Papers

A. Goldschmidt, F. Chong·Apr 24, 2023

Model-based quantum optimal control promises to solve a wide range of critical quantum technology problems within a single, flexible framework. The catch is that highly-accurate models are needed if the optimized controls are to meet the exacting dem...

Mengdi Zhao, Yunkai Wang, Shanhui Fan +1 more·Apr 23, 2023

Photons, by nature, typically do not exhibit interactions with each other. Creating photon-photon interactions holds immense importance in both fundamental physics and quantum technologies. Currently, such interactions have only been achieved indirec...

G. Dauphinais, D. Kribs, M. Vasmer·Apr 22, 2023

We introduce a stabilizer formalism for the general quantum error correction framework called operator algebra quantum error correction (OAQEC), which generalizes Gottesman's formulation for traditional quantum error correcting codes (QEC) and Poulin...

Jiyoung Yun, Seung-Hyun Nam, Hyun-Young Park +3 more·Apr 21, 2023

In this work, we consider two-sender, one-receiver communication over a discrete memoryless multiple-access channel without feedback, where two senders may cooperate on channel coding by using preshared resources, such as shared randomness, quantum s...

H. Lagemann·Apr 21, 2023

In this thesis we study aspects of Hamiltonian models which can affect the time evolution of transmon systems. We model the time evolution of various systems as a unitary real-time process by numerically solving the time-dependent Schr\"odinger equat...

A. Morvan, B. Villalonga, X. Mi +180 more·Apr 21, 2023

Undesired coupling to the surrounding environment destroys long-range correlations in quantum processors and hinders coherent evolution in the nominally available computational space. This noise is an outstanding challenge when leveraging the computa...

Koustubh Phalak, Swaroop Ghosh·Apr 21, 2023

Quantum Machine Learning (QML) has recently emerged as a rapidly growing domain as an intersection of Quantum Computing (QC) and Machine Learning (ML) fields. Hybrid quantum-classical models have demonstrated exponential speedups in various machine l...

K. Zakharova·Apr 21, 2023

The search task is one of the most difficult when it comes to execution speed, and reducing the latter is important both when working with large data and with small samples, if they need to be processed frequently and in a limited time. Grover's algo...

K. Chern, K. Boothby, Jack Raymond +2 more·Apr 20, 2023

Quantum annealing has emerged as a powerful platform for simulating and optimizing classical and quantum Ising models. Quantum annealers, like other quantum and/or analog computing devices, are susceptible to non-idealities including crosstalk, devic...

Daniel Hothem, K. Young, Tommie A. Catanach +1 more·Apr 20, 2023

Accurately predicting a quantum computer's capability—which circuits it can run and how well it can run them—is a foundational goal of quantum characterization and benchmarking. As modern quantum computers become increasingly hard to simulate, we mus...

S. Ulyanov, V. Ulyanov·Apr 20, 2023

The difference between classical and quantum algorithms (QA) is following: problem solved by QA is coded in the structure of the quantum operators. Input to QA in this case is always the same. Output of QA says which problem coded. In some sense, giv...

Pradeep Niroula, C. White, Qingfeng Wang +5 more·Apr 20, 2023

Magic is a property of quantum states that enables universal fault-tolerant quantum computing using simple sets of gate operations. Understanding the mechanisms by which magic is created or destroyed is, therefore, a crucial step towards efficient an...

Sounak Kar, J. L. Boudec·Apr 20, 2023

The BB84 QKD protocol is based on the idea that the sender and the receiver can reconcile a certain fraction of the teleported qubits to detect eavesdropping or noise and decode the rest to use as a private key. Under the present hardware infrastruct...

Irtaza Khalid, C. Weidner, E. Jonckheere +2 more·Apr 19, 2023

We propose a model-based reinforcement learning (RL) approach for noisy time-dependent gate optimization with improved sample complexity over model-free RL. Sample complexity is the number of controller interactions with the physical system. Leveragi...

Salvatore Certo, Anh Pham, Nicolas Robles +1 more·Apr 19, 2023

A framework to learn a multi-modal distribution is proposed, denoted as the conditional quantum generative adversarial network (C-qGAN). The neural network structure is strictly within a quantum circuit and, as a consequence, is shown to represent a ...

Sebastian Horvat, Iulian D. Toader·Apr 18, 2023

This entry reviews Rudolf Carnap's philosophical views on the quantum mechanics of his time. It also offers some thoughts on how Carnap might have reacted to some recent developments in the foundations of quantum mechanics.

Mark-Oliver Wolf, Thomas Ewen, Ivica Turkalj·Apr 18, 2023

Classical Monte Carlo algorithms can theoretically be sped up on a quantum computer by employing amplitude estimation (AE). To realize this, an efficient implementation of state-dependent functions is crucial. We develop a straightforward approach ba...

Zhiding Liang, Jinglei Cheng, Zhixin Song +8 more·Apr 18, 2023

The advantages of quantum pulses over quantum gates have attracted increasing attention from researchers. Quantum pulses offer benefits such as flexibility, high fidelity, scalability, and real-time tuning. However, while there are established workfl...

Conrad J. Haupt, D. Egger·Apr 18, 2023

Quantum computers require high fidelity quantum gates. These gates are obtained by routine calibration tasks that eat into the availability of cloud-based devices. Restless circuit execution speeds-up characterization and calibration by foregoing qub...

A. Krasnok, P. Dhakal, A. Fedorov +3 more·Apr 18, 2023

Superconducting microwave cavities with ultra-high Q-factors are revolutionizing the field of quantum computing, offering long coherence times exceeding 1 ms, which is critical for realizing scalable multi-qubit quantum systems with low error rates. ...