Spoofing Linear Cross-Entropy Benchmarking in Shallow Quantum Circuits

• URL: http://arxiv.org/abs/2005.02421v1
• Date: Tue, 5 May 2020 18:01:48 GMT
• Title: Spoofing Linear Cross-Entropy Benchmarking in Shallow Quantum Circuits
• Authors: Boaz Barak, Chi-Ning Chou, Xun Gao
• Abstract summary: Google's noisy quantum simulation of a 53 qubit circuit $C$ achieved a fidelity value of $(2.24pm0.21)times10-3$. Our results can be considered as an evidence that fooling the linear XEB test might be easier than achieving a full simulation of quantum circuit.
• Score: 8.401078947103475
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The linear cross-entropy benchmark (Linear XEB) has been used as a test for procedures simulating quantum circuits. Given a quantum circuit $C$ with $n$ inputs and outputs and purported simulator whose output is distributed according to a distribution $p$ over $\{0,1\}^n$, the linear XEB fidelity of the simulator is $\mathcal{F}_{C}(p) = 2^n \mathbb{E}_{x \sim p} q_C(x) -1$ where $q_C(x)$ is the probability that $x$ is output from the distribution $C|0^n\rangle$. A trivial simulator (e.g., the uniform distribution) satisfies $\mathcal{F}_C(p)=0$, while Google's noisy quantum simulation of a 53 qubit circuit $C$ achieved a fidelity value of $(2.24\pm0.21)\times10^{-3}$ (Arute et. al., Nature'19). In this work we give a classical randomized algorithm that for a given circuit $C$ of depth $d$ with Haar random 2-qubit gates achieves in expectation a fidelity value of $\Omega(\tfrac{n}{L} \cdot 15^{-d})$ in running time $\textsf{poly}(n,2^L)$. Here $L$ is the size of the \emph{light cone} of $C$: the maximum number of input bits that each output bit depends on. In particular, we obtain a polynomial-time algorithm that achieves large fidelity of $\omega(1)$ for depth $O(\sqrt{\log n})$ two-dimensional circuits. To our knowledge, this is the first such result for two dimensional circuits of super-constant depth. Our results can be considered as an evidence that fooling the linear XEB test might be easier than achieving a full simulation of the quantum circuit.

Related papers

• Classical simulation of peaked shallow quantum circuits [2.6089354079273512]
  We describe an algorithm with quasipolynomial runtime $nO(logn)$ that samples from the output distribution of a peaked constant-depth circuit. Our algorithms can be used to estimate output probabilities of shallow circuits to within a given inverse-polynomial additive error.
  arXiv  Detail & Related papers  (2023-09-15T14:01:13Z)
• On the average-case complexity of learning output distributions of quantum circuits [55.37943886895049]
  We show that learning the output distributions of brickwork random quantum circuits is average-case hard in the statistical query model. This learning model is widely used as an abstract computational model for most generic learning algorithms.
  arXiv  Detail & Related papers  (2023-05-09T20:53:27Z)
• Mind the gap: Achieving a super-Grover quantum speedup by jumping to the end [114.3957763744719]
  We present a quantum algorithm that has rigorous runtime guarantees for several families of binary optimization problems. We show that the algorithm finds the optimal solution in time $O*(2(0.5-c)n)$ for an $n$-independent constant $c$. We also show that for a large fraction of random instances from the $k$-spin model and for any fully satisfiable or slightly frustrated $k$-CSP formula, statement (a) is the case.
  arXiv  Detail & Related papers  (2022-12-03T02:45:23Z)
• Near-optimal fitting of ellipsoids to random points [68.12685213894112]
  A basic problem of fitting an ellipsoid to random points has connections to low-rank matrix decompositions, independent component analysis, and principal component analysis. We resolve this conjecture up to logarithmic factors by constructing a fitting ellipsoid for some $n = Omega(, d2/mathrmpolylog(d),)$. Our proof demonstrates feasibility of the least squares construction of Saunderson et al. using a convenient decomposition of a certain non-standard random matrix.
  arXiv  Detail & Related papers  (2022-08-19T18:00:34Z)
• How to simulate quantum measurement without computing marginals [3.222802562733787]
  We describe and analyze algorithms for classically computation measurement of an $n$-qubit quantum state $psi$ in the standard basis. Our algorithms reduce the sampling task to computing poly(n)$ amplitudes of $n$-qubit states.
  arXiv  Detail & Related papers  (2021-12-15T21:44:05Z)
• Random quantum circuits transform local noise into global white noise [118.18170052022323]
  We study the distribution over measurement outcomes of noisy random quantum circuits in the low-fidelity regime. For local noise that is sufficiently weak and unital, correlations (measured by the linear cross-entropy benchmark) between the output distribution $p_textnoisy$ of a generic noisy circuit instance shrink exponentially. If the noise is incoherent, the output distribution approaches the uniform distribution $p_textunif$ at precisely the same rate.
  arXiv  Detail & Related papers  (2021-11-29T19:26:28Z)
• Random matrices in service of ML footprint: ternary random features with no performance loss [55.30329197651178]
  We show that the eigenspectrum of $bf K$ is independent of the distribution of the i.i.d. entries of $bf w$. We propose a novel random technique, called Ternary Random Feature (TRF) The computation of the proposed random features requires no multiplication and a factor of $b$ less bits for storage compared to classical random features.
  arXiv  Detail & Related papers  (2021-10-05T09:33:49Z)
• Improved Weak Simulation of Universal Quantum Circuits by Correlated $L_1$ Sampling [0.0]
  Weak simulation is often called weak simulation and is a way to determine when they confer a quantum advantage. We constructively tighten the upper bound on the worst-case $L_$ norm sampling cost to next order in $t$ from $mathcal O(xit delta-2)$. This is the first weak simulation algorithm that has lowered this bound's dependence on finite $t$ in the worst-case to our knowledge.
  arXiv  Detail & Related papers  (2021-04-15T05:50:11Z)
• Quantum-classical algorithms for skewed linear systems with optimized Hadamard test [10.386115383285288]
  We discuss hybrid quantum-classical algorithms for skewed linear systems for over-determined and under-determined cases. Our input model is such that the columns or rows of the matrix defining the linear system are given via quantum circuits of poly-logarithmic depth. We present an algorithm for the special case of a factorized linear system with run time poly-logarithmic in the respective dimensions.
  arXiv  Detail & Related papers  (2020-09-28T12:59:27Z)
• The Quantum Supremacy Tsirelson Inequality [0.22843885788439797]
  For a quantum circuit $C$ on $n$ qubits and a sample $z in 0,1n$, the benchmark involves computing $|langle z|C|0n rangle|2$. We show that for any $varepsilon ge frac1mathrmpoly(n)$, outputting a sample $z$ is the optimal 1-query for $|langle z|C|0nrangle|2$ on average.
  arXiv  Detail & Related papers  (2020-08-20T01:04:32Z)
• Quantum Algorithms for Simulating the Lattice Schwinger Model [63.18141027763459]
  We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings. In lattice units, we find a Schwinger model on $N/2$ physical sites with coupling constant $x-1/2$ and electric field cutoff $x-1/2Lambda$. We estimate observables which we cost in both the NISQ and fault-tolerant settings by assuming a simple target observable---the mean pair density.
  arXiv  Detail & Related papers  (2020-02-25T19:18:36Z)

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.