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Lindsay Bassman Oftelie

Publications and source records attributed to Lindsay Bassman Oftelie.

9 recordsLinked to original sources

Quantum error correction with global control

Reaching fault tolerance means scaling qubit counts by orders of magnitude, a jump that conventional superconducting architectures cannot sustain without solving the so-called `wiring problem'. Global control sidesteps this bottleneck, but implementing quantum error correction (QEC) on previously proposed global architectures incurs extremely steep overhead costs, due to the need for separate correction procedures for the computational and auxiliary qubits that comprise the global device. We resolve this by introducing the first globally-controlled architecture with zero qubit overhead. Every physical qubit is a computational qubit, and thus, every qubit is protected under a single error correcting scheme. We identify a class of cyclic stabilizer codes realizable through global iSWAP and single-qubit gates, yielding QEC thresholds nearly seven orders of magnitude larger than previous estimates for globally-controlled arrays. We further show these thresholds improve systematically as the global architecture is augmented with a limited amount of local measurement sites, demonstrating a trade-off between wiring simplicity and fault-tolerant performance.

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Impact of Information on Quantum Heat Engines

The emerging field of quantum thermodynamics is beginning to reveal the intriguing role that information can play in quantum thermal engines. Information enters as a resource when considering feedback-controlled thermal machines. While both a general theory of quantum feedback control as well as specific examples of quantum feedback-controlled engines have been presented, still lacking is a general framework for such machines. Here, we present a framework for a generic, two-stroke quantum heat engine interacting with $N$ thermal baths and Maxwell's demon. The demon performs projective measurements on the engine working substance, the outcome of which is recorded in a classical memory, embedded in its own thermal bath. To perform feedback control, the demon enacts unitary operations on the working substance, conditioned on the recorded outcome. By considering the compound machine-memory as a hybrid (classical-quantum) standard thermal machine interacting with $N+1$ thermal baths, our framework puts the working substance and memory on equal footing, thereby enabling a comprehensible resolution to Maxwell's paradox and elucidating the intricate manner in which information impacts the performance of quantum engines. We illustrate the application of our framework with a two-qubit engine. A remarkable observation is that more information does not necessarily result in better thermodynamic performance: sometimes knowing less is better.

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Roadmap on Quantum Thermodynamics

The last two decades has seen quantum thermodynamics become a well established field of research in its own right. In that time, it has demonstrated a remarkably broad applicability, ranging from providing foundational advances in the understanding of how thermodynamic principles apply at the nano-scale and in the presence of quantum coherence, to providing a guiding framework for the development of efficient quantum devices. Exquisite levels of control have allowed state-of-the-art experimental platforms to explore energetics and thermodynamics at the smallest scales which has in turn helped to drive theoretical advances. This Roadmap provides an overview of the recent developments across many of the field's sub-disciplines, assessing the key challenges and future prospects, providing a guide for its near term progress.

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Algebraic Compression of Free Fermionic Quantum Circuits: Particle Creation, Arbitrary Lattices and Controlled Evolution

Recently we developed a local and constructive algorithm based on Lie algebraic methods for compressing Trotterized evolution under Hamiltonians that can be mapped to free fermions. The compression algorithm yields a circuit which scales linearly in the number of qubits, has a depth independent of evolution time and compresses time-dependent Hamiltonians. The algorithm is limited to simple nearest-neighbor spin interactions and fermionic hopping. In this work, we extend our methods to compress evolution with long-range fermionic hopping, thereby enabling the embedding of arbitrary lattices onto a chain of qubits for fermion models. Moreover, we show that controlled time evolution, as well as fermion creation and annihilation operators can also be compressed. We demonstrate our results by adiabatically preparing the ground state for a half-filled fermionic chain, simulating a $4 \times 4$ tight binding model on ibmq washington, and calculating the topological Zak phase on a Quantinuum H1-1 trapped-ion quantum computer. With these new developments, our results enable the simulation of a wider range of models of interest and the efficient compression of subcircuits.

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Measurement of the work statistics of an open quantum system using a quantum computer

We report on the experimental measurement of the work statistics of a genuinely open quantum system using a quantum computer. Such measurement has remained elusive thus far due to the inherent difficulty in measuring the total energy change of a system-bath compound (which is the work) in the open quantum system scenario. We overcome this difficulty by extending the interferometric scheme, originally conceived for closed systems, to the open system case and implement it on a superconducting quantum computer, taking advantage of the relatively high levels of noise on current quantum hardware to realize an open quantum system. We demonstrate that the method can be used as a diagnostic tool to probe physical properties of the system-bath compound, such as its temperature and specific transitions frequencies in its spectrum. Our experiments corroborate that the interferometric scheme is a promising tool to achieve the long-sought experimental validation of the Jarzynski equality for arbitrary open quantum systems.

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QuL: Programming Library for Computational Cooling of Qubits

A key hurdle to the success of quantum computers is the ability to initialize qubits into a pure state, which can be achieved by cooling qubits down to very low temperatures. Computational cooling of qubits, whereby a subset of the qubits is cooled at the expense of heating the other qubits via the application of special sets of logic gates, offers a route to effectively cool qubits. Here, we present QuL, a programming library which can be used to generate, analyze, and test quantum circuits for various computational cooling protocols. In its most basic usage, QuL enables a novice user to easily produce cooling circuits with minimal input or knowledge required. The programming library, however, offers flexibility to more advanced users to finely tune the cooling protocol used to generate the quantum circuit. Finally, QuL offers methods to assess and compare various cooling protocols for users interested in studying optimal implementation of computational cooling in general, or on specific quantum backends. It is our hope that QuL will not only facilitate the execution of computational cooling on current quantum computers, but also serve as a tool to investigate open questions in the optimal implementation of computational cooling.

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Dynamic Cooling on Contemporary Quantum Computers

We study the problem of dynamic cooling whereby a target qubit is cooled at the expense of heating up $N-1$ further identical qubits, by means of a global unitary operation. A standard back-of-the-envelope high temperature estimate establishes that the target qubit temperature can only be dynamically cooled by at most a factor of $1/\sqrt{N}$. Here, we provide the exact expression for the minimum temperature to which the target qubit can be cooled and reveal that there is a crossover from the high initial temperature regime where the scaling is in fact $1/\sqrt{N}$ to a low initial temperature regime where a much faster scaling of $1/N$ occurs. This slow $1/\sqrt{N}$ scaling, which was relevant for early high-temperature NMR quantum computers, is the reason dynamic cooling was dismissed as ineffectual around 20 years ago; the fact that current low-temperature quantum computers fall in the fast $1/N$ scaling regime, reinstates the appeal of dynamic cooling today. We further show that the associated work cost of cooling is exponentially more advantageous in the low temperature regime. We discuss the implementation of dynamic cooling in terms of quantum circuits and examine the effects of hardware noise. We successfully demonstrate dynamic cooling in a 3-qubit system on a real quantum processor. Since the circuit size grows quickly with $N$, scaling dynamic cooling to larger systems on noisy devices poses a challenge. We therefore propose a suboptimal cooling algorithm, whereby relinquishing a small amount of cooling capability results in a drastically reduced circuit complexity, greatly facilitating the implementation of dynamic cooling on near-future quantum computers.

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Simulating dirty bosons on a quantum computer

The physics of dirty bosons highlights the intriguing interplay of disorder and interactions in quantum systems, playing a central role in describing, for instance, ultracold gases in a random potential, doped quantum magnets, and amorphous superconductors. Here, we demonstrate how quantum computers can be used to elucidate the physics of dirty bosons in one and two dimensions. Specifically, we explore the disorder-induced delocalized-to-localized transition using adiabatic state preparation. In one dimension, the quantum circuits can be compressed to small enough depths for execution on currently available quantum computers. In two dimensions, the compression scheme is no longer applicable, thereby requiring the use of large-scale classical state vector simulations to emulate quantum computer performance. In addition, simulating interacting bosons via emulation of a noisy quantum computer allowed us to study the effect of quantum hardware noise on the physical properties of the simulated system. Our results suggest that scaling laws control how noise modifies observables versus its strength, the circuit depth, and the number of qubits. Moreover, we observe that noise impacts the delocalized and localized phases differently. A better understanding of how noise alters the genuine properties of the simulated system is essential for leveraging noisy intermediate-scale quantum devices for simulation of dirty bosons, and indeed for condensed matter systems in general.

cond-mat.dis-nn↗

Exploring Finite Temperature Properties of Materials with Quantum Computers

Thermal properties of nanomaterials are crucial to not only improving our fundamental understanding of condensed matter systems, but also to developing novel materials for applications spanning research and industry. Since quantum effects arise at the nano-scale, these systems are difficult to simulate on classical computers. Quantum computers can efficiently simulate quantum many-body systems, yet current quantum algorithms for calculating thermal properties of these systems incur significant computational costs in that they either prepare the full thermal state on the quantum computer, or they must sample a number of pure states from a distribution that grows with system size. Canonical thermal pure quantum (TPQ) states provide a promising path to estimating thermal properties of quantum materials as they neither require preparation of the full thermal state nor require a growing number of samples with system size. Here, we present an algorithm for preparing canonical TPQ states on quantum computers. We compare three different circuit implementations for the algorithm and demonstrate their capabilities in estimating thermal properties of quantum materials. Due to its increasing accuracy with system size and flexibility in implementation, we anticipate that this method will enable finite temperature explorations of relevant quantum materials on near-term quantum computers.

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