Polynomial scaling of the quantum approximate optimization algorithm for ground-state preparation of the fully connected p -spin ferromagnet in a transverse field

We show that the quantum approximate optimization algorithm (QAOA) can construct, with polynomially scaling resources, the ground state of the fully connected p-spin Ising ferromagnet, a problem that notoriously poses severe difficulties to a vanilla quantum annealing (QA) approach due to the exponentially small gaps encountered at first-order phase transition for p≥3. For a target ground state at arbitrary transverse field, we find that an appropriate QAOA parameter initialization is necessary to achieve good performance of the algorithm when the number of variational parameters 2P is much smaller than the system size N because of the large number of suboptimal local minima. Instead, when P exceeds a critical value PN∗N, the structure of the parameter space simplifies, as all minima become degenerate. This allows achieving the ground state with perfect fidelity with a number of parameters scaling extensively with N and with resources scaling polynomially with N

Reinforcement-learning-assisted quantum optimization

We propose a reinforcement learning (RL) scheme for feedback quantum control within the quantum approximate optimization algorithm (QAOA). We reformulate the QAOA variational minimization as a learning task, where an RL agent chooses the control parameters for the unitaries, given partial information on the system. Such an RL scheme finds a policy converging to the optimal adiabatic solution of the quantum Ising chain that can also be successfully transferred between systems with different sizes, even in the presence of disorder. This allows for immediate experimental verification of our proposal on more complicated models: The RL agent is trained on a small control system, simulated on classical hardware, and then tested on a larger physical sample

Ion cyclotron wall conditioning experiments on Tore Supra in presence of the toroidal magnetic field

Wall conditioning techniques applicable in the presence of the high toroidal magnetic field will be required for the operation of ITER for tritium removal, isotopic ratio control and recovery to normal operation after disruptions. Recently ion cyclotron wall conditioning (ICWC) experiments have been carried out on Tore Supra in order to assess the efficiency of this technique in ITER relevant conditions. The ICRF discharges were operated in He/H-2 Mixtures at the Tore Supra nominal field (3.8 T) and a RF frequency of 48 MHz, i.e. within the ITER operational space. RF pulses of 60 s (max.) were applied using a standard Tore Supra two-strap resonant double loop antenna in ICWC mode, operated either in pi or 0-phasing with a noticeable improvement of the RF coupling in the latter case. In order to assess the efficiency of the technique for the control of isotopic ratio the wall was first preloaded using a D-2 glow discharge. After 15 minutes of ICWC in He/H-2 gas mixtures the isotopic ratio was altered from 4% to 50% at the price of an important H implantation into the walls. An overall analysis comparing plasma production and the conditioning efficiency as a function of discharge parameters is given

The half-life of 221^{221}Fr in Si and Au at 4K and at mK temperatures

The half-life of the $\alpha$ decaying nucleus $^{221}$Fr was determined in different environments, i.e. embedded in Si at 4 K, and embedded in Au at 4 K and about 20 mK. No differences in half-life for these different conditions were observed within 0.1%. Furthermore, we quote a new value for the absolute half-life of $^{221}$Fr of t$_{1/2}$ = 286.1(10) s, which is of comparable precision to the most precise value available in literature

Enabling emergency flow prioritization in SDN networks

Emergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software-Defined Networking (SDN) principles allow to assign different Quality-of-Service (QoS) levels to different network slices.This paper proposes an SDN-based solution, executable both offline and online, that guarantees the required bandwidth for the emergency flows and maximizes the best-effort flows over the remaining bandwidth based on their priority. The offline model allows to optimize the problem for a batch of flow requests, but is computationally expensive, especially the variant where flows can be split up over parallel paths. For practical, dynamic situations, an online approach is proposed that periodically recalculates the optimal solution for all requested flows, while using shortest path routing and a greedy heuristic for bandwidth allocation for the intermediate flows.Afterwards, the offline approaches are evaluated through simulations while the online approach is validated through physical experiments with SDN switches, both in a scenario with 500 best-effort and 50 emergency flows. The results show that the offline algorithm is able to guarantee the resource allocation for the emergency flows while optimizing the best-effort flows with a sub-second execution time. As a proof-of-concept, a physical setup with Zodiac switches effectively validates the feasibility of the online approach in a realistic setup

Quantifying maternal investment in mammals using allometry

Maternal investment influences the survival and reproduction of both mothers and their progeny and plays a crucial role in understanding individuals’ life-history and population ecology. To reveal the complex mechanisms associated with reproduction and investment, it is necessary to examine variations in maternal investment across species. Comparisons across species call for a standardised method to quantify maternal investment, which remained to be developed. This paper addresses this limitation by introducing the maternal investment metric – MI – for mammalian species, established through the allometric scaling of the litter mass at weaning age by the adult mass and investment duration (i.e. gestation + lactation duration) of a species. Using a database encompassing hundreds of mammalian species, we show that the metric is not highly sensitive to the regression method used to fit the allometric relationship or to the proxy used for adult body mass. The comparison of the maternal investment metric between mammalian subclasses and orders reveals strong differences across taxa. For example, our metric confirms that Eutheria have a higher maternal investment than Metatheria. We discuss how further research could use the maternal investment metric as a valuable tool to understand variation in reproductive strategies

Unexpected borderline malignant and malignant smooth muscle cell tumors of the uterine corpus in women treated with LH-RH analogues

In this report, two cases of uterine smooth muscle cell tumors, one of uncertain malignant potential and one clearly malignant, are described in women treated for prolonged periods with luteinizing hormone-releasing hormone (LH-RH) analogues. Due to lengthy monitoring of LH-RH therapy, surgical intervention and histologic classification of these tumors was late in the course of disease, resulting in a delay in definite treatment. The risk to these women is discussed. The effects of LH-RH analogue therapy on fibroids is reviewed. Suggestions are put forward for monitoring LH-RH analogue therapy

On routing scalability in flat SDN architectures

The rigidity of traditional network architectures, with tightly coupled control and data planes, impair their ability to adapt to the dynamic requirements of future application domains, such as the Tactile Internet or Holographic-Type Communications. Software-Defined Networking (SDN) architectures, which provide programmability to configure the network, have the potential to provide the required dynamism. However, given its centralized essence, SDN suffers from scalability issues. Therefore, efforts have been made to propose alternative decentralized solutions, such as the flat distributed SDN architecture. Despite its potential, the real applicability and scalability of decentralized SDN solutions are still open research questions. This paper presents a comparative analysis of the effects of different routing approaches on the scalability of flat distributed SDN architectures. Using the Open Network Operating System (ONOS) as our evaluation architecture, we have studied the tradeoff between routing overhead in the control data plane and inter-controller communications for different degrees of decentralization. We have found that routing applications, which only require control-data plane communication for setting the path, benefit more from decentralization than the ones which utilize inter-controller communications and ensure Quality of Service (QoS). Our findings highlight the need for efficient routing mechanisms to deal with inter-controller overhead while lowering the amount of control-data plane communication

Physiological stress and spatio-temporal fluctuations of food abundance and population density in Eurasian red squirrels

In continuously changing environments, variation of different ecological factors could affect the functioning of the hypothalamic-pituitary-adrenal (HPA) axis in wild mammals, increasing the secretion of glucocorticoids (GCs). In different animal species, GC concentrations are often used as a measure of the physiological stress response to environmental pressures, such as fluctuations in food abundance, population density, intra-and interspecific competition, and predation risk. However, previous studies reported contrasting results or did not find clear associations between physiological stress and environmental variables. Here, we used concentrations of faecal glucocorticoid metabolites (FGMs) as an integrated measure of physiological stress in wild Eurasian red squirrels (Sciurus vulgaris) from three study areas in the Italian Alps, to investigate whether variations in conifer-seed crop size and/or population density affected HPA axis activity. Squirrel density was estimated in each trapping session using the minimum number of animals alive, and annual counts of fresh cones from different conifer species were used to estimate annual food abundance (MJ/ha). We expected higher FGMs in response to increasing population density and/or decreasing food abundance, since these two variables could act as environmental stressors. Our results showed a lack of association between population density and FGMs and a significant effect of food abundance on FGMs. When conifer seed-crops were poor to moderate, FGMs increased with food abundance, while in the range of high seed-crops, FGMs remained first constant and then slightly decreased with a further increase in seed abundance. We also found differences in FGMs among seasons, as previously observed in this species. Our study adds further evidence that physiological stress can be influenced in different ways by environmental pressures and that long-term studies using individually marked animals are needed to disentangle the potential adaptive outcome of the physiological stress response in pulsed resource systems