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As quantum technology advances and the size of quantum computers grow, it becomes increasingly important to understand the extent of quality in the devices. As large-scale entanglement is a quantum resource crucial for achieving quantum advantage, the challenge in its generation makes it a valuable benchmark for measuring the performance of universal quantum devices. In this paper, we study entanglement in Greenberger-Horne-Zeilinger (GHZ) and graph states prepared on the range of IBM Quantum devices. We generate GHZ states and investigate their coherence times with respect to state size and dynamical decoupling techniques. A GHZ fidelity of 0.519±0.014 is measured on a 32-qubit GHZ state, certifying its genuine multipartite entanglement (GME). We show a substantial improvement in GHZ decoherence rates for a seven-qubit GHZ state after implementing dynamical decoupling, and observe a linear trend in the decoherence rate of α=(7.13N+5.54)×10^{−3}µs^{−1} for up to N=15 qubits, confirming the absence of superdecoherence. Additionally, we prepare and characterize fully bipartite entangled native-graph states on 22 superconducting quantum devices with qubit counts as high as 414 qubits, all active qubits of the 433-qubit IBM Osprey device. Analysis of the decay of two-qubit entanglement within the prepared states shows suppression of coherent noise signals with the implementation of dynamical decoupling techniques. Additionally, we observe that the entanglement in some qubit pairs oscillates over time, which is likely caused by residual ZZ-interactions. Characterizing entanglement in native-graph states, along with detecting entanglement oscillations, can be an effective approach to low-level device benchmarking that encapsulates two-qubit error rates along with additional sources of noise, with possible applications to quantum circuit compilation. We develop several tools to automate the preparation and entanglement characterization of GHZ and graph states. In particular, a method to characterize graph state bipartite entanglement using just 36 circuits, constant with respect to the number of qubits.

Abstract The efficient preparation of quantum states is an important step in the execution of many quantum algorithms. In the noisy intermediate-scale quantum (NISQ) computing era, this is a significant challenge given quantum resources are scarce and typically only low-depth quantum circuits can be implemented on physical devices. We present a genetic algorithm for state preparation (GASP) which generates relatively low-depth quantum circuits for initialising a quantum computer in a specified quantum state. The method uses a basis set of $$R_x$$ R x , $$R_y$$ R y , $$R_z$$ R z , and CNOT gates and a genetic algorithm to systematically generate circuits to synthesize the target state to the required fidelity. GASP can produce more efficient circuits of a given accuracy with lower depth and gate counts than other methods. This variability of the required accuracy facilitates overall higher accuracy on implementation, as error accumulation in high-depth circuits can be avoided. We directly compare the method to the state initialisation technique based on an exact synthesis technique by implemented in IBM Qiskit simulated with noise and implemented on physical IBM Quantum devices. Results achieved by GASP outperform Qiskit’s exact general circuit synthesis method on a variety of states such as Gaussian states and W-states, and consistently show the method reduces the number of gates required for the quantum circuits to generate these quantum states to the required accuracy.

Background: Several studies have demonstrated the utility of methylene blue (MB) to treat vasoplegic syndrome (VS), but some have cautioned against its routine use in lung transplantation with only two cases described in prominent literature. Cystic fibrosis patients commonly have chronic infections which predispose them to a systemic inflammatory syndrome-like vasoplegic response during lung transplantation. We present 13 cystic fibrosis patients who underwent lung transplantation and received MB for vasoplegic syndrome while on cardiopulmonary bypass, with or without inhaled pulmonary vasodilator therapy. Methods: Single-center, retrospective, case series analysis of cystic fibrosis patients who underwent lung transplant and received MB for vasoplegia. We defined the primary outcome as 30-day mortality, and secondary outcomes as primary graft failure, 1-year mortality, postoperative complications, and hemodynamic response to MB. Results: MB was associated with a significant increase in mean arterial pressure (MAP) (P < 0.001) in all patients, and 84.6% (11/13) of the patients had either a decrease or no change in vasopressor requirement. No patients developed acute primary graft dysfunction and there was 100% 30-day and 1-year survival. One patient required Extracorporeal membrane oxygenation (ECMO) for hypoxemia and 69% (9/13) of the patients had evidence of postoperative right ventricular dysfunction, but no patients required a right ventricular assist device. Conclusion: This case series demonstrates the effectiveness of MB in treating vasoplegia in cystic fibrosis patients during lung transplantation, without evidence of primary graft dysfunction, 30-day or 1-year mortality. The safety of MB regarding hypoxemia and increased pulmonary vascular resistance requires further investigation.

Abstract Quantum computers hold promise to circumvent the limitations of conventional computing for difficult molecular problems. However, the accumulation of quantum logic errors on real devices represents a major challenge, particularly in the pursuit of chemical accuracy requiring the inclusion of electronic correlation effects. In this work we implement the quantum computed moments (QCM) approach for hydrogen chain molecular systems up to H $$_6$$ 6 . On a superconducting quantum processor, Hamiltonian moments, $$\langle H^p\rangle$$ ⟨ H p ⟩ are computed with respect to the Hartree–Fock state, which are then employed in Lanczos expansion theory to determine an estimate for the ground-state energy which incorporates electronic correlations and manifestly improves on the direct energy measurement. Post-processing purification of the raw QCM data takes the estimate below the Hartree–Fock energy to within 99.9% of the exact electronic ground-state energy for the largest system studied, H $$_6$$ 6 . Calculated dissociation curves indicate precision at about 10mH for this system and as low as 0.1mH for molecular hydrogen, H $$_2$$ 2 , over a range of bond lengths. In the context of stringent precision requirements for chemical problems, these results provide strong evidence for the error suppression capability of the QCM method, particularly when coupled with post-processing error mitigation. While calculations based on the Hartree–Fock state are tractable to classical computation, these results represent a first step towards implementing the QCM method in a quantum chemical trial circuit. Greater emphasis on more efficient representations of the Hamiltonian and classical preprocessing steps may enable the solution of larger systems on near-term quantum processors.

Pancreatic neuroendocrine tumors (pNETs) are rare pancreatic neoplasms and are even more uncommon in the pediatric patients, thus leading to a lack of clinical research on diagnosis and management in this population. The purpose of this report is to review relevant literature and discuss a rare occurrence of a non-functioning pNET in a pediatric patient. This is a report of an 11-year-old male who presented with symptomatic anemia and was found to have a 6 cm mass near the pancreatic head with erosion into the duodenum. Surgical biopsy demonstrated a non-functioning pNET. He was successfully managed with complete surgical resection via a standard pancreaticoduodenectomy without evidence of recurrence after 1 year follow up. Further multi-institutional prospective studies or meta-analyses are warranted to further explore optimal management in the pediatric population.

In the lead up to fault tolerance, the utility of quantum computing will be determined by how adequately the effects of noise can be circumvented in quantum algorithms. Hybrid quantum-classical algorithms such as the variational quantum eigensolver (VQE) have been designed for the short-term regime. However, as problems scale, VQE results are generally scrambled by noise on present-day hardware. While error mitigation techniques alleviate these issues to some extent, there is a pressing need to develop algorithmic approaches with higher robustness to noise. Here, we explore the robustness properties of the recently introduced quantum computed moments (QCM) approach to ground state energy problems, and show through an analytic example how the underlying energy estimate explicitly filters out incoherent noise. Motivated by this observation, we implement QCM for a model of quantum magnetism on IBM Quantum hardware to examine the noise-filtering effect with increasing circuit depth. We find that QCM maintains a remarkably high degree of error robustness where VQE completely fails. On instances of the quantum magnetism model up to 20 qubits for ultra-deep trial state circuits of up to 500 CNOTs, QCM is still able to extract reasonable energy estimates. The observation is bolstered by an extensive set of experimental results. To match these results, VQE would need hardware improvement by some 2 orders of magnitude on error rates.

Hepatic mesenchymal hamartomas (HMH) are benign liver lesions that present as cystic, slow growing masses within the first few years of life. Few cases demonstrate placental abnormalities and abnormal levels of alpha-fetoprotein (AFP). We report an unusual case of a rapidly growing HMH with associated placental anomalies and elevated AFP. A 2-month-old female born prematurely due to concerning placental findings presented with a prenatally-identified liver mass. Magnetic resonance imaging (MRI) showed a marked increase in the size of the mass over a three-month period. Prior to surgery, the AFP was elevated and decreased after operative resection. Histopathology confirmed the diagnosis HMH. Rapid growth of HMH is not commonly reported and raises concerns for malignancy. Abnormal placental findings may lead to prematurity, which can affect surgical management. We identified 27 cases of prenatally diagnosed HMH since 1983. The mean gestational age for identification was 29 weeks, with the majority managed by delayed resection. The timing for surgical intervention lacks consensus, but malnutrition and perioperative complications should be considered. High AFP levels with an infantile hepatic mass may indicate a more malignant process but does not exclude HMH.

A 46-year-old patient with previously documented Ebola virus persistence in his ocular fluid, associated with severe panuveitis, developed a visually significant cataract. A multidisciplinary approach was taken to prevent and control infection. Ebola virus persistence was assessed before and during the operation to provide safe, vision-restorative phacoemulsification surgery.

The Stratospheric Aerosol and Gas Experiment III (SAGE III) on the International Space Station (ISS) is widely accepted as a stable source for high-quality stratospheric ozone, aerosol, and water vapor measurements since it was installed on the ISS in 2017. The ISS is a unique platform that provides access for hosted payloads while furnishing infrastructure for power, uplink, downlink, etc. for instrument operations. The opportunities, risks, and challenges from operating on the ISS are described in addition to comprehensive lessons learned. In addition, SAGE IV is presented as an option for the future of the SAGE lineage where the lessons learned from SAGE III and technological advances have enabled the instrument to fit into a 6U CubeSat yielding a significantly smaller and cheaper form-factor to preserve the continuity of critical atmospheric measurements.

The variational principle of quantum mechanics is the backbone of hybrid quantum computing for a range of applications. However, as the problem size grows, quantum logic errors and the effect of barren plateaus overwhelm the quality of the results. There is now a clear focus on strategies that require fewer quantum circuit steps and are robust to device errors. Here we present an approach in which problem complexity is transferred to dynamic quantities computed on the quantum processor – Hamiltonian moments, $\langle H^n\rangle$. From these quantum computed moments, an estimate of the ground-state energy can be obtained using the ``infimum'' theorem from Lanczos cumulant expansions which manifestly corrects the associated variational calculation. With higher order effects in Hilbert space generated via the moments, the burden on the trial-state quantum circuit depth is eased. The method is introduced and demonstrated on 2D quantum magnetism models on lattices up to $5\times 5$ (25 qubits) implemented on IBM Quantum superconducting qubit devices. Moments were quantum computed to fourth order with respect to a parameterised antiferromagnetic trial-state. A comprehensive comparison with benchmark variational calculations was performed, including over an ensemble of random coupling instances. The results showed that the infimum estimate consistently outperformed the benchmark variational approach for the same trial-state. These initial investigations suggest that the quantum computed moments approach has a high degree of stability against trial-state variation, quantum gate errors and shot noise, all of which bodes well for further investigation and applications of the approach.

We detail techniques to optimise high-level classical simulations of Shor's quantum factoring algorithm. Chief among these is to examine the entangling properties of the circuit and to effectively map it across the one-dimensional structure of a matrix product state. Compared to previous approaches whose space requirements depend on $r$, the solution to the underlying order-finding problem of Shor's algorithm, our approach depends on its factors. We performed a matrix product state simulation of a 60-qubit instance of Shor's algorithm that would otherwise be infeasible to complete without an optimised entanglement mapping.