Gaussian breeding for encoding a qubit in propagating light
- URL: http://arxiv.org/abs/2212.05436v1
- Date: Sun, 11 Dec 2022 07:41:23 GMT
- Title: Gaussian breeding for encoding a qubit in propagating light
- Authors: Kan Takase, Kosuke Fukui, Akito Kawasaki, Warit Asavanant, Mamoru
Endo, Jun-ichi Yoshikawa, Peter van Loock, Akira Furusawa
- Abstract summary: Practical quantum computing requires robust encoding of logical qubits in physical systems to protect fragile quantum information.
Here, we propose Gaussian breeding that encodes arbitrary Gottesman-Kitaev-Preskill qubits in propagating light.
Our simulations show that GKP qubits above a fault-tolerant threshold, including magic states'', can be generated with a high success probability and with a high fidelity exceeding 0.99.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Practical quantum computing requires robust encoding of logical qubits in
physical systems to protect fragile quantum information. Currently, the lack of
scalability limits the logical encoding in most physical systems, and thus the
high scalability of propagating light can be a game changer for realizing a
practical quantum computer. However, propagating light also has a drawback: the
difficulty of logical encoding due to weak nonlinearity. Here, we propose
Gaussian breeding that encodes arbitrary Gottesman-Kitaev-Preskill (GKP) qubits
in propagating light. The key idea is the efficient and iterable generation of
quantum superpositions by photon detectors, which is the most widely used
nonlinear element in quantum propagating light. This formulation makes it
possible to systematically create the desired qubits with minimal resources.
Our simulations show that GKP qubits above a fault-tolerant threshold,
including ``magic states'', can be generated with a high success probability
and with a high fidelity exceeding 0.99. This result fills an important missing
piece toward practical quantum computing.
Related papers
- Deterministic generation of concatenated graph codes from quantum emitters [0.0]
Concatenation of a fault-tolerant construction with a code able to efficiently correct loss is a promising approach to achieve this.
We propose schemes for generatingd graph codes using multi-photon emission from two quantum emitters or a single quantum emitter coupled to a memory.
We show that these schemes enable fault-tolerant fusion-based quantum regimes in practical computation with high photon loss and standard fusion gates.
arXiv Detail & Related papers (2024-06-24T14:44:23Z) - Compression of quantum shallow-circuit states [11.305910458469098]
Storing quantum information generated by shallow circuits is a fundamental question of both theoretical and practical importance.
We show that $N$ copies of an unknown $n$-qubit state can be compressed into a hybrid memory of $O(n log N)$ (qu)bits.
arXiv Detail & Related papers (2024-04-17T08:48:07Z) - Propagating Gottesman-Kitaev-Preskill states encoded in an optical
oscillator [0.3901201146779002]
A logical qubit called Gottesman-Kitaev-Preskill (GKP) qubit is efficient for mitigating errors in a quantum computer.
GKP qubits have been only demonstrated at mechanical and microwave frequency in a highly nonlinear physical system.
In this work, we realize a GKP state in propagating light at the telecommunication wavelength and demonstrate homodyne meausurements on the GKP states.
arXiv Detail & Related papers (2023-09-05T15:21:20Z) - Hybrid quantum transfer learning for crack image classification on NISQ
hardware [62.997667081978825]
We present an application of quantum transfer learning for detecting cracks in gray value images.
We compare the performance and training time of PennyLane's standard qubits with IBM's qasm_simulator and real backends.
arXiv Detail & Related papers (2023-07-31T14:45:29Z) - Deep Quantum Error Correction [73.54643419792453]
Quantum error correction codes (QECC) are a key component for realizing the potential of quantum computing.
In this work, we efficiently train novel emphend-to-end deep quantum error decoders.
The proposed method demonstrates the power of neural decoders for QECC by achieving state-of-the-art accuracy.
arXiv Detail & Related papers (2023-01-27T08:16:26Z) - Scalable quantum error correction code on a ring topology of qubits [0.0]
We propose a linear scalable code of the permutative stabilizers for small distances on the ring architecture.
We present the way to construct the quantum circuit of the code and provide numerical simulation that demonstrate the exponential logical error rate suppression.
arXiv Detail & Related papers (2022-11-06T12:22:23Z) - Quantum Error Correction with Quantum Autoencoders [0.0]
We show how quantum neural networks can be trained to learn optimal strategies for active detection and correction of errors.
We highlight that the denoising capabilities of quantum autoencoders are not limited to the protection of specific states but extend to the entire logical codespace.
arXiv Detail & Related papers (2022-02-01T16:55:14Z) - Error mitigation and quantum-assisted simulation in the error corrected
regime [77.34726150561087]
A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations.
We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
arXiv Detail & Related papers (2021-03-12T20:58:41Z) - The Hintons in your Neural Network: a Quantum Field Theory View of Deep
Learning [84.33745072274942]
We show how to represent linear and non-linear layers as unitary quantum gates, and interpret the fundamental excitations of the quantum model as particles.
On top of opening a new perspective and techniques for studying neural networks, the quantum formulation is well suited for optical quantum computing.
arXiv Detail & Related papers (2021-03-08T17:24:29Z) - Imaginary Time Propagation on a Quantum Chip [50.591267188664666]
Evolution in imaginary time is a prominent technique for finding the ground state of quantum many-body systems.
We propose an algorithm to implement imaginary time propagation on a quantum computer.
arXiv Detail & Related papers (2021-02-24T12:48:00Z) - Space-efficient binary optimization for variational computing [68.8204255655161]
We show that it is possible to greatly reduce the number of qubits needed for the Traveling Salesman Problem.
We also propose encoding schemes which smoothly interpolate between the qubit-efficient and the circuit depth-efficient models.
arXiv Detail & Related papers (2020-09-15T18:17:27Z)
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.