Quantum vs classical genetic algorithms: A numerical comparison shows faster convergence

Genetic algorithms are heuristic optimization techniques inspired by Darwinian evolution. Quantum computation is a new computational paradigm which exploits quantum resources to speed up information processing tasks. Therefore, it is sensible to explore the potential enhancement in the performance of genetic algorithms by introducing quantum degrees of freedom. Along this line, a modular quantum genetic algorithm has recently been proposed, with individuals encoded in independent registers comprising exchangeable quantum subroutines [arXiv:2203.15039], which leads to different variants. Here, we perform a numerical comparison among quantum and classical genetic algorithms, which was missed in previous literature. In order to isolate the effect of the quantum resources in the performance, the classical variants have been selected to resemble the fundamental characteristics of the quantum genetic algorithms. Under these conditions, we encode an optimization problem in a two-qubit Hamiltonian and face the problem of finding its ground state. A numerical analysis based on a sample of 200 random cases shows that some quantum variants outperform all classical ones in convergence speed towards a near-to-optimal result. Additionally, we have considered a diagonal Hamiltonian and the Hamiltonian of the hydrogen molecule to complete the analysis with two relevant use-cases. If this advantage holds for larger systems, quantum genetic algorithms would provide a new tool to address optimization problems with quantum computers.Comment: 7 pages, 4 figures, submitted to the IEEE Symposium Series On Computational Intelligence 202

Quantum Genetic Algorithm with Individuals in Multiple Registers

Genetic algorithms are heuristic optimization techniques inspired by Darwinian evolution, which are characterized by successfully finding robust solutions for optimization problems. Here, we propose a subroutine-based quantum genetic algorithm with individuals codified in independent registers. This distinctive codification allows our proposal to depict all the fundamental elements characterizing genetic algorithms, i.e. population-based search with selection of many individuals, crossover, and mutation. Our subroutine-based construction permits us to consider several variants of the algorithm. For instance, we firstly analyze the performance of two different quantum cloning machines, a key component of the crossover subroutine. Indeed, we study two paradigmatic examples, namely, the biomimetic cloning of quantum observables and the Bu\v zek-Hillery universal quantum cloning machine, observing a faster average convergence of the former, but better final populations of the latter. Additionally, we analyzed the effect of introducing a mutation subroutine, concluding a minor impact on the average performance. Furthermore, we introduce a quantum channel analysis to prove the exponential convergence of our algorithm and even predict its convergence-ratio. This tool could be extended to formally prove results on the convergence of general non-unitary iteration-based algorithms

Gesteme-free context-aware adaptation of robot behavior in human–robot cooperation

Background: Cooperative robotics is receiving greater acceptance because the typical advantages provided by manipulators are combined with an intuitive usage. In particular, hands-on robotics may benefit from the adaptation of the assistant behavior with respect to the activity currently performed by the user. A fast and reliable classification of human activities is required, as well as strategies to smoothly modify the control of the manipulator. In this scenario, gesteme-based motion classification is inadequate because it needs the observation of a wide signal percentage and the definition of a rich vocabulary. Objective: In this work, a system able to recognize the user's current activity without a vocabulary of gestemes, and to accordingly adapt the manipulator's dynamic behavior is presented. Methods and material: An underlying stochastic model fits variations in the user's guidance forces and the resulting trajectories of the manipulator's end-effector with a set of Gaussian distribution. The high-level switching between these distributions is captured with hidden Markov models. The dynamic of the KUKA light-weight robot, a torque-controlled manipulator, is modified with respect to the classified activity using sigmoidal-shaped functions. The presented system is validated over a pool of 12 naive users in a scenario that addresses surgical targeting tasks on soft tissue. The robot's assistance is adapted in order to obtain a stiff behavior during activities that require critical accuracy constraint, and higher compliance during wide movements. Both the ability to provide the correct classification at each moment (sample accuracy) and the capability of correctly identify the correct sequence of activity (sequence accuracy) were evaluated. Results: The proposed classifier is fast and accurate in all the experiments conducted (80% sample accuracy after the observation of similar to 450 ms of signal). Moreover, the ability of recognize the correct sequence of activities, without unwanted transitions is guaranteed (sequence accuracy similar to 90% when computed far away from user desired transitions). Finally, the proposed activity-based adaptation of the robot's dynamic does not lead to a not smooth behavior (high smoothness, i.e. normalized jerk score <0.01). Conclusion: The provided system is able to dynamic assist the operator during cooperation in the presented scenario

Ultrafast beam research at the PEGASUS laboratory

The PEGASUS laboratory at the UCLA Physics Department has been recently commissioned as a new advanced photoinjector facility for ultrafast beam research. With a newly installed state-of-the-art Ti:Sa laser driver capable of delivering sub 100 fs UV pulses onto the cathode, the laboratory capabilities have been greatly expanded. The beam charge is low (10 pC) to avoid excessive pulse lengthening. Nevertheless various applications could greatly benefit by this novel regime of operation of an rf photoinjector. We discuss the measurements performed to characterize the system with particular attention to the ones that are peculiar of a low charge sub-ps beam

Safety and Feasibility of Transperineal Targeted Microwave Ablation for Low- to Intermediate-risk Prostate Cancer

BACKGROUND: Focal therapy has emerged as an interesting option for localized low- to intermediate-risk prostate cancer (PCa). Targeted microwave ablation (TMA) is a novel FT modality involving targeted delivery of microwave energy under multiparametric magnetic resonance imaging (MRI)/ultrasound guidance. OBJECTIVE: To describe the step-by-step procedure for TMA and report early functional outcomes. DESIGN, SETTING, AND PARTICIPANTS: This was an experimental phase 1–2 trial in 11 patients diagnosed with a single, MRI-visible PCa lesion of up to 12 mm, scored as International Society of Urological Pathology grade group (GG) 1 or 2. SURGICAL PROCEDURE: Transperineal TMA under MRI/ultrasound image fusion guidance. MEASUREMENTS: We recorded patient and PCa features; intraoperative and postoperative parameters; pain (Visual Analog Scale [VAS]) and adverse events (Common Terminology Criteria for Adverse Events v5.0); and prostate-specific antigen (PSA), International Prostate Symptom Score (IPSS) and International Index of Erectile Function (IIEF-5) scores at 1 wk and 1, 3, and 6 mo. RESULTS AND LIMITATIONS: The median patient age was 67 yr (interquartile range [IQR] 18). Median PSA was 5.4 ng/ml (IQR 1.8), median prostate volume was 51 cm(3) (IQR 35), and median lesion size on MRI was 10 mm (IQR 4). Ten patients had GG 2 PCa and one had GG 1 disease. The median procedure time was 40 min (IQR 30). No intraoperative complications were reported. All treatments were performed on a day-case basis and no patients were discharged with a urinary catheter. Postoperatively, no grade ≥2 complications were reported. No significant changes in PSA (p = 0.46), IPSS (p = 0.39), or IIEF-5 scores (p = 0.18) scores were reported. The postoperative VAS score at 24 h was 0 for all patients. CONCLUSIONS: TMA is safe, feasible, and well tolerated in patients with low- to intermediate-risk PCa. Oncological outcomes are still awaited. PATIENT SUMMARY: Targeted microwave therapy is safe and feasible for selected patients with low- to intermediate-risk prostate cancer. The procedure is well tolerated and does not require a urinary catheter after the procedure. Cancer control outcomes are still awaited

Characterisation and Modelling of Ultrashort Laser-Driven Electromagnetic Pulses

Recent advances on laser technology have enabled the generation of ultrashort (fs) high power (PW) laser systems. For such large scale laser facilities there is an imperative demand for high repetition rate operation in symbiosis with beamlines or end-stations. In such extreme conditions the generation of electromagnetic pulses (EMP) during high intense laser target interaction experiments can tip the scale for the good outcome of the campaign. The EMP effects are several including interference with diagnostic devices and actuators as well as damage of electrical components. The EMP issue is quite known in the picosecond (ps) pulse laser experiments but no systematic study on EMP issues at multi-Joule fs-class lasers has been conducted thus far. In this paper we report the first experimental campaign for EMP-measurements performed at the 200 TW laser system (VEGA 2) at CLPU laser center. EMP pulse energy has been measured as a function of the laser intensity and energy together with other relevant quantities such as (i) the charge of the laser-driven protons and their maximum energy, as well as (ii) the X-ray K-alpha emission coming from electron interaction inside the target. Analysis of experimental results demonstrate (and confirm) a direct correlation between the measured EMP pulse energy and the laser parameters such as laser intensity and laser energy in the ultrashort pulse duration regime. Numerical FEM (Finite Element Method) simulations of the EMP generated by the target holder system have been performed and the simulations results are shown to be in good agreement with the experimental ones

Action observation and motor imagery in performance of complex movements: Evidence from EEG and kinematics analysis

Motor imagery (MI) and action observation (AO) are considered effective cognitive tools for motor learning, but little work directly compared their cortical activation correlate in relation with subsequent performance. We compared AO and MI in promoting early learning of a complex four-limb, hand?foot coordination task, using electroencephalographic (EEG) and kinematic analysis. Thirty healthy subjects were randomly assigned into three groups to perform a training period in which AO watched a video of the task, MI had to imagine it, and Control (C) was involved in a distracting computation task. Subjects were then asked to actually perform the motor task with kinematic measurement of error time with respect to the correct motor performance. EEG was recorded during baseline, training and task execution, with task-related power (TRPow) calculation for sensorimotor (alpha and beta) rhythms reactive with respect to rest. During training, the AO group had a stronger alpha desynchronization than the MI and C over frontocentral and bilateral parietal areas. However, during task execution, AO group had greater beta synchronization over bilateral parietal regions than MI and C groups. This beta synchrony furthermore demonstrated the strongest association with kinematic errors, which was also significantly lower in AO than in MI. These data suggest that sensorimotor activation elicited by action observation enhanced motor learning according to motor performance, corresponding to a more efficient activation of cortical resources during task execution. Action observation may be more effective than motor imagery in promoting early learning of a new complex coordination task