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Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Quantum Programmable Reflections
E. Schoute, Dmitry Grinko, Yiğit Subaşı +1 more·Nov 6, 2024
Similar to a classical processor, which is an algorithm for reading a program and executing its instructions on input data, a universal programmable quantum processor is a fixed quantum channel that reads a quantum program $\lvert\psi_{U}\rangle$ tha...
Laplace transform based quantum eigenvalue transformation via linear combination of Hamiltonian simulation
Dong An, Andrew M. Childs, Lin Lin +1 more·Nov 6, 2024
Eigenvalue transformations, which include solving time-dependent differential equations as a special case, have a wide range of applications in scientific and engineering computation. While quantum algorithms for singular value transformations are we...
Structure-preserving quantum algorithms for linear and nonlinear Hamiltonian systems
Hsuan-Cheng Wu, Xiantao Li·Nov 6, 2024
Hamiltonian systems of ordinary and partial differential equations are fundamental mathematical models spanning virtually all physical scales. A critical property for the robustness and stability of computational methods in such systems is the underl...
Randomly Compiled Quantum Simulation with Exponentially Reduced Circuit Depths
J. D. Watson·Nov 6, 2024
The quantum stochastic drift protocol, also known as qDRIFT, has become a popular algorithm for implementing time-evolution of quantum systems using randomised compiling. In this work we develop qFLO, a higher order randomised algorithm for time-evol...
Increasing the hardness of posiform planting using random QUBOs for programmable quantum annealer benchmarking
Elijah Pelofske, Georg Hahn, H. Djidjev·Nov 6, 2024
Posiform planting is a method for constructing QUBO instances with a unique planted solution that can be tailored to arbitrary connectivity graphs. In this study we investigate making posiform planted QUBOs computationally harder by fusing many small...
Programming an Optical Lattice Interferometer
L. M. Seifert, V. Colussi, Michael A. Perlin +2 more·Nov 6, 2024
Programming a quantum device describes the usage of quantum logic gates, agnostic of hardware specifics, to perform a sequence of operations with (typically) a computing or sensing task in mind. Such programs have been executed on digital quantum com...
High-fidelity gates in a transmon using bath engineering for passive leakage reset
Ted Thorbeck, Alexander McDonald, O. Lanes +6 more·Nov 6, 2024
Leakage, the occupation of any state not used in the computation, is one of the of the most devastating errors in quantum error correction. Transmons, the most common superconducting qubits, are weakly anharmonic multilevel systems, and are thus pron...
Exploring the quantum capacity of a Gaussian random-displacement channel using Gottesman-Kitaev-Preskill codes and maximum-likelihood decoding
Mao Lin, Kyungjoo Noh·Nov 6, 2024
Determining the quantum capacity of a noisy quantum channel is an important problem in the field of quantum communication theory. In this work, we consider the Gaussian random displacement channel $N_{\sigma}$, a type of bosonic Gaussian channels rel...
Superadditivity in large $N$ field theories and performance of quantum tasks
S. Leutheusser, Hong Liu·Nov 6, 2024
Field theories exhibit dramatic changes in the structure of their operator algebras in the limit where the number of local degrees of freedom ($N$) becomes infinite. An important example of this is that the algebras associated to local subregions may...
Slow Mixing of Quantum Gibbs Samplers
David Gamarnik, B. Kiani, Alexander Zlokapa·Nov 6, 2024
Preparing thermal (Gibbs) states is a common task in physics and computer science. Recent algorithms mimic cooling via system-bath coupling, where the cost is determined by mixing time, akin to classical Metropolis-like algorithms. However, few metho...
Quantum Diffusion Models for Few-Shot Learning
Ruhan Wang, Ye Wang, Jing Liu +1 more·Nov 6, 2024
Modern quantum machine learning (QML) methods involve the variational optimization of parameterized quantum circuits on training datasets, followed by predictions on testing datasets. Most state-of-the-art QML algorithms currently lack practical adva...
Toward end-to-end quantum simulation for protein dynamics
Zhenning Liu, Xiantao Li, Chunhao Wang +1 more·Nov 6, 2024
Modeling and simulating the protein folding process overall remains a grand challenge in computational biology. We systematically investigate end-to-end quantum algorithms for simulating various protein dynamics with effects, such as mechanical force...
Low-depth quantum symmetrization
Zhenning Liu, Andrew M. Childs, Daniel Gottesman·Nov 6, 2024
Quantum symmetrization is the task of transforming a non-strictly increasing list of $n$ integers into an equal superposition of all permutations of the list (or more generally, performing this operation coherently on a superposition of such lists). ...
Optimizing Quantum Circuits, Fast and Slow
Amanda Xu, A. Molavi, Swamit S. Tannu +1 more·Nov 6, 2024
Optimizing quantum circuits is critical: the number of quantum operations needs to be minimized for a successful evaluation of a circuit on a quantum processor. In this paper we unify two disparate ideas for optimizing quantum circuits, rewrite rules...
Learning the Closest Product State
Ainesh Bakshi, John Bostanci, William Kretschmer +5 more·Nov 6, 2024
We study the problem of finding a product state with optimal fidelity to an unknown n-qubit quantum state ρ, given copies of ρ. This is a basic instance of a fundamental question in quantum learning: is it possible to efficiently learn a simple appro...
Self-consistent Quantum Linear Response with a Polarizable Embedding Environment.
Peter Reinholdt, E. Kjellgren, K. M. Ziems +3 more·Nov 6, 2024
Quantum computing presents a promising avenue for solving complex problems, particularly in quantum chemistry, where it could accelerate the computation of molecular properties and excited states. This work focuses on computing excitation energies wi...
Topological modes in monitored quantum dynamics
Haining Pan, Hassan Shapourian, Chao-Ming Jian·Nov 6, 2024
Dynamical quantum systems both driven by unitary evolutions and monitored through measurements have proved to be fertile ground for exploring new dynamical quantum matters. While the entanglement structure and symmetry properties of monitored systems...
Multimodal Structure-Aware Quantum Data Processing
Hala Hawashin, M. Sadrzadeh·Nov 6, 2024
While large language models (LLMs) have advanced the field of natural language processing (NLP), their"black box"nature obscures their decision-making processes. To address this, researchers developed structured approaches using higher order tensors....
Infinitely fast critical dynamics: Teleportation through temporal rare regions in monitored quantum circuits
Gal Shkolnik, Sarang Gopalakrishnan, David A. Huse +2 more·Nov 5, 2024
We consider measurement-induced phase transitions in monitored quantum circuits with a measurement rate that fluctuates in time, remaining spatially uniform at each time. The spatially correlated fluctuations in the measurement rate disrupt the volum...
Does connected wedge imply distillable entanglement?
Takato Mori, Beni Yoshida·Nov 5, 2024
The Ryu-Takayanagi formula predicts that two boundary subsystems $A$ and $C$ can exhibit large mutual information $I(A:C)$ even when they are spatially disconnected on the boundary and separated by a buffer subsystem $B$, as long as $A$ and $C$ have ...