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We explore the potential for hybrid development of quantum hardware where currently available quantum computers simulate open Cavity Quantum Electrodynamical (CQED) systems for applications in optical quantum communication, simulation and computing. Our simulations make use of a recent quantum algorithm that maps the dynamics of a singly excited open Tavis-Cummings model containing N atoms coupled to a lossy cavity. We report the results of executing this algorithm on two noisy intermediate-scale quantum computers: a superconducting processor and a trapped ion processor, to simulate the population dynamics of an open CQED system featuring N = 3 atoms. By applying technology-specific transpilation and error mitigation techniques, we minimize the impact of gate errors, noise, and decoherence in each hardware platform, obtaining results which agree closely with the exact solution of the system. These results can be used as a recipe for efficient and platform-specific quantum simulation of cavity-emitter systems on contemporary and future quantum computers. 

Abstract We discuss the model of astrophysical emission at millimeter wavelengths used to characterize foregrounds in the multi-frequency power spectra of the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6), expanding on Louis et al. (2025) (2503.14452). We detail several tests to validate the capability of the DR6 parametric foreground model to describe current observations and complex simulations, and show that cosmological parameter constraints are robust against model extensions and variations. We demonstrate consistency of the model with pre-DR6 ACT data and observations fromPlanckand the South Pole Telescope. We evaluate the implications of using different foreground templates and extending the model with new components and/or free parameters. In all scenarios, the DR6 ΛCDM and ΛCDM+N_effcosmological parameters shift by less than 0.5σrelative to the baseline constraints. Some foreground parameters shift more; we estimate their systematic uncertainties associated with modeling choices. From our constraint on the kinematic Sunyaev-Zel'dovich power, we obtain a conservative limit on the duration of reionization of Δz_rei< 4.4, assuming a reionization midpoint consistent with optical depth measurements and a minimal low-redshift contribution, with varying assumptions for this component leading to tighter limits. Finally, we analyze realistic non-Gaussian, correlated microwave sky simulations containing Galactic and extragalactic foreground fields, built independently of the DR6 parametric foreground model. Processing these simulations through the DR6 power spectrum and likelihood pipeline, we recover the input cosmological parameters of the underlying cosmic microwave background field, a new demonstration for small-scale CMB analysis. These tests validate the robustness of the ACT DR6 foreground model and cosmological parameter constraints. 

ABSTRACT The interstellar medium is threaded by a hierarchy of filaments from large scales (∼100 pc) to small scales (∼0.1 pc). The masses and lengths of these nested structures may reveal important constraints for cloud formation and evolution, but it is difficult to investigate from an evolutionary perspective using single observations. In this work, we extract simulated molecular clouds from the ‘Cloud Factory’ galactic-scale ISM suite in combination with 3D Monte Carlo radiative transfer code polaris to investigate how filamentary structure evolves over time. We produce synthetic dust continuum observations in three regions with a series of snapshots and use the filfinder algorithm to identify filaments in the dust derived column density maps. When the synthetic filaments mass and length are plotted on an mass–length (M–L) plot, we see a scaling relation of L ∝ M0.45 similar to that seen in observations, and find that the filaments are thermally supercritical. Projection effects systematically affect the masses and lengths measured for the filaments, and are particularly severe in crowded regions. In the filament M–L diagram we identify three main evolutionary mechanisms: accretion, segmentation, and dispersal. In particular we find that the filaments typically evolve from smaller to larger masses in the observational M–L plane, indicating the dominant role of accretion in filament evolution. Moreover, we find a potential correlation between line mass and filament growth rate. Once filaments are actively star forming they then segment into smaller sections, or are dispersed by internal or external forces. 

The HI-based Stokes parameter maps used in (https://arxiv.org/abs/2306.10107) Filamentary Dust Polarization and the Morphology of HI Structures, Halal et al. 2023. Use of these data must cite that paper and (https://ui.adsabs.harvard.edu/abs/2019ApJ...887..136C/abstract) Clark & Hensley 2019. There are four sets of data cubes: one at Nside=1024 based on the 4' GALFA-HI data computed using the Spherical RHT algorithm, one at Nside=2048 based on the 4' GALFA-HI data smoothed to 7' computed using the Hessian algorithm, and two at Nside=1024 based on the 16.2' HI4PI data (one computed using the Spherical RHT algorithm and the other using the Hessian algorithm). A map based on the Hessian algorithm and the 16.2' HI4PI data, integrated over the velocity range -13 km/s to 16 km/s (Section 4.1 in Halal et al. 2023), is also available. The provided data cubes can be used to produce integrated maps over any velocity range desired. <br/><br/> These maps are given in units of K km/s and follow the Galactic IAU polarization convention. Multiply U by -1 to obtain maps corresponding to the COSMO convention as those provided by Planck. Multiply both Q and U by -1 to obtain maps corresponding to the magnetic field orientation in the IAU convention. <br/><br/> Please see (https://github.com/seclark/ClarkHensley2019) for code that demonstrates the use of data of the same format. The velocity binning of this data follows that of <a href="https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/P41KDE">Clark & Hensley 2019</a> and can be found <a href="https://github.com/seclark/ClarkHensley2019/tree/master/data">here</a>. 

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations. 

Most near-term quantum information processing devices will not be capable of implementing quantum error correction and the associated logical quantum gate set. Instead, quantum circuits will be implemented directly using the physical native gate set of the device. These native gates often have a parameterization (e.g., rotation angles) which provide the ability to perform a continuous range of operations. Verification of the correct operation of these gates across the allowable range of parameters is important for gaining confidence in the reliability of these devices. In this work, we demonstrate a procedure for sample-efficient verification of continuously-parameterized quantum gates for small quantum processors of up to approximately 10 qubits. This procedure involves generating random sequences of randomly-parameterized layers of gates chosen from the native gate set of the device, and then stochastically compiling an approximate inverse to this sequence such that executing the full sequence on the device should leave the system near its initial state. We show that fidelity estimates made via this technique have a lower variance than fidelity estimates made via cross-entropy benchmarking. This provides an experimentally-relevant advantage in sample efficiency when estimating the fidelity loss to some desired precision. We describe the experimental realization of this technique using continuously-parameterized quantum gate sets on a trapped-ion quantum processor from Sandia QSCOUT and a superconducting quantum processor from IBM Q, and we demonstrate the sample efficiency advantage of this technique both numerically and experimentally. 

Abstract We present a cross-correlation analysis between $1\prime$resolution total intensity and polarization observations from the Atacama Cosmology Telescope (ACT) at 150 and 220 GHz and 15″ mid-infrared photometry from the Wide-field Infrared Survey Explorer (WISE) over 107 12.°5 × 12.°5 patches of sky. We detect a spatially isotropic signal in the WISE×ACTTTcross-power spectrum at 30σsignificance that we interpret as the correlation between the cosmic infrared background at ACT frequencies and polycyclic aromatic hydrocarbon (PAH) emission from galaxies in WISE, i.e., the cosmic PAH background. Within the Milky Way, the Galactic dustTTspectra are generally well described by power laws inℓover the range 10³<ℓ< 10⁴, but there is evidence both for variability in the power-law index and for non-power-law behavior in some regions. We measure a positive correlation between WISE total intensity and ACTE-mode polarization at 1000 <ℓ≲ 6000 at >3σin each of 35 distinct ∼100 deg²regions of the sky, suggesting that alignment between Galactic density structures and the local magnetic field persists to subparsec physical scales in these regions. The distribution ofTEamplitudes in thisℓrange across all 107 regions is biased to positive values, while there is no evidence for such a bias in theTBspectra. This work constitutes the highest-ℓmeasurements of the Galactic dustTEspectrum to date and indicates that cross-correlation with high-resolution mid-infrared measurements of dust emission is a promising tool for constraining the spatial statistics of dust emission at millimeter wavelengths.