On the complexity of sampling from shallow Brownian circuits
- URL: http://arxiv.org/abs/2411.04169v1
- Date: Wed, 06 Nov 2024 19:00:00 GMT
- Title: On the complexity of sampling from shallow Brownian circuits
- Authors: Gregory Bentsen, Bill Fefferman, Soumik Ghosh, Michael J. Gullans, Yinchen Liu,
- Abstract summary: We study a constant-time Brownian circuit model which shares many similarities with constant-depth random quantum circuits.
We show that the output distributions of Brownian circuits at shallow depths follow a Porter-Thomas distribution, just like in the case of deep circuits.
We discover that for these circuits, while the quantum computer typically scores within a constant factor of the expected value, the classical spoofer suffers from an exponentially larger variance.
- Score: 0.0
- License:
- Abstract: While many statistical properties of deep random quantum circuits can be deduced, often rigorously and other times heuristically, by an approximation to global Haar-random unitaries, the statistics of constant-depth random quantum circuits are generally less well-understood due to a lack of amenable tools and techniques. We circumvent this barrier by considering a related constant-time Brownian circuit model which shares many similarities with constant-depth random quantum circuits but crucially allows for direct calculations of higher order moments of its output distribution. Using mean-field (large-n) techniques, we fully characterize the output distributions of Brownian circuits at shallow depths and show that they follow a Porter-Thomas distribution, just like in the case of deep circuits, but with a truncated Hilbert space. The access to higher order moments allows for studying the expected and typical Linear Cross-entropy (XEB) benchmark scores achieved by an ideal quantum computer versus the state-of-the-art classical spoofers for shallow Brownian circuits. We discover that for these circuits, while the quantum computer typically scores within a constant factor of the expected value, the classical spoofer suffers from an exponentially larger variance. Numerical evidence suggests that the same phenomenon also occurs in constant-depth discrete random quantum circuits, like those defined over the all-to-all architecture. We conjecture that the same phenomenon is also true for random brickwork circuits in high enough spatial dimension.
Related papers
- More global randomness from less random local gates [0.26388783516590225]
We prove that one-dimensional structured random circuits with non-Haar random local gates can exhibit substantially more global randomness compared to Haar random circuits with the same underlying circuit architecture.
Our findings have applications in improving circuit depth bounds for randomized benchmarking and the generation of approximate unitary 2-designs from shallow random circuits.
arXiv Detail & Related papers (2024-10-31T16:51:52Z) - Quantum advantage from measurement-induced entanglement in random shallow circuits [0.18749305679160366]
We show that long-range measurement-induced entanglement (MIE) proliferates when the circuit depth is at least a constant critical value.
We introduce a two-dimensional, depth-2, "coarse-grained" circuit architecture, composed of random Clifford gates acting on O(log n) qubits.
arXiv Detail & Related papers (2024-07-30T21:39:23Z) - Characterizing randomness in parameterized quantum circuits through expressibility and average entanglement [39.58317527488534]
Quantum Circuits (PQCs) are still not fully understood outside the scope of their principal application.
We analyse the generation of random states in PQCs under restrictions on the qubits connectivities.
We place a connection between how steep is the increase on the uniformity of the distribution of the generated states and the generation of entanglement.
arXiv Detail & Related papers (2024-05-03T17:32:55Z) - On verifiable quantum advantage with peaked circuit sampling [9.551919087634522]
We show that getting $1/textpoly(n)$ peakedness from such circuits requires $tau_p = Omega(tau_r/n)0.19)$ with overwhelming probability.
We also give numerical evidence that nontrivial peakedness is possible in this model.
arXiv Detail & Related papers (2024-04-22T18:00:06Z) - Majorization-based benchmark of the complexity of quantum processors [105.54048699217668]
We numerically simulate and characterize the operation of various quantum processors.
We identify and assess quantum complexity by comparing the performance of each device against benchmark lines.
We find that the majorization-based benchmark holds as long as the circuits' output states have, on average, high purity.
arXiv Detail & Related papers (2023-04-10T23:01:10Z) - Gaussian initializations help deep variational quantum circuits escape
from the barren plateau [87.04438831673063]
Variational quantum circuits have been widely employed in quantum simulation and quantum machine learning in recent years.
However, quantum circuits with random structures have poor trainability due to the exponentially vanishing gradient with respect to the circuit depth and the qubit number.
This result leads to a general belief that deep quantum circuits will not be feasible for practical tasks.
arXiv Detail & Related papers (2022-03-17T15:06:40Z) - Learnability of the output distributions of local quantum circuits [53.17490581210575]
We investigate, within two different oracle models, the learnability of quantum circuit Born machines.
We first show a negative result, that the output distributions of super-logarithmic depth Clifford circuits are not sample-efficiently learnable.
We show that in a more powerful oracle model, namely when directly given access to samples, the output distributions of local Clifford circuits are computationally efficiently PAC learnable.
arXiv Detail & Related papers (2021-10-11T18:00:20Z) - Boundaries of quantum supremacy via random circuit sampling [69.16452769334367]
Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling.
We examine the constraints of the observed quantum runtime advantage in a larger number of qubits and gates.
arXiv Detail & Related papers (2020-05-05T20:11:53Z) - On estimating the entropy of shallow circuit outputs [49.1574468325115]
Estimating the entropy of probability distributions and quantum states is a fundamental task in information processing.
We show that entropy estimation for distributions or states produced by either log-depth circuits or constant-depth circuits with gates of bounded fan-in and unbounded fan-out is at least as hard as the Learning with Errors problem.
arXiv Detail & Related papers (2020-02-27T15:32:08Z) - Efficient classical simulation of random shallow 2D quantum circuits [104.50546079040298]
Random quantum circuits are commonly viewed as hard to simulate classically.
We show that approximate simulation of typical instances is almost as hard as exact simulation.
We also conjecture that sufficiently shallow random circuits are efficiently simulable more generally.
arXiv Detail & Related papers (2019-12-31T19:00:00Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.