Establishing the quantum supremacy frontier with a 281 Pflop/s simulation

Villalonga, Benjamin; Lyakh, Dmitry I.; Boixo, Sergio; Neven, Hartmut; Humble, Travis S.; Biswas, Rupak; Rieffel, Eleanor; Ho, Alan; Mandrà, Salvatore

doi:10.1088/2058-9565/ab7eeb

Cited by 142 publications

(120 citation statements)

References 63 publications

Supporting

Mentioning

113

Contrasting

Order By: Relevance

“…Therefore, this approach is impractical to simulate large quantum circuits. Several studies have proposed to use tensor network simulation technique to simulate low-depth supremacy circuits [10,15,53,63]. To trade the simulation fidelity for computational resources, the approximate simulation is proposed [10,48].…”

Section: Quantum Circuit Simulationmentioning

confidence: 99%

“…To trade the simulation fidelity for computational resources, the approximate simulation is proposed [10,48]. The previous studies of approximate simulations target the overall circuit fidelity at 0.005 [48,63], but if we want to use the simulation results to help calibrate and validate the real machines, we might need higher circuit fidelity. As for quantum software development, several types of quantum applications require intermediate measurement [4,5,12,29].…”

Section: Quantum Circuit Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Full-state quantum circuit simulation by using data compression

Dasgupta

et al. 2019

Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

View full text Add to dashboard Cite

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∼16 qubits for general quantum circuits.

show abstract

Section: Quantum Circuit Simulationmentioning

confidence: 99%

Section: Quantum Circuit Simulationmentioning

confidence: 99%

Full-state quantum circuit simulation by using data compression

Dasgupta

et al. 2019

Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

View full text Add to dashboard Cite

show abstract

“…To pursue efficiency, parts of the data is duplicated on several computing nodes to reduce the cost of data communication, leading to a larger memory usage than theoretical prediction 16 TB. Here we note that recently in [25] the authors compute, with 0.5% fidelity, 10 6 amplitudes for a 7 × 7 (1+40+1) random quantum circuit with single-precision numbers on Summit in 2.4 hours, using 2.67 PB memory and R Node-peak = 200.8 PFlops. Their optimized implementation, when mapped to unit fidelity, is currently faster than our proof-of-principle calculation.…”

mentioning

confidence: 96%

“…A). RQCs have also stimulated 2 the search for efficient classical algorithms which would show where exactly the limits of classical simulations are [17][18][19][20][21][22][23][24][25].…”

mentioning

confidence: 99%

“…Currently our results have 100% fidelity with the exact wave function, however we could also investigate the trade-off between fidelity and speed, so as to be able to sample many trajectories. For instance, we could reduce the memory requirement of our method by using the 'cut' technique in [25], namely mapping a large tensor contraction into summations over many smaller tensor contractions by unraveling several for-loops. This investigation is left for future works, together with the plan to include the effects of noise or errors in order to characterize more closely the actual behavior of a noisy intermediate-scale quantum computer.…”

mentioning

confidence: 99%

See 1 more Smart Citation

General-Purpose Quantum Circuit Simulator with Projected Entangled-Pair States and the Quantum Supremacy Frontier

et al. 2019

View full text Add to dashboard Cite

Recent advances on quantum computing hardware have pushed quantum computing to the verge of quantum supremacy. Here we bring together many-body quantum physics and quantum computing by using a method for strongly interacting two-dimensional systems, the Projected Entangled-Pair States, to realize an effective general-purpose simulator of quantum algorithms. We apply our method to study random quantum circuits, which are outstanding candidates to demonstrate quantum supremacy on quantum computers that supports nearest-neighbour gate operations on a two-dimensional configuration. Our approach allows to quantify precisely the memory usage and the time requirements of random quantum circuits, thus showing the frontier of quantum supremacy. Applying this general quantum circuit simulator we measured amplitudes for a 7 × 7 lattice of qubits with depth (1 + 40 + 1) and double-precision numbers in 31 minutes using less than 93 TB memory on the Tianhe-2 supercomputer. Our analytic complexity bounds also show that simulating a 8 × l circuit (l > 8) with depth (1 + 40 + 1), or a 10 × l (l > 10) circuit with depth (1 + 32 + 1) is within reach of current supercomputers.Quantum computers offer the promise of efficiently solving certain problems that are intractable for classical computers, most famously factorizing large numbers [1][2][3]. With the rapid progress of various quantum systems towards Noisy Intermediate-Scale Quantum computing devices [4][5][6][7][8][9][10][11], we are now on the verge of quantum supremacy [12], i.e. demonstrating that an actual quantum computer has the ability to do a computation that no classical computers can tackle, an important milestone in the field of computer science. Various candidates have been suggested to demonstrate quantum supremacy, such as BosonSampling [13,14], the instantaneous quantum polynomial protocol [15,16] and random quantum circuits (RQCs) [3,17] which demand less physical resources and are easier to implement compared to, for instance, factorization. The central aspect for all these near-term supremacy proof-of-principle computations, which poses fundamental limitations to classical computations, is that the quantum states produced, and from which we wish to sample configurations, live in a Hilbert space that grows exponentially with the system size.In view of recent progresses in quantum computing hardware, it is important to find effective ways to simulate accurately quantum algorithms on classical computers. While the quantum circuit simulator we present can tackle generic circuits, in the following we focus on RQCs. They consist of a series of single and two-qubit gates which are applied to different qubits in a particular order. A group of commuting gates which can be applied simultaneously constitute one layer of the circuit, and the more groups of operations that do not commute, the deeper the circuit is. The qualification of random circuit comes from the fact that the single-qubit gates applied are chosen at random from a small set of them (for more details about...

show abstract

An Exact and Practical Classical Strategy for 2D Graph State Sampling

et al. 2023

View full text Add to dashboard Cite

Constant-depth quantum circuits that prepare and measure graph states on 2D grids are proved to possess a computational quantum advantage over their classical counterparts due to quantum nonlocality and are also well suited for demonstrations on current superconducting quantum processor architectures. To simulate the partial or full sampling of 2D graph states, a practical two-stage classical strategy that can exactly generate any number of samples (bit strings) from such circuits is proposed. The strategy is inspired by exploiting specific properties of a hidden linear function problem solved by the target quantum circuit, which in particular combines traditional classical parallel algorithms and an explicit gate-based constant-depth classical circuit together. A theoretical analysis reveals that on average each sample can be obtained in nearly constant time for sampling specific circuit instances of large size. Moreover, the feasibility of the theoretical model is demonstrated by implementing typical instances up to 25 qubits on a moderate field programmable gate array platform. Therefore, the strategy can be used as a practical tool for verifying experimental results obtained from shallow quantum circuits of this type.

show abstract

Establishing the quantum supremacy frontier with a 281 Pflop/s simulation

Cited by 142 publications

References 63 publications

Full-state quantum circuit simulation by using data compression

Full-state quantum circuit simulation by using data compression

General-Purpose Quantum Circuit Simulator with Projected Entangled-Pair States and the Quantum Supremacy Frontier

An Exact and Practical Classical Strategy for 2D Graph State Sampling

Contact Info

Product

Resources

About