Events

Geometry of Banach spaces: a new route towards Position Based Cryptography

Aleksander Kubicki, University Complutense of Madrid

In this talk I will explain how some techniques coming from the local theory of Banach spaces can be used to obtain claims about the security of protocols for Position Based Cryptography.

Scientists of all backgrounds and genders, have made important contributions in science, technology, engineering and mathematics (STEM), but the participation of women remains low in many areas of STEM, including physics. What can we do to build an inclusive STEM community? Shohini Ghose, IQC associate and Director of the Laurier Centre for Women in Science (WinS) will discuss data that can shed light on where we stand today and describe a practical framework for increasing access and inclusion in STEM.

Post-quantum security of the Even-Mansour cipher

Chen Bai, University of Maryland, College Park

The Even-Mansour cipher is a simple method for constructing a (keyed) pseudorandom permutation E from a public random permutation P: {0,1}^n ->{0,1}^n. It is a core ingredient in a wide array of symmetric-key constructions, including several lightweight cryptosystems presently under consideration for standardization by NIST.

Local-dimension-invariant stabilizer codes

Protection of quantum information is a central challenge in building a quantum computer. Quantum error-correcting codes can correct for logical errors that occur in the system. A particularly well-studied category is stabilizer codes, such as the 9-qubit Shor code, as these are the quantum analogue of classical additive codes. Qudits (particles with local-dimension greater than 2) have more computational basis states per particle than qubits and retain this feature in stabilizer codes.

Universal efficient compilation: Solovay-Kitaev without inverses

Tudor Giurgica-Tiron, Stanford University

The Solovay-Kitaev algorithm is a fundamental result in quantum computation. It gives an algorithm for efficiently compiling arbitrary unitaries using universal gate sets: any unitary can be approximated by short gates sequences, whose length scales merely poly-logarithmically with accuracy. As a consequence, the choice of gate set is typically unimportant in quantum computing. However, the Solovay-Kitaev algorithm requires the gate set to be inverse-closed.

From quantum circuit complexity to quantum information thermodynamics

Philippe Faist, Freie Universität Berlin

Quantifying quantum states' complexity is a key problem in various subfields of science, from quantum computing to black-hole physics. My talk will focus on two approaches to understand the behavior and the operational significance of quantum complexity in a many-body physical quantum system. First, I'll consider a simple model on n quantum bits: We create a random quantum circuit by randomly sampling the gates that compose it.

In celebration of World Quantum Day, join IQC's Senior Manager of Scientific Outreach, John Donohue, for some fun light experiments with Exploring By The Seat Of Your Pants.

Interactive Proofs for Synthesizing Quantum States and Unitaries

Gregory Rosenthal, University of Toronto

Whereas quantum complexity theory has traditionally been concerned with problems arising from classical complexity theory (such as computing boolean functions), it also makes sense to study the complexity of inherently quantum operations such as constructing quantum states or performing unitary transformations.

The theory of quantum information: Channels, Capacities, and all that

Graeme Stewart Baird Smith, University of Colorado, Boulder

 Information theory offers mathematically precise theory of communication and data storage that guided and fueled the information age.  Initially, quantum effects were thought to be an annoying source of noise, but we have since learned that they offer new capabilities and vast opportunities. Quantum information theory seeks to identify, quantify, and ultimately harness these capabilities.

Tensor Methods for Quantum Systems and Beyond

Edgar Solomonik, University of Illinois at Urbana-Champaign

Tensors are an effective numerical representation for both computation with and analysis of multidimensional datasets and operators. In this talk, we review and motivate how tensor rank, decompositions, and eigenvalues can be used for computational simulation and for hardness measures, such as bilinear complexity and quantum entanglement. We then survey algorithms for computing low-rank decompositions of tensors.