A5078323341- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Quantum and electron transport phenomena
- Quantum many-body systems
- Quantum-Dot Cellular Automata
- Neural Networks and Reservoir Computing
- Cloud Computing and Resource Management
- Quantum Mechanics and Applications
- Advanced Memory and Neural Computing
- Parallel Computing and Optimization Techniques
- Antimicrobial agents and applications
- Marine Biology and Environmental Chemistry
- Advanced Electrical Measurement Techniques
- Ferroelectric and Negative Capacitance Devices
- Peroxisome Proliferator-Activated Receptors
- Advanced Condensed Matter Physics
- Atomic and Subatomic Physics Research
- Topological Materials and Phenomena
- NF-κB Signaling Pathways
- Cold Atom Physics and Bose-Einstein Condensates
- Near-Field Optical Microscopy
- Environmental Toxicology and Ecotoxicology
- Autophagy in Disease and Therapy
- Physics of Superconductivity and Magnetism
- Low-power high-performance VLSI design
Tarim University
2023-2024
Alibaba Group (China)
2021-2023
Northeast Agricultural University
2023
Delft University of Technology
2020
QuTech
2020
Max Planck Institute of Quantum Optics
2012-2018
RWTH Aachen University
2018
Technical University of Munich
2017
Max Planck Society
2013
Tsinghua University
2009-2010
Superconducting qubits provide a promising path toward building large-scale quantum computers. The simple and robust transmon qubit has been the leading platform, achieving multiple milestones. However, fault-tolerant computing calls for operations at error rates significantly lower than those exhibited in state of art. Consequently, alternative superconducting with better protection have attracted increasing interest. Among them, fluxonium is particularly candidate, featuring large...
A quantum instruction set is where hardware and software meet. We develop characterization compilation techniques for non-Clifford gates to accurately evaluate its designs. Applying these our fluxonium processor, we show that replacing the iSWAP gate by square root SQiSW leads a significant performance boost at almost no cost. More precisely, on measure fidelity of up 99.72% averaging 99.31%, realize Haar random two-qubit with an average 96.38%. This error reduction 41% former 50% latter...
Abstract We develop an algorithmic framework for contracting tensor networks and demonstrate its power by classically simulating quantum computation of sizes previously deemed out reach. Our main contribution, index slicing, is a method that efficiently parallelizes the contraction breaking it down into much smaller identically structured subtasks, which can then be executed in parallel without dependencies. benchmark our algorithm on class random circuits, achieving greater than 10 5 times...
We utilize machine learning models which are based on recurrent neural networks to optimize dynamical decoupling (DD) sequences. DD is a relatively simple technique for suppressing the errors in quantum memory certain noise models. In numerical simulations, we show that with minimum use of prior knowledge and starting from random sequences, able improve over time eventually output DD-sequences performance better than well known DD-families. Furthermore, our algorithm easy implement...
Machine learning has the potential to become an important tool in quantum error correction as it allows decoder adapt distribution of a chip. An additional motivation for using neural networks is fact that they can be evaluated by dedicated hardware which very fast and consumes little power. been previously applied decode surface code. However, these approaches are not scalable training redone every system size becomes increasingly difficult. In this work existence local decoders higher...
One significant advantage of superconducting processors is their extensive design flexibility, which encompasses various types qubits and interactions. Given the large number tunable parameters a processor, ability to perform gradient optimization would be highly beneficial. Efficient backpropagation for computation requires tightly integrated software library, no open-source implementation currently available. In this work, we introduce SuperGrad, simulator that accelerates quantum by...
We still do not have perfect decoders for topological codes that can satisfy all needs of different experimental setups. Recently, a few neural network based been studied, with the motivation they adapt to wide range noise models, and easily run on dedicated chips without full-fledged computer. The later feature might lead fast speed ability operate at low temperatures. However, question which has addressed in previous works is whether handle 2D large distances. In this work, we provide...
The study of quantum circuits composed commuting gates is particularly useful to understand the delicate boundary between and classical computation. Indeed, while being a restricted class, exhibit genuine effects such as entanglement. In this paper we show that computational power exhibits surprisingly rich structure. First every 2-local circuit acting on $d$-level systems followed by single-qudit measurements can be efficiently simulated classically with high accuracy. contrast, prove...
We propose a non-commutative extension of the Pauli stabilizer formalism. The aim is to describe class many-body quantum states which richer than standard states. In our framework, operators are tensor products single-qubit drawn from group 〈αI, X, S〉, where α = eiπ/4 and S diag(1, i). provide techniques efficiently compute various properties related bipartite entanglement, expectation values local observables, preparation by means circuits, parent Hamiltonians, etc. also highlight...
ABSTRACT Trimethyltin chloride (TMT) is a highly toxic organotin pollutant frequently found in aquatic environments, posing significant threat to the ecological system. The kidney plays vital role body's detoxification processes, and TMT present environment tends accumulate kidneys. However, it remained unclear whether exposure different doses of could induce pyroptosis immune dysfunction grass carp cells (CIK cells). For this purpose, after assessing half‐maximal inhibitory concentration...
The study of quantum circuits composed commuting gates is particularly useful to understand the delicate boundary between and classical computation. Indeed, while being a restricted class, exhibit genuine effects such as entanglement. In this paper we show that computational power exhibits surprisingly rich structure. First every 2-local circuit acting on d-level systems followed by single-qudit measurements can be efficiently simulated classically with high accuracy. contrast, prove strong...
We report, in a sequence of notes, our work on the Alibaba Cloud Quantum Development Platform (AC-QDP). AC-QDP provides set tools for aiding development both quantum computing algorithms and processors, is powered by large-scale classical simulator deployed Cloud. In this note, we simulate distance-3 logical qubit encoded 17-qubit surface code using experimental noise parameters transmon qubits planar circuit QED architecture. Our simulation features crosstalk induced ZZ-interactions. show...
One significant advantage of superconducting processors is their extensive design flexibility, which encompasses various types qubits and interactions. Given the large number tunable parameters a processor, ability to perform gradient optimization would be highly beneficial. Efficient backpropagation for computation requires tightly integrated software library, no open-source implementation currently available. In this work, we introduce SuperGrad, simulator that accelerates quantum by...
Abstract In a quantum processor, the device design and external controls together contribute to quality of target operations. As we continuously seek better alternative qubit platforms, explore increasingly large control space. Thus, optimization becomes more challenging. this work, demonstrate that figure merit reflecting goal can be made differentiable with respect parameters. addition, compute gradient objective efficiently in similar manner back-propagation algorithm then utilize...
We study the preparation of topologically ordered states by interpolating between an initial Hamiltonian with a unique product ground state and degenerate space. By simulating dynamics for small systems, we numerically observe certain stability prepared as function Hamiltonian. For systems or long interpolation times, argue that resulting can be identified computing suitable effective Hamiltonians. anyon models, this analysis singles out relevant physical processes extends splitting...
A quantum instruction set is where hardware and software meet. We develop new characterization compilation techniques for non-Clifford gates to accurately evaluate different designs. specifically apply them our fluxonium processor that supports mainstream $\mathrm{iSWAP}$ by calibrating characterizing its square root $\mathrm{SQiSW}$. measure a gate fidelity of up $99.72\%$ with an average $99.31\%$ realize Haar random two-qubit using $\mathrm{SQiSW}$ $96.38\%$. This error reduction $41\%$...
Scaling bottlenecks the making of digital quantum computers, posing challenges from both and classical components. We present a architecture to cope with comprehensive list latter {\em all at once}, implement it fully in an end-to-end system by integrating multi-core RISC-V CPU our in-house control electronics. Our enables scalable, high-precision large processors accommodates evolving requirements hardware. A central feature is microarchitecture executing operations parallel on arbitrary...
Scaling bottlenecks the making of digital quantum computers, posing challenges from both and classical components. We present a architecture to cope with comprehensive list latter all at once , implement it fully in an end-to-end system by integrating multi-core RISC-V CPU our in-house control electronics. Our enables scalable, high-precision large processors accommodates evolving requirements hardware. A central feature is microarchitecture executing operations parallel on arbitrary...
In the quest for fault-tolerant quantum computation using superconducting processors, accurate performance assessment and continuous design optimization stands at forefront. To facilitate both meticulous simulation streamlined optimization, we introduce a multi-level framework that spans Hamiltonian error correction levels, is equipped with capability to compute gradients efficiently. This toolset aids in tailored specific objectives like memory performance. Within our framework, investigate...
Using exponential quadratic operators, we present a general framework for studying the exact dynamics of system-bath interaction in which Hamiltonian is described by form bosonic operators. To demonstrate versatility approach, study how environment affects squeezing quadrature components system. We further propose that can be enhanced when parity kicks are applied to
We study the feasibility of implementing a quantum NOT gate (approximate) when state lies between two latitudes on Bloch's sphere and present an analytical formula for optimized 1-to-$M$ gate. Our result generalizes previous results concerning distributed uniformly whole Bloch as well phase covariant state. have also shown that such can be implemented using sequential generation scheme via matrix product states (MPS).