Recycling qubits in near-term quantum computers

• URL: http://arxiv.org/abs/2012.01676v2
• Date: Sat, 26 Dec 2020 08:27:12 GMT
• Title: Recycling qubits in near-term quantum computers
• Authors: Galit Anikeeva, Isaac H. Kim, Patrick Hayden
• Abstract summary: We propose a protocol that can unitarily reset qubits when the circuit has a common convolutional form. This protocol generates fresh qubits from used ones by partially applying the time-reversed quantum circuit over qubits that are no longer in use.
• Score: 1.2891210250935146
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum computers are capable of efficiently contracting unitary tensor networks, a task that is likely to remain difficult for classical computers. For instance, networks based on matrix product states or the multi-scale entanglement renormalization ansatz (MERA) can be contracted on a small quantum computer to aid the simulation of a large quantum system. However, without the ability to selectively reset qubits, the associated spatial cost can be exorbitant. In this paper, we propose a protocol that can unitarily reset qubits when the circuit has a common convolutional form, thus dramatically reducing the spatial cost for implementing the contraction algorithm on general near-term quantum computers. This protocol generates fresh qubits from used ones by partially applying the time-reversed quantum circuit over qubits that are no longer in use. In the absence of noise, we prove that the state of a subset of these qubits becomes $|0\ldots 0\rangle$, up to an error exponentially small in the number of gates applied. We also provide a numerical evidence that the protocol works in the presence of noise. We also provide a numerical evidence that the protocol works in the presence of noise, and formulate a condition under which the noise-resilience follows rigorously.

Related papers

• Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
  We develop a reinforcement learning-based quantum compiler for a superconducting processor. We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths. Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
  arXiv  Detail & Related papers  (2024-06-18T01:49:48Z)
• Scaling quantum computing with dynamic circuits [0.6990493129893112]
  Quantum computers process information with the laws of quantum mechanics. Current quantum hardware is noisy, can only store information for a short time, and is limited to a few quantum bits, i.e., qubits. Here we overcome these limitations with error mitigated dynamic circuits and circuit-cutting to create quantum states requiring a periodic connectivity employing up to 142 qubits.
  arXiv  Detail & Related papers  (2024-02-27T19:00:07Z)
• A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity [50.387179833629254]
  We introduce a collaborative classical-quantum architecture called co-TenQu. Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting. It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
  arXiv  Detail & Related papers  (2024-02-23T14:09:41Z)
• QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits [82.50620782471485]
  QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits. It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness. Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
  arXiv  Detail & Related papers  (2024-01-10T22:33:00Z)
• Sequential quantum simulation of spin chains with a single circuit QED device [5.841833052422423]
  Quantum simulation of many-body systems in materials science and chemistry are promising application areas for quantum computers. We show how a single-circuit quantum electrodynamics device can be used to simulate the ground state of a highly-entangled quantum many-body spin chain. We demonstrate that the large state space of the cavity can be used to replace multiple qubits in a qubit-only architecture, and could therefore simplify the design of quantum processors for materials simulation.
  arXiv  Detail & Related papers  (2023-08-30T18:00:03Z)
• Circuit Cutting with Non-Maximally Entangled States [59.11160990637615]
  Distributed quantum computing combines the computational power of multiple devices to overcome the limitations of individual devices. circuit cutting techniques enable the distribution of quantum computations through classical communication. Quantum teleportation allows the distribution of quantum computations without an exponential increase in shots. We propose a novel circuit cutting technique that leverages non-maximally entangled qubit pairs.
  arXiv  Detail & Related papers  (2023-06-21T08:03:34Z)
• Iterative Qubits Management for Quantum Index Searching in a Hybrid System [56.39703478198019]
  IQuCS aims at index searching and counting in a quantum-classical hybrid system. We implement IQuCS with Qiskit and conduct intensive experiments. Results demonstrate that it reduces qubits consumption by up to 66.2%.
  arXiv  Detail & Related papers  (2022-09-22T21:54:28Z)
• Data compression for quantum machine learning [2.119778346188635]
  We address the problem of efficiently compressing and loading classical data for use on a quantum computer. Our proposed methods allow both the required number of qubits and depth of the quantum circuit to be tuned.
  arXiv  Detail & Related papers  (2022-04-24T03:03:14Z)
• Error rate reduction of single-qubit gates via noise-aware decomposition into native gates [0.0]
  knowledge of a qubit's initial quantum state and the standard parameters describing its decoherence can be leveraged to mitigate the noise present during the execution of a single-qubit gate. We demonstrate a reduction of the single-qubit error rate by $38%$, from $1.6 times 10 -3$ to $1.0 times 10 -3$, provided the initial state of the input qubit is known.
  arXiv  Detail & Related papers  (2021-04-14T18:00:01Z)
• Fault-tolerant Coding for Quantum Communication [71.206200318454]
  encode and decode circuits to reliably send messages over many uses of a noisy channel. For every quantum channel $T$ and every $eps>0$ there exists a threshold $p(epsilon,T)$ for the gate error probability below which rates larger than $C-epsilon$ are fault-tolerantly achievable. Our results are relevant in communication over large distances, and also on-chip, where distant parts of a quantum computer might need to communicate under higher levels of noise.
  arXiv  Detail & Related papers  (2020-09-15T15:10:50Z)
• Machine learning of noise-resilient quantum circuits [0.8258451067861933]
  Noise mitigation and reduction will be crucial for obtaining useful answers from near-term quantum computers. We present a general framework based on machine learning for reducing the impact of quantum hardware noise on quantum circuits. Our method, called noise-aware circuit learning (NACL), applies to circuits designed to compute a unitary transformation, prepare a set of quantum states, or estimate an observable of a many-qubit state.
  arXiv  Detail & Related papers  (2020-07-02T15:43:32Z)

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.