Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userOptimal Usage of Quantum Random Access Memory in Quantum Machine Learning
192
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
By considering an unreliable oracle in a query-based model of quantum learning, we present a tradeoff relation between the oracles reliability and the reusability of quantum state of the input data. The tradeoff relation manifests as the fundamental upper bound on the reusability. This limitation on the reusability would increase the quantum access to the input data, i.e., the usage of quantum random access memory (qRAM), repeating the preparation of a superposition of `big input data on the query failure. However, it is found that, a learner can obtain a correct answer even from an unreliable oracle without any additional usage of qRAM---i.e., the complexity of qRAM query does not increase even with an unreliable oracle. This is enabled by repeatedly cycling the quantum state of the input data to the upper bound on the reusability.
rate research
Read More
Random access memory is an indispensable device for classical information technology. Analog to this, for quantum information technology, it is desirable to have a random access quantum memory with many memory cells and programmable access to each cell. We report an experiment that realizes a random access quantum memory of 105 qubits carried by 210 memory cells in a macroscopic atomic ensemble. We demonstrate storage of optical qubits into these memory cells and their read-out at programmable times by arbitrary orders with fidelities exceeding any classical bound. Experimental realization of a random access quantum memory with many memory cells and programmable control of its write-in and read-out makes an important step for its application in quantum communication, networking, and computation.
As in conventional computing, key attributes of quantum memories are high storage density and, crucially, random access, or the ability to read from or write to an arbitrarily chosen register. However, achieving such random access with quantum memories in a dense, hardware-efficient manner remains a challenge, for example requiring dedicated cavities per qubit or pulsed field gradients. Here we introduce a protocol using chirped pulses to encode qubits within an ensemble of quantum two-level systems, offering both random access and naturally supporting dynamical decoupling to enhance the memory lifetime. We demonstrate the protocol in the microwave regime using donor spins in silicon coupled to a superconducting cavity, storing up to four multi-photon microwave pulses in distinct memory modes and retrieving them on-demand up to 2~ms later. A further advantage is the natural suppression of superradiant echo emission, which we show is critical when approaching unit cooperativity. This approach offers the potential for microwave random access quantum memories with lifetimes exceeding seconds, while the chirped pulse phase encoding could also be applied in the optical regime to enhance quantum repeaters and networks.
In quantum computing architectures, one important factor is the trade-off between the need to couple qubits to each other and to an external drive and the need to isolate them well enough in order to protect the information for an extended period of time. In the case of superconducting circuits, one approach is to utilize fixed frequency qubits coupled to coplanar waveguide resonators such that the system can be kept in a configuration that is relatively insensitive to noise. Here, we propose a scalable voltage-tunable quantum memory (QuMem) design concept compatible with superconducting qubit platforms. Our design builds on the recent progress in fabrication of Josephson field effect transistors (JJ-FETs) which use InAs quantum wells. The JJ-FET is incorporated into a tunable coupler between a transmission line and a high-quality resonator in order to control the overall inductance of the coupler. A full isolation of the high-quality resonator can be achieved by turning off the JJ-FET. This could allow for long coherence times and protection of the quantum information inside the storage cavity. The proposed design would facilitate the implementation of random access memory for storage of quantum information in between computational gate operations.
Qubit connectivity is an important property of a quantum processor, with an ideal processor having random access -- the ability of arbitrary qubit pairs to interact directly. Here, we implement a random access superconducting quantum information processor, demonstrating universal operations on a nine-bit quantum memory, with a single transmon serving as the central processor. The quantum memory uses the eigenmodes of a linear array of coupled superconducting resonators. The memory bits are superpositions of vacuum and single-photon states, controlled by a single superconducting transmon coupled to the edge of the array. We selectively stimulate single-photon vacuum Rabi oscillations between the transmon and individual eigenmodes through parametric flux modulation of the transmon frequency, producing sidebands resonant with the modes. Utilizing these oscillations for state transfer, we perform a universal set of single- and two-qubit gates between arbitrary pairs of modes, using only the charge and flux bias of the transmon. Further, we prepare multimode entangled Bell and GHZ states of arbitrary modes. The fast and flexible control, achieved with efficient use of cryogenic resources and control electronics, in a scalable architecture compatible with state-of-the-art quantum memories is promising for quantum computation and simulation.
Loading data in a quantum device is required in several quantum computing applications. Without an efficient loading procedure, the cost to initialize the algorithms can dominate the overall computational cost. A circuit-based quantum random access memory named FF-QRAM can load M n-bit patterns with computational cost O(CMn) to load continuous data where C depends on the data distribution. In this work, we propose a strategy to load continuous data without post-selection with computational cost O(Mn). The proposed method is based on the probabilistic quantum memory, a strategy to load binary data in quantum devices, and the FF-QRAM using standard quantum gates, and is suitable for noisy intermediate-scale quantum computers.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
