218 research outputs found
Limits on Fundamental Limits to Computation
An indispensable part of our lives, computing has also become essential to
industries and governments. Steady improvements in computer hardware have been
supported by periodic doubling of transistor densities in integrated circuits
over the last fifty years. Such Moore scaling now requires increasingly heroic
efforts, stimulating research in alternative hardware and stirring controversy.
To help evaluate emerging technologies and enrich our understanding of
integrated-circuit scaling, we review fundamental limits to computation: in
manufacturing, energy, physical space, design and verification effort, and
algorithms. To outline what is achievable in principle and in practice, we
recall how some limits were circumvented, compare loose and tight limits. We
also point out that engineering difficulties encountered by emerging
technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl
Optimized Surface Code Communication in Superconducting Quantum Computers
Quantum computing (QC) is at the cusp of a revolution. Machines with 100
quantum bits (qubits) are anticipated to be operational by 2020
[googlemachine,gambetta2015building], and several-hundred-qubit machines are
around the corner. Machines of this scale have the capacity to demonstrate
quantum supremacy, the tipping point where QC is faster than the fastest
classical alternative for a particular problem. Because error correction
techniques will be central to QC and will be the most expensive component of
quantum computation, choosing the lowest-overhead error correction scheme is
critical to overall QC success. This paper evaluates two established quantum
error correction codes---planar and double-defect surface codes---using a set
of compilation, scheduling and network simulation tools. In considering
scalable methods for optimizing both codes, we do so in the context of a full
microarchitectural and compiler analysis. Contrary to previous predictions, we
find that the simpler planar codes are sometimes more favorable for
implementation on superconducting quantum computers, especially under
conditions of high communication congestion.Comment: 14 pages, 9 figures, The 50th Annual IEEE/ACM International Symposium
on Microarchitectur
Efficient Distributed Quantum Computing
We provide algorithms for efficiently addressing quantum memory in parallel.
These imply that the standard circuit model can be simulated with low overhead
by the more realistic model of a distributed quantum computer. As a result, the
circuit model can be used by algorithm designers without worrying whether the
underlying architecture supports the connectivity of the circuit. In addition,
we apply our results to existing memory intensive quantum algorithms. We
present a parallel quantum search algorithm and improve the time-space
trade-off for the Element Distinctness and Collision problems.Comment: Some material rearranged and references adde
Quantum machine learning: a classical perspective
Recently, increased computational power and data availability, as well as
algorithmic advances, have led machine learning techniques to impressive
results in regression, classification, data-generation and reinforcement
learning tasks. Despite these successes, the proximity to the physical limits
of chip fabrication alongside the increasing size of datasets are motivating a
growing number of researchers to explore the possibility of harnessing the
power of quantum computation to speed-up classical machine learning algorithms.
Here we review the literature in quantum machine learning and discuss
perspectives for a mixed readership of classical machine learning and quantum
computation experts. Particular emphasis will be placed on clarifying the
limitations of quantum algorithms, how they compare with their best classical
counterparts and why quantum resources are expected to provide advantages for
learning problems. Learning in the presence of noise and certain
computationally hard problems in machine learning are identified as promising
directions for the field. Practical questions, like how to upload classical
data into quantum form, will also be addressed.Comment: v3 33 pages; typos corrected and references adde
Where Quantum Complexity Helps Classical Complexity
Scientists have demonstrated that quantum computing has presented novel
approaches to address computational challenges, each varying in complexity.
Adapting problem-solving strategies is crucial to harness the full potential of
quantum computing. Nonetheless, there are defined boundaries to the
capabilities of quantum computing. This paper concentrates on aggregating prior
research efforts dedicated to solving intricate classical computational
problems through quantum computing. The objective is to systematically compile
an exhaustive inventory of these solutions and categorize a collection of
demanding problems that await further exploration
SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation
Compiling high-level quantum programs to machines that are size constrained
(i.e. limited number of quantum bits) and time constrained (i.e. limited number
of quantum operations) is challenging. In this paper, we present SQUARE
(Strategic QUantum Ancilla REuse), a compilation infrastructure that tackles
allocation and reclamation of scratch qubits (called ancilla) in modular
quantum programs. At its core, SQUARE strategically performs uncomputation to
create opportunities for qubit reuse.
Current Noisy Intermediate-Scale Quantum (NISQ) computers and forward-looking
Fault-Tolerant (FT) quantum computers have fundamentally different constraints
such as data locality, instruction parallelism, and communication overhead. Our
heuristic-based ancilla-reuse algorithm balances these considerations and fits
computations into resource-constrained NISQ or FT quantum machines, throttling
parallelism when necessary. To precisely capture the workload of a program, we
propose an improved metric, the "active quantum volume," and use this metric to
evaluate the effectiveness of our algorithm. Our results show that SQUARE
improves the average success rate of NISQ applications by 1.47X. Surprisingly,
the additional gates for uncomputation create ancilla with better locality, and
result in substantially fewer swap gates and less gate noise overall. SQUARE
also achieves an average reduction of 1.5X (and up to 9.6X) in active quantum
volume for FT machines.Comment: 14 pages, 10 figure
Towards Practical Hybrid Quantum / Classical Computing
Quantum computing is in a critical phase where theoretical schemes and protocols are now being implemented in the real world for the first time. Experimental implementations can help us solidify ideas, and can also complicate them. In the case of quantum communication protocols, we present the first experimental implementations of two entanglement-based schemes using IBM’s superconducting transmon qubit based technology. We find that the schemes are experimentally feasible with current technology, and give an idea of how much room for improvement there is before quantum technology can meet the highest theoretical expectations. These communication schemes may be fundamental components of the future quantum internet. We also present an overview of the emerging field of quantum blockchain protocols that could form a part of the quantum / classical communication structures of the future. Interaction between classical and quantum technologies can impair purely quantum designs, but can also be harnessed to enhance hybrid quantum / classical approaches. Finally, we suggest a path towards the hybridization of arbitrary code execution and verification in the hybrid quantum / classical networks of the future
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