Ultrafast measurements using x-ray free-electron lasers

X-ray free-electron lasers (XFELs) are unique tools for ultrafast science, allowing one to generate tunable pairs of few-fs x-ray pulses with photon energies between ~10 eV and ~10 keV. XFEL machines are however much larger and much more complex than table-top optical lasers, spanning from several hundreds of metres in length up to a few kilometres. This increased size and complexity makes them very prone to fluctuations and single-shot jitter in the parameters of the generated x-ray pulses such as photon energy, intensity and time delay, of up to ~1%, ~100% and ~15 fs, respectively. Using data from different experiments carried out at the Linac Coherent Light Source (LCLS) and the SPring-8 Angstrom Compact Free Electron Laser (SACLA), the author will show examples of the influence that these fluctuations can have on the experimental signals, proposing solutions to separate this influence from actual meaningful experimental results. The thesis starts with a brief introduction to x-ray science and the working principles of XFELs followed by an extensive description of the common configurations that allow generating pairs of pulses for time-resolved experiments. The first experimental results are then presented for two successful experiments measuring nuclear dynamics in the 10-100 fs timescales in the acetylene and C60 molecules. While successful, these experiments already show the effects of the fluctuations, effects that, as shown in the following chapter, are amplified when attempting to use few-fs pulses to measure few-fs dynamics. Although the presence of the fluctuations may be unavoidable, this thesis shows, using data from three additional ultrafast experiments, that the fluctuations can be circumvented by performing a full single-shot characterization of all x-ray pulses and implementing sophisticated data analysis techniques to sort the experimental data. Finally, having exposed the importance of single-shot x-ray characterization, the author proposes and demonstrates a technique based on machine learning to enable such full x-ray characterization at the next generation of high-repetition-rate XFELs.Open Acces

Proposal for an Advanced Structural Elective Pertaining to Fire Protection

ARCE 401 Fire Protection is a class that will finally give ARCE students an introduction to fire-resilience and its major importance in the structural and planning spheres. The class would have a structural emphasis along with interdisciplinary qualities, unlike the graduate classes offered in the CE and ME departments. ARCE 401 covers a broad spectrum of topics and is meant to bring ARCE students closer to a comprehensive understanding of the overall work environment

CompILE: Compositional Imitation Learning and Execution

We introduce Compositional Imitation Learning and Execution (CompILE): a framework for learning reusable, variable-length segments of hierarchically-structured behavior from demonstration data. CompILE uses a novel unsupervised, fully-differentiable sequence segmentation module to learn latent encodings of sequential data that can be re-composed and executed to perform new tasks. Once trained, our model generalizes to sequences of longer length and from environment instances not seen during training. We evaluate CompILE in a challenging 2D multi-task environment and a continuous control task, and show that it can find correct task boundaries and event encodings in an unsupervised manner. Latent codes and associated behavior policies discovered by CompILE can be used by a hierarchical agent, where the high-level policy selects actions in the latent code space, and the low-level, task-specific policies are simply the learned decoders. We found that our CompILE-based agent could learn given only sparse rewards, where agents without task-specific policies struggle.Comment: ICML (2019

Patients with Schizophrenia Showed Worse Cognitive Performance than Bipolar and Major Depressive Disorder in a Sample with Comorbid Substance Use Disorders

Comorbidity of substance use disorders (SUD) and severe mental illness (SMI) is highly frequent in patients, the most common diagnoses being schizophrenia (SZ), bipolar disorder (BD) and major depressive disorder (MDD). Since comorbidity has its own clinical features, and neurocognitive functioning is not always similar to psychiatric symptoms the present study explores the cognitive performance of patients with dual disorders. A neuropsychological battery of tests was used to assess 120 under treatment male patients, 40 for each group considered (SZ + SUD, BD + SUD and MDD + SUD) who were mainly polyconsumers. Significant differences (with premorbid IQ as a covariate) were found among the groups, with SZ + SUD having a worse performance in attention, verbal learning, short term memory and recognition. The consideration of a global Z score for performance evidenced an impaired neurocognitive pattern for SZ + SUD compared with BD + SUD and MDD + SUD. According to norms, all patients showed difficulties in verbal learning, short-term memory and recognition. Our research indicated that the neurocognitive functioning of dual disorder patients was influenced by the comorbid SMI, with SZ + SUD presenting major difficulties. Future studies should thoroughly explore the role of such difficulties as indicators or endophenotypes for dual schizophrenia disorders, and their usefulness for prevention and treatment.This research was funded by the grant PID2020-117767GB-I00 of Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033) and the Generalitat de Catalunya (2017SGR-748). Partial funding for open access charge: Universidad de Málag