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In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, despite significant progress and excitement, the path toward a full-stack scalable technology is largely unknown. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. These issues could seriously undermine the arrival of utility-scale quantum computers for the foreseeable future. Here, we provide a comprehensive review of these scaling challenges. We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits, employing system engineering approaches, and performing distributed quantum computation within heterogeneous high-performance computing infrastructures. These opportunities for research and development could unlock certain promising applications, in particular, efficient quantum simulation/learning of quantum data generated by natural or engineered quantum systems. To estimate the true cost of such promises, we provide a detailed resource and sensitivity analysis for classically hard quantum chemistry calculations on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. Furthermore, we argue that, to tackle industry-scale classical optimization and machine learning problems in a cost-effective manner, distributed quantum-assisted probabilistic computing with custom-designed accelerators should be considered as a complementary path toward scalability., Comment: 50 pages, 42 figures

Disordered superconductors offer new impedance regimes for quantum circuits, enable a pathway to protected qubits and improve superconducting single photon detectors due to their high kinetic inductance and sheet resistance. However, the relaxation of quasiparticles, which cause decoherence and microwave loss, is drastically affected by disorder, which is still not understood. We address this issue by measuring the quasiparticle relaxation time in a disordered $\beta$-Ta film, which we pattern as the inductor of a microwave resonator. We observe that the quasiparticle relaxation time is governed by the phonon scattering time and is independent on the phononic environment, which is in stark contrast to the relaxation of quasiparticles in ordered superconductors. We explain these observations in terms of the recombination of localized quasiparticles that first delocalize via phonon scattering. We analyse quasiparticle relaxation measurements on superconductors with different degrees of disorder and conclude that this phenomenon is inherent to disordered superconductors., Comment: 8 pages main text, including 3 figures

In the evolving landscape of human-autonomy teaming (HAT), fostering effective collaboration and trust between human and autonomous agents is increasingly important. To explore this, we used the game Overcooked AI to create dynamic teaming scenarios featuring varying agent behaviors (clumsy, rigid, adaptive) and environmental complexities (low, medium, high). Our objectives were to assess the performance of adaptive AI agents designed with hierarchical reinforcement learning for better teamwork and measure eye tracking signals related to changes in trust and collaboration. The results indicate that the adaptive agent was more effective in managing teaming and creating an equitable task distribution across environments compared to the other agents. Working with the adaptive agent resulted in better coordination, reduced collisions, more balanced task contributions, and higher trust ratings. Reduced gaze allocation, across all agents, was associated with higher trust levels, while blink count, scan path length, agent revisits and trust were predictive of the humans contribution to the team. Notably, fixation revisits on the agent increased with environmental complexity and decreased with agent versatility, offering a unique metric for measuring teammate performance monitoring. These findings underscore the importance of designing autonomous teammates that not only excel in task performance but also enhance teamwork by being more predictable and reducing the cognitive load on human team members. Additionally, this study highlights the potential of eye-tracking as an unobtrusive measure for evaluating and improving human-autonomy teams, suggesting eye gaze could be used by agents to dynamically adapt their behaviors.

Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This systematic review provides an overview of Artificial Intelligence (AI) methods using radiological imaging for diagnosis and prognosis of these tumours, highlighting challenges in clinical translation, and evaluating study alignment with the Checklist for AI in Medical Imaging (CLAIM) and the FUTURE-AI international consensus guidelines for trustworthy and deployable AI to promote the clinical translation of AI methods. The review covered literature from several bibliographic databases, including papers published before 17/07/2024. Original research in peer-reviewed journals focused on radiology-based AI for diagnosing or prognosing primary STBT was included. Exclusion criteria were animal, cadaveric, or laboratory studies, and non-English papers. Abstracts were screened by two of three independent reviewers for eligibility. Eligible papers were assessed against guidelines by one of three independent reviewers. The search identified 15,015 abstracts, from which 325 articles were included for evaluation. Most studies performed moderately on CLAIM, averaging a score of 28.9$\pm$7.5 out of 53, but poorly on FUTURE-AI, averaging 5.1$\pm$2.1 out of 30. Imaging-AI tools for STBT remain at the proof-of-concept stage, indicating significant room for improvement. Future efforts by AI developers should focus on design (e.g. define unmet clinical need, intended clinical setting and how AI would be integrated in clinical workflow), development (e.g. build on previous work, explainability), evaluation (e.g. evaluating and addressing biases, evaluating AI against best practices), and data reproducibility and availability (making documented code and data publicly available). Following these recommendations could improve clinical translation of AI methods., Comment: 23 pages, 6 figures, 6 supplementary figures

Parallel plate capacitors (PPC) significantly reduce the size of superconducting microwave resonators, reducing the pixel pitch for arrays of single photon energy-resolving kinetic inductance detectors (KIDs). The frequency noise of KIDs is typically limited by tunneling Two-Level Systems (TLS), which originate from lattice defects in the dielectric materials required for PPCs. How the frequency noise level depends on the PPC's dimensions has not been experimentally addressed. We measure the frequency noise of 56 resonators with a-SiC:H PPCs, which cover a factor 44 in PPC area and a factor 4 in dielectric thickness. To support the noise analysis, we measure the TLS-induced, power-dependent, intrinsic loss and temperature-dependent resonance frequency shift of the resonators. From the TLS models, we expect a geometry-independent microwave loss and resonance frequency shift, set by the TLS properties of the dielectric. However, we observe a thickness-dependent microwave loss and resonance frequency shift, explained by surface layers that limit the performance of PPC-based resonators. For a uniform dielectric, the frequency noise level should scale directly inversely with the PPC area and thickness. We observe that an increase in PPC size reduces the frequency noise, but the exact scaling is, in some cases, weaker than expected. Finally, we derive an engineering guideline for the design of KIDs based on PPC-based resonators., Comment: 13 pages, 11 figures

Kinetic Inductance Detectors (KIDs) are superconducting energy-resolving detectors, sensitive to single photons from the near-infrared to ultraviolet. We study a hybrid KID design consisting of a beta phase tantalum ($\beta$-Ta) inductor and a NbTiN interdigitated capacitor (IDC). The devices show an average intrinsic quality factor $Q_i$ of 4.3$\times10^5$ $\pm$ 1.3 $\times10^5$. To increase the power captured by the light sensitive inductor, we 3D-print an array of 150$\times$150 $\mu$m resin micro lenses on the backside of the sapphire substrate. The shape deviation between design and printed lenses is smaller than 1$\mu$m, and the alignment accuracy of this process is $\delta_x = +5.8 \pm 0.5$ $\mu$m and $\delta_y = +8.3 \pm 3.3$ $\mu$m. We measure a resolving power for 1545-402 nm that is limited to 4.9 by saturation in the KID's phase response. We can model the saturation in the phase response with the evolution of the number of quasiparticles generated by a photon event. An alternative coordinate system that has a linear response raises the resolving power to 5.9 at 402 nm. We verify the measured resolving power with a two-line measurement using a laser source and a monochromator. We discuss several improvements that can be made to the devices on a route towards KID arrays with high resolving powers., Comment: 13 pages, 11 Figures, Journal Paper

Typical materials for optical Kinetic Inductance Detetectors (KIDs) are metals with a natural absorption of 30-50% in the visible and near-infrared. To reach high absorption efficiencies (90-100%) the KID must be embedded in an optical stack. We show an optical stack design for a 60 nm TiN film. The optical stack is modeled as sections of transmission lines, where the parameters for each section are related to the optical properties of each layer. We derive the complex permittivity of the TiN film from a spectral ellipsometry measurement. The designed optical stack is optimised for broadband absorption and consists of, from top (illumination side) to bottom: 85 nm SiOx, 60 nm TiN, 23 nm of SiOx, and a 100 nm thick Al mirror. We show the modeled absorption and reflection of this stack, which has >80% absorption from 400 nm to 1550 nm and near-unity absorption for 500 nm to 800 nm. We measure transmission and reflection of this stack with a commercial spectrophotometer. The results are in good agreement with the model., Comment: 8 pages, 5 figures (color), Journal of Low Temperature Physics (2022)

This paper describes a research study that aims to investigate changes in effective communication during human-AI collaboration with special attention to the perception of competence among team members and varying levels of task load placed on the team. We will also investigate differences between human-human teamwork and human-agent teamwork. Our project will measure differences in the communication quality, team perception and performance of a human actor playing a Commercial Off - The Shelf game (COTS) with either a human teammate or a simulated AI teammate under varying task load. We argue that the increased cognitive workload associated with increases task load will be negatively associated with team performance and have a negative impact on communication quality. In addition, we argue that positive team perceptions will have a positive impact on the communication quality between a user and teammate in both the human and AI teammate conditions. This project will offer more refined insights on Human - AI relationship dynamics in collaborative tasks by considering communication quality, team perception, and performance under increasing cognitive workload., Comment: Presented at AI-HRI symposium as part of AAAI-FSS 2021 (arXiv:2109.10836)

Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, finding the optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-and-error process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows per application. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms for each component. To optimize the workflow per application, we employ automated machine learning using a random search and ensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1) liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77); 5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis (0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer's disease (0.87); and 12) head and neck cancer (0.84). We show that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performs similar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automatically optimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications. To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework, and the code to reproduce this study., Comment: 33 pages, 4 figures, 4 tables, 2 supplementary figures, 3 supplementary table, submitted to Medical Image Analysis; revision

A noiseless, photon counting detector, which resolves the energy of each photon, could radically change astronomy, biophysics and quantum optics. Superconducting detectors promise an intrinsic resolving power at visible wavelengths of $R=E/\delta E\approx100$ due to their low excitation energy. We study superconducting energy-resolving Microwave Kinetic Inductance Detectors (MKIDs), which hold particular promise for larger cameras. A visible/near-infrared photon absorbed in the superconductor creates a few thousand quasiparticles through several stages of electron-phonon interaction. Here we demonstrate experimentally that the resolving power of MKIDs at visible to near-infrared wavelengths is limited by the loss of hot phonons during this process. We measure the resolving power of our aluminum-based detector as a function of photon energy using four lasers with wavelengths between $1545-402$ nm. For detectors on thick SiN/Si and sapphire substrates the resolving power is limited to $10-21$ for the respective wavelengths, consistent with the loss of hot phonons. When we suspend the sensitive part of the detector on a 110 nm thick SiN membrane, the measured resolving power improves to $19-52$ respectively. The improvement is equivalent to a factor $8\pm2$ stronger phonon trapping on the membrane, which is consistent with a geometrical phonon propagation model for these hot phonons. We discuss a route towards the Fano limit by phonon engineering., Comment: 14 pages, 8 figures, including appendices

We measure temperature dependent quasiparticle fluctuations in a small Al volume, embedded in a NbTiN superconducting microwave resonator. The resonator design allows for read-out close to equilibrium. By placing the Al film on a membrane, we enhance the fluctuation level and separate quasiparticle from phonon effects. When lowering the temperature, the recombination time saturates and the fluctuation level reduces a factor $\sim$100. From this we deduce that the number of free quasiparticles is still thermal. Therefore, the theoretical, inverse relation between quasiparticle number and recombination time is invalid in this experiment. This is consistent with quasiparticle trapping, where on-trap recombination limits the observed quasiparticle lifetime., Comment: Main text: 5 pages, 3 figures; Supplemental material: 11 pages, 8 figures

The idea that preformed Cooper pairs could exist in a superconductor above its zero-resistance state has been explored for unconventional, interface, and disordered superconductors, yet direct experimental evidence is lacking. Here, we use scanning tunneling noise spectroscopy to unambiguously show that preformed Cooper pairs exist up to temperatures much higher than the zero-resistance critical temperature $T_{C}$ in the disordered superconductor titanium nitride, by observing a clear enhancement in the shot noise that is equivalent to a change of the effective charge from 1 to 2 electron charges. We further show that spectroscopic gap fills up rather than closes when increasing temperature. Our results thus demonstrate the existence of a novel state above $T_{C}$ that, much like an ordinary metal, has no (pseudo)gap, but carries charge via paired electrons.

Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA,BRAF mutational status and mitotic index (MI). All 247 included patients (125 GISTS, 122 non-GISTs) underwent a contrast-enhanced venous phase CT. The GIST vs. non-GIST radiomics model, including imaging, age, sex and location, had a mean area under the curve (AUC) of 0.82. Three radiologists had an AUC of 0.69, 0.76, and 0.84, respectively. The radiomics model had an AUC of 0.52 for c-KIT, 0.56 for c-KIT exon 11, and 0.52 for the MI. Hence, our radiomics model was able to distinguish GIST from non-GISTS with a performance similar to three radiologists, but was not able to predict the c-KIT mutation or MI., Comment: Martijn P.A. Starmans and Milea J.M. Timbergen contributed equally

We are developing an ultra-wideband spectroscopic instrument, DESHIMA (DEep Spectroscopic HIgh-redshift MApper), based on the technologies of an on-chip filter-bank and Microwave Kinetic Inductance Detector (MKID) to investigate dusty star-burst galaxies in the distant universe at millimeter and submillimeter wavelength. An on-site experiment of DESHIMA was performed using the ASTE 10-m telescope. We established a responsivity model that converts frequency responses of the MKIDs to line-of-sight brightness temperature. We estimated two parameters of the responsivity model using a set of skydip data taken under various precipitable water vapor (PWV, 0.4-3.0 mm) conditions for each MKID. The line-of-sight brightness temperature of sky is estimated using an atmospheric transmission model and the PWVs. As a result, we obtain an average temperature calibration uncertainty of $1\sigma=4$%, which is smaller than other photometric biases. In addition, the average forward efficiency of 0.88 in our responsivity model is consistent with the value expected from the geometrical support structure of the telescope. We also estimate line-of-sight PWVs of each skydip observation using the frequency response of MKIDs, and confirm the consistency with PWVs reported by the Atacama Large Millimeter/submillimeter Array., Comment: Accepted for publication in the Journal of Low Temperature Physics for LTD-18 special issue