15,527 research outputs found
Full-State Quantum Circuit Simulation by Using Data Compression
Quantum circuit simulations are critical for evaluating quantum algorithms
and machines. However, the number of state amplitudes required for full
simulation increases exponentially with the number of qubits. In this study, we
leverage data compression to reduce memory requirements, trading computation
time and fidelity for memory space. Specifically, we develop a hybrid solution
by combining the lossless compression and our tailored lossy compression method
with adaptive error bounds at each timestep of the simulation. Our approach
optimizes for compression speed and makes sure that errors due to lossy
compression are uncorrelated, an important property for comparing simulation
output with physical machines. Experiments show that our approach reduces the
memory requirement of simulating the 61-qubit Grover's search algorithm from 32
exabytes to 768 terabytes of memory on Argonne's Theta supercomputer using
4,096 nodes. The results suggest that our techniques can increase the
simulation size by 2 to 16 qubits for general quantum circuits.Comment: Published in SC2019. Please cite the SC versio
Gate-Level Simulation of Quantum Circuits
While thousands of experimental physicists and chemists are currently trying
to build scalable quantum computers, it appears that simulation of quantum
computation will be at least as critical as circuit simulation in classical
VLSI design. However, since the work of Richard Feynman in the early 1980s
little progress was made in practical quantum simulation. Most researchers
focused on polynomial-time simulation of restricted types of quantum circuits
that fall short of the full power of quantum computation. Simulating quantum
computing devices and useful quantum algorithms on classical hardware now
requires excessive computational resources, making many important simulation
tasks infeasible. In this work we propose a new technique for gate-level
simulation of quantum circuits which greatly reduces the difficulty and cost of
such simulations. The proposed technique is implemented in a simulation tool
called the Quantum Information Decision Diagram (QuIDD) and evaluated by
simulating Grover's quantum search algorithm. The back-end of our package,
QuIDD Pro, is based on Binary Decision Diagrams, well-known for their ability
to efficiently represent many seemingly intractable combinatorial structures.
This reliance on a well-established area of research allows us to take
advantage of existing software for BDD manipulation and achieve unparalleled
empirical results for quantum simulation
Investigation into intermodulation distortion in HEMTs using a quasi-2-D physical model
The need for both linear and efficient pseudomorphic high electron-mobility transistors (pHEMTs) for modern wireless handsets necessitates a thorough understanding of the origins of intermodulation distortion at the device level. For the first time, the dynamic large-signal internal physical behavior of a pHEMT is examined using a quasi-two-dimensional physical device model.
The model accounts fully for device-circuit interaction and is validated experimentally for a two-tone experiment around 5 GHz
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