output
19972026
most citedDirect electronic measurement of the spin Hall effect

1.5k citations

Showing 2022 · quant-phShow all

8 papers · 2 filters

quant-ph2022★ 8 cited

Operational Quantum Mereology and Minimal Scrambling

Paolo Zanardi, Emanuel Dallas, Faidon Andreadakis +1

In this paper we will attempt to answer the following question: what are the natural quantum subsystems which emerge out of a system's dynamical laws? To answer this question we fi…

quant-ph2022★ 31 cited

Efficient classical algorithms for simulating symmetric quantum systems

Eric R. Anschuetz, Andreas Bauer, Bobak T. Kiani +1

In light of recently proposed quantum algorithms that incorporate symmetries in the hope of quantum advantage, we show that with symmetries that are restrictive enough, classical a…

quant-ph2022★ 8 cited

SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture

Han Zheng, Christopher Kang, Gokul Subramanian Ravi +4

We propose SnCQA, a set of hardware-efficient variational circuits of equivariant quantum convolutional circuits respective to permutation symmetries and spatial lattice symmetries…

quant-ph2022★ 3 cited

Physical Computing: A Category Theoretic Perspective on Physical Computation and System Compositionality

Nima Dehghani, Gianluca Caterina

This paper introduces a category theory-based framework to redefine physical computing in light of advancements in quantum computing and non-standard computing systems. By integrat…

quant-ph2022★ 21 cited

Geometric Event-Based Relativistic Quantum Mechanics

Vittorio Giovannetti, Seth Lloyd, Lorenzo Maccone

We propose a special relativistic framework for quantum mechanics. It is based on introducing a Hilbert space for events. Events are taken as primitive notions (as customary in rel…

quant-ph2022★ 233 cited

Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps

Eric R. Anschuetz, Bobak T. Kiani

One of the most important properties of classical neural networks is how surprisingly trainable they are, though their training algorithms typically rely on optimizing complicated,…