Events

Tight bounds for Pauli channel learning with and without entanglement

Quantum Nano Centre, 200 University Ave West, Room QNC 1201
Waterloo, ON CA N2L 3G1

Quantum entanglement is a crucial resource for learning properties from nature, but a precise characterization of its advantage can be challenging. In this work, we consider learning algorithms without entanglement as those that only utilize separable states, measurements, and operations between the main system of interest and an ancillary system. Interestingly, these algorithms are equivalent to those that apply quantum circuits on the main system interleaved with mid-circuit measurements and classical feedforward. Within this setting, we prove a tight lower bound for Pauli channel learning without entanglement that closes the gap between the best-known upper bound. In particular, we show that Θ(n^2/ε^2) rounds of measurements are required to estimate each eigenvalue of an n-qubit Pauli channel to ε error with high probability when learning without entanglement. In contrast, a learning algorithm with entanglement only needs Θ(1/ε^2) copies of the Pauli channel. Our results strengthen the foundation for an entanglement-enabled advantage for Pauli noise characterization. We will talk about ongoing experimental progress in this direction.

Reference: Mainly based on [arXiv: 2309.13461]

Unruh phenomena and thermalization for qudit detectors

Quantum-Nano Centre, 200 University Ave West, Room QNC 1201 Waterloo, ON CA N2L 3G1

The Unruh effect is the flat space analogue to Hawking radiation, describing how an observer in flat spacetime perceives the quantum vacuum state to be in a thermal state when moving along a constantly accelerated trajectory. This effect is often described operationally using the qubit-based Unruh-DeWitt detector.

We study Unruh phenomena for more general qudit detectors coupled to a quantized scalar field, noting the limitations to the utility of the detailed balance condition as an indicator for Unruh thermality of higher-dimensional qudit detector models. We illustrate these limitations using two types of qutrit detector models based on the spin-1 representations of SU(2) and the non-Hermitian generalization of the Pauli observables (the Heisenberg-Weyl operators).

[2309.04598] Unruh phenomena and thermalization for qudit detectors (arxiv.org)

CS Math Seminar - Kewen Wu, UC Berkeley (ZOOM + in person)

200 University Ave W. Waterloo On. N2G 4K3 QNC 1201

Motivated by limitations on the depth of near-term quantum devices, we study the depth-computation trade-off in the query model, where the depth corresponds to the number of adaptive query rounds and the computation per layer corresponds to the number of parallel queries per round. We achieve the strongest known separation between quantum algorithms with r versus r−1 rounds of adaptivity. We do so by using the k-fold Forrelation problem introduced by Aaronson and Ambainis (SICOMP'18). For k=2r, this problem can be solved using an r round quantum algorithm with only one query per round, yet we show that any r−1 round quantum algorithm needs an exponential (in the number of qubits) number of parallel queries per round.

Our results are proven following the Fourier analytic machinery developed in recent works on quantum-classical separations. The key new component in our result are bounds on the Fourier weights of quantum query algorithms with bounded number of rounds of adaptivity. These may be of independent interest as they distinguish the polynomials that arise from such algorithms from arbitrary bounded polynomials of the same degree.

Joint work with Uma Girish, Makrand Sinha, Avishay Tal

Research Advancement Centre, 475 Wes Graham Way, Room RAC 2009, Waterloo, ON, CA N2L 6R2

A quick introduction to Clifford theory

Quantum-Nano Centre, 200 University Ave West, Room QNC 1201 Waterloo, ON CA N2L 3G1

Clifford theory studies the connection between representations of a group and those of its normal subgroups. In recent work, I examined the Clifford theory of the Clifford group to determine parts of its character table for future applications. The goal of this talk is to introduce the representation theory and Clifford theory of finite groups sufficiently to understand next week's talk when I will explain the Clifford theory of the n-qubit Clifford group. Note that these are two distinct Cliffords. I may also briefly discuss the applications of Clifford theory in quantum error correction, time permitting.

The Clifford theory of the n-qubit Clifford group

Quantum-Nano Centre, 200 University Ave West, Room QNC 1201 Waterloo, ON CA N2L 3G1

The n-qubit Pauli group and its normalizer the n-qubit Clifford group have applications in quantum error correction and device characterization. Recent applications have made use of the representation theory of the Clifford group. We apply the tools of (the coincidentally named) Clifford theory to examine the representation theory of the Clifford group using the much simpler representation theory of the Pauli group. We find an unexpected correspondence between irreducible characters of the n-qubit Clifford group and those of the (n + 1)-qubit Clifford group. This talk will rely on the explanation of Clifford theory given last week.

Improving the Fidelity of CNOT Circuits on NISQ Hardware

Quantum-Nano Centre, 200 University Ave West, Room QNC 1201 Waterloo, ON CA N2L 3G1

We introduce an improved CNOT synthesis algorithm that considers nearest-neighbour interactions and CNOT gate error rates in noisy intermediate-scale quantum (NISQ) hardware. Our contribution is twofold. First, we define a \Cost function by approximating the average gate fidelity Favg. According to the simulation results, \Cost fits the error probability of a noisy CNOT circuit, Prob = 1 - Favg, much tighter than the commonly used cost functions. On IBM's fake Nairobi backend, it fits Prob with an error at most 10^(-3). On other backends, it fits Prob with an error at most 10^(-1). \Cost accounts for the machine calibration data, and thus accurately quantifies the dynamic error characteristics of a NISQ-executable CNOT circuit. Moreover, it circumvents the computation complexity of calculating Favg and shows remarkable scalability. 

Second, we propose an architecture-aware CNOT synthesis algorithm, NAPermRowCol, by adapting the leading Steiner-tree-based synthesis algorithms. A weighted edge is used to encode a CNOT gate error rate and \Cost-instructed heuristics are applied to each reduction step. Compared to IBM's Qiskit compiler, it reduces \Cost by a factor of 2 on average (and up to a factor of 8.8). It lowers the synthesized CNOT count by a factor of 13 on average (up to a factor of 162). Compared with algorithms that are noise-agnostic, it is effective and scalable to improve the fidelity of CNOT circuits. Depending on the benchmark circuit and the IBM backend selected, it lowers the synthesized CNOT count up to 56.95% compared to ROWCOL and up to 21.62% compared to PermRowCol. It reduces the synthesis \Cost up to 25.71% compared to ROWCOL and up to 9.12% compared to PermRowCol. NAPermRowCol improves the fidelity and execution time of a synthesized CNOT circuit across varied NISQ hardware. It does not use ancillary qubits and is not restricted to certain initial qubit maps. It could be generalized to route a more complicated quantum circuit, and eventually boost the overall efficiency and accuracy of quantum computing on NISQ devices. 

Joint-work with: Dohun Kim, Minyoung Kim, and Michele Mosca

Overparameterization and Expressivity of Realistic Quantum Systems

Quantum-Nano Centre, 200 University Ave West, Room QNC 1201 Waterloo, ON CA N2L 3G1

Quantum computing devices require exceptional control of their experimental parameters to prepare quantum states and simulate other quantum systems, in particular while subject to noise. Of interest here are notions of trainability, how difficult is it to classically optimize parameterized, realistic quantum systems to represent target states or operators of interest, and expressivity, how much of a desired set of these targets is our parameterized ansatze even capable of representing? We observe that overparameterization phenomena, where systems are adequately parameterized, are resilient in noisy settings at short times and optimization can converge exponentially with circuit depth. However fidelities decay to zero past a critical depth due to accumulation of either quantum or classical noise. To help explain these noise-induced phenomena, we introduce the notion of expressivity of non-unitary, trace preserving operations, and highlight differences in average behaviours of unitary versus non-unitary ensembles. We rigorously prove that highly-expressive noisy quantum circuits will suffer from barren plateaus, thus generalizing reasons behind noise-induced phenomena. Our results demonstrate that appropriately parameterized ansatze can mitigate entropic effects from their environment, and care must be taken when selecting ansatze of channels.

Variational methods for quantum sensing

Quantum-Nano Centre, 200 University Ave West, Room QNC 1201 Waterloo, ON CA N2L 3G1

The precise estimation of unknown physical quantities is foundational across science and technology. Excitingly, by harnessing carefully-prepared quantum correlations, we can design and implement sensing protocols that surpass the intrinsic precision limits imposed on classical approaches. Applications of quantum sensing are myriad, including gravitational wave detection, imaging and microscopy, geoscience, and atomic clocks, among others.

However, current and near-term quantum devices have limitations that make it challenging to capture this quantum advantage for sensing technologies, including noise processes, hardware constraints, and finite sampling rates. Further, these non-idealities can propagate and accumulate through a sensing protocol, degrading the overall performance and requiring one to study protocols in their entirety.

In recent work [1], we develop an end-to-end variational framework for quantum sensing protocols. Using parameterized quantum circuits and neural networks as adaptive ansätze of the sensing dynamics and classical estimation, respectively, we study and design variational sensing protocols under realistic and hardware-relevant constraints. This seminar will review the fundamentals of quantum metrology, cover common sensing applications and protocols, introduce and benchmark our end-to-end variational approach, and conclude with perspectives on future research.

[1] https://arxiv.org/abs/2403.02394

Rajibul Islam
Faculty, Institute for Quantum Computing
Associate Professor, Department of Physics and Astronomy, University of Waterloo
Co-founder, Open Quantum Design

Quantum-Nano Centre, 200 University Ave West, Room QNC 0101 Waterloo, ON CA N2L 3G1

Quantum computing promises to advance our computational abilities significantly in many high-impact research areas. In this period of rapid development, the experimental capabilities needed to build quantum computing devices and prototypes are highly specialized and often difficult to access. In this public talk, we'll discuss how to build quantum computing devices one atom a time using the ion-trap approach. We'll show how we build quantum bits out of individually isolated atoms, explore how we use them to simulate other complex systems, and showcase how we're building open-access hardware to advance research in this exciting field.