91,275 research outputs found
Which graph states are useful for quantum information processing?
Graph states are an elegant and powerful quantum resource for measurement
based quantum computation (MBQC). They are also used for many quantum protocols
(error correction, secret sharing, etc.). The main focus of this paper is to
provide a structural characterisation of the graph states that can be used for
quantum information processing. The existence of a gflow (generalized flow) is
known to be a requirement for open graphs (graph, input set and output set) to
perform uniformly and strongly deterministic computations. We weaken the gflow
conditions to define two new more general kinds of MBQC: uniform
equiprobability and constant probability. These classes can be useful from a
cryptographic and information point of view because even though we cannot do a
deterministic computation in general we can preserve the information and
transfer it perfectly from the inputs to the outputs. We derive simple graph
characterisations for these classes and prove that the deterministic and
uniform equiprobability classes collapse when the cardinalities of inputs and
outputs are the same. We also prove the reversibility of gflow in that case.
The new graphical characterisations allow us to go from open graphs to graphs
in general and to consider this question: given a graph with no inputs or
outputs fixed, which vertices can be chosen as input and output for quantum
information processing? We present a characterisation of the sets of possible
inputs and ouputs for the equiprobability class, which is also valid for
deterministic computations with inputs and ouputs of the same cardinality.Comment: 13 pages, 2 figure
Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design
Artificial intelligence (AI) algorithms based on neural networks have been
designed for decades with the goal of maximising some measure of accuracy. This
has led to two undesired effects. First, model complexity has risen
exponentially when measured in terms of computation and memory requirements.
Second, state-of-the-art AI models are largely incapable of providing
trustworthy measures of their uncertainty, possibly `hallucinating' their
answers and discouraging their adoption for decision-making in sensitive
applications.
With the goal of realising efficient and trustworthy AI, in this paper we
highlight research directions at the intersection of hardware and software
design that integrate physical insights into computational substrates,
neuroscientific principles concerning efficient information processing,
information-theoretic results on optimal uncertainty quantification, and
communication-theoretic guidelines for distributed processing. Overall, the
paper advocates for novel design methodologies that target not only accuracy
but also uncertainty quantification, while leveraging emerging computing
hardware architectures that move beyond the traditional von Neumann digital
computing paradigm to embrace in-memory, neuromorphic, and quantum computing
technologies. An important overarching principle of the proposed approach is to
view the stochasticity inherent in the computational substrate and in the
communication channels between processors as a resource to be leveraged for the
purpose of representing and processing classical and quantum uncertainty
Measurement-based quantum computation beyond the one-way model
We introduce novel schemes for quantum computing based on local measurements
on entangled resource states. This work elaborates on the framework established
in [Phys. Rev. Lett. 98, 220503 (2007), quant-ph/0609149]. Our method makes use
of tools from many-body physics - matrix product states, finitely correlated
states or projected entangled pairs states - to show how measurements on
entangled states can be viewed as processing quantum information. This work
hence constitutes an instance where a quantum information problem - how to
realize quantum computation - was approached using tools from many-body theory
and not vice versa. We give a more detailed description of the setting, and
present a large number of new examples. We find novel computational schemes,
which differ from the original one-way computer for example in the way the
randomness of measurement outcomes is handled. Also, schemes are presented
where the logical qubits are no longer strictly localized on the resource
state. Notably, we find a great flexibility in the properties of the universal
resource states: They may for example exhibit non-vanishing long-range
correlation functions or be locally arbitrarily close to a pure state. We
discuss variants of Kitaev's toric code states as universal resources, and
contrast this with situations where they can be efficiently classically
simulated. This framework opens up a way of thinking of tailoring resource
states to specific physical systems, such as cold atoms in optical lattices or
linear optical systems.Comment: 21 pages, 7 figure
Interconnection Networks for Scalable Quantum Computers
We show that the problem of communication in a quantum computer reduces to
constructing reliable quantum channels by distributing high-fidelity EPR pairs.
We develop analytical models of the latency, bandwidth, error rate and resource
utilization of such channels, and show that 100s of qubits must be distributed
to accommodate a single data communication. Next, we show that a grid of
teleportation nodes forms a good substrate on which to distribute EPR pairs. We
also explore the control requirements for such a network. Finally, we propose a
specific routing architecture and simulate the communication patterns of the
Quantum Fourier Transform to demonstrate the impact of resource contention.Comment: To appear in International Symposium on Computer Architecture 2006
(ISCA 2006
Constructive simulation and topological design of protocols
We give a topological simulation for tensor networks that we call the
two-string model. In this approach we give a new way to design protocols, and
we discover a new multipartite quantum communication protocol. We introduce the
notion of topologically-compressed transformations. Our new protocol can
implement multiple, non-local compressed transformations among multi-parties
using one multipartite resource state.Comment: 16 page
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