Xanadu is a Canadian quantum computing company with the mission to build quantum computers that are useful and available to people everywhere. Xanadu is one of the world’s leading quantum hardware and software companies and also leads the development of PennyLane, an open-source software library for quantum computing and application development.

This talk begins with the problem of pricing American basket options in a multivariate setting. In high dimensions, nonlinear PDE methods for solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation become expensive due to the curse of dimensionality.

The risk of security breaches is now higher than ever, and attackers routinely break into corporate networks, government services, and even critical infrastructures. As a result, it is not a matter of `if' a system will be compromised, but only a matter of `when' -- thus making the way we handle computer incidents and investigations of paramount importance.

This seminar will articulate the growth, and fabrication methodologies employed, discuss the device characterization under high-temperature conditions, and extrapolate on the far-reaching implications of these advancements for the realm of electronics designed to operate under extreme environmental conditions.

Abstract

The COVID-19 pandemic produced excess mortality in many countr

Simulation tools capable of transient electromagnetic analysis are essential for designing and optimizing electromagnetic, photonic, and optoelectronic devices. In recent years, time-domain differential equation based solvers have found widespread use due to their advantages over integral equation counterparts in analyzing transient electromagnetic field/wave interactions and multiphysics problems. This dissertation develops a group of time-domain differential equation solvers for analyzing transient electromagnetic scattering from penetrable objects and multiphysics phenomena in optoelectronic devices. In addition to providing detailed formulations of these solvers, this dissertation presents numerical examples which demonstrate their accuracy, efficiency, and applicability to real-life problems.

The Euler equation does not possess a unique solution for the flow over a two-dimensional object. This problem has serious repercussions in aerodynamics; it implies that the inviscid aero-hydrodynamic lift force over a two-dimensional object cannot be determined from first principles; a closure condition must be provided. The Kutta condition has been ubiquitously considered for such closure in the literature, even in cases where it is not applicable (e.g. unsteady).

The field of molecular chemistry has witnessed a remarkable transformation with the integration of deep generative models. Exploring the intricate interplay between machine learning techniques and molecular generation, paving the way for novel advancements in drug discovery, materials science, and beyond.

Numerical software is being reinvented to provide opportunities to tune dynamically the accuracy of computation to the requirements of the application, resulting in savings of memory, time, and energy. Floating point computation in science and engineering has a history of “oversolving” relative to expectations for many models. So often are real datatypes defaulted to double precision that GPUs did not gain wide acceptance until they provided in hardware operations not required in their original domain of graphics. However, computational science is now reverting to employ lower precision arithmetic where possible. Many matrix operations considered at a blockwise level allow for lower precision and many blocks can be approximated with low rank near equivalents.

III-Nitride materials have continuously attracted the attention of semiconductor researchers for the last decades. III-Nitrides are considered a key material for a wide range of applications, such as power electronics and color displays, and have proven to be suitable as an efficient light source. This work provides a multi-directional approach for realizing efficient InGaN Light-Emitting Diodes (LEDs).

We will explore a novel process flow in the usage of laser scanning for existing buildings to support sustainability-led design by a new scan-to-BIM process, materials identification through hyperspectral imaging, environmental schemes, and materials embodied energy whole lifecycle assessments.

During this talk, we shall deep dive into the neutral atoms quantum machine of PASQAL to learn what makes such a machine tick. Following along the full stack approach of Pasqal, we will focus on how such a computer can be used to address hard combinatorial problems, machine learning-related tasks, as well as quantum simulation-based problems present in all walks of life.

Spatial data analysis commonly needs to deal with spatial data derived from multiple sources (e.g. satellites, stations, survey samples) with different supports, but associated with the same properties of a spatial phenomenon under interest. Usually, predictors are also measured on different spatial supports than the response variable.

Quantinuum is the world’s largest integrated quantum computing company. Quantinuum has developed the H-Series quantum computers based on a trapped-ion architecture using the unique and highly-scalable QCCD architecture (QCCD = Quantum Charge-Coupled Device), and released its first two generations: the System Model H1 and H2. The H-Series QPUs are well-known for their superior, low noise performance and differentiating capabilities such as all-to-all connectivity and mid-circuit measurement with very low qubit cross talk.  Dr. Brian Neyenhuis will discuss how the QCCD architecture enables these differentiators and what researchers can do with the H-Series quantum computers that they cannot do on other commercially available quantum computers.  As a full stack quantum computing company, Quantinuum also makes TKET, an open source SDK compiler and optimizer, as well as algorithm and application layers for applications in Machine Learning, Finance, Chemistry, and modeling of Quantum Systems.  Anand Shah will review the application and algorithm activities at Quantinuum.

In this talk we propose and validate a Space Multiscale model for the description of particle diffusion in the presence of trapping boundaries. We start from a drift diffusion equation in which the drift term describes the effect of bubble traps, and it is simulated by the Lennard–Jones potential.

The increasing popularity of machine learning models in real-world automated and decision support systems has underscored the need for assessing and then mitigating biases that may manifest, often spuriously, in their predictions either at the population, sub-population, or individual level. These biases can be assessed in terms of calibration, performance stratification, fairness metrics, prediction interval coverages, etc., and are mainly due to poor model specification (e.g., overparameterization without regularization or loss/likelihood mismatch) or data collection issues (e.g., population misrepresentation or unmeasured confounders).

During the last decade, the demand for wireless connection over the world has tremendously increased, including the areas where unconnected. Raising with topics like "Breaking down the data divide," "Connect to unconnected," etc. In the sixth-generation wireless network, the underwater world attracts a lot of attention. Besides that, the huge unexplored resource is another driving force for underwater exploration. Unlike the well-developed Internet of Things (IoT) on the terrestrial, there is almost no underwater wireless communication network, not to mention the underwater IoT.

Keeping in mind the current proliferation of smartphones as a popular hand-held gadget (with adequate sensing and computational capabilities), we propose to use smartphones as a health diagnostic tool for do-it-yourself (DIY) monitoring of one’s own health.

Highly coherent light, although beneficial in specific applications, suffers from the formation of speckles, resulting in poor imaging, lighting, and projection/display quality. Moreover, the long coherence length limits the resolution in interference based sensing. The aim of this dissertation is to design low-coherence surface-emitting lasers to push simultaneous illumination and optical wireless communication (OWC) toward reliable implementation with higher speeds.

Security and privacy systems are often composed of complex components and details. However, users’ experience shouldn’t be as complex. In this seminar, Eman will discuss the human factor in the security and privacy chain. While human privacy perceptions and behaviors have been investigated in Western societies, little is known about these issues in non-Western societies.

Abstract

The goal of the least squares method is to find the best linea

The degenerate Cahn-Hilliard equation, initially introduced in material science, is nowadays used in several different fields, including biology (tumor growth, cell-cell adhesion) and fluid dynamics (high-friction limit in the Euler-Korteweg equation).

Heterogeneous permeability, porosity, capillary pressure, and strength are key characteristics of sedimentary and volcanic rocks in geologic reservoirs. In many cases, the heterogeneity is due to nested geological features like the mm-scale coarse-fine intercalations of cross-bedded sandstones, or the km-scale channel, levy, and overbank facies associations in a fluvial environment of deposition. Where such rocks have experienced an overprint by deformation or reactive fluid flow, initial heterogeneities might be amplified even further: fracturing can impart long-range spatial correlations on the permeability structure, strongly amplifying permeability anisotropy, even in the absence of a noticeable increase of porosity.

In this talk, we will show how, through a large scale Internet measurement campaign, we have been able to experimentally validate a novel technique to automatically detect malicious webscrapers bots taking advantage of so called Residential IP proxy providers. That technique has then been deployed in a real world environment and enabled us, thanks to a novel geolocalization technique, to identify malicious actors hiding behind these infrastructures, leading to actionable threat intelligence for the victims.

In this talk, we will go over the various projects in the lab and discuss the challenges faced by lab members and the opportunities that exist.