$, and constant $\rho$ returns the classical slope. For this family a horizontally accelerating frame removes the forcing. The bottom motion then disappears from the hodograph equation, and two quadratures recover the physical variables. If the gradient varies in time, the bed displacement grows without bound offshore and the far field cannot remain at rest. The domain must therefore be finite, although the pivot may be placed anywhere. A bottom-tilting wave maker realises this family. Closed forms follow for the hinge response, for the crest-to-trough steepness of the generated wave, and for the leading nonlinear correction. The correction depends on the point to which the steepness is referred, and so differs between a leading-elevation and a leading-depression wave. Because the hinge is at the beach toe, these closed forms provide the incident wave required by the classical plane-beach solution. The run-up can therefore be predicted from the plate motion alone. The steepness is predicted without a fitted constant and agrees with the reference computations. Sixty-one runs over a level bed, reported here for the first time, carry the test to deeper water and longer plate motions. The measured run-up follows the predicted run-up, with an offset that the inviscid theory does not account for.

We introduce a shell model method for calculating nuclear level density (NLD) generally applicable for arbitrarily heavy deformed nuclei. The method is novel because of our use of physical guidance for the construction of its configuration space and the computational breakthrough with the Pfaffian algorithm. Taking a well deformed even-even $^{164}$Dy nucleus as an example, we solve exactly the eigenvalue equation to obtain a large ensemble of eigenstates of angular momentum and parity. Our results indicate a potential need to revise some common understanding of the structural behavior in the pair-breaking region where the structure changes in NLD of the compound nuclei would be sensitive for cross-sections of neutron capture.

Frontogenesis is the process by which ocean fronts–regions of strong horizontal density gradients in the upper ocean–strengthen. It is a highly non-linear phenomenon arising from many competing effects, such as background strain, instabilities, and surface forcing. Vertical mixing plays a complicated role in governing both frontogenesis and the long-term dynamics of ocean fronts. For weak fronts, it has been shown to drive shear dispersion which further weakens the front over long timescales. However, vertical mixing also mixes the vertically-sheared thermal wind velocity, driving the front out of balance and causing a secondary circulation to develop that may strengthen the front. Here, it is shown that vertical mixing can directly act to oppose the frontogenetic secondary circulation, provided the frontal width is larger than a critical value. A non-linear iteration method is described for finding balanced states in which vertical mixing arrests frontogenesis and the parameter dependence of this regime is discussed. Further, existing asymptotic solutions for the buoyancy and velocity fields are extended and found to closely match these balanced states, even outside their region of formal validity.

Collective semantic change in populations of language model agents is a measurable dynamical phenomenon. We present a passive longitudinal instrument called Kopterix that observes the semantic state of an agent population as a sequence of bounded observations under a protocol defined before the observations begin. Each observation divides the sampled feed by post age into surface, mid-stream, and residue layers, which makes semantic differences across content age measurable alongside run-to-run change. We validate the instrument on Moltbook, an agent-native social platform, over a two-month window of scheduled observations, with the periodicity check extended across approximately four months. At the lexical level, rarefied entropy resolves an April-May difference in the evenness of the stored top 200 unigram distributions, and adjacent states are lexically closer than states paired after timestamp shuffling. At the geometric level, grand mean centering exposes the scale of a common embedding direction, and scheduled shuffle checks support a recurring excess in the mid-stream to residue separation relative to the shuffled reference. At the temporal level, detrended scalar quantities and centered layer centroids lose much of their similarity over several hours, and a weaker positive component declines across longer separations with no strong weekly recurrence. Several attractive apparent structures failed their controls, and each reading is limited to the level its controls support. The design applies wherever a population of agents produces a timestamped language environment that can be observed repeatedly and divided by content age.

We present a comparative study of DC electrical breakdown in liquid nitrogen, liquid helium, and liquid argon using a common cryostat, electrode assembly, voltage-ramp protocol, and analysis procedure. This common experimental configuration minimizes systematic differences that often complicate comparisons among cryogenic liquids, including variations in electrode geometry, stressed area, surface finish, and gap spacing. For each liquid, breakdown was characterized as a statistical distribution rather than by a single characteristic voltage, allowing the stochastic nature of the process to be examined. Measurements were performed both near saturated vapor pressure and under modest pressurization to assess the influence of bubble formation and related thermodynamic effects. Liquid argon exhibited a non-stationary "turn-on" behavior, with breakdown voltage increasing over repeated discharges, consistent with evolution of the local impurity environment or electrode surface state. Near saturated vapor pressure, liquid helium showed a bimodal breakdown distribution, with a lower-field component consistent with bubble-mediated processes. Liquid nitrogen exhibited higher breakdown fields than liquid argon and fields comparable to those measured in pressurized liquid helium, within the observed run-to-run variation associated with surface state. Taken together, these results support a comparative framework in which breakdown strength reflects both thermodynamic stability against bubble formation and the transport properties of the dominant negative charge carrier.

We systematically investigate four cosmological models within a parameterized framework that allows for a redshift dependence of \(H_0\): three phenomenological models (\(\alpha\Lambda\)CDM, \(\alpha w\)CDM, and \(\alpha w_0w_a\)CDM), and the $J$CDM model motivated by big bang quantum cosmology. Using cosmic microwave background (CMB) data, baryon acoustic oscillations (BAO), cosmic chronometer (CC) measurements of the Hubble parameter, and three Type Ia supernova samples (PantheonPlus, DESY5, and Union3), we perform Markov chain Monte Carlo (MCMC) analyses to obtain posterior distributions of the model parameters. We also perform separate analyses using early-time and late-time data to assess how each observational epoch affects the model constraints. For the three phenomenological models, the parameter \(\alpha\) describing the redshift evolution of \(H_0\) is consistent with zero within \(2\sigma\). The Hubble constant inferred from the \(\alpha\Lambda\)CDM model is consistent with CMB results, while the $J$CDM model yields a larger Hubble constant but is strongly disfavored by model comparison criteria. Using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) for model comparison, we find that the standard \(\Lambda\)CDM model remains the most favored by the data. Among the four models, the \(\alpha w_0w_a\)CDM model shows a marginal AIC advantage ($\rm \Delta AIC \sim$ -2 to -13). However, this preference does not translate into a reduction of the Hubble tension, which is consistent with existing studies supporting dynamical dark energy. Moreover, none of the models can simultaneously satisfy both the early- and late-time constraints, and the combined datasets alone are insufficient to conclusively determine whether these parametrizations can resolve the tension.

Graphons are measurable functions used to describe the asymptotic behavior of convergent graph families. Originally motivated by problems in combinatorics and graph theory, graphons have found numerous applications in the modeling and analysis of dynamical processes on networks. In this work, we use graphons to formulate the Ising model on convergent graph sequences, which include many network topologies common in applications. We derive the mean-field limit for the resulting model and obtain exact results for phase transitions in such systems. Specifically, we show that the critical temperatures of the Ising model on graphons are determined by the eigenvalues of the Hilbert-Schmidt operator associated with the graph limit. For many important network topologies, these eigenvalues can be computed explicitly. We illustrate our results with three representative random network models: Erdős-Rényi, small-world, and power-law. In the small-world case, we demonstrate phase transitions to both ferromagnetic and antiferromagnetic phases, as well as coexistence of local minima of the free energy. The latter gives rise to multistability, as confirmed by Monte Carlo simulations. The results of this work demonstrate that the Ising model on graphons combines the analytical tractability of exactly solvable mean-field models with the ability to accommodate a broad range of network topologies. We expect that the use of graphons in spin models will lead to new insights into the statistical physics of interacting systems on complex networks.

We demonstrate programmable, frequency-tunable and size-selective drop motion on an elastic metastrip substrate with a centipede-like array of cantilever resonators. Under harmonic excitation, the strip experiences simultaneously an in-plane (IP) collective motion and out-of-plane (OOP) deformation, thus establishing a frequency-dependent IP-OOP phase landscape. This prescribes the direction of motion to the drops on the strip based on their position, causing the emergence of clustering and rarefaction regions. By tuning the tip masses of the resonators, we open reconfigurable OOP bandgaps that modify the IP-OOP phase makeup and locally suppress drop motion, contributing an additional layer of spatial selectivity. Using multi-frequency excitations, we selectively actuate drops based on their resonances, effectively filtering them by volume and position.

This doctoral dissertation on the foundations of quantum theory isolates and then formalizes a physically relevant concept that I have called "Epistemic Constraint." Here, epistemic constraints are the definite, intersubjectively agreeable, ordinary-language conditions under which experiments are described. The usual formulation of the quantum measurement problem, which I call the Schrodingerian measurement problem, has the structure of an anomaly: if we take quantum theory at face value, we expect no definite values, and yet we see definite values in experiments. The responses to this problem have been either to solve it or to dissolve it. These responses, which have taken the form of interpretation, modification, or reconstruction of quantum mechanics, seek either to derive (conceptually or mathematically) epistemic constraints from within quantum mechanics or suitable modifications of it, as is the case with certain interpretations and modifications, or to posit the epistemic constraint, or parts of it, as a primitive assumption with the goal of deriving quantum mechanics, as is the case in some reconstruction programs. In contrast to the Schrodingerian measurement problem, which had the structure of an anomaly, this dissertation develops the Bohrian Program, which (for lack of a better comparison) has a structure similar to the problem historically associated with Euclid's fifth postulate. It seeks to keep epistemic constraints as primitive in an onto-epistemic sense. It then seeks new physical conclusions from the joint consideration of quantum mechanics and epistemic constraints, without seeking to derive one from the other. Among other results, this leads to a notion of the probability of instantiability of the Born Rule that specifies when to apply the Born Rule and when to apply a unitary transformation to a quantum state.

We investigate how quantum correlations in squeezed driving fields determine scaling laws in dissipative multiphoton quantum sensing. Independently squeezed fields yield factorized scaling, with separate absorption and emission contributions and nonlinear thresholds that suppress exponential scaling in linear processes. In contrast, jointly squeezed fields generate collective scaling governed by the total nonlinear photon order of the dissipative interaction. Remarkably, we show that normally ordered observables do not inherit the full nonlinear scaling of the underlying multiphoton fluctuations. Instead, they exhibit asymptotic behavior with an effective nonlinear order reduced by one. This arises because normally ordered observables probe only part of the underlying multiphoton fluctuation structure. These findings reveal how multiphoton fluctuations, quantum correlations, and measurement structure jointly determine the experimentally accessible sensitivity of nonlinear dissipative quantum sensors and establish design principles for quantum sensing protocols based on structured squeezed light.

Quantum machine learning (QML) for network intrusion detection (NIDS) is routinely reported to reach near-perfect accuracy, yet the most rigorous studies find that well-tuned classical models remain competitive, and that apparent quantum gains may be artefacts of classical dimensionality reduction and implicit regularisation rather than genuine quantum effects. We ask not whether a quantum model can post a high accuracy, but how quantum the advantage really is. We present a unified, reproducible QML-IDS benchmark evaluating hybrid variational quantum circuits and quantum-kernel SVMs against five honestly-tuned classical baselines across four standard NIDS datasets (NSL-KDD, UNSW-NB15, CICIDS2017, NF-ToN-IoT-v2) under one leakage-controlled protocol, with an equal-budget feature view, imbalance- and calibration-aware metrics with significance testing, and a simulated NISQ noise sweep. We introduce a quantum-attribution audit (parameter-matched classical controls, a random-feature kernel, and a regularisation sweep) that quantifies how much of any gain is genuinely attributable to the quantum component. Tuned classical models (Random Forest, XGBoost) match or exceed the quantum models on aggregate detection on every dataset, and the audit attributes this to classical preprocessing and regularisation rather than quantum effects. Two advantages survive false-discovery-rate correction: the quantum-kernel SVM out-ranks its direct classical surrogate (a random-feature kernel) on AUPRC and ROC-AUC, and a small four-qubit hybrid out-detects the best classical baseline at the 1% false-positive operating point on the distribution-shifted NSL-KDD task (p = 0.005, BH q = 0.030). Code, seeds, and splits are released; our contribution stands whether quantum wins, ties, or loses.

We report a fixed-order Clauser-Horne-Shimony-Holt (CHSH) acquisition and reporting protocol for two encoded photonic qubits on Quandela's commercial, cloud-accessible Belenos processor, executed end-to-end by external users through the public cloud interface. Each logical qubit is a two-dimensional spatial-mode subspace in the seven-dimensional zero-sum sector of an eight-mode single-photon register, and a target postselected linear-optical controlled-$Z$ (ideal success probability $1/9$) couples the registers on $16$ of $24$ modes. The primary quantity is the operational CHSH score $S$ on accepted logical coincidences, with each complete four-setting pass as the experimental unit. Eight sequential same-day passes each gave a raw score above $2$; session means were $2.40$ and $2.58$ (sample standard deviations $0.15$ and $0.03$), with excess dispersion $Q/\nu=6.1$ ($\nu=7$). Count-pooled secondary descriptors are $S_{\mathrm{count}}=2.485\pm0.019$ and a fixed-ratio efficiency-reweighted model scenario $S^{\mathrm{rw}}_{\mathrm{count}}=2.380\pm0.021$, whose weakest reweighted pass ($2.040\pm0.062$) overlapped $2$ within $1\sigma$. The reweighting is an archived-metadata model scenario, not a corrected platform score; an ad hoc $\kappa\in[1.2,1.8]$ stress scan (not a calibrated uncertainty band) spans $2.341$-$2.441$. Setting order was fixed, the compiled mapping was not returned, and residual remote-setting marginals remain, so the data support an operational reference acquisition rather than an entanglement-witness or cross-platform benchmarking claim. The parity-check terminology labels the encoding subspace; no syndrome measurement was performed. Count records, job identifiers, circuit-construction code, and analysis are openly archived with content hashes for the submitted targets.

Topological charge pumping is paradigmatically understood through two-band systems such as the Rice-Mele model, which are intrinsically restricted to a single independent pumping channel. In this work, we introduce the Trimer Thouless Pump (TTP), a minimal three-band generalization that exhibits genuinely multigap topological transport. By subjecting a one-dimensional three-site lattice to cyclic adiabatic modulations of its hopping amplitudes and antisymmetric onsite potentials, we explore a topological regime characterized by two independent bulk gaps. We show that the quantized charge transport is driven by highly localized Berry curvature hotspots corresponding to effective two-level Dirac avoided crossings on the parameter torus. Crucially, we demonstrate that the middle energy band acts as a geometric mediator: it facilitates the exchange of quantized Berry flux between the upper and lower bands while maintaining a net zero Chern number itself. This bulk topology is corroborated by the spectral flow of boundary-localized edge states traversing multiple gaps. Furthermore, we map the topological phase diagram as a function of central-site detuning, illustrating a band-selective transfer of topological invariants across discrete phase transitions. Finally, we propose a concrete experimental protocol to realize the TTP and observe its multigap charge transport using ultracold atoms in phase-controlled optical superlattices.

Recovering high-resolution states from sparse, low-resolution observations is a central challenge in scientific machine learning and data assimilation. Classical data assimilation exploits temporal information through forecast-analysis cycles, but often requires repeated access to expensive high-resolution forecast models. Generative super-resolution can recover unresolved structure from coarse observations, but is commonly used as a one-shot mapping that does not fully exploit constraints from past states. We introduce Iterative Refinement (IR), a learned data assimilation framework that combines these perspectives. Instead of performing a single coarse-to-fine reconstruction, IR decomposes the task into resolution-wise forecast-analysis operations across a multiresolution hierarchy. At each stage, a shared neural operator with resolution-dependent spectral mode slicing provides a dynamical prior, while a shared conditional diffusion corrector uses the current coarser-resolution state to produce a refined posterior at the next finer resolution. We evaluate IR on one-dimensional stochastically forced Burgers dynamics and two-dimensional Kraichnan turbulence. On the challenging 256x256 Kraichnan benchmark, IR achieves an RMSE of 0.184 and an SSIM of 0.836, outperforming spectral upsampling, one-shot diffusion super-resolution, enhanced deep super-resolution, and an autoregressive forecaster. On the more constrained Burgers testbed, IR remains competitive with one-shot diffusion, which achieves the lowest RMSE. These results show that one-shot generative reconstruction can be effective for simpler settings, while hierarchical forecast-analysis refinement becomes advantageous in strongly multiscale and underdetermined regimes. Overall, IR combines temporal priors, generative correction, and multiresolution reconstruction for learned data assimilation in complex physical systems.

The term "superatom" was introduced over three decades ago to describe clusters that emulate elemental atoms. The field has long been guided by the spherical jellium model, where magic numbers arise from shell closure of delocalized electrons. This Perspective argues that delocalization, not near-sphericity, is what makes a system atom-like. It shows that superatomic shell structure persists under arbitrary point-group symmetry, that superatomicity survives as a tunable quantum state across pressurized, ionized, and chemically precompressed systems, and that the symmetry rules governing superatoms are conditional, deeper than the jellium picture admits. The future of this field lies not in finding more magic numbers, but in exploiting superatomic states as artificial quantum systems at the atomic level.