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Model bias is an inherent limitation of the current dominant approach to optimal quantum control, which relies on a system simulation for optimization of control policies. To overcome this limitation, we propose a circuit-based approach for training a reinforcement learning agent on quantum control tasks in a model-free way. Given a continuously parametrized control circuit, the agent learns its parameters through trial-and-error interaction with the quantum system, using measurement outcomes as the only source of information about the quantum state. Focusing on control of a harmonic oscillator coupled to an ancilla qubit, we show how to reward the learning agent with measurements of experimentally available observables. We train the agent to prepare various nonclassical states via both unitary control and control with adaptive measurement-based quantum feedback, and to execute logical gates on encoded qubits. The agent does not rely on averaging for state tomography or fidelity estimation, and significantly outperforms widely used model-free methods in terms of sample efficiency. Our numerical work is of immediate relevance to superconducting circuits and trapped ions platforms where such training can be implemented in experiment, allowing complete elimination of model bias and the adaptation of quantum control policies to the specific system in which they are deployed.

The ambition of harnessing the quantum for computation is at odds with the fundamental phenomenon of decoherence. The purpose of quantum error correction (QEC) is to counteract the natural tendency of a complex system to decohere. This cooperative process, which requires participation of multiple quantum and classical components, creates a special type of dissipation that removes the entropy caused by the errors faster than the rate at which these errors corrupt the stored quantum information. Previous experimental attempts to engineer such a process 1 – 7 faced the generation of an excessive number of errors that overwhelmed the error-correcting capability of the process itself. Whether it is practically possible to utilize QEC for extending quantum coherence thus remains an open question. Here we answer it by demonstrating a fully stabilized and error-corrected logical qubit whose quantum coherence is substantially longer than that of all the imperfect quantum components involved in the QEC process, beating the best of them with a coherence gain of G  = 2.27 ± 0.07. We achieve this performance by combining innovations in several domains including the fabrication of superconducting quantum circuits and model-free reinforcement learning. A study demonstrates the extension of a lifetime of a quantum memory using active quantum error correction and reinforcement learning.

Sharing information coherently between nodes of a quantum network is fundamental to distributed quantum information processing. In this scheme, the computation is divided into subroutines and performed on several smaller quantum registers that are connected by classical and quantum channels 1 . A direct quantum channel, which connects nodes deterministically rather than probabilistically, achieves larger entanglement rates between nodes and is advantageous for distributed fault-tolerant quantum computation 2 . Here we implement deterministic state-transfer and entanglement protocols between two superconducting qubits fabricated on separate chips. Superconducting circuits 3 constitute a universal quantum node 4 that is capable of sending, receiving, storing and processing quantum information 5 – 8 . Our implementation is based on an all-microwave cavity-assisted Raman process 9 , which entangles or transfers the qubit state of a transmon-type artificial atom 10 with a time-symmetric itinerant single photon. We transfer qubit states by absorbing these itinerant photons at the receiving node, with a probability of 98.1 ± 0.1 per cent, achieving a transfer-process fidelity of 80.02 ± 0.07 per cent for a protocol duration of only 180 nanoseconds. We also prepare remote entanglement on demand with a fidelity as high as 78.9 ± 0.1 per cent at a rate of 50 kilohertz. Our results are in excellent agreement with numerical simulations based on a master-equation description of the system. This deterministic protocol has the potential to be used for quantum computing distributed across different nodes of a cryogenic network. Deterministic quantum state transfer and entanglement generation is demonstrated between superconducting qubits on distant chips using single photons.

We retrospectively reviewed 49 patients with light chain (LC) Fanconi syndrome (FS). Patients presented with chronic kidney disease (median estimated glomerular filtration rate (eGFR) of 33 ml/min/1.73 m 2 ) and tubular proteinuria. All patients tested had elevated fractional excretion of phosphate, uric acid, generalized aminoaciduria and/or normoglycemic glycosuria. Thirty-eight patients had monoclonal gammopathy of renal significance and eleven patients had an overt hematological malignancy. The monoclonal LC isotype was kappa in 46/49 cases. Kidney biopsy in 39 patients showed various proximal tubular lesions and characteristic LC intracytoplasmic crystalline inclusions in 24 patients. Forty-two patients received chemotherapy. Patients with plasma cell proliferation ( n =38) received bortezomib-based regimens ( n =11), immunomodulatory agents ( n =7) or alkylating agents ( n =6). High-dose melphalan (HDM) followed by autologous stem cell transplantation was performed in 14 patients. Hematological response was obtained in 90% of evaluable patients, assessed on serum free light chains (FLC). GFR remained stable as long as hematological response was maintained and declined when serum FLC level rebounded. Improvement in proximal tubule function occurred in 13 patients. In patients with LC-associated FS, chemotherapy using HDM and/or new generation anti-myeloma agents can stabilize renal function and improve proximal tubule function. Serum FLC should be used to assess the hematological response, related to renal outcome.

Background Infusion of high-dose intravenous methotrexate (MTX) has been demonstrating to penetrate the blood-brain barrier. The aim of this present study was to assess the efficacy and safety of high dose MTX in patients with central nervous system (CNS) metastases of breast cancer. Methods Twenty-two patients with CNS metastases treated by MTX (3 g/m2) between April 2004 and October 2009 were enrolled. Clinical response rate, time to progression (TTP), overall survival (OS), and safety were assessed. Results In terms of brain metastases, 2 patients (9%) achieved a partial response, 10 patients (45%) had disease stabilization, and 10 patients (45%) had disease progression. In others metastatic sites, 7 patients (39%) achieved a disease stabilization, and 11 patients (61%) had disease progression. TTP and OS were 2.1 (95%CI 1.4–2.9) and 6.3 (95%CI 1.8–10) months, respectively. Conclusion High-dose MTX demonstrated a moderate activity at 3 g/m 2 . Nonetheless, the favorable toxicity profile should suggest the possibility to increase the dosage and further study are planned.

Background This study evaluated the impact of time to surgery (TTS) on overall survival (OS), disease free survival (DFS) and postoperative complication rate in patients with upfront resected pancreatic adenocarcinoma (PA). Methods We retrospectively included patients who underwent upfront surgery for PA between January 1, 2004 and December 31, 2014 from four French centers. TTS was defined as the number of days between the date of the first consultation in specialist care and the date of surgery. DFS for a 14-day TTS was the primary endpoint. We also analyzed survival depending on different delay cut-offs (7, 14, 28, 60 and 75 days). Results A total of 168 patients were included. 59 patients (35%) underwent an upfront surgery within 14 days. Patients in the higher delay group (> 14 days) had significantly more vein resections and endoscopic biliary drainage. Adjusted OS (p = 0.44), DFS (p = 0.99), fistulas (p = 0.41), hemorrhage (p = 0.59) and severe post-operative complications (p = 0.82) were not different according to TTS (> 14 days). Other delay cut-offs had no impact on OS or DFS. Discussion TTS seems to have no impact on OS, DFS and 90-day postoperative morbidity.

Purpose Everolimus has demonstrated its efficacy in metastatic renal cell carcinoma (mRCC). Preliminary studies have shown high variability of everolimus blood concentrations (EBC). In other settings, its activity was correlated with EBC. We therefore decided to monitor EBC in patients treated with mRCC to assess its influence on oncologic outcomes. Patients and methods Our study analyzed first 3 months’ trough EBC levels in 42 patients treated in 4 French oncologic centers between March 2010 and August 2013. Patients presented a histologically confirmed diagnosis of mRCC and have failed prior anti-angiogenic (AA) therapies. Results Median follow-up was 25.9 months. A total of 113 EBC were analyzed. The median trough concentration was 14.1 μg/L (range 2.6–91.5). Fourteen patients (67 %) versus 8 (38 %) patients with median EBC above or below 14.1 μg/L were free from progression at 6 months ( p  = 0.06). Median progression-free survival was 13.3 versus 3.9 months (HR 0.66 95 % CI 0.33–1.31; p  = 0.23), and the median overall survival was 26.2 versus 9.9 months (HR 0.62 95 % CI 0.28–1.37; p  = 0.24), for patients above or below the median value of trough concentrations, respectively. Conclusion Impact of drug exposure for AA tyrosine kinase inhibitors activity has been demonstrated in mRCC setting. Interpatients EBC variability was confirmed in the present study, and the results suggest a relationship between initial EBC within the first 3 months and the drug activity. It underlines the need to prospectively include EBC monitoring in future clinical trials to determine the need of its implementation in routine use.

Background: HuHMFG1 (AS1402) is a humanised monoclonal antibody that has undergone a phase I trial in metastatic breast cancer. The aim of this study was to characterise the pharmacokinetics (PKs) of HuHMFG1 using a population PK model. Method: Data were derived from a phase I study of 26 patients receiving HuHMFG1 at doses ranging from 1 to 16 mg kg −1 . Data were analysed using NONMEM software and covariates were included. A limited sampling strategy (LSS) was developed using training and a validation data set. Results: A linear two-compartment model was shown to be adequate to describe data. Covariate analysis indicated that weight was not related to clearance. An LSS was successfully developed on the basis of the model, in which one sample is collected immediately before the start of an infusion and the second is taken at the end of infusion. Conclusion: A two-compartment population PK model successfully describes HuHMFG1 behaviour. The model suggests using a fixed dose of HuHMFG1, which would simplify dosing. The model could be used to optimise dose level and dosing schedule if more data on the correlation between exposure and efficacy become available from future studies. The derived LSS could optimise further PK assessment of this antibody.