Faculty

Felix Motzoi - University of California

In the NISQ era of quantum computing, as system sizes are progressively increasing, there are major concerns about the degradation of performance with increasing complexity. These can largely be reduced to the problems of crosstalk and correlations between system components, of fabrication uncertainties and drift in system parameters, and of multi-parameter optimization across multi-qubit state spaces in a fixed uptime duty cycle. In this presentation, we address inroads towards a more comprehensive, scalable approach for control theoretic solutions to maintaining (given architecture) performance that encompasses: a method to incorporate arbitrary couplings into an effective Hamiltonian frame with superexponential speedup compared to standard perturbative approaches [B. Li, T. Calarco, F. Motzoi, PRX Quantum 3, 030313 (2022)]; a control theoretic approach to tracking uncertainties in quantum circuits giving tight error bounds [M. Dalgaard, C. Weidner, F, Motzoi - Phys. Rev. Lett. 128, 150503 (2022)]; and a machine learning framework for symbolic optimization given particular Hamiltonian and associated uncertainties with a single meta-optimization permitting simultaneous tuneup of all qubits within the architecture belonging to the same class of Hamiltonians [F. Preti, T. Calarco, F. Motzoi, arXiv:2203.13594 (2022)].

Tuesday, September 13, 2022 12:00 pm - 1:00 pm EDT

Quantum Perspectives: Computing

Quantum computing promises to dramatically alter how we solve many computational problems by controlling information encoded in quantum bits. With potential applications in optimization, materials science, chemistry, and more, building functional quantum computers is one of the most exciting challenges in research today. To build and use these devices, we need to precisely control quantum bits in the lab, understand the ability and limitations of quantum algorithms, and find new methods to correct for decoherence and other quantum errors.

Research in quantum computing is highly multidisciplinary, with important contributions being made from computer scientists, mathematicians, physicists, chemists, engineers, and more. In this panel, we’ll learn from three researchers at the forefront of the field studying experimental quantum devices, quantum algorithms, and quantum error correction:

  • Crystal Senko, Assistant Professor, Institute for Quantum Computing and the Department of Physics
  • Shalev Ben-David, Assistant Professor, Institute for Quantum Computing and Cheriton School of Computer Science
  • Michael Vasmer, Postdoctoral Researcher, Institute for Quantum Computing and Perimeter Institute for Theoretical Physics

Quantum Perspectives: A Panel Series celebrates 20 years of quantum at IQC. Over the past two decades, IQC’s leading quantum research has powered the development of transformative technologies, from ideas to commercialization, through research in theory, experiment and quantum applications. This year, we’re celebrating IQC’s 20th anniversary with a panel series exploring all perspectives of quantum, including sensing, materials, communication, simulation and computing.

 

 

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Researchers at IQC have made significant contributions to a Post-Quantum Cryptography standardization process run by the National Institute for Standards and Technology (NIST). As the process enters its fourth round, researchers are one step closer to identifying codes that will be widely accepted as reliable and safe against attacks enabled by emerging quantum computers.  

Jerry Li - Microsoft Research

In this talk, we consider two fundamental tasks in quantum state estimation, namely, quantum tomography and quantum state certification. In the former, we are given n copies of an unknown mixed state rho, and the goal is to learn it to good accuracy in trace norm. In the latter, the goal is to distinguish if rho is equal to some specified state, or far from it. When we are allowed to perform arbitrary (possibly entangled) measurements on our copies, then the exact sample complexity of these problems is well-understood. However, arbitrary measurements are expensive, especially in terms of quantum memory, and impossible to perform on near-term devices. In light of this, a recent line of work has focused on understanding the complexity of these problems when the learner is restricted to making incoherent (aka single-copy) measurements, which can be performed much more efficiently, and crucially, capture the set of measurements that can be be performed without quantum memory. However, characterizing the copy complexity of such algorithms has proven to be a challenging task, and closing this gap has been posed as an open question in various previous papers.

Quantum Machine Learning Prediction Model for Retinal Conditions: Performance Analysis

Quantum machine learning predictive models are emerging and in this study we developed a classifier to infer the ophthalmic disease from OCT images. We used OCT images of the retina in  vision threatening conditions such as choroidal neovascularization (CNV) and diabetic macular edema (DME). PennyLane an open-source software tool based on the concept of quantum differentiable programming was used mainly to train the quantum circuits. The training was tested on an IBM 5 qubits System “ibmq_belem” and 32 qubits simulator “ibmq_qasm_simulator”. The results are promising. 

EvolutionQ, a leading quantum-safe cybersecurity company founded and led by Executive Director of the Institute for Quantum Computing Norbert Lütkenhaus, and IQC faculty member Michele Mosca, recently announced their latest partnership with SandboxAQ, an enterprise Saas company. This partnership was formed in relation to evolutionQ’s Series A funding and its recent grant of $7 million in funding, which will help organizations like SandboxAQ prepare for quantum computers.  

Previously, higher-order Hamiltonians (HoH) had been shown to offer an advantage in both metrology and quantum energy storage. In this work, we axiomatize a model of computation that allows us to consider such Hamiltonians for the purposes of computation. From this axiomatic model, we formally prove that an HoH-based algorithm can gain up to a quadratic speed-up (in the size of the input) over classical sequential algorithms—for any possible classical computation. We show how our axiomatic model is grounded in the same physics as that used in HoH-based quantum advantage for metrology and battery charging. Thus we argue that any advance in implementing HoH-based quantum advantage in those scenarios can be co-opted for the purpose of speeding up computation. 

QNC 1201
 

Improved Synthesis of Restricted Clifford+T Circuits

In quantum information theory, the decomposition of unitary operators into gates from some fixed universal set is of great research interest. Since 2013, researchers have discovered a correspondence between certain quantum circuits and matrices over rings of algebraic integers. For example, there is a correspondence between a family of restricted Clifford+T circuits and the group On(Z[1/2]). Therefore, in order to study quantum circuits, we can study the corresponding matrix groups and try to solve the constructive membership problem (CMP): given a set of generators and an element of the group, how to factor this element as a product of generators? Since a good solution to CMP yields a smaller decomposition of an arbitrary group element, it helps us implement quantum circuits using fewer resources. 

Noncommuting charges: Bridging theory to experiment

Noncommuting conserved quantities have recently launched a subfield of quantum thermodynamics. In conventional thermodynamics, a system of interest and an environment exchange quantities—energy, particles, electric charge, etc.—that are globally conserved and are represented by Hermitian operators. These operators were implicitly assumed to commute with each other, until a few years ago. Freeing the operators to fail to commute has enabled many theoretical discoveries—about reference frames, entropy production, resource-theory models, etc. Little work has bridged these results from abstract theory to experimental reality. This work provides a methodology for building this bridge systematically: we present a prescription for constructing Hamiltonians that conserve noncommuting quantities globally while transporting the quantities locally. The Hamiltonians can couple arbitrarily many subsystems together and can be integrable or nonintegrable. Our Hamiltonians may be realized physically with superconducting qudits, with ultracold atoms, and with trapped ions.