Browsing by Author "Jackel, Brian"
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- ItemOpen AccessCharacterizing Energetic Electron Precipitation and Whistler-mode Waves during Electron Injection Events(2022-01) Ghaffari, Reihaneh; Cully, Christopher M; Jackel, Brian; Spanswick, Emma Louise; Gomes da Rocha, Claudia; Jaynes, Allison NMagnetically trapped particles in the magnetosphere can be lost and precipitate into the atmosphere. Precipitated particles deposit energy into the atmosphere and affect the atmospheric chemistry and ionization in the ionosphere. The change in the ionospheric charge density can disturb telecommunication on the Earth. The precipitated particles can also alter the density of substantial atmospheric components such as HOx and NOx which are critical catalysts in ozone destruction. Therefore, studying the causes and effects of energetic particle precipitation has great importance. One type of geomagnetic event that is associated with energetic particle precipitation is a substorm injection. Energetic electron precipitation associated with substorm injections typically occurs when magnetospheric waves, particularly whistler-mode waves, resonantly interact with electrons to affect their pitch angle and scatter particles into the loss cone through a diffusion process. In this thesis, I describe two studies about electron precipitation through wave-particle interactions during substorm injection events. The first study aims to quantitatively characterize energetic electron precipitations during injection events in the magnetosphere. This part uses in-situ measurements by the Van Allen Probes and presents the typical substorm-induced precipitation flux as 4×〖10〗^6 el/cm2.s.sr. The precipitation flux is estimated from characterizing the ground signatures of precipitated electrons on radio signal propagation in the ionosphere. The second study aims to investigate the physical drivers of electron precipitation during injections. This part investigates whistler-mode wave generation in conjunction with electron injections using in-situ wave measurements by the Time History of Events and Macroscale Interactions during Substorms (THEMIS) mission. This study indicates that only 5% of the injection events are associated with an order of magnitude wave power enhancement. Investigating diffusion rates due to the generated waves during the selected events states that strong scattering is not typically associated with injection events in the magnetosphere.
- ItemOpen AccessLaser Cooling of Antihydrogen(2022-01) Evans, Andrew; Thompson, Robert; Jackel, Brian; Ouyed, Rachid; Moazzen-Ahmadi, Nasser; Lassen, JensAntihydrogen, the simplest atomic antimatter system, is an excellent platform to search for matter- antimatter asymmetries. The kinetic energy (and thus velocity) of synthesized antihydrogen trapped in the laboratory setting is very large relative to the energy well depth of the trap providing the confining force. Accuracy of any measurements performed on trapped antihydrogen, and the complexity of future experiments, is sensitive to the kinetic energy of the sample. There are a variety of techniques used in atomic physics experiments to decrease a sample’s temperature, but the additional constraints of working with trapped antimatter made laser cooling the most promising choice. I demonstrate the ability to modify the kinetic energy distribution of a trapped sample of antihydrogen using the 1S-2Pf transition in antihydrogen using a vacuum ultraviolet (VUV) laser system (i.e. laser cooling). The change in kinetic energy is observed using a time-of-flight analysis from a pulsed laser spectroscopy run as well as a narrowing of the 1S-2S line shape. Using the centre frequencies of the 1S- 2S and 1S-2P transitions we can also determine a value for the Lamb shift in antihydrogen. I will detail these results as well as my individual contributions toward this achievement of the ALPHA collaboration. In this thesis I observed an increase in both the 1S-2S, 1S-2P, and time of flight when the laser cooling transition was applied, when compared to control and laser heating runs. Using the trap depth of the neutral atom trap confining the antihydrogen sample, I estimate the temperature of the laser cooled sample to be approximately 31mK, an order of magnitude decrease. This will be demonstrated through changes in transition linewidths, both the 1S-2P and 1S-2S transition, as well as increases in time-of- flight data.
- ItemOpen AccessMachine Learning for Designing Fast Quantum Gates(2016-01-26) Zahedinejad, Ehsan; Sanders, Barry C.; Salahub, Dennis; Far, Behrouz H.; Hobill, David; Jackel, Brian; Bose, SougatoFault-tolerant quantum computing requires encoding the quantum information into logical qubits and performing the quantum information processing in a code-space. Quantum error correction codes, then, can be employed to diagnose and remove the possible errors in the quantum information, thereby avoiding the loss of information. Although a series of single- and two-qubit gates can be employed to construct a quantum error correcting circuit, however this decomposition approach is not practically desirable because it leads to circuits with long operation times. An alternative approach to designing a fast quantum circuit is to design quantum gates that act on a multi-qubit gate. Here I devise quantum control schemes to design high-fidelity single-shot multi-qubit (up to three) quantum gates. Quantum control task is to steer quantum dynamics towards closely realizing specific quantum operation by varying the external control parameters (external field) such that the resultant evolution closely approximates the desired evolution. A set of instructions that determines the control parameters, and hence the effectiveness of the control scheme, is called a policy. Machine learning algorithms can be employed to find successful policies for designing quantum gates. In particular, we employ supervised machine learning techniques to generate these successful policies. Finding successful policies is a feasibility problem for which optimization algorithms can be employed. Greedy algorithms are at the heart of machine learning techniques. They converge faster onto a successful policy and require less-computational resource than non-greedy algorithms. However, there is no guarantee that greedy algorithms succeed to a feasible solution when there exist constraints on i) gate operation time ii) computational resources, and iii) experimental resources. Our results show the failure of standard greedy machine learning algorithms and the superiority of non-greedy machine learning algorithms over greedy ones for designing quantum logic gates, when there exist constraints on the quantum system. We have also observed the failure of existing greedy and non-greedy techniques for designing high-fidelity three-qubit gates. Hence, we devised our machine learning technique called Subspace-Selective Self-adaptive Differential Evolution (SuSSADE). Each three-qubit gate designed by SuSSADE operates as fast as an entangling two-qubit gate under the same experimental constraints.
- ItemOpen AccessMid Infrared Investigation of Two Isomers of the CO-N2O van der Waals Complex(2017) Barclay, Aaron; Moazzen-Ahmadi, Nasser; Heyne, Belinda Josiane M.; Thompson, Robert Ian; Jackel, BrianInfrared spectra in the carbon monoxide CO stretch region (~2150 cm−1) and in the nu3 asymmetric stretch region of N2O (~2223 cm−1) are assigned to the previously unobserved O-bonded form of the CO-N2O dimer (“isomer 2”). This van der Waals complex has a planar skewed T-shaped structure like that of the previously observed C-bonded form (“isomer 1”), but with the CO rotated by 180°. In addition to the fundamental band, combination bands for both isomers are observed and intermolecular frequencies for the out of plane torsion and the in-plane CO-rock, or disrotatory bend are reported. Vibrational assignment of these bands is achieved by comparison with data recently published (A. Barclay et al., Chem. Phys. Letters, 651 (2016) 62), concerning OC-CO2. We show that the most recent ab initio potential energy surface is inadequate in predicting the intermolecular frequencies for both isomers (CO-N2O and OC-N2O).
- ItemOpen AccessModeling Complex Systems as Dynamical Networks(2016) Martin, Elliot Asher; Davidsen, Jörn; Jackel, Brian; Feder, DavidThis thesis is devoted to the study of complex systems as dynamical networks. Complex systems typically have many interacting components with non-trivial dynamics, and often have a natural network representation. Examples of such networks are abundant, from the world wide web and power plants, to gene regulation and the human brain. However, often we can not observe these networks themselves, but can only passively observe the dynamics of their nodes. For example, neural activity is often available but not the connections between neurons. This motivated researchers to attempt to infer networks from observations of systems’ dynamics. These efforts resulted in the application of network methods to systems whose underlying structure is not intuitively described by a network, e.g., Earth’s climate. Therefore, it is important that the appropriateness and robustness of these analyses are critically analyzed — the focus of the bulk of this thesis. Recent work has outlined a way to assess how much information about a system can be captured by pairwise relationships — from which these networks are generally constructed. As most commonly formulated however, the method is based on cross-correlations, and therefore only sensitive to linear relationships. We extend this by using mutual informations, which are sensitive to a wide range of nonlinear relationships undetectable by the cross-correlation. We illustrate the advantages of our method using phase oscillators and fMRI data. Our method also allows a novel method for network inference, letting us estimate the conditional mutual informations between all pairs of variables when given their mutual informations. When applied to phase oscillator networks, this has resulted in superior results than using the mutual information alone. I also address the robustness of dynamical networks. We show that contrary to previous results, networks formed during El Niño periods have more connectivity than during “normal” periods, where the discrepancy is a result of the original analysis mixing different climate regimes. Finally, we address the question of inferring time delays for constructing dynamical networks. We show that a common technique is biased towards large time lags, and suggest an alternative estimator that does not suffer from this bias.
- ItemUnknownMonitoring Energetic Electron Precipitation Using a Ground-based Radio Array(2016) Davis, Eric; Cully, Christopher; Jackel, Brian; Brown, Jo-Anne; Sesay, AbuThe Van Allen radiation belts are regions of trapped energetic particles in near-Earth space. Radiation belt loss mechanisms into the atmosphere are still not well quantified, a process known as electron precipitation. This thesis describes a method for monitoring energetic electron precipitation using the ground-based Array for Broadband Observations of Very low frequency/extremely low frequency Emissions (ABOVE). A signal processing algorithm is described to calculate the relative time delay and power of a signal travelling hundreds to thousands of kilometers from transmitter to receiver. Instrument response is shown to be consistent with the literature for energetic electron precipitation. Instrumental uncertainty is evaluated, revealing a random instrument uncertainty substantially less than electron precipitation signatures. The method is applied to two case studies. The flux, energy, and location of energetic electron precipitation are inferred in both studies, and the use of ABOVE for monitoring energetic electron precipitation is validated.
- ItemOpen AccessA network neuroscience approach to Developmental Topographical Disorientation(2022-08-31) Faryadras, Mahsa; Davidsen, Joern; Iaria, Giuseppe; Towlson, Emma; Jackel, BrianDespite a decade-long study on Developmental Topographical Disorientation (DTD), the underlying mechanism behind this neurological condition remains unknown. This lifelong selective inability in orientation, which causes these individuals to get lost even in familiar surroundings, is present in the absence of any other neurological disorder or acquired brain damage. Herein, we report an analysis of the functional brain network of individuals with DTD (n = 19) compared against that of healthy controls (n = 21), all of whom underwent resting state fMRI, to identify if and how their underlying functional brain network is altered. While the established resting state networks are confirmed in both groups, there is on average a greater connectivity and connectivity strength, in addition to increased global and local efficiency in the overall functional network of the DTD group. In particular, there is an enhanced connectivity between some resting state networks facilitated through indirect functional paths. We identify a handful of nodes that encode part of these differences. Overall, our findings provide strong evidence that the brain networks of individuals suffering from DTD are modified by compensatory mechanisms, which might open the door for new diagnostic tools.
- ItemOpen AccessOrientation of solar wind dynamic pressure phase fronts(American Geophysical Union, 2013-02) Jackel, Brian; Cameron, Taylor; Weygand, James M.
- ItemOpen AccessPhotonic approaches to multi-party entanglement in solids and learning in the brain(2021-08-06) Zarkeshian, Parisa; Simon, Christoph; Barzanjeh, Shabir; Oblak, Daniel; Craddock, Travis; Jackel, BrianUnderstanding the fundamental quantum and classical properties of photons is crucial in a wide range of applications. Photons exhibit quantum entanglement, the strongest form of correlation that has been observed between subsystems. Entanglement is perhaps the most valuable resource for many quantum information and quantum computation tasks, empowering them to be superior to their classical counterparts. Undoubtedly, understanding how entanglement can be generated, manipulated, and measured are among the most pre-eminent research questions in quantum information processing. However, the realm of influence of photons is not just limited to information technologies. Photons are, surprisingly, being produced constantly in biological systems as well. Modeling and characterizing the involvement of photons in various biological processes are active areas of research. In the first part of my Ph.D. program, I focused on the problem of quantifying multi-partite entanglement in a solid, an atomic frequency comb (AFC) crystal, using a single photon. We proposed a novel entanglement witness and showed that our witness is well suited for demonstrating and quantifying multi-partite entanglement in AFC systems. Our results are the first demonstration of multi-partite entanglement in a solid between over two hundred ensembles each containing a billion atoms. The second project of my Ph.D. was motivated by the question of why brain cells are producing biophotons. Photons are known as perfect carriers for information. The brain is the computation centre where all the learning and decision makings are happening. Learning, in theory, is an informational task, and its biological realization in the brain is not completely understood. We asked if photons could play a role in the process of learning in the brain. A common form of learning involves multiple cycles of training, evaluating, and receiving feedback. Both forward and backward parts of these cycles require an information flow. Existing theories mainly focus on neural electrochemical signals. We proposed that biophotons can propagate the feedback teaching signals required for learning in the brain. By multiple numerical experiments simulated on an artificial neural network, we demonstrated that stochastic emissions of biophotons carrying partial backward information enable learning in the network.
- ItemOpen AccessThe Magnetic Field in the Galactic Disk from Extended Emission Rotation Measures(2016-01-05) Ordog, Anna; Brown, Jo-Anne; Landecker, Thomas; Jackel, BrianI present my analysis of the extended emission (XE) polarisation data from the Canadian Galactic Plane Survey. I used this dataset to determine Rotation Measures (RMs) with the aim of studying the Galactic magnetic field (GMF) structure. I have shown that RMs of the XE do contain useful information, despite predicted difficulties with this kind of dataset. I have found evidence that the large-scale field reversal between the local arm and the Sagittarius arm is not strictly perpendicular to the Galactic plane as previously thought, but has some component within the Galactic disk. This geometry lends credibility to a model of the GMF similar to the Parker spiral Solar magnetic field, an idea proposed in 1982 but rejected shortly thereafter on the grounds of incompatibility with observations available at the time. I have created a Galactic scale version of this model of the magnetic field, constrained by the XE RMs.
- ItemOpen AccessTime Dependence of the RXTE X-ray Spectrum of Hercules X-1/HZ Hercules(2016) Abdallah, Mohammed Hassan; Leahy, Denis Alan; Jackel, Brian; Stil, Jeroen; Ouyed, RachidWe study the time dependence of the energy spectra (i.e. of the spectral model parameters, and the interpretation) of the X-ray binary system Hercules X-1/HZ Hercules (Her X-1/HZ Her) over the superorbital/35-day cycle. The results are discussed separately in two parts: one for the data during the main high state and one for the data obtained during low state and short high state. We made use of data collected by RXTE/PCA instrument in the standard-2 mode during the period from July,1996 to August of 2005 (MJD = 50290 - 53584) acquired as a result of 23 study proposals for observing the HZ Her/Her X-1 system. Observations made while the system was in anomalous low state (ALS) were removed, as the ALS are believed to be caused by a change in the status of the disc which results in disappearance of the 35-day superorbital cycle. In our data there are two anomalous low states (MJD = 51226.4 to 51756.9 & MJD = 52950.6 to 53159.4). Due to the rapid change of count rates and energy spectra during eclipse and dips periods, we remove these periods from our analysis. The main results during main high state are directly linked to the disc precession and its effect in occulting the central source and surrounding emission regions, while results obtained for the low state and short high state are related to the changing visibility of the irradiated face of HZ Her which contributes to the observed spectra by the reflected emission off of its heated face.
- ItemOpen AccessUsing the Motion of Patchy Pulsating Aurora to Remote Sense Magnetospheric Convection(2017) Yang, Bing; Donovan, Eric; Millan, Robyn; Knudsen, David; Jackel, Brian; Behjat, LalehMagnetospheric convection is the main process of transport, energization and injection of energetic particles into the magnetosphere, and plays an important role in all dynamics in the Earth’s magnetosphere. It can be directly measured through in-situ ion/electron drift measurements or electric field measurements from satellites in the magnetosphere, and can also be remotely sensed by the in-situ ion drift velocity from satellites in the top ionosphere and ground-based radar measurements. Satellites either in the top ionosphere or magnetosphere can give accurate measurements of convection, but there is always the problem of separating spatial from temporal variation. Ground-based radar measurements either are often absent from the region of interests or have small field of view. In this thesis, I will develop a new technique – the motion of patchy pulsating aurora (PPA) – to remotely sense the magnetospheric convection. In a series of three papers, I will present a detailed demonstration of the equivalence of patch velocities and E × B convection, a statistical study of the motion of PPA and a case in which we use the motion of PPA to investigate the magnetospheric convection. These studies are great evidence showing that patch motion is a proxy for convection and an interesting complement to other convection measurements.