2026 Invited Speakers

When one considers measurements in any specialty, it is easy to focus only of one or two key units, whether it is kilogram and second for particle physics, or the coulomb and kelvin for condensed matter studies. But taking into account everything that goes into an experiment: from sample preparation to the dependencies of the measurement method, it becomes apparent that the complete SI (base and derived units) is likely represented:

second – controlling experimental acquisition times, determining particle velocities;

metre – positioning of equipment, characterizing optical path lengths;

ampere – power requirements, HV supplies, measurement of single electrons in quantum devices;

kelvin – environmental considerations, cryogenics, thermodynamics;

kilogram – weight limits for laboratory design, sample preparation;

mole – chemical analysis (even physicists have to do a little chemistry!);

candela – luminance characteristics of imaging displays and light sources.

This presentation will explore the history of international metrology and how it impacts measurements today. It will describe the activities of the Metrology Research Centre at the NRC – Canada’s National Metrology Institute – and how it is adapting to new challenges facing science, technology, and society in Canada as we move into the next 150 years of the Metre Convention.

Firstly, HDR CIS concepts will be reviewed including control of direct sunlight and bright headlamps. Light flicker mitigation (LFM) and motion artifact compensation requirements will be contrasted with typical HDR CIS design tradeoffs related to secondary sub-pixels (~500 nm pitch) and/or short exposures (<0.1 ms).

Secondly, SPAD arrays for use in direct time-of-flight (dToF) light detection and ranging (LiDAR) will be described. Both short-range (< 50 m) flash LiDAR and long-range (100 m to 300 m) scanning LiDAR approaches will be discussed.
Finally, novel SPAD-based HDR stop-motion sensors with capabilities for both imaging and depth sensing will be presented.

Nevertheless, even when an experiment is deep underground, there are still backgrounds present at levels which can hinder experimental searches for neutrino interactions or the search for dark matter. These backgrounds can include high-energy cosmic ray muons which pass through the rock overburden that then interact with the experiment or rock nearby the experiment, and the detector environment itself, which can include the radioactivity naturally emitted from the surrounding rock and the materials used to construct the experiment. Since many of these backgrounds may be present in the underground environment and the experimental materials themselves, it is highly desirable to measure these backgrounds and to determine the effort required to reduce them further to meet the desired scientific goals of the experiments.

This presentation will describe SNOLAB’s low-background material screening facilities and background measurement capabilities which can be used to directly measure these radioactive backgrounds and to search for new low-background materials which can be used for future detector fabrication.

The SoLID GPD program is ambitious, including Deeply Virtual Compton Scattering (DVCS) and Deep Exclusive Meson Production (DEMP) with polarized targets, as well as Double DVCS (DDVCS) and Timelike Compton Scattering (TCS) at high luminosity. Together, these will provide a variety of GPD data that are unlikely to be obtained from any other facility. An overview of the proposed GPD program with SoLID will be presented.

Recently, the signatures of a predicted exotic isoscalar, η1 has been reported by the BESIII collaboration in the radiative decay of J/ψ → η1γ → ηη′γ. The production of a two pseudoscalar system, ηη′, is also allowed in the photon-induced interaction γp → ηη′p and can be reconstructed with the GlueX spectrom- eter, giving us an excellent opportunity to validate η1’s existence. An analysis of this two-meson system based on a statistics-limited GlueX data set did not provide a conclusive result.

Recently, the data set has been increased by a factor of 2-3, which will facilitate this search. Preliminary studies for this channel will be presented.

In this talk, I will highlight scientific themes within I.ANN QCD, including high-density gluon dynamics and ultraperipheral collisions as clean photon-induced probes connected to the future Electron–Ion Collider program. I will also discuss how advances in AI, quantum science, computing, and next-generation detector and accelerator technologies, together with industry partnerships, are creating shared challenges and opportunities across physics, with QCD both driving and benefiting from this broader transformation at the heart of matter.

In this talk, I will discuss how we can distinguish between different scenarios by constraining the nuclear physics uncertainties, particularly the (α,n) reaction rates in the weak r-process, and comparing nucleosynthesis models to the abundance patterns observed in limited-r stars. I will discuss current experimental campaigns aimed at measuring key (α,n) reaction rates, and and how new, high-quality spectroscopic data from limited-r stars will provide essential constraints for the next generation of astrophysical models.

The TITAN (TRIUMF’s Ion Trap for Atomic and Nuclear science) facility is committed to conducting high-precision and fast mass measurements. Over the past several measurement campaigns, the masses of numerous nuclides located across the nuclear chart have been measured. Most campaigns have utilized a fast, time-of-flight technique using a Multi-Reflection Time-of-flight Mass Spectrometer (MR-TOF-MS). The measured masses have been used to constrain calculations and probe nuclear structure effects.

In addition to the MR-TOF-MS, use of the TITAN Penning trap has allowed higher precision in mass measurements to be achieved. A new cryogenic cooling system has been installed at the TITAN Penning trap, to achieve ultra-high vacuum conditions (~ 10^-11 mbar), and facilitate trapping of ions over longer periods of time (≥1 s), as well as measurements of highly charged ions formed in the TITAN Electron Beam Ion Trap. The cryogenic trap was commissioned with a measurement campaign to probe beta (β) decay in ⁴⁸CA and refine β decay calculations. A final upgrade to the trap is currently being implemented, changing from a time-of-flight to a phase-based determination of the cyclotron frequency and therefore the mass. This is expected to push the limit of achievable mass precision to below 10^-10 level, making it possible to conduct measurements probing fundamental symmetries, tests of the Standard Model and beyond. Results from mass measurements of neutron-rich nuclides using the MR-TOF-MS, and the cryogenic Penning trap commissioning will be presented, along with a summary of the implemented and ongoing upgrades.

One ARIEL station will receive a driver beam of 500 MeV protons, up to 100 μA from TRIUMF’s H- cyclotron. The other ARIEL station will utilize an electron beam from the new superconducting linear accelerator, with energy up to 35 MeV and up to 100 kW beam power. The addition of these two ISOL targets enables the delivery of three simultaneous RIB beams to different experiments, while concurrently producing radioisotopes for medical applications.

This contribution will describe the target station and its completion status, and will highlight the recent qualification tests that have been performed on its core components in our offline facility. The predicted beam intensities from the additional two stations will be presented, highlighting the main strengths and weaknesses of this combined facility. Moreover, the current status of the ARIEL facilities will be discussed, along with the roadmap their completion and ramp-up.

Moving beyond the light elements, neutron captures are crucial processes to create elements heavier than iron on the opposite side of the nuclear chart. The specific neutron density at which neutron capture processes operate in their corresponding astrophysical sites is the primary determinant of their unique nucleosynthesis paths and resulting abundance patterns. The rapid neutron capture process (r-process) occurring in explosive events such as neutron star mergers with extremely abundant free neutron supplies is traditionally held responsible for the enrichment of actinides, in particular Thorium and Uranium.

However, recent research suggested a possibility of synthesizing these actinides through the intermediate neutron capture process (i-process) in AGB stars with neutron densities many orders of magnitude lower than those required for the r-process. This possibility could fundamentally change our understanding of galactic chemical evolution. To explore the viability of this alternative scenario, we employed the PRISM code to simulate nucleosynthesis across a range of neutron injection strengths and timescales.

We will conclude this talk by comparing specific nucleosynthetic examples where actinides are successfully forged against those where they are once created but depleted by subsequent nuclear reactions, identifying the conditions for i-process actinide survival.

In this talk, I will present an overview of the BIC concept, which integrates a high-resolution scintillating-fiber–lead sampling calorimeter with low-power AstroPix monolithic active pixel sensors for imaging. I will summarize the physics-driven design choices, the expected performance based on simulation studies benchmarked to EIC requirements, and the current status of component integration and testing. Highlights from recent beam tests will be shown, along with an outlook on the development roadmap for this critical subsystem of the ePIC detector.

Experimental validation of these decays can allow us to understand their complex nuclear-structure effects, any quenching of the weak axial-vector coupling, their prominence as a background for rare-event searches and their relevance for 0νββ experiments. However, although the long half-life makes these isotopes interesting, it also makes them very challenging to measure.

This presentation will detail the motivation behind measuring these isotopes as well as go over recent experimental efforts to measure these decays, including: the RadioActive isotope Measurement Program at SNOLAB (RAMPS), KDK+ and LUtetium sCintillation Experiment (LUCE).

For charged antimatter particles, gravitational forces are dwarfed by electromagnetic effects, making such measurements impractical. Antihydrogen—the electrically neutral bound state of an antiproton and a positron—overcomes this limitation and can be routinely produced, trapped, and studied by the ALPHA collaboration at CERN.

While ALPHA was originally designed for precision laser spectroscopy of antihydrogen, the dedicated vertical apparatus ALPHA-g was commissioned to enable measurements of gravitational effects.

In this talk, I will present the first experimental observation of the influence of gravity on antihydrogen atoms, together with a detailed discussion of systematic studies of the magnetic field based on electron-cyclotron-resonance (ECR) magnetometry. These measurements are essential for controlling and characterizing the dominant non-gravitational forces acting on trapped antihydrogen.

I will conclude with an update on the current performance of ALPHA-g and an outlook on future experimental programs aimed at improving the precision of antimatter gravity measurements.

The TRIUMF main cyclotron produces 483 MeV protons, which are directed into a tungsten spallation target. The resulting spallation neutrons are moderated first by room-temperature D2O, then by liquid deuterium (LD2) at 25 K before they reach the production volume, which is filled with $\approx$~28 liquid litres of isopure He4 at nearly 1 K. At this temperature, the superfluid component of the helium (He-II) has a phonon excitation mode that is close in energy to the peak thermal energy of the LD2-moderated neutrons. As the (now) cold neutrons excite this phonon mode in the He-II, they lose almost all their kinetic energy, becoming UCN with kinetic energy < 300 neV. The UCN can then be directed to experimental apparatus via specially coated guides as one would direct a gas.

This presentation will go over the latest results and current status of both the TUCAN source and the nEDM experiment.

To address these challenges, the University of Toronto Department of Physics recently redesigned a first-year physics lab curriculum to emphasize experimental design, uncertainty, and data analysis. Instead of running a different experiment every week, students investigate a single experiment over multiple weeks, with data being collected in the first week and then analyzed it in the second. This new model encourages students to think like a scientist by deciding what data to collect, how to measure it, and how to understand their results.

In this presentation, I will discuss the structure of the revised lab, share key lessons learned from its implementation, and comment on how it will be further improved in future semesters. I will also summarize the general trends from student feedback and reflect on how this new model shaped their understanding of experimentation.

New tools and approaches, such as smartphone-based investigations using Phyphox, are intentionally embedded to promote modelling, approximation, experimental design, and reasoning under uncertainty. Supported by over 80 volunteers, undergraduate and graduate students, faculty, and staff, the Physics Olympics fosters sustained collaboration between physicists, physics educators, and teachers. Notably, many former participants have gone on to become physics students and secondary physics teachers, highlighting the event’s long-term impact on the physics education pipeline and the larger community.

I will share some observations gathered from high school physics teachers. This session serves as an open, yet constructive, forum for educators to share their observations, assumptions and intentions. By examining where our expectations diverge and where our efforts overlap, we will have a necessary conversation about how to better support students and educators navigating this increasingly difficult step.

PHYSICS 1D03/1E03, the first year mechanics and E&M courses for engineering students at McMaster, present a rare opportunity to help close this gap. Prompted by institutional changes, the department has elected to overhaul these courses completely. Rather than a series of small tweaks, we are rebuilding them from the ground up.

While all course components are changing, lectures and labs anchor the redesign. The new lecture structure emphasizes student exploration and collaborative problem solving in real world engineering contexts. Building on the wealth of active-learning research, we are adopting a Productive Failure model that introduces challenging, meaningful problems early to promote deeper sense making and motivate learning. Meanwhile, the lab program is shifting from prescriptive, confirmatory exercises to inquiry based labs that prioritize experimental technique, decision making, and expert-like habits of mind.

This talk will describe the rationale and process behind the overhaul, including consultations with stakeholders, learning-goal mapping, and the development of materials. The redesigned mechanics course will be piloted in May 2026, and we will report preliminary data on student engagement and learning. The emphasis will be on lessons learned in practice: what worked well, what did not, and what questions we still need to answer before full implementation with 1300 students in the Fall 2026 semester.

Today I would like to celebrate his life, and his many innovations in teaching and science communication. I will review a selection of David’s most useful and relevant PER papers, which include investigations into how students read, groupwork in labs, data analysis and uncertainties. I will also share a selection of David’s many online teaching animations and simulations, which I have updated to be accessible on modern devices. The topics covered in these simulations include Mechanics, Chaos, Fluid Mechanics, Electricity and Magnetism, Quantum Mechanics and Relativity.

For introductions and informal education, games provide a way for learners to develop intuition for physical and mathematical concepts by role-playing. We will present an activity that explores the quantum search (Grover’s) algorithm as a player-vs-player board game, where learners role-play as a classical and quantum computer to try to find marked elements as quickly as possible, intended for high-school students and early undergraduates. We will present how the game incorporates fundamental elements of quantum information science like probability, decoherence, quantum error correction, and measurement collapse, how it demonstrates the scaling of the classical and quantum solutions relative to each other, and the limitations of the analogies used in the game.

Feedback from workshops using the game with high-school students, undergraduates, and teachers will be presented. All materials are open-source and possible to print at home, with custom 3D-printed die models available. And yes, we will have copies available to play with.

As introductory physics course enrollment grew over the past decades, large publisher textbooks have been common for both the textbook content, and the online software they provide to facilitate the submission and grading of course assignments (as traditional assignment submissions became unfeasible to grade with typical TA resources). Therefore a barrier to using OER in large introductory physics courses is a matter of both a) the course content and b) the grading resource problem.

In this talk we will discuss the implementation of OER material into multiple large introductory physics courses, and different ways the grading resource problem has been addressed in these courses. We will then discuss preliminary results from a multi-year study on this implementation, for both Science and Engineering large introductory physics courses.

In this talk, I will summarize recent developments and my lab’s work developing and applying such models using numerical simulations of the vasculature and analytical descriptions of the BOLD signal. These have allowed us to extract detailed physiological information, which is quantitative and interpretable, from functional MRI, thereby providing valuable insights into healthy and diseased brain function.

In this presentation, I will lay the foundation for understanding the impact of image guidance on the treatment of cancer with radiation. With a focus on our experience at The Ottawa Hospital Cancer Centre, I will outline how image guidance has enabled advances in treatment delivery techniques. Finally, I will explore how some of these advances in technology and computer science are allowing us to use image information to adapt the radiation dose distribution as a given treatment progresses.

Building on these experimental results, we present a combined theoretical and numerical investigation aimed at identifying the physical mechanism responsible for the acceleration and optimizing its performance. An analytical model for linearly polarized tightly focused ultrashort laser fields reflected by high-NA mirrors is derived and coupled to fully three-dimensional Particle-In-Cell simulations. By varying the laser wavelength (0.8–7 µm) and normalized vector potential (a₀ = 3.6–7.0), we confirm that acceleration is governed by the relativistic ponderomotive force, leading to preferential forward emission. A maximum electron kinetic energy of ≈1.4 MeV is predicted near a central wavelength of 1.8 µm, consistent with experimental results.

We further investigate the influence of polarization and plasma density on acceleration efficiency. In the generated near-critical plasmas, linearly and circularly polarized pulses outperform radially polarized pulses in terms of both maximum energy and total accelerated charge, while linear polarization yields lower divergence beams. Scaling analyses indicate that multi-MeV electrons can be generated with charges above 1 nanocoulomb.

These results establish tightly focused mJ-class lasers as a promising platform for compact, high-repetition-rate multi-MeV electron sources with potential applications in ultrafast imaging and FLASH radiotherapy.

Here, we report on a single-shot longitudinal phase-space reconstruction diagnostic for electron beams in a laser wakefield accelerator via the experimental observation of distinct periodic modulations in the angularly resolved spectra. Such modulated angular spectra arise as a result of the direct interaction between the ultra-relativistic electron beam and the laser driver in the presence of the wakefield. A constrained theoretical model for the coupled oscillator, assisted by a genetic algorithm, was used to recreate the experimental electron spectra and fully reconstruct the longitudinal phase-space distribution of the electron beam with a temporal resolution of ∼1.3 fs. In particular, it revealed the slice energy spread of the electron beam, which is important to measure for applications such as XFELs.

In our experiment, the root-mean-square slice energy spread retrieved is bounded at 9.9 MeV, corresponding to a 0.9-3.0% relative spread, despite the overall GeV energy beam having ∼100% relative energy spread. Particle-in-cell simulations demonstrate that our method also applies for electron beams from traditional accelerators. We show that periodically modulated electron spectra can be induced via either direct laser-electron interaction in vacuum or in a beam-driven plasma wakefield accelerator.

Plasma systems are utilized for nuclear and municipal waste treatment with analysis of different waste categories and types. Process design is discussed for plasma torch that can reduce the volume and lifecycle cost of waste processing. Simulation methods and experimental setups demonstrate lab-scale process technologies for plasma-based waste treatment.

In this work, we present a systematic investigation of Mg acceptor incorporation in GaN grown by PA-MBE under both Ga-rich and N-rich conditions spanning low (~580 °C) and high (~740 °C) temperature regimes. The growth temperature boundary near ~650 °C separates two fundamentally distinct kinetic regimes: in the low-temperature Ga-rich regime, a self-regulated Ga bilayer stabilizes the surface, while at higher temperatures excess Ga rapidly desorbs, eliminating bilayer formation. Although Ga-rich growth has traditionally been favored for achieving high crystalline quality, its influence on Mg incorporation efficiency requires further investigation.

A comprehensive growth map was constructed to correlate Mg incorporation, surface morphology, and electrical properties as a function of III/V ratio and temperature. Secondary ion mass spectroscopy (SIMS) reveals significantly enhanced Mg incorporation efficiency (~80%) under N-rich conditions. In contrast, Ga-rich growth produces smoother surfaces with root-mean-square roughness of ~1–2 nm but exhibits reduced Mg incorporation. Room-temperature Hall measurements confirm tunable hole concentrations ranging from ~7 × 10¹⁷ cm⁻³ (Ga-rich) to ~2 × 10¹⁹ cm⁻³ (N-rich) at fixed Mg flux.These results establish a clear trade-off between surface morphology and Mg incorporation efficiency and provide a practical growth-regime guideline for optimizing p-type GaN.

The findings are directly relevant to nitride-based light emitters, tunnel diodes, quantum emitters, PEC cells, and other advanced electronic and photonic device architectures.

However, there has been no clear evidence that such a model is indeed appropriate in the reconnection diffusion region in terms of the kinetic physics. The present study demonstrates that, using a large-scale 3D kinetic simulation and analytical analysis, the spatial distribution of the non-ideal electric field is consistent with the dissipation due to the viscosity rather than the resistivity, when electromagnetic (EM) turbulence is dominant in the electron diffusion region (EDR).

The effective viscosity is caused by the EM turbulence that is driven by the flow shear instabilities leading to the electron momentum transport across the EDR. The result suggests a fundamental modification of the fluid equations using the resistivity in the Ohm’s law. In contrast, for the 2D current sheet without significant turbulence activity, the non-ideal field profile does not obey the simple form based on the viscosity. A general form of the of non-ideal electric field in 2D and 3D current sheets appropriate for fluid simulations is presented. The second part of the talk will be concerned with the time domain structures (TDS) associated with free energy sources (beams, thermal anisotropy, etc) that arise from the energy conversion process in magnetic reconnection and magnetic flux rope interaction.

The results of both anomalous transport and TDS studies are connected to recent satellite observations (Magnetospheric Multiscale Satellites – MMS) and laboratory magnetized plasma experiments.

However, when plasma transport is governed by turbulence or strong instabilities, merely satisfying these criteria at their margins proves insufficient. In this work, we demonstrate that sub-Debye length refinement of the spatial grid combined with high-order shape functions is essential to capture important physical effects and transport mechanisms that are systematically overlooked when first order shape functions with marginally fulfilled PIC criteria are used instead. This finding represents a paradigm shift in quantitative PIC modelling. To support this claim, we compare two typical cases: (i) electropositive, (ii) electronegative plasmas. For both situations, 1D and 2D simulations have been carried out. Remarkable differences occur in the charged particle transport and especially the micro instabilities.

In the light of these results, the numerical approach used to simulate plasmas is crucial to capture the anomalous transport.

We investigate the power of multipartite entanglement for pseudotelepathy. Some known games that can be won with tripartite entanglement cannot be won with bipartite entanglement, but they can be won with bipartite non-signalling resources such as the so-called Popescu-Rohrlich nonlocal box. We exhibit a five-player game that can be won with tripartite entanglement, but not with arbitrary bipartite non-signalling resources even in the presence of arbitrary five-partite classical resources. This illustrates both the power of bipartite non-signalling resources (over bipartite entanglement) and the even superior power of tripartite entanglement.

Turning to cosmology, we use a simple measure of how “complicated” the tiny patterns of matter and energy become as the Universe expands. During the rapid growth phase of the early Universe, this complexity increases steadily, but in later eras it drops and eventually stops changing. We also find a maximum rate at which this complexity can grow, with the inflationary period reaching that limit. These results show how ideas from information theory can shed light on both black holes and cosmic evolution.

In this talk, I will explore the boundaries of computational advantage in circuit sampling in different regimes, focusing on shallow circuits and the effects of noise. I will describe a sharp transition that occurs as a function of the circuit depth, which separates a classically simulable phase from a putatively complex, non-simulable phase. I will present a precise, statistical description of the quantum states generated by these circuits in the shallow, non-simulable regime, which both accounts for the hardness of classical simulations, and also predicts a dramatic susceptibility to noise.

Based on this structural characterisation of shallow circuit sampling, I will argue that even a very small noise rate – scaling with the system size n as log(n) / n – renders the output distribution classically simulable. This highlights the extreme sensitivity of circuit sampling problems to noise, and sheds light on the complexity of simulating quantum many-body dynamics more generally.

In the first part, I will focus on a single-photon interferometric architecture in which we realise one of the most loophole-tight tests of macrorealism to date. By combining LGI and related No-Signalling-in-Time conditions with careful control of measurement invasiveness, detector inefficiencies, multiphoton contamination and preparation/coincidence loopholes, we obtain a clear and robust violation of macrorealist bounds for a genuinely single system evolving in time.

The second part explains how such temporal correlations can be turned into a resource. By mapping the observed LGI violation to a lower bound on min-entropy, we obtain semi– device-independent guarantees on the unpredictability of the measurement outcomes, and demonstrate LGI-based quantum random number generation in a photonic platform. Finally, I will show how the same temporal-correlation framework can be implemented on contemporary noisy quantum processors, providing a platform-agnostic route to certified randomness.

I will conclude by outlining how these ideas are engineered into QRange, a deployable QRNG module in which “testing reality” via LGI becomes the underlying certificate for high-quality randomness, with applications to cryptography, simulation and AI-oriented workloads.

Despite much recent advancement, a fundamental question about the value of NPA hierarchy remained open. Given a nonlocal game, does there exist a (finite) level for which the NPA hierarchy attains the commuting operator value? Perhaps surprisingly, a positive and negative answer to this question is consistent with the recent undecidability results for the quantum and commuting operator values. In this talk, I will show that the above question has a negative answer. Moreover, I will discuss how the answer to the above question follows from a seemingly unrelated question about the computability of the commuting operator value.

In this talk, I will introduce two of our main contributions to the field in addressing this challenge: (1) asymmetric Measurement-Device-Independent (MDI) and Twin-Field (TF) QKD protocols, which close loopholes from the receiver’s detectors while also enabling high-performance and scalable quantum networks unrestrained by user location, as well as (2) fully passive QKD protocols, which remove loopholes from the sender’s modulators, and they can further be combined with MDI-QKD/TF-QKD to simultaneously protect the sender and the receiver and enable more secure quantum networks.

The above two new families of protocols represent a huge step toward building more implementation-secure QKD systems and future quantum networks with high performance and robustness.

We show efficient spectrum learning for the 1D Fermi–Hubbard models at large scale, achieving improved accuracy relative to standalone MODMD and other available methods. We anticipate that TERRA will serve as a widely applicable algorithmic building block for utility-scale algorithm design, providing a practical pathway toward scalable, noise-resilient computation on near-term devices.

In this talk, I will describe the demographics of these objects—their mass, spin, redshift, etc., distributions—and their use as astrophysical probes. I will emphasize a hallmark feature of GW astronomy that is crucial to this exercise: our ability to model selection effects (the GW analogue of the Malmquist bias) accurately and precisely.

I will also summarize our current understanding of formation pathways and the open questions that remain, with a concentration on the emerging hints of repeated mergers in the binary black hole population. I will end with my view on the exciting prospects ahead for gravitational-wave science.

I will discuss the impact of the LMC on the local dark matter distribution in state-of-the-art cosmological simulations. I will then present the implications for dark matter direct detection, considering both standard and non-standard dark matter interactions and different dark matter masses.

In this talk, after a brief introduction to the the CPS formalism, I will present xCPS, a Mathematica package designed to automate the covariant phase space formalism for general Lagrangian field theories. The package computes equations of motion, presymplectic potentials, symplectic currents, Noether currents and charges, and related geometric structures in a fully covariant manner. I will conclude with some interesting examples.

We present here the most recent results from the WIMP search, together with the first results from the analysis of the third‑fill data, which will inform both the impact of the detector upgrades on our backgrounds and the design of future noble‑liquid experiments.

Then, this talk presents precise measurements of Higgs boson production and decay rates, obtained using the full Run 2 and partial Run 3 pp collision dataset collected by the ATLAS experiment at 13 TeV and 13.6 TeV. These include total and fiducial cross-sections for the main Higgs boson processes as well as branching ratios into final states with bosons and fermions. Differential cross-sections in a variety of observables are also reported, as well as a fine-grained description of the Higgs boson production kinematics within the Simplified Template Cross-section (STXS) framework.

In particular, it can measure the survival probability of these electron antineutrinos, which depends on so-called “long baseline” oscillation parameters, namely the mixing angle θ₁₂ and the mass-squared difference Δm²₂₁. Using 1.46 ktonne-years of data from May 2022 to July 2025, 7.93^+0.21_-0.24 x 10^-5 eV² was measured, with a precision approaching the previous result from the KamLAND experiment 7.54^+0.19_-0.18  x 10^-5 eV², and providing a valuable cross-check to the recent measurement by the JUNO collaboration. In addition, electron antineutrinos produced from radioactive decays inside the Earth were detected. This geoneutrino flux was simultaneously measured to be 49⁺¹³_-12 TNU at SNO+. The result was obtained by using a novel classifier to distinguish the positron annihilation engendered by inverse beta decays from their primary background: (α, n)-induced proton recoils.

This provides the only measurement of the geoneutrino flux in the Americas, and the third location worldwide, adding crucial data to a global calculation of the mantle’s radiogenic heat production.

Cosmological data also point toward an effective Fermi constant significantly larger than what the Standard Model offers. In this talk, I will show how neutrinophilic mediators can leave indirect yet measurable signatures through radiative corrections to neutrino-matter scattering. I will also discuss the resulting new contributions to the Z-boson decay width and to non-standard neutrino interactions relevant for neutrino oscillation experiments.

Many beyond the Standard Model (BSM) theories have been proposed to address these shortcomings, and many such theories predict signatures directly accessible at the LHC. This talk will present selected results from the ATLAS full run-2 and/or partial run-3 dataset at a center of mass energy of 13/13.6 TeV, including constraints on SUSY, exotic signatures, and BSM models with Higgs and vector boson signatures.

PIONEER aims to surpass the precision of the current best measurement, obtained by the PIENU experiment at TRIUMF, by more than an order of magnitude. This improvement would bring the experimental precision of R_e/μ to the 10^-4 level, matching the accuracy of Standard Model calculations and providing a stringent test of lepton flavour universality.

To achieve this ambitious goal, PIONEER will exploit the world’s most intense pion beam at PSI, an active silicon-strip target based on Low Gain Avalanche Detectors (LGADs), and an optimized calorimeter geometry. This talk will present an overview of the experiment and its physics program, including searches for sterile neutrinos and tests of Cabibbo–Kobayashi–Maskawa matrix unitarity. It will also highlight recent detector R&D activities for PIONEER, including LGAD beam tests performed at TRIUMF.

To fill this gap, we have proposed the MATHUSLA detector (Massive Timing Hodoscope for Ultra-Stable neutral particles), which would be constructed on the surface above CMS and would take data during High-Luminosity LHC operations. The detector would be composed of several layers of solid plastic scintillator, with wavelength-shifting fibers connected to silicon photomultipliers, monitoring an empty air-filled decay volume. The Conceptual Design Report (CDR) published last year sets out a benchmark geometry of 40m x 40m x 25m, with a modular detector construction scheme that would allow data collection to begin as soon as the first of 16 modules is installed.

This talk will summarize the results of more detailed studies conducted by the Canadian MATHUSLA team since the CDR, with the aim of building the first 4 modules (20m x 20m x 25m) in Canadian facilities. These studies include higher-statistics simulations of rare Standard Model backgrounds, FPGA implementation of trigger algorithms that would permit an “LLP trigger” to be sent to CMS, and “test stands” at the University of Victoria and the University of Toronto.

Hyper-Kamiokande consists of a large cylindrical tank with 258 thousand tonnes of ultrapure water as its detection medium and it is placed 295 m from the neutrino beam production at J-PARC. The project also consists of a suite of near detectors including a movable 500 tonne Water Cherenkov detector placed 1 km from J-PARC called the Intermediate Water Cherenkov Detector (IWCD) and it is used to constrain major systematic uncertainties related to neutrino interactions in the water.

In this talk I will present an overview of the Hyper-Kamiokande experiment, details of its detector design and provide the construction status.

The Deep Underground Neutrino Experiment (DUNE) is an ambitious research program in neutrino physics under construction at Fermilab and the Sanford Underground Research Facility (SURF), uniquely designed to measure many oscillation parameters and eventually test the validity of the oscillation model. Additionally, its design will offer the opportunity for non-beam related neutrino physics including supernova neutrinos, atmospheric neutrinos, and neutrinos originating in the core of the Sun. DUNE is a long baseline neutrino oscillation experiment with a detector close to the neutrino beam source at Fermilab (Near Detector) and a detector 1300 km away in South Dakota (Far Detector).

Both the Near and Far Detector are based on Liquid Argon Time Projection Chamber (LArTPC) technology that measures neutrinos and antineutrinos over a wide range of energies. The Near Detector measures the unoscillated neutrino flux and constrains systematic uncertainties to predict the neutrino flux at the Far Detector, where the oscillated (anti-)neutrino beam is measured. The Far Detector will comprise at least two multi-kiloton underground LArTPCs, and the Near Detector will consist of a LArTPC module combined with two additional tracking detectors to obtain a robust characterization of the neutrino flux. In this talk, I will present the rich DUNE neutrino physics program, its sophisticated design, and the results from the Near and Far detector prototypes, together with the current status and future plans, emphasizing the contributions of the Canadian institutions involved.

To benefit from such a rich data-sample it is fundamental to upgrade the detector to cope with the challenging experimental conditions that include huge levels of radiation and pile-up events. The ATLAS upgrade comprises the completely novel all-silicon Inner Tracker (ITk) with extended rapidity coverage that will replace the current Inner Detector; a redesigned trigger and data acquisition system for the calorimeters and muon systems allowing the implementation of a free-running readout system.

This presentation will describe the ongoing ATLAS detector upgrade status and the main results obtained with the prototypes, giving a synthetic, yet global, view of the whole upgrade project. The focus will be on the Canadian contributions to the tracking and calorimeter upgrades which are in progress.

The experiment will probe low-mass WIMPs, dark photon absorption, and Axion-Like Particles. With the detectors cooled to their operating temperature, the commissioning phase is underway, with science data-taking expected later this year. This talk gives an overview of the experiment, its science goals, and a status update of the experiment at SNOLAB.

This talk describes an ongoing research program exploring AI applications across three areas: longitudinal imaging biomarkers for tumour response monitoring during radiotherapy, prediction of treatment outcomes in surgically managed head and neck cancer using multi-omic data, and early detection of treatment-related complications.

These projects are being developed in parallel with OPTIMA-OPC, a prospective de-escalation trial in HPV-positive oropharyngeal cancer, with the longer-term goal of embedding validated biomarkers into adaptive treatment protocols. We share preliminary findings, current limitations, and the practical challenges of translating AI tools from the research setting into clinical trials.

This talk presents recent works addressing these challenges. First, deep learning methods for radiotherapy longitudinal imaging analysis are described, highlighting performance in automated assessment of therapy outcomes under standard imaging conditions. Building on this foundation, the limitations caused by missing contrast-enhanced MRI are addressed through a contrast-aware generative modeling framework that synthesizes contrast-enhanced T1-weighted images from routinely acquired non-contrast sequences. The framework supports both single-timepoint and longitudinal imaging configurations, and is validated on multi-institutional datasets, demonstrating high fidelity and preservation of tumor enhancement patterns.

Finally, the efficacy of synthesized images for downstream tasks, including automated tumor detection and segmentation, is demonstrated, enabling reliable AI workflows even when key imaging modalities are unavailable. This work highlights a path toward data-robust AI systems in radiotherapy, bridging the gap between algorithmic performance and real-world applicability.

This presentation highlights how AI is used to model, optimize, and personalize radiation-based cancer treatments. One area of focus is brachytherapy, a form of radiation therapy in which radioactive sources are placed close to or inside the tumour. In this context, I will describe AI-based treatment planning methods that optimize source placement and treatment delivery, with the goal of maximizing tumour dose while minimizing exposure to surrounding healthy tissue.

I will also present deep learning tools for rapid dose estimation that approximate computationally intensive physics-based Monte Carlo simulations while preserving clinical accuracy. Another component of the presentation focuses on data collection and curation efforts, including the assembly of large, multi-institutional and multimodal datasets needed to train and validate clinically generalizable AI models. Finally, I will discuss multimodal prediction models that combine imaging, pathology, molecular, and clinical data to improve understanding of treatment response, progression-free survival, and individualized patient risk.

Building on this rigorous foundation, we apply high-throughput screening to resolve physics questions that remain elusive on a material-by-material basis. Utilizing the computational 2D materials database (C2DB), we screened hundreds of stable, nonmagnetic, direct-gap monolayers to determine if reduced dimensionality intrinsically enhances the radiative transition strength. Our analysis identified multiple 2D candidates with transition strengths that rival or exceed those of molybdenum disulfide (MoS2), while establishing the performance limits of monolayers relative to traditional III-V semiconductors like GaAs and GaN.

We further anchor these results to experimental benchmarks by examining the accuracy of band structure predictions beyond simple energy gaps. Using a curated dataset of 60 experimental effective masses from 18 semiconductors, we quantify the performance of different exchange-correlation approximations. Our findings highlight that achieving accurate band gaps does not guarantee reliable predictions of band curvature (effective mass) and demonstrate the critical role of nonlocal exchange in capturing the physics of charge carrier transport.

These results provide a rigorous framework for high-throughput discovery, ensuring that the next generation of data-driven materials design is anchored in both computational precision and physical reality.

As PEX pipes age while in use, they sometimes fail unexpectedly. To gain insight into this phenomenon, we use sophisticated instrumentation, high spatial resolution IR microscopy and atomic force microscopy, accelerated aging, and a deep learning analysis to track the evolution of the polyethylene and the stabilizing additives that are incorporated into the pipes to extend their lifetime. Hyperspectral IR images of pipe cross-sections contain a large amount of spatially resolved information about their chemical composition.

However, the analysis of these data for complex heterogeneous systems can be challenging because of spectroscopic and spatial complexity. We implement a deep generative modeling approach using a β-variational autoencoder to learn disentangled representations of the generative factors of variance in our large data set of over 30,000 IR spectra collected on cross-sectional slices of unused virgin and used in-service pipes, both with and without cracks. This approach has allowed us to identify three distinct factors of aging and degradation learned by the model, including one associated with crack formation.

We also purposely introduce scratches of adjustable depth along the length of the inner surface of the pipes and then subject the pipes to accelerated aging. Our high-resolution IR images have allowed us to identify a new spectroscopic feature near the apex of the scratches that develops during the aging of the pipes. We identified this new feature, associated with a localized enhancement of carboxylate absorbance, through the observation of a large mean square error when processed with our β-VAE model, demonstrating that deep learning approaches can be used to identify new features in data.

In this talk, I argue for the existence of an enriched perspective in which solutions are not optimized but instead emerge from collective behaviour. I will motivate this framework using an example from topology optimization, where early-stage collective dynamics encode critical design information well before convergence. Using Bayesian statistics, I then show how inference can be reformulated in terms of ensembles, where collective variables emerge naturally from the geometry of over-parameterized models without any a priori assumptions. Finally, I demonstrate how this framework extends to learning in neural networks, state estimation, and parameter identification. The key message is that useful solutions need not be enforced by optimization, but can arise through collective dynamics.

This talk will focus on computational efforts, in support of that goal, to understand the emergence of structure and its relationship to dynamics in soft materials on the nano- and micro-scales. I will primarily discuss two recent projects: In the first, we closely examined how bulk structure emerges in a model system of colloidal clusters, thereby uncovering a relationship between interparticle interaction shape and structural evolution. In the second project, we used linear control theory to predict mechanical response in jammed and disordered systems, thereby uncovering an often-obscured relationship between amorphous structure and rearrangement dynamics. This work collectively demonstrates the intertwined relationship between local interaction, local structure, and complex global behavior in soft material systems, and points toward exciting future directions related to the design of that behavior.

In this talk, I discuss the role that machine learning is playing in advancing material and device fabrication, as well as quantum technologies, specifically those based on diamond and hexagonal-boron nitride. This is particularly relevant as these materials, with their optically addressable spin defects, are emerging as leading hardware platforms for solid-state quantum applications in information processing, computing and sensing.

I will show how ML-based methods can be successfully applied to measure certain physical quantities with better accuracy, higher resolution and/or overall fewer data points than standard approaches based on statistical inference. I will also discuss the increasingly important role machine learning is taking in the context of material design and (quantum-based) data processing, with specific focus on both its merits and its limits.

In this talk, I will show how artificial intelligence can optimize the control of quantum experiments, enable efficient evaluation of experimentally prepared states, and uncover detailed insights into quantum many-body physics. By highlighting the strengths of different artificial intelligence algorithms for specific tasks, I will illustrate how harnessing artificial intelligence opens new opportunities for control and discovery in quantum research.

Here, we propose a symmetry-equivariant attention mechanism for SLMC that allows for systematic improvement through increased model depth. The method is tested on the two-dimensional spin–fermion (double-exchange) model. We find that the proposed architecture substantially improves acceptance rates compared to conventional linear models. Furthermore, the performance of the effective model follows a clear scaling behavior, with accuracy improving monotonically as the number of layers increases, reminiscent of trends observed in large-scale language models. These results indicate that deep equivariant architectures provide a promising route toward more efficient and reliable SLMC simulations of complex physical systems.

In this talk, I will present our lab’s ongoing work on the creation and assessment of latent space-associated deep learning models and optimization procedures for peptide design. I will discuss model design and optimization in the context of latent space-associated models, including data curation and semi-supervised learning in the context of designing antimicrobial peptides, for which there is plentiful physico-chemical data but sparse highly-relevant experimental data. I will also discuss model quality analysis, focusing on latent space organization, information content, and visualization, and performance and visualization of optimization procedures within different latent spaces. Finally, I will present preliminary work on bringing together deep learning, molecular dynamics simulation, and experiment to design peptides aggregating into functional amyloid structures. Overall, our work lays necessary groundwork for peptide design procedures and for assessing the quality of generative models.

The resulting maps reflect research and innovation clusters, extracted in an emergent rather than a prescriptive manner. In this way, we can trace through the impact of basic research or federal funding, and isolate new areas that are likely to experience extreme growth.

To further enhance plasma stability and confinement, precise equilibrium field regulation is underway. This work focuses on optimizing plasma positioning and shaping to provide a stable foundation for high-performance discharges, such as the transition toward the Quasi-Single Helicity (QSH) state.Experimental investigations into edge turbulence are also being conducted to clarify transport mechanisms at the plasma boundary. Utilizing a dual-biasing electrodes system for electric field manipulation, these studies aim to understand the relationship between rotation control and turbulence suppression.

These efforts are supported by advanced diagnostics, including a terahertz polarimeter-interferometer for equilibrium reconstruction and a double-foil soft X-ray system for monitoring plasma instabilities. Furthermore, the successful testing of a novel Compact Torus Injection (CTI) system, achieving injection speeds up to 300 km/s, has demonstrated enhanced core fueling and density control capabilities. Together with numerical simulations exploring helicity and drift flows, these comprehensive studies on KTX provide multi-faceted insights into universal physics of magnetic magnetic confinement fusion plasma. The details of KTX experimental results will be presented in this conference.

Over the past decades an alternative path has begun to emerge: a collider built utilizing muons could avoid these existing limitations, but of course introduces its own challenging hurdles. This talk gives an overview of the physics possibilities of a muon collider, including the unique probes of new physics such as machine could deliver. A brief overview of the status of the international collaboration working towards such a machine will also be discussed.

Chiral Belle will also provide the highest precision measurements of neutral current universality ratios, precision measurements of tau lepton properties, including the tau magnetic moment and Michel parameters. This paper will review recent work on the physics potential and report on the status of R&D initiatives underway to realize this upgrade. These R&D initiatives include the development of polarized sources, a Compton polarimeter, and compact spin rotator magnets designed to be ‘drop-in’ replacements of existing dipole magnets in the SuperKEKB High Energy Ring.

To implement this principle, we use an adaptive optics scanning light ophthalmoscope (AOSLO), which corrects optical aberrations and enables precise delivery of light to targeted cone photoreceptors. The scanning architecture allows high-speed retinal imaging and tracking, as well as the delivery of carefully controlled microflashes to each cone across the region of the retina encompassed by the display. The display is small — about twice the width of the full moon — but can contain over 5,000 cones. This system enables new ways to study visual perception in both healthy and diseased eyes.

We demonstrate two applications of Oz Vision: first, the generation of color sensations that lie outside the normal human color gamut; and second, the ability to test the perceptual consequences of cone loss—such as in retinal degenerative disease—by emulating specific patterns of photoreceptor loss in otherwise healthy observers.

In non‑human primates, two‑photon excited fluorescence signals change in response to visual stimulation and show distinct alterations in models of retinal degeneration and during systemic hypoxia. In human participants, single-photon fluorescence enables visualization of cellular mosaics and detection of molecular variations. Furthermore, in preclinical studies, the introduction of extrinsic fluorophores into cells allows these molecules to serve as optical reporters of retinal function.

Over the past few decades, Optical Coherence Tomography (OCT) has transformed retinal imaging by enabling non-invasive, depth-resolved imaging of the retina. Early applications focused on structural characterization of retinal layers and quantitative assessment of pathological changes in retinal neurodegenerative diseases. These advances established OCT as an indispensable clinical and research tool.

Building on this structural foundation, more recent developments have extended OCT beyond morphology toward functional imaging. Doppler OCT enabled quantitative assessment of retinal blood flow and provided new insights into vascular regulation. More recently, optoretinography (ORG) has emerged as a powerful approach for detecting stimulus-evoked intrinsic optical signals associated with neuronal activation, allowing direct, non-invasive measurement of retinal function *in vivo*.

This talk will trace the progression of retinal imaging from structural characterization to the investigation of retinal dynamics, highlighting advances in OCT-based techniques that bridge morphology, vascular physiology, and neuronal activity. Particular emphasis will be placed on recent work examining stimulus-evoked retinal blood flow changes and their relationship to neurovascular coupling, demonstrating how modern OCT approaches can probe functional hyperemia in the living human retina.

Together, these advances illustrate the continuing evolution of OCT from structural imaging to a powerful platform for probing retinal physiology *in vivo*.

Methods: A custom module was added to the front of a commercial retinal imaging system, which produced circularly polarized light incident on the eye. Light reflected from the retina exited the eye, was incident on the quarter wave plate followed by a linear polarizer and was recorded at 30 frames/sec. The individuals imaged included 1 with a diagnosis of AD, 1 over 65 with a family history of AD, 1 diagnosed with age related macular degeneration (AMD) and 1 who had no history of AD or AMD.

Results: In the individuals with either a family history of the disease or a diagnosis of AD, deposits, consistent with Alzheimer’s disease (and similar to those imaged ex vivo), were imaged in the anterior (neural) layers of the retina. One had numerous deposits and one had sparse deposits consistent with early Alzheimer’s disease pathology. Three individuals had deposits located in the more posterior layers of the retina, consistent with AMD.

Conclusion: This Imaging method would be the only dye-free, non-invasive, inexpensive and widely available diagnostic of pathology due to Alzheimer’s and other neurodegenerative diseases. It could facilitate early interventions known to slow diseases progression.

The EDIT-STEM (EDI Technologies/Transformation for STEM) initiative aims to develop novel technologies as a transformative approach to address the challenges to EDI in STEM. This unique interdisciplinary collaboration unites researchers across disciplines, sectors, organizations, and geographic regions. It will make use of recent developments in the computer science sub-field of Persuasive Technology – interactive systems to motivate positive changes in user attitude and behaviour through informed persuasion.

This presentation will provide an overview of EDIT-STEM. For context, recent work on resources to empower scientists to initiate actions to advance EDI will be reviewed. The Teaching Toolkit, “Science is for everyone: Integrating equity, diversity and inclusion in teaching science and engineering – a toolkit for instructors”, and Research Pocket Guide, “Striving for inclusive excellence in science and engineering research: a pocket guide”, focus on practical, actionable ideas to engage with EDI (zenodo.org/communities/edit-stem).

We will describe how the EDIT-STEM collaboration was formed by researchers from across STEM fields in partnership with organizations that are STEM changemakers in Canada. Our approach, including participatory design and integrated knowledge mobilization, will be outlined. We will sketch our vision of developing an innovative technological approach to achieve a user-centric, accessible, interactive, and scalable solution to this societal problem.

The design of the questionnaire is grounded in a well-established theory of human behaviour change that delineates 4 stages of change common across different contexts; we applied the theory to the context of EDI in STEM. The questionnaire aims to quantify an individual’s attitudes and behaviours associated with EDI initiatives. We conducted a pilot study to evaluate the EDI-Ready questionnaire at Carleton University by recruiting graduate students, postdoctoral fellows, and faculty in STEM.

Over 250 scientists and engineers completed the EDI-Ready questionnaire, and 33 participated in follow-up semi-structured interviews. Statistical analyses of participant responses to the questionnaire suggest that participants’ behaviours and attitudes align with the theory’s 4 stages of change; these results show the majority of participants are preparing to engage in EDI initiatives (but are not fully action-oriented). Qualitative analyses based on the interviews validated the questionnaire as an assessment tool to capture change readiness and to gain a better understanding of participants’ perspectives and experiences with EDI.

Initial results demonstrate that the EDI-Ready questionnaire can effectively assess individuals’ behaviours and attitudes related to EDI in STEM. Ongoing work focuses on refining the questionnaire and engaging in broader validity studies, towards the aim of providing a validated tool to measure progress in advancing EDI at individual and institutional levels. Data collected from the questionnaire provides the foundation for the design of tailored, theory-driven interventions, including interactive technologies.

I will recount the initial lessons from the journeys of three master students (second, third and fourth author of this abstract). I will present projects in various stages including early ideations and prototypes on the topics of anxiety and power dynamics, and two more developed games on micro-aggressions and bystander interventions.

I will discuss challenges arising when designing educational EDI games, such as how to balance usability, engagement and fun while conveying the intended EDI messages. I will also consider specific challenges involving differences with the research team’s background, their experiences with games and game design, as well as the game genre and the EDI topic of interest. The general lessons will include both specific design recommendations for games, as well as the type of mentoring and onboarding efforts needed to allow intelligent and faithful exploration of the synergy between games and EDI. The end of the talk will be dedicated to an open forum to elicit feedback and ideas for potential EDI educational games.

This talk will suggest policies that might matter to Canadian physicists, such as opposing Canadian participation in the Golden Dome project, engaging with the Treaty on the Prohibition of Nuclear Weapons, and resisting any consideration of Canadian nuclear weapons development. In this talk, I will also describe actions that Canadian physicists can take, in cooperation with the Physicists Coalition for Nuclear Threat Reduction. These include: Education through colloquia and webinars; joint US-Canadian advocacy (building on the Coalition’s DC engagement, but tailored to the Canadian context); and conducting research through the Coalition’s Next-Generation Fellowship. The Pugwash movement, including Pugwash Canada, provides further opportunities to reduce nuclear threats, with a focus on science diplomacy between countries with tense relations. Canadian scientists played a formative role in Student/Young Pugwash, which remains active today.

Today, the danger from nuclear weapons is growing as arms-control treaties are abandoned, as states with such weapons are engaged in conventional war, as new risks emerge from cyber attacks, as nuclear threats from leaders are issued more regularly, and as the US and other states massively modernize their entire nuclear weapon systems. But, this problem can be solved. All nations of the world, except for nine, have by treaty foresworn the possession of nuclear weapons. Numerous changes to nuclear policy and forces can be enacted to reverse the danger. Physicists, because of their special relationship to nuclear weapons and the weight given by the public to their views on this issue, can be a vital part of the solution. To this end, the Physicists Coalition for Nuclear Threat Reduction was formed to facilitate physicist contributions to nuclear arms control and disarmament education and advocacy.