Realizing a deep reinforcement learning agent discovering real-time feedback control strategies for a quantum system

To realize the full potential of quantum technologies, finding good strategies to control quantum information processing devices in real time becomes increasingly important. Usually these strategies require a precise understanding of the device itself, which is generally not available. Model-free reinforcement learning circumvents this need by discovering control strategies from scratch without relying on an accurate description of the quantum system. Furthermore, important tasks like state preparation, gate teleportation and error correction need feedback at time scales much shorter than the coherence time, which for superconducting circuits is in the microsecond range. Developing and training a deep reinforcement learning agent able to operate in this real-time feedback regime has been an open challenge. Here, we have implemented such an agent in the form of a latency-optimized deep neural network on a field-programmable gate array (FPGA). We demonstrate its use to efficiently initialize a superconducting qubit into a target state. To train the agent, we use model-free reinforcement learning that is based solely on measurement data. We study the agent’s performance for strong and weak measurements, and for three-level readout, and compare with simple strategies based on thresholding. This demonstration motivates further research towards adoption of reinforcement learning for real-time feedback control of quantum devices and more generally any physical system requiring learnable low-latency feedback control

Photoproduction of pi0 omega off protons for E(gamma) < 3 GeV

Differential and total cross-sections for photoproduction of gamma proton to proton pi0 omega and gamma proton to Delta+ omega were determined from measurements of the CB-ELSA experiment, performed at the electron accelerator ELSA in Bonn. The measurements covered the photon energy range from the production threshold up to 3GeV.Comment: 8 pages, 13 figure

Learning Control of Quantum Systems

This paper provides a brief introduction to learning control of quantum systems. In particular, the following aspects are outlined, including gradient-based learning for optimal control of quantum systems, evolutionary computation for learning control of quantum systems, learning-based quantum robust control, and reinforcement learning for quantum control.Comment: 9 page

Neutral pion photoproduction off protons in the energy range 0.3 GeV < E(gamma) < 3 GeV

Single pi0 photoproduction has been studied with the CB-ELSA experiment at Bonn using tagged photon energies between 0.3 and 3.0 GeV. The experimental setup covers a very large solid angle of about 98% of 4 pi. Differential cross sections (d sigma)/(d Omega) have been measured. Complicated structures in the angular distributions indicate a variety of different resonances being produced in the s channel intermediate state gamma p --> N* (Delta*) --> p pi0. A combined analysis including the data presented in this letter along with other data sets reveals contributions from known resonances and evidence for a new resonance N(2070)D15.Comment: LaTeX file, 4 pages, 4 encapsulated postscript figures, submitted to Phys. Rev. Lett. The publication of hep-ex/0407022 is accompanied by hep-ex/0311045 on photoproduction of eta mesons. Reference [3]: changed, reference [17]: citation added. Figure 3, 4: SAID added up to 2 GeV for comparison, update

Photoproduction of eta mesons off protons for photon energies from 0.75 GeV to 3 GeV

Total and differential cross sections for the reaction p(gamma, eta)p have been measured for photon energies in the range from 750 MeV to 3 GeV. The low-energy data are dominated by the S11 wave which has two poles in the energy region below 2 GeV. Eleven nucleon resonances are observed in their decay into p eta. At medium energies we find evidence for a new resonance N(2070)D15 with (mass, width) = (2068+-22, 295+-40) MeV. At photon energies above 1.5 GeV, a strong peak in forward direction develops, signalling the exchange of vector mesons in the t channel.Comment: LaTeX, 4 pages including 4 eps-figures, submitted to Phys. Rev. Lett. The publication of hep-ex/0311045 is accompanied by hep-ex/0407022 on photoproduction of neutral pions, submitted to Phys. Rev. Lett. Fits published in the latest version are based on additional data, new beam asymmetry data from GRAAL are included, for instance. The data demanded more resonant contributions which were studied in detail. PWA reference adde

N* and Delta* decays into N pi0 pi0

Decays of baryon resonances in the second and the third resonance region into N pi0 pi0 are studied by photoproduction of two neutral pions off protons. Partial decay widths of N* and Delta* resonances decaying into Delta(1232) pi, N(\pi\pi)_{S}, N(1440)P_{11} pi, and N(1520)D_{13} pi are determined in a partial wave analysis of this data, and data from other reactions. Several partial decay widths were not known before. Interesting decay patterns are observed which are not even qualitatively reproduced by quark model calculations. In the second resonance region, decays into Delta(1232) pi dominate clearly. The N(\pi\pi)_{S}-wave provides a significant contribution to the cross section, especially in the third resonance region. The P_{13}(1720) properties found here are at clear variance to PDG values.Comment: 13 pages, 4 figures, long author's lis

<em>Pseudomonas campi </em>sp. Nov., a nitrate-reducing bacterium isolated from grassland soil.

A novel strain was isolated from grassland soil that has the potential to assimilate ammonium by the reduction of nitrate in the presence of oxygen. Whole genome sequence analysis revealed the presence of an assimilatory cytoplasmic nitrate reductase gene nasA and the assimilatory nitrite reductase genes nirBD which are involved in the sequential reduction of nitrate to nitrite and further to ammonium, respectively. Phylogenetic analysis based on 16S rRNA gene sequences revealed that the isolate represents a member of the genus Pseudomonas. The closest phylogenetic neighbours based on 16S rRNA gene sequence analysis are the type strains of Pseudomonas peli (98.17%) and Pseudomonas guineae (98.03%). In contrast, phylogenomic analysis revealed a close relationship to Pseudomonas alcaligenes. Computation of the average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) with the closest phylogenetic neighbours of S1-A32-2 revealed genetic differences at the species level, which were further substantiated by differences in several physiological characteristics. On the basis of these results, it was concluded that the soil isolate represents a novel species of the genus Pseudomonas, for which the name Pseu-domonas campi sp. nov. (type strain S1-A32-2 =LMG 31521 =DSM 110222 ) is proposed. T T T

Effect of the nursing mother on the gut microbiome of the offspring during early mouse development.

The development of the gut microbiome is influenced by several factors. It is acquired during and after birth and involves both maternal and environmental factors as well as the genetic disposition of the offspring. However, it is unclear if the microbiome development is directly triggered by the mode of delivery and very early contact with the mother or mostly at later stages of initial development mainly by breast milk provided by the mother. To investigate to what extent the gut microbiome composition of the offspring is determined by the nursing mother, providing breast milk, compared to the birth mother during early development, a cross-fostering experiment involving two genetically different mouse lines was developed, being prone to be obese or lean, respectively. The microbiome of the colon was analyzed by high-throughput 16S rRNA gene sequencing, when the mice were 3&nbsp;weeks old. The nursing mother affected both α- and β-diversity of the offspring’s gut microbiome and shaped its composition. Especially bacterial families directly transferred by breast milk, like Streptococcaceae, or families which are strongly influenced by the quality of the breast milk like Rikenellaceae, showed a strong response. The core microbiome transferred from the obese nursing mother showed a higher robustness in comparison to the microbiome transferred from the lean nursing mother. Overall, the nursing mother impacts the gut microbial composition of the offspring during early development and might play an important role for health and disease of the animals at later stages of life